Search results for: genetic differentiation

Authors: Rouhallah Bagheri, Morteza Mahmoudi, Hadi Moheb-Alizadeh

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In this paper, we develop a supplier selection and order allocation multi-objective model in stochastic environment in which purchasing cost, percentage of delivered items with delay and percentage of rejected items provided by each supplier are supposed to be stochastic parameters following any arbitrary probability distribution. To do so, we use dependent chance programming (DCP) that maximizes probability of the event that total purchasing cost, total delivered items with delay and total rejected items are less than or equal to pre-determined values given by decision maker. After transforming the above mentioned stochastic multi-objective programming problem into a stochastic single objective problem using minimum deviation method, we apply a genetic algorithm to get the later single objective problem solved. The employed genetic algorithm performs a simulation process in order to calculate the stochastic objective function as its fitness function. At the end, we explore the impact of stochastic parameters on the given solution via a sensitivity analysis exploiting coefficient of variation. The results show that as stochastic parameters have greater coefficients of variation, the value of objective function in the stochastic single objective programming problem is worsened.

Keywords: dependent chance programming, genetic algorithm, minimum deviation method, order allocation, supplier selection

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Authors: Hoo Cheol Lee, Dae Seung Kim, Sang Myung Jung, Gwang Heum Yoon, Hwa Sung Shin

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Loss of bone tissue can occur due to a bone tissue disease and aging or fracture. Renewable formation of bone is mainly made by its differentiation and metabolism. For this reason, osteoblasts have been studied for regeneration of bone tissue. So, tissue engineering has attracted attention as a recovery means. In tissue engineering, a particularly important factor is a scaffold that supports cell growth. For osteoblast scaffold, we used the cellulose nanowhisker (CNW) extracted from marine organism. CNW is one of an abundant material obtained from a number of plants and animals. CNW is polymer consisting of monomer cellulose and this composition offers biodegradability and biocompatibility to CNW. Mechanical strength of CNW is superior to the existing natural polymers. In addition, substances of marine origin have a low risk of secondary infection by bacteria and pathogen in contrast with those of land-derived. For evaluating its suitability as an osteoblast scaffold, we fabricate CNW film for osteoblast culture and performed the MTT assay and ALP assay to confirm its cytotoxicity and effect on differentiation. Taking together these results, we assessed CNW is a potential candidate of a material for bone tissue regeneration.

Keywords: bone regeneration, cellulose nanowhisker, marine derived material, osteoblast

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Authors: Essa Abrahim Abdulgader Saleem, Thien-My Dao

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The main objective of this paper is to optimize series-parallel system reliability using Genetic Algorithm (GA) and statistical analysis; considering system reliability constraints which involve the redundant numbers of selected components, total cost, and total weight. To perform this work, firstly the mathematical model which maximizes system reliability subject to maximum system cost and maximum system weight constraints is presented; secondly, a statistical analysis is used to optimize GA parameters, and thirdly GA is used to optimize series-parallel systems reliability. The objective is to determine the strategy choosing the redundancy level for each subsystem to maximize the overall system reliability subject to total cost and total weight constraints. Finally, the series-parallel system case study reliability optimization results are showed, and comparisons with the other previous results are presented to demonstrate the performance of our GA.

Keywords: reliability, optimization, meta-heuristic, genetic algorithm, redundancy

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Authors: E. Tandis, E. Assareh

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Designing the optimal shape of MW wind turbine blades is provided in a number of cases through evolutionary algorithms associated with mathematical modeling (Blade Element Momentum Theory). Evolutionary algorithms, among the optimization methods, enjoy many advantages, particularly in stability. However, they usually need a large number of function evaluations. Since there are a large number of local extremes, the optimization method has to find the global extreme accurately. The present paper introduces a new population-based hybrid algorithm called Genetic-Based Bees Algorithm (GBBA). This algorithm is meant to design the optimal shape for MW wind turbine blades. The current method employs crossover and neighborhood searching operators taken from the respective Genetic Algorithm (GA) and Bees Algorithm (BA) to provide a method with good performance in accuracy and speed convergence. Different blade designs, twenty-one to be exact, were considered based on the chord length, twist angle and tip speed ratio using GA results. They were compared with BA and GBBA optimum design results targeting the power coefficient and solidity. The results suggest that the final shape, obtained by the proposed hybrid algorithm, performs better compared to either BA or GA. Furthermore, the accuracy and speed convergence increases when the GBBA is employed

Keywords: Blade Design, Optimization, Genetic Algorithm, Bees Algorithm, Genetic-Based Bees Algorithm, Large Wind Turbine

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Authors: Emma K. Sales

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Durian is the flagship fruit of Mindanao and there is an abundance of several cultivars with many confusing identities/ names. The project was conducted to develop procedure for reliable and rapid detection and sorting of durian planting materials. Moreover, it is also aimed to establish specific genetic or DNA markers for routine testing and authentication of durian cultivars in question. The project developed molecular procedures for routine testing. SSR primers were also screened and identified for their utility in discriminating durian cultivars collected. Results of the study showed the following accomplishments; 1. Twenty (29) SSR primers were selected and identified based on their ability to discriminate durian cultivars, 2. Optimized and established standard procedure for identification and authentication of Durian cultivars 3. Genetic profile of durian is now available at Biotech Unit. Our results demonstrate the relevance of using molecular techniques in evaluating and identifying durian clones. The most polymorphic primers tested in this study could be useful tools for detecting variation even at the early stage of the plant especially for commercial purposes. The process developed combines the efficiency of the microsatellites development process with the optimization of non-radioactive detection process resulting in a user-friendly protocol that can be performed in two (2) weeks and easily incorporated into laboratories about to start microsatellite development projects. This can be of great importance to extend microsatellite analyses to other crop species where minimal genetic information is currently available. With this, the University can now be a service laboratory for routine testing and authentication of durian clones.

Keywords: DNA, SSR analysis, genotype, genetic diversity, cultivars

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Authors: Hyungoo Kang, Jinkoo Kim

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This study investigated the determination of the optimal location and friction force of friction dampers to effectively reduce the seismic response of a reinforced concrete structure designed without considering seismic load. To this end, the genetic algorithm process was applied and the results were compared with those obtained by simplified methods such as distribution of dampers based on the story shear or the inter-story drift ratio. The seismic performance of the model structure with optimally positioned friction dampers was evaluated by nonlinear static and dynamic analyses. The analysis results showed that compared with the system without friction dampers, the maximum roof displacement and the inter-story drift ratio were reduced by about 30% and 40%, respectively. After installation of the dampers about 70% of the earthquake input energy was dissipated by the dampers and the energy dissipated in the structural elements was reduced by about 50%. In comparison with the simplified methods of installation, the genetic algorithm provided more efficient solutions for seismic retrofit of the model structure.

Keywords: friction dampers, genetic algorithm, optimal design, RC buildings

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Authors: Sahriye Sonmez, Salih Ulger, Mustafa Kaplan, Mustafa Karhan

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The objective of this study was to investigate the effects of external ALAR application on nutrients contents in leaf and node in ‘on (bearing)’ and ‘off (non-bearing)’ years in Memecik olive trees. For this purpose; 2000 mg L-1 ALAR was externally applied to Memecik olive trees, and leaf and node samples from olive trees were taken during the induction, initiation and differentiation periods in ‘on’ and ‘off’ years. Nutrients contents (N, P, K, Ca, Mg, Fe, Mn, Zn and Cu) in leaf and node samples were determined. The K, Ca, Mg, Fe, Mn, Zn and Cu contents were determined by atomic absorption spectrophotometry, Nitrogen by Kjeldahl procedure, and P by a spectrophotometric method. The results showed that the N, Ca, Mg, Fe, Mn, Zn and Cu contents in ‘on’ year were higher than ‘off’ year while the K contents in ‘on’ year were lower than ‘off ‘ year, but the P content was not different. The N, Ca, Mg, Fe and Mn contents in leaf samples were higher in the node samples except for K while the P, Zn and Cu contents were not different. The N, K, Ca, Fe, Mn, Zn and Cu contents were lowest during the initiation period while the P content was highest in this period. The Mg content was not different in all period.

Keywords: bearing, differentiation period, induction period, initiation period, non bearing, olive

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Authors: Abdullah M. Alzahrani

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The unicellular alga Chlorella vulgaris was isolated from Al-Asfar Lake, which is located in the Al-Ahsa province of Saudi Arabia. Two different isolates were sub-cultured under laboratory conditions. The wild type was grown under a regular concentration of copper, whereas the other isolate was grown under a progressively increasing copper concentration. An Inter Simple Sequence Repeats (ISSR) analysis was performed using DNA isolated from the wild type and tolerant strains. The sum of the scored bands of the wild type was 155, with 100 (64.5%) considered to be polymorphic bands, whereas the resistant strain displayed 147 bands, with 92 (62.6%) considered to be polymorphic bands. The sum of the scored bands of a mixed sample was 117 bands, of which only 4 (3.4%) were considered to be polymorphic. The average Nei's genetic diversity (h) and Shannon-Weiner diversity indices (I) were 0.3891 and 0.5394, respectively. These results clearly indicate that the adaptation to a high level of copper in Chlorella vulgaris is not merely physiological but rather driven by modifications at the genomic level.

Keywords: chlorella vulgaris, copper tolerance, genetic diversity, green algae

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Authors: M. Maatar, M. Mekadem, M. Medale, B. Hadjed, B. Imine

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In this paper, numerical simulations have been carried out to study the performances of a flapping wing used as an energy collector. Metamodeling and genetic algorithms are used to detect the optimal configuration, improving power coefficient and/or efficiency. Radial basis functions and genetic algorithms have been applied to solve this problem. Three optimization factors are controlled, namely dimensionless heave amplitude h₀, pitch amplitude θ₀ and flapping frequency f. ANSYS FLUENT software has been used to solve the principal equations at a Reynolds number of 1100, while the heave and pitch motion of a NACA0015 airfoil has been realized using a developed function (UDF). The results reveal an average power coefficient and efficiency of 0.78 and 0.338 with an inexpensive low-fidelity model and a total relative error of 4.1% versus the simulation. The performances of the simulated optimum RBF-NSGA-II have been improved by 1.2% compared with the validated model.

Keywords: numerical simulation, flapping wing, energy extraction, power coefficient, efficiency, RBF, NSGA-II

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Authors: Katalin Gombos, Bence Gálik, Krisztina Ildikó Kalács, Krisztina Gödöny, Ákos Várnagy, József Bódis, Attila Gyenesei, Gábor L. Kovács

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Although non-invasive pre-implantation genetic testing for aneuploidy (NIPGT-A) is potentially appropriate to assess chromosomal ploidy of the embryo, practical application of it in a routine IVF center has not been started in the absence of a recommendation. We developed a comprehensive workflow for a clinically applicable strategy for NIPGT-A based on next-generation sequencing (NGS) technology. We performed MALBAC whole genome amplification and NGS on spent blastocyst culture media of Day 3 embryos fertilized with intra-cytoplasmic sperm injection (ICSI). Spent embryonic culture media of morphologically good quality score embryos were enrolled in further analysis with the blank culture media as background control. Chromosomal abnormalities were identified by an optimized bioinformatics pipeline applying a copy number variation (CNV) detecting algorithm. We demonstrate a comprehensive workflow covering both wet- and dry-lab procedures supporting a clinically applicable strategy for NIPGT-A. It can be carried out within 48 h which is critical for the same-cycle blastocyst transfer, but also suitable for “freeze all” and “elective frozen embryo” strategies. The described integrated approach of non-invasive evaluation of embryonic DNA content of the culture media can potentially supplement existing pre-implantation genetic screening methods.

Keywords: next generation sequencing, in vitro fertilization, embryo assessment, non-invasive pre-implantation genetic testing

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Authors: Marina Franulovic, Robert Basan, Bozidar Krizan

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Constitutive modelling of material behaviour is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behaviour of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behaviour modelling.

Keywords: genetic algorithm, kinematic hardening, material model, objective function

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Authors: Reema K. AlEssa, Sahar Alshomer, Abdullah Alfaleh, Sultan ALkhenaizan, Mohammed Albalwi

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Ichthyosis is a disorder of abnormal keratinization, characterized by excessive scaling, and consists of more than twenty subtypes varied in severity, mode of inheritance, and the genes involved. There is insufficient data in the literature about the epidemiology and characteristics of ichthyosis locally. Our aim is to identify the histopathological features and genetic profile of ichthyosis. Method: It is an observational retrospective case series study conducted in March 2020, included all patients who were diagnosed with Ichthyosis and confirmed by histological and molecular findings over the last 20 years in King Abdulaziz Medical City (KAMC), Riyadh, Saudi Arabia. Molecular analysis was performed by testing genomic DNA and checking genetic variations using the AmpliSeq panel. All disease-causing variants were checked against HGMD, ClinVar, Genome Aggregation Database (gnomAD), and Exome Aggregation Consortium (ExAC) databases. Result: A total of 60 cases of Ichthyosis were identified with a mean age of 13 ± 9.2. There is an almost equal distribution between female patients 29 (48%) and males 31 (52%). The majority of them were Saudis, 94%. More than half of patients presented with general scaling 33 (55%), followed by dryness and coarse skin 19 (31.6%) and hyperlinearity 5 (8.33%). Family history and history of consanguinity were seen in 26 (43.3% ), 13 (22%), respectively. History of colloidal babies was found in 6 (10%) cases of ichthyosis. The most frequent genes were ALOX12B, ALOXE3, CERS3, CYP4F22, DOLK, FLG2, GJB2, PNPLA1, SLC27A4, SPINK5, STS, SUMF1, TGM1, TGM5, VPS33B. Most frequent variations were detected in CYP4F22 in 16 cases (26.6%) followed by ALOXE3 6 (10%) and STS 6 (10%) then TGM1 5 (8.3) and ALOX12B 5 (8.3). The analysis of molecular genetic identified 23 different genetic variations in the genes of ichthyosis, of which 13 were novel mutations. Homozygous mutations were detected in the majority of ichthyosis cases, 54 (90%), and only 1 case was heterozygous. Few cases, 4 (6.6%) had an unknown type of ichthyosis with a negative genetic result. Conclusion: 13 novel mutations were discovered. Also, about half of ichthyosis patients had a positive history of consanguinity.

Keywords: ichthyosis, genetic profile, molecular characterization, congenital ichthyosis

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Authors: Shih-Yu Wang, Shun-Wen Hsiao

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In the field of cybersecurity, there exists many vendors giving malware samples classified results, namely naming after the label that contains some important information which is also called AV label. Lots of researchers relay on AV labels for research. Unfortunately, AV labels are too cluttered. They do not have a fixed format and fixed naming rules because the naming results were based on each classifiers' viewpoints. A way to fix the problem is taking a majority vote. However, voting can sometimes create problems of bias. Thus, we create a novel ensemble approach which does not rely on the cacophonous naming result but depend on group identification to aggregate everyone's opinion. To achieve this purpose, we develop an scoring system called Pairwise Consensus Score (PCS) to calculate result similarity. The entire method architecture combine Genetic Algorithm and PCS to find maximum consensus in the group. Experimental results revealed that our method outperformed the majority voting by 10% in term of the score.

Keywords: genetic algorithm, ensemble learning, malware family, malware labeling, AV labels

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Authors: Adesoji Tunbosun Jaiyeola, Josiah Adeyemo

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Sediment yield can be considered to be the total sediment load that leaves a drainage basin. The knowledge of the quantity of sediments present in a river at a particular time can lead to better flood capacity in reservoirs and consequently help to control over-bane flooding. Furthermore, as sediment accumulates in the reservoir, it gradually loses its ability to store water for the purposes for which it was built. The development of hydrological models to forecast the quantity of sediment present in a reservoir helps planners and managers of water resources systems, to understand the system better in terms of its problems and alternative ways to address them. The application of artificial intelligence models and technique to such real-life situations have proven to be an effective approach of solving complex problems. This paper makes an extensive review of literature relevant to the theories and applications of evolutionary algorithms, and most especially genetic programming. The successful applications of genetic programming as a soft computing technique were reviewed in sediment modelling and other branches of knowledge. Some fundamental issues such as benchmark, generalization ability, bloat and over-fitting and other open issues relating to the working principles of GP, which needs to be addressed by the GP community were also highlighted. This review aim to give GP theoreticians, researchers and the general community of GP enough research direction, valuable guide and also keep all stakeholders abreast of the issues which need attention during the next decade for the advancement of GP.

Keywords: benchmark, bloat, generalization, genetic programming, over-fitting, sediment yield

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Authors: Muhamad Afiq Faisal, Yahaya, Mohd Faizal, Hamzah

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Genetic modification technology allows scientists to alter the genetic information of a particular organism. The technology allows the production of genetically modified organism (GMO) that has the enhanced property compared to the unmodified organism. The application of such technology is not only in agriculture industry, it is now has been applied extensively in biopharmaceutical industry such as transgenic vaccines. In Malaysia, Biosafety Act 2007 has been enacted in which all GMO-based products must be labeled with adequate information before being marketed. This paper aims to determine the awareness level amongst Malaysian consumers on the GM products available in the market and the efficiency of information supplied in the GM product labeling. The result of the survey will serve as a guideline for Malaysia government agency bodies to provide comprehensive yet efficient information to consumers for the purpose of GM product labeling in the near future. In conclusion, the efficiency of information delivery plays a vital role in ensuring that the information is being conveyed clearly to Malaysian consumers during the selection process of GM products available in the market.

Keywords: genetic modification technology, genetically modified organisms, genetically modified organism products labeling, Biosafety Act 2007

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Authors: T. Toathom, M. Munlin, P. Sugunnasil

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The traveling salesman problem (TSP) is one of the best-known problems in optimization problem. There are many research regarding the TSP. One of the most usage tool for this problem is the genetic algorithm (GA). The chromosome of the GA for TSP is normally encoded by the order of the visited city. However, the traditional chromosome encoding scheme has some limitations which are twofold: the large solution space and the inability to encapsulate some information. The number of solution for a certain problem is exponentially grow by the number of city. Moreover, the traditional chromosome encoding scheme fails to recognize the misplaced correct relation. It implies that the tradition method focuses only on exact solution. In this work, we relax some of the concept in the GA for TSP which is the exactness of the solution. The proposed work exploits the relation between cities in order to reduce the solution space in the chromosome encoding. In this paper, a second order GA is proposed to solve the TSP. The term second order refers to how the solution is encoded into chromosome. The chromosome is divided into 2 types: the high order chromosome and the low order chromosome. The high order chromosome is the chromosome that focus on the relation between cities such as the city A should be visited before city B. On the other hand, the low order chromosome is a type of chromosome that is derived from a high order chromosome. In other word, low order chromosome is encoded by the traditional chromosome encoding scheme. The genetic operation, mutation and crossover, will be performed on the high order chromosome. Then, the high order chromosome will be mapped to a group of low order chromosomes whose characteristics are satisfied with the high order chromosome. From the mapped set of chromosomes, the champion chromosome will be selected based on the fitness value which will be later used as a representative for the high order chromosome. The experiment is performed on the city data from TSPLIB.

Keywords: genetic algorithm, traveling salesman problem, initial population, chromosomes encoding

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Authors: Roozbeh Aghamajidi

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Shaft spillways are circling spillways used generally for emptying unexpected floods on earth and concrete dams. There are different types of shaft spillways: Stepped and Smooth spillways. Stepped spillways pass more flow discharges through themselves in comparison to smooth spillways. Therefore, awareness of flow behavior of these spillways helps using them better and more efficiently. Moreover, using vortex breaker has great effect on passing flow through shaft spillway. In order to use more efficiently, the risk of flow pressure decreases to less than fluid vapor pressure, called cavitations, should be prevented as far as possible. At this research, it has been tried to study different behavior of spillway with different vortex shapes on spillway crest on flow. From the viewpoint of the effects of flow regime changes on spillway, changes of step dimensions, and the change of type of discharge will be studied effectively. Therefore, two spillway models with three different vortex breakers and three arrangements have been used to assess the hydraulic characteristics of flow. With regard to the inlet discharge to spillway, the parameters of pressure and flow velocity on spillway surface have been measured at several points and after each run. Using these kinds of information leads us to create better design criteria of spillway profile. To achieve these purposes, optimization has important role and genetic algorithm are utilized to study the emptying discharge. As a result, it turned out that the best type of spillway with maximum discharge coefficient is smooth spillway with ogee shapes as vortex breaker and 3 number as arrangement. Besides it has been concluded that the genetic algorithm can be used to optimize the results.

Keywords: shaft spillway, vortex breaker, flow, genetic algorithm

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Authors: Tae-Hoon Kim, Kwon-Ha Yoon, Hong Young Jun, Ki-Jong Kim, Young Hwan Lee, Myeung Su Lee, Keum Ha Choi, Ki Jung Yun, Eun Young Cho, Yong-Yeon Jeong, Chung-Hwan Jun

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Purpose: To assess the changes of hepatic metabolite for differentiation between non-alcoholic steatohepatitis (NASH) and simple steatosis on proton magnetic resonance spectroscopy (1H-MRS) in both humans and animal model. Methods: The local institutional review board approved this study and subjects gave written informed consent. 1H-MRS measurements were performed on a localized voxel of the liver using a point-resolved spectroscopy (PRESS) sequence and hepatic metabolites of alanine (Ala), lactate/triglyceride (Lac/TG), and TG were analyzed in NASH, simple steatosis and control groups. The group difference was tested with the ANOVA and Tukey’s post-hoc tests, and diagnostic accuracy was tested by calculating the area under the receiver operating characteristics (ROC) curve. The associations between metabolic concentration and pathologic grades or non-alcoholic fatty liver disease(NAFLD) activity scores were assessed by the Pearson’s correlation. Results: Patient with NASH showed the elevated Ala(p<0.001), Lac/TG(p < 0.001), TG(p < 0.05) concentration when compared with patients who had simple steatosis and healthy controls. The NASH patients were higher levels in Ala(mean±SEM, 52.5±8.3 vs 2.0±0.9; p < 0.001), Lac/TG(824.0±168.2 vs 394.1±89.8; p < 0.05) than simple steatosis. The area under the ROC curve to distinguish NASH from simple steatosis was 1.00 (95% confidence interval; 1.00, 1.00) with Ala and 0.782 (95% confidence interval; 0.61, 0.96) with Lac/TG. The Ala and Lac/TG levels were well correlated with steatosis grade, lobular inflammation, and NAFLD activity scores. The metabolic changes in human were reproducible to a mice model induced by streptozotocin injection and a high-fat diet. Conclusion: 1H-MRS would be useful for differentiation of patients with NASH and simple hepatic steatosis.

Keywords: non-alcoholic fatty liver disease, non-alcoholic steatohepatitis, 1H MR spectroscopy, hepatic metabolites

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Authors: Aidin Foroutan, David S. Wishart, Leluo L. Guan, Carolyn Fitzsimmons

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Maximizing efficiency and growth potential of beef cattle requires not only genetic selection (i.e. residual feed intake (RFI)) but also adequate nutrition throughout all stages of growth and development. Nutrient restriction during gestation has been shown to negatively affect post-natal growth and development as well as fertility of the offspring. This, when combined with RFI may affect progeny traits. This study aims to investigate the impact of selection for divergent genetic potential for RFI and maternal nutrition during early- to mid-gestation, on bull calf traits such as fertility and muscle development using multiple ‘omics’ approaches. Comparisons were made between High-diet vs. Low-diet and between High-RFI vs. Low-RFI animals. An epigenetics experiment on semen samples identified 891 biomarkers associated with growth and development. A gene expression study on Longissimus thoracis muscle, semimembranosus muscle, liver, and testis identified 4 genes associated with muscle development and immunity of which Myocyte enhancer factor 2A [MEF2A; induces myogenesis and control muscle differentiation] was the only differentially expressed gene identified in all four tissues. An initial metabolomics experiment on serum samples using nuclear magnetic resonance (NMR) identified 4 metabolite biomarkers related to energy and protein metabolism. Once all the biomarkers are identified, bioinformatics approaches will be used to create a database covering all the ‘omics’ data collected from this project. This database will be broadened by adding other information obtained from relevant literature reviews. Association analyses with these data sets will be performed to reveal key biological pathways affected by RFI and maternal nutrition. Through these association studies between the genome and metabolome, it is expected that candidate biomarker genes and metabolites for feed efficiency, fertility, and/or muscle development are identified. If these gene/metabolite biomarkers are validated in a larger animal population, they could potentially be used in breeding programs to select superior animals. It is also expected that this work will lead to the development of an online tool that could be used to predict future traits of interest in an animal given its measurable ‘omics’ traits.

Keywords: biomarker, maternal nutrition, omics, residual feed intake

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Authors: Xuan Zhao, Wen Jiang

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In this study, a web crawler was used to collect POI sample data from 38 districts and counties of Chongqing in 2022, and ArcGIS was combined to coordinate and projection conversion and realize data visualization. Nuclear density analysis and spatial correlation analysis were used to explore the spatial distribution characteristics of elderly care facilities in Chongqing, and K mean cluster analysis was carried out with GeoDa to study the spatial concentration degree of elderly care resources in 38 districts and counties. Finally, the driving force of spatial differentiation of elderly care facilities in various districts and counties of Chongqing is studied by using the method of geographic detector. The results show that: (1) in terms of spatial distribution structure, the distribution of elderly care facilities in Chongqing is unbalanced, showing a distribution pattern of ‘large dispersion and small agglomeration’ and the asymmetric pattern of ‘west dense and east sparse, north dense and south sparse’ is prominent. (2) In terms of the spatial matching between elderly care resources and the elderly population, there is a weak coordination between the input of elderly care resources and the distribution of the elderly population at the county level in Chongqing. (3) The analysis of the results of the geographical detector shows that the single factor influence is mainly the number of elderly population, public financial revenue and district and county GDP. The high single factor influence is mainly caused by the elderly population, public financial income, and district and county GDP. The influence of each influence factor on the spatial distribution of elderly care facilities is not simply superimposed but has a nonlinear enhancement effect or double factor enhancement. It is necessary to strengthen the synergistic effect of two factors and promote the synergistic effect of multiple factors.

Keywords: aging, elderly care facilities, spatial differentiation, geographical detector, driving force analysis, Mountain city

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Authors: Henrik L. Funke, Lars Ulke-Winter, Sandra Gelbrich, Lothar Kroll

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This work reports about an approach for an automatic adaptation of concrete formulations based on genetic algorithms (GA) to optimize a wide range of different fit-functions. In order to achieve the goal, a method was developed which provides a numerical description of a fibre reinforced concrete (FRC) mixture regarding the production technology and the property spectrum of the concrete. In a first step, the FRC mixture with seven fixed components was characterized by varying amounts of the components. For that purpose, ten concrete mixtures were prepared and tested. The testing procedure comprised flow spread, compressive and bending tensile strength. The analysis and approximation of the determined data was carried out by GAs. The aim was to obtain a closed mathematical expression which best describes the given seven-point cloud of FRC by applying a Gene Expression Programming with Free Coefficients (GEP-FC) strategy. The seven-parametric FRC-mixtures model which is generated according to this method correlated well with the measured data. The developed procedure can be used for concrete mixtures finding closed mathematical expressions, which are based on the measured data.

Keywords: concrete design, fibre reinforced concrete, genetic algorithms, GEP-FC

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Authors: Mukhtiar Singh, Sumeet Nagar

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Vehicle routing problem (VRP) is a combinatorial optimization and nonlinear programming problem aiming to optimize decisions regarding given set of routes for a fleet of vehicles in order to provide cost-effective and efficient delivery of both services and goods to the intended customers. This paper proposes the application of integrated particle swarm optimization (PSO) and genetic optimization algorithm (GA) to address the Vehicle routing problem in sugarcane industry in India. Suger industry is very prominent agro-based industry in India due to its impacts on rural livelihood and estimated to be employing around 5 lakhs workers directly in sugar mills. Due to various inadequacies, inefficiencies and inappropriateness associated with the current vehicle routing model it costs huge money loss to the industry which needs to be addressed in proper context. The proposed algorithm utilizes the crossover operation that originally appears in genetic algorithm (GA) to improve its flexibility and manipulation more readily and avoid being trapped in local optimum, and simultaneously for improving the convergence speed of the algorithm, level set theory is also added to it. We employ the hybrid approach to an example of VRP and compare its result with those generated by PSO, GA, and parallel PSO algorithms. The experimental comparison results indicate that the performance of hybrid algorithm is superior to others, and it will become an effective approach for solving discrete combinatory problems.

Keywords: fuzzy logic, genetic algorithm, particle swarm optimization, vehicle routing problem

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Authors: Marziyeh Bahrami, Hamed Pahlevan Hsseini, Behnam Ghamami, Arman Alvanpour, Hamed Ezzati, Amir Salar Sadeghi

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One of the ways to increase the efficiency of services in the system of agents and, of course, in the world of cloud computing, is to use virtualization techniques. The aim of this research is to create changes in cloud computing services that will reduce as much as possible the energy consumption related to the migration of virtual machines and, in some way, the energy related to the allocation of resources and reduce the amount of pollution. So far, several methods have been proposed to increase the efficiency of cloud computing services in order to save energy in the cloud environment. The method presented in this article tries to prevent energy consumption by data centers and the subsequent production of carbon and biological pollutants as much as possible by increasing the efficiency of cloud computing services. The results show that the proposed algorithm, using the improvement in virtualization techniques and with the help of a genetic algorithm, improves the efficiency of cloud services in the matter of migrating virtual machines and finally saves consumption. becomes energy.

Keywords: consumption reduction, cloud computing, genetic algorithm, live migration, virtual Machine

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Authors: Dmitry V. Pasynkov, Ivan A. Egoshin, Alexey A. Kolchev, Ivan V. Kliouchkin

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In most cases, typical cysts are easily recognized at ultrasonography. The specificity of this method for typical cysts reaches 98%, and it is usually considered as gold standard for typical cyst diagnosis. However, it is necessary to have all the following features to conclude the typical cyst: clear margin, the absence of internal echoes and dorsal acoustic enhancement. At the same time, not every breast cyst is typical. It is especially characteristic for protein-contained cysts that may have significant internal echoes. On the other hand, some solid lesions (predominantly malignant) may have cystic appearance and may be falsely accepted as cysts. Therefore we tried to develop the automatic method of cystic and solid breast lesions differentiation. Materials and methods. The input data were the ultrasonography digital images with the 256-gradations of gray color (Medison SA8000SE, Siemens X150, Esaote MyLab C). Identification of the lesion on these images was performed in two steps. On the first one, the region of interest (or contour of lesion) was searched and selected. Selection of such region is carried out using the sigmoid filter where the threshold is calculated according to the empirical distribution function of the image brightness and, if necessary, it was corrected according to the average brightness of the image points which have the highest gradient of brightness. At the second step, the identification of the selected region to one of lesion groups by its statistical characteristics of brightness distribution was made. The following characteristics were used: entropy, coefficients of the linear and polynomial regression, quantiles of different orders, an average gradient of brightness, etc. For determination of decisive criterion of belonging to one of lesion groups (cystic or solid) the training set of these characteristics of brightness distribution separately for benign and malignant lesions were received. To test our approach we used a set of 217 ultrasonic images of 107 cystic (including 53 atypical, difficult for bare eye differentiation) and 110 solid lesions. All lesions were cytologically and/or histologically confirmed. Visual identification was performed by trained specialist in breast ultrasonography. Results. Our system correctly distinguished all (107, 100%) typical cysts, 107 of 110 (97.3%) solid lesions and 50 of 53 (94.3%) atypical cysts. On the contrary, with the bare eye it was possible to identify correctly all (107, 100%) typical cysts, 96 of 110 (87.3%) solid lesions and 32 of 53 (60.4%) atypical cysts. Conclusion. Automatic approach significantly surpasses the visual assessment performed by trained specialist. The difference is especially large for atypical cysts and hypoechoic solid lesions with the clear margin. This data may have a clinical significance.

Keywords: breast cyst, breast solid lesion, differentiation, ultrasonography

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Authors: Ankush M. Dewle, Suditi Bhattacharya, Prachi R. Abhang, Savita Datar, Ajay J. Jog, Rupesh K. Srivastava, Geetanjali Tomar

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Objectives: The aim of this study was to investigate the quality of mesenchymal stem cells (MSCs) obtained from ageing gingival tissues, in order to suggest their potential role in autologous stem cell therapy for old individuals. Methods: MSCs were isolated from gingival tissues of young (18-45 years) and old (above 45 years) donors by enzymatic digestion. MSCs were analysed for cfu-f, surface marker expression by flow-cytometry and multilineage differentiation potential. The angiogenic potential was compared in a chick embryo yolk sac membrane model. The aging and differentiation markers including SA-β-galactosidase and p21 respectively were analysed by staining and flow-cytometry analysis. Additionally, osteogenic markers such as glucocorticoid receptor (GR), vitamin D receptor (VDR) were measured by flow-cytometry and RT-qPCR was performed for quantification of osteogenic gene expression. Alizarin Red S and alkaline phosphatase (ALP) activity were also quantitated. Results: Gingival MSCs (GMSCs) from both the age groups were similar in their morphology and displayed cfu-f. They had similar expression of MSC surface markers and p21, comparable rate of proliferation and differentiated to all the four lineages. GMSCs from young donors had a higher adipogenic differentiation potential as compared to the old GMSCs. Moreover, these cells did not display a significant difference in ALP activity probably due to comparable expression of GR, VDR, and osteogenic genes. Conclusions: Ageing of GMSCs occurs at a much slower rate than stem cells from other sources. Thus we suggest GMSCs as an excellent candidate for autologous stem cell therapy in degenerative diseases of elderly individuals. Clinical Significance: GMSCs could help overcome the setbacks in clinical implementation of autologous stem cell therapy for regenerative medicine in all age group of patient.

Keywords: bone regeneration, cell therapy, senescence, stem cell

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Authors: Ovidiu Domşa, Nicolae Bold

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Using Information and Communication Technologies (ICT) notions in education and three basic processes of education (teaching, learning and assessment) can bring benefits to the pupils and the professional development of teachers. In this matter, we refer to these notions as concepts taken from the informatics area and apply them to the domain of education. These notions refer to genetic algorithms and arborescent structures, used in the specific process of assessment or evaluation. This paper uses these kinds of notions to generate subtrees from a main tree of tests related between them by their degree of difficulty. These subtrees must contain the highest number of connections between the nodes and the lowest number of missing edges (which are subtrees of the main tree) and, in the particular case of the non-existence of a subtree with no missing edges, the subtrees which have the lowest (minimal) number of missing edges between the nodes, where a node is a test and an edge is a direct connection between two tests which differs by one degree of difficulty. The subtrees are represented as sequences. The tests are the same (a number coding a test represents that test in every sequence) and they are reused for each sequence of tests.

Keywords: chromosome, genetic algorithm, subtree, test

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Authors: Maki Mizogami, Hironori Tsuchiya, Yoshiroh Hayabuchi, Kenji Shigemi

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Since drugs exhibit significant structure-dependent differences in activity and toxicity, their differentiation based on the mechanism of action should have implications for comparative drug efficacy and safety. We aimed to differentiate drug stereoisomers by their stereostructure-selective membrane interactions underlying pharmacological and toxicological effects. Biomimetic lipid bilayer membranes were prepared with phospholipids and sterols (either cholesterol or epicholesterol) to mimic the lipid compositions of neuronal and cardiomyocyte membranes and to provide these membranes with the chirality. The membrane preparations were treated with different classes of stereoisomers at clinically- and pharmacologically-relevant concentrations (25-200 μM), followed by measuring fluorescence polarization to determine the membrane interactivity of drugs to change the physicochemical property of membranes. All the tested drugs acted on lipid bilayers to increase or decrease the membrane fluidity. Drug stereoisomers could not be differentiated when interacting with the membranes consisting of phospholipids alone. However, they stereostructure-selectively interacted with neuro-mimetic and cardio-mimetic membranes containing 40 mol% cholesterol ((3β)-cholest-5-en-3-ol) to show the relative potencies being local anesthetic R(+)-bupivacaine > rac-bupivacaine > S(‒)-bupivacaine, α2-adrenergic agonistic D-medetomidine > rac-medetomidine > L-medetomidine, β-adrenergic antagonistic R(+)-propranolol > rac-propranolol > S(–)-propranolol, NMDA receptor antagonistic S(+)-ketamine > rac-ketamine, analgesic monoterpenoid (+)-menthol > (‒)-menthol, non-steroidal anti-inflammatory S(+)-ibuprofen > rac-ibuprofen > R(‒)-ibuprofen, and bioactive flavonoid (+)-epicatechin > (‒)-epicatechin. All of the order of membrane interactivity were correlated to those of beneficial and adverse effects of the tested stereoisomers. In contrast, the membranes prepared with epicholesterol ((3α)-chotest-5-en-3-ol), an epimeric form of cholesterol, reversed the rank order of membrane interactivity to be S(‒)-enantiomeric > racemic > R(+)-enantiomeric bupivacaine, L-enantiomeric > racemic > D-enantiomeric medetomidine, S(–)-enantiomeric > racemic > R(+)-enantiomeric propranolol, racemic > S(+)-enantiomeric ketamine, (‒)-enantiomeric > (+)-enantiomeric menthol, R(‒)-enantiomeric > racemic > S(+)-enantiomeric ibuprofen, and (‒)-enantiomeric > (+)-enantiomeric epicatechin. The opposite configuration allows drug molecules to interact with chiral sterol membranes enantiomer-selectively. From the comparative results, it is speculated that a 3β-hydroxyl group in cholesterol is responsible for the enantioselective interactions of drugs. In conclusion, the differentiation of drug stereoisomers by their stereostructure-selective membrane interactions would be useful for designing and predicting drugs with higher activity and/or lower toxicity.

Keywords: chiral membrane, differentiation, drug stereoisomer, enantioselective membrane interaction

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Authors: Fariborz Ahmadi, Hamid Salehi, Khosrow Karimi

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A sensor network is set of sensor nodes that cooperate together to perform a predefined tasks. The important problem in this network is power consumption. So, in this paper one algorithm based on the eurygaster life is introduced to minimize power consumption by the nodes of these networks. In this method the search space of problem is divided into several partitions and each partition is investigated separately. The evaluation results show that our approach is more efficient in comparison to other evolutionary algorithm like genetic algorithm.

Keywords: evolutionary computation, genetic algorithm, particle swarm optimization, sensor network optimization

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Authors: Ghaleb Bin Huraib, Fahad Al Harthi, Mohammad Mustafa, Abdulrahman Al-Asmari

Abstract:

Introduction: Vitiligo is an acquired pigmentary skin disorder with the regional disappearance of melanocytes. Vitiligo affects 0.1 to 2% of the global population, and the incidence varies substantially depending on ethnicity. Glutathione S-transferase (GST) is a multigene family of enzymes that detoxify oxidative stress products. The oxidative stress-related GSTM1/GSTT1 genes deletion may cause epidermal melanocytes destruction and the development of vitiligo. Hence, the present study aimed to investigate the association of GST gene polymorphisms with vitiligo in the Saudi population, if any. Materials and Methods: The present study includes 129 vitiligo cases and 130 age-matched healthy controls. The proportion of male and female patients with vitiligo is almost equal. The multiplex polymerase chain reaction (PCR) method was used for polymorphic analysis. Results: Increased odds of generalized vitiligo was observed with the null genotypes of GSTT1- gene (OR = 1.91, 95% CI = 1.07-3.42, p = 0.019). The possible genetic combinations of GSTM1/GSTT1 and their genotypic distribution showed the frequency of GSTM1+/GSTT1+ 62/130 (47.69%) and GSTM1-/GSTT1+ 52/130 (40.00%) were higher in controls than in cases 44/129 (34.11%), 43/129 (33.34%), respectively while GSTM1+/GSTT1- and GSTM1-/GSTT1- null genotypes were higher 22/129 (17.05%) and 20/129 (15.50%) in vitiligo patients as compared to controls 11/130 (8.46%), 5/130 (3.84%), respectively. The strength of association of different genetic combinations with cases have shown GSTM1+/GSTT1- (OR = 2.81, 95% CI = 1.24-6.40, p = 0.009) and GSTM1-/GSTT1- (OR = 5.63, 95% CI = 1.96 - 16.16, p = 0.0004) were significantly higher in vitiligo cases as compared to controls. We did not observe any significant association of age and gender of patients with GST gene polymorphisms. Conclusions: The GSTT1-, GSTM1+/GSTT1- and GSTM1-/GSTT1- null genotypes were significantly associated with vitiligo. These genetic polymorphisms may be the associative genetic risk factor for vitiligo among Saudis. It could be used as a genetic marker for screening vitiligo patients among Saudis. Further studies on GSTs gene polymorphism in larger sample sizes from different geographical areas and ethnicity are needed to strengthen the present findings.

Keywords: vitiligo, GSTM1, GSTT1, gene polymorphism, oxidative stress

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Authors: Xiyang Li, Qi Yu, Lun Zhang

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In the face of natural disasters and other emergency situations, determining the optimal location of rescue centers is crucial for improving rescue efficiency and minimizing impact on affected populations. This paper proposes a method that integrates genetic algorithms (GA) and backpropagation neural networks (BPNN) to address the site selection optimization problem for emergency rescue centers. We utilize BPNN to accurately estimate the cost of delivering supplies from rescue centers to each temporary camp. Moreover, a genetic algorithm with a special partially matched crossover (PMX) strategy is employed to ensure that the number of temporary camps assigned to each rescue center adheres to predetermined limits. Using the population distribution data during the 2022 epidemic in Jiading District, Shanghai, as an experimental case, this paper verifies the effectiveness of the proposed method. The experimental results demonstrate that the BPNN-GA method proposed in this study outperforms existing algorithms in terms of computational efficiency and optimization performance. Especially considering the requirements for computational resources and response time in emergency situations, the proposed method shows its ability to achieve rapid convergence and optimal performance in the early and mid-stages. Future research could explore incorporating more real-world conditions and variables into the model to further improve its accuracy and applicability.

Keywords: emergency rescue centers, genetic algorithms, back-propagation neural networks, site selection optimization

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