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CAN CONCRETE BE GREEN IN BOSNIA AND HERZEGOVINA?
Sanin Džidić
International BURCH University Sarajevo
Faculty of Engineering and Information Technologies
Department of Architecture
Francuske revolucije bb, 71210 Ilidža, Sarajevo
e-mail: sanin.dzidic@ibu.edu.ba
SUMMARY
Bosnia and Herzegovina ratified the United Nations Framework Convention on Climate
Change (UNFCCC) on May 17, 2000. The Kyoto Protocol was signed and ratified by the
governments of 192 states and territories in the world. The Kyoto Protocol was ratified by
Bosnia and Herzegovina on April 22, 2007, after completion of ratification procedures of all
government levels. The First National Report of Bosnia and Herzegovina in accordance to the
UNFCCC was issued in 2009 and the Second National Report of Bosnia and Herzegovina in
accordance to the UNFCCC was adopted by B&H Council of Ministers in July 2013. The
main goal of the Kyoto Protocol is to reduce greenhouse gas emissions to environment what
caused many to focus on CO2 emissions as the most critical environment impact indicator.
Concrete is by far the most widely used construction material worldwide. One of its major
components is Portland cement as a binder. Total production of cement in Bosnia and
Herzegovina is about 850,000 tons in 2012, while fresh concrete production and concrete
products amount approximately to 1,300,000 tons in 2012. Taking in consideration that
production of every ton of cement yields to approximately 0.9 tons of CO2 and every cubic
meter of concrete contains about ten percent by weight of cement, significant quantity of CO2
is produced by cement industry in Bosnia and Herzegovina. It is estimation in 2001, that
cement industry emissions of CO2 represented around 4 percent of total CO2 emissions by
energy and industry in Bosnia and Herzegovina. However, substituting significant amounts of
cement in concrete mixture with industrial by-products such as silica fume, fly ash and blast
furnace slag also leads to minimization of cement consumption, even producing more durable
concrete. This paper discuss possibilities in decreasing CO2 emissions in cement and concrete
industry, as well as necessity of following directions of green and sustainable building in
Bosnia and Herzegovina.
Key Words: CO2 emission, cement, concrete, green buildings
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Introduction
The essence of the Kyoto Protocol invites nations to commit themselves in reducing
greenhouse gas (GHG) emissions. The Kyoto Protocol was adopted in Kyoto, Japan,
December 11, 1997, but enacted or enforced on February 16, 2005. The goal of this protocol
is to cope with the adverse effects of climate change, or global warming. The UNFCCC
(United Nations Framework Convention on Climate Change), states the goal of the Kyoto
Protocol is "stabilization of greenhouse gas concentrations in the atmosphere at a level that
would prevent dangerous anthropogenic interference with the climate system."
Many countries have agreed to legally bind limitations/reductions in their emissions of
greenhouse gases, as part of the Kyoto Protocol. These binding limitations/reductions are tight
in two commitments periods. The first commitment period is related to emissions between
2008-2012, and the second commitment period for emissions between 2013-2020.
The Kyoto Protocol considers emissions of six greenhouse gases:
carbon dioxide (CO2);
methane (CH4);
nitrous oxide (N2O);
hydrofluorocarbons (HFCs);
perfluorocarbons (PFCs);
sulphur hexafluoride (SF6).
There are 192 parties committed to the Kyoto Protocol. This includes 191 states (all the UN
members except Andorra, Canada, South Sudan and the United States) and the European
Union. The United States signed but did not ratify the Protocol. Canada withdrew from
Protocol in 2011.
Figure 1 – Kyoto Protocol Participation
The Kyoto Protocol was ratified by Bosnia and Herzegovina on April 22, 2007, after
completion of ratification procedures of all government levels. The First National Report of
Bosnia and Herzegovina in accordance to the UNFCCC was issued in 2009 and the Second
National Report of Bosnia and Herzegovina in accordance to the UNFCCC was adopted by
B&H Council of Ministers in July 2013.
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New Construction Paradigm
Construction industry is important part of the economy of each country. The old paradigm of
construction took in consideration costs, schedule and quality. This paradigm was often
presented as a triangle or a pyramid with cost supported by schedule and quality in each angle.
This was very well known to each construction or project manager. There was attention in
achieving the desired quality in a scheduled period of time for a minimal particular cost. New
principles of green and sustainable approach to all aspects of human life introduced
modifications of this paradigm in construction sector too. The Paradigm has changed and
become much more comprehensive.
Figure 2 – New Construction Paradigm
The new paradigm involves additional factors beyond above mentioned. The decision making
model in designing a project in order to achieve sustainability requires the balance of the old
factors, plus human health, safety and comfort as it relates to the environment. Instead of a
triangle or pyramid shape, depicting the decision model, the shape of the decision making
model for sustainability construction looks like much more comprehensive.
The new EU Construction Products Regulation (CPR 305/2011/EU), published by the
European Parliament on March 9, 2011, completely replaced the Construction Products
Directive (CPD 89/106/EEC) officially on July 1, 2013 and took in consideration this new
approach. In its definitions, CPR 305/2011/EU defines construction product as any product or
kit which is produced and placed on the market for incorporation in a permanent manner in
construction works or parts thereof and the performance of which has an effect on the
performance of the construction works with respect to the basic requirements for construction
works. “Kit” means a construction product placed on the market by a single manufacturer as
a set of at least two separate components that need to be put together to be incorporated in the
construction works. CPR 305/2011/EU defines term “construction works” buildings and civil
engineering works.
According to the CPR 305/2011/EU ANNEX I - Basic Requirements for Construction Works,
Construction works as a whole and in their separate parts must be fit for their intended use,
taking into account in particular the health and safety of persons involved throughout the life
cycle of the works. Subject to normal maintenance, construction works must satisfy these
basic requirements for construction works for an economically reasonable working life as
follows:
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1. Mechanical resistance and stability
The construction works must be designed and built in such a way that the loadings that are
liable to act on them during their constructions and use will not lead to any of the following:
collapse of the whole or part of the work;
major deformations to an inadmissible degree;
damage to other parts of the construction works or to fittings or installed equipment as
a result of major deformation of the load-bearing construction;
damage by an event to an extent disproportionate to the original cause.
2. Safety in case of fire
The construction works must be designed and built in such a way that in the event of an
outbreak of fire:
the load-bearing capacity of the construction can be assumed for a specific period of
time;
the generation and spread of fire and smoke within the construction works are limited;
the spread of fire to neighboring construction works is limited;
occupants can leave the construction works or be rescued by other means;
the safety of rescue teams is taken into consideration.
3. Hygiene, health and the environment
The construction works must be designed and built in such a way that they will, throughout
their life cycle, not be a threat to the hygiene or health and safety of workers, occupants or
neighbors, nor have an exceedingly high impact, over their entire life cycle, on the
environmental quality or on the climate during their construction, use and demolition, in
particular as a result of any of the following:
the giving-off of toxic gas;
the emissions of dangerous substances, volatile organic compounds (VOC),
greenhouse gases or dangerous particles into indoor or outdoor air;
the emission of dangerous radiation;
the release of dangerous substances into ground water, marine waters, surface waters
or soil;
the release of dangerous substances into drinking water or substances which have an
otherwise negative impact on drinking water;
faulty discharge of waste water, emission of flue gases or faulty disposal of solid or
liquid waste;
dampness in parts of the construction works or on surfaces within the construction
works.
4. Safety and accessibility in use
The construction works must be designed and built in such a way that they do not present
unacceptable risks of accidents or damage in service or in operation such as slipping, falling,
collision, burns, electrocution, injury from explosion and burglaries. In particular,
construction works must be designed and built taking into consideration accessibility and use
for disabled persons.
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5. Protection against noise
The construction works must be designed and built in such a way that noise perceived by the
occupants or people nearby is kept to a level that will not threaten their health and will allow
them to sleep, rest and work in satisfactory conditions.
6. Energy economy and heat retention
The construction works and their heating, cooling, lighting and ventilation installations must
be designed and built in such a way that the amount of energy they require in use shall be low,
when account is taken of the occupants and of the climatic conditions of the location.
Construction works must also be energy-efficient, using as little energy as possible during
their construction and dismantling.
7. Sustainable use of natural resources
The construction works must be designed, built and demolished in such a way that the use of
natural resources is sustainable and in particular ensure the following:
reuse or recyclability of the construction works, their materials and parts after
demolition;
durability of the construction works;
use of environmentally compatible raw and secondary materials in the construction
works.
While the parties will ultimately always consider the cost of the design in construction, they
now have to take into account the human factors as well as the environment and how the
ecology of the design relates to the overall environment.
Engineers and architects have choices of the material and products they use to design projects.
Considering structure, the typical choice is among concrete, steel and wood. For roads and
highways, the choice is generally between concrete and asphalt. Choice of the material
depends on many factors including cost, characteristics, maintenance and performance for
specific application. Today, engineers and architects are motivated more than ever before to
select materials that are more sustainable due to increased interest in sustainable development.
Discussing the term green building technology, it considers structures that are environmental
friendly and resource-efficient throughout a building service life, from design to construction.
Green approach to design of buildings assumes reducing overall impact on the natural
environment by efficient use of energy, water and other resources as well as reducing waste,
pollution and environmental degradation.
Right now it is assumed that about thirty percent of total CO2 emissions in the world belong
to the human activities related to the construction sector. The Tables 1 and 2 show total CO2
emissions per sectors in twenty-seven EU countries in period 1990-2007.
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Table 1 - CO2 emissions by sector in EU 27 in millions of tones
3.
Concrete and Cement
Concrete is by far the most widely used construction material worldwide. In this regard,
sustainable development of concrete and concrete design needs to be foundation of all
construction activity in this millennium. For concrete production, the billions of tons of
natural materials have been mined and processed worldwide and leave substantial mark on the
environment. However, the most damaging aspect to the environment is huge quantity of
energy used for production of Portland cement. In this process, large quantities of CO2 are
also released into atmosphere. So, cement and concrete may have an important role to play in
enabling reducing the total CO2 emissions from cement and concrete production.
Table 2 - CO2 emissions by sector in EU 27 in shares (%)
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Though “cement” and “concrete” are often used interchangeably, concrete is actually the final
product made from cement. The primary component of cement is limestone. To produce
cement, limestone and other clay-like materials are heated in a kiln at 1400°C and then
ground to form a lumpy, solid substance called clinker; clinker is then combined with gypsum
to form cement.
Cement manufacturing is highly energy and emissions intensive because of the extreme heat
required to produce it. Producing a ton of cement requires 4.7 million BTU of energy,
equivalent to about 200 kilo of coal, and generates nearly a ton of CO2. Given its high
emissions and critical importance to society, cement is an obvious place to look to reduce
greenhouse gas emissions.
A single industry of cement accounts for around five percent of global carbon dioxide (CO2)
emissions. It produces a material so ubiquitous it is nearly invisible: cement. Cement is the
primary ingredient in concrete, which in turn forms the foundations and structures of the
buildings we live and work in, and the roads and bridges we drive on. Concrete is the second
most consumed substance on Earth after water. On average, each year, three tons of concrete
are consumed by every person on the planet.
Concrete is used globally to build buildings, bridges, roads, runways, sidewalks, and dams.
Cement is indispensable for construction activity, so it is tightly linked to the global economy.
Cement production is growing by percent annually, and is expected to rise from 2.55 billion
tons in 2006 to 3.7 - 4.4 billion tons by 2050.
The production of cement releases greenhouse gas emissions both directly and indirectly: the
heating of limestone releases CO2 directly, while the burning of fossil fuels to heat the kiln
indirectly results in CO2 emissions.
The direct emissions of cement occur through a chemical process called calcination.
Calcination occurs when limestone, which is made of calcium carbonate, is heated, breaking
down into calcium oxide and CO2. This process accounts for approximately fifty percent of all
emissions from cement production.
Indirect emissions are produced by burning fossil fuels to heat the kiln. Kilns are usually
heated by coal, natural gas, or oil, and the combustion of these fuels produces additional CO2
emissions, just as they would in producing electricity. This represents around forty percent of
cement emissions. Finally, the electricity used to power additional plant machinery, and the
final transportation of cement, represents another source of indirect emissions and account for
five to ten percent of the industry’s emissions.
According to the First and Second BIH National Reports according to the UNFCCC, cement
production industry in BiH produces the biggest amount of CO2 in industrial sector after the
industry of steel and iron. It represents three percent of total CO2 emission in BiH.
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Figure 3 – CO2 Emission in BiH in 2001
The following table shows the quantity of cement produced in BiH made according to the data
by Thematic Reports on Industrial Production in BiH in years 2009-2012 by Agency for
Statistics BiH.
2009
1,073,762
Cement Production in BiH in Tonnes
2010
2011
948,513
893,017
2012
845,657
Table 3 - Cement Production in BiH 2009-2012
Table 4 is made based upon data from the same source as previous table and represents
production of concrete in BiH in period 2009-2012.
Concrete Products
Fresh Concrete Mix
TOTAL
2009
282,496
807,675
1,090,171
Concrete Production in BiH in Tonnes
2010
2011
330,194
408,732
1,019,618
1,175,035
1,349,812
1,583,767
2012
328,788
1,270,725
1,599,513
Table 4 - Concrete Production in BiH 2009-2012
Analyzing these two last tables, it is obvious that cement production in BiH is reduced in
period 2009-2012 by twenty-one percent, while concrete and concrete products production
increased by almost forty-seven percent, which is very interesting comparison. Most possibly,
it is a result of cement import in BiH from neighboring countries, while increase in concrete
production is result of intensified efforts in construction on Highway-Corridor Vc, in period
of time considered. However, as much as such trends are favorable to emissions of CO2,
economical effects for economy of BiH are questionable. We will be happy to conclude that
such trends are result of introducing green technologies in cement production, but
unfortunately this was probably not a case.
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Opportunities for Reducing CO2 Emissions in Concrete Production in BiH
A primary goal is a reduction in use of Portland cement, which is possible to archive by
partially replacing it with various cementitious materials. Most preferably are byproducts of
different industrial processes in which way double goal is scored. One of such materials is fly
ash, actually a residue of coal combustion which can be excellent substitution. The use of fly
ash has a number of advantages but some disadvantages as well. Fly ash can improve specific
properties of concrete, such as durability. The fly ash is less expensive than Portland cement
and since it is a waste product, it should be disposed at great cost. However, there is a
relatively slow rate of concrete strength development, but it is irrelevant in applications where
high early strength is not required.
Another excellent cementitious material is ground granulated blast furnace slag. It is
byproduct by steel industry. As fly ash, the ground granulated blast furnace slug can improve
some mechanical and durability properties of concrete, while the cost of slag is comparable to
Portland cement.
Replacing cement with silica fume which is a byproduct of semiconductor industry is
additional option, although there is no such industry in Bosnia and Herzegovina. This
siliceous material improves both strength and durability of concrete and it is already part of
concrete mix for high strength concretes. The silica fume is difficult to handle due to its
extreme fineness and is much more expensive than cement. It also reduces the concrete fire
resistance.
The other aspect to make green concrete is substitution of virgin aggregate material with
concrete debris, especially taking in consideration that vast amounts of material are needed
for aggregate in concrete. Using such debris to produce new concrete conserves natural
resources and reduces valuable landfill capacity at the same time.
Additional possibility is material excavated from the construction of tunnels such as current
construction of the tunnels at the Highway Corridor Vc, which may very well be suitable as
aggregate to produce concrete for tunnel lining. In absolute terms, it may render unnecessary
mining of hundreds of thousand tons of virgin materials for concrete aggregate. According to
findings of the author of this paper, it is currently done exactly on the construction of the
Highway Corridor Vc.
Except the possibility discussed in last paragraph, Bosnia and Herzegovina did not do much
about production of green concrete. However, further research developments abroad and in
Bosnia and Herzegovina and different analysis should highlight the direction in reducing
GHGs emissions in concrete and cement production, as well as other environmental aspects of
the concrete production. So, the answer to the question from the title of this paper is not
simple, but definite conclusion is – “concrete can be greener, than it is now”. This paper just
highlights some possibilities and directions, but future research and analysis will provide the
answer.
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Conclusion
In general, the construction industry consumes forty percent of the total energy and about one
half of the world’s major resources. It is estimation that production of concrete produces
seven percent of total CO2 emissions in the world. Every one ton of cement produced, leads to
about 0.9 tons of CO2 emissions and typical cubic meter of concrete contains about ten
percent of cement. In the other hand, available sources of suitable virgin aggregates are
depleted and opening new sources of virgin materials is getting increasingly difficult, because
of environmental concerns. The water requirements for concrete production in the world are
almost four trillion liters of water each year worldwide, and this does not include wash water
and curing water. So, the possibilities for production of green concrete in Bosnia and
Herzegovina are more or less the same as in the other countries and lead in two major
directions:
Increased use of supplementary cementitious material, especially those that are
byproducts of industrial processes; and
Increased reliance on recycled materials. Since aggregate constitutes the bulk of
concrete, en effective recycling strategy will lesson the demand for virgin materials
and diminish landfill areas capacities.
6.
References
1. European Commission, Directorate General for Energy and Transportation, “EU Energy in Figures
2010, CO2 Emissions by Sector”;
2.M. J. Backer Esq, “The New Paradigm in Construction…no Longer It Is Simply Cost, Quality and
Budget”, CMAA, Southern California Chapter, 2009;
3. L.S. da Silva, “A Course on Design of Steel Structures”; ECCS, CECM, EKS, Stockholm; April
2013;
4. Goran Vukmir i dr, “Prvi nacionalni izvještaj Bosne i Hercegovine u skladu sa okvirnom
konvencijom Ujedinjenih nacija o klimatskim promjenama”, Banja Luka, BiH, 2009;
5. Svjetlana Radusin i dr, “Drugi nacionalni izvještaj Bosne i Hercegovine u skladu sa okvirnom
konvencijom Ujedinjenih”, juni 2013;
6. Tematski bilten TB 05, “Industrijska proizvodnja u Bosni i Hercegovini 2009”, Agencija za statistiku
Bosne i Hercegovine, Zelenih beretki 26, Sarajevo, BiH, 2010, ISSN 1840 – 104X;
7.Tematski bilten TB 05, “Industrijska proizvodnja u Bosni i Hercegovini 2010”, Agencija za statistiku
Bosne i Hercegovine, Zelenih beretki 26, Sarajevo, BiH, 2011, ISSN 1840 – 104X;
8. “Industrijska proizvodnja u Bosni i Hercegovini 2011”, Agencija za statistiku Bosne i Hercegovine,
Zelenih beretki 26, Sarajevo, BiH, 2012;
9. “Industrijska proizvodnja u Bosni i Hercegovini 2012”, Agencija za statistiku Bosne i Hercegovine,
Zelenih beretki 26, Sarajevo, BiH, 2013;
10.C. Meyer, “Concrete as a Green Building Material”, Columbia University; New York, NY 10027,
USA;
11. K. H. Obla, “What is Green Concrete”, Concrete in Focus, May/June 2009;
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12.L. Yang, “Sustainability and Innovative Construction: Green Building with Concrete”, Civil and
Enviromental Engineering 2012, Volume 2, Issue 5, ISSN 2165-784X JCEE;
13. M Glavind, C. Munch-Petersen; “Green Concrete in Denmark”, Structural Concrete, 2000, 1, No.
1M
14. K. Edvardsen, K. Tollose, “Envoromentally Green Concrete Structures”, featured at the proceedings
FIB-symposium “Concrete and Enviroment” in Berlin, October 2001.
15. http://unfccc.int/kyoto_protocol/items/2830.php
16. http://www.cop17-cmp7durban.com/en/frequently-asked-questions/what-is-the- kyotoprotocol.html
17. http://en.wikipedia.org/wiki/Kyoto_Protocol
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2493
Title
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CAN CONCRETE BE GREEN IN BOSNIA AND HERZEGOVINA?
Author
Author
DŽIDIĆ, Sanin
Abstract
A summary of the resource.
Bosnia and Herzegovina ratified the United Nations Framework Convention on Climate Change (UNFCCC) on May 17, 2000. The Kyoto Protocol was signed and ratified by the governments of 192 states and territories in the world. The Kyoto Protocol was ratified by Bosnia and Herzegovina on April 22, 2007, after completion of ratification procedures of all government levels. The First National Report of Bosnia and Herzegovina in accordance to the UNFCCC was issued in 2009 and the Second National Report of Bosnia and Herzegovina in accordance to the UNFCCC was adopted by B&H Council of Ministers in July 2013. The main goal of the Kyoto Protocol is to reduce greenhouse gas emissions to environment what caused many to focus on CO2 emissions as the most critical environment impact indicator. Concrete is by far the most widely used construction material worldwide. One of its major components is Portland cement as a binder. Total production of cement in Bosnia and Herzegovina is about 850,000 tons in 2012, while fresh concrete production and concrete products amount approximately to 1,300,000 tons in 2012. Taking in consideration that production of every ton of cement yields to approximately 0.9 tons of CO2 and every cubic meter of concrete contains about ten percent by weight of cement, significant quantity of CO2 is produced by cement industry in Bosnia and Herzegovina. It is estimation in 2001, that cement industry emissions of CO2 represented around 4 percent of total CO2 emissions by energy and industry in Bosnia and Herzegovina. However, substituting significant amounts of cement in concrete mixture with industrial by-products such as silica fume, fly ash and blast furnace slag also leads to minimization of cement consumption, even producing more durable concrete. This paper discuss possibilities in decreasing CO2 emissions in cement and concrete industry, as well as necessity of following directions of green and sustainable building in Bosnia and Herzegovina. Key Words: CO2 emission, cement, concrete, green buildings
Publisher
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International Burch University
Date
A point or period of time associated with an event in the lifecycle of the resource
2014-05-15
Keywords
Keywords.
Article
PeerReviewed
Identifier
An unambiguous reference to the resource within a given context
ISSN 978-9958-834-36-3
Q Science (General),QH301 Biology,QH426 Genetics
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https://omeka.ibu.edu.ba/files/original/5db2b35e0acf5a572566d74cb85a975c.pdf
356cf588575d8deb79b4bc7349b4a620
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RETROTRANSPOSON BASED MARKERS AND THEIR APPLICATIONS
IN BARLEY (Hordeum vulgare L.cvs.) TISSUE CULTURE
Nermin Gozukirmizi
Istanbul University, Department of Molecular Biology and Genetics, 34134 Vezneciler,
Istanbul/Turkey
E-mail: nermin@istanbul.edu.tr
Abstract
Barley has economical value and it is an important model plant. Transposons cover more than
80% of barley genome. More than 40 retrotransposons were characterized in barley genome.
This type of transposons replicate via RNA and move in the genome. As a result of these
movements, mutations and genome enlargements are occurred. During the recent years, active
transcripts and protein products of some retrotransposons have been determined. Somaclonal
variations are spontaneously occurred variations in tissue culture conditions. These variations
could be produced by genetic and/or epigenetic mechanisms and result in problems in gen
transfer applications. We investigated the retrotransposon movements in barley tissue culture
and regenerated plantlets using inter retrotransposon amplified polymorphism (IRAP), inter
primer binding side (iPBS) and analytical techniques (DNA and RNA levels) and determined
the relationship between retrotransposon movements, changes in copy number and
differention in culture conditions. For these purposes BARE1, NIKITA, BAGY2 and
SUKKULA retrotransposons were analyzed. Our research results show that tissue culture
conditions and time increase the transposon based variation and copy numbers of
retrotransposons and thus, cause genome enlargements. This research will be contribute the
understanding of basic mechanisms related to plant development and differentiation in
cultured material and also restriction of variations in applications.
Keywords: Barley, Tissue Culture, Retrotransposon markers, Somaclonal variation
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1. Introduction
Hordeum vulgare L. (barley) is an important cereal crop and is also an excellent model
organism for biochemists, physiologists, geneticists and molecular biologists. In addition,
barley provides a reference to the genomes of other Triticeae crops such as wheat, rye and
some forage grasses. H. vulgare cvs. have been used as a model system for more than 40
years at the Istanbul University Molecular Biology and Genetics (former Biology)
Department. The first studies on experimental mutagenesis were followed by tissue culture,
gene transfers, DNA marker applications, DNA arrays finally epigenetic studies which,
progressed further after the 1990 - 2005 when collaboration was established with the Plant
Biotechnology group at the TUBITAK Research Institute for Genetic Engineering and
Biotechnology in Gebze, Kocaeli-Turkey (Gozukirmizi, 2003). Since 2011, we focused on the
roles of retrotransposons on tissue culture grown barley material since transposons cover
more than 80% of the barley genome. More than 40 retrotransposons were characterized in
barley genome (http://www.ncbi.nlm.nih.gov/). These types of transposons replicate via RNA
and move in the genome. As a result of these movements, mutations and genome
enlargements occur. Recently, active transcripts and protein products of some
retrotransposons were determined. They use an RNA intermediate mechanism for
transposition. Because of their copy–paste transposition, they cause genome expansion
(Shirasu, Schulman, Lahaye, & Schulze-Lefert, 2000; Vitte & Panaud, 2005; Grzebelus,
2006). Considering their transposition mechanism and structure, they are thought to resemble
retroviruses (Kalendar, Tanskanen, Immonen, Nevo, & Schulman, 2000; Sabot & Schulman,
2006; Sabot et al., 2006). Their new copies can insert themselves into near or within genes in
a head-to-head, tail-to-tail or head-to-tail orientation.
Therefore, they can cause altered gene products, frame-shift mutations, reduction of
transcription level or even silencing of genes (Fedoroff, 2000). Due to their dynamic feature,
they are accepted as an important reason for genome evolution and speciation (Bento et al.,
2008). Since retrotransposon insertions are irreversible, they are considered useful genetic
elements in phylogenetic studies (Kumar, Gupta, Misra, Modi, & Pandey, 2009). Due to their
variation capacity between species, retrotransposons are usually studied for detection of
genetic relationships between varieties and related species (Waugh et al., 1997; Alavi-Kia,
Mohammadi, Aharizad, & Moghaddam, 2008; Baumel, Ainouche, Kalendar, & Schulman,
2002; Saeidi, Rahiminejad, & Heslop-Harrison, 2008; Belyayev et al., 2010; Smykal et al.,
2011;). Our group has mainly been working on BARE1 (Evrensel, Yilmaz, Temel, &
Gozukirmizi, 2011), BAGY2 (Yilmaz, Marakli, & Gozukirmizi, 2014), NIKITA (Bayram,
Yilmaz, Hamat-Mecbur, Kartal-Alacam, & Gozukirmizi, 2012) and SUKKULA (KartalAlacam, Yilmaz, Marakli, & Gozukirmizi, 2014, in press) retrotransposon insertion patterns
in barley calli and regenerated shoots with retrotransposon-based marker techniques (IRAP
and iPBS) to determine the effect of retrotransposon movements in somaclonal variations.
This presentation outlines the results of retrotransposon research in barley tissue culture with
the intention of contributing to barley-breeding programmes with recent biotechnological
techniques.
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2. Materials and Methods
2.1. Tissue Culture and Plantlet Regeneration
Mature embryos were excised from seeds after surface sterilization as described previously.
Basal salts of Murashige and Skoog (MS) (Murashige & Skoog, 1962) were supplemented
with 3% (w/v) sucrose, 1ml of MS vitamin mixture and 0.9% agar supplemented with 4 mg/L
dicamba with a pH of 5.7. All cultures were kept in a growth chamber with standard
conditions [25± oC, 16/8-h day/night photoperiod with fluorescent lights at 7000 lux] and was
maintained on the same medium for different period of time. After different cultivation times,
each callus was cut into three pieces and each piece was numbered with the starting embryo’s
number. One of the callus pieces was used for genomic DNA isolation, the second for shoot
regeneration in MS medium supplemented with 0.5 mg/L zeatin, and the third was
subcultured under the same callus culture conditions for aging. One of the pieces was used for
shoot regeneration and the other for DNA isolation. At the end of the tissue culture, we
obtained four experimental plant materials (calli with different aging times and their
regenerated shoots) from one embryo; these were considered a single group. IRAP was
performed with three different groups. Genomic DNA was isolated from those three groups
and three control groups using Tri Reagent (Sigma T9424) according to the manufacturer’s
instructions. The control groups consisted of noncultured mature embryos.
2.2. IRAP
IRAP was performed with forward and reverse primers designed for LTR sequences of
BARE1 (Yilmaz & Gozukirmizi, 2013) and BAGY2 (Yilmaz et al., 2014) retrotransposon.
Amplification was carried out in a 20 μL reaction volume containing 3.5 μL nuclease-free
dH2O, 0.5 μL dNTP mixture (10 mM), 2 μL of each primer (10 nmol/μL), 2 μL template
genomic DNA (10 ng/μL), and 10 μL 2× Sapphire enzyme mix. PCR conditions were an
initial denaturation step at 94°C for 3 min; followed by 30 cycles at 94°C for 20 s, 52°C for
20 s, and 72°C for 2 min; and a final extension step at 72°C for 10 min.
2.3. Evaluation of PCR Products
PCR products were loaded to 6% non-denature polyacrylamide gel (29:1 Acrylamide:Bis) and
gel was run at 200 V for 4 h in 1X TBE buffer. A molecular weight marker (GeneRuler™ 1
kb DNA Ladder, SM0312, Fermentas) was also loaded to determine the size of amplicons.
Gel was stained and photographed on a UV transilluminator. Well-resolved bands were
scored with a binary value, (1) for presence and (0) for absence. The binary matrix (1/0) was
used to calculate the similarity between embryo, 40 and 80 day-old calli. Jaccard’s similarity
index was calculated using the formula: NAB / (NAB + NB + NA); where NAB is the number of
bands shared by 2 samples, NA represents amplified fragments in sample A, and NB represents
amplified fragments in sample B (Jaccard, 1908).
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3. Results and Discussion
Our results showed that calli which have different culturing time can have different IRAP
band patterns although they originated from the same embryo (Figure 1).
Figure 1. IRAP profiles for BARE1. 1-3; mature embryo (control), 4-9; first group [4, 5, 6;
calli originated from the same embryo (30, 60, 90 day-old respectively), and 7, 8, 9;
regenerated shoot originated from these calli respectively)], 10-15; second group [10, 11, 12;
calli originated from another embryo (30, 60, 90 day-old respectively), and 13, 14, 15;
regenerated shoot originated from the second group’s calli)]. Arrows indicate the polymorphic
bands (Yilmaz & Gozukirmizi, 2013).
We also performed studies on NIKITA and SUKKULA retrotransposons on aging calli
materials (Bayram et al., 2012; Kartal-Alacam et al., 2014). We were able to observe
polymorphisms in cultured materials. Finally, we studied BAGY2 retrotransposon (Figure 2).
We observed that BARE1 and BAGY2 are the most active retrotransposons (with
polymorphism rates; up to 25% and 20% respectively) during callus culture (Evrensel et al.,
2011, Yilmaz et al., 2014). We also observed NIKITA polymorphisms at different ages in old
barley calli but the polymorphism rates were lower than BARE1 and BAGY2 (Bayram et al.,
2012).
Figure 2. IRAP profiles of calli and shoots for BAGY2. 1, non-cultured embryo; 2-13, tissue
culture materials (2, 6, 10 45-days-old calli; 3, 7, 11 shoots regenerated from 45-days-old calli;
4, 8, 12 90-days-old calli; 5, 9, 13 shoots regenerated from 90-days-old calli) (Yilmaz et al.,
2014).
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In addition to retrotransposon-based marker techniques, we also analyzed the copy number
alterations of BAGY2 internal domains (GAG, PR, RT, RH, INT) by real-time PCR (qPCR).
qPCR results proved that all internal domains have copy number variations between different
aged calli (Yilmaz et al., 2014). These findings show that tissue culture conditions and
culturing time cause insertional activation of some barley retrotransposons.
These findings may prove that tissue culture conditions and duration of cultivation period do
not cause the same effect on calli. This research will contribute to the understanding
of scientific mechanisms related to plant development and differentiation and also restriction
of variations in applications (Evrensel et al., 2011; Bayram et al., 2012; Yilmaz &
Gozukirmizi, 2013; Yilmaz et al., 2014; Kartal-Alacam et al., 2014).
Hirochika (1993) published one of the pioneer studies showing transposon activity changes in
tobacco protoplast culture. Afterward many studies were published for tissue culture effect on
transposon activations. Liu et al. (2004) demonstrated that Tos17 retrotransposon has been
activated during rice tissue culture. Somaclonal variations were also studied at banana by
IRAP technique (Muhammad & Othman 2005). Retrotransposon-derived polymorphisms
were also reported at tissue culture of a wild barley species (Hordeum brevisubulatum) by
various marker systems (Li et al., 2007). Campbell et al. (2011) also showed that BARE1
retrotransposon was activated in barley tissue culture.
We need more detailed studies on transposons, and their effects on epigenetic and genetic
mechanisms. Our data will be helpful for the understanding of their behavior during tissue
culture. We briefly conclude that barley retrotransposons, both autonomous and nonautonomous, are very active during tissue culture procedure and we still do not have an
opinion if these movements are randomly or partly directed according to the cultural
development of the plants.
4. References
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phylogenetic relationships in Crocus genus of Iran using inter-retrotransposon amplified polymorphism.
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Baumel, A., Ainouche, M., Kalendar, R., & Schulman, A.H. (2002). Retrotransposons and genomic stability in
populations of the young allopolyploid species Spartina anglica C.E. Hubbard (Poaceae). Molecular Biology
and Evolution, 19(8), 1218-1227.
Bayram, E., Yilmaz, S., Hamat-Mecbur, H., Kartal-Alacam, G. & Gozukirmizi, N. (2012). Nikita
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Belyayev, A., Kalendar, R., Brodsky, L., Nevo, E., Schulman, A.H. & Raskina, O. (2010). Transposable
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Bento, M., Pereira, H. S., Rocheta, M., Gustafson, P., Viegas, W., & Silva, M. (2008). Polyploidization as a
retraction force in plant genome evolution: Sequence rearrangements in Triticale. PLoS One, 3, 1-11.
Campbell, B. C., LeMare, S., Piperidis, G., & Godwin, I. D. (2011). IRAP, a retrotransposon-based marker
system for the detection of somaclonal variation in barley. Molecular Breeding, 27, 193-206.
Evrensel, C., Yilmaz, S., Temel, A., & Gozukirmizi, N. (2011). Variations in BARE-1 insertion patterns in barley
callus cultures. Genetics and Molecular Biology Research, 10, 980-987.
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Fedoroff, N. (2000). Transposons and genome evolution in plants. Proceedings of the National Academy of
Sciences of the United States of America, 97(13), 7002-7007.
Gozukirmizi, N. (2003). Pioneering biotechnological works on Hordeum vulgare L. cvs performed in
collaboration with the Istanbul University Biology Department and the TUBITAK Research Institute for Genetic
Engineering and Biotechnology. Turkish Journal of Botany, 27, 243-248.
Grzebelus, D. (2006). Transposon insertion polymorphism as a new source of molecular markers. Journal of
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Hirochika, H. (1993). Activation of tobacco retrotransposons during tissue culture. The EMBO Journal, 12,
2521–2528.
Jaccard, P. (1908). Nouvelles recherches sur la distribution florale. Bulletin de la Societe Vaudoise des Sciences
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Kalendar, R., Tanskanen, J., Immonen, S., Nevo, E., & Schulman, A.H. (2000). Genome evolution of wild
barley (Hordeum spontaneum) by BARE-1 retrotransposon dynamics in response to sharp microclimatic
divergence. Proceedings of the National Academy of Sciences of the United States of America, 97, 6603-6607.
Kartal-Alacam, G., Yilmaz, S., Marakli, S., & Gozukirmizi, N. (2014). Sukkula retrotransposon insertion
polymorphisms in barley. Russian Journal of Plant Physiology, (in press).
Kumar, P., Gupta, V.K., Misra, A.K., Modi, D.R., & Pandey, B.K. (2009). Potential of molecular markers in
plant biotechnology. Plant Omics, 2, 141-162.
Li, X., Yu, X., Wang, N., Feng, Q., Dong, Z., Liu, L., Shen, J., & Liu, B. (2007). Genetic and epigenetic
instabilities induced by tissue culture in wild barley (Hordeum brevisubulatum (Trin.) Link). Plant Cell,
Tissue and Organ Culture, 90, 153-168.
Liu, Z. L., Han, F. P., Tan, M., Shan, X. H., Dong, Y. Z., Wang, X. Z., Fedak, G., Hao, S., & Liu, B. (2004).
Activation of a rice endogenous retrotransposon Tos17 in tissue culture is accompanied by cytosine
demethylation and causes heritable alteration in methylation pattern of flanking genomic regions. Theoretical
and Applied Genetics, 109, 200–209.
Muhammad, A. J., & Othman, R. Y. (2005). Characterization of Fusarium wilt-resistant and Fusarium wiltsusceptible somaclones of banana cultivar rastali (Musa AAB) by random amplified polymorphic DNA and
retrotransposon markers. Plant Molecular Biology Reporter, 23, 241-249.
Murashige, T. & Skoog, F. (1962). A revised medium for rapid growth and bio assays with tobacco tissue
cultures. Physiologia Plantarum, 15, 473-497.
Sabot, F., Kalendar, R., Jääskeläinen, M., Wei, C., Tanskanen, J. & Schulman A. H. (2006). Retrotransposons:
metaparasites and agents of genome evolution. Israel Journal of Ecology & Evolution, 52, 319-330.
Sabot, F. & Schulman, A.H. (2006). Parasitism and the retrotransposon life cycle in plants: a hitchhiker's guide
to the genome. Heredity, 97, 381-388.
Saeidi, H., Rahiminejad, M. R., & Heslop-Harrison, J. S. (2008). Retroelement insertional polymorphisms,
diversity and phylogeography within diploid, D-genome Aegilops tauschii (Triticeae, Poaceae) Sub-taxa in Iran.
Annals of Botany, 101, 855-861.
Shirasu, K., Schulman, A. H., Lahaye, T., & Schulze-Lefert, P. (2000). A contiguous 66-kb barley DNA
sequence provides evidence for reversible genome expansion. Genome Research, 10, 908-915.
Smykal, P., Bacova-Kerteszova, N., Kalendar, R., Corander, J., Schulman, A. H., & Pavelek, M. (2011).
Genetic diversity of cultivated flax (Linum usitatissimum L.) germplasm assessed by retrotransposonbased markers. Theoretical and Applied Genetics, 122(7), 1385-1397.
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Waugh, R., McLean, K., Flavell, A. J., Pearce, S. R., Kumar, A., Thomas, B. B., & Powell, W. (1997). Genetic
distribution of Bare-1-like retrotransposable elements in the barley genome revealed by sequence-specific
amplification polymorphisms (S-SAP). Molecular and General Genetics, 253(6), 687-694.
Vitte, C., & Panaud, O. (2005). LTR retrotransposons and flowering plant genome size: emergence of the
increase/decrease model. Cytogenetic and Genome Research, 110, 91-107.
Yilmaz, S., & Gozukirmizi, N. (2013). Variation of retrotransposon movement in callus culture and regenerated
shoots of barley. Biotechnology and Biotechnological Equipment, 27, 4227-4230.
Yilmaz, S., Marakli, S., & Gozukirmizi, N. (2014). BAGY2 retrotransposon analyses in barley calli cultures and
regenerated plantlets. Biochemical Genetics,52, DOI 10.1007/s10528-014-9643-z.
Prof.Dr. Nermin Gozukirmizi is a scientist from Istanbul University, Molecular Biology and
Genetics Department, Istanbul-Turkey. She took part for Establishment of Plant
Biotechnology Research Unit at Marmara Research Centre, Research Institute of Genetic
Engineering and Biotechnology, 1992-2006. She also had an active role for the establishment
of Molecular Biology and Genetics Department at Istanbul University. Her areas of research
include molecular biology, tissue culture and gene transfers, somatic variations, GMO and
biotechnology. She is an author or co-author of numerous scientific papers and several boks.
Her recent internationally published scientific papers are related to retrotransposons, gene
transfers and salt tolerance.
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Title
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RETROTRANSPOSON BASED MARKERS AND THEIR APPLICATIONS IN BARLEY (Hordeum vulgare L.cvs.) TISSUE CULTURE
Author
Author
GOZUKIRMIZI, Nermin
Abstract
A summary of the resource.
Barley has economical value and it is an important model plant. Transposons cover more than 80% of barley genome. More than 40 retrotransposons were characterized in barley genome. This type of transposons replicate via RNA and move in the genome. As a result of these movements, mutations and genome enlargements are occurred. During the recent years, active transcripts and protein products of some retrotransposons have been determined. Somaclonal variations are spontaneously occurred variations in tissue culture conditions. These variations could be produced by genetic and/or epigenetic mechanisms and result in problems in gen transfer applications. We investigated the retrotransposon movements in barley tissue culture and regenerated plantlets using inter retrotransposon amplified polymorphism (IRAP), inter primer binding side (iPBS) and analytical techniques (DNA and RNA levels) and determined the relationship between retrotransposon movements, changes in copy number and differention in culture conditions. For these purposes BARE1, NIKITA, BAGY2 and SUKKULA retrotransposons were analyzed. Our research results show that tissue culture conditions and time increase the transposon based variation and copy numbers of retrotransposons and thus, cause genome enlargements. This research will be contribute the understanding of basic mechanisms related to plant development and differentiation in cultured material and also restriction of variations in applications. Keywords: Barley, Tissue Culture, Retrotransposon markers, Somaclonal variation
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International Burch University
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2014-05-15
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ISSN 978-9958-834-36-3
Q Science (General),QH301 Biology,QH426 Genetics
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https://omeka.ibu.edu.ba/files/original/fef42c0f2e365d343ab6b0407d044617.pdf
a4ec7f9ad451b4fcd615e6b3957de035
PDF Text
Text
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DIAGNOSING SLEEP APNEA VIA FEATURE SELECTION ON SINGLE
CHANNEL ECG
Huseyin Guruler1, Abdullah Ferikoglu 2
1
Mugla Sitki Kocman University, Faculty of Technology, Department of Information Systems
Engineering, Mugla-Turkey
hguruler@mu.edu.tr
2
Sakarya University, Faculty of Technology, Department of Electrical & Electronics
Engineering, Sakarya-Turkey
af@sakarya.edu.tr
1
Corresponding Author
ABSTRACT
This article is based on a combination of time-frequency domain functions, and nonlinear
techniques in the analysis of heart rate variability (HRV) for diagnosing obstructive sleep
apnea (OSA) using only single-lead electrocardiography (ECG) signals. The contribution of
the presented study to earlier ones is that it enables numerically determining what type of
HRV features better represent the aforementioned target by using correlation matrices and
neural networks (NNs).
Keywords: Diagnosing disease, neural network, sleep apnea, heart rate variability, feature
selection, correlation matrices
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1. INTRODUCTION
Study on variations in the instantaneous heart rate (HR) time series using the beat-to-beat RR
intervals are known as HRV analysis. HR increases with sympathetic activity and decreases
with parasympathetic (vagal) activity. The balance between the effects of the sympathetic and
the parasympathetic systems, the two opposite acting branches of the autonomic nervous
system (ANS), is referred to as the sympathovagal balance (SB) (Acharya, Joseph, Kannathal,
Lim, & Suri, 2006).
Spectral analysis is typically used to estimate the effect of the sympathetic and
parasympathetic modulation of the RR intervals. The two main frequency bands of interest
are referred to as the low frequency (LF) band and the high frequency (HF) band.
Sympathetic tone is believed to influence the LF component, whereas both sympathetic and
parasympathetic activities have an effect on the HF component. The ratio of the power
contained in the LF and HF components has been used as a measure of the SB (Jos & Spaan,
2007).
OSA is a serious disorder caused by intermittent airway obstruction in sleep (Abdullah,
Maddage, Cosic, & Cvetkovic, 2010), (Lado, et al., 2009). OSA causes changes in cardiac
and neuronal activity and discontinuities in sleep pattern when observed via ECG and
electroencephalogram (EEG). OSA is usually diagnosed using polysomnography (PSG)
conducted in sleep laboratories (Roche, Celle, Pichot, Barthélémy, & Sforza, 2007). PSG is
utilized to define physiological sleep and its different stages, to assess sleep quality and to
diagnose many types of sleep disorders such as insomnia, OSA, restless legs syndrome and
periodic leg movement disorders. However, PSG is very expensive and the technology
requires not only the connection of various sensors and electrodes (e.g. EEG,
Electrooculogram (EOG) and Electromyogram (EMG), and ECG etc.) but also spending the
night in a bed (Yilmaz, Asyali, Arikan, Yetkin, & Ozgen, 2010).
Detection of OSA can be performed and significantly improved through HRV analysis, since
fluctuations of oxygen saturation in blood accompanied by apnea, cause variations in the HR
(Quiceno-Manrique, Alonso-Hernandez, Travieso-Gonzalez, Ferrer-Ballester, & CastellanosDominguez, 2009), (Al-Abed, Manry, Burk, Lucas, & Behbehani, 2009). SB has been used
for detection of OSA in many studies. The review (Penzel, et al., 2002), presents systematic
comparison of studies using different algorithms for OSA detection based on the same ECG
recordings (Moody, Mark, Goldberger, & Penzel, 2000). In these researches, HRV with or
without respiratory signals are generally analyzed in three main areas: Time, Frequency and
Non-linear Analysis. Each analysis technic produces some features, which are usually
numerical values. These values are used in decision-making algorithms or mathematical
models that may involve neural networks (NNs), support vector machines (SVMs), wavelet
etc. So far, many combinations of time, frequency and non-linear domain features of HRV
obtained from ECG have been used with different type of classification methods. Although
high accuracies of OSA detection and significant successes on apnea classification can be
achieved, it is still unclear which feature parameters are more effective for classification.
This study aims to classify pre-collected sleep data into one of the three basic types; apnea,
hypopnea, and healthy episodes, with fewer parameters obtained from single-lead ECG
recordings. Besides that, it determines numerically what features of HRV better represent the
classification.
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2. MATERIALS and METHODS
The present study uses a variety of significant and relevant characteristic features include
morphological information, duration and complexity details of the ECG to classification.
Table 1. summarize all the HRV measures.
Table 1. Summary of the HRV Measures
Nonlinear
Frequency
Time-Domain
Measures
RR
SDNN
HR
STD HR
RMSSD
NN50
pNN50
HRV
triangular
index
TINN
Peak frequencies
Absolute powers
Relative powers
Normalized
powers
SD1,
SD2
ApEn
SampEn
D2
DFA
Alfa 1
Alfa 2
RPA
Lmean
Lmax
REC
DET
ShanEn
Description
The mean of RR intervals
Standard deviation of RR intervals
The mean of HR
Standard deviation of instantaneous HR values
Square root of the mean squared differences between successive RR
intervals
Number of successive RR interval pairs that differ more than 50 ms
NN50 divided by the total number of RR intervals
The integral of the RR interval histogram divided by the height of the
histogramwidth of the RR interval histogram
Baseline
VLF, LF, and HF band peak frequencies
Absolute powers of VLF, LF, and HF bands
Relative powers of VLF, LF, and HF bands
Powers of LF and HF bands in normalized units
The standard deviation of the Poincare plot perpendicular to (SD1) and
along (SD2) the
line-of-identity
Approximate
entropy
Sample entropy
Correlation dimension
Detrended fluctuation analysis
Short term fluctuation slope
Long term fluctuation slope
Recurrence plot analysis
Mean line length
Maximum line length
Recurrence rate
Determinism
Shannon entropy
The feature sets obtained from analysis methods those are time-domain, frequency-domain
and non-linear methods. Time domain analysis involved statistical and geometrical
calculations. Frequency domain analysis was performed using fast Fourier transform (FFT)
and autoregressive (AR) modelings. Non-linear methods including Poincaré and recurrence
plots, approximate and sample entropies, detrended fluctuations and correlation dimensions
were used.
WFDB (WaveForm Databases) software package used for viewing, analyzing, and creating
recordings of physiologic signals. “Kubios HRV” software used for HRV analysis (Niskanen,
Tarvainen, Ranta-Aho, & Karjalainen, 2004). Matlab NN toolbox was used for classification.
Classification of OSA was realized on Apnea-ECG Database in PhysioBank (Penzel, Moody,
Mark, Goldberger, & Peter, 2000). Table 2 shows Demographic and Clinical Features of the
dataset. The data consists of 70 records, divided into learning and test sets equally. Learning
and test recordings involves three classes namely Apnea, Hypopnea, and Healthy depending
on apnea-hypopnea index (AHI) (Ruehland, et al., 2009).
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Table 2. Demographic and clinical features of apnea-ECG dataset
Subjects (n)
Age (years)
Males (n)
BMI (kg/m2)
Records (h)
AHI (e/h)
All subjects
70
45.6±10.6
57
28.1±6.5
8.2±0.5
-
Apnea
40
51.5±7.6
38
30.8±4.6
8.4±0.4
45.4±22.5
Hypopnea
10
47.2±5.9
8
30.4±9.2
8.0±0.6
12.1±12.0
Healthy
20
32.9±5.4
11
21.3±1.9
7.9±0.4
0.0±0.0
p-value
NS
p<0.01
NS
NS
p<0.01
Data are presented as mean ± SD or n; BMI: Body mass index; NS: no significant statistical difference
Depending of AHI: Apnea: Recordings with clear occurrence of sleep apnea (100 min or more). 40 recordings fulfilled this criterion.
Hypopnea: Recordings with some degree of sleep apnea (between 5 and 99 min). The recordings revealed either mild apnea, up to an
apnea index of 10 events per hour, or obstructive snoring in otherwise healthy subjects. 10 recordings fulfilled this criterion. Healthy:
Recordings of healthy subjects with neither sleep apnea (fewer than 5 min) nor habitual snoring. 20 recordings fulfilled this criterion.
Figure 1 describes the classification process.
Figure 1. OSA Classification Process
Feature extraction was realized on HRV by time, frequency and non-linear techniques. Due to
the feature extraction involves number of parameters having various degrees of importance
for classification, CMs were used to select the parameters, which are preferred for neural
networks (NNs) as an input. Better correlation provides better classification ability for NNs.
CMs are simply tables, in which correlation coefficients “see (1)” for every single column in
relation to target column take place.
(1)
Feed forward back propagation NNs can give high accuracy results with small number of
hidden layers. Hence, the classification process was realized with feed forward back
propagation NNs.
3. RESULTS
Table 3 and Figure 2 shows the classification and iteration results for 6 methods. Here, only
highly correlated parameters in each methods were noticed. CMs helps to find lower
correlated parameters, which could be eliminated by looking their correlation coefficients.
Methods 1 to 4 indicates classification ability of parameters belonging to each HRV analysis
method individually. Methods 5 and 6, on the other hand, involves mixed parameters from
methods 1 to 4. Method 6 use only high correlated parameters in its groups.
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Table 3. Classification results
Classes
1
Method
Accuracy
Iterations
2
Method
Accuracy
Iterations
3
Method
Accuracy
Iterations
4
Method
Accuracy
Iterations
5
Method
Accuracy
Iterations
6
Method
Accuracy
Iterations
A, B, C
(A+B), C
Temporal parameters
0.63
0.85
100
60
FFT spectral parameters
0.78
0.93
500
300
AR spectral parameters
0.78
0.93
300
70
Non-Linear parameters
0.72
0.96
400
100
All parameters from 1 to 4 methods
0.78
0.96
600
50
High correlated parameters from 1 to 4 methods
0.82
0.96
600
30
*
Three Classes are A, B, C and two classes are (A+B), C (A:Apnea B:Hypopnea C:Healthy)
Classification Accuracy
Iterations
Figure 2. Classification and Iteration Results
Series 1 the results for two classes (A+B) and C, Series 2 the results for three classes A, B and C
Accuracy was high using the parameters of non-linear, frequency and time domain respectively. The accuracy was
found 96.42% for the classification to A and C (A- Apnea C- Healthy) and 82% for the classification to A, B and C (AApnea B- Hypopnea C- Healthy) respectively. When certain parameters selected only higher correlated from 1 to 4
methods, highest accuracy observed with minimum iteration numbers using NNs.
4. CONCLUSIONS
This work offers a method for feature selection and regularization of classifier parameters that
were used to optimize classifier performance. The accuracy of the results with the dimension
reduction on the feature sets clearly shows that correlation matrices can be focused on
minimizing the feature sets used for sleep classification. Classification performance was
highest with non-linear equations and lowest with time domain features, with frequency
features at midpoint on OSA diagnosis. On the other hand, computational works were in
opposite direction in terms of iterations, which required to obtain reasonable results on NN
structures.
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5. ACKNOWLEDGMENTS
We would like to acknowledge the funding support for this project from The Scientific and
Technological Research Council of Turkey (TÜBİTAK), (2214) International Research
Fellowship Program, December 2010-December 2011.
6. REFERENCES
Abdullah, H., Maddage, N. C., Cosic, I., & Cvetkovic, D. (2010). Cross-correlation of EEG frequency bands and
heart rate variability for sleep apnoea classification. Medical & biological engineering & computing, 48(12),
1261-1269.
Acharya, U. R., Joseph, K. P., Kannathal, N., Lim, C. M., & Suri, J. S. (2006). Heart rate variability: A review.
Medical and Biological Engineering and Computing, 44(1), 1031-1051.
Al-Abed, M. A., Manry, M., Burk, J. R., Lucas, E. A., & Behbehani, K. (2009). Sleep disordered breathing
detection using heart rate variability and R-peak envelope spectrogram. IEEE Engineering in Medicine and
Biology Society, EMBC 2009, (pp. 7106-7109).
Jos, S. M., & Spaan, A. E. (2007). Advances in Cardiac Signal Processing. Berlin Heidelberg: Springer-Verlag.
Lado, M. J., Vila, X. A., Rodriguez-Linares, L., Mendez, A. J., Olivieri, D. N., & Felix, P. (2009). Detecting
Sleep Apnea by Heart Rate Variability Analysis: Assessing the Validity of Databases and Algorithms. Journal of
medical systems, 35(4), 473-481.
Moody, G. B., Mark, R. G., Goldberger, A. L., & Penzel, T. (2000). Stimulating rapid research advances via
focused competition: the computers in cardiology challenge 2000. IEEE Computers in Cardiology 2000, (pp.
207-210). Cambridge, MA, USA.
Niskanen, J. P., Tarvainen, M. P., Ranta-Aho, P. O., & Karjalainen, P. A. (2004). Software for advanced HRV
analysis. Computer methods and programs in biomedicine, 76(1), 73-81.
Penzel, T., McNames, J., Murray, A., de Chazal, P., Moody, G., & Raymond, B. (2002). Systematic comparison
of different algorithms for apnoea detection based on electrocardiogram recordings. Medical and Biological
Engineering and Computing, 40(4), 402-407.
Penzel, T., Moody, G. B., Mark, R. G., Goldberger, A. L., & Peter, J. H. (2000). Apnea-ECG database. IEEE
Computers in Cardiology 2000, (pp. 255-258). Cambridge, MA, USA.
Quiceno-Manrique, A. F., Alonso-Hernandez, J. B., Travieso-Gonzalez, C. M., Ferrer-Ballester, M. A., &
Castellanos-Dominguez, G. (2009). Detection of obstructive sleep apnea in ECG recordings using timefrequency distributions and dynamic features. IEEE Engineering in Medicine and Biology Society, EMBC 2009,
(pp. 5559-5562).
Roche, F., Celle, S., Pichot, V., Barthélémy, C., & Sforza, E. (2007). Analysis of the interbeat interval increment
to detect obstructive sleep apnoea/hypopnoea. European Respiratory Journal, 29(6), 1206-1211.
Ruehland, W. R., Rochford, P. D., O'Donoghue, F. J., Pierce, R. J., Singh, P., & Thornton, A. T. (2009). The
new AASM criteria for scoring hypopneas: impact on the apnea hypopnea index. Sleep, 32(2), 150-157.
Yilmaz, B., Asyali, M. H., Arikan, E., Yetkin, S., & Ozgen, F. (2010). Sleep stage and obstructive apneaic epoch
classification using single-lead ECG. Biomedical engineering online, 9, 39.
Huseyin Guruler is academic staff in the Department of Information Systems Engineering in
Mugla Sitki Kocman University, Turkey. His bachelor's degree is in the field of electronics
and computer from Marmara University. MSc is in the field of statistics and computer in
Mugla Sitki Kocman University. PhD is in the field of electronics and computer in Sakarya
University. PhD thesis is about diagnosing sleep apnea using ECG signals. His research
interests merge in data mining and knowledge discovery besides dealing with computational
biology and multi-user computers architecture.
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Title
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DIAGNOSING SLEEP APNEA VIA FEATURE SELECTION ON SINGLE CHANNEL ECG
Author
Author
GURULER, Huseyin
FERIKOGLU, Abdullah
Abstract
A summary of the resource.
This article is based on a combination of time-frequency domain functions, and nonlinear techniques in the analysis of heart rate variability (HRV) for diagnosing obstructive sleep apnea (OSA) using only single-lead electrocardiography (ECG) signals. The contribution of the presented study to earlier ones is that it enables numerically determining what type of HRV features better represent the aforementioned target by using correlation matrices and neural networks (NNs). Keywords: Diagnosing disease, neural network, sleep apnea, heart rate variability, feature selection, correlation matrices
Publisher
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International Burch University
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2014-05-15
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ISSN 978-9958-834-36-3
Q Science (General),QH301 Biology,QH426 Genetics
-
https://omeka.ibu.edu.ba/files/original/3c4ea2a361184edbe46f7f89e0c19c95.pdf
7a2c98031c57e45aa4ab1c50916c4516
PDF Text
Text
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REMOVAL OF NITROGEN FROM MUNICIPAL WASTEWATER - THE EFFECT
OF THE ADDITION OF CARBON SOURCES ON BIOLOGICAL
DENITRIFICATION
Jasmina Ibrahimpašić1, Merima Toromanović1, Tibela Landeka Dragičević2
1
2
University of Bihać, Biotechnical Faculty, Bihać, Bosnia and Herzegovina
University of Zagreb, Faculty of Food Technology and Biotechnology, Zagreb, Croatia
jasmina.ibrahimpasic@btf.unbi.ba, toromanovic_merima@hotmail.com
ABSTRACT
In this work was used activated sludge from the WWTP (wastewater treatment plant), in
which with technique accumulation nitrificants and denitrificants, were prepared mixed
bacterial cultures which showed the ability nitrification of ammonia- nitrogen to nitrate, as
well as the ability of denitrification of nitrate nitrogen to gaseous nitrogen in municipal
wastewater. As carbon source in the process of biological denitrification was used sodium
acetate, in the ratio C/N=1 and C/N=2. Activity of mixed microbial cultures for removal
components with nitrogen was determined by measuring the concentration of organic matter,
expressed as COD, ammonia-nitrogen, nitrite, nitrate, pH, concentration dissolved oxygen,
and the concentration of microbial biomass.
Keywords: municipal water, activated sludge, nitrogen removal
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INTRODUCTION
The most widely used procedure for the treatment of municipal wastewater is an aerobic
process with activated sludge. The activated sludge system with balance between different
types of bacteria is essential to ensure effective removal of pollutants, good sedimentation of
sludge and low levels of suspended particulate matter (Mesquita et al. 2009). Biological
nitrogen removal from wastewater is achieved by applying the process of aerobic ammonia
oxidation, or autotrophic aerobic nitrification and anoxic (facultative-anaerobic)
denitrification. Ammonia oxidizing bacteria (AOB), such as Nitrosomonas, Nitrosospira and
Nitrosococcus, converted ammonia to nitrite.
Nitrate oxidizing bacteria (NOB), such as Nitrobacter, Nitrosospira, Nitrococcus and
Nitrospina, further converted nitrite to nitrate (Henze et al. 2002). During denitrification
process nitrates are exceeding into the nitrogen gas. Nitrogen gas is released into the air, and
in this way removed from the wastewater. These two processes depend on several factors,
such as temperature, pH, dissolved oxygen, alkalinity, toxicity, etc. (Metcalf & Eddy, 2003;
Jeyanayaga, 2005; Gerardi, 2002).
The main objective of this study was to define the working conditions of removal nitrogen
compounds process of nitrification and denitrification in municipal wastewater, with the
addition of heterotrophic carbon source, and to determine the conditions for quality water
treatment in accordance with current regulations.
MATERIAL AND METHODS
In the research was used activated sludge from the WWTP (wastewater treatment plant). In
the activated sludge is, with a technique accumulation nitrificants and denitrificants, prepared
mixed bacterial cultures, which showed the ability of nitrification ammonia nitrogen to
nitrate, and the ability of denitrification of nitrate nitrogen to nitrogen gas. The enrichment of
mixed microbial culture was performed in Erlenmeyer flasks (500 mL, with working volume
of 100 mL) on rotary shaker and room temperature, with municipal wastewater as a source
of ammonium nitrogen (15-147 mg NH4+-N L–1). After of cultivation, the biomass as
inoculum was prepared and used in all experiments.
Activity of the microbial culture for the removal of nitrogen compounds was determined by
measuring the concentration of ammonia nitrogen, nitrite, nitrate, pH, dissolved oxygen
concentration and the concentration of the microbial biomass. Nitrogen removal in oxy/anoxia
conditions, as well as all the experiments that preceded: autotrophic and heterotrophic
nitrification with adding an external carbon source for nitrification, were conducted in a
laboratory reactor working volume of 2 liters. Denitrification is carried out in conditions
without aeration, with stirring the reactor contents with the help of the mixer placed in the
reactor. The reactor is equipped with gauges of pH, dissolved oxygen and temperature.
All analytical data were determined by the methods prescribed by APHA (APHA, 1998): the
concentration of organic substances, expressed as COD-value, BOD, NH4-N, NO3-N, NO2-N,
pH, temperature, dissolved oxygen concentration, dry matter, suspended solids and biomass
concentration.
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RESULTS
Experiments were carried out by gradually increasing the concentration of NH4-N, 15 mg/L to
147 mg/L, which is the same concentration of ammonia in municipal wastewater. In
experiments was monitored microbial activity with the addition of sodium acetate as a carbon
source in an external ratios C:N=1:1, C:N=2:1. Once the technique of enrichment and
adaptation prepared microbial cultures which showed the ability of biodegradation, in
experiments is added municipal wastewater and is accompanied by its biodegradation. Below
are shown the most important results.
Table 1. Chemical and physical indicators of quality of municipal wastewater
Parameter
Value
Color
Smell
Temperature (°C)
pH
Conductivity (µS)
Oxygen saturation (%)
Dissolved oxygen (mg/L)
Sediment matter (ml of sediment)
Evaporated residue (mg/L)
Annealed rest (mg/L)
Suspended solids (mg/L)
Nitrites (mg/L)
Nitrates (mg/L)
Ammonia (mg/L)
COD (mgO2/L)
BOD5 (mgO2/L)
gray-brown
typical
14,7
8
816
7,2
3,4
5
754,48
231
1014
0,41
1,1
147
284
245
Sludge from the treatment of wastewater NaAc was added as an external carbon source in the
ratio of C:N=2:1, and the concentration of NH4-N addition to the initial 50 mg/L. The total
volume of the reactor is 2L.
Figure 1. NH4-N, NO3-N, NO2-N and dissolved oxygen concentration, pH and temperature
determined during the process of nitrification
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Figure 2. The concentration of organic substances, expressed as COD
In the enriched microbial culture was added a municipal wastewater in an amount so that the
concentration of NH4-N is set to the initial 70 mg/L. As an external carbon source was added
sodium acetate at a ratio of C:N=1:1. The experiment was carried out with alternating
nitrification and denitrification. Nitrification is carried out in the oxy and denitrification in
anoxia conditions, with stirring. Oxy/anoxia conditions during the process of alternating
nitrification/denitrification maintained by the dynamics: 0.5 hours of anoxia conditions, then 1
hour oxy conditions, then again 0.5 hours of anoxia conditions and again oxy conditions. The
total volume of the reactor is 2L.
Figure 3. NO3-N, NO2-N and dissolved oxygen concentration and pH value determined
during the biodegradation process of wastewater
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Figure 4. The concentration of organic substances, expressed as COD and NH4-N during the
biodegradation of wastewater
After the technique of adaptation and enrichment, it was prepared microbial culture capable of
biological degradation, and in the sludge is added municipal wastewater and the NH4-N
concentration of 147 mg/L. The total volume of the reactor is 2L.
Dissolved oxygen
Nitrites
Nitrates
Figure 5. NO3-N, NO2-N, dissolved oxygen concentration and pH during the biodegradation
process of wastewater
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Figure 6. The concentration of organic substances, expressed as COD, NH4-N, and the
temperature
All previous nitrification processes were carried out under aerobic conditions. After nitrite
nitrogen completely oxidized, after 6 hours, into nitrate nitrogen, investigate the ability of
microbial cultures for the denitrification. Denitrification is carried out under anoxic conditions,
only by stirring. As a carbon source was used municipal wastewater. Parameters were
monitored every 3 hours, and 24 hours. The volume of the reactor is 2L.
Figure 7. NH4-N, NO3-N, NO2-N and the concentration of dissolved oxygen, pH and
temperature during the process of denitrification
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Figure 8. The concentration of organic substances, expressed as COD
DISCUSSION
In the experiment in the heterotrophic nitrification, where the organic compound as a source
of added sodium acetate in a 2:1 ratio, and the initial concentration of NH4-N 50 mg / l,
nitrification is done for five hours (Figure 1). Oxidation of ammonia (ammonia converted into
NO3 -N and NO 2-N) is followed by decomposition of organic matter (COD) in the beginning
of the process, as well as the accumulation of nitrite and nitrate (see Figures 1 and 2).
Extended aeration for a further three hours, all the NO2-N is converted to NO3-N. From the
first hour until the end of the process, NO3-N has accumulated (Figure 1). In the experiment,
heterotrophic nitrification rate of oxidation of ammonia was 19.4 mg NH4-N removed/L,h.
The highest concentration of nitrite of 8 mg/L was determined after two hours of nitrification,
when all the NH4-N was converted to NO3-N and NO2-N (Figure 1) and the pH of the lowest
point is reached, known as "ammonium valley" (7, 6). This "valley ammonia" pH profile can
be used as an indicator of the end of nitrification - accumulation of nitrite. For a further three
hours of aeration nitrite is oxidized to nitrate, and the pH is slowly started to rise (7.8 and 7.9),
(Figure 2). It was observed a decrease of pH during nitrification due to reduced buffering
capacity as well as reaching the lowest value of pH in point of nitrification and dissolved
oxygen. These profiles of pH (decrease of pH during nitrification due to reduced buffering
capacity as well as reaching the lowest pH in point of nitrification) and dissolved oxygen
(oxidation of ammonia during the process of low dissolved oxygen concentrations and a
progressive increase in dissolved oxygen concentration when ammonia is almost completely
oxidized) during the removal process nitrogen described by other authors (Chang & Hao,
1996; Paul et al. 1998).
Experiment alternating nitrification/denitrification was carried out at an initial concentration
of NH4-N 70 mg/L NO3-N 4.9 mg/L and COD 205 mg O2/L, with the addition of NaAc in a
ratio C:N=1:1 (Figure 3 and 4). Oxy/anoxia conditions during the process of alternating
nitrification/denitrification maintained by the dynamics: 0.5 hours of anoxia conditions, one
hour of oxy conditions, 0.5 hours of anoxia conditions, then again oxy conditions. In the
experiment was added sodium acetate at a ratio of C:N= 1:1 as the source of the carbon for
denitrification. Oxy conditions are achieved airing content in the reactor (air intake) and
denitrification is carried out in conditions without ventilation (auto aeration) but stirring the
contents of the reactor (by using the mixer). In experiments is added municipal wastewater.
During the first 0.5 hours of anoxic conditions increases the pH and reduces the concentration
of organic substances, expressed as COD value (see Figures 3 and 4). During denitrification
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reduces the concentration of NO3-N and slightly decreases the concentration of NH4-N (see
Figures 3 and 4). The concentration of dissolved oxygen in the denitrification ranged was
from 1.9 ± 0.2 mg/L. After completing the first stage of denitrification (0.5 hours anoxia
conditions) the aeration is included and under the oxy conditions nitrification is carried out for
one hour. In doing so, it reduces the pH value with the accumulation of NO3-N and NO2-N.
Then follows the second denitrification, which caused a significant reduction in COD values.
And this follows the denitrification reduction of NO3-N and a slight decrease in residual NH4N (see Figures 3 and 4). Denitrification again accompanied by an increase in pH (Figure 3).
After finishing second denitrification, aeration was included and conducted the experiment
nitrification. Over the next two and half hours, a process of nitrification was through
accumulation of NO3-N and NO2-N in the first three and a half hours the process, followed
by further aeration oxidation of NO2-N to NO3-N. In these experiments of nitrification it was
observed a decrease in pH value, which achieved the lowest value in the point of nitritation,
after which the pH value increases slightly by the end of the process. COD value does not
change significantly during the process of nitrification. In the experiment of alternating
nitrification/denitrification, dissolved oxygen concentration is reached 2 mg O2/L during the
first half hour of anoxia conditions; 2.6 mg O2/L during the first hour of the oxy conditions
and 2.2 mg O2/L in the next half hour anoxia conditions. During the last phase of nitrification
in this experiment, there was a slight increase in the concentration of dissolved oxygen
(Figure 3). Rate of oxidation of ammonia in the experiment alternating
nitrification/denitrification is 11.95 NH4-N/L,h. Rate of accumulation of nitrate in the
experiment alternating nitrification/denitrification was 2.2 mg NO3-N/L,h during all phases of
the observed processes. The experiment of removing substances with nitrogen from municipal
wastewater was carried out with a previously prepared mixed microbial culture and municipal
wastewater. NH4-N concentration is reached 147 mg/L (see Figures 5 and 6). Complete
nitrification was achieve d for six hours. In this work the oxidation of the ammonia is
achieved for five hours, and to the accumulation of nitrate and nitrite. Extended aeration for
one hour nitrite is completely converted into nitrate. The rate of removal of ammonia was
28.82 mg NH4-N/L, h. The highest concentration of nitrite was 5.5 mg/L. In the fifth hour all
the NH4-N is converted to NO3-N and NO2-N. The concentration of dissolved oxygen in the
course of these experiments (Figure 5) shows a pronounced oxygen consumption during the
oxidation of NH4-N with accumulation and NO3-N and NO2-N. Shortly after graduating
nitritation (accumulation of nitrite) concentration of dissolved oxygen begins to grow until the
end of the experiment. After complete nitrification concentration of NO3-N amounted 11.1
mg/L The experiment was conducted under conditions of temperature 26±2. Concentration of
organic ingredients is expressed as COD value, and the speed of decomposition of organic
substances, expressed as COD value was 22.16 mg/L,h. Concentration of sludge dry matter
amounted to 3.5 g/L.
All previous nitrification processes were carried out under aerobic conditions. After nitrite
nitrogen completely oxidized, or after six hours passed into nitrate nitrogen, experiment was
set out to investigate the ability of microbial cultures for the implementation of denitrification.
Denitrification was carried out under anaerobic conditions, only stirring. Parameters were
monitored every three hours, and 24 hours. Dry matter was 3 g/L. The concentration of NH4N during denitrification process has not changed, and amounted to 0 mg/L. The concentration
of nitrite and nitrate is reduced during the process of denitrification. Nitrates are from the
initial 11.3 mg/L after 24 hours of completely oxidized to nitrogen gas. Dissolved oxygen is
consumed in the process of denitrification, and after 24 hours the dissolved oxygen
concentration was 0.7 mg/L. The process of denitrification, nitrate reduction, follow the
increase in pH. The pH of the initial value of 8.1 after 24 hours the process was 9.3. Speed
degradation of organic substances, expressed as COD value was 1.95 mg/L,h (see Figures 7
and 8).
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CONCLUSION
Based on the obtained results and conducting discussion may be adopted the following
conclusions:
Biological processes with activated sludge achieved very efficiently removal of
nitrogen from wastewater.
Wastewater investigated in this work is a municipal wastewater in which the
ingredients are organic biodegradable, as evidenced by the results of research.
The activated sludge from the WWTP (wastewater treatment plant), which is used
in research, with technique of accumulation nitrificants and denitrificants, was
prepared as a mixed microbial culture that has the ability to process simultaneous
nitrification and denitrification of nitrogen compounds in municipal wastewater.
Removal of nitrogen from wastewater is achieved by the process of denitrification,
where the process must ensure the existence of anoxic conditions. Many studies
have confirmed that controled nitrogen in the used water can be achieved in the
most efficient processes with a combined nitrification and denitrification
(Stefancic, 2003, Dong et al. 2006).
In the experiment of heterotrophic nitrification, with addition of sodium acetate as
an external carbon source at a ratio of 2:1 and a pH of 7.8, the rate of oxidation of
ammonia was 16.4 mg NH4-N removed/L,h.
Rate of oxidation ammonia in the experiment alternating nitrification/denitrification
amounted to 11.95 mg NH4-N/L,h.
Mixed culture has shown the ability for a higher degree of nitrification at higher pH
values from 7.7 to 8.8 and a temperature of 27-30°C in municipal wastewater in
which is presented ammonia nitrogen source.
REFERENCES
APHA (1998). Standard Methods for the Examination of Wastewater and Wastewater Treatment. 20. Edition
American Public Health Association. American Water Works Association and Water Pollution Control
Federation, Washington, D.C.
Gerardi, M. H. (2002). Nitrification and Denitrification in the Activated Sludge Process. New York: John Wiley
& Sons, Inc.
Henze, M., Harremoës, P., La Cour Jansen, J., Arvin, E. (2002). Wastewater Treatement. Biological and
Chemical Processes. 3. Ed. pp 89-108.
Jeyanayaga, S. (2005). True Confessions of the Biological Nutrient Removal Process. Florida Water Resources
Journal. pp 37-46.
Mesquita, D.P., Dias, O., Amaral, A.L., and Ferreira, E.C. (2009). Monitoring of activated sludge settling ability
through image analysis: validation on full-scale wastewater treatment plants. Bioprocess and Biosystems
Engineering Vol. 32 Issue 3, pp 361–367.
Metcalf & Eddy (2003). Wastewater Engineering - Treatment and Reuse. 4th edition. New York: McGraw-Hill.
pp 60, 749.
Wang, K. (2012). Enhanced Biological Nitrogen Removal by Increasing Wastewater Temperature in An
Activated Sludge System. Industrial Ecology, Royal Institute of Technology. Stocholm. pp 3–16.
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Title
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REMOVAL OF NITROGEN FROM MUNICIPAL WASTEWATER - THE EFFECT OF THE ADDITION OF CARBON SOURCES ON BIOLOGICAL DENITRIFICATION
Author
Author
IBRAHIMPAŠIĆ, Jasmina
TOROMANOVIĆ, Merima
LANDEKA DRAGIČEVIĆ, Tibela
Abstract
A summary of the resource.
In this work was used activated sludge from the WWTP (wastewater treatment plant), in which with technique accumulation nitrificants and denitrificants, were prepared mixed bacterial cultures which showed the ability nitrification of ammonia- nitrogen to nitrate, as well as the ability of denitrification of nitrate nitrogen to gaseous nitrogen in municipal wastewater. As carbon source in the process of biological denitrification was used sodium acetate, in the ratio C/N=1 and C/N=2. Activity of mixed microbial cultures for removal components with nitrogen was determined by measuring the concentration of organic matter, expressed as COD, ammonia-nitrogen, nitrite, nitrate, pH, concentration dissolved oxygen, and the concentration of microbial biomass. Keywords: municipal water, activated sludge, nitrogen removal
Publisher
An entity responsible for making the resource available
International Burch University
Date
A point or period of time associated with an event in the lifecycle of the resource
2014-05-15
Keywords
Keywords.
Article
PeerReviewed
Identifier
An unambiguous reference to the resource within a given context
ISSN 978-9958-834-36-3
Q Science (General),QH301 Biology,QH426 Genetics
-
https://omeka.ibu.edu.ba/files/original/7324bad9a16b4b70a427bb9766ef51ee.pdf
b5f13e0e906d367b98795b97b4a90c2f
PDF Text
Text
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EFFECTS OF VEGETABLE AND ANIMAL FAT ENRICHMENT IN BROILER
FEED ON CONTENT OF FATTY ACIDS IN WHITE AND RED MEAT
Suzana Jahić , Halid Makić, Mirsad Veladžić
Biotehnical Faculty, University of Bihac, Bihac, Bosnia and Herzegovina
e-mail: halid_btf@yahoo.com
ABSTRACT
In order to gain a more complete insight into the effects of vegetable and animal fat
enrichment in broiler feed on content of fatty acids in meat, an experimental research has been
conducted on 240 Cobb 500female broilers, divided into four separate treatments of 60
broilers each. The experiment was conducted in the period of 42 days. During that period, the
first group of broilers was fed with 3% pork fat enriched feed – treatment 1, second group was
fed with 3% soy oil enriched feed – treatment 2, third group with 3% bovine tallow –
treatment 3, and fourth group with 3% sunflower oil – treatment 4. The content of fatty acids
in red and white broiler meat was determined by the gas chromatography method. The content
of saturated fatty acids in the red meat was not of statistical significance (p>0.05), the content
of monounsaturated fatty acids was of statistical significance (p<0.05), while the content of
polyunsaturated fatty acids in the red broiler meat was of high statistical significance (p<0.01)
with reference to the applied feeding treatments. The content of saturated fatty acids in the
white meat was not of statistical significance (p>0.05), while the content of monounsaturated
and polyunsaturated fatty acids in white broiler meat was of high statistical significance
(p<0.01) with reference to the applied feeding treatments. The n-6/n-3 fatty acids ratio in red
broiler meat was determined as follows: treatment 1 - 19.3:1; treatment 2 - 16.0:1; treatment 3
- 20.5:1; treatment 4 - 12.9:1. The n-6/n-3 fatty acids ratio in white broiler meat was:
treatment 1 - 20.3:1, treatment 2 –16.1:1, treatment 3 –17.6:1 and treatment 4 –12.2:1.
Keywords: broiler meat, sunflower oil, vegetable fat, animal fat, fatty acids content
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INTRODUCTION
Birds generally have a high capacity for lipid biosynthesis (Klasing, 1998) including modern
broilers or meat of chickens that have a tendency to accumulation of excess fat. This
accumulation of body fat in broiler chickens, which is also an important source of fats in the
human diet, has a significant impact on human health.
Many studies connected the selection of chickens with the tendency of reduction of
accumulation of triacylglycerol as well as the ability to produce changes in the composition in
triacylglycerol due to a modification in the dietary intake of lipids (Leskanich & Noble, 1997).
The aim of the current studies was to improve the intake of polyunsaturated fatty acids
through diet in order to achieve favorable ratio n-6 fatty acids towards n-3 fatty acids.
Nutritional studies on humans have shown that we can manipulate with composition of body
fats with changing of intakes of the polyunsaturated fatty acids towards saturated fatty acids
in the diet, especially with intakes of long-chain polyunsaturated fatty acids in the diet (Field
at al. 1990, Pan at al. 1994, Luo at al. 1996, Couet at al. 1997). The enrichment of chicken
meat with the essential linoleic and linolenic acid is possible when as a food additive
sunflower oil and soya oil are used instead of lard (Božić, 1997).
Mehmet et al. (2005) analyzed the effects of different sources of fats such as soybean oil,
chicken fat, tallow on fatty acid content of abdominal fats and content of fatty acids in white
and red meat in broiler chickens. They found low content of total monounsaturated fatty acids
in the white meat in broilers that they were feeding with supplemented soybean oil. Linoleic
acid C18: 2n-6 was concentrated in the red meat, in the abdominal fat and in the white meat
in broilers that they were feeding with supplemented soybean as well as in the red meat in
broilers that they were feeding with supplemented chicken fat. Crespo & Esteve-Garcia (2001)
used in the nutrition of female broilers addition of beef tallow, olive oil, sunflower oil and
flaxseed oil. Broilers, being were fed with diet adding beef tallow, had high values of
saturated acids, mainly of myristic, palmitic and stearic acid as compared to broilers were fed
with the addition of olive oil, sunflower oil or linseed oil. They found higher levels of
arachidonic acid C20: 4n-6 and of the fatty acids of the n-6 series in broilers that were fed
with the addition of sunflower oil, except in abdominal fat. A higher level of eicosapentaenoic
acid C 20:5 n-3 and docosahexaenoic acid C22: 6 n - 3 were found in the red and white meat
of broiler chickens that were fed with an addition of flaxseed oil, whereas in abdominal fat
these fatty acids were not measurable.
Veladžić et al. (2010) determined a statistically significant difference (p <0.01) for the
cholesterol content in blood plasma between the observed treatments, therewith the higher
cholesterol content was determined for the treatments in which were added animal fats in
relation to treatments in which were added vegetable fats.
Kirshgessner at al. (1993) have found the enhancement contents of crude fat in the white meat
of broilers which received in their nutrition higher percent of linoleic acid. Chickens fed with
low-protein food (18% crude protein) supplemented with the oil enriched with 2% or 4%
conjugated linoleic acid had low triglycerides of liver, a relatively high concentration of
saturated fatty acids and relatively low concentration of monounsaturated fatty acids in lipids
of liver and adipose tissue than chickens fed without the addition of conjugated linoleic acid.
Chickens fed with low-protein food without the addition of conjugated linoleic acid had
higher concentrations of triglycerides in the liver than chickens fed with high-protein food
(23% crude protein) without the addition of conjugated linoleic acid (Aletor et al. 2003).
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MATERIAL AND METHODS
The experiment was set up and implemented in the facilities for the production of chicken
meat “Koka – Sana” from Sanski Most. Laboratory samples of chicken meat were performed
at the Biotechnical Faculty, University of Bihać.
Day-old Cobb 500 broiler hybrid was placed in four separate boxes (treatments), and there
were 60 broilers in each of them. All chickens were held on the floor in facilities fitted for
broiler breeding. During the experiment, which lasted for 42 days, temperature, humidity and
lighting were regularly controlled. Chicken breeding was split in two periods. From day one
to day 15, chickens were bred with the initial mixture containing approximately 23% of
proteins. From day sixteen to 42, they were bred with the final mixture containing
approximately 20% of proteins, so the final mixtures were isoproteinic and isoenergetic. In
chickens’ nutrition, there was increased content of fats by 3% (treatment I – lard, treatment II
– soybean oil, treatment III – tallow, and treatment IV – sunflower oil). The chickens
consumed food and water ad libitum. Having turned 42 days of life, chickens were marked
with rings, for each treatment separately, and after 12 hours of fasting were killed at
slaughterhouse facilities.
After slaughter and meat packing processing of chicken carcasses, the carcasses are chilled to
a temperature of 0-4 ° C and then frozen at -18 °C until the moment of analysis, and on the
day of analysis thawed to room temperature.
We used six broilers per each treatment for the determination of fatty acids in the red and
white meat. Meat samples were analyzed in the laboratory BiotechLab, Sremska Kamenica,
Serbia. Preparation of fatty acid methyl esters was performedby the method EN ISO550:2007,
and determination of fatty acid methyl esters was performed by gas chromatography method:
JUSISO5508:2002.
The results obtained in the experiment were analyzed by ANOVA test and found differences
were analyzed using Tukey’s test.
Table 1. shows the contents of nutrients in the broilers’ feeding.
Table 1. Contents of the mixtures used for feeding broilers
from 0. to 15.days of their lives and from 16. to 42.days of their lives
Nutrients %
Experimental group
I/lard
Corn
Soybean shot
Sunflower shot
Lard
Soybean oil
Tallow
Sunflower oil
Premix/s-starter,
f- finisher
II/soybean oil
III/tallow
IV/sunflower oil
0-15
15-16
0-15
15-16
0-15
15-16
0-15
15-16
53.5
38.0
1.5
3.0
4.0s
58.5
33.0
1.5
3.0
4.0f
53.5
38.0
1.5
3.0
4.0s
58.5
33.0
1.5
3.0
53.5
38.0
1.5
3.0
4.0s
58.5
33.0
1.5
3.0
4.0f
53.5
38.0
1.5
3.0
4.0s
58.5
33.0
1.5
3.0
4.0f
4.0f
Premix of starter: lysine 2.34 %; methionine 4.17%; methionine + cystine 4.17%; robenidine
825 mg/kg, vitamin A 275000.00 IU/kg; vitamin D3 125000.00 IU /kg; Vitamin E 1250.00
IU/kg; Premix of finisher: methionine 3.36%; methionine + cystine 3.36%; Vitamin A
314600.00 IU/kg; vitamin D3 114400.00 IU /kg; Vitamin E 1430.00 IU/kg
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RESULTS AND DISCUSSION
In the Tables 2. and 3. are shown the contents of fatty acids in the red and in the white meat.
Table 2. Contents of fatty acids in the red meat of broilers
C 14:0
X
SD
CV
C 16:0
X
SD
CV
C 16:1
X
SD
CV
C 18:0
X
SD
CV
C:18n9c
X
SD
CV
C18:2 n6c
X
SD
CV
C18:3n3
X
SD
CV
C20:0
X
SD
CV
Treatment 1
0.75B
Contents of fatty acids (%)
Treatment 2
Treatment 3
0.60D
0.77A
F value
Treatment 4
0.67AC
0.05
0.07
Treatment 1
24.83
0.08
0.14
Treatment 2
23.78
0.02
0.03
Treatment 3
25.92
0.08
0.12
Treatment 4
24.91
0.56
0.02
Treatment 1
6.15
8.94
0.38
Treatment 2
4.23
1.17
0.05
Treatment 3
5.67
0.36
0.01
Treatment 4
4.84
1.73
0.28
Treatment 1
6.42
0.86
0.20
Treatment 2
7.16
0.18
0.03
Treatment 3
6.81
0.35
0.07
Treatment 4
6.78
0.74
0.12
Treatment 1
37.98
0.73
0.10
Treatment 2
34.26
0.02
0.003
Treatment 3
38.47
0.29
0.04
Treatment 4
34.82
0.73
0.02
Treatment 1
22.55AB
0.73
0.02
Treatment 2
28.07D
2.81
0.07
Treatment 3
23.21AC
0.72
0.02
Treatment 4
25.82A
1.36
0.06
Treatment 1
1.17DA
1.70
0.06
Treatment 2
1.75BC
1.13
0.05
Treatment 3
1.21CA
0.99
0.04
Treatment 4
1.99ABD
0.07
0.06
Treatment 1
0.23ADC
0.15
0.08
Treatment 2
0.15DB
0.11
0.09
Treatment 3
0.20B
0.19
0.10
Treatment 4
0.16C
0.02
0.11
0.02
0.13
0.05
0.23
0.04
0.25
17.000**
2.680
NS
2.306
NS
0.971
NS
2.640
NS
11.442**
30.750**
28.571**
Treatment 1-addition of 3% lard; Treatment 2-addition of 3% soybean oil; Treatment 3addition of 3% tallow; Treatment 4-addition of 3% sunflower oil
F – values of Fisher test, X - mean value, SD – standard deviation, CV – coefficient of
variation, NS – Inside examined treatments did not establish significant difference (p>0.05)
** Highly significant difference (p<0.01) between treatments, *significant difference (p<0, 05)
between treatments
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Table 3. Contents of fatty acids in the white meat of broilers
C 14:0
X
SD
CV
C 16:0
X
SD
CV
C 16:1
X
SD
CV
C 18:0
X
SD
CV
C:18n9c
X
SD
CV
C18:2 n6c
X
SD
CV
C18:3n3
X
SD
CV
C20:0
X
SD
CV
Contents of fatty acids (%)
Treatment 1
Treatment 2
Treatment 3
1.04ADC
0.63DB
0.93B
Treatment 4
0.69C
F value
0.10
0.10
Treatment 1
26.19b
0.04
0.07
Treatment 2
25.34c
0.14
0.15
Treatment 3
28.28ad
0.05
0.07
Treatment 4
24.18d
1.62
0.06
Treatment 1
5.71BA
1.30
0.05
Treatment 2
5.10CA
0.83
0.03
Treatment 3
7.74AD
1.33
0.06
Treatment 4
4.92D
0.72
0.13
Treatment 1
6.80
0.44
0.09
Treatment 2
6.83
0.31
0.04
Treatment 3
5.87
0.49
0.10
Treatment 4
6.92
0.81
0.12
Treatment 1
36.53ad
0.18
0.03
Treatment 2
34.36db
0.27
0.05
Treatment 3
36.11b
0.20
0.03
Treatment 4
35.44c
0.16
0.004
Treatment 1
20.52C
0.51
0.01
Treatment 2
25.98AD
0.47
0.01
Treatment 3
17.13DB
1.03
0.03
Treatment 4
25.58B
2.36
0.11
Treatment 1
1.01CBA
0.38
0.01
Treatment 2
1.61BDA
0.63
0.04
Treatment 3
0.97DA
1.83
0.07
Treatment 4
2.09A
0.06
0.06
Treatment 1
2.53BDC
0.09
0.06
Treatment 2
0.16DA
0.07
0.07
Treatment 3
2.96AC
0.15
0.07
Treatment 4
0.17C
0.52
0.21
0.01
0.06
0.19
0.06
0.04
0.25
19.661**
5.366*
18.280**
3.756
NS
7.482*
21.894**
99.651**
96.145**
Treatment 1-addition of 3% lard; Treatment 2-addition of 3% soybean oil; Treatment 3addition of 3% tallow; Treatment 4-addition of 3% sunflower oil
F – values of Fisher test, X - mean value, SD – standard deviation, CV – coefficient of
variation, NS – Inside examined treatments did not establish significant difference (p>0.05)
** Highly significant difference (p<0.01) between treatments, *significant difference (p<0, 05)
between treatments
The content of saturated fatty acids in the red meat was not of statistical significance (p>0.05),
the content of monounsaturated fatty acids was of statistical significance (p<0.05), while the
content of polyunsaturated fatty acids in the red broiler meat was of high statistical
significance (p<0.01) with reference to the applied feeding treatments. The content of
saturated fatty acids in the white meat was not of statistical significance (p>0.05), while the
content of monounsaturated and polyunsaturated fatty acids in white broiler meat was of high
statistical significance (p<0.01) with reference to the applied feeding treatments. The n-6/n-3
fatty acids ratio in red broiler meat was determined as follows: treatment 1 - 19.3:1; treatment
2 - 16.0:1; treatment 3 - 20.5:1; treatment 4 - 12.9:1. The n-6/n-3 fatty acids ratio in white
broiler meat was: treatment 1 - 20.3:1, treatment 2 –16.1:1, treatment 3 –17.6:1 and treatment
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4 –12.2:1. Mehmet et al. (2005) added to broilers feeding 6% fats in the period from 21.to
41.days of their lives. They found the levels of 42.14%, 29.66%, 24.15%, saturated,
monounsaturated and polyunsaturated fatty acids respectively in the red meat of chickens
feeding with addition of soybean oil and the levels of 48.02%, 24.61%, 22.11% saturated,
monounsaturated and polyunsaturated fatty acids respectively in the red meat chickens
feeding with the addition of beef tallow. In the white meat of broilers feeding with addition of
soybean oil, they found 43.58%, 20.03%, 30.58%, saturated, monounsaturated and
polyunsaturated fatty acids respectively and in the white meat of chickens feeding with
addition of beef tallow 48.02%, 24.61%, 30.58% saturated, monounsaturated and
polyunsaturated fatty acids respectively. Popescu and Criste (2003) used addition of soybean
oil in broiler’s feeding and found the content of fatty acids in the red meat of broiler’s at the
end of the fattening period: 26.29% saturated fatty acids, 73.41% monounsaturated and
polyunsaturated fatty acids.
CONCLUSION
The dietary treatments used in feeding broilers can significantly affect the amount of fatty
acids in the red and white meat of broilers. The highest contents of polyunsaturated fatty acids
in the red broiler meat were achieved with the addition of soybean oil in the mixture of food.
The highest contents of polyunsaturated fatty acids in the white broiler meat was achieved
with the addition of sunflower oil in the mixture of food and it was shown that the addition of
soybean oil and sunflower oil affects the increasing of polyunsaturated fatty acids in the meat
of broilers.Therefore the recommendation would be that in the nutrition of broilers vegetable
supplements should be used, especially sunflower oil, because it considerable reduces the
ratio n-6 fatty acids towards n-3 fatty acids in the meat and thus it has more favorable effect
on the human body.
REFERENCES
1. Aletor, V.A., Eder, K., Becker, K., Paulicks, B.R., Roth, F.X. and Roth-Maier, D.A. (2003). The effect of
conjugated linoleic acids or an alpha glycosidase inhibitor on tissue lipid concentrations and fatty acid
composition of broiler chicks fed a low-protein diet. Poult Sci. 82:796-804.
2. Božić, A. (1997). Uticaj porekla masnih kiselina hrane na masnokiselinski sastav i aterogeni potencijal
mišićnog i masnog tkiva tovnih pilića. Doktorska disertacija. Poljoprivredni fakultet. Novi Sad.
3. Crespo, N. and Esteve-Garcia, E. (2001). Dietary fatty acid profile modifies abdominal fat deposition in
broiler chickens. Poult.Sci. 80: 71 - 78.
4. Couet, C., Delarue, J., Ritz, P., Antoine, J.M., and Lamisse, F. (1997). Effect of dietary fish oil on body fat
mass and basal oxidation in healthy adults. International Journal of Obesity. 21: 637–643.
5. EN ISO 550:2007: Preparation of fatty acid methyl esters.
6. Field, C.J., Edmond, A.R., Thompson, A.B.R., and Clandinin M.T. (1990). Diet fat composition alters
membrane phospholipid composition, insulin binding, and glucose metabolism in adipocytes from control and
diabetic animals. Journal of Biological Chemistry. 265: 1143–1150.
7. JUS ISO 5508:2002: Determination of fatty acid methyl esters
8. Kirchgessner, M., Ristic, M., Kreuzer, and M., Roth, M.F.X. (1993). Inclusion of fats with high quantities of
free fatty acids in broiler diets. 2. Growth as well as quality of carcass, meat and fat as affected by the stepwise
substitution of saturated by unsaturated fatty acids. Arch. Geflu gelk. 57: 265–274.
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9. Klasing, K.C. (1998). Comparative Avian Nutrition. Wallingford, Oxon: CAB International.
10. Leskanich, C.O. and Noble, M.P. (1997). Manipulation of the n-3 polyunsaturated fatty acid composition of
avian eggs and meat. World’s Poult. Sci. J. 53:155-183.
11. Luo, J., Rizkalla, S.W., Boillot, J., Alamowitch, C., Chaib, H., Bruzzo, F., Desplanque, N., Dalix , A.M.,
Durand, G., and Slama, G. (1996). Dietary (n-3) polyunsaturated fatty acids improve adipocyte insulin action
and glucose metabolism in insulin-resistant rats: relation to membrane fatty acids. Journal of Nutrition. 126:
1951–1958.
12. Mehmet Azman, A., Ibrahim Cerci, H., and Nurgül Birben, M. (2005). Effects of various dietary fat sources
on performance and body fatty acid composition of broiler chickens. Turk. J. Vet. Anim. Sci. 20: 811-819.
13. Pan, D.A., Hulbert, A.J., and Storlien, L.H. (1994). Dietary fats, membrane phospholipids and obesity,
Journal of Nutrition. 124: 1555–1565.
14. Popesku, A. and Criste, R. (2003). Using full fat soybean in broilers diets and its effect on the production and
economic efficiency of fattening, Journal of Central Europian Agriculture. 4:No 2: 167-174.
15. Veladžić, M., Jahić, S., Makić, H. and Galijašević, E.(2010). Analysis of the effects of vegetable and animal
fats on lipids and cholesterol contents in broilers' plasma, 5th Central European Congress on Food, 19th-22nd May
2010, Bratislava, Slovak Republik, Book of full papers.p:205.
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EFFECTS OF VEGETABLE AND ANIMAL FAT ENRICHMENT IN BROILER FEED ON CONTENT OF FATTY ACIDS IN WHITE AND RED MEAT
Author
Author
JAHIĆ, Suzana
MAKIĆ, Halid
Veladžić, Mirsad
Abstract
A summary of the resource.
In order to gain a more complete insight into the effects of vegetable and animal fat enrichment in broiler feed on content of fatty acids in meat, an experimental research has been conducted on 240 Cobb 500female broilers, divided into four separate treatments of 60 broilers each. The experiment was conducted in the period of 42 days. During that period, the first group of broilers was fed with 3% pork fat enriched feed – treatment 1, second group was fed with 3% soy oil enriched feed – treatment 2, third group with 3% bovine tallow – treatment 3, and fourth group with 3% sunflower oil – treatment 4. The content of fatty acids in red and white broiler meat was determined by the gas chromatography method. The content of saturated fatty acids in the red meat was not of statistical significance (p>0.05), the content of monounsaturated fatty acids was of statistical significance (p<0.05), while the content of polyunsaturated fatty acids in the red broiler meat was of high statistical significance (p<0.01) with reference to the applied feeding treatments. The content of saturated fatty acids in the white meat was not of statistical significance (p>0.05), while the content of monounsaturated and polyunsaturated fatty acids in white broiler meat was of high statistical significance (p<0.01) with reference to the applied feeding treatments. The n-6/n-3 fatty acids ratio in red broiler meat was determined as follows: treatment 1 - 19.3:1; treatment 2 - 16.0:1; treatment 3 - 20.5:1; treatment 4 - 12.9:1. The n-6/n-3 fatty acids ratio in white broiler meat was: treatment 1 - 20.3:1, treatment 2 –16.1:1, treatment 3 –17.6:1 and treatment 4 –12.2:1. Keywords: broiler meat, sunflower oil, vegetable fat, animal fat, fatty acids content
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International Burch University
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2014-05-15
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ISSN 978-9958-834-36-3
Q Science (General),QH301 Biology,QH426 Genetics
-
https://omeka.ibu.edu.ba/files/original/307b42c3cef861414e1001eb3eebaf07.pdf
3746e6851ad3367f90753ff42b7cf43b
PDF Text
Text
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MULTI-RESOLUTION WAVELET ANALYSIS FOR FAULT DETECTION
Zeynep Kara1, Serhat Seker2
1
International Burch University, Bosnia and Herzegovina
2
Istanbul Technical University, Turkey
Abstract
In this study, a multi-resolution wavelet analysis technique is applied to simulation data for
fault detection. Data is simulated at the MATLAB environment. For this purpose, a sinusoidal
wave form is generated at around 1 kHz sampling frequency and then a faulty case is
simulated between 250- 500 Hz using a random process under the band-pass filtering. Hence
data and its noisy form are used to show healthy and faulty cases of any physical system
respectively. In order to show the fundamental properties of the data set, power spectral
density variations are shown to indicate the availability of the data. After that Multi–
Resolution Wavelet Analysis (MRWA) is applied to each case. In general, wavelet transform
is a time-scale analysis technique which can be accepted as an alternative method to the
Fourier transform. However, in this study, MRWA approach is considered. MRWA is a kind
of the discrete wavelet transform and it uses filter banks approach. Hence, the time domain
properties are shown in the sense of the statistical parameters. Also, calculating the power
spectral densities, this comparison is done in frequency domain. With this way, a faulty case
and its some properties can be determined at both of the time and frequency domains.
Key Words: Wavelets, Filtering, Sub-band analysis, Fault detection
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Introduction
Anomaly is an unwanted transient case in the system which occurs in very short time in the
signal and can be detected from the signal characteristics. Anomalies in data can be translated
to significant information in a wide variety of application domains for this reason; this
translation method can be named as anomally detection in general. Detection of outliers or
anomalies were started to be studying in the 19th century (Edgeworth, 1887). And its results
can be very important in terms of the system reliability and economical operation of the some
critical systems related with energy production, space applicatons and so on.
Anomalies might be caused because of such a terrorist activity, credit card fraud, cyberterrorism, malicious threats or breakdown of a system, e.g. Noise removal (Teng, Chen and
Lu, 1990) and noise accommodation (Rousseeuw and Leroy, 1987) are deal with unwanted
noise and related with anomaly detection(Chandola, Banerjee and Kumar, 2009). Noisy data
considered is as an obstacle to analysis and that is the reason why it is of interest to analysts,
meaning that they are responsible to clean the data before analysis in order to get useful
information out of them.
Noise reduction is necessary before any data analysis is performed on the data to wipe out the
unwanted objects. Towards anomalous observations, noise accommodation mentions about
self-defense of a new model of estimation (Huber, 1974). Novelty detection (Markou and
Singh, 2003; Saunders and Gero, 2000) whose goal is to detect previously unrealized
(emergent, novel) patterns in the data, is also related with anomaly detection. Not being added
into the initial model after detection is the main difference of novel patterns and anomalies.
Another research on signal and noise separation in time series is studied by Khelifa,
Kahlouche and Belbachir (2012). Two approaches are used to check the noises which are the
wavelet transform in the frequency space and the Singular Spectrum Analysis (SSA) in the
phase space. By this process the main goal is extracting the noise from signals and wavelet
analysis is found as more rapid and direct for the determination of noise.
In this paper we dealed with these problems and it is prepared to provide a structured and
comprehensive overview of the research on anomaly detection with the artificial data
generation in MATLAB environment. There are various methods to detect the anomaly
according to the signal in the data. Under the assumptions to be considered in this paper:
The Linear sytems provide the super-position principle and most simple case of the signals/
sytems can be accepted as linear time-invariant signals. Deterministic signals can be defined
by analytical functions, Random Signals can be defined by means of the probability
distribution functions using the random variable concept. Any anomally case, which will
occur in the system, can be detected from the signal characteristics.For this purpose, there are
so many mathematical approaches. In this area, several methods can be shown by the
following items :
1.
2.
3.
4.
Statistical Calculations
Spectral Analysis methods like FourierTransform
Time-Frequency analysis like Short-Time Fourier Transform
Time-Scale analysis like Wavelet transform.
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In this study, we considered linear, deterministic/Random, non-stationary signal types and
we used short-time fourier transform based on time frequency domain and wavelet analysis
as an anomaly detection techniques. Wavelet methods facilitate to zoom into the details and
draw a comprehensive picture of the time series in different scales. It provides to detect and
isolate the anomalies. The failure or fault detection methods are similar with the anomaly
detection methods, and also, they can be described as a transient case which occurs in very
short time in the signal. For this reason, it can be named as anomally detection in general. For
this purpose, we will produce deterministic signal like pure sinosoidal or any signal with
harmonics.
In terms of the simulation of the anomaly case, we used random signal characteristics and we
produced random number in standard normal distribution. After that changing the statistical
parameters or statistical properties of the randomness, we considered the different random
signal characteristics. Also, in terms of the frequency domain properties, we used the bandpass filters to generate the data in a special frequency band.
In this paper, there are two important aproaches. These are as folows:
1.
2.
Detection of the anomally
Isolation of the transient case.
From this view point, for the detection case, we considered the Fourier Transform based
applications like Short-Time Fourier Transform. In this manner, we tried to find the most
suitable technique for the non-stationary signals. Then the anomaly case was isolated from the
data by the Multi-Resolution Wavelet Analysis (MRWA). In this study we used Wavelet
analysis but a thorough presentation of Fourier analysis is provided as well. Because the
Fourier methods are an alternative for the wavelet methods and although there are different
methods of wavelets, all of them are based on Fourier analysis (Mallat, 1999).
Wavelet Transforms and Multi Resolution Analysis
Wavelets are functions are used to represent data or functions and satisfy certain mathematical
requirements. Thus the Wavelet transform can be used to decompose a signal into different
frequency components and then present each component with a resolution matched to its scale.
In the signal analysis framework, the Wavelet transform of the time varying signal depends on
the scale that is related to frequency and time. Hence, the Wavelets provide a tool for timefrequency localization. The main idea behind wavelets is to analyze according to scale.
Therefore, wavelet algorithms can process data at different scales or resolutions. This concept
of signal analysis is termed Multi-Resolution Analysis (MRA) and it makes the Wavelets
interesting and useful.
Wavelet Transforms
In 1909, Haar first mentioned about the wavelets which had a compact support means that
itvanishes outside of the finite interval, but Haar wavelets are not continuously differentiable.
Later wavelets are considered with an effective algorithm for numerical image processing by
an earlier discovered function that can vary in scale and can conserve energy when computing
the functional energy (Gabor, 1946). Between 1960 and 1980, mathematicians such as
Grossman and Morlet (1985) defined wavelets in the context of quantum physics. Mallat
(1989) gave a boost to digital signal processing by inventing the pyramidal algorithms, and
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orthonormal wavelet bases. Later Daubechies (1990) used Mallat’s work to construct a set of
wavelet orthonormal basic functions that are the cornerstone of wavelet applications today.
The class of functions that present the wavelet transform are those that are square integrable
on the real time. This class is denoted as L2 ( R )
(1)
The mother wavelet is scaled and translated in the wavelet analysis to generate the set of
functions.
The wavelet function ψ (x) ∈ L2 (R) consists of two parameters which vary continuously, they
are known as dilation (a) and translation (b). A wavelet basic functions a ,b ( x) is given as
a ,b ( x )
1
a
(
x b
)
a
a , b R; a 0
(2)
Here, the location of the wavelet in time is measured by the translation parameter, “b”. The
“narrow” wavelet can attain high frequency information, while the more widened wavelet can
attain low frequency information. Hence the parameter “a” differs for different frequencies.
The continuous wavelet transform is defined by
Wa ,b ( f ) f , a,b
f ( x) a ,b ( x)dx.
(3)
The wavelet coefficients are assigned as the inner product of the function that is transformed
with each basis function. Daubechies (1990) conceived one of the most sophisticated families
of wavelets, named Compactly Supported Orthonormal Wavelets, and are used in Discrete
Wavelet Transform (DWT). The scaling function is used to calculate the ψ in this approach. It
is defined by:
N 1
( x) ck (2 x k )
(4)
k 0
And its corresponding wavelet ψ (x) is defined by:
N 1
( x) (1)k ck (2 x k N 1),
(5)
k 0
Here N corresponds to an even number of wavelet coefficients ck,
k = 0 to N-1. Dilation and
translation of signal function ( x) provides the discrete representation of a wavelet basis of
L2 ( R ) which is orthonormal compactly supported. If we assume that to dilation parameters “a”
and “b” are assigned only discrete values:
where k , j ,
a0 1, and b0 0.
a a0 j , b kb0 a0 j ,
Than the wavelet function could be written as follows:
j ,k ( x ) a0 j / 2 ( a0 j x kb0 )
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And we have the Discrete-Parameter Wavelet Transform (DPWT) to be:
DPWT ( f ) f , j ,k
f ( x )a0 j / 2 (a0 j x kb0 )dx
(7)
In order to make the analysis efficient and accurate, the choice between dilations and
translations is made on the basis of the power of two. The frequency axis is divided into band
by using the power of two for the scale parameter ˝a˝ .
Considering samples at the dyadic values, we have b0 1 and a0 2 , so, the discrete wavelet
transform is
DPWT ( f ) f , j ,k
f ( x) 2 j /2 (2 j x k ) dx
(8)
and j ,k ( x ) is defined as
j , k ( x ) 2 j / 2 (2 j x k ),
j, k
(9)
Multi-resolution Analysis (MRA)
An efficient algorithm is introduced in1989 by Mallat which perform the DPWT known as the
Multi-Resolution Analysis(MRW).It is well known in signal processing area as the TwoChannel Sub-Band Coder.The MRA of L2 ( R ) consists of successive approximations of the
space V j of L2 ( R ) .A scaling function ( x) V0 exists such that j , k ( x) 2 j / 2 (2 j x k );
j, k Z
(10)
For the scaling function ( x ) V0 V1 , there is a sequence hk ,
( x) 2 hk (2 x k )
(11)
k
This equation is known as the two-scale difference equation. Furthermore, let us define W j as
a complementary space of V j in V j 1 , such that V j 1 V j W j and W j L2 ( R ). Since the
j
( x) is a wavelet and it is also an element of V0 , a sequence gk exists such that
( x) 2 g k (2 x k )
(12)
k
It is concluded that the multiscale representation of a signal f ( x) may be achieved in
different scales of the frequency domain by means of an orthogonal family of functions
( x) .Now, let us see how the function in V j is computed.The projection of the signal
f ( x ) V0 on V j defined by Pv f i ( x ) is given by
Pv f i ( x) c j ,k j , k ( x)
(13)
k
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Here, c j , k f , j , k ( x ) . Similarly, the projection of the function f ( x) on the subspace W j
is also defined by
Pv f i ( x) d j ,k j ,k ( x)
(14)
k
where d j,k f , j ,k ( x ) . Because V j V j 1 W j 1 , the original function f ( x ) V0 can be
rewritten as
J 1
f ( x) c j ,k j ,k ( x) d j ,k j ,k ( x) , J j0
k
j
(15)
k
The coefficients c j 1,k 2 hi 2 k c j , k
(16)
and
d j , k 2 g j 2 k c j ,k
(17)
i
j
The multiresolution representation is linked to Finite Impulse Response (FIR) filters. The
scaling function and the wavelet are obtained using the filter theory and consequently the
coefficients are also defined by the last two equations. If at x t / 2, F ( x) is considered
and
(18)
( x) H
2 2
As (0) 0, H (0) 1, this means that H ( ) is a low-pass filter. According to this result
(t ) is computed by the low-pass fitler .The mother wavelet (t ) is computed by defining
the function G ( ) so that
H ( )G * ( ) H ( )G * ( ) 0 .Here,
MRA solution.
G ( ) exp( j ) H * ( ).
and G ( ) are quadrature mirror filters for the
(19)
Substituting H (0) 1 and H ( ) 0, it yields G (0) 0 and G ( ) 1, respectively. This
means that G ( ) is a high-pass filter.As a result, the MRA is a kind of Two-Channel SubBand Coder used in the high-pass and low-pass filters, from which the original signal can be
reconstructed.
Wavelet Application on a Generated Data
In this paper, the artificial data generation in MATLAB environment is considered and
deterministic signal like pure sinosoidal is generated. Here we covered the Fourier Transform
based applications like Short-Time Fourier Transform and the Wavelet analysis in details.
Randomly chosen 10000 numbers (N=10000) are generated according to standard normal
distribution and we used Matlab for this purpose. Randomly selected numbers are used to
simulate the noisy signal. A sinusoid wavelet was generated as an artificial data that is formed
of the harmonics. The main frequency is 50 Hz, second and third frequencies are assigned
respectively as 100 Hz and 150 Hz. The signal, generation of these three frequency compound,
is expressed as the sum of sinus and a, b, c coefficients. The generated signal in this manner is
(5.1)
y A sin 2 f1t B sin(2 f 2t ) C sin 2 f 3t ,
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where f1 represents main frequency, f 2 and f 3 are respectively second and third harmonics.
A signal generation with noisy is carried out. The noisy signal, represented with randomly
numbers, is added with a known proportion (g coefficient) to the sinusoid signal that is
generated for this purpose. The sinusoid signal containing noise is represented with random
numbers, with a known proportion (g coefficient).
Fourier Transform is used for the spectral analysis of the generated noisy signal. Fourier
Transform is represented at PSD (Power Spectrum). Here the sampling frequency is selected
to be 1000 Hz (1 kHz). Figure 1 illustrates the changes on the PSD.
Using a Short Time Fourier Transform (STFT) the same noisy signal is calculated and
illustrated in a Figure 2. The STFT illustrates the signal compounds on the frequency plane.
The time- frequency plane is illustrated in Figure 2; the frequency plane is a normalized plane
and half of the sampling frequency 500Hz is symbolized by unit value. In Figure 2 frequency
components of the signal 50, 100, 150 Hz are illustrated as spread over time plane.
Power SpectralDensity-PSD
90
80
70
Amplitude
60
50
40
30
20
10
0
0
50
100
150
200
250
300
Frequency [Hz]
350
400
450
500
Figure 1: Spectral Analysis using PSD
1400
10
1200
0
1000
Time
-10
800
-20
600
-30
400
-40
200
0
0.2
0.4
0.6
0.8
Normalized Frequency ( rad/sample)
1
Figure 2 : Spectral Analysis using STFT
After this process, an anomaly signal is generated at random process and added to the noisy
signal that is generated previously. In the application a Butterworth band pass filter. İs used
and the bandwidth is taken between 200 and 250 Hz.. PSD for filter output is illustrated on
figure 3. As shown on the figures the generated anomaly case contains a random signal with
200-250 Hz. The signal at the output of the filter is the anomaly case between 200-250 Hz, on
the time-frequency plane it is illustrated on figure 4.
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Power SpectralDensity-PSD for filter output
1.5
Amplitude
1
0.5
0
0
50
100
150
200
250
300
Frequency [Hz]
350
400
450
500
Figure 3: PSD for filter output
0
1400
-10
-20
1200
-30
1000
Time
-40
800
-50
-60
600
-70
400
-80
-90
200
-100
0
0.2
0.4
0.6
0.8
Normalized Frequency ( rad/sample)
1
Figure 4 : Signal of anomaly (STFT of Filter Output)
After this step the anomaly case generated by the filtration is added on the previously
generated y signal (sinusoidal waveform) in order to generate another new noisy signal. The
difference between new noisy signal and the previous one is the anomaly case which is
generated by first band pass filter is illustrated on figure 5 and anomaly between 200-250 Hz
could be easily recognized.
Power SpectralDensity-PSD forfiltered noisy signal
70
60
Amplitude
50
40
30
20
10
0
0
50
100
150
200
250
300
Frequency [Hz]
350
400
450
500
Figure 5 : PSD for Noisy Signal under the Anomally
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Conclusion
In this paper, a Multi-Resolution Wavelet Analysis is used to detect the anomaly inside of the
signal and then to isolate that transient case from the signal. Here we covered the Wavelet
analysis in details as well as we did for the Fourier analysis. Main reason for covering both of
the methods is that Fourier methods are considered as an alternative for the wavelet methods.
For the detection case, we considered the Fourier Transform based applications like ShortTime Fourier Transform. It is a reperesentation of the signals in the time-frequency domain.
Hence the anomally case is shown in the time-frequency plane. In terms of the isolation of the
anomally case, we consiredered the multi-resolution wavelet analysis (MRWA). In this
method, time-scale reperesentations of the signals are used and scales are presented by the
low-pass filters (LPF) and High-Pass Filters (HPF) sequences. By sub-band analysis the
anomaly case is shown in a special sub-band and it is isolated from the other sub-bands. After
this isolation, the power spectral density (PSD) of the isolated sub-band is calculated and all
frequency domain properties are identified as well as its statistical properties.
References
Chandola V., Banerjee A. & Kumar V. (2009), Anomaly Detection, University Of Minnesota
Edgeworth, F. Y. 1887. On discordant
observations. Philosophical Magazine 23, 5, 364{375.
Daubechies, L.,1990. The Wavelet Transform, Time-Frequency Localization and Signal Analysis. IEEE Trans.
on Information Theory, 36
Gabor, D., 1946. Theory of Communications. J.IEEE, 93, 3, 429.
Huber, P. 1974. Robust Statistics. Wiley, New York.
Khelifa S., Kahlouche S., Belbachir M. F., 2012 Signal and noise separation in time series of DORIS station
coordinates using wavelet and singular spectrum analysis, Elsevier Masson SAS.
Mallat, S., 1989. A Theory for Multiresolution Signal Decomposition of the Wavelet Representation. IEEE
Trans. Pattern Anal. and Machine Intelligence, 31,679-693.
Mallat, S., 1999. A Wavelet Tour of Signal Processing. 2nd Edn., Academic Press, San Diego, California,USA..
Markou, M. and Singh, S. 2003. Novelty detection: a review-part 1: statistical approaches. Signal Processing 83,
12, 2481{2497.
Rousseeuw, P. J. and Leroy, A. M. 1987.Robust regression and outlier detection. John Wiley & Sons, Inc., New
York, NY, USA.
Saunders, R. and Gero, J. 2000. The importance of being emergent. In Proceedings of Artificial Intelligence in
Design.
Teng, H., Chen, K., and Lu, S. 1990. Adaptive real-time
anomaly detection using inductively generated
sequential patterns. In Proceedings of IEEE Computer Society Symposium on Research in Security and Privacy.
IEEE Computer Society Press, 278{284.
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2533
Title
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MULTI-RESOLUTION WAVELET ANALYSIS FOR FAULT DETECTION
Author
Author
KARA, Zeynep
SEKER, Serhat
Abstract
A summary of the resource.
In this study, a multi-resolution wavelet analysis technique is applied to simulation data for fault detection. Data is simulated at the MATLAB environment. For this purpose, a sinusoidal wave form is generated at around 1 kHz sampling frequency and then a faulty case is simulated between 250- 500 Hz using a random process under the band-pass filtering. Hence data and its noisy form are used to show healthy and faulty cases of any physical system respectively. In order to show the fundamental properties of the data set, power spectral density variations are shown to indicate the availability of the data. After that Multi– Resolution Wavelet Analysis (MRWA) is applied to each case. In general, wavelet transform is a time-scale analysis technique which can be accepted as an alternative method to the Fourier transform. However, in this study, MRWA approach is considered. MRWA is a kind of the discrete wavelet transform and it uses filter banks approach. Hence, the time domain properties are shown in the sense of the statistical parameters. Also, calculating the power spectral densities, this comparison is done in frequency domain. With this way, a faulty case and its some properties can be determined at both of the time and frequency domains. Key Words: Wavelets, Filtering, Sub-band analysis, Fault detection
Publisher
An entity responsible for making the resource available
International Burch University
Date
A point or period of time associated with an event in the lifecycle of the resource
2014-05-15
Keywords
Keywords.
Article
PeerReviewed
Identifier
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ISSN 978-9958-834-36-3
Q Science (General),QH301 Biology,QH426 Genetics
-
https://omeka.ibu.edu.ba/files/original/14da713495539293b340e52c90cb2f90.pdf
c39e16c8fad2d65920ed3860eaf64407
PDF Text
Text
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TORQUE-FLUX PLANE BASED SWITCHING TABLE IN DIRECT TORQUE
CONTROL
M Ozgur Kizilkaya1, Tarik Veli Mumcu2, Kayhan Gulez2
1
Electronics Engineering, Aeronautics and Space Technologies Instıtute, Turkish Air Force
Academy, Istanbul, Turkey
2
Control and Automation Engineering, Faculty of Electrical and Electronics Engineering,
Yildiz Technical University, Istanbul, Turkey
mkizilkaya@hho.edu.tr, tmumcu@yildiz.edu.tr, gulez@yildiz.edu.tr
Abstract
Direct Torque Control (DTC) is a preferred method for its fast torque response and easy
implementation in induction motor (IM) applications. However varying switching frequency
and current harmonics are the drawbacks of the method. There are many industrial
applications already using DTC. In this study, a novel switching table is proposed to reduce
current harmonics based on torque-flux plane that can be applied to current motor drives with
software modification, rather than a hardware advancement. The study is illustrated with
Simulink model and motor output results.
Keywords: Direct Torque Control, Torque-Flux Plane, Total Harmonic Distortion, Vector
Selection Table.
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INTRODUCTION
Today Field Oriented Control (FOC) and Direct Torque Control (DTC) are the preferred
vector control method to drive Induction motor (IM) among industrial applications (Farid,
Sebti, Mebarka, & Tayeb 2007; Mumcu, Aliskan, Gülez, & Tuna, 2013). The most wellknown superiority of DTC over FOC is, it has fast torque and flux control property even with
its simplicity. Other advantages of DTC are being precise and free from rotor parameters. The
basic DTC algorithm aims to control both torque and stator flux linkage of motor by selecting
appropriate voltage vector and use stator resistance as motor parameter, voltage and current
measurement as feedback, that’s how it works independent of rotor parameters and without
need for speed or position feedback. (Takahashi, & Noguchi, 1986, Depenbrock, M. 1988).
One disadvantage of this method is high harmonic distortion causing acoustic noise and EMI
interference.
In order to enhance DTC method, there are several methods proposed in the literature. Kenny
& Lorenz (2003) used deadbeat control, Ahammad, Beig & Al-Hosani (2013) preferred
sliding mode control, Kumar, Gupta, Bhangale and Gothwal (2007) studied neural network
based DTC. Hafeez, Uddin, Rahim & Hew (2013) used self-tuned neuro-fuzzy control. While,
all these methods improves side effects of the DTC, they also lead the control technique
become more complicated and cause a longer adaptation time delay to adopt to the current
motor drive systems. Some of the developed control methods can be expressed with switching
tables with the purpose of easy implementation (Casadei, Serra, Tani, & Zarri, 2013; Ludtke,
& Jayne, 1995; Gulez, Adam, & Pastaci, 2007). Switching table based DTC (ST-DTC) is not
complicated to apply which leads less application time delay on motor drive systems.
Regarding the phase of developing new algorithms for DTC, induction motor voltage vectors,
which are in three phase system, is transformed to α, β plane as in Fig. 1, so as to illustrate the
voltage vector selection in a two dimensional plane. In this plane, the stator flux linkage is
defined as a vector and the variation of it is defined as the flux ripple. And, the torque is
visualized with the magnitude of both rotor and stator flux vector and the angle between them.
In order to decrease the torque ripple, it is aimed to move the stator and rotor flux vector more
harmoniously and smoother.
Fig. 1 Voltage vector representation on α-β plane (Buja, & Kazmierkowski. 2004).
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The existing voltage vectors, which are necessary to drive the inverter in DTC algorithm, can
be seen in α-β plane in Fig.1. In this study, the main focus is to define motor operating point
on torque-flux plane, instead of α-β plane, which gives the designer a different perspective in
order to develop/consider different design options for a control concept. In the following
sections, ST-DTC algorithm and our proposed method which is basically a new interpretation
of the switching table will be compared; the simulations and the comparison of the simulation
results will be discussed respectively.
BASIC ST-DTC SCHEME
DTC is a feedback control method where the voltage vectors and phase currents applied to the
induction motor are required as feedback signals. Stator flux linkage and motor torque are
calculated so that they can be applied in the next time interval to the motor in algorithm.
Voltage vector selection as the stator flux linkage is determined by the equation (1). In DTC
algorithm, defining inverter control signals is basically the main core in order to keep the
motor torque and the flux linkage around the control reference points given by the user.
d
s Vs rs I s
(1)
dt
Rotor and stator flux vectors are interrelated in induction motor, that a change in stator flux is
followed with a delay by the rotor flux, both are crucial to control motor torque. Thus, torque
at the induction motor output is determined as a function of both flux magnitudes in equation
(2).
Te
L
3
P m s r sin
2 Ls Lr
(2)
In equation (2) the terms are expressed as:
Te: the induction motor output torque,
ψS: stator flux magnitude, ψr: rotor flux magnitude,
γ: torque angle between stator and rotor flux,
P: Number of poles, Ls: Stator inductance,
Lr: Rotor inductance, Lm: Mutual inductance,
σ: leakage factor.
Conventional ST-DTC scheme is depicted in Fig.2. In this method, the difference between
reference and calculated flux linkage are processed by a two level hysteresis comparator.
Similarly, the difference between reference torque and the calculated torque values are
processed by a three level comparator. The outcomes of these are inputs for voltage vector
selection function. In conventional ST-DTC method, voltage vector selection is determined by
table I on which present stator flux linkage sector (Fig.1), digitized torque and stator flux
linkage error are the inputs. As the vector selection table I denotes, when torque values reach
to hysteresis comparator set values, in order to keep torque and flux around the reference
points and to prevent violation of limits, voltage vectors are changed between V0 and V7.
Thus, all possible voltage vectors regarding DTC algorithm can be seen on Fig. 1.
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Fig. 2 Conventional ST-DTC scheme.
TABLE 1. DTC VOLTAGE VECTOR SELECTION TABLE [12]
dDψ dTe
1
-1
S1
S2
S3
S4
S5
S6
1
V2
V3
V4
V5
V6
V1
0
V7
V0
V7
V0
V7
V0
-1
V6
V1
V2
V3
V4
V5
1
V3
V4
V5
V6
V1
V2
0
V0
V7
V0
V7
V0
V7
-1
V5
V6
V1
V2
V3
V4
To understand the conventional ST-DTC algorithm, table I can be explained in detail. S1-S6
determines the sector number of the stator flux linkage. Likely, V0-7 determines the voltage
vector numbers which are needed to bring the motor outputs around the reference point. V0
and V7 are zero voltage vectors. dψ and dTe defines the digitized flux and the torque errors on
controller side. ‘+1’ illustrates that torque or flux parameter need to be increased, ‘-1’
illustrates the parameters which are processed by the controller need to be decreased and ‘0’ is
to define the control parameters are already around the reference point.
NOVEL ST-DTC SCHEME
The proposed method does not use hysteresis controller as depicted in Fig.3. Instead, stator
flux linkage and torque output is traced and compared with the reference magnitudes
continuously instead of using hysteresis controller.
Motor stator flux linkage and torque outputs are defined as an operating point in torque-flux
plane. Voltage vector selection is done in order to move the operating point of motor inside a
hypothetical region in torque-flux plane. In this study, It is aimed to keep the motor operating
point in rectangular shaped region, that size of the rectangular is defined as allowed torque
and stator flux linkage error as in Fig.4. In that manner, torque-flux plane is divided into nine
zones. Selected voltage vector forces the motor operating point to a different direction as in
Fig.4. For instance, if motor torque and flux linkage values are both below the defined error
limit, this express that motor is operating in zone 7. Similarly, if both values are in limits,
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motor is operating in zone 5. When the motor is in zone 7, and if the stator flux linkage sector
number is `k`, then `k+1`th voltage vector needs to be applied so that motor operating point
can be forced towards zone 5.
Fig. 3 Proposed ST-DTC scheme.
Fig. 4 Effect of voltage vectors to operating point in torque flux plane.
THE PROPOSED VECTOR SELECTION TABLE
The basis of this study is to reduce current harmonic distortion without any lack of control for
an induction motor output parameters such as torque and flux linkage errors. For this purpose,
an implementation of a new vector selection table based DTC algorithm is designed based on
torque flux plane to define the selection of the voltage vectors which will be applied to.
After the torque and flux hysteresis band are determined as shown in Fig.4, one has to decide
the related action for the nine zones in the torque-flux plane. After trails among different
choices, the vector selection table in Table II is determined so as to decrease the phase current
harmonics.
TABLE 2. VOLTAGE VECTOR SELECTION TABLE
Zone
Vector
1
k+2
2
0/7
3
0/7
4
k+1
5
NC
6
0/7
7
k+1
8
k+1
9
k-1
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Table II can be explained in detail as, if the motor is operating in zone 1 and the stator flux
linkage is in sector ‘k’ apply ‘k+2th’ voltage vector till motor operating point moves to a
different zone. When the motor comes to zone 5, do not change the voltage vector as NC
states ‘No Change’. For zones 2/3 and 6 apply zero voltage, V0 or V7 in a manner to keep the
switching frequency lower.
In the simulation, while using the texture in Fig.4, one problem with the method is high
frequency swinging of motor operating point between zone 4 and 2, and between zone 8 and
6, Thus, the result is inevitable with high frequency switching while still keeping the torque
and flux linkage in the limit. To overcome this issue, texture is adjusted to avoid swinging
while keeping the motor in zone 5. The texture after adjustment is as shown in Fig.5. Zone 1
is expanded as 0.8 times flux band by experience. Mathematical expressions for torque flux
plane are a future work.
Fig. 5 Modified motor operating zones in torque flux plane.
This adjustment is an example to show how the design can be visualized clearly.
SIMULATION RESULTS
To show the effectiveness of the proposed method, a test scheme is constructed using a
predetermined induction motor model in the Simulink environment using the motor
parameters below.
4kW, 50 Hz, 1430 Rpm, Squirrel Cage IM
Stator Resistance
: 1.405 Ohm
Stator Inductance
: 0.005839 H
Rotor Resistance
: 1.395 Ohm
Rotor Inductance
: 0.005839 H
Mutual Inductance
: 0.1722 H
Pole Pair
:2
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To compare the both method, control parameters and input voltage are assigned same.
Simulation parameters are:
DC link Voltage
Torque error limit
Flux error limit
Torque reference
Flux linkage reference
: 400 Volt
: ±0.5Nm
: ±0.01 Wb
: 10 Nm
: 0.5 Wb.
Then, a model is formed for induction motor drive system with the principle of conventional
ST-DTC scheme by Matlab/Simulink. The conventional ST-DTC algorithm is compared with
the proposed algorithm for new voltage vector selection table. The simulation results shows
lower phase current harmonics, lower total harmonic distortion (THD), better flux trajectory
follow as compared to the conventional ST-DTC scheme.
Fig. 6 Conventional ST-DTC Stator flux linkage variation in time.
Fig. 7 Proposed ST-DTC Stator flux linkage variation in time.
When the two method is compared by means of flux linkage, both method achieves to keep
the flux linkage in the set band at the steady state. However at the start up, the fluxlinkage of
the conventional ST-DTC needed more duration to settle in the band than proposed method as
shown in Fig. 6 and Fig 7. That is because conventinal DTC aims to keep the torque in the
band as a priority, while the proposed method does not assign a priority between torque and
flux linkage determined by the proposed switching table.
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Fig. 8 Conventional ST-DTC phase current and phase current THD.
Fig. 9 Proposed ST-DTC phase current and phase current THD.
The flux linkage of the motor is controlled with lower distortion than conventional ST-DTC
thus leading a better total harmonic distortion in phase current. THD value for the
conventional method is %6.17 as in Fig. 8 while it is %5.31 for the proposed method as in Fig
9.
Fig. 10 Conventional ST-DTC torque variation in time
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Fig. 11 Proposed ST-DTC torque variation in time.
The torque response of the both method are similar. The proposed method achieved a better
flux linkage results while preserving torque response characteristic of the motor as can be
depicted in Fig 10 and Fig 11 respectively.
CONCLUSION
In this study, the switching table based DTC application of Induction motor in torque-flux
plane is explained. The proposed torque-flux plane achieved a visual platform to construct a
switching table which is defined by the operation point of induction motor. Motor fluxlinkage and torque output is traced continuously, instead of using flux and torque controller in
a hysteresis band manner. An improvement in the phase current total harmonic distortion is
achieved without any degradation in the torque and flux band. The proposed method can be
applied to the current motor drives by software upgrade. The study is carried on rectangular
shaped torque and flux band, thus different band approaches can be investigated for improved
THD values and reduced switching frequency as a future work.
REFERENCES
Ahammad, T., Beig, A.R. & Al-Hosani, K. (2013) “An improved direct torque control of induction motor with
modified sliding mode control approach, IEEE International Electric Machines & Drives Conference (IEMDC),
166-171, doi: 10.1109/IEMDC.2013.6556249
Buja, G.S. & M.P. Kazmierkowski M.P. (2004). Direct torque control of PWM inverter-fed AC motors - a
survey. IEEE Transactions on Industrial Electronics. 51, 4,744-757.
Casadei, D., Serra, G., Tani, A. & Zarri, L. (2013). Direct Torque Control for induction machines: A technology
status review. IEEE Workshop on Electrical Machines Design Control and Diagnosis (WEMDCD). 117-129,
Depenbrock, M. (1988). “Direct Self-Control (DSC) of Inverter-Fed Induction Machine”, IEEE Transactions on
Power Electronics, 3,. 4, 420-429
Farid, N., Sebti, B., Mebarka, K. & Tayeb, B. (2007). Performance analysis of field-oriented control and direct
torque control for sensorless induction motor drives. in Proc. IEEE, Mediterranean Conference on Control &
Automation, 1-6
Gulez, K., Adam, A.A., & Pastaci, H. (2007). A Novel Direct Torque Control Algorithm for IPMSM With
Minimum Harmonics and Torque Ripples" IEEE/ASME Transactions on Mechatronics, 12,.2, 223-227
173 | P a g e
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Hafeez, M., Uddin, M.N., Rahim N.A &, Hew W.P. (2013). Self-Tuned NFC and Adaptive Torque Hysteresis
based DTC Scheme for IM Drive, IEEE Transactions on Industry Applications,99.
Kenny B. & Lorenz, R. (2003). Stator- and rotor-flux-based deadbeat direct torque control of induction
machines. IEEE Trans. Ind. Appl., 39, 4, 1093–1101.
Kumar, R., Gupta, R.A., Bhangale, S.V. & Gothwal, H. (2007). Artificial neural network based direct Torque
Control of Induction Motor drives," IET-UK International Conference on Information and Communication
Technology in Electrical Sciences, 361-367
Ludtke, I. & Jayne, M.G (1995). A new direct torque control strategy. IEE Colloquium on Advances in Control
Systems for Electric Drives,5/1-5/4,Available: 0.1049/ic:19950758
Mumcu T.V., Aliskan I., Gülez, K. & Tuna, G. (2013). Reducing Current and Moment Fluctuations of Induction
Motor System of Electrical Vehicles by Using Adaptive Field Oriented Control. Elektronika Ir Elektrotechnika,
19, 2, 21-24, http://dx.doi.org/10.5755/j01.eee.19.2.3464
Takahashi, I. & Noguchi, T. (1986). A New Quick-Response and High-Efficiency Control Strategy of Induction
Motor, IEEE Transaction on Industrial Applications, 22, 5, 820-827.
M. Ozgur KIZILKAYA was born in Burdur, Turkey. He received his B.S. degree from Gazi
university in 1998, M.S degree from Middle East Technical Universtiy in 2002. He is
currently PhD candidate in Turkish Air Force Academy, both in electronics engineering. He is
interested in nonlinear control of electrical machines.
Traık V. MUMCU was born in Ankara, Turkey. He received his B.S. and M.S. degrees in
Electrical engineering in 2002 and 2005 respectively, Ph.D. in Control and Automation
Engineering in 2013 all from Yıldız Technical University. He is interested in control of
UAVs.
Kayhan GULEZ was born in İstanbul, Turkey. He is an Associate Professor of Control and
Automation Engineering at the Yıldız Technical University. He received his B.S., M.S., and
Ph.D. degrees all in Electrical Engineering from Yıldız Technical University. His major
research interests are Electrical Vehicle and Unmanned Air Vehicle Applications, Intelligent
based Control Systems, Sensor Network Control Problems, EMC and EMI Control Methods,
Active, Passive and EMI Filter Design Methods and Applications for EMI Noise and
Harmonic Problems on which he has over 200 scientific papers and technical reports in
various journals and conference proceedings.
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Title
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TORQUE-FLUX PLANE BASED SWITCHING TABLE IN DIRECT TORQUE CONTROL
Author
Author
KIZILKAYA, M Ozgur
MUMCU, Tarik Veli
GULEZ , Kayhan
Abstract
A summary of the resource.
Direct Torque Control (DTC) is a preferred method for its fast torque response and easy implementation in induction motor (IM) applications. However varying switching frequency and current harmonics are the drawbacks of the method. There are many industrial applications already using DTC. In this study, a novel switching table is proposed to reduce current harmonics based on torque-flux plane that can be applied to current motor drives with software modification, rather than a hardware advancement. The study is illustrated with Simulink model and motor output results. Keywords: Direct Torque Control, Torque-Flux Plane, Total Harmonic Distortion, Vector Selection Table.
Publisher
An entity responsible for making the resource available
International Burch University
Date
A point or period of time associated with an event in the lifecycle of the resource
2014-05-15
Keywords
Keywords.
Article
PeerReviewed
Identifier
An unambiguous reference to the resource within a given context
ISSN 978-9958-834-36-3
Q Science (General),QH301 Biology,QH426 Genetics
-
https://omeka.ibu.edu.ba/files/original/907cbbd3e58985ca628d546b743f6a56.pdf
551d693419df73ca402b797eabfe0349
PDF Text
Text
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ANALYSIS OF MAGNETIC FIELD EFFECTS OF
UNDERGROUND POWER CABLES ON HUMAN HEALTH
Celal Kocatepe, Celal Fadil Kumru, Eyup Taslak
Yildiz Technical University, Istanbul, Turkey
kocatepe@yildiz.edu.tr, cfkumru@yildiz.edu.tr, etaslak@yildiz.edu.tr
ABSTRACT
Transmission and distribution lines of electrical energy are generally used to plant far from
residential areas. But today, due to the growing population, the cities considerably expanded
and electrical network have to lie within the living spaces. Especially, uses of medium voltage
underground cables for distribution systems become widespread in such areas. The voltage
levels of these cables are not too high and the electric field caused by the voltage is fairly
shielded by the cable’s screen. However, by the reason of flowing load current through the
cable’s conductor, low frequency magnetic fields occur around the cable. It is known that this
magnetic field strength becomes greater with increasing current. Basically, shielding of low
frequency magnetic fields is quite harder than shielding the electric fields. In case of being
exposed to this kind of magnetic fields by people may lead to crucial health problems.
Therefore, some limit values are introduced by the “International Commission On
Non‐Ionizing Radiation Protection” (ICNIRP) and “The Institute of Electrical and Electronics
Engineers” (IEEE). For this reason, it has importance of measuring magnetic fields caused by
high voltage cables (HVC) in urban areas and the required shielding measures should be taken
if needed. In this study, magnetic field strengths at different points above a 12/20 kV, 150
mm2 (Al), single core HVC are measured for different current values. According to the results
obtained, even at low currents, the magnetic field strength values could exceed the limiting
values for certain distances.
Keywords: Magnetic Field, Underground Power Cable, Human Health
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1. INTRODUCTION
Electrical energy is one of the most important sources in our age. The need for electrical
energy is rapidly growing with developing technology and increasing population. Generated
energy is supplied for the end users through transmission and distribution lines to meet this
energy demand. Resulting from expanding of residential areas and increasing energy demand,
especially distribution lines penetrate in living spaces [1]. While energy is distributed with
overhead lines in the beginning, today underground power cables are being used especially
for human safety and clear visual pollution. These cables are widely used for supplying
distribution transformers in thickly populated places [2,3].
Underground power cables used in distribution systems cause electric field because of being
operated at medium voltage. All underground power cables, which operate at medium voltage,
consist a screen layer made of copper or lead [4]. This screen is grounded in practice and can
shield almost all electric field arise from conductor. However, this screen layer cannot totally
shield low frequency magnetic fields arise from load current. Current carrying capacity of
underground power cables, which generally used in residential areas, is quite high. Therefore,
magnetic field exposure risk occurs for humans.
In literature, there several studies about the effects of magnetic field exposure on human
health [5-8]. Thus, analysis of magnetic fields arise from underground power cables has an
importance. Limiting magnetic field values for different frequencies are introduced by
ICNIRP [9].
In this study, magnetic field measurements of an underground power cable are carried out for
different currents at certain distances. The results obtained are analyzed by using ICNIRP
standard. In the following section, for magnetic field calculation for, fundamental formulas of
a current carrying conductor are given and limit values by ICNIRP are presented. In the third
section, measurement setup and results are presented. Consideration of results and suggestions
are given in the last section.
2. BASIC THEORY
In power systems, magnetic fields occur around the conductors which carry currents. When
the current increases, the magnetic field is also strengthen proportionally. Magnetic field
induced a voltage in conductors and dielectric materials placed within the field [10]. This
induced voltage cause to flow current in object which harms the livings. Limiting values are
defined to keep human health in safe. It is important to consider these values while designing
a system which consist current carrying conductors.
At a specified distance, magnetic field value of a current carrying conductor can be calculated
by Bio-Savart equation given in Eq. (1).
H
I
2 r
[A/m]
where,
H = Magnetic Field Strength [A/m]
I = Current [A]
r = Distance [m]
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As it is known that magnetic field strength (H) is a vectorial magnitude. So, a current carrying
conductor at point K causes to occur both horizontal and vertical magnetic field component.
With vectorial sum of these components, resultant magnetic field (H) at point P is acquired as
shown in Fig. 1 [10].
Figure 1 Magnetic field strength of a conductor (K) at point P
According to the Figure 1, horizontal and vertical components of magnetic field strength (H)
at point P can be calculated with formulas given in Eq. (2) and (3) respectively.
Hx
y j yi
I
2
r2
(2)
Hy
x j xi
I
2
r2
(3)
Here, xi and yi are the coordinates of point K and xj and yj are the coordinates of point P. r is
the distance from the current source defined as,
r
x
xi y j y i
2
j
2
(4)
To calculate resultant magnetic field strength, horizontal and vertical components are
vectorially added. If there are n conductors in a system, resultant magnetic field strength can
be calculated with the Eq. (5).
2
n
n
H H xi H yi
i 1
i 1
2
(5)
Magnetic flux density (MFD) can be calculated by multiplying the magnetic field strength (H)
and magnetic permeability of vacuum or air ( 0 4 10 7 [H/m] ) as given in Eq. (6).
B 0 H
(6)
In Eq. (6), B is the magnetic flux density or magnetic induction in Wb/m2 or Tesla.
Several studies have been published about the effects of magnetic field on human health.
Magnetic field exposure levels depend on many factors such as distance from the magnetic
field source, exposure duration, strength and frequency of the magnetic field. Therefore, limit
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values for magnetic fields at different frequencies are specified by the ICNIRP [9]. These
values are given in Table 1 for occupational and general public exposure.
Table 1 Reference levels for occupational exposure to time varying magnetic fields
(unperturbed rms values).
Exposure
Occupational
General Public
Frequency Range
1 Hz – 8 Hz
8 Hz – 25 Hz
25 Hz – 300 Hz
300 Hz – 3 kHz
3 kHz – 10 Mhz
1 Hz – 8 Hz
8 Hz – 25 Hz
25 Hz – 50 Hz
50 Hz – 400 Hz
400 Hz – 3 kHz
3 kHz – 10 MHz
Magnetic Field Strength
H (A/m)
1.63 x 105/f2
2 x 104/f
8 x 102
2.4 x 105/f
80
3.2 x 104/f2
4 x 103/f
1.6 x 102
1.6 x 102
6.4 x 104/f
21
Magnetic Flux Density
B (T)
0.2/f2
2.5 x 10-2/f
1 x 10-3
0.3/f
1 x 10-4
4 x 10-2/f2
5 x 10-3/f
2 x 10-4
2 x 10-4
8 x 10-2/f
2.7 x 10-5
In this study, 50 Hz power system frequency is considered. Measured MFD values at this
frequency should be under 1 mT for general public exposure and 0.2 mT for occupational
exposure.
3. EXPERIMENTAL SETUP AND RESULTS
In the measurement, 12/20 kV, 150 mm2, single core high voltage underground cable is used.
The technical specifications of the cable sample are given in Table 2 [11].
Table 2 Technical specifications of the cable sample
Parameter
VDE Code
Nominal voltage (kV)
Nominal cross-section (Al/Cu Tape) (mm2)
Value
NA2XSY
12 / 20
1x150/16
Conductor DC resistance
(at 20°C) (ohm/km)
0.198
Operating inductance (mH/km)
Operating capacitance (µF/km)
Current carrying capacity (in air) (A)
Cable length (m)
Overall diameter (mm)
0.63
0.25
425
12
33.5
The cross-sectional area of the sample cable is given in Fig. 2. The underground power cable
consists of a few layers. The conductor is the main part which transfers energy. The main
insulation material of the cable is cross linked polyethylene (XLPE). There are semiconductor layers around the copper conductor and insulation. Semi-conductor layer is used for
smoothing the field distortion caused by stranded structure of conductor and roughness of the
sheath. The role of the screen is shielding of electric and magnetic fields. For this reason, lead
is generally used as screen material for cables which have high current carrying capacity. The
outer sheath is made of PVC and it protects cable from environmental effects.
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Figure 2 Cross-sectional area of underground power cable
The measurement setup given in Fig. 3 is arranged for flowing current through the cable
conductor. The conductor of the cable is connected to the secondary windings of a 220V/5V
and 5 kVA high current transformer. This transformer is supplied with a 220V/0-220V, 5
kVA variac. So the desired current value is obtained by varying the secondary winding
voltage of the variac. A 1000 A clamp meter with ±1.5% sensitivity is used to measure the
cable current. Additionally, the screen of the cable is grounded as in practice.
Figure 3 The experimental setup
In the measurement, a magnetic field measurement device Spectran NF-5035 is used. The
measurements are realized for certain distances (5, 10, 20, 40, 60, 80 and 100 cm) above the
upper side of cable. The minimum load current for measurement is specified as 50 A. The
measurements are carried out up to 450 A with 50 A steps. The results obtained are given in
Table 3.
Table 3 Measured magnetic flux density values
Distance From
Upper Side
(cm)
5
10
20
40
60
80
100
Magnetic Flux Density [µT]
50 A
135.5
70.27
39.65
18.98
16.54
14.79
12.04
100 A
150 A
200 A
250 A
300 A
350 A
400 A
450 A
262.5
142.5
75.05
40.81
23.45
19.55
19.05
371.3
210.9
113.8
60.37
40.6
27.31
21.1
471.6
267
149.8
78.37
50.51
36.59
27.81
559.1
333.6
182
97
65.9
46.97
33.5
693.7
384.4
215.4
113.9
75.08
54.67
42
794.2
449.9
247.7
131.2
87.94
63.56
50.72
914
504.2
283
151.2
102
75.46
56.27
1010
567.2
312.9
170.3
112.8
83.29
63.89
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As seen in Table 1, MFD is increasing with the increased current. Also, it reaches the highest
values for all current levels when it gets closer to the cable surface. The highest MFD is
obtained as 1010 µT for 450A current and 5 cm distance. The weakest MFD value is acquired
as 12.04 µT for 50 A current and 100 cm distance. Additionally in Table 1, some values,
which exceed the limit values in ICNIRP for general public exposure, are given in bold.
Especially for the currents from 300 A up to 450 A and 20–30 cm distance, it is clearly seen
that the measured MFD values are unsafe for general public.
1100
Magnetic flux density (µT)
1000
900
occupational exposure
800
700
600
100A
200A
300A
400A
450A
500
public exposure
400
300
200
100
0
0
5
10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
Distance (cm)
Figure 4 The relation between distance and magnetic flux density
The relation between the distance and MFD for all current levels is given in Fig. 4. It seen
from the Fig. 4 that, MFD is exponentially increasing with decreasing distance from the
source for all current levels. Additionally, the difference between MFDs obtained for certain
current levels show difference according to the distances. When it gets closer to the cable
such as 5 cm distance, the difference is quite high for different current levels. In contrast with
this change, the difference is quite small when it goes far from the cable.
4. CONCLUSION
In this study, magnetic field measurements of a 12/20 kV, 1x150/16 mm2 underground power
cable is realized for particular current and measurement distances. The results showed that
magnetic field is increasing with the increased current and decreased distance. Especially for
450 A current, the MFD value exceed the limit value for general public at 35 cm distance.
In addition, underground power cables are commonly installed 80 cm below the ground
surface. So approximate distance value, that the people can be exposed to magnetic field, is
over 80 cm distances from the cable. Therefore, the MFD values obtained in this study seem
safe for human health. However in practice, there are at least three cables in the cable route
for three phase systems. In this situation, each magnetic field strength value is vectorially
added together as in Eq. (5). Thus, the magnitude of MFD can be reach to considerable high
values which can be unsafe for human health. Additionally, there underground cables whose
sectional area and so the current carrying capacity is higher from the one in this study. So, the
cables which have high current carrying capacities are bigger threads for human health.
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Consequently, magnetic field strength caused by an underground power cable can be at
dangerous levels for human health. To get over this problem, magnetic field measurements
around the underground power cables should be done carefully. In the case of existing high
magnetic field values, the whole cable system could be shielded by a ferromagnetic material
or the cable route could be further from the ground. Thus, generated magnetic field can be
decreased down to required limit values.
5. REFERENCES
[1] Kalenderli, O., Kocatepe, C., Arikan, O., (2011). High Voltage Technique with Solved Problems, Vol.1,
Birsen Press, Istanbul, Turkey.
[2] Gobba, F., Bargellini, A., Scaringi, M., Bravo, G., & Borella, P., (2008), Extremely Low FrequencyMagnetic Fields (ELF-EMF) occupational exposure and natural killer activity in peripheral blood lymphocytes,
Science of The Total Environment, 407(3), 1218–1223.
[3] Ali, E., Memari, A.R., (2010). Effects of Magnetic Field of Power Lines and Household Appliances on
Human and Animals and its Mitigation, IEEE Middle East Conference on Antennas and Propagation
(MECAP),Cairo, Egypt, 1-7.
[4] Gudmundsdottir, U. S., De Silva, J., Bak, C. L., Wiechowski, W., (2010). Double Layered Sheath in
Accurate HV XLPE Cable Modeling, IEEE Power and Energy Society General Meeting, 1-7.
[5] A. S. Safigianni, A. I. Spyridopoulos and V. L. Kanas, (2011), Electric and magnetic field measurements in a
high voltage center, 10th International Conference on Environment and Electrical Engineering (EEEIC), 1-4.
[6] Takebe, H., Shiga, T., Kato, M., Masada, E., (2001). Biological and Health Effects from Exposure to Power
Line Frequency Electromagnetic Fields – Confirmation of Absence of Any Effects at Environmental Field
Strength, IOS Press, ISBN 158 603 1058.
[7] M. Maslanyj et al., Investigation of the sources of residential power frequency magnetic field exposure in the
UK Childhood Cancer Study, (2007). Journal of Radiological Protection Vol. 27, 41–58.
[8] World Health Organization (WHO), (2007). Extremely Low Frequency Fields Environmental Health Criteria
Monograph No. 238, Chapter. 2, p. 48.
[9] ICNIRP Publication (2010). ICNIRP Guidelines, For limiting exposure to time varying electric and magnetic
fields (1 Hz – 100 kHz), Health Physics 99(6), 818-834.
[10] Guclu, G., Kaypmaz, A., Kalenderli, O., (2011). Calculation of Magnetic Field Around 34,5 kV Power
Lines, Electromagnetic Fields and Effects Symposium, 270-273.
[11] Demirer Cable, Low, Medium and High Voltage Cables Catalogue, (2012).
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Title
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ANALYSIS OF MAGNETIC FIELD EFFECTS OF UNDERGROUND POWER CABLES ON HUMAN HEALTH
Author
Author
KOCATEPE, Celal
KUMRU, Celal F.
TASLAK, Eyup
Abstract
A summary of the resource.
Transmission and distribution lines of electrical energy are generally used to plant far from residential areas. But today, due to the growing population, the cities considerably expanded and electrical network have to lie within the living spaces. Especially, uses of medium voltage underground cables for distribution systems become widespread in such areas. The voltage levels of these cables are not too high and the electric field caused by the voltage is fairly shielded by the cable’s screen. However, by the reason of flowing load current through the cable’s conductor, low frequency magnetic fields occur around the cable. It is known that this magnetic field strength becomes greater with increasing current. Basically, shielding of low frequency magnetic fields is quite harder than shielding the electric fields. In case of being exposed to this kind of magnetic fields by people may lead to crucial health problems. Therefore, some limit values are introduced by the “International Commission On Non‐Ionizing Radiation Protection” (ICNIRP) and “The Institute of Electrical and Electronics Engineers” (IEEE). For this reason, it has importance of measuring magnetic fields caused by high voltage cables (HVC) in urban areas and the required shielding measures should be taken if needed. In this study, magnetic field strengths at different points above a 12/20 kV, 150 mm2 (Al), single core HVC are measured for different current values. According to the results obtained, even at low currents, the magnetic field strength values could exceed the limiting values for certain distances. Keywords: Magnetic Field, Underground Power Cable, Human Health
Publisher
An entity responsible for making the resource available
International Burch University
Date
A point or period of time associated with an event in the lifecycle of the resource
2014-05-15
Keywords
Keywords.
Article
PeerReviewed
Identifier
An unambiguous reference to the resource within a given context
ISSN 978-9958-834-36-3
Q Science (General),QH301 Biology,QH426 Genetics
-
https://omeka.ibu.edu.ba/files/original/57511de7d445d5d0d98a45649f3521a0.pdf
b9cda18f0d0d1f44fdaa11e2ba5697cc
PDF Text
Text
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INVESTIGATION OF A BIOMASS GASIFICATION SYSTEM BASED ON ENERGY
AND EXERGY ANALYSIS
Abbas Alpaslan Kocer1, Yunus Emre Yuksel2, Murat Ozturk3
1
Uluborlu Selahattin Karasoy Vocational School, Suleyman Demirel University,
32260, Isparta Turkey, alpaslankocer@sdu.edu.tr
2
Department of Science and Education, Education Faculty, Afyon Kocatepe University,
03200, Afyon, Turkey, yeyuksel@aku.edu.tr
3
Department of Mechatronics Engineering, Faculty of Technology, Suleyman Demirel
University, 32260, Isparta Turkey, muratozturk@sdu.edu.tr
Abstract
Biomass gasification procedure is a very complex process and it is influenced by many
physical and chemical factors such as biomass gasification temperature and gasifier type.
Thermodynamic assessment methodology based on the energy and exergy analysis can be
used to evaluate the system performance and environmental impacts. In this paper,
thermodynamic analysis of the biomass gasification system is given for the whole system and
its components. The parametric studies reveal the effects of design and operating indicators
on the exergy efficiency and exergy destruction rate. The result shows that the gasification
temperatures for the biomass gasification system change significantly with the type of the
gasifying medium.
Keywords: Biomass gasification, energy analysis, exergy analysis, parametric study.
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1. Introduction
Energy is a key indicator for social, cultural and economic development of any country, and
also is evaluated as an important aspect for sustainable development. It has been clearly seen
that the energy production and consumption rate of a country is proportional to its economic
status. By extension, the development of a country can be quantified as a ratio of its energy
consumption per capita. Fossil energy sources, such as crude oil and natural gas, have been
and refined to serve a dramatic growth in world population especially since the 1970s.
Nevertheless, it is usually indicated that fossil energy sources are not sufficient to meet the
constantly expanding needs of humanity. Conventional energy sources are non-renewable;
they draw on finite sources that will finally dwindle, becoming more expensive or
environmentally damaging to retrieve. Actually, at the nowadays consumption rate,
conventional energy sources are reaching a natural discharge limitation with ongoing
depletion [Ozturk et al., 2008]. Moreover, having relied merely on conventional energy
sources has exhibited different significant environmental damages. Renewable energy sources
are one of the most promising solutions for this energy demand. Alternative energy sources
should preferentially be more environmentally and economical than conventional fossil
energy sources in order to present wide scale applications. On the other hand, global warming,
air pollution, acid precipitation, ozone depletion, forest destruction, and emission of
radioactive substances are among the significant environmental problems [Ozturk et al., 2009].
Clean energy conversion and production variations with lower environmental concern should
be obtained by considering all mentioned issues simultaneously [Dincer, 2000]. The usage of
alternative energy sources provides a clean way to reduce the emissions of poisonous gases,
such as CO, CO2, NOx and SOx. As an important example, in Turkey, approximately 25% of
greenhouse gas emissions can be reduced by usage of renewable energy sources.
Many developed and developing countries installed intensive search plans in the before 1970s
to install renewable energy technologies and change fossil energy sources [Ozturk et al.,
2011]. The renewable energy technologies are the flat-plate solar panel installation for roofs
of the residential and commercial building for heating and hot water production applications;
photovoltaic (PV) system, wind turbine and ocean system for the electricity production; water
splitting for hydrogen output; and biomass or bio-waste for conversion to gaseous fuel sources
via gasification system for heat, steam or electricity generation.
Biomass is a large potential renewable energy sources, supplied from plants and animal
wastes. It is one of the oldest renewable energy sources and has been used by humankind for
daily needs since centuries [Toonssen et al., 2008]. To produce energy from biomass, the
most preferred method is conventional combustion of biomass. This technique is not only
valid in Turkey but also throughout the World. According to method which produces energy
from biomass, biomass techniques are classified as classic and modern biomass. Classic
biomass is the most popular method until now and this procedure consists of burning biomass
such as wood, plant residues, and animal dung. Modern biomass technologies are new relative
to classic ones and modern biomass is still on the development stages. In modern biomass
technique, biomass is converted into solid, liquid or gas fuels by means of bio-chemical and
thermo-chemical processes.
Investigations of the thermodynamic system are complex processes and involve consideration
of the system components and their characteristic, chemical reaction and thermodynamic loss.
Energy conversion technologies such as biomass gasification system should be investigated
for their performance by using the first and second laws of thermodynamic (or energy and and
exergy analysis). The use of exergy analysis should allow the determination of the processes
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having the greatest irreversibilities, as well as the causes and locations of the irreversibilities.
Exergy analysis also would allow exergy efficiencies to be determined for whole system and
its components. These important indicators should be used in design or retrofit of the process
for increasing system performance. In this paper, energy and exergy analysis of the biomass
gasification system and energy and exergy efficiencies of the system components are
investigated for better system design. The simulations have been performed using
Engineering Equation Solver (EES) software program. The following is a general outline of
the present study;
To investigate the effects of temperature and pressure of the gasifier, and biomass
concentration variation on the biomass gasification system.
To develop a theoretical model based on the thermodynamic laws performed in order
to study in greater detail the effect of process flows on gasification system and
investigate its performance.
To calculate the exergy content for the system components including the chemical
exergies for the biomass gasification plant.
To investigate the performance assessments of the gasification system.
2. Properties of Biomass
Each biomass fuel has significantly different fuel properties, and the gasification chamber
properties should be designed by using fuel properties. The specific properties of biomass
sources are given in Table 1. Generally, biomass energy sources have less carbon, more
oxygen and moisture contents than coal sources. Because of higher moisture and oxygen
content, the lower heating values (LHV) and higher heating values (HHV) of biomass fuels
are significantly lower than coal sources. The LHV and larger particle size of biomass sources
cause storage difficulties. But, biomass sources have lower nitrogen and sulphur contents than
coal sources, which are clearer, based on greenhouse gas emissions. The HHV of biomass
sources is calculated from the following equation [Loo and J. Koppejan, 2008];
(1)
where subscript B is biomass fuel, C, H, S, N, O and A are the carbon, hydrogen, sulphur,
nitrogen, oxygen and ash content of biomass sample in weight %, respectively. Proximate and
ultimate analysis (wt%) of biomass examples are given in Table 2.
Table 1. Specific properties of biomass sources
Specific properties
Density (kg/m3)
Particle size (mm)
SiO2 Contents (wt% of dry ash)
K2O (wt% of dry ash)
Fe2O3 (wt% of dry ash)
Al2O3 (wt% of dry ash)
Lower Heating Value (kJ/kg)
Values
~480-520
~2.8-3.2
~23-49
~4-48
~1.5-8.5
~2.4-9.5
~14,000-21,000
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Table 2. Proximate and ultimate analyses (wt%) of biomass sources
Beech bark
Oak wood
Sawdust
Switch Grass
Straw
Almond shell
Proximate analysis (received basis)
VM
FC
M
A
67.5
17
8.4
7.1
73
20
6.5
0.3
55.1
9.3
34.9
0.7
70.8
12.8
11.9
4.5
64.3
13.8
12.4
9.5
69.5
20.2
7.2
3.1
Ultimate analysis (dry ash free basis)
C
O
H
N
S
51
41.8
6
0.7
0.11
50
42.9
6.1
0.3
0.10
49
43.4
6.1
0.7
0.11
49
43.4
6.1
0.7
0.11
48
44.5
5.6
1
0.13
50
42.5
6.2
1
0.05
CI
0.11
0.01
0.08
0.54
0.06
3. System Design
Figure 1 shows a schematic of the biomass gasification system, modeled for the theoretical
investigation. Both air and the biomass fuels enter the gasifier at the environment temperature
and pressure. Gasification takes place in the gasification chamber and the flue gases after
exchanging the heat with the feed water exit through the stack at 155 °C. The most of the ash,
which is assumed approximately as 80% fly ash, exits the gasifier with the flue gases by the
chimney. Gasification technology converts biomass fuels into product gases that should be
used in energy conversation technology as an input gas fuel. The product gases are generally
consists of CO, CO2, CH4 and H2, and combusted to generate heat and shaft work. The
produced gasses are also used as feedstock for the production of synthesis gas, liquid fuels
and different chemicals. The lower heating values of the produced gases should be determined
via the gasses composition data. The outputs of the biomass gasification chamber also include
unused materials, such as particulars, tar, ammonia and hydrogen sulfide.
Produced Gases, T=TR
Biomass fuels
Biomass gasifier (Tbg)
Particular, tar, ammonia and
hydrogen sulfide
T=T0
Air
T=T0
Figure 1. Schematic diagram of the biomass gasification system
The biomass gasification reaction for 1 kg dry biomass source should be written as
follows;
(2)
Here, c, h, o and n values are used as kmol/kg, and mass fraction.
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4. Thermodynamic Analysis
Thermodynamic analysis of a biomass gasification system and its components requires special
consideration of multiple aspects, such as fluid dynamics, gasifier design, gas-dynamics and
thermodynamics of expanding flows with non-linear behavior and heat transfer. The proposed
mathematical model for a biomass gasification system includes the conservation of mass,
energy and exergy. To mathematically describe the biomass gasification system, a
comprehensive knowledge of physical and chemical exergy content for processes is required.
Mass, energy, entropy and exergy balance equations should be written for system components
and for the whole system under the assumption of steady state operation. This is done in
regard to a selected working fluid in a given cycle configuration and imposed operating
conditions of source. A general balance equation for any quantity in a system can be written
as [Dincer and Rosen, 2013];
Input + Generation – Output- Consumption = Accumulation
The general mass, energy, entropy and exergy balance equations for system
thermodynamic analysis on control volumes of process components are written as follows,
respectively;
Mass balance equation;
(3)
Energy balance equation;
(4)
Entropy balance equation;
(5)
where T is the temperature at where heat transfer cross the system boundary. Exergy balance
equation;
(6)
where
is the exergy destruction rate. Exergy analysis should be given as the highest
content of work that should be derived by investigating processes that bring the system into
equilibrium [Szargut et al., 1988; Rosen, 1986].
4.1 General efficiency equations
The energy efficiency ( ) of the investigated system should be given as the ratio of useful
energy produced by the process to the total energy input. The useful produced energy
represents the desired results produced by the system components, such as electricity, heating
and cooling, hot water, hydrogen and other chemicals. The energy efficiency for steady-state
processes should be written as follows:
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(7)
Exergy efficiency of the system components and whole system give the main
effectiveness of each process of the system. The exergy efficiency ( ) of the investigated
system can be given as the divided of exergy output rate (
) that is created by the
considered system to the overall exergy inlet rate (
) that is cross the boundaries of
the system. The exergy efficiency for steady-state processes should be written as follows:
(8)
5. Assumptions
The chosen assumptions for this paper are given as follows:
All the system components and whole system operate at steady state conditions.
All the proses gases are considered as ideal gases.
References ambient temperature and pressure are chosen as 25 oC and 1 atm,
respectively.
Ambient reference air considerations are considered as 21% oxygen and 79% nitrogen
on the volume basis.
Heat loss via radiation and convection from the gasifier to the environment is 1-2% of
fuel energy input [Basu et al., 2000; Fauklker and de Saouza-Santos, 2010].
Kinetic and potential energy impacts are neglected.
6. System Analysis
The exergy contents of flowing material have two indicators, such as physical exergy part and
chemical exergy part. In the gasification system, both physical and chemical exergy indicators
should be required because chemical reactions take place in the gasifier while only physical
exergy is combined by the steam process elements. The specific exergy for an investigated
state should be written as follows;
(9)
The physical exergy or specific flow exergy should be given as follows;
(10)
The chemical exergy contents of ideal gas should be given as follows;
(11)
where, zi is the mole fractions of the ith components and
is the molar chemical exergy at
the given reference temperature and pressure, and should be given as follows [Kotas, 1980];
(12)
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where
,
and T are standard molar chemical exergy of ith chemical composition,
formation enthalpy and gasifier temperature, respectively. The specific values of standard
molar chemical exergies of the various substances given in the theoretical investigation are
given in Table 3 [Cengel and Boles, 2006].
Table 3. Standard enthalpy and chemical exergy of various substances
Substance
O2 (g)
N2 (g)
CO2 (g)
H2O (g)
H2O (l)
SO2 (g)
NO (g)
NO2 (g)
Standard enthalpy
(MJ/mol)
0
0
-393.52
-241.82
-285.83
-297.10
90.59
33.72
Standard chemical exergy
(MJ/mol)
3.97
0.72
19.87
9.5
0.9
313.40
88.90
55.60
The exergy balance equation of the gasification chamber should be given as follows;
(13)
where
,
,
,
and
are exergy rate of biomass fuels, air, heat, hot product
gases and exergy destruction rate of gasifier, respectively.
Biomass fuels and air enter the gasifier at reference temperature and pressure,
therefore their physical exergies equal zero. In this paper, specific chemical exergies of
biomass fuels are calculated using the method which proposed by Szargut [2005], and this
methology should be given as follows;
(14)
where w is weight percent (w%) of moisture in fuel and
is the specific chemical exergy
of water at ambient temperature and pressure. The coefficient f is derived from experimental
results, and should be calculated as follows;
(15)
The chemical exergy of the air should be determined as follows;
(16)
where Aa is air molar flow rate,
nitrogen, respectively.
and
are specific chemical exergy of oxygen and
7. Results and Discussion
In this paper, Engineering Equation Solver (EES) software program utilized to investigate the
modeling biomass gasification system based on the thermodynamic assessment methodology.
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Also, EES contains built in library of thermodynamic data for many chemical substances.
Exergy destruction rate, energy efficiency and exergy efficiency of the biomass gasification
system components are investigated in the present paper, besides the assessment of system
components performance. Heat is lost from the gasifier to the environment during the process
that has been approved in many papers. Heat transfer through the temperature difference
always increases the entropy generation or exergy destruction rate. In order to investigate the
gasifier efficiency, analysis results of exergy destruction rate can help to identify the defect
within the gasification plant, and the system efficiency should be improved via modification
of the biomass gasification plant from considering reduction of heat losses in the further
system design.
Energy contents of matters are the measure of quantity, but exergy contents of matters are
measure of both quantity and quality of energy contents. Exergy values of biomass fuels are
approximately 20% greater than energy values by exergetic indicator (). In addition to that,
exergetic indicators of biomass fuels are higher than coal samples. The system performances
have been investigated in terms of key indicators. Gasifier temperature, ambient temperature
and pressure, work output, exergy destruction rate and main losses are used for efficiency
analysis of the biomass gasification system. It is also observed that moisture contents of
biomass fuels have more important effects on the decrease of gasifier outlet temperatures than
ash contents.
The effects of varying ambient temperature from 10 °C to 30 °C on the exergy destruction rate
and exergy efficiency of the biomass gasification system are given in Figure 2. According to
the Figure 2, the exergy destruction rate of the biomass gasification system decreases with
rising ambient temperature. On the other hand, exergy efficiency of the biomass gasification
system increases with increasing ambient temperature.
0.462
340.5
0.4618
340
0.4616
339.5
0.4614
339
0.4612
y gasifier (%)
ExD,gasifier (MW)
341
Ex D,gasifier
338.5
338
10
0.461
y gasifier
14
18
22
26
0.4608
30
T0 (oC)
Figure 2. Variations with ambient temperature of the exergy destruction rate and exergy
efficiency for the biomass gasification system
Figure 3 shows that, the exergy destruction rate of the gasifier decreases with
increasing gasifer temperature from 625 °C to 850 °C, but its exergy efficiency increases. The
variations of exergy destruction rate and exergy efficiencies of gasifer remain almost linear
depending on the ambient and gasifier temperature. These results are expected since the
exergy destruction rate and exergy efficiency of the process are usually inversely proportional
properties.
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0.502
0.5
0.498
0.496
325
0.494
0.492
324.5
ExD,gasifier
0.49
y gasifier
324
625
y gasifier (%)
ExD,gasifier (MW)
325.5
650
675
700
725
750
775
800
825
0.488
850
o
T gasifier ( C)
Figure 3. Variations with gasifier temperature of the exergy destruction rate and exergy
efficiency for the biomass gasification system
8. Conclusions
The main objective of the present study is to investigate the biomass gasification system
operating characteristics that provide power for various operating conditions by using
parametric analyses. The parametric analyses compare the system components and their
responses to variations in selected operating conditions, such as ambient temperature and
gasifer temperature. In addition to that, exergy efficiency of the biomass gasification is
investigated to indicate how the gasification process reaches the real operating conditions.
The main conclusions of the present paper should be given as follows;
Mass, energy and exergy balance equations for the system components and whole
system are necessary to investigate the gasification system performance.
The parametric studies are very useful to investigate the variations of system
efficiency for changing operating indicators.
Decreasing the exergy destruction rate of biomass gasification system components and
whole system, and increasing the energy and exergy efficiency result in decreased
greenhouse gas emissions, less environmental impacts and increased sustainability.
Important cause for higher exergy destruction rate or lower exergy efficiency in the
present paper is highly irreversible chemical reaction in the biomass gasifier.
9. References
Basu, P., Kefa, C., & Jestin, L. (2000). Boilers and Burners: Design and Theory. Springer, New York.
Cengel, Y. A., & Boles, M. A. (2006). Thermodynamics: An Engineering Approach. Fifty Edition, Boston:
McGraw Hill.
Dincer, I. (2000). Renewable energy and sustainable development: a crucial review. Renewable and Sustainable
Energy Reviews. 4,157-175.
Dincer I., & Rosen M. A. (2013). Exergy, Energy, Environment and Sustainable Development, First ed.: Elsevier.
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Fauklker, L., & de Saouza-Santos, M. L. (2010). Solid Fuels Combustion and Gasification. Second Edition,
CRC Press.
Kotas, T. J. (1980). Exergy concepts for thermal plant: First of two papers on exergy techniques in thermal plant
analysis. International Journal of Heat and Fluid Flow, 2(3);105-114.
Loo, S. V., & Koppejan, J. (2008). The Handbook of Biomass Combustion and Co-firing. London: Earthscan.
Ozturk, M., Bezir, N. C., & Ozek, N. (2008). Energy Market Structure of Turkey. Energy Sources Part B. 3,
384-395.
Ozturk, M., Bezir, N. C., & Ozek, N. (2009). Hydropower-Water and Renewable Energy in Turkey: Sources and
Policy. Renewable and Sustainable Energy Reviews, 13, 605-615.
Ozturk, M., Ozek, N., & Yuksel, Y. E. (2011). Energetic and Exergetic Performance Assessment of Some Coals
in Turkey for Gasification Process. International Journal of Exergy, 8(3), 297-309.
Rosen, M. A. (1986). The development and application of a process analysis methodology and code based on
exergy, cost, energy and mass, Toronto: University of Toronto.
Szargut, J. (2005). Exergy Method: Technical and Ecological Applications, Southhampton, U.K: WIT Press.
Szargut J., Morris D.R., & Steward F.R. (1988). Exergy Analysis of Thermal,Chemical, and Metallurgical
Processes, New York: John Benjamins Publishing Co.
Toonssen, R., Woudstra, N., & Verkooijen, A. H. M. (2008). Exergy Analysis of Hydrogen Production Plants
Based on Biomass Gasification‖, International Journal of Hydrogen Energy, 33, 4074–4082.
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2527
Title
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INVESTIGATION OF A BIOMASS GASIFICATION SYSTEM BASED ON ENERGY AND EXERGY ANALYSIS
Author
Author
KOCER, Abbas Alpaslan
YUKSEL, Yunus Emre
OZTURK, Murat
Abstract
A summary of the resource.
Biomass gasification procedure is a very complex process and it is influenced by many physical and chemical factors such as biomass gasification temperature and gasifier type. Thermodynamic assessment methodology based on the energy and exergy analysis can be used to evaluate the system performance and environmental impacts. In this paper, thermodynamic analysis of the biomass gasification system is given for the whole system and its components. The parametric studies reveal the effects of design and operating indicators on the exergy efficiency and exergy destruction rate. The result shows that the gasification temperatures for the biomass gasification system change significantly with the type of the gasifying medium. Keywords: Biomass gasification, energy analysis, exergy analysis, parametric study.
Publisher
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International Burch University
Date
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2014-05-15
Keywords
Keywords.
Article
PeerReviewed
Identifier
An unambiguous reference to the resource within a given context
ISSN 978-9958-834-36-3
Q Science (General),QH301 Biology,QH426 Genetics
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https://omeka.ibu.edu.ba/files/original/5a6220379fdbb063f4036eb11f77ebd2.pdf
3c35b51e209db25e4d76aff6984ce7d6
PDF Text
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BIOINFORMATICS TOOLS FOR GENE LIST ANALYSIS
Imer Muhović*, Larisa Bešić, Adna Ašić, Serkan Dogan, Osman Doluca
International Burch University, Department of Genetics and Bioengineering
*Corresponding author: imer91@gmail.com
ABSTRACT
The advent of the era of high-throughput sequencing has brought a wealth of biological data
to researchers, but the vastness of the available data has created a demand for tools that could
be used to analyze it. One such type of tools are gene set analysis tools, that take a list of
genes that were found to be up or down regulated during an experiment. For the sake of
simplicity this review focuses solely on freely available web based tools that have been
published or have undergone significant updates in the last 5 years. This review is meant to
assist tool developers to better understand the needs of the end-users, and in it we look at the
currently available gene list analysis tools, their strengths and weaknesses, and offer
suggestions for their improvement.
Key words: microarray, gene set, systems biology, enrichment, gene ontology
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INTRODUCTION
Many modern molecular biology experiments result in the production of a list of important
molecules. These molecules may be up/down regulated genes obtained from microarray or
RNA-seq experiments, or a list of SNP – containing genes. The issue that is created by such
lists is in the length of them. Your average co-expression experiment results in a list of
hundreds or thousands of „interesting“ genes, and determining the biological significance of
such a list is very difficult, as it requires either significant knowledge about the metabolic
process being investigated, or it requires the researcher to conduct an extensive literature
search to answer questions such as „What does this gene do? Where is it expressed? Does it
interact with other genes? Is it linked to a particular disorder?“ Manually performing such a
task would be time consuming and tedious, costing the researcher precious time and resources.
To save the time and sanity of researchers undertaking such experiments various tools for
annotation enrichment (also known as pathway analysis) have been developed. These tools
map genes and proteins to their associated biological annotations (gene Ontology terms, or
pathway membership) and then compare the frequency of such terms in the given gene list,
with a background list to identify the over expressed, or under expressed terms in the list,
following the assumption that such terms are important to the metabolic process that is being
studied. As an example, imagine that in a list obtained by a microarray experiment, 20% of
the genes are tumor suppressor genes, while in a „normal“ tissue only 5% are. By using
standard statistical method we can determine that tumor suppressor genes are enriched in this
list, and therefore play an important role in the biological process we are investigating.
Most review articles in this field divide tools according to the statistical method that they use.
There are three most common ones: Singular Enrichment Analysis (SEA), Gene set
enrichment analysis (GSEA), and modular enrichment analysis (MEA).(Huang, Sherman, &
Lempicki, 2009)
SEA – compares annotation terms one by one with a list of interesting genes for enrichment.
A p-value for enrichment is obtained by comparing the frequency of an annotation term with
the frequency of that term appearing by chance. All terms that are beyond the cut-off value
are said to be enriched. The drawback of this approach is that it ignores the hierarchical
relationship between GO terms, and results in large lists of enriched terms due to the fact that
it treats similar terms as though they were unique.
GSEA – these methods take as an input not only the list of interesting (up or down regulated
genes) but all of the genes obtained by an experiment. It functions best in experiments in
which two tissue types are compared, because it requires a quantitative value (change in
differential expression) for each gene in order to rank them by significant enrichment. A so
called maximum enrichment score (MES) is calculated from the ranked list of genes in an
annotation category, and enrichment p-values are determined by comparing the MES of the
term to a randomly generated MES distribution. To put it in simpler terms, GSEA determines
if genes that share a biological annotation (for example belong to the same pathway) are
randomly distributed in the gene list (and therefore not significantly attributing to a change in
phenotype), or if they are overrepresented in a part of the list (top or bottom, according to fold
change, or differential expression), which would indicate that they play a role in the pathway
that is being studied.(Subramanian et al., 2005)
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MEA – seeks to use the relationships between different annotation terms to remove the
redundancy, or underrepresentation of important terms that may be caused by SEA and GSEA
methods. They seek to improve sensitivity and specificity by using composite annotation
terms. The issue with them may be found if they use only a single information source, usually
GO.
Most current tools seem to have switched to using MEA as opposed to SEA, as the link
between different levels of annotation has become clearer, and the integration of different
databases has become easier.
Molecular interaction network present the easiest, most intuitive way of representing such
large and complex datasets, and several curated databases already exist that link all known
binary protein interactions, as well as enrichment data, whether extracted from literature of
HT experiments.
DATABASES
To better study and keep track of all known pathway data several databases have been
constructed. A key difference between databases lays in their data acquisition methods. We
can separate curated databases from automatic ones; by the way the data are added in the
database, either by trained experts or via automatic methods.
Each has its own advantages, shallow curated databases have larger network coverage, while
curated ones have higher quality of data, but still data capture errors such as false positives in
the data still can't be excluded.
Another difference is the data source, as some databases take their data from peer reviewed
literature, while secondary databases look to integrate primary databases and thus become a
one-stop shop for all your protein interaction needs.
One we have a list of PPI interactions we need methods to visualize this data and extract the
useful data from them. Due to the large number of PPIs in a possible network the results
usually look like a giant ball of yarn that is difficult to interpret so visualization techniques
offered by the tool play an important role.
H-InvDB (http://www.h-invitational.jp/) is a human gene database first published in 2004.It
contains 244,709 human DNA sequences, and provides the user with a broad variety of tools
for genome analysis. According to the authors analysis 19,309 annotated genes were found to
be specific to H-InvDB and not to be found in RefSeq or Ensembl.(Takeda et al., 2012)
PINA (The Protein Interaction Network Analysis) is an integrative resource that combines
data from six manually curated public databases, and offers a set of tools for network
construction, filtering, analysis and visualization. It offers protein-protein interaction (PPI)
network construction, by clustering approaches from an interactome constructed for six
available model organisms. All identified terms are annotated using GO terms, KEGG
pathways, Pfam domains and MsigDB data.(Cowley et al., 2011)
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STRING is a database that seeks to provide biologists with a global perspective on as many
interactions from as many organisms as possible. It scores both known and predicted
interactions, and offers the users tools for statistical analysis and enrichment analysis of
queried terms.(Franceschini et al., 2012)
GeneSigDB (http://www.genesigdb.org or http://compbio.dfci.harvard.edu/genesigdb/) is a
database of gene signatures collected manually from published literature, focusing on cancer
studies, as well as immune cells, stem cells and lung disease. It is an excellent tool for
prognostic analysis of cancer and related diseases, or use as an gene set enrichment tool. The
visualization of enriched terms is performed via heatmap that provides us with publicationquality images, and GeneSigDB allows us to download data in .gmt file format that can be
later used for additional gene set enrichment analysis.(Culhane et al., 2011)
IntAct is an open-source, molecular interaction database that contains data manually curated
from literature or raw depositions. It has two levels of curation, and contains around 275 000
interactions, collected from over 5000 publications. A recent upgrade has brought it a visual
display of data, which are downloadable in multiple formats.(Kerrien et al., 2011)
The MetaCyc database (http://metacyc.org/) is a freely accessible resource that contains data
from metabolic pathways and enzymes from all domains of life. MetaCyc pathway data is
obtained experimental and small-molecule metabolic pathways and are curated from the
primary scientific literature. Currently there are more than 1800 pathways derived from over
30 000 publications, making MetaCyc the largest curated collection of metabolic pathways.
(Caspi et al., 2011)
IPAVS (Integrated Pathway Resources, Analysis and Visualization System) is a manually
curated database of known protein pathways. It combines several publicly available pathway
databases, and provides the tools to filter search and analyze biological pathways. It is freely
available, interactive and integrated pathway database which is designed to address the needs
of bench biologists, computational biologists and physicians. It offers biologists a single point
of access to several manually curated pathway resources, in addition to its own expert-curated
pathways that are in standard format. (Sreenivasaiah, Rani, Cayetano, Arul, & Kim, 2011)
NETWORK CLUSTERING
Proteins are usually represented as nodes, and interactions as vertices, giving us a ball and
stick model of interactions. One of the main aims of pathway analysis strategies is to discover
clusters of proteins that perform a similar function. This is mostly done by network topology
as highly interconnected nodes form clusters, and the basic assumption is that clusters identify
proteins that share a common function. Issues that may arise from analyzing pathways in this
fashion is that large networks tend to resemble balls of yarn, due to having hundreds of nodes
and vertices, thus making the inference of biological data from them very hard, and confusing.
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Annotation of nodes and edges is usually needed to make some sense of the information
found in PPINs. The annotations may include info about the method by which the interaction
was detected, some confidence scores and similar parameters. Gene Ontology project is the
most widely used source of extra information that can be used in network analysis. It's creates
a hierarchical list of terms called Ontologies that covers three independent biological domains:
1 - Cellular Components 2 - Biological Processes 3- Molecular Function.(Ashburner et al.,
2000)
This enables us to highlight the proteins that perform the same function, thus allowing a
functional representation of a network, usually GO is combined with cluster detection to
provide greater interpretation of a network.
GENE LIST ANALYSIS TOOLS
Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool
Enrichr is a web based tool that takes in as an input a list of differentially expressed genes,
and produces lists of enriched terms. The authors have solved the issues that arise when using
only one source of enrichment data, by using 35 gene set libraries split into six groups, with
each containing different data about different enrichment terms. It uses
1) ChEA (The ChIP-x Enrichment Analysis Database), it’s own resource of putative
transcription factor targets created from publications that report experiments of profiling
mammalian DNA binding transcription factors. ;
2) position weight matrices (PWMs) from TRANSFAC and JASPAR ; that were used to scan
all promoter regions (-2000 to +500 from the start of transcription) of all human genes, they
kept all 100% matches to the consensus sequence between a factor and a target gene.
3) target genes generated from PMWs downloaded from the UCSC genome browser , because
it produces different results compared to the ones mentioned above
4) transcription factor targets extracted from the ENCODE project . In addition, the two other
gene-set libraries in the transcription category are gene sets associated with:
5) histone modifications extracted from the Roadmap Epigenomics Project ; and
6) microRNAs targets computationally predicted by TargetScan .
It provides three different statistical measures of the results, of which one is the Fischer exact
test, the other an in-house variation and last a combination of the two. The authors performed
a quality evaluation of these methods in their original paper. Enrichr provides many different
options for visualizing the data, one of which is a grid of squares, with the most enriched
elements being colored more brightly when compared to the rest. It also allows the
visualization in the form of a list of enriched terms, bar graph, network and table.
An advantage of Enrichr over other programs of the same type is it’s availability and modern
design, it’s available as a mobile application for smartphones and tablets, and the webinterface is clear, and intuitive. The authors tested the software by comparing nine cancer cell
lines and found an upregulation in the PRC2 polycomb group target genes.(Chen et al., 2013)
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Network2Canvas is a network visualization program that makes it easier to visualize large
protein-protein interaction networks, and enrichment terms. The most common issue with
using ball and stick models of PPI networks is that larger networks tend to end up looking like
balls of yarn, making it very difficult to visually analyze the properties of the network.
Network2Canvas works around this issue by placing the nodes on a square toroidal canvas,
the nodes are then clustered on the canvas via simulated annealing in order to have the
maximum number of local connections, and their brightness is set to correspond to the local
fitness of the node.
This software takes as input a list of differentially expressed genes, or a list of drugs and
outputs a set of enriched terms including drug side effects, common pathways etc. The
website is accompanied by a video tutorial on how to use the program, and offers a variety of
possible canvases, for example Kinase Enrichment Analysis or KEGG pathways, and more.
Overall N2C is a very useful and intuitive tool for molecular data analysis, especially for
larger lists of genes or drugs.(Tan, Chen, Dannenfelser, Clark, & Ma’ayan, 2013)
Genes2FAN: Proteins interaction studies are mostly done by analyzing binary protein
interactions, but these are not the only ways two genes, or their protein products can interact.
The authors of this program used knowledge on the shared properties of genes from diverse
sources to create functional association networks (FANs), to allow researchers to identify
additional interactions between groups of genes, which are not immediately obvious from PPI
networks.
G2F uses a database of 14 FANs, and large scale PPI networks to create subnetworks that can
connect lists of human and mouse genes. Lists of genes are taken as an input to produce a
subnetwork, using a ranked list of intermediate genes that connect the genes from the queried
list. This web application offers a powerful new approach to analyzing gene associations, as it
can find the intermediate parts of a pathway, and thus allow us to observe a greater, clearer
picture of a molecular process.(Dannenfelser, Clark, & Ma’ayan, 2012)
Sets2Network is a tool created to allow the creation of interaction networks by analyzing the
co-occurrence of entities in related sets. It gives us a general method for inferring networks by
repeated observation of sets of related terms. It interprets the frequency of the occurrence of
the link as the probability that it is present in the real-world network.
This tool has usages outside the realm of biology, as it can create a network from any file
given in the GMT (Gene Matrix Transpose) format, for example it can be used to create a
network of co-authorship by taking in a GMT file of publications and authors, or predict
direct PPI from HT MS data. (Clark, Dannenfelser, Tan, Komosinski, & Ma’ayan, 2012, p. 2)
S2N can output the data in various formats, so subsequent analysis can be performed on the
data, using additional visualization tools such as yEd.
DAVID (Database for Annotation, Visualization and Integrated Discovery, available at
http://david.abcc.ncifcrf.gov/) is one of the oldest and most well-known web-based
bioinformatics resources for the functional interpretation of gene/protein lists. It has been
cited over 6000 times since its initial publication. It takes inputs in list form and allows the
user to perform gene-term enrichment analysis, visualization of the gene-term relationships,
search for related genes, pathway analysis and much more. They have recently published
DAVID-WS (Web service) an API (application programming interface) which allows for the
programmatic automation of requests to DAVID, and thus the easier automation of tasks,
without the need for human interactions.(Jiao et al., 2012)
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EnrichNet is a web-based tool created in order to address the current limitations of gene set
analysis tools. Most GSA tools use the over-representation-based enrichment analysis method
which uses the overrepresentation of a gene list of interest in a reference list via a statistical
test (usually Fisher’s exact test) as proof of biological significance. The issue with this
approach is that it low power of discrimination, and significant variance with changes in
overlap size, among others. EnrichNet uses an graph-based statistic approach to analyze gene
sets, via exploiting information from molecular network structures of, and offers interactive
visualization of network sub-structures. It offers integrated data sources (molecular interaction
data, pathway and tissue-specific gene expression data) and uses graph-based statistical
analysis and forced – directed layout generation to provide a clearer and more detailed
understanding of the gene set interactions. It uses a minimalist interface, with clear output,
and we refer the reader to the paper for more information.(Glaab, Baudot, Krasnogor,
Schneider, & Valencia, 2012)
GeneCodis is a tool for enrichment analysis, available since 2007, its newest version offers a
more concise output and removes some redundancy, via summarizing of significantly
enriched terms, they also expanded the original application, by adding new sources of
information, such as genetic diseases, gene-drug interactions and PUBMED information.
GeneCodis offers a very customizable input, as it integrates data from several organisms,
which is rather rare as most of the enrichment analysis tools focus only on humans. Its
capable of filtering the output.(Tabas-Madrid, Nogales-Cadenas, & Pascual-Montano, 2012)
GeneMANIA (http://www.genemania.org) is a web-app for gene list analysis. Given a list, it
will extend it with functionally similar genes, obtained from genomics and proteomics
databases. It’s capable of finding genes of similar function, and those that are most likely to
interact with the ones in the list. It supports multiple organisms, and integrates hundreds of
datasets from GEO, BioGRID, IRefIndex and I2D.(Zuberi et al., 2013)
Graphite Web: A new web-app for pathway analysis and visualization, that takes as input
gene lists from microarray or RNA-seq experiments. It combines topological methods with
multivariate pathway analyses and provides a clear network visualization tool, for efficient
interpretation of expression experiment results. It works with three model organisms, and
integrates two pathway databases.(Sales, Calura, Martini, & Romualdi, 2013)
CONCLUSION
While new tools are constantly arriving they individually don’t see too much use or
recognition, this may be due to low popularity, or just being hard to find. This lack of
visibility makes it hard for researchers to test out new tools, as they rarely know that they
even exist, and this leads to a lack of feedback for the tool makers, which in turn leads to a
lack of improvement in the available tools. The usage of targeted internet marketing to
possible users should be considered by future tool makers as a way of reaching out to new
users, and obtaining feedback on their work. The current focus of enrichment analysis should
probably be turned over to better visualization of datasets, as the ball and stick models are
prone to looking like a ball of yarn if the input list is too large. Better visualization of data
will allow for much easier analysis, and comprehension of experimental results.
API support is another issue, as most of the tools listed in this review rely on manual input of
data, DAVID-WS is a nice exception to the rule. APIs could allow for easier testing and
automation of enrichment analysis tools, thus simplifying and speeding up a biologist’s
workflow.
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Standardization is another issue encountered in the use of these tools, as few of them support
multiple formats of output files, while exception do exist, they are few and mostly consist of
older, more established tools. While some tools do offer advantages over others, there exists
no gold standard for enrichment analysis, with labs using whichever tools they prefer, this
makes it hard to gauge the effectiveness of an approach, as only by repeat usage do the
advantages of a tool become clearly apparent.
While we have covered some integrative tools, none of them offers the full package, a modern
enrichment analysis tool should offer a customizable input, output, network visualization,
different scoring systems, multiple output formats, and allow for publication quality images.
The closest we have come to this are the tools from Maya’an Labs (Enrichr, S2N, N2L etc.),
which provide a wide array of functionality, but still aren’t seeing much use.
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Imer Muhović is a MSc student at the International Burch University. His main interests lie
in bioinformatics and systems biology, and he is currently in the process of constructing a
novel bioinformatics tool for sequence analysis, which will form his Master’s thesis.
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Dublin Core
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Extent
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2450
Title
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BIOINFORMATICS TOOLS FOR GENE LIST ANALYSIS
Author
Author
MUHOVIĆ, Imer
BEŠIĆ, Larisa
AŠIĆ, Adna
DOGAN, Serkan
DOLUCA, Osman
Abstract
A summary of the resource.
The advent of the era of high-throughput sequencing has brought a wealth of biological data to researchers, but the vastness of the available data has created a demand for tools that could be used to analyze it. One such type of tools are gene set analysis tools, that take a list of genes that were found to be up or down regulated during an experiment. For the sake of simplicity this review focuses solely on freely available web based tools that have been published or have undergone significant updates in the last 5 years. This review is meant to assist tool developers to better understand the needs of the end-users, and in it we look at the currently available gene list analysis tools, their strengths and weaknesses, and offer suggestions for their improvement. Key words: microarray, gene set, systems biology, enrichment, gene ontology
Publisher
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International Burch University
Date
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2014-05-15
Keywords
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Article
PeerReviewed
Identifier
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ISSN 978-9958-834-36-3
Q Science (General),QH301 Biology,QH426 Genetics