Search results for: recursive least square identification

Authors: Marjan Moradi Fard, Hossein Rassi, Masoud Houshmand

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Aim: Breast cancer is one of the most common cancers affecting the morbidity and mortality of Iranian women. This disease is a result of collective alterations of oncogenes and tumor suppressor genes. Studies have produced conflicting results concerning the role of p53 codon 72 polymorphism (G>C) and miR-146a rs2910164 polymorphism (G>C) on the risk of several cancers; therefore, a research was performed to estimate the association between the p53 codon 72 polymorphism and miR-146a rs2910164 polymorphism in breast cancer. Methods and Materials: A total of 45 archival breast cancer samples from khatam hospital and 40 healthy samples were collected. Verification of each cancer reported in a relative was sought through the pathology reports of the hospital records. Then, DNA extracted from all samples by standard methods and p53 codon 72 polymorphism genotypes and miR-146a rs2910164 polymorphism genotypes were analyzed using multiplex PCR. The tubules, mitotic activity, necrosis, polymorphism and grade of breast cancer were staged by Nottingham histological grading and immunohistochemical staining of the sections from the paraffin wax embedded tissues for the expression of ER, PR and p53 was carried out using a standard method. Finally, data analysis was performed using the 7 version of the Epi Info(TM) 2012 software and test chi-square(x2) for trend. Results: Successful DNA extraction was assessed by PCR amplification of b-actin gene (99 bp). According to the results, p53 GG genotype and miR-146a rs2910164 CC genotype was significantly associated with increased risk of breast cancer in the study population. In this study, we established that tumors of p53 GG genotype and miR-146a rs2910164 CC genotype exhibited higher mitotic activity, higher polymorphism, lower necrosis, lower tubules, higher ER- and PR-negatives and lower TP53-positives than the other genotypes. Conclusion: The present study provided preliminary evidence that a p53 GG genotype may effect breast cancer risk in the study population, interacting synergistically with miR-146a rs2910164 CC genotype. Our results demonstrate that the testing of p53 codon 72 polymorphism genotypes and miR-146a rs2910164 polymorphism genotypes in combination with clinical parameters can serve as major risk factors in the early identification of breast cancers.

Keywords: breast cancer, p53 codon 72 polymorphism, miR-146a rs2910164 polymorphism, genotypes

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Authors: Muhammad Ali Syed, Arshad Saleem Bhatti, Chen-zhong Li, Habib Ali Bokhari

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Surface plasmon resonance (SPR) biosensors have emerged as a promising technique for bioanalysis as well as microbial detection and identification. Real time, sensitive, cost effective, and label free detection of biomolecules from complex samples is required for early and accurate diagnosis of infectious diseases. Like many other types of optical techniques, SPR biosensors may also be successfully utilized for microbial detection for accurate, point of care, and rapid results. In the present study, we have utilized a commercially available automated SPR biosensor of BI company to study the microbial detection form water samples spiked with different concentration of Staphylococcus aureus bacterial cells. The gold thin film sensor surface was functionalized to react with proteins such as protein G, which was used for directed immobilization of monoclonal antibodies against Staphylococcus aureus. The results of our work reveal that this immunosensor can be used to detect very small number of bacterial cells with higher sensitivity and specificity. In our case 10^3 cells/ml of water have been successfully detected. Therefore, it may be concluded that this technique has a strong potential to be used in microbial detection and identification.

Keywords: surface plasmon resonance (SPR), Staphylococcus aureus, biosensors, microbial detection

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Authors: Ahmed Abdullah Ahmed

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The task of recognizing the writer of a handwritten text has been an attractive research problem in the document analysis and recognition community with applications in handwriting forensics, paleography, document examination and handwriting recognition. This research presents an automatic method for writer recognition from digitized images of unconstrained writings. Although a great effort has been made by previous studies to come out with various methods, their performances, especially in terms of accuracy, are fallen short, and room for improvements is still wide open. The proposed technique employs optimal codebook based writer characterization where each writing sample is represented by a set of features computed from two codebooks, beginning and ending. Unlike most of the classical codebook based approaches which segment the writing into graphemes, this study is based on fragmenting a particular area of writing which are beginning and ending strokes. The proposed method starting with contour detection to extract significant information from the handwriting and the curve fragmentation is then employed to categorize the handwriting into Beginning and Ending zones into small fragments. The similar fragments of beginning strokes are grouped together to create Beginning cluster, and similarly, the ending strokes are grouped to create the ending cluster. These two clusters lead to the development of two codebooks (beginning and ending) by choosing the center of every similar fragments group. Writings under study are then represented by computing the probability of occurrence of codebook patterns. The probability distribution is used to characterize each writer. Two writings are then compared by computing distances between their respective probability distribution. The evaluations carried out on ICFHR standard dataset of 206 writers using Beginning and Ending codebooks separately. Finally, the Ending codebook achieved the highest identification rate of 98.23%, which is the best result so far on ICFHR dataset.

Keywords: off-line text-independent writer identification, feature extraction, codebook, fragments

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Authors: Raquel Rossini, Edelvais Caldeira

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The aim of this work is to investigate the motivation for the metaphorical uses of two verb combinations: come out and take over. Drawing from cognitive semantics theories, image schemas and metaphors, it was attempted to demonstrate that: a) the metaphorical senses of both 'come out' and 'take over' extend from both the verbs and the particles central (spatial) senses in such verb combinations; and b) the particles 'out' and 'over' also contribute to the whole meaning of the verb combinations. In order to do so, a random selection of 579 concordance lines for come out and 1,412 for take over was obtained from the Corpus of Contemporary American English – COCA. One of the main procedures adopted in the present work was the establishment of verb and particle central senses. As per the research questions addressed in this study, they are as follows: a) how does the identification of trajector and landmark help reveal patterns that contribute for the identification of the semantic network of these two verb combinations?; b) what is the relationship between the schematic structures attributed to the particles and the metaphorical uses found in empirical data?; and c) what conceptual metaphors underlie the mappings from the source to the target domains? The results demonstrated that not only the lexical verbs come and take, but also the particles out and over play an important whole in the different meanings of come out and take over. Besides, image schemas and conceptual metaphors were found to be helpful in order to establish the motivations for the metaphorical uses of these linguistic structures.

Keywords: cognitive linguistics, English syntax, multi-word verbs, prepositions

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Authors: A. Anbu Raj, V. Mugendiren

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Sheet metal forming is a vital manufacturing process used in automobile, aerospace, agricultural industries, etc. Incremental forming is a promising process providing a short and inexpensive way of forming complex three-dimensional parts without using die. The aim of this research is to study the forming behaviour of AA 5052, Aluminium Alloy, using incremental forming and also to study the FLD of cone shape AA 5052 Aluminium Alloy at room temperature and various annealing temperature. Initially the surface roughness and wall thickness through incremental forming on AA 5052 Aluminium Alloy sheet at room temperature is optimized by controlling the effects of forming parameters. The central composite design (CCD) was utilized to plan the experiment. The step depth, feed rate, and spindle speed were considered as input parameters in this study. The surface roughness and wall thickness were used as output response. The process performances such as average thickness and surface roughness were evaluated. The optimized results are taken for minimum surface roughness and maximum wall thickness. The optimal results are determined based on response surface methodology and the analysis of variance. Formability Limit Diagram is constructed on AA 5052 Aluminium Alloy at room temperature and various annealing temperature by using optimized process parameters from the response surface methodology. The cone has higher formability than the square pyramid and higher wall thickness distribution. Finally the FLD on cone shape and square pyramid shape at room temperature and the various annealing temperature is compared experimentally and simulated with Abaqus software.

Keywords: incremental forming, response surface methodology, optimization, wall thickness, surface roughness

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Authors: Kuldeep Rawat, Michael O'Shea, Maureen McGough

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The paper will discuss a National Institute of Justice (NIJ) funded project to provide cost-effective aviation technologies and research to support counter-poaching operations related to endangered, protected, and/or regulated wildlife. The goal of this project is to provide cost-effective aviation technology and research support to Kenya Wildlife Service (KWS) in their counter-poaching efforts. In pursuit of this goal, Elizabeth City State University (ECSU) is assisting the National Institute of Justice (NIJ) in enhancing the Kenya Wildlife Service’s aviation technology and related capacity to meet its counter-poaching mission. Poaching, at its core, is systemic as poachers go to the most extreme lengths to kill high target species such as elephant and rhino. These high target wildlife species live in underdeveloped or impoverished nations, where poachers find fewer barriers to their operations. In Kenya, with fifty-nine (59) parks and reserves, spread over an area of 225,830 square miles (584,897 square kilometers) adequate surveillance on the ground is next to impossible. Cost-effective aviation surveillance technologies, based on a comprehensive needs assessment and operational evaluation, are needed to curb poaching and effectively prevent wildlife trafficking. As one of the premier law enforcement Air Wings in East Africa, KWS plays a crucial role in Kenya, not only in counter-poaching and wildlife conservation efforts, but in aerial surveillance, counterterrorism and national security efforts as well. While the Air Wing has done, a remarkable job conducting aerial patrols with limited resources, additional aircraft and upgraded technology should significantly advance the Air Wing’s ability to achieve its wildlife protection mission. The project includes: (i) Needs Assessment of the KWS Air Wing, to include the identification of resources, current and prospective capacity, operational challenges and priority goals for expansion, (ii) Acquisition of Low-Cost Aviation Technology to meet priority needs, and (iii) Operational Evaluation of technology performance, with a focus on implementation and effectiveness. The Needs Assessment reflects the priorities identified through two site visits to the KWS Air Wing in Nairobi, Kenya, as well as field visits to multiple national parks receiving aerial support and interviewing/surveying KWS Air wing pilots and leadership. Needs Assessment identified some immediate technology needs that includes, GPS with upgrades, including weather application, Night flying capabilities, to include runway lights and night vision technology, Cameras and surveillance equipment, Flight tracking system and/or Emergency Position Indicating Radio Beacon, Lightweight ballistic-resistant body armor, and medical equipment, to include a customized stretcher and standard medical evacuation equipment. Results of this assessment, along with significant input from the KWS Air Wing, will guide the second phase of this project: technology acquisition. Acquired technology will then be evaluated in the field, with a focus on implementation and effectiveness. Results will ultimately be translated for any rural or tribal law enforcement agencies with comparable aerial surveillance missions and operational environments, and jurisdictional challenges, seeking to implement low-cost aviation technology. Results from Needs Assessment phase, including survey results and our ongoing technology acquisition and baseline operational evaluation will be discussed in the paper.

Keywords: aerial surveillance mission, aviation technology, counter-poaching, wildlife protection

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Authors: Anupuma Raina, Ajay P. Balayan, Prateek Pandya, Pankaj Shrivastava, Uma Kanga, Tulika Seth

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DNA fingerprinting analysis aids in personal identification for forensic purposes and has always been a driving motivation for law enforcement agencies in almost all countries since its inception. The introduction of DNA markers (Y-STR) has allowed for greater precision and higher discriminatory power in forensic testing. A criminal/ person committing crime after bone marrow transplantation is a rare situation but not an impossible one. Keeping such a situation in mind, a study was carried out to find out the best biological sample to be used for personal identification, especially in forensic situation. We choose a female patient (recipient) and a male donor. The pre transplant sample (blood) and post transplant samples (blood, buccal swab, hair roots) were collected from the recipient (patient). The same were compared with the blood sample of the donor using DNA FP technique. Post transplant samples were collected at different interval of time (15, 30, 60, and 90 days). The study was carried out using Y-STR kit at 23 loci. The results determined discusses the phenomenon of chimerism and its impact on Y-STR. Hair sample was found the most suitable sample which had no donor DNA profiling up to 90 days.

Keywords: bone marrow transplantation, chimerism, DNA profiling, Y-STR

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Authors: Zahra khaksari, Mahboobeh Mehrabi

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One of the biggest health problems in communities, suicide is now one of the top ten causes of death in the world. This study aimed to investigate the risk factors of suicide attempt in Minab city over two years. This was a descriptive and cross-sectional study. Subjects of this study were cases who admitted in Hazrat Abolfazl hospital of minab city over two years Since the beginning of 1389 to end of 1390. During this period,their cases were reviewed. To analyze data, descriptive statistics was applied. During this two-year period, 275 patients who had attempted suicide, of which 65 percent are female and most of them were 15-24 years. 60% of them were single and 70 % of rural areas. 51% of suicides in 1390 and most of the suicide attempts occurred at a rate of 37 percent in summer. and the most common way of attempting suicide was medication poisoning (74%). The suicide rate leading to death was 1.5% The chi-square test showes that there were significant relationship between suicide by gender and residence status. This means that more women are committing suicide of rural areas.based on The chi-square test there were significant relation between the gender and method, gender and the result of suicide and means that more women than men commit suicide with the use of drugs. Males were more successful suicide. who had attempted with organophosphates and hanging were more successful in suicide. The finding of the current study showed that most of the suicide victims were female ,rural deweller,14-24 years old,single, serious attention must be paid to the problems of this group. It also extends the field of education professionals and health centers, and psychological therapy that focuses specifically on this topic.

Keywords: attempt to suicide, minab, risk factors, suicide

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Authors: Najlae Bendou, Jean-Jacques Lilti, Khalid Elbadraoui

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In this paper, we examine stock market integration of emerging markets around the global financial turmoil of 2007-2008. Following Pukthuanthong and Roll (2009), we measure the integration of 46 emerging countries using the adjusted R-square from the regression of each country's daily index returns on global factors extracted from the covariance matrix computed using dollar-denominated daily index returns of 17 developed countries. Our sample surrounds the global financial crisis and ranges between 2000 and 2018. We analyze results using four cohorts of emerging countries: East Asia & Pacific and South Asia, Europe & Central Asia, Latin America & Caribbean, Middle East & Africa. We find that the level of integration of emerging countries increases at the commencement of the crisis and during the booming phase of the business cycles. It reaches a maximum point in the middle of the crisis and then tends to revert to its pre-crisis level. This pattern tends to be common among the four geographic zones investigated in this study. Finally, we investigate the determinants of stock market integration of emerging countries in our sample using panel regressions. Our results suggest that the degree of stock market integration of these countries should be put into perspective by some macro-economic factors, such as the size of the equity market, school enrollment rate, international liquidity level, stocks traded volume, tax revenue level, imports and exports volumes.

Keywords: correlations, determinants of integration, diversification, emerging markets, financial crisis, integration, markets co-movement, panel regressions, r-square, stock markets

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Authors: D. P. Houhoula, J. Papaparaskevas, S. Konteles, A. Dargenta, A. Farka, C. Spyrou, M. Ziaka, S. Koussisis, E. Charvalos

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Objectives: Nanotechnology is providing revolutionary opportunities for the rapid and simple diagnosis of many infectious diseases. Staphylococcus aureus, Listeria monocytogenes and Salmonella enteritis are important human pathogens. Diagnostic assays for bacterial culture and identification are time consuming and laborious. There is an urgent need to develop rapid, sensitive, and inexpensive diagnostic tests. In this study, a gold nanoprobe strategy developed and relies on the colorimetric differentiation of specific DNA sequences based approach on differential aggregation profiles in the presence or absence of specific target hybridization. Method: Gold nanoparticles (AuNPs) were purchased from Nanopartz. They were conjugated with thiolated oligonucleotides specific for the femA gene for the identification of members of Staphylococcus aureus, the mecA gene for the differentiation of Staphylococcus aureus and MRSA Staphylococcus aureus, hly gene encoding the pore-forming cytolysin listeriolysin for the identification of Listeria monocytogenes and the invA sequence for the identification of Salmonella enteritis. DNA isolation from Staphylococcus aureus Listeria monocytogenes and Salmonella enteritis cultures was performed using the commercial kit Nucleospin Tissue (Macherey Nagel). Specifically 20μl of DNA was diluted in 10mMPBS (pH5). After the denaturation of 10min, 20μl of AuNPs was added followed by the annealing step at 58oC. The presence of a complementary target prevents aggregation with the addition of acid and the solution remains pink, whereas in the opposite event it turns to purple. The color could be detected visually and it was confirmed with an absorption spectrum. Results: Specifically, 0.123 μg/μl DNA of St. aureus, L.monocytogenes and Salmonella enteritis was serially diluted from 1:10 to 1:100. Blanks containing PBS buffer instead of DNA were used. The application of the proposed method on isolated bacteria produced positive results with all the species of St. aureus and L. monocytogenes and Salmonella enteritis using the femA, mecA, hly and invA genes respectively. The minimum detection limit of the assay was defined at 0.2 ng/μL of DNA. Below of 0.2 ng/μL of bacterial DNA the solution turned purple after addition of HCl, defining the minimum detection limit of the assay. None of the blank samples was positive. The specificity was 100%. The application of the proposed method produced exactly the same results every time (n = 4) the evaluation was repeated (100% repeatability) using the femA, hly and invA genes. Using the gene mecA for the differentiation of Staphylococcus aureus and MRSA Staphylococcus aureus the method had a repeatability 50%. Conclusion: The proposed method could be used as a highly specific and sensitive screening tool for the detection and differentiation of Staphylococcus aureus Listeria monocytogenes and Salmonella enteritis. The use AuNPs for the colorimetric detection of DNA targets represents an inexpensive and easy-to-perform alternative to common molecular assays. The technology described here, may develop into a platform that could accommodate detection of many bacterial species.

Keywords: gold nanoparticles, pathogens, nanotechnology, bacteria

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Authors: Biruhi Tesfaye, Avinash M. Potdar

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The laboratory test process to determine the California bearing ratio (CBR) of black cotton soils is not only overpriced but also time-consuming as well. Hence advanced prediction of CBR plays a significant role as it is applicable In pavement design. The prediction of CBR of treated soil was executed by Artificial Neural Networks (ANNs) which is a Computational tool based on the properties of the biological neural system. To observe CBR values, combined eggshell and waste glass was added to soil as 4, 8, 12, and 16 % of the weights of the soil samples. Accordingly, the laboratory related tests were conducted to get the required best model. The maximum CBR value found at 5.8 at 8 % of eggshell waste glass powder addition. The model was developed using CBR as an output layer variable. CBR was considered as a function of the joint effect of liquid limit, plastic limit, and plastic index, optimum moisture content and maximum dry density. The best model that has been found was ANN with 5, 6 and 1 neurons in the input, hidden and output layer correspondingly. The performance of selected ANN has been 0.99996, 4.44E-05, 0.00353 and 0.0067 which are correlation coefficient (R), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE) respectively. The research presented or summarized above throws light on future scope on stabilization with waste glass combined with different percentages of eggshell that leads to the economical design of CBR acceptable to pavement sub-base or base, as desired.

Keywords: CBR, artificial neural network, liquid limit, plastic limit, maximum dry density, OMC

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Authors: Aditi Chauhan, Neethu S. Mohan

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In the modern era, the advancement and digitalization in technology have taken place during an investigation of crime scene. The rapid enhancement and investigative techniques have changed the mean of identification of suspect. Identification of the person is one of the significant aspects, and personal authentication is the key of security and reliability in society. Since early 90 s, people have relied on comparing handwriting through its class and individual characteristics. But in today’s 21st century we need more reliable means to identify individual through handwriting. An approach employing computer modalities have lately proved itself auspicious enough in exploration of hieroglyphics substantial in investigating the case. Various software’s such as FISH, WRITEON, and PIKASO, CEDAR-FOX SYSTEM identify and verify the associated quantitative measure of the similarity between two samples. The research till date has been confined to identify the authorship of the concerned samples. But prospects associated with the use of computational modalities might help to identify disguised writing, forged handwriting or say altered or modified writing. Considering the applications of such modal, similar work is sure to attract plethora of research in immediate future. It has a promising role in national security too. Documents exchanged among terrorist can also be brought under the radar of surveillance, bringing forth their source of existence.

Keywords: documents, identity, computational system, suspect

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Authors: I. Agboola Julius, Christopher A. Kumolu-Johnson, O. Kolade Rafiu, A. Saba Abdulwakil

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This work elucidates on mangrove diversity, trends of change, factors responsible for loss over the years and implications for sustainable livelihoods of locals in four villages (Ajido (L1), Tarkwa bay (L2), University of Lagos (L3), and Ikosi (L4)) along the coast of Lagos, Nigeria. Primary data were collected through field survey, questionnaires, interviews, and review of existing literature. Field observation and data analysis reveals mangrove diversity as low and varied on a spatial scale, where Margalef’s Diversity Index (D) was 0.368, 0.269, 0.326, and 0.333, respectively for L1, L2, L3, and L4. Shannon Weiner’s Index (H) was estimated to be 1.003, 1.460, 1.160, 1.046, and Specie Richness (E) 0.913, 0.907, 0.858, and 0.015, respectively, for the four villages. Also, The Simpson’s index of diversity was analyzed to be 0.632, 0. 731, 0.647, 0.667, and Simpson’s reciprocal index 2.717, 3.717, 3.060, and 3.003, respectively, for the four villages. Chi-square test was used to analyze the impact of mangrove loss on the sustainable livelihood of coastal communities. Calculated Chi-square (X2) value (5) was higher than tabulated value (4.30), suggesting that loss of mangrove wetlands impacted on local communities’ livelihood at the four villages. Analyses of causes and trends of mangrove wetland loss over the years suggest that urbanization, fuel wood and agricultural activities are major causes. Current degradation observed in mangrove wetlands on the Lagos coast suggest a reduction in mangroves biodiversity and associated fauna with potential cascading effects on higher trophic levels such as fisheries. Low yield in fish catch, reduction in income and increasing cases of natural disaster has culminated in threats to sustainable livelihoods of local communities along the coast of Lagos.

Keywords: Mangroves, lagos coast, fisheries, management

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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Authors: Chia-Ju Peng, Shih-Jui Chen

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This paper proposes a method to discriminate electroencephalogram (EEG) signals between different concentration states using empirical mode decomposition (EMD). Brain-computer interface (BCI), also called brain-machine interface, is a direct communication pathway between the brain and an external device without the inherent pathway such as the peripheral nervous system or skeletal muscles. Attention level is a common index as a control signal of BCI systems. The EEG signals acquired from people paying attention or in relaxation, respectively, are decomposed into a set of intrinsic mode functions (IMF) by EMD. Fast Fourier transform (FFT) analysis is then applied to each IMF to obtain the frequency spectrums. By observing power spectrums of IMFs, the proposed method has the better identification of EEG attention level than the original EEG signals between different concentration states. The band power of IMF3 is the most obvious especially in β wave, which corresponds to fully awake and generally alert. The signal processing method and results of this experiment paves a new way for BCI robotic system using the attention-level control strategy. The integrated signal processing method reveals appropriate information for discrimination of the attention and relaxation, contributing to a more enhanced BCI performance.

Keywords: biomedical engineering, brain computer interface, electroencephalography, rehabilitation

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Authors: Hyo-In Koh, Anders Nordborg, Alex Sievi, Chun-Kwon Park

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The noise source for the interior room of the high speed train is constituted by the rolling contact between the wheel and the rail, aerodynamic noise and structure-borne sound generated through the vibrations of bogie, connection points to the carbody. Air-borne sound is radiated through the panels and structures into the interior room of the trains. The high-speed lines are constructed with slab track systems and many tunnels. The interior noise level and the frequency characteristics vary according to types of the track structure and the infrastructure. In this paper the main sound sources and the transfer paths are studied to find out the contribution characteristics of the sources to the interior noise of a high-speed rail vehicle. For the identification of the acoustic power of each parts of the rolling noise sources a calculation model of wheel/rail noise is developed and used. For the analysis of the transmission of the sources to the interior noise noise and vibration are measured during the operation of the vehicle. According to operation speeds, the mainly contributed sources and the paths could be analyzed. Results of the calculations on the source generation and the results of the measurement with a high-speed train are shown and discussed.

Keywords: rail vehicle, high-speed, interior noise, noise source

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Authors: Kishor Chandra Kandpal, Amit Kumar

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The Indian Himalaya region harbours approximately 1748 plants of medicinal importance, and as per International Union for Conservation of Nature (IUCN), the 112 plant species among these are threatened and endangered. To ease the pressure on these plants, the government of India is encouraging its in-situ cultivation. The Saussurea costus, Valeriana jatamansi, and Picrorhiza kurroa have also been prioritized for large scale cultivation owing to their market demand, conservation value and medicinal properties. These species are found from 1000 m to 4000 m elevation ranges in the Indian Himalaya. Identification of these plants in the field requires taxonomic skills, which is one of the major bottleneck in the conservation and management of these plants. In recent years, Hyperspectral remote sensing techniques have been precisely used for the discrimination of plant species with the help of their unique spectral signatures. In this background, a spectral library of the above 03 medicinal plants was prepared by collecting the spectral data using a handheld spectroradiometer (325 to 1075 nm) from farmer’s fields of Himachal Pradesh and Uttarakhand states of Indian Himalaya. The Random forest (RF) model was implied on the spectral data for the classification of the medicinal plants. The 80:20 standard split ratio was followed for training and validation of the RF model, which resulted in training accuracy of 84.39 % (kappa coefficient = 0.72) and testing accuracy of 85.29 % (kappa coefficient = 0.77). This RF classifier has identified green (555 to 598 nm), red (605 nm), and near-infrared (725 to 840 nm) wavelength regions suitable for the discrimination of these species. The findings of this study have provided a technique for rapid and onsite identification of the above medicinal plants in the field. This will also be a key input for the classification of hyperspectral remote sensing images for mapping of these species in farmer’s field on a regional scale. This is a pioneer study in the Indian Himalaya region for medicinal plants in which the applicability of hyperspectral remote sensing has been explored.

Keywords: himalaya, hyperspectral remote sensing, machine learning; medicinal plants, random forests

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Authors: W. A. Gonçalves, E. P. Souza, C. R. Alcântara

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The ISCCP-Tracking database offers an opportunity to study physical and morphological characteristics of Convective Systems based on geostationary meteorological satellites. This database contains 26 years of tracking of Convective Systems for the entire globe. Then, Tropical Squall Lines which occur in Brazil are certainly within the database. In this study, we propose a methodology for identification of these systems based on the ISCCP-Tracking database. A physical and morphological characterization of these systems is also shown. The proposed methodology is firstly based on the year of 2007. The Squall Lines were subjectively identified by visually analyzing infrared images from GOES-12. Based on this identification, the same systems were identified within the ISCCP-Tracking database. It is known, and it was also observed that the Squall Lines which occur on the north coast of Brazil develop parallel to the coast, influenced by the sea breeze. In addition, it was also observed that the eccentricity of the identified systems was greater than 0.7. Then, a methodology based on the inclination (based on the coast) and eccentricity (greater than 0.7) of the Convective Systems was applied in order to identify and characterize Tropical Squall Lines in Brazil. These thresholds were applied back in the ISCCP-Tracking database for the year of 2007. It was observed that other systems, which were not Squall Lines, were also identified. Then, we decided to call all systems identified by the inclination and eccentricity thresholds as Linear Convective Systems, instead of Squall Lines. After this step, the Linear Convective Systems were identified and characterized for the entire database, from 1983 to 2008. The physical and morphological characteristics of these systems were compared to those systems which did not have the required inclination and eccentricity to be called Linear Convective Systems. The results showed that the convection associated with the Linear Convective Systems seems to be more intense and organized than in the other systems. This affirmation is based on all ISCCP-Tracking variables analyzed. This type of methodology, which explores 26 years of satellite data by an objective analysis, was not previously explored in the literature. The physical and morphological characterization of the Linear Convective Systems based on 26 years of data is of a great importance and should be used in many branches of atmospheric sciences.

Keywords: squall lines, convective systems, linear convective systems, ISCCP-Tracking

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Authors: Rafiqul Tarefder, Mohiuddin Ahmad, Mohammad Hossain

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While milling materials from old pavement surface can be an important component of cost effective maintenance operation, their use in maintenance projects are not uniform and well documented. This study documents the different maintenance practices followed by four transportation districts of New Mexico Department of Transportation (NMDOT) in an attempt to find whether millings are being used in maintenance projects by those districts. Based on existing literature, a questionnaire was developed related to six common maintenance practices. NMDOT district personal were interviewed face to face to discuss and get answers to that questionnaire. It revealed that NMDOT districts mainly use chip seal and patching. Other maintenance procedures such as sand seal, scrub seal, slurry seal, and thin overlay have limited use. Two out of four participating districts do not have any documents on chip sealing; rather they employ the experiences of the chip seal crew. All districts use polymer modified high float emulsion (HFE100P) for chip seal with an application rate ranging from 0.4 to 0.56 gallons per square yard. Chip application rate varies from 15 to 40 lb/ square yard. State wide, the thickness of chip seal varies from 3/8" to 1" and life varies from 3 to 10 years. NMDOT districts mainly use three type of patching: pothole, dig-out and blade patch. Pothole patches are used for small potholes and during emergency, dig-out patches are used for all type of potholes sometimes after pothole patching, and blade patch is used when a significant portion of the pavement is damaged. Pothole patches last as low as three days whereas, blade patch lasts as long as 3 years. It was observed that all participating districts use millings in maintenance projects.

Keywords: chip seal, sand seal, scrub seal, slurry seal, overlay, patching, millings

Procedia PDF Downloads 337

Authors: A. I. Alajtal, H. G. M. Edwards, M. A. Elbagermi

Abstract:

Raman spectroscopy is currently a part of the instrumentation suite of the ESA ExoMars mission for the remote detection of life signatures in the Martian surface and subsurface. Terrestrial analogues of Martian sites have been identified and the biogeological modifications incurred as a result of extremophilic activity have been studied. Analytical instrumentation protocols for the unequivocal detection of biomarkers in suitable geological matrices are critical for future unmanned explorations, including the forthcoming ESA ExoMars mission to search for life on Mars scheduled for 2018 and Raman spectroscopy is currently a part of the Pasteur instrumentation suite of this mission. Here, Raman spectroscopy using 785nm excitation was evaluated for determining various concentrations of beta-carotene in admixture with polyaromatic hydrocarbons and usnic acid have been investigated by Raman microspectrometry to determine the lowest levels detectable in simulation of their potential identification remotely in geobiological conditions in Martian scenarios. Information from this study will be important for the development of a miniaturized Raman instrument for targetting Martian sites where the biosignatures of relict or extant life could remain in the geological record.

Keywords: raman spectroscopy, mars-analog, beta-carotene, PAHs

Procedia PDF Downloads 335

Authors: Luis C. Parra

Abstract:

The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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Authors: Mani Venkatesh, Catarina Delgado, Purvishkumar Patel

Abstract:

The sustainable supply chain is gaining popularity among practitioners because of increased environmental degradation and stakeholder awareness. On the other hand supply chain, risk management is very crucial for the practitioners as it potentially disrupts supply chain operations. Prediction and addressing the risk caused by social issues in the supply chain is paramount importance to the sustainable enterprise. More recently, the usage of Big data analytics for forecasting business trends has been gaining momentum among professionals. The aim of the research is to explore the application of big data, predictive analytics in successfully mitigating supply chain social risk and demonstrate how such mitigation can help in achieving sustainability (environmental, economic & social). The method involves the identification and validation of social issues in the supply chain by an expert panel and survey. Later, we used a case study to illustrate the application of big data in the successful identification and mitigation of social issues in the supply chain. Our result shows that the company can predict various social issues through big data, predictive analytics and mitigate the social risk. We also discuss the implication of this research to the body of knowledge and practice.

Keywords: big data, sustainability, supply chain social sustainability, social risk, case study

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Authors: Hossein Rassi, Marjan Moradi Fard, Masoud Houshmand

Abstract:

Background: Cervical cancer is multistep disease that is thought to result from an interaction between genetic background and environmental factors. Human papillomavirus (HPV) infection is the leading risk factor for cervical intraepithelial neoplasia(CIN)and cervical cancer. In other hand, some of p53 and miRNA polymorphism may plays an important role in carcinogenesis. This study attempts to clarify the relation of p53 genotypes and miR-146a rs2910164 polymorphism in cervical lesions. Method: Forty two archival samples with cervical lesion retired from Khatam hospital and 40 sample from healthy persons used as control group. A simple and rapid method was used to detect the simultaneous amplification of the HPV consensus L1 region and HPV-16,-18, -11, -31, 33 and -35 along with the b-globin gene as an internal control. We use Multiplex PCR for detection of P53 and miR-146a rs2910164 genotypes in our lab. Finally, data analysis was performed using the 7 version of the Epi Info(TM) 2012 software and test chi-square(x2) for trend. Results: Cervix lesions were collected from 42 patients with Squamous metaplasia, cervical intraepithelial neoplasia, and cervical carcinoma. Successful DNA extraction was assessed by PCR amplification of b-actin gene (99bp). According to the results, p53 GG genotype and miR-146a rs2910164 CC genotype was significantly associated with increased risk of cervical lesions in the study population. In this study, we detected 13 HPV 18 from 42 cervical cancer. Conclusion: The connection between several SNP polymorphism and human virus papilloma in rare researches were seen. The reason of these differences in researches' findings can result in different kinds of races and geographic situations and also differences in life grooves in every region. The present study provided preliminary evidence that a p53 GG genotype and miR-146a rs2910164 CC genotype may effect cervical cancer risk in the study population, interacting synergistically with HPV 18 genotype. Our results demonstrate that the testing of p53 codon 72 polymorphism genotypes and miR-146a rs2910164 polymorphism genotypes in combination with HPV18 can serve as major risk factors in the early identification of cervical cancers. Furthermore, the results indicate the possibility of primary prevention of cervical cancer by vaccination against HPV18 in Iran.

Keywords: cervical cancer, p53, miR-146a, rs2910164, polymorphism

Procedia PDF Downloads 465

Authors: Marjan Moradi fard, Hossein Rassi, Masoud Houshmand

Abstract:

Aim: Breast cancer is one of the most common cancers affecting the morbidity and mortality of Iranian women. This disease is a result of collective alterations of oncogenes and tumor suppressor genes. Studies have produced conflicting results concerning the role of p53 codon 72 polymorphism (G>C) and miR-146a rs2910164 polymorphism (G>C) on the risk of several cancers; therefore, a research was performed to estimate the association between the p53 codon 72 polymorphism and miR-146a rs2910164 polymorphism in breast cancer. Methods and Materials: A total of 45 archival breast cancer samples from Khatam hospital and 40 healthy samples were collected. Verification of each cancer reported in a relative was sought through the pathology reports of the hospital records. Then, DNA extracted from all samples by standard methods and p53 codon 72 polymorphism genotypes and miR-146a rs2910164 polymorphism genotypes were analyzed using multiplex PCR. The tubules, mitotic activity, necrosis, polymorphism and grade of breast cancer were staged by Nottingham histological grading and immunohistochemical staining of the sections from the paraffin wax embedded tissues for the expression of ER, PR and p53 was carried out using a standard method. Finally, data analysis was performed using the 7 version of the Epi Info(TM) 2012 software and test chi-square(x2) for trend. Results: Successful DNA extraction was assessed by PCR amplification of b-actin gene (99 bp). According to the results, p53 GG genotype and miR-146a rs2910164 CC genotype was significantly associated with increased risk of breast cancer in the study population. In this study, we established that tumors of p53 GG genotype and miR-146a rs2910164 CC genotype exhibited higher mitotic activity, higher polymorphism, lower necrosis, lower tubules, higher ER- and PR-negatives and lower TP53-positives than the other genotypes. Conclusion: The present study provided preliminary evidence that a p53 GG genotype may effect breast cancer risk in the study population, interacting synergistically with miR-146a rs2910164 CC genotype. Our results demonstrate that the testing of p53 codon 72 polymorphism genotypes and miR-146a rs2910164 polymorphism genotypes in combination with clinical parameters can serve as major risk factors in the early identification of breast cancers.

Keywords: breast cancer, miR-146a rs2910164 polymorphism, p53 codon 72 polymorphism, tumors, pathology reports

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

Procedia PDF Downloads 76

Authors: Hossein Rassi, Marjan Moradi fard, Masoud Houshmand

Abstract:

Background: Cervical cancer is multistep disease that is thought to result from an interaction between genetic background and environmental factors. Human Papillomavirus (HPV) infection is the leading risk factor for Cervical Intraepithelial Neoplasia (CIN) and cervical cancer. In other hand, some of p53 and miRNA polymorphism may plays an important role in carcinogenesis. This study attempts to clarify the relation of p53 genotypes and miR-146a rs2910164 polymorphism in cervical lesions. Method: Forty two archival samples with cervical lesion retired from Khatam hospital and 40 sample from healthy persons used as control group. A simple and rapid method was used to detect the simultaneous amplification of the HPV consensus L1 region and HPV-16,-18, -11, -31, 33, and -35 along with the b-globin gene as an internal control. We use Multiplex PCR for detection of P53 and miR-146a rs2910164 genotypes in our lab. Finally, data analysis was performed using the 7 version of the Epi Info(TM) 2012 software and test chi-square(x2) for trend. Results: Cervix lesions were collected from 42 patients with Squamous metaplasia, cervical intraepithelial neoplasia, and cervical carcinoma. Successful DNA extraction was assessed by PCR amplification of b-actin gene (99 bp). According to the results, p53 GG genotype and miR-146a rs2910164 CC genotype was significantly associated with increased risk of cervical lesions in the study population. In this study, we detected 13 HPV 18 from 42 cervical cancer. Conclusion: The connection between several SNP polymorphism and human virus papilloma in rare researches were seen. The reason of these differences in researches' findings can result in different kinds of races and geographic situations and also differences in life grooves in every region. The present study provided preliminary evidence that a p53 GG genotype and miR-146a rs2910164 CC genotype may effect cervical cancer risk in the study population, interacting synergistically with HPV 18 genotype. Our results demonstrate that the testing of p53 codon 72 polymorphism genotypes and miR-146a rs2910164 polymorphism genotypes in combination with HPV18 can serve as major risk factors in the early identification of cervical cancers. Furthermore, the results indicate the possibility of primary prevention of cervical cancer by vaccination against HPV18 in Iran.

Keywords: cervical cancer, miR-146a rs2910164 polymorphism, p53 polymorphism, intraepithelial, neoplasia, HPV

Procedia PDF Downloads 395

Authors: Mohammad Javad Seddighi, Avar Almukhtar

Abstract:

Sustainable urban planning and design (SUPD) play a critical role in achieving the United Nations Sustainable Development Goals (UN SDGs). While there are many rating systems and standards available to assess the sustainability of the built environment, there is still a lack of a comprehensive framework that can assess the quality of SUPD in a specific context. In this paper, we present a framework for assessing the quality of SUPD in Iranian cities, considering their unique cultural, social, and environmental contexts. The aim of this study is to develop a framework for assessing the quality of SUPD in Iranian cities. To achieve this aim, the following objectives are pursued review and synthesis of relevant literature on SUPD, identification of key indicators and criteria for assessing the quality of SUPD in Iranian cities application of the framework to case studies of Iranian cities and evaluation and refinement of the framework based on the results of the case studies. The framework is developed based on a review and synthesis of relevant literature on SUPD, and the identification of key indicators and criteria for assessing the quality of SUPD in Iranian cities. The framework is then applied to case studies of Iranian cities and the results are evaluated and refined. The data for this study are collected through a review of relevant literature on SUPD, including academic journals, conference proceedings, and books. The case studies of Iranian cities are selected based on their relevance and availability of data. The data are collected through interviews, site visits, and document analysis. This paper presents a framework for assessing the quality of SUPD in Iranian cities. The framework is developed based on a review and synthesis of relevant literature, identification of key indicators and criteria, application to case studies, and evaluation and refinement. The framework provides a comprehensive and context-specific approach to assessing the quality of SUPD in Iranian cities. It can be used by urban planners, designers, and policymakers to improve the sustainability and liveability of Iranian cities, and it can be adapted for use in other contexts.

Keywords: sustainable urban planning and design, framework, quality assessment, Iranian cities, case studies

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Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

Abstract:

In this paper, a new robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics and using the weighted sum-squared prediction error as the residual. The recursive orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. The several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control

Procedia PDF Downloads 492

Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

Abstract:

Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

Procedia PDF Downloads 255

Authors: J. Bernasovská, R. Lohajová Behulová, E. Petrejčiková, I. Boroňová, I. Bernasovský

Abstract:

Y chromosome microdeletions are the most common genetic cause of male infertility and screening for these microdeletions in azoospermic or severely oligospermic men is now standard practice. Analysis of the Y chromosome in men with azoospermia or severe oligozoospermia has resulted in the identification of three regions in the euchromatic part of the long arm of the human Y chromosome (Yq11) that are frequently deleted in men with otherwise unexplained spermatogenic failure. PCR analysis of microdeletions in the AZFa, AZFb and AZFc regions of the human Y chromosome is an important screening tool. The aim of this study was to analyse the type of microdeletions in men with fertility disorders in Slovakia. We evaluated 227 patients with azoospermia and with normal karyotype. All patient samples were analyzed cytogenetically. For PCR amplification of sequence-tagged sites (STS) of the AZFa, AZFb and AZFc regions of the Y chromosome was used Devyser AZF set. Fluorescently labeled primers for all markers in one multiplex PCR reaction were used and for automated visualization and identification of the STS markers we used genetic analyzer ABi 3500xl (Life Technologies). We reported 13 cases of deletions in the AZF region 5,73%. Particular types of deletions were recorded in each region AZFa,b,c .The presence of microdeletions in the AZFc region was the most frequent. The study confirmed that percentage of microdeletions in the AZF region is low in Slovak azoospermic patients, but important from a prognostic view.

Keywords: AZF, male infertility, microdeletions, Y chromosome

Procedia PDF Downloads 366