Search results for: genetic difference

Authors: Aminu Bashir Mohammad, Agwu Ezera, Abdulrazaq G. Habib, Garba Iliyasu

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Background: Drug resistance tuberculosis (DR-TB) continues to be a challenge in developing countries with poor resources. Routine screening for primary DR-TB before commencing treatment is not done in public hospitals in Nigeria, even with the large body of evidence that shows a high prevalence of primary DR-TB. Data on drug resistance and its genetic determinant among follow up TB patients is lacking in Nigeria. Hence the aim of this study was to determine the prevalence and genetic determinant of drug resistance among follow up TB patients in a tertiary hospital in Nigeria. Methods: This was a cross-sectional laboratory-based study conducted on 384 sputum samples collected from consented follow-up tuberculosis patients. Standard microbiology methods (Zeil-Nielsen staining and microscopy) and PCR (Line Probe Assay)] were used to analyze the samples collected. Person’s Chi-square was used to analyze the data generated. Results: Out of three hundred and eighty-four (384) sputum samples analyzed for mycobacterium tuberculosis (MTB) and DR-TB twenty-five 25 (6.5%) were found to be AFB positive. These samples were subjected to PCR (Line Probe Assay) out of which 18(72%) tested positive for DR-TB. Mutations conferring resistance to rifampicin (rpo B) and isoniazid (katG, and or inhA) were detected in 12/18(66.7%) and 6/18(33.3%), respectively. Transmission dynamic of DR-TB was not significantly (p>0.05) dependent on demographic characteristics. Conclusion: There is a need to strengthened the laboratory capacity for diagnosis of TB and drug resistance testing and make these services available, affordable, and accessible to the patients who need them.

Keywords: drug resistance tuberculosis, genetic determinant, intensive phase, Nigeria

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Authors: Jun Su Park, Byung Kwan Oh, Jin Woo Hwang, Yousok Kim, Hyo Seon Park

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For the structural safety, the maximum stress calculated from the stress distribution of a structure is widely used. The stress distribution can be estimated by deformed shape of the structure obtained from measurement. Although the estimation of stress is strongly affected by the location and number of sensing points, most studies have conducted the stress estimation without reasonable basis on sensing plan such as the location and number of sensors. In this paper, an optimal sensing technique for estimating the stress distribution is proposed. This technique proposes the optimal location and number of sensing points for a 2-D frame structure while minimizing the error of stress distribution between analytical model and estimation by cubic smoothing splines using genetic algorithm. To verify the proposed method, the optimal sensor measurement technique is applied to simulation tests on 2-D steel frame structure. The simulation tests are performed under various loading scenarios. Through those tests, the optimal sensing plan for the structure is suggested and verified.

Keywords: genetic algorithm, optimal sensing, optimizing sensor placements, steel frame structure

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Authors: Farzana Parveen, Shahina Maqbool

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Nowadays most of the researchers focused on adolescents that were the most crucial and critical stage of their life’s. In this study, we want to know to what extent does spirituality and psychological well-being plays a vital role in adolescent’s life, and to what extent both were correlated. The first objective of the present study is to examine difference between the mean scores of male and female students on spirituality and Psychological well-being. The second objective of this study is to find out the relationship between Spirituality and Psychological Well-being. The participants of the present study comprised N=100 students who are further divided n=50 male and n=50 female and they were from senior secondary schools and recruited from Metropolitan cities, their age ranged from 13 to 18 years. Data were collected through Spirituality questionnaire and Psychological well-being questionnaire. Results showed that there was insignificant difference between male and female students on spirituality and significant difference between male and female students on psychological well-being. Relationship showed that there was positive correlation between spirituality and psychological well-being. Result was analyzed by SPSS version 20.0 software. Insignificant difference was found between males and females students on Spirituality and significant difference showed between males and females students on Psychological well-being. There was positive correlation between Spirituality and psychological well-being.

Keywords: spirituality, psychological well-being, male and female, students

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Authors: Saule Mussabekova

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Forensic investigation of human teeth plays an important role in detection of crime, particularly in cases of personal identification of dead bodies changed by putrefactive processes or skeletonized bodies as well as when finding bodies of unknown persons. 152 teeth have been investigated; 85 of them belonged to men and 67 belonged to women taken from alive people of different age. Teeth have been investigated after extraction. Two types of teeth have been investigated: teeth without integrity violation of dental crown and teeth with different degrees of its violation. Additionally, 517 teeth have been investigated that were collected from dead bodies, 252 of which belonged to women and 265 belonged to men, whatever the cause of death with death limitation from 1 month to 20 years. Isohemagglutinating serums and Coliclons of different series have been used for the research of tooth-group specificity by serological methods according to the AB0 system. Standard protocols of different techniques have been used for DNA purification from teeth (by reagent Chelex 100 produced by Bio-Rad using reagent kit 'DNA IQTM System' produced by Promega company (USA) and using columns 'QIAamp DNA Investigator Kit' produced by Qiagen company). Results of comparative forensic investigation of human teeth using serological and molecular genetic methods have shown that use of serological methods for forensic identification is sensible only in cases of preselection prior to the next molecular genetic investigation as well as in cases of impossibility of corresponding genetic investigation for different objective reasons. A number of advantages of methods of molecular genetics in the dental investigation have been marked, particularly in putrefactive changes, in personal identification. Key moments of modern condition of personal identification have been reflected according to dental state. Prospective directions of advance preparation of material have been emphasized for identification of teeth in forensic practice.

Keywords: dental state, forensic identification, molecular genetic analysis, teeth

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Authors: Bliss Singhal

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Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

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Authors: Libo Jiang, Huan Li, Rongling Wu

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Ordinary differentiation equations (ODE) have proven to be powerful for reconstructing precise and informative gene regulatory networks (GRNs) from dynamic gene expression data. However, joint modeling and analysis of all genes, essential for the systematical characterization of genetic interactions, are challenging due to high dimensionality and a complex pattern of genetic regulation including activation, repression, and antitermination. Here, we address these challenges by unifying variable selection and game theory through ODE. Each gene within a GRN is co-expressed with its partner genes in a way like a game of multiple players, each of which tends to choose an optimal strategy to maximize its “fitness” across the whole network. Based on this unifying theory, we designed and conducted a real experiment to infer salt tolerance-related GRNs for Euphrates poplar, a hero tree that can grow in the saline desert. The pattern and magnitude of interactions between several hub genes within these GRNs were found to determine the capacity of Euphrates poplar to resist to saline stress.

Keywords: gene regulatory network, ordinary differential equation, game theory, LASSO, saline resistance

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Authors: Babak H. Tabrizi, Seyed Farid Ghaderi

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Concurrent planning of the resource constraint project scheduling and material ordering problems have received significant attention within the last decades. Hence, the issue has been investigated here with the aim to minimize total project costs. Furthermore, the presented model considers different discount options in order to approach the real world conditions. The incorporated alternatives consist of all-unit and incremental discount strategies. On the other hand, a modified version of the genetic algorithm is applied in order to solve the model for larger sizes, in particular. Finally, the applicability and efficiency of the given model is tested by different numerical instances.

Keywords: genetic algorithm, material ordering, project management, project scheduling

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Authors: Khaled Moaddy

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In this paper, we present a fast and accurate numerical scheme for the solution of a Laplace equation with Dirichlet boundary conditions. The non-standard finite difference scheme (NSFD) is applied to construct the numerical solutions of a Laplace equation with two different Dirichlet boundary conditions. The solutions obtained using NSFD are compared with the solutions obtained using the standard finite difference scheme (SFD). The NSFD scheme is demonstrated to be reliable and efficient.

Keywords: standard finite difference schemes, non-standard schemes, Laplace equation, Dirichlet boundary conditions

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Authors: Karen Fang

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Investigative genetic genealogy has attracted much interest in both the field of ethics and the public eye due to its global application in criminal cases. Arguments have been made regarding privacy and informed consent, especially with law enforcement using consumer genetic testing results to convict individuals. In the case of public interest, DNA databases have the strong potential to significantly reduce crime, which in turn leads to safer communities and better futures. With the advancement of genetic technologies, the integration of a universal forensic DNA database in violent crimes, crimes against children, and missing person cases is expected to deter crime while protecting one’s privacy. Rather than collecting whole genomes from the whole population, STR profiles can be used to identify unrelated individuals without compromising personal information such as physical appearance, disease risk, and geographical origin, and additionally, reduce cost and storage space. STR DNA profiling is already used in the forensic science field and going a step further benefits several areas, including the reduction in recidivism, improved criminal court case turnaround time, and just punishment. Furthermore, adding individuals to the database as early as possible prevents young offenders and first-time offenders from participating in criminal activity. It is important to highlight that DNA databases should be inclusive and tightly governed, and the misconception on the use of DNA based on crime television series and other media sources should be addressed. Nonetheless, deterrent effects have been observed in countries like the US and Denmark with DNA databases that consist of serious violent offenders. Fewer crimes were reported, and fewer people were convicted of those crimes- a favorable outcome, not even the death penalty could provide. Currently, there is no better alternative than a universal forensic DNA database made up of STR profiles. It can open doors for investigative genetic genealogy and fostering better communities. Expanding the appropriate use of DNA databases is ethically acceptable and positively impacts the public.

Keywords: bioethics, deterrent effects, DNA database, investigative genetic genealogy, privacy, public interest

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Authors: Masoud Sheidai

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Biologists with a special field of population genetics and phylogeny have different research tasks such as populations’ genetic variability and divergence, species relatedness, the evolution of genetic and morphological characters, and identification of DNA SNPs with adaptive potential. To tackle these problems and reach a concise conclusion, they must use the proper and efficient statistical and bioinformatic methods as well as suitable genetic and morphological characteristics. In recent years application of different bioinformatic and statistical methods, which are based on various well-documented assumptions, are the proper analytical tools in the hands of researchers. The species delineation is usually carried out with the use of different clustering methods like K-means clustering based on proper distance measures according to the studied features of organisms. A well-defined species are assumed to be separated from the other taxa by molecular barcodes. The species relationships are studied by using molecular markers, which are analyzed by different analytical methods like multidimensional scaling (MDS) and principal coordinate analysis (PCoA). The species population structuring and genetic divergence are usually investigated by PCoA and PCA methods and a network diagram. These are based on bootstrapping of data. The Association of different genes and DNA sequences to ecological and geographical variables is determined by LFMM (Latent factor mixed model) and redundancy analysis (RDA), which are based on Bayesian and distance methods. Molecular and morphological differentiating characters in the studied species may be identified by linear discriminant analysis (DA) and discriminant analysis of principal components (DAPC). We shall illustrate these methods and related conclusions by giving examples from different edible and medicinal plant species.

Keywords: GWAS analysis, K-Means clustering, LFMM, multidimensional scaling, redundancy analysis

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Authors: Amr A. El Hanafy, Yasser M. Saad, Saleh A. Alkarim, Hussein A. Almehdar, Elrashdy M. Redwan

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Camels are substantial providers of transport, milk, sport, meat, shelter, fuel, security and capital in many countries, particularly Saudi Arabia. Identification of animal breeds has progressed rapidly during the last decade. Advanced molecular techniques are playing a significant role in breeding or strain protection laws. On the other hand, fingerprinting of some molecular markers related to some productive traits in farm animals represents most important studies to our knowledge, which aim to conserve these local genetic resources, and to the genetic improvement of such local breeds by selective programs depending on gene markers. Milk records were taken two days in each week from female camels of Majahem, Safara, Wathaha, and Hamara breeds, respectively from different private farms in northern Jeddah, Riyadh and Alwagh governorates and average weekly yields were calculated. DNA sequencing for CSN2 gene was used for evaluating the genetic variations and calculating the genetic distance values among four Saudi camel populations which are Hamra(R), Safra(Y), Wadha(W) and Majaheim(M). In addition, this marker was analyzed for reconstructing the Neighbor joining tree among evaluating camel breeds. In respect to milk yield during winter season, result indicated that average weekly milk yield of Safara camel breed (30.05 Kg/week) is significantly (p < 0.05) lower than the other 3 breeds which ranged from 39.68 for Hamara to 42.42 Kg/week for Majahem, while there are not significant differences between these three breeds. The Neighbor Joining analysis that re-constructed based on DNA variations showed that samples are clustered into two unique clades. The first clade includes Y (from Y4 to Y18) and M (from M1, to M9). On the other hand, the second cluster is including all R (from R1 to R6) and W (from W1 to W6). The genetic distance values were equal 0.0068 (between the groups M&Y and R&W) and equal 0 (within each group).

Keywords: milk yield, beta-casein precursor (CSN2), Saudi camel, molecular markers

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Authors: Kimi Ueda, Kosuke Sugita, Soma Kawamoto, Hiroshi Shimoda, Hirotake Ishii, Fumiaki Obayashi, Kazuhiro Taniguchi, Ayaka Suzuki

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The authors have focused on the thermal difference between office rooms and break rooms, and proposed an integrated thermal control method to improve workers’ intellectual concentration. First, a trial experiment was conducted to verify the effect of temperature difference on workers’ intellectual concentration with using two experimental rooms; a thermally neutral break room and a cooler office room. As the result of the experiment, it was found that the thermal difference had a significant effect on improving their intellectual concentration. Workers, however, often take a short break at their desks without moving to a break room, so that the thermal difference cannot be given to them. So utilization of airflow was proposed as an integrated thermal control method instead of the temperature difference to realize the similar effect. Concretely, they are exposed to airflow when working in order to reduce their effective temperature while it is weakened when taking a break. Another experiment was conducted to confirm the effect of the airflow control on their intellectual concentration. As the result of concentration index and questionnaire survey, their intellectual concentration was significantly improved in the integrated thermal controlled environment. It was also found that most of them felt more comfortable and had higher motivation and higher degree of concentration in the environment.

Keywords: airflow, evaluation experiment, intellectual concentration, thermal difference

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Authors: Trupti Diwan

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Predicting student failure at school has changed into a difficult challenge due to both the large number of factors that can affect the reduced performance of students and the imbalanced nature of these kinds of data sets. This paper surveys the two elements needed to make prediction on Students’ Academic Performances which are parameters and methods. This paper also proposes a framework for predicting the performance of engineering students. Genetic programming can be used to predict student failure/success. Ranking algorithm is used to rank students according to their credit points. The framework can be used as a basis for the system implementation & prediction of students’ Academic Performance in Higher Learning Institute.

Keywords: classification, educational data mining, student failure, grammar-based genetic programming

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Authors: Farahnaz Amini, Woo Yun Kin, Lazwani Kolandaiveloo

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Availability of different genetic tests after completion of Human Genome Project increases the physicians’ responsibility to keep themselves update on the potential implementation of these genetic tests in their daily practice. However, due to numbers of barriers, still many of physicians are not either aware of these tests or are not willing to offer or refer their patients for genetic tests. This study was conducted an anonymous, cross-sectional, mailed-based survey to develop a primary data of Malaysian physicians’ level of knowledge and perception of gene profiling. Questionnaire had 29 questions. Total scores on selected questions were used to assess the level of knowledge. The highest possible score was 11. Descriptive statistics, one way ANOVA and chi-squared test was used for statistical analysis. Sixty three completed questionnaires was returned by 27 general practitioners (GPs) and 36 medical specialists. Responders’ age range from 24 to 55 years old (mean 30.2 ± 6.4). About 40% of the participants rated themselves as having poor level of knowledge in genetics in general whilst 60% believed that they have fair level of knowledge. However, almost half (46%) of the respondents felt that they were not knowledgeable about available genetic tests. A majority (94%) of the responders were not aware of any lab or company which is offering gene profiling services in Malaysia. Only 4% of participants were aware of using gene profiling for detection of dosage of some drugs. Respondents perceived greater utility of gene profiling for breast cancer (38%) compared to the colorectal familial cancer (3%). The score of knowledge ranged from 2 to 8 (mean 4.38 ± 1.67). Non-significant differences between score of knowledge of GPs and specialists were observed, with score of 4.19 and 4.58 respectively. There was no significant association between any demographic factors and level of knowledge. However, those who graduated between years 2001 to 2005 had higher level of knowledge. Overall, 83% of participants showed relatively high level of perception on value of gene profiling to detect patient’s risk of disease. However, low perception was observed for both statements of using gene profiling for general population in order to alter their lifestyle (25%) as well as having the full sequence of a patient genome for the purpose of determining a patient’s best match for treatment (18%). The lack of clinical guidelines, limited provider knowledge and awareness, lack of time and resources to educate patients, lack of evidence-based clinical information and cost of tests were the most barriers of ordering gene profiling mentioned by physicians. In conclusion Malaysian physicians who participate in this study had mediocre level of knowledge and awareness in gene profiling. The low exposure to the genetic questions and problems might be a key predictor of lack of awareness and knowledge on available genetic tests. Educational and training workshop might be useful in helping Malaysian physicians incorporate genetic profiling into practice for eligible patients.

Keywords: gene profiling, knowledge, Malaysia, physician

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Authors: Ismail El Gayar, Ossama Ismail, Yousri El Gamal

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This paper presented a technique to solve one of the transportation problems that faces us in real life which is the Bus Scheduling Problem. Most of the countries using buses in schools, companies and traveling offices as an example to transfer multiple passengers from many places to specific place and vice versa. This transferring process can cost time and money, so we build a decision support system that can solve this problem. In this paper, a genetic algorithm with the shortest path technique is used to generate a competitive solution to other well-known techniques. It also presents a comparison between our solution and other solutions for this problem.

Keywords: bus scheduling problem, decision support system, genetic algorithm, shortest path

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Authors: Adel Bessadok

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The theory of values postulates that each human has a set of values, or attractive and trans-situational goals, that drive their actions. The Basic Human Values as an incentive construct that apprehends human's values have been shown to govern a wide range of human behaviors. Individuals within and within societies have very different value preferences that reflect their enculturation, their personal experiences, their social places and their genetic heritage. Using a focus group composed by Islamic religious Preachers and a sample of 800 young students; this ongoing study will establish Moderate Islamic Values parameters. We analyze later, for the same students sample the difference between Moderate Islamic Values and Schwartz’s Basic Human Values. Keywords—Moderate Islamic Values, Basic Human Values, Exploratory Factor Analysis and Confirmatory Factor Analysis.

Keywords: moderate Islamic values, basic human values, exploratory factor analysis, confirmatory factor analysis

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Authors: Jiawen Wang, Qijun Chen

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The performance of most machine-learning methods for image inpainting depends on the quantity and quality of the training samples. However, it is very expensive or even impossible to obtain a great number of training samples in many scenarios. In this paper, an image inpainting model based on a generative adversary network (GAN) is constructed for the cases when the number of training samples is small. Firstly, a feature extraction network (F-net) is incorporated into the GAN network to utilize the available information of the inpainting image. The weighted sum of the extracted feature and the random noise acts as the input to the generative network (G-net). The proposed network can be trained well even when the sample size is very small. Secondly, in the phase of the completion for each damaged image, a genetic algorithm is designed to search an optimized noise input for G-net; based on this optimized input, the parameters of the G-net and F-net are further learned (Once the completion for a certain damaged image ends, the parameters restore to its original values obtained in the training phase) to generate an image patch that not only can fill the missing part of the damaged image smoothly but also has visual semantics.

Keywords: image inpainting, generative adversary nets, genetic algorithm, small-sample size

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Authors: Tofigh Hamidavi, Sepehr Abrishami, Pasquale Ponterosso, David Begg

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Structural design and analysis is an important and time-consuming process, particularly at the conceptual design stage. Decisions made at this stage can have an enormous effect on the entire project, as it becomes ever costlier and more difficult to alter the choices made early on in the construction process. Hence, optimisation of the early stages of structural design can provide important efficiencies in terms of cost and time. This paper suggests a structural design optimisation (SDO) framework in which Genetic Algorithms (GAs) may be used to semi-automate the production and optimisation of early structural design alternatives. This framework has the potential to leverage conceptual structural design innovation in Architecture, Engineering and Construction (AEC) projects. Moreover, this framework improves the collaboration between the architectural stage and the structural stage. It will be shown that this SDO framework can make this achievable by generating the structural model based on the extracted data from the architectural model. At the moment, the proposed SDO framework is in the process of validation, involving the distribution of an online questionnaire among structural engineers in the UK.

Keywords: building information, modelling, BIM, genetic algorithm, GA, architecture-engineering-construction, AEC, optimisation, structure, design, population, generation, selection, mutation, crossover, offspring

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Authors: Sajjad Baghernezhad

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Meta-heuristic and hybrid algorithms have high adeer in modeling medical problems. In this study, a neural network was used to predict covid-19 among high-risk and low-risk patients. This study was conducted to collect the applied method and its target population consisting of 550 high-risk and low-risk patients from the Kerman University of medical sciences medical center to predict the coronavirus. In this study, the memetic algorithm, which is a combination of a genetic algorithm and a local search algorithm, has been used to update the weights of the neural network and develop the accuracy of the neural network. The initial study showed that the accuracy of the neural network was 88%. After updating the weights, the memetic algorithm increased by 93%. For the proposed model, sensitivity, specificity, positive predictivity value, value/accuracy to 97.4, 92.3, 95.8, 96.2, and 0.918, respectively; for the genetic algorithm model, 87.05, 9.20 7, 89.45, 97.30 and 0.967 and for logistic regression model were 87.40, 95.20, 93.79, 0.87 and 0.916. Based on the findings of this study, neural network models have a lower error rate in the diagnosis of patients based on individual variables and vital signs compared to the regression model. The findings of this study can help planners and health care providers in signing programs and early diagnosis of COVID-19 or Corona.

Keywords: COVID-19, decision support technique, neural network, genetic algorithm, memetic algorithm

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Authors: Manas Shah

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Black Scholes option pricing model is one of the most important concepts in modern world of computational finance. However, its practical use can be challenging as one of the input parameters must be estimated; implied volatility of the underlying security. The more precisely these values are estimated, the more accurate their corresponding estimates of theoretical option prices would be. Here, we present a novel model based on Cuckoo Search Optimization (CS) which finds more precise estimates of implied volatility than Particle Swarm Optimization (PSO) and Genetic Algorithm (GA).

Keywords: black scholes model, cuckoo search optimization, particle swarm optimization, genetic algorithm

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Authors: Amar Khoukhi, Mohamed Shahab

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This paper presents the optimal control problem of mobile robot motion as a nonlinear programming problem (NLP) and solved using a direct method of numerical optimal control. The NLP is initialized with a B-Spline for which node locations are optimized using a genetic search. The system acceleration inputs and sampling periods are considered as optimization variables. Different scenarios with different objectives weights are implemented and investigated. Interesting results are found in terms of complying with the expected behavior of a mobile robot system and time-energy minimization.

Keywords: multi-objective control, non-holonomic systems, mobile robots, nonlinear programming, motion planning, B-spline, genetic algorithm

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Authors: Wafa Al Jabri

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Background: In Middle Eastern Islamic Countries (MEICs), there is a high prevalence of genetic blood disorders (GBDs), particularly sickle cell disease and thalassemia. The GBDs are considered a major public health concern, especially with the increase in affected populations along with the associated psychological, social, and financial cost of management. Despite the availability of premarital screening services (PSS) that aim to identify the asymptomatic carriers of GBDs and provide genetic counseling to couples in order toreduce the prevalence of these diseases; yet, the success rate of PSS is very low due to religious and socio-cultural concerns. Purpose: This paper aims to highlight the factors that affect the success of PSS in MEICs. Methods: A literature review of articles located in CINAHL, PubMed, SCOPUS, and MedLinewas carried out using the following terms: “premarital screening,” “success,” “effectiveness,” and “ genetic blood disorders.” Second, a hand search of the reference lists and Google searches were conducted to find studies that did not exist in the primary database searches. Only studies which are conducted in MEICs countries and published in the last five years were included. Studies that were not published in English were excluded. Results: Fourteen articles were included in the review. The results showed that PSS in most of the MEICs was successful in achieving its objective of identifying high-risk marriages; however, the service failed to meetitsultimate goal of reducing the prevalence of GBDs. Various factors seem to hinder the success of PSS, including poor public awareness, late timing of the screening, culture and social stigma, religious beliefs, availability of prenatal diagnosis and therapeutic abortion, emotional factors, and availability of genetic counseling services. However, poor public awareness, late timing of the screening, and unavailability of adequate counseling services were the most common barriers identified. Conclusion: Overcoming the identified barriers by providing effective health education programs, offering the screening test to young adults at an earlier stage, and tailoring the genetic counseling would be crucial steps to provide a framework for an effective PSS in MEICs.

Keywords: premarital screening, success, effectiveness, and genetic blood disorders

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Authors: Biji Jacob

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Vector quantization algorithm which uses minimum distance calculation for codebook generation, a time consuming calculation performed on each pixel values leads to computation complexity. The codebook is updated by comparing the distance of each vector to their centroid vector and measure for their closeness. In this paper vector quantization is modified based on vector difference algorithm for image enhancement purpose. In the proposed scheme, vector differences between the vectors are considered as the new generation vectors or new codebook vectors. The codebook is updated by comparing the new generation vector with a threshold value having minimum error with the parent vector. The minimum error decides the fitness of each newly generated vector. Thus the codebook is generated in an adaptive manner and the fitness value is determined for the suppression of the degraded portion of the image and thereby leads to the enhancement of the image through the adaptive searching capability of the vector quantization through vector difference algorithm. Experimental results shows that the vector difference scheme efficiently modifies the vector quantization algorithm for enhancing the image with peak signal to noise ratio (PSNR), mean square error (MSE), Euclidean distance (E_dist) as the performance parameters.

Keywords: codebook, image enhancement, vector difference, vector quantization

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Authors: Aicha Rima Cheniti, Hatem Besbes, Joseph Haggege, Christophe Sintes

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In this paper, we are interested to determine the carbon dioxide pressure in the arterial blood through radial velocity difference. The blood was modeled as a two phase mixture (an aqueous carbon dioxide solution with carbon dioxide gas) by Drift flux model and the Young-Laplace equation. The distributions of mixture velocities determined from the considered model permitted the calculation of the radial velocity distributions with different values of mean mixture pressure and the calculation of the mean carbon dioxide pressure knowing the mean mixture pressure. The radial velocity distributions are used to deduce a calculation method of the mean mixture pressure through the radial velocity difference between two positions which is measured by ultrasound. The mean carbon dioxide pressure is then deduced from the mean mixture pressure.

Keywords: mean carbon dioxide pressure, mean mixture pressure, mixture velocity, radial velocity difference

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Authors: Sammy Kibor, Filip Huyghe, Marc Kochzius, James Kairo

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Goldstripe Sardinella, Sardinella gibbosa, (Bleeker, 1849) is a commercially and ecologically important small pelagic fish common in the Western Indian Ocean region. The present study aimed to assess genetic diversity and population structure of the species in the Kenya-Tanzania transboundary area using mtDNA and msDNA markers. Some 630 bp sequence in the mitochondrial DNA (mtDNA) Cytochrome C Oxidase I (COI) and five polymorphic microsatellite DNA loci were analyzed. Fin clips of 309 individuals from eight locations within the transboundary area were collected between July and December 2018. The S. gibbosa individuals from the different locations were distinguishable from one another based on the mtDNA variation, as demonstrated with a neighbor-joining tree and minimum spanning network analysis. None of the identified 22 haplotypes were shared between Kenya and Tanzania. Gene diversity per locus was relatively high (0.271-0.751), highest Fis was 0.391. The structure analysis, discriminant analysis of Principal component (DAPC) and the pair-wise (FST = 0.136 P < 0.001) values after Bonferroni correction using five microsatellite loci provided clear inference on genetic differentiation and thus evidence of population structure of S. gibbosa along the Kenya-Tanzania coast. This study shows a high level of genetic diversity and the presence of population structure (Φst =0.078 P < 0.001) resulting to the existence of four populations giving a clear indication of minimum gene flow among the population. This information has application in the designing of marine protected areas, an important tool for marine conservation.

Keywords: marine connectivity, microsatellites, population genetics, transboundary

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Authors: Agostinho Antunes

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The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of varied species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: adaptation, animals, evolution, genomics

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Authors: I. Boroňová, J. Bernasovská, J. Kmec, E. Petrejčíková

Abstract:

Dilated cardiomyopathy (DCM) is a primary myocardial disease, it is characterized by progressive systolic dysfunction due to cardiac chamber dilatation and inefficient myocardial contractility with estimated prevalence of 37 in 100 000 people. It is the most frequent cause of heart failure and cardiac transplantation in young adults. About one-third of all patients have a suspected familial disease indicating a genetic basis of DCM. Many candidate gene studies in humans have tested the association of single nucleotide polymorphisms (SNPs) in various genes coding for proteins with a known cardiovascular function. In our study we present the results of ZBTB17 gene rs10927875 polymorphism genotyping in relation to dilated cardiomyopathy in Slovak population. The study included 78 individuals, 39 patients with DCM and 39 healthy control persons. The mean age of patients with DCM was 50.7±11.5 years; the mean age of individuals in control group was 51.3±9.8 years. Risk factors detected at baseline in each group included age, sex, body mass index, smoking status, diabetes and blood pressure. Genomic DNA was extracted from leukocytes by a standard methodology and screened for rs10927875 polymorphism in intron of ZBTB17 gene using Real-time PCR method (Step One Applied Biosystems). The distribution of investigated genotypes for rs10927875 polymorphism in the group of patients with DCM was as follows: CC (89.74%), CT (10.26%), TT (0%), and the distribution in the control group: CC (92.31%), CT (5.13%), and TT (2.56%). Using the chi-square (χ2) test we compared genotype and allele frequencies between patients and controls. There was no difference in genotype or allele frequencies in ZBTB17 gene rs10927875 polymorphism between patients and control group (χ2=3.028, p=0.220; χ2=0.264, p=0.608). Our results represent an initial study, it can be considered as preliminary and first of its kind in Slovak population. Further studies of ZBTB17 gene polymorphisms of more numerous files and additional functional investigations are needed to fully understand the role of genetic associations.

Keywords: dilated cardiomyopathy, SNP polymorphism, ZBTB17 gene, bioscience

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Authors: Gordana Branković, Dejan Dodig, Vesna Pajić, Vesna Kandić, Desimir Knežević, Nenad Đurić

Abstract:

The wheat grain quality properties are influenced by genotype, environmental conditions and genotype × environment interaction (GEI). The increasing request of more nutritious wheat products will direct future breeding programmes. Therefore, the aim of investigation was to determine: i) variability of the protein content (PC), wet gluten content (WG) and Zeleny sedimentation volume (ZS); ii) components of variance, heritability in a broad sense (hb2), and expected genetic advance as percent of mean (GAM) for PC, WG, and ZS; iii) correlations between PC, WG, ZS, and most important agronomic traits; in order to assess expected breeding success versus environmental impact for these quality traits. The plant material consisted of 30 genotypes of bread wheat (Triticum aestivum L. ssp. aestivum) and durum wheat (Triticum durum Desf.). The trials were sown at the three test locations in Serbia: Rimski Šančevi, Zemun Polje and Padinska Skela during 2010-2011 and 2011-2012. The experiments were set as randomized complete block design with four replications. The plot consisted of five rows of 1 m2 (5 × 0.2 m × 1 m). PC, WG and ZS were determined by the use of Near infrared spectrometry (NIRS) with the Infraneo analyser (Chopin Technologies, France). PC, WG and ZS, in bread wheat, were in the range 13.4-16.4%, 22.8-30.3%, and 39.4-67.1 mL, respectively, and in durum wheat, in the range 15.3-18.1%, 28.9-36.3%, 37.4-48.3 mL, respectively. The dominant component of variance for PC, WG, and ZS, in bread wheat, was genotype with the genetic variance/GEI variance (VG/VG × E) relation of 3.2, 2.9 and 1.0, respectively, and in durum wheat was GEI with the VG/VG × E relation of 0.70, 0.69 and 0.49, respectively. hb2 and GAM values for PC, WG and ZS, in bread wheat, were 94.9% and 12.6%, 93.7% and 18.4%, and 86.2% and 28.1%, respectively, and in durum wheat, 80.7% and 7.6%, 79.7% and 10.2%, and 74% and 11.2%, respectively. The most consistent through six environments, statistically significant correlations, for bread wheat, were between PC and spike length (-0.312 to -0.637); PC, WG, ZS and grain number per spike (-0.320 to -0.620; -0.369 to -0.567; -0.301 to -0.378, respectively); PC and grain thickness (0.338 to 0.566), and for durum wheat, were between PC, WG, ZS and yield (-0.290 to -0.690; -0.433 to -0.753; -0.297 to -0.660, respectively); PC and plant height (-0.314 to -0.521); PC, WG and spike length (-0.298 to -0.597; -0.293 to -0.627, respectively); PC, WG and grain thickness (0.260 to 0.575; 0.269 to 0.498, respectively); PC, WG and grain vitreousness (0.278 to 0.665; 0.357 to 0.690, respectively). Breeding success can be anticipated for ZS in bread wheat due to coupled high values for hb2 and GAM, suggesting existence of additive genetic effects, and also for WG in bread wheat, due to very high hb2 and medium high GAM. The small, and medium, negative correlations between PC, WG, ZS, and yield or yield components, indicate difficulties to select simultaneously for high quality and yield, depending on linkage for particular genetic arrangements to be broken by recombination.

Keywords: bread and durum wheat, genetic advance, protein and wet gluten content, Zeleny sedimentation volume

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Authors: Paromik Bhattacharyya, Vijay Kumar, Johannes Van Staden

Abstract:

Micropropagation is an important tool for the conservation of threatened and commercially important plant species of which orchids deserve special attention. Ansellia africana is one such medicinally important orchid species having much commercial significance. Thus, development of regeneration protocols for producing clonally stable regenerates using axillary buds is of much importance. However, for large-scale micropropagation to become not only successful but also acceptable by end-users, somaclonal variations occurring in the plantlets need to be eliminated. In the light of the various factors (genotype, ploidy level, in vitro culture age, explant and culture type, etc.) that may account for the somaclonal variations of divergent genetic changes at the cellular and molecular levels, genetic analysis of micropropagated plants using a multidisciplinary approach is of utmost importance. In the present study, the clonal integrity of the long term micropropagated A. africana plants were assessed using advanced molecular marker system i.e. Start Codon Targeted Polymorphism (SCoT). Our studies recorded a clonally stable regeneration protocol for A. africana with a very high degree of clonal fidelity amongst the regenerates. The results obtained from these molecular analyses could help in modifying the regeneration protocols for obtaining clonally stable true to type plantlets for sustainable commercial use.

Keywords: medicinal orchid micropropagation, start codon targeted polymorphism (SCoT), RAP), traditional African pharmacopoeia, genetic fidelity

Procedia PDF Downloads 403

Authors: Minjung Kim, Hyunkoo Kang, Jinkoo Kim

Abstract:

In this study, a seismic retrofit scheme for a reinforced concrete shear wall structure using steel slit dampers was presented. The stiffness and the strength of the slit damper used in the retrofit were verified by cyclic loading test. A genetic algorithm was applied to find out the optimum location of the slit dampers. The effects of the slit dampers on the seismic retrofit of the model were compared with those of jacketing shear walls. The seismic performance of the model structure with optimally positioned slit dampers was evaluated by nonlinear static and dynamic analyses. Based on the analysis results, the simple procedure for determining required damping ratio using capacity spectrum method along with the damper distribution pattern proportional to the inter-story drifts was validated. The analysis results showed that the seismic retrofit of the model structure using the slit dampers was more economical than the jacketing of the shear walls and that the capacity spectrum method combined with the simple damper distribution pattern led to satisfactory damper distribution pattern compatible with the solution obtained from the genetic algorithm.

Keywords: seismic retrofit, slit dampers, genetic algorithm, jacketing, capacity spectrum method

Procedia PDF Downloads 246