Search results for: non genetic factors

Authors: M. Saiful Islam, M. Mohandes, S. Rehman, S. Badran

Abstract:

Increasing necessity of wind power is directing us to have precise knowledge on wind resources. Methodical investigation of potential locations is required for wind power deployment. High penetration of wind energy to the grid is leading multi megawatt installations with huge investment cost. This fact appeals to determine appropriate places for wind farm operation. For accurate assessment, detailed examination of wind speed profile, relative humidity, temperature and other geological or atmospheric parameters are required. Among all of these uncertainty factors influencing wind power estimation, vertical extrapolation of wind speed is perhaps the most difficult and critical one. Different approaches have been used for the extrapolation of wind speed to hub height which are mainly based on Log law, Power law and various modifications of the two. This paper proposes a Artificial Neural Network (ANN) and Genetic Algorithm (GA) based hybrid model, namely GA-NN for vertical extrapolation of wind speed. This model is very simple in a sense that it does not require any parametric estimations like wind shear coefficient, roughness length or atmospheric stability and also reliable compared to other methods. This model uses available measured wind speeds at 10m, 20m and 30m heights to estimate wind speeds up to 100m. A good comparison is found between measured and estimated wind speeds at 30m and 40m with approximately 3% mean absolute percentage error. Comparisons with ANN and power law, further prove the feasibility of the proposed method.

Keywords: wind profile, vertical extrapolation of wind, genetic algorithm, artificial neural network, hybrid machine learning

Procedia PDF Downloads 490

Authors: Kassaye Balkew Workagegn, Gunnar Klemetsdal, Hans Magnus Gjøen

Abstract:

In this study, the first objective was to investigate whether non-lethal or non-invasive methods, utilizing body measurements, could be used to efficiently predict fillet weight and fillet yield for a complete diallel cross of three Nile tilapia (Oreochromis niloticus) strains collected from three Ethiopian Rift Valley lakes, Lakes Ziway, Koka and Chamo. The second objective was to estimate heritability of body weight, actual and predicted fillet traits, as well as genetic correlations between these traits. A third goal was to estimate additive, reciprocal, and heterosis effects for body weight and the various fillet traits. As in females, early sexual maturation was widespread, only 958 male fish from 81 full-sib families were used, both for the prediction of fillet traits and in genetic analysis. The prediction equations from body measurements were established by forward regression analysis, choosing models with the least predicted residual error sums of squares (PRESS). The results revealed that body measurements on live Nile tilapia is well suited to predict fillet weight but not fillet yield (R²= 0.945 and 0.209, respectively), but both models were seemingly unbiased. The genetic analyses were carried out with bivariate, multibreed models. Body weight, fillet weight, and predicted fillet weight were all estimated with a heritability ranged from 0.23 to 0.28, and with genetic correlations close to one. Contrary, fillet yield was only to a minor degree heritable (0.05), while predicted fillet yield obtained a heritability of 0.19, being a resultant of two body weight variables known to have high heritability. The latter trait was estimated with genetic correlations to body weight and fillet weight traits larger than 0.82. No significant differences among strains were found for their additive genetic, reciprocal, or heterosis effects, while total heterosis effects were estimated as positive and significant (P < 0.05). As a conclusion, prediction of prediction of fillet weight based on body measurements is possible, but not for fillet yield.

Keywords: additive, fillet traits, genetic correlation, heritability, heterosis, prediction, reciprocal

Procedia PDF Downloads 187

Authors: M. Sakthivel, A. Devaki, D. Balasubramanyam, P. Kumarasamy, A. Raja, R. Anilkumar, H. Gopi

Abstract:

The genetic parameters of growth traits in the New Zealand White rabbits maintained at Sheep Breeding and Research Station, Sandynallah, The Nilgiris, India were estimated by partitioning the variance and covariance components. The (co)variance components of body weights at weaning (W42), post-weaning (W70) and marketing (W135) age and growth efficiency traits viz., average daily gain (ADG), relative growth rate (RGR) and Kleiber ratio (KR) estimated on a daily basis at different age intervals (1=42 to 70 days; 2=70 to 135 days and 3=42 to 135 days) from weaning to marketing were estimated by restricted maximum likelihood, fitting six animal models with various combinations of direct and maternal effects. Data were collected over a period of 15 years (1998 to 2012). A log-likelihood ratio test was used to select the most appropriate univariate model for each trait, which was subsequently used in bivariate analysis. Heritability estimates for W42, W70 and W135 were 0.42 ± 0.07, 0.40 ± 0.08 and 0.27 ± 0.07, respectively. Heritability estimates of growth efficiency traits were moderate to high (0.18 to 0.42). Of the total phenotypic variation, maternal genetic effect contributed 14 to 32% for early body weight traits (W42 and W70) and ADG1. The contribution of maternal permanent environmental effect varied from 6 to 18% for W42 and for all the growth efficiency traits except for KR2. Maternal permanent environmental effect on most of the growth efficiency traits was a carryover effect of maternal care during weaning. Direct maternal genetic correlations, for the traits in which maternal genetic effect was significant, were moderate to high in magnitude and negative in direction. Maternal effect declined as the age of the animal increased. The estimates of total heritability and maternal across year repeatability for growth traits were moderate and an optimum rate of genetic progress seems possible in the herd by mass selection. The estimates of genetic and phenotypic correlations among body weight traits were moderate to high and positive; among growth efficiency traits were low to high with varying directions; between body weights and growth efficiency traits were very low to high in magnitude and mostly negative in direction. Moderate to high heritability and higher genetic correlation in body weight traits promise good scope for genetic improvement provided measures are taken to keep the inbreeding at the lowest level.

Keywords: genetic parameters, growth traits, maternal effects, rabbit genetics

Procedia PDF Downloads 447

Authors: Halil Ibrahim Demir, Caner Erden, Mumtaz Ipek, Ozer Uygun

Abstract:

Traditionally, the three important manufacturing functions, which are process planning, scheduling and due-date assignment, are performed separately and sequentially. For couple of decades, hundreds of studies are done on integrated process planning and scheduling problems and numerous researches are performed on scheduling with due date assignment problem, but unfortunately the integration of these three important functions are not adequately addressed. Here, the integration of these three important functions is studied by using genetic, random-genetic hybrid, simulated annealing, random-simulated annealing hybrid and random search techniques. As well, the importance of the integration of these three functions and the power of meta-heuristics and of hybrid heuristics are studied.

Keywords: process planning, weighted scheduling, weighted due-date assignment, genetic search, simulated annealing, hybrid meta-heuristics

Procedia PDF Downloads 469

Authors: Muhammad R. Bello, Mamman A. Wasagu, Yahya M. Kamar

Abstract:

The study investigated the effects of computer-aided instructional package (CAIP) on performance and retention of genetic concepts among secondary school students in Niger State. Quasi-experimental research design i.e. pre-test-post-test experimental and control groups were adopted for the study. The population of the study was all senior secondary school three (SS3) students’ offering biology. A sample of 223 students was randomly drawn from six purposively selected secondary schools. The researchers’ developed computer aided instructional package (CAIP) on genetic concepts was used as treatment instrument for the experimental group while the control group was exposed to the conventional lecture method (CLM). The instrument for data collection was a Genetic Performance Test (GEPET) that had 50 multiple-choice questions which were validated by science educators. A Reliability coefficient of 0.92 was obtained for GEPET using Pearson Product Moment Correlation (PPMC). The data collected were analyzed using IBM SPSS Version 20 package for computation of Means, Standard deviation, t-test, and analysis of covariance (ANCOVA). The ANOVA analysis (Fcal (220) = 27.147, P < 0.05) shows that students who received instruction with CAIP outperformed the students who received instruction with CLM and also had higher retention. The findings also revealed no significant difference in performance and retention between male and female students (tcal (103) = -1.429, P > 0.05). It was recommended amongst others that teachers should use computer-aided instructional package in teaching genetic concepts in order to improve students’ performance and retention in biology subject. Keywords: Computer-aided Instructional Package, Performance, Retention and Genetic Concepts.

Keywords: computer aided instructional package, performance, retention, genetic concepts, senior secondary school students

Procedia PDF Downloads 362

Authors: Kelsi Hagerty, Ami Rosen, Aaliyah Heyward, Nadia Ali, Emily Brown, Erin Demo, Yue Guan, Modele Ogunniyi, Brianna McDaniels, Alanna Morris, Kunal Bhatt

Abstract:

Hereditary transthyretin amyloidosis (hATTR) is a progressive, multi-systemic, and life-threatening disease caused by a disruption in the TTR protein that delivers thyroxine and retinol to the liver. This disruption causes the protein to misfold into amyloid fibrils, leading to the accumulation of the amyloid fibrils in the heart, nerves, and GI tract. Over 130 variants in the TTR gene are known to cause hATTR. The Val122Ile variant is the most common in the United States and is seen almost exclusively in people of African descent. TTR variants are inherited in an autosomal dominant fashion and have incomplete penetrance and variable expressivity. Individuals with hATTR may exhibit symptoms from as early as 30 years to as late as 80 years of age. hATTR is characterized by a wide range of clinical symptoms such as cardiomyopathy, neuropathy, carpal tunnel syndrome, and GI complications. Without treatment, hATTR leads to progressive disease and can ultimately lead to heart failure. hATTR disproportionately affects individuals of African descent; the estimated prevalence of hATTR among Black individuals in the US is 3.4%. Unfortunately, hATTR is often underdiagnosed and misdiagnosed because many symptoms of the disease overlap with other cardiac conditions. Due to the progressive nature of the disease, multi-systemic manifestations that can lead to a shortened lifespan, and the availability of free genetic testing and promising FDA-approved therapies that enhance treatability, early identification of individuals with a pathogenic hATTR variant is important, as this can significantly impact medical management for patients and their relatives. Furthermore, recent literature suggests that TTR genetic testing should be performed in all patients with suspicion of TTR-related cardiomyopathy, regardless of age, and that follow-up with genetic counseling services is recommended. Relatives of patients with hATTR benefit from genetic testing because testing can identify carriers early and allow relatives to receive regular screening and management. Despite the striking prevalence of hATTR among Black individuals, hATTR remains underdiagnosed in this patient population, and germline genetic testing for hATTR in Black individuals seems to be underrepresented, though the reasons for this have not yet been brought to light. Historically, Black patients experience a number of barriers to seeking healthcare that has been hypothesized to perpetuate the underdiagnosis of hATTR, such as lack of access and mistrust of healthcare professionals. Prior research has described a myriad of factors that shape an individual’s decision about whether to pursue presymptomatic genetic testing for a familial pathogenic variant, such as family closeness and communication, family dynamics, and a desire to inform other family members about potential health risks. This study explores these factors through 10 in-depth interviews with patients with hATTR about what factors may be contributing to the underdiagnosis of hATTR in the Black population. Participants were selected from the Emory University Amyloidosis clinic based on having a molecular diagnosis of hATTR. Interviews were recorded and transcribed verbatim, then coded using MAXQDA software. Thematic analysis was completed to draw commonalities between participants. Upon preliminary analysis, several themes have emerged. Barriers identified include i) Misdiagnosis and a prolonged diagnostic odyssey, ii) Family communication and dynamics surrounding health issues, iii) Perceptions of healthcare and one’s own health risks, and iv) The need for more intimate provider-patient relationships and communication. Overall, this study gleaned valuable insight from members of the Black community about possible factors contributing to the underdiagnosis of hATTR, as well as potential solutions to go about resolving this issue.

Keywords: cardiac amyloidosis, heart failure, TTR, genetic testing

Procedia PDF Downloads 97

Authors: Kamel Barka, Lyamine Guezouli, Assem Rezki

Abstract:

In this article, we propose a protocol called DataGA-DRF (a protocol for Data collection using a Genetic Algorithm through Dynamic Reference Points) that collects data from Heterogeneous wireless sensor networks. This protocol is based on DGA (Destination selection according to Genetic Algorithm) to control the movement of the UAV (Unmanned aerial vehicle) between dynamic reference points that virtually represent the sensor node deployment. The dynamics of these points ensure an even distribution of energy consumption among the sensors and also improve network performance. To determine the best points, DataGA-DRF uses a classification algorithm such as K-Means.

Keywords: heterogeneous wireless networks, unmanned aerial vehicles, reference point, collect data, genetic algorithm

Procedia PDF Downloads 82

Authors: Delowar Hossain, Genci Capi

Abstract:

This paper concerns with the problem of deep learning parameters tuning using a genetic algorithm (GA) in order to improve the performance of deep learning (DL) method. We present a GA based DL method for robot object recognition and grasping. GA is used to optimize the DL parameters in learning procedure in term of the fitness function that is good enough. After finishing the evolution process, we receive the optimal number of DL parameters. To evaluate the performance of our method, we consider the object recognition and robot grasping tasks. Experimental results show that our method is efficient for robot object recognition and grasping.

Keywords: deep learning, genetic algorithm, object recognition, robot grasping

Procedia PDF Downloads 353

Authors: Girija Madhavanprabhakaran, Frincy Franacis, Sheeba Elizabeth John

Abstract:

Introduction: A wide range of prenatal genetic screening is introduced with increasing incidences of congenital anomalies even in low-risk pregnancies and is an emerging standard of care. Being frontline caretakers, the role and responsibilities of nurses and midwives are critical as they are working along with couples to provide evidence-based supportive educative care. The increasing genetic disorders and advances in prenatal genetic screening with limited genetic counselling facilities urge nurses and midwifery nurses with essential competencies to help couples to take informed decision. Objective: This integrative literature review aimed to explore nurse midwives’ knowledge and role in prenatal screening and genetic counselling competency and the challenges faced by them to cater to all pregnant women to empower their autonomy in decision making and ensuring psychological comfort. Method: An electronic search using keywords prenatal screening, genetic counselling, prenatal counselling, nurse midwife, nursing education, genetics, and genomics were done in the PUBMED, SCOPUS and Medline, Google Scholar. Finally, based on inclusion criteria, 8 relevant articles were included. Results: The main review results suggest that nurses and midwives lack essential support, knowledge, or confidence to be able to provide genetic counselling and help the couples ethically to ensure client autonomy and decision making. The majority of nurses and midwives reported inadequate levels of knowledge on genetic screening and their roles in obtaining family history, pedigrees, and providing genetic information for an affected client or high-risk families. The deficiency of well-recognized and influential clinical academic midwives in midwifery practice is also reported. Evidence recommended to update and provide sound educational training to improve nurse-midwife competence and confidence. Conclusion: Overcoming the challenges to achieving informed choices about fetal anomaly screening globally is a major concern. Lack of adequate knowledge and counselling competency, communication insufficiency, need for education and policy are major areas to address. Prenatal nurses' and midwives’ knowledge on prenatal genetic screening and essential counselling competencies can ensure services to the majority of pregnant women around the globe to be better-informed decision-makers and enhances their autonomy, and reduces ethical dilemmas.

Keywords: challenges, genetic counselling, prenatal screening, prenatal counselling

Procedia PDF Downloads 199

Authors: Chunye Gong, Ming Tie, Jie Liu, Weimin Bao, Xinbiao Gan, Shengguo Li, Bo Yang, Xuguang Chen, Tiaojie Xiao, Yang Sun

Abstract:

Large-scale CFD simulation relies on high-performance parallel computing, and the load balance is the key role which affects the parallel efficiency. This paper focuses on the load-balancing problem of parallel CFD simulation with structured mesh. A mathematical model for this load-balancing problem is presented. The genetic algorithm, fitness computing, two-level code are designed. Optimal selector, robust operator, and local optimization operator are designed. The properties of the presented genetic algorithm are discussed in-depth. The effects of optimal selector, robust operator, and local optimization operator are proved by experiments. The experimental results of different test sets, DLR-F4, and aircraft design applications show the presented load-balancing algorithm is robust, quickly converged, and is useful in real engineering problems.

Keywords: genetic algorithm, load-balancing algorithm, optimal variation, local optimization

Procedia PDF Downloads 185

Authors: Sanjay Kumar Parjapati, Ajai Jain

Abstract:

This paper presents optimization of makespan for ‘n’ jobs and ‘m’ machines flexible job shop scheduling problem with sequence dependent setup time using genetic algorithm (GA) approach. A restart scheme has also been applied to prevent the premature convergence. Two case studies are taken into consideration. Results are obtained by considering crossover probability (pc = 0.85) and mutation probability (pm = 0.15). Five simulation runs for each case study are taken and minimum value among them is taken as optimal makespan. Results indicate that optimal makespan can be achieved with more than one sequence of jobs in a production order.

Keywords: flexible job shop, genetic algorithm, makespan, sequence dependent setup times

Procedia PDF Downloads 332

Authors: Asiye Ciftci, Zeki Kaya

Abstract:

Populus nigra is one of the most economically and ecologically important forest trees in Turkey, well known for its rapid growth, good ability to vegetative propagation and the extreme uses of its wood. Due to overexploitation, loss of natural distribution area and extreme hybridization and introgression, Populus nigra is one of the most threatened tree species in Turkey and Europe. Using 20 nuclear microsatellite loci, the genetic structure of European black poplar populations along the two largest rivers of Turkey was analyzed. All tested loci were highly polymorphic, displaying 5 to 15 alleles per locus. Observed heterozygosity (overall Ho = 0.79) has been higher than the expected (overall He = 0.58) in each population. Low level of genetic differentiation among populations (FST= 0,03) and excess of heterozygotes for each river were found. Human-mediated dispersal, phenotypic selection, high level of gene flow and extensive circulations of clonal materials may cause those situations. The genetic data obtained from this study could provide the basis for efficient in situ and ex-situ conservation and restoration of species natural populations in its natural habitat as well as having sustainable breeding and poplar plantations in the future.

Keywords: populus, clonal, loci, ex situ

Procedia PDF Downloads 295

Authors: Saleem Z. Ramadan

Abstract:

The material selection problem is concerned with the determination of the right material for a certain product to optimize certain performance indices in that product such as mass, energy density, and power-to-weight ratio. This paper is concerned about optimizing the selection of the manufacturing process along with the material used in the product under performance indices and availability constraints. In this paper, the material selection problem is formulated using binary programming and solved by genetic algorithm. The objective function of the model is to minimize the total manufacturing cost under performance indices and material and manufacturing process availability constraints.

Keywords: optimization, material selection, process selection, genetic algorithm

Procedia PDF Downloads 420

Authors: Ahmed Z. Gabr, Ahmed A. Helal, Hussein E. Said

Abstract:

With the incessant increase of power systems capacity and voltage grade, the safety of grounding grid becomes more and more prominent. In this paper, the designing substation grounding grid is presented by means of genetic algorithm (GA). This approach purposes to control the grounding cost of the power system with the aid of controlling grounding rod number and conductor lengths under the same safety limitations. The proposed technique is used for the design of the substation grounding grid in Khalda Petroleum Company “El-Qasr” power plant and the design was simulated by using CYMGRD software for results verification. The result of the design is highly complying with IEEE 80-2000 standard requirements.

Keywords: genetic algorithm, optimum grounding grid design, power system analysis, power system protection, single layer model, substation

Procedia PDF Downloads 535

Authors: Yasaman Mohammadi

Abstract:

Executive functions are a critical component of goal-directed behavior, encompassing a diverse set of cognitive processes such as working memory, cognitive flexibility, and inhibitory control. These functions are known to decline with age, but the precise mechanisms underlying this decline remain unclear. This paper provides an in-depth review of recent research investigating age-related changes in executive functions, drawing on insights from neuroimaging, genetics, and cognitive neuroscience. Through an interdisciplinary approach, this paper offers a nuanced understanding of the complex interplay between neural mechanisms, genetic factors, and cognitive processes that contribute to executive function decline in aging. Here, we investigate how different neuroimaging methods, like functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), have helped scientists better understand the brain bases for age-related declines in executive function. Additionally, we discuss the role of genetic factors in mediating individual differences in executive functions across the lifespan, as well as the potential for cognitive interventions to mitigate age-related decline. Overall, this paper presents a comprehensive and integrative view of the current state of knowledge regarding age-related changes in executive functions. It underscores the need for continued interdisciplinary research to fully understand the complex and dynamic nature of executive function decline in aging, with the ultimate goal of developing effective interventions to promote healthy cognitive aging.

Keywords: executive functions, aging, neuroimaging, cognitive neuroscience, working memory, cognitive training

Procedia PDF Downloads 67

Authors: Wafa Slaibi Alsharafat

Abstract:

Genetic algorithms (GA) are random algorithms as random numbers that are generated during the operation of the algorithm determine what happens. This means that if GA is applied twice to optimize exactly the same problem it might produces two different answers. In this project, we propose an evolutionary algorithm and Genetic Algorithm (GA) to be implemented in symmetric encryption and decryption. Here, user's message and user secret information (key) which represent plain text to be transferred into cipher text.

Keywords: GA, encryption, decryption, crossover

Procedia PDF Downloads 446

Authors: Sonveer Singh, Sanjay Agrawal, D. V. Avasthi, Jayant Shekhar

Abstract:

The aim of this paper is to improve the efficiency of photovoltaic thermal (PVT) system with the help of Genetic Algorithms with multi-objective function. There are some parameters that affect the efficiency of PVT system like depth and length of the channel, velocity of flowing fluid through the channel, thickness of the tedlar and glass, temperature of inlet fluid i.e. all above parameters are considered for optimization. An attempt has been made to the model and optimizes the parameters of glazed hybrid single channel PVT module when two objective functions have been considered separately. The two objective function for optimization of PVT module is overall electrical and thermal efficiency. All equations for PVT module have been derived. Using genetic algorithms (GAs), above two objective functions of the system has been optimized separately and analysis has been carried out for two cases. Two cases are: Case-I; Improvement in electrical and thermal efficiency when overall electrical efficiency is optimized, Case-II; Improvement in electrical and thermal efficiency when overall thermal efficiency is optimized. All the parameters that are used in genetic algorithms are the parameters that could be changed, and the non-changeable parameters, like solar radiation, ambient temperature cannot be used in the algorithm. It has been observed that electrical efficiency (14.08%) and thermal efficiency (19.48%) are obtained when overall thermal efficiency was an objective function for optimization. It is observed that GA is a very efficient technique to estimate the design parameters of hybrid single channel PVT module.

Keywords: genetic algorithm, energy, exergy, PVT module, optimization

Procedia PDF Downloads 605

Authors: Artem Kim, Clara Savary, Christele Dubourg, Wilfrid Carre, Houda Hamdi-Roze, Valerie Dupé, Sylvie Odent, Marie De Tayrac, Veronique David

Abstract:

Holoprosencephaly (HPE) is a rare congenital brain malformation resulting from the incomplete separation of the two cerebral hemispheres. It is characterized by a wide phenotypic spectrum and a high degree of locus heterogeneity. Genetic defects in 16 genes have already been implicated in HPE, but account for only 30% of cases, suggesting that a large part of genetic factors remains to be discovered. HPE has been recently redefined as a complex multigenic disorder, requiring the joint effect of multiple mutational events in genes belonging to one or several developmental pathways. The onset of HPE may result from accumulation of the effects of multiple rare variants in functionally-related genes, each conferring a moderate increase in the risk of HPE onset. In order to decipher the genetic basis of HPE, unconventional patterns of inheritance involving multiple genetic factors need to be considered. The primary objective of this study was to uncover possible disease causing combinations of multiple rare variants underlying HPE by performing trio-based Whole Exome Sequencing (WES) of familial cases where no molecular diagnosis could be established. 39 families were selected with no fully-penetrant causal mutation in known HPE gene, no chromosomic aberrations/copy number variants and without any implication of environmental factors. As the main challenge was to identify disease-related variants among a large number of nonpathogenic polymorphisms detected by WES classical scheme, a novel variant prioritization approach was established. It combined WES filtering with complementary gene-level approaches: transcriptome-driven (RNA-Seq data) and clinically-driven (public clinical data) strategies. Briefly, a filtering approach was performed to select variants compatible with disease segregation, population frequency and pathogenicity prediction to identify an exhaustive list of rare deleterious variants. The exome search space was then reduced by restricting the analysis to candidate genes identified by either transcriptome-driven strategy (genes sharing highly similar expression patterns with known HPE genes during cerebral development) or clinically-driven strategy (genes associated to phenotypes of interest overlapping with HPE). Deeper analyses of candidate variants were then performed on a family-by-family basis. These included the exploration of clinical information, expression studies, variant characteristics, recurrence of mutated genes and available biological knowledge. A novel bioinformatics pipeline was designed. Applied to the 39 families, this final integrated workflow identified an average of 11 candidate variants per family. Most of candidate variants were inherited from asymptomatic parents suggesting a multigenic inheritance pattern requiring the association of multiple mutational events. The manual analysis highlighted 5 new strong HPE candidate genes showing recurrences in distinct families. Functional validations of these genes are foreseen.

Keywords: complex genetic disorder, holoprosencephaly, multiple rare variants, whole exome sequencing

Procedia PDF Downloads 203

Authors: Nicolae Bold, Daniel Nijloveanu

Abstract:

The idea of cropping-system is a method used by farmers. It is an environmentally-friendly method, protecting the natural resources (soil, water, air, nutritive substances) and increase the production at the same time, taking into account some crop particularities. The combination of this powerful method with the concepts of genetic algorithms results into a possibility of generating sequences of crops in order to form a rotation. The usage of this type of algorithms has been efficient in solving problems related to optimization and their polynomial complexity allows them to be used at solving more difficult and various problems. In our case, the optimization consists in finding the most profitable rotation of cultures. One of the expected results is to optimize the usage of the resources, in order to minimize the costs and maximize the profit. In order to achieve these goals, a genetic algorithm was designed. This algorithm ensures the finding of several optimized solutions of cropping-systems possibilities which have the highest profit and, thus, which minimize the costs. The algorithm uses genetic-based methods (mutation, crossover) and structures (genes, chromosomes). A cropping-system possibility will be considered a chromosome and a crop within the rotation is a gene within a chromosome. Results about the efficiency of this method will be presented in a special section. The implementation of this method would bring benefits into the activity of the farmers by giving them hints and helping them to use the resources efficiently.

Keywords: chromosomes, cropping, genetic algorithm, genes

Procedia PDF Downloads 427

Authors: Tareg Belali, Mosleh Abomughaid, Muhanad Alhujaily

Abstract:

HNF4a is one of the steroid hormone receptor family of transcription factors with roles in the development of the liver and the regulation of several critical metabolic pathways, such as glycolysis, drug metabolism, and apolipoproteins and blood coagulation. The transcriptional potency of HNF4a is well known due to its involvement in diabetes and other metabolic diseases. However, recently HNF4a has been discovered to be closely associated with several haematological disorders, mainly because of genetic mutations, drugs, and hepatic disorders. We review HNF4a structure and function and its role in haematological disorders. We discuss possible good therapies that are based on targeting HNF4a.

Keywords: hepatocyte nuclear factor 4 alpha, HNF4a nuclear receptor, steroid hormone receptor family of transcription factors, hematological disorders

Procedia PDF Downloads 95

Authors: Xu LiYun, Briand Florent, Fan GuoLiang

Abstract:

The loop-layout design problem (LLDP) aims at optimizing the sequence of positioning of the machines around the cyclic production line. Traffic congestion is the usual criteria to minimize in this type of problem, i.e. the number of additional cycles spent by each part in the network until the completion of its required routing sequence of machines. This paper aims at applying several improvements mechanisms such as a positioned-based crossover operator for the Genetic Algorithm (GA) called a Two Points Crossover (TPC) and an offspring selection process. The performance of the improved GA is measured using well-known examples from literature and compared to other evolutionary algorithms. Good results show that GA can still be competitive for this type of problem against more recent evolutionary algorithms.

Keywords: crossover, genetic algorithm, layout design problem, loop-layout, manufacturing optimization

Procedia PDF Downloads 279

Authors: R. M. Srivastava, Subbanna A.R.N.S, Md Abbas Ahmad, S. P.More, Shivashankar, B. Kalyanbabu

Abstract:

The similar morphology associated with high genetic variability poses problems in phylogenetic studies of Helicoverpa armigera (Hubner). To identify genetic variation of North Western Himalayan population’s, partial (Mid to terminal region) cytochrome c oxidase subunit I (COX-1) gene was amplified and sequenced for three populations collected from Pantnagar, Almora, and Chinyalisaur. The alignment of sequences with other two populations, Nagpur representing central India population and Anhui, China representing complete COX-1 sequence revealed unanimity in middle region with eleven single nucleotide polymorphisms (SNPs) in Nagpur populations. However, the consensus is missing when approaching towards terminal region, which is associated with 15 each SNPs and pair base substitutions in Chinyalisaur populations. In minimum evolution tree, all the five populations were majorly separated into two clades, one comprising of only Nagpur population and the other with rest. Amongst, North Western populations, Chinyalisaur one is promising by farming a separate clade. The pairwise genetic distance ranges from 0.025 to 0.192 with the maximum between H. armigera populations of Nagpur and Chinyalisaur. This genetic isolation of populations can be attributed to a key role of topological barriers of weather and mountain ranges and temporal barriers due to cropping patterns.

Keywords: cytochrome c oxidase subunit I, northwestern Himalayan population, Helicoverpa armigera (Noctuidae: Lepidoptera), phylogenetic relationship, genetic variation

Procedia PDF Downloads 309

Authors: Halimi Mohamed Taher, Kordoghli Bassem, Ben Hassen Mohamed, Sakli Faouzi

Abstract:

Textile industry has been an important part of many developing countries economies such as Tunisia. This industry is confronted with a challenging and increasing competitive environment. Good quality management in production process is the key factor for retaining existence especially in raw material exploitation. The present work aims to develop an intelligent system for fabric inspection. In the first step, we have studied the method used for fabric control which takes into account the default length and localization in woven. In the second step, we have used a method based on the fuzzy logic to minimize the Demerit point indicator with appropriate total rollers length, so that the quality problem becomes multi-objective. In order to optimize the total fabric quality, we have applied the genetic algorithm (GA).

Keywords: fabric control, Fuzzy logic, genetic algorithm, quality management

Procedia PDF Downloads 591

Authors: Nwogiji Cletus Olando, Oselebe Happiness Ogba, Enoch Achigan-Dako

Abstract:

Digitaria iburua, commonly known as black fonio, is a cereal crop native to Africa and extensively cultivated by smallholder farmers in Northern Benin, Togo, and Nigeria. This crop holds immense nutritional and socio-cultural value. Unfortunately, limited knowledge about its genetic diversity exists due to a lack of scientific attention. As a result, its potential for improvement in food and agriculture remains largely untapped. To address this gap, a study was conducted using 41 accessions of D. iburua stored in the genebank of the Laboratory of Genetics, Biotechnology, and Seed Science at Abomey-Calavi University, Benin. The study employed both morphological and simple sequence repeat (SSR) markers to evaluate the genetic variability of the accessions. Agro-morphological assessments were carried out during the 2020 cropping season, utilizing an alpha lattice design with three replications. The collected data encompassed qualitative and quantitative traits. Additionally, molecular variability was assessed using eleven SSR markers. The results revealed significant phenotypic variability among the evaluated accessions, leading to their classification into three main clusters. Furthermore, the eleven SSR markers identified a total of 50 alleles, averaging 4.55 alleles per locus. The primers exhibited an average polymorphic information content value of 0.43, with the DE-ARC019 primer displaying the highest value (0.59). These findings suggest a substantial degree of genetic heterogeneity within the evaluated accessions, and the SSR markers employed in the study proved highly effective in detecting and characterizing this genetic variability. In conclusion, this study highlights the presence of significant genetic diversity in black fonio and provides valuable insights for future efforts aimed at its genetic improvement and conservation.

Keywords: genetic diversity, digitaria iburua, genetic improvement, simple sequence repeat markers, Nigeria, conservation

Procedia PDF Downloads 86

Authors: Behzad Niknam, Kourosh Shahriar, Hassan Madani

Abstract:

This paper demonstrates the applicability of Hybrid Neural Networks that combine with back propagation networks (BPN) and Genetic Algorithms (GAs) for predicting the flame length of tunnel fire A hybrid neural network model has been developed to predict the flame length of tunnel fire based parameters such as Fire Heat Release rate, air velocity, tunnel width, height and cross section area. The network has been trained with experimental data obtained from experimental work. The hybrid neural network model learned the relationship for predicting the flame length in just 3000 training epochs. After successful learning, the model predicted the flame length.

Keywords: tunnel fire, flame length, ANN, genetic algorithm

Procedia PDF Downloads 643

Authors: Enea Danut Nicolae, Osman (Defta) Aurelia, Vidu Livia, Marginean Gheorghe, Defta Nicoleta, Moise Andrada

Abstract:

Today, as a result of population growth, there is an increase in demand for animal products; milk and dairy products are an important part of this category. Maintaining production at maximum levels for as long as possible is one of the main objectives of dairy farmers. Over the course of lactation, a cow's milk production is not uniform. During the initial stage of lactation, the cow's milk production follows an upward slope, a plateau, and then a downward slope, which is a reflection of the lactation curve. The evolution of the lactation curve is influenced by numerous factors, which are genetic, exploitation, physiological, environmental and technological. The aim of this study was to observe the lactation curve of Holstein cows in Romania and determine the extent to which they conform to the expected pattern. In addition, there has been an analysis of the factors which have an influence on this curve and the extent of this influence. In order to be able to carry out the present study, data were collected from three farms located in three different geographical areas. To highlight the findings, the data collected was then statistically processed and graphically interpreted. All the farms have only Holstein cows, which are kept in free stalls.

Keywords: lactation curve, Holstein, milk production, influencing factors

Procedia PDF Downloads 62

Authors: Safa A. Mohammed Ali, Ammar S. Ahamed, Mohammed Khair Abdalla

Abstract:

The objectives of this study were to estimate the means and genetic parameters of birth and weaning weight of calves of pure Holstein-Friesian cows raised in Sudan. The traits studied were:*Weight at birth *Weight at weaning. The study also included some of the important factors that affected these traits. The data were analyzed using Harvey’s Least Squares and Maximum Likelihood programme. The results obtained showed that the overall mean weight at birth of the calves under study was 34.36±0.94kg. Male calves were found to be heavier than females; the difference between the sexes was highly significant (P<0.001). The mean weight at birth of male calves was 34.27±1.17 kg while that of females was 32.51±1.14kg. The effect of sex of calves, sire and parity of dam were highly significant (P<0.001). The overall mean of weight at weaning was 67.10 ± 5.05 kg, weight at weaning was significantly (p<0.001) effected by sex of calves, sire, year and season of birth have highly significant (P<0.001) effect on either trait. Also estimates heritabilities of birth weight was (0.033±0.015) lower than heritabilities of weaning weight (0.224±0.039), and genetic correlation was 0.563, the phenotypic correlation 0.281, and the environmental correlation 0.268.

Keywords: birth, weaning, weight, friesian

Procedia PDF Downloads 665

Authors: Ben Mansour Mouin, Elloumi Abdelkarim

Abstract:

We will discuss the problem of routing a fleet of different vehicles from a central depot to different types of infrastructure-defaults with dynamic maintenance requests, modified time windows, and control of default maintained. For this reason, we propose a modified metaheuristicto to solve our mathematical model. SVRDP-CMTW is a variant VRP of an optimal vehicle plan that facilitates the maintenance task of different types of infrastructure-defaults. This task will be monitored after the maintenance, based on its priorities, the degree of danger associated with each default, and the neighborhood at the black-spots. We will present, in this paper, a multidimensional genetic algorithm “MGA” by detailing its characteristics, proposed mechanisms, and roles in our work. The coding of this algorithm represents the necessary parameters that characterize each infrastructure-default with the objective of minimizing a combination of cost, distance and maintenance times while satisfying the priority levels of the most urgent defaults. The developed algorithm will allow the dynamic integration of newly detected defaults at the execution time. This result will be displayed in our programmed interactive system at the routing time. This multidimensional genetic algorithm replaces N genetic algorithm to solve P different type problems of infrastructure defaults (instead of N algorithm for P problem we can solve in one multidimensional algorithm simultaneously who can solve all these problemsatonce).

Keywords: mathematical model, VRP, multidimensional genetic algorithm, metaheuristics

Procedia PDF Downloads 196

Authors: Nafiseh Noormohammadi, Ahmad Sobhani Najafabadi

Abstract:

Hypericins (hypericin and pseudohypericin) are natural napthodianthrone derivatives produced by Hypericum perforatum (St. John’s Wort), which have many medicinal properties such as antitumor, antineoplastic, antiviral, and antidepressant activities. Production and accumulation of hypericin in the plant are influenced by both genetic and environmental conditions. Despite the existence of different high-throughput data on the plant, genetic dimensions of hypericin biosynthesis have not yet been completely understood. In this research, 21 high-quality RNA-seq data on different parts of the plant were integrated into metabolic data to reconstruct a coexpression network. Results showed that a cluster of 30 transcripts was correlated with total hypericin. The identified transcripts were divided into three main groups based on their functions, including hypericin biosynthesis genes, transporters, detoxification genes, and transcription factors (TFs). In the biosynthetic group, different isoforms of polyketide synthase (PKSs) and phenolic oxidative coupling proteins (POCPs) were identified. Phylogenetic analysis of protein sequences integrated into gene expression analysis showed that some of the POCPs seem to be very important in the biosynthetic pathway of hypericin. In the TFs group, six TFs were correlated with total hypericin. qPCR analysis of these six TFs confirmed that three of them were highly correlated. The identified genes in this research are a rich resource for further studies on the molecular breeding of H. perforatum in order to obtain varieties with high hypericin production.

Keywords: hypericin, St. John’s Wort, data mining, transcription factors, secondary metabolites

Procedia PDF Downloads 93

Authors: Z. Nourmohammadi, F. Farahani, M. Shaker

Abstract:

Aloe is an important commercial crop available in a wide range of species and varieties in international markets. The applications of this plant have been recorded in the ancient cultures of India, Egypt, Greece, Rome and China. Aloe has been used for centuries and is currently being actively studied for medicinal purposes. Aloe is propagated through lateral buds, which is slow, very expensive and low income practice. Nowadays, it has been cultured by in vitro propagation for rapid multiplication of plants, genetic improvement of crops, obtaining disease-free clones and for progressive valuable germplasm. The present study focused on the influence of different phytohormones on rapid in vitro propagation of Aloe plants. We also investigated the effect of gamma radiation on biochemical characters as well as genetic changes. Shoot tip of 2-3 cm were collected from offshoot of Aloe barbadensis and Aloe littoralis, and were inoculated with MS medium containing various concentrations of BA (0.5, 1, 2 mg/l), IAA (0.5, 1 mg/l). The best treatment for a highest shoot number and bud proliferation was MS medium containing 2 mg/l BAP and 0.5 mg/l IAA in A. barbadensis and A. littoralis. Maximum percentage of proliferated shoot buds (90% and 95%) from a single explant were obtained in MS medium after 4-5 weeks of the second and the first subcultures, respectively. Different genome sizes were also indicated among treatments and subcultures. The mixoploids identified in flow cytometery histograms in different treatments. The effect of gamma radiation on A. littoralis showed that by increasing the dose of gamma radiation, amounts of chlorophyll A, B, carotenoids, total protein content and superoxide dismutase were significantly increased compared to control plants. Genetic variation analysis also revealed significant genetic differences between control and gamma radiation treated regenerated plants by AMOVA test. Higher genetic heterozygocity was observed in radiation treated plants. Our findings may provide useful method for improving of Aloe plant proliferation with increasing of useful material such as antioxidant enzymes.

Keywords: aloe, antioxidant enzyme, micropropagation, gamma radiation, genetic variation

Procedia PDF Downloads 428