Search results for: genetic improvement

Authors: Abejide Dorcas Ropo, Falusi Olamide Ahmed, Daudu Oladipupo Abdulazeez Yusuf, Muhammad Liman Muhammad, Gado Aishatu Adamu

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Bambara groundnut is an indigenous African legume with great potential to tackle the problem of food insecurity in Nigeria. A germplasm collection mission was carried out in collaboration with the Agricultural Developments Project (ADP) Extension officers of Nigeria between October and December 2014. Bambara groundnut seeds were collected from farmers in different States in Nigeria, such as Kaduna, Niger, Kogi, Benue, Plateau, Adamawa, Nasarawa, Jigawa, Enugu, and Federal Capital Territoy (FCT) Abuja. Some seeds were also collected from National Centre for Genetic Resources and Biotechnology (NACGRAB). The seeds were phenotyped using the descriptor list of Vigna subterranea produced by the International Plant Genetic Resource Institute. A total of 45 original seed lots were collected, which comprised of mixed seeds having different seed coat colours (15) and pure seeded accessions having the same seed coat and eye colour (30). After sorting, a total of 83 accessions were derived from the 45 original seed lots collected, and a total of 24 distinct seed morphotypes with varying seed coat colours and eye colours were identified from the collections. They include cream ( cream ash eye, cream plain eye, and cream black eye), cream purplish spots, cream brown spots/stripe, cream black stripe, cream dark brown patches, cream light grey spots, cream black patches, black, red, light red, dark red, brownish red, brown speckled with black, red speckled with black, brown, brown with brown pattern below hilum, brown with black pattern below hilum, cream black, grey brown, grey black and variegated red. The highest number of accessions were collected from NACGRAB (11), followed by Niger State (10), and the lowest from Benue, Jigawa, and Adamawa States (2). Niger State also had the highest number of mixed seeds. The different seed phenotypes observed in the study are important for the field production of true-to-type lines and can be exploited for the genetic improvement of the Bambara groundnut.

Keywords: Bambara groundnut, characterization, collection, germplasm, phenotypic

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Authors: Riffat Iqbal, Sidra Ihsan, Andleeb Batool, Maryam Mukhtar

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Glaucoma is a gathering of optic neuropathies described by dynamic degeneration of retinal ganglionic cells. It is clinically and innately heterogenous illness containing a couple of particular forms each with various causes and severities. Primary open-angle glaucoma (POAG) is the most generally perceived kind of glaucoma. This study investigated the genetic association of single nucleotide polymorphisms (SNPs; rs10483727 and rs33912345) at the SIX1/SIX6 locus with primary open-angle glaucoma (POAG) in the Pakistani population. The SIX6 gene plays an important role in ocular development and has been associated with morphology of the optic nerve. A total of 100 patients clinically diagnosed with glaucoma and 100 control individuals of age over 40 were enrolled in the study. Genomic DNA was extracted by organic extraction method. The SNP genotyping was done by (i) PCR based restriction fragment length polymorphism (RFLP) and sequencing method. Significant genetic associations were observed for rs10483727 (risk allele T) and rs33912345 (risk allele C) with POAG. Hence, it was concluded that Six6 gene is genetically associated with pathogenesis of Glaucoma in Pakistan.

Keywords: genotyping, Pakistani population, primary open-angle glaucoma, SIX6 gene

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Authors: Othman Elmahdy Othman, Agnés Germot, Daniel Petit, Muhammad Khodary, Abderrahman Maftah

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Recently, the control (D-loop) and cytochrome b (Cyt b) regions of mtDNA have received more attention due to their role in the genetic diversity and phylogenetic studies in different livestock which give important knowledge towards the genetic resource conservation. Studies based on sequencing of sheep mitochondrial DNA showed that there are five maternal lineages in the world for domestic sheep breeds; A, B, C, D and E. By using cytochrome B sequencing, we aimed to clarify the genetic affinities and phylogeny of six Egyptian sheep breeds. Blood samples were collected from 111 animals belonging to six Egyptian sheep breeds; Barki, Rahmani, Ossimi, Saidi, Sohagi and Fallahi. The total DNA was extracted and the specific primers were used for conventional PCR amplification of the cytochrome B region of mtDNA. PCR amplified products were purified and sequenced. The alignment of sequences was done using BioEdit software and DnaSP 5.00 software was used to identify the sequence variation and polymorphic sites in the aligned sequences. The result showed that the presence of 39 polymorphic sites leading to the formation of 29 haplotypes. The haplotype diversity in six tested breeds ranged from 0.643 in Rahmani breed to 0.871 in Barki breed. The lowest genetic distance was observed between Rahmani and Saidi (D: 1.436 and Dxy: 0.00127) while the highest distance was observed between Ossimi and Sohagi (D: 6.050 and Dxy: 0.00534). Neighbour-joining (Phylogeny) tree was constructed using Mega 5.0 software. The sequences of 111 analyzed samples were aligned with references sequences of different haplogroups; A, B, C, D and E. The phylogeny result showed the presence of four haplogroups; HapA, HapB, HapC and HapE in the examined samples whereas the haplogroup D was not found. The result showed that 88 out of 111 tested animals cluster with haplogroup B (79.28%), whereas 12 tested animals cluster with haplogroup A (10.81%), 10 animals cluster with haplogroup C (9.01%) and one animal belongs to haplogroup E (0.90%).

Keywords: phylogeny, genetic biodiversity, MtDNA, cytochrome B, Egyptian sheep

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Authors: Hanieh Tarbiat Khosrowshahi, Mojtaba Shakeri

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Wireless Sensor Networks (WSNs) consist of a set of sensor nodes with limited capability. WSNs may suffer from multiple node failures when they are exposed to harsh environments such as military zones or disaster locations and lose connectivity by getting partitioned into disjoint segments. Relay nodes (RNs) are alternatively introduced to restore connectivity. They cost more than sensors as they benefit from mobility, more power and more transmission range, enforcing a minimum number of them to be used. This paper addresses the problem of RN placement in a multiple disjoint network by developing a genetic algorithm (GA). The problem is reintroduced as the Steiner tree problem (which is known to be an NP-hard problem) by the aim of finding the minimum number of Steiner points where RNs are to be placed for restoring connectivity. An upper bound to the number of RNs is first computed to set up the length of initial chromosomes. The GA algorithm then iteratively reduces the number of RNs and determines their location at the same time. Experimental results indicate that the proposed GA is capable of establishing network connectivity using a reasonable number of RNs compared to the best existing work.

Keywords: connectivity restoration, genetic algorithms, multiple-node failure, relay nodes, wireless sensor networks

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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: 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: Fiona Lourenco, William Allen

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Dentofacial deformities are primarily surgically treated via orthognathic surgery. Health-related quality of life is concerned with aspects of quality of life that relate specifically to an individual’s health. Design and Setting: Retrospective analysis of patients who had orthognathic surgery from January 2018 - December 2022 at the trust using the previously validated Orthognathic Quality of Life questionnaire (OQoL). Materials and Methods: 32 Patient questionnaires (which included pre-operative and post-operative separate sections) were obtained via telephone survey. The data was analysed using the two-tailed paired t-test and Wilcoxon signed-rank test. Results: The change in perception post-surgery was highly significant (both tests resulted in p<0.001 for overall analysis as well as for each domain). Overall, a 74% improvement in QoL was seen following orthognathic surgery. Reports of improvement in each domain were as follows: 71% in the social aspect of the deformity domain, 76% in facial aesthetics, 60% in function, and 57% improvement in awareness of facial deformity. Conclusion: The assessment of QoL is becoming progressively imperative in clinical research. The above data shows that orthognathic surgery has a significant improvement in the QoL of patients post-operatively. The results demonstrate improvement in all domains, with perceptions in facial aesthetics seeing the highest change post-operatively.

Keywords: dentofacial, oral, facial asymmetry, orthognathic surgery, quality of life

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Authors: Mandeep Singh Azad.Dibyendu Chakraborty, Vikas Vohra

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Introduction: Poonch is one of the remotest districts of the Jammu and Kashmir (UT) and situated on international borders. This native poultry population in these areas is quite hardy and thrives well in adverse climatic conditions. Till date, no local breed from this area (Jammu Province) has been characterized thus present study was undertaken with the main objectives of molecular characterization of ChB6 gene in local native chicken of Poonch region located at international borders between India and Pakistan. The chicken B-cell marker (ChB6) gene has been proposed as a candidate gene in regulating B-cell development. Material and Method: RNA was isolated by Blood RNA Purification Kit (HiPura) and Trizol method from whole blood samples. Positive PCR products with size 1110 bp were selected for further purification, sequencing and analysis. The amplified PCR product was sequenced by Sangers dideoxy chain termination method. The obtained sequence of ChB6 gene of Poonchi chicken were compared by MEGAX software. BioEdit software was used to construct phylogenic tree, and Neighbor Joining method was used to infer evolutionary history. In order to compute evolutionary distance Maximum Composite Likelihood method was used. Results: The positively amplified samples of ChB6 genes were then subjected to Sanger sequencing with “Primer Walking. The sequences were then analyzed using MEGA X and BioEdit software. The sequence results were compared with other reported sequence from different breed of chicken and with other species obtained from the NCBI (National Center for Biotechnology Information). ClustalW method using MEGA X software was used for multiple sequence alignment. The sequence results of ChB6 gene of Poonchi chicken was compared with Centrocercus urophasianus, G. gallus mRNA for B6.1 protein, G. gallus mRNA for B6.2, G. gallus mRNA for B6.3, Gallus gallus B6.1, Halichoeres bivittatus, Miniopterus fuliginosus Ferringtonia patagonica, Tympanuchus phasianellus. The genetic distances were 0.2720, 0.0000, 0.0245, 0.0212, 0.0147, 1.6461, 2.2394, 2.0070 and 0.2363 for ChB6 gene of Poonchi chicken sequence with other sequences in the present study respectively. Sequencing results showed variations between different species. It was observed that AT content were higher then GC content for ChB6 gene. The lower AT content suggests less thermostable. It was observed that there was no sequence difference within the Poonchi population for ChB6 gene. The high homology within chicken population indicates the conservation of ChB6 gene. The maximum difference was observed with Miniopterus fuliginosus (Eastern bent-wing bat) followed by Ferringtonia patagonica and Halichoeres bivittatus. Conclusion: Genetic variation is the essential component for genetic improvement. The results of immune related gene Chb6 shows between population genetic variability. Therefore, further association studies of this gene with some prevalent diseases in large population would be helpful to identify disease resistant/ susceptible genotypes in the indigenous chicken population.

Keywords: ChB6, sequencing, ClustalW, genetic distance, poonchi chicken, SNP

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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: 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: M. Ntswane, N. Mbuma, M. Labuschagne, A. Mofokeng, M. Rantso

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Cowpea is an essential legume for the nutrition and health of millions of people in different regions. The production and productivity of the crop are very limited in South Africa due to a lack of adapted and stable genotypes. The improvement of nutritional quality is made possible by manipulating the genes of diverse cowpea genotypes available around the world. Assessing the adaptability and stability of the cowpea mutant genotypes for yield and nutritional quality requires examining them in different environments. The objective of the study was to determine the adaptability and stability of cowpea mutant genotypes under South African conditions and to identify the superior genotypes that combine grain yield components, antioxidants, and nutritional quality. Thirty-one cowpea genotypes were obtained from the Agricultural Research Council grain crops (ARC-GC) and were planted in Glen, Mafikeng, Polokwane, Potchefstroom, Taung, and Vaalharts during the 2021/22 summer cropping season. Significant genotype by location interactions indicated the possibility of genetic improvement of these traits. The genotype plus genotype by environment indicated broad adaptability and stability of mutant genotypes. The principal component analysis identified the association of the genotypes with the traits. Phenotypic correlation analysis showed that Zn and protein content were significant and positively correlated and suggested the possibility of indirect selection of these traits. Results from this study could be used to help plant breeders in making informed decisions and developing nutritionally improved cowpea genotypes with the aim of addressing the challenges of poor nutritional quality.

Keywords: cowpea seeds, adaptability, stability, mineral elements, protein content

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Authors: Andreea D. Șerban, Răzvan Mălăncuș, Mihaela Ivancia, Șteofil Creangă

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Just as air influences the quality of life in the terrestrial environment, water, as a living environment, is one of great importance when it comes to the quality of life of underwater animals, which acquires an even higher degree of importance when analyzing underwater creatures as future products for human consumption. Thus, going beyond the ideal environment, in which all water quality parameters are permanently in perfect standards for reproduction, growth, and development of fish material and customizing this study to reality, it was demonstrated the importance of reproduction, development, and growth of biological material, necessary in the population fish farms, in the same environment to gain the maximum yield that a fish farm can offer. The biological material used was harvested from 3 fish farms located at great distances from each other to have environments with different parameters. The specimens were clinically healthy at 2 years of age. Thus, the differences in water quality parameters had effects on specimens from other environments, describing large curves in their evolution in new environments. Another change was observed in the new environment, the specimens contributing with the "genetic package" to its modification, tending to a balance of the parameters studied to the values in the environment in which they lived until the time of the experiment. The study clearly showed that adaptability to the environment in which an individual has developed and grown is not valid in environments with different parameters, resulting even in the fatality of one sample during the experiment. In some specimens, the values of the studied hematological parameters were halved after the transfer to the new environment, and in others, the same parameters were doubled. The study concludes that the specimens were adapted to the environment in which they developed and grew, their descendants having a higher value of heritability only in the initial environment. It is known that heritability is influenced 50% by the genetic package of the individual and 50% by the environment, by removing the value of the environment, the duration of improvement of characters of interest will be shorter and the maximum yield of fish farms can be achieved in a smaller period.

Keywords: environment, heritability, quality, water

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Authors: Sabir Messalti, Ahmed Gherbi, Ahmed Bouchlaghem

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This paper presents comparative study for power systems transient stability improvement using three FACTS devices: the SVC(Static Var Compensator), the Thyristor Control Breaking Resistor (TCBR) and superconducting fault current limiter (SFCL)The transient stability is assessed by the criterion of relative rotor angles. Critical Clearing Time (CCT) is used as an index for evaluated transient stability. The present study is tested on the WSCC3 nine-bus system in the case of three-phase short circuit fault on one transmission line.

Keywords: SVC, TCBR, SFCL, power systems transient stability improvement

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Authors: Stephanie Aguirre Moreno, Jesús Everardo Olguín Tiznado, Claudia Camargo Wilson, Juan Andrés López Barreras

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This research work presents a proposal to evaluate the environmental performance of a Higher Education Institution (HEI) in Mexico in order to minimize their environmental impact. Given that public education has limited financial resources, it is necessary to conduct studies that support priorities in decision-making situations and thus obtain the best cost-benefit ratio of continuous improvement programs as part of the environmental management system implemented. The methodology employed, adapted from the Environmental Effect Analysis (EEA), weighs the environmental aspects identified in the environmental diagnosis by two characteristics. Number one, environmental priority through the perception of the stakeholders, compliance of legal requirements, and environmental impact of operations. Number two, the possibility of improvement, which depends of factors such as the exchange rate that will be made, the level of investment and the return time of it. The highest environmental priorities, or hot spots, identified in this evaluation were: electricity consumption, water consumption and recycling, and disposal of municipal solid waste. However, the possibility of improvement for the disposal of municipal solid waste is higher, followed by water consumption and recycling, in spite of having an equal possibility of improvement to the energy consumption, time of return and cost-benefit is much greater.

Keywords: environmental performance, environmental priority, possibility of improvement, continuous improvement programs

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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: Adamu Usman, Grace Stanley Balami

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Pearl millet (Pennisetum glaucum L. R. Br.) is a cereal cultivated in arid and semi-arid areas of the world. It supports more than 100 million people around the world. Parasitic weed (Striga hermonthica Del. Benth) is a major constraint to its production. Estimated yield losses are put at 10 - 95% depending on variety, ecology and cultural practices. Potentials in selection of traits in pearl millets for grain yield have been reported and it depends on genotypic variability and heritability among landraces. Variability and heritability among cultivars could offer opportunities for improvement. The study was conducted to determine the genetic variability among cultivars and estimate broad sense heritability among grain yield and related traits. F1 breeding populations were generated with 9 parental cultivars, viz; Ex-Gubio, Ex-Monguno, Ex-Baga as males and PEO 5984, Super-SOSAT, SOSAT-C88, Ex-Borno and LCIC9702 as females through Line × Tester mating during 2017 dry season at Lushi Irrigation Station, Bauchi Metropolitan in Bauchi State, Nigeria. The F1 population and the parents were evaluated during cropping season of 2018 at Bauchi and Maiduguri. Data collected were subjected to analysis of variance. Results showed significant difference among cultivars and among traits indicating variability. Number of plants at emergence, days to 50% flowering, days to 100% flowering, plant height, panicle length, number of plants at harvest, Striga count at 90 days after sowing, panicle weight and grain yield were significantly different. Significant variability offer opportunity for improvement as superior individuals can be isolated. Genotypic variance estimates of traits were largely greater than environmental variances except in plant height and 1000 seed weight. Environmental variances were low and in some cases negligible. The phenotypic variances of all traits were higher than genotypic variances. Similarly phenotypic coefficient of variation (PCV) was higher than genotypic coefficient of variation (GCV). High heritability was found in days to 50% flowering (90.27%), Striga count at 90 days after sowing (90.07%), number of plants at harvest (87.97%), days to 100% flowering (83.89%), number of plants at emergence (82.19%) and plant height (73.18%). Greater heritability estimates could be due to presence of additive gene. The result revealed wider variability among genotypes and traits. Traits having high heritability could easily respond to selection. High value of GCV, PCV and heritability estimates indicate that selection for these traits are possible and could be effective.

Keywords: variability, heritability, phenotypic, genotypic, striga

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Authors: Jiawen Wang, Qijun Chen

Abstract:

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: 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

Abstract:

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

Procedia PDF Downloads 429