Search results for: genetic algorithms

Authors: Kunyaporn Pipithsangchan, Alongkorn Korntong, Assanee Songserm, Phatchara Piriyavinit, Saowanee Dechakampoo

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The Kingdom of Thailand is one of the South East Asian countries. From its area of 514,000 square kilometers (51 million ha), at least 18,000 plant species (8% of the world total) have been estimated to be found in the country. As a result, the conservation of plant genetic diversity, particularly food crops, is becoming important and is an assurance for the national food security. Department of Agriculture Genebank or DOA Genebank, Thailand is responsible for the conservation of plant germplasm by participating and accomplishing several collaborative projects both at national and international levels. Integrated Management System of Plant Genetic Resources or IMPGR is one of the most outstandingly successful cooperation. It is a multilateral project under the Asian Food and Agriculture Cooperation Initiative (AFACI) supported by the Rural Development Administration (RDA) of South Korea. The member countries under the project consist of 11 nations namely Bangladesh, Cambodia, Indonesia, Laos PDR, Mongolia, Nepal, Philippines, Sri Lanka, Thailand, Vietnam and South Korea. The project enabled the members to jointly address the global issues in plant genetic resource (PGR) conservation and strengthen their network in this aspect. The 1st phase of IMPGR project, entitled 'Collection, Conservation, Regeneration and Characterization of Cucurbitaceae and Solanaceae 2012-2014', comprises three main objectives that are: 1) To improve management in storage facilities, collection, and regeneration, 2) To improve linkage between Genebank and material sources (for regeneration), and 3) To improve linkage between Genebank and other field crop or/and horticultural research centers. The project was done for three years from 2012 to 2014. The activities of the project can be described as following details: In the 1st year, there were 9 target provinces for completing plant genetic resource survey and collection. 108 accessions of PGR were collected. In the 2nd year, PGR were continuously surveyed and collected from 9 provinces. The total number of collection was 140 accessions. In addition, the process of regeneration of 237 accessions collected from 1st and 2nd year was started at several sites namely Biotechnology Research and Development Office, Sukothai Horticultural Research Center, Tak Research, and Development Center and Nakhon Ratchasima Research and Development Center. In the 3rd year, besides survey and collection of 115 accessions from 9 target provinces, PGR characterization and evaluation were done for 206 accessions. Moreover, safety duplication of 253 PGR at the World Seed Vault, RDA, was also done according to Standard Agreement on Germplasm Safety Duplication between Department of Agriculture, Ministry of Agriculture and Cooperatives, the Kingdom of Thailand and the National Agrobiodiversity Center, Rural Development Administration of the Republic of Korea. The success of the 1st phase project led to the second phase which entitled 'Collection and Characterization for Effective Conservation of Local Capsicum spp., Solanum spp. and Lycopersicon spp. in Thailand 2015-2017'.

Keywords: characterization, conservation, DOA genebank, plant genetic resources

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Authors: Atitallah Sofien, Bouyahia Olfa, Attar Souleima, Missaoui Nada, Ben Rabeh Rania, Yahyaoui Salem, Mazigh Sonia, Boukthir Samir

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Introduction: Ciliopathies are a spectrum of diseases that have in common a defect in the synthesis of ciliary proteins. It is a rare cause of neonatal cholestasis. Clinical presentation varies extremely, and the main affected organs are the kidneys, liver, and pancreas. Methodology: This is a descriptive case report of a newborn who was admitted for exploration of neonatal cholestasis in the Paediatric Department C at the Children’s Hospital of Tunis, where the investigations concluded with a rare genetic mutation. Results: This is the case of a newborn male with no family history of hepatic and renal diseases, born to consanguineous parents, and from a well-monitored uneventful pregnancy. He developed jaundice on the second day of life, for which he received conventional phototherapy in the neonatal intensive care unit. He was admitted at 15 days for mild bronchiolitis. On clinical examination, intense jaundice was noted with normal stool and urine colour. Initial blood work showed an elevation in conjugated bilirubin and a high gamma-glutamyl transferase level. Transaminases and prothrombin time were normal. Abdominal sonography revealed hepatomegaly, splenomegaly, and undifferentiated renal cortex with bilateral medullar micro-cysts. Kidney function tests were normal. The infant received ursodeoxycholic acid and vitamin therapy. Genetic testing showed a homozygous mutation in the DCDC2 gene that hadn’t been documented before confirming the diagnosis of renal-hepatic ciliopathy. The patient has regular follow-ups, and his conjugated bilirubin and gamma-glutamyl transferase levels have been decreasing. Conclusion: Genetic testing has revolutionized the approach to etiological diagnosis in pediatric cholestasis. It enables personalised treatment strategies to better enhance the quality of life of patients and prevent potential complications following adequate long-term monitoring.

Keywords: cholestasis, newborn, ciliopathy, DCDC2, genetic

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Authors: Sirus Mohammadi, Rohala Moghimi

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The main advantages of microgrids are high energy efficiency through the application of Combined Heat and Power (CHP), high quality and reliability of the delivered electric energy and environmental and economic advantages. This study presents an energy management system (EMS) to optimize the operation of the microgrid (MG). In this paper an Adaptive Modified Firefly Algorithm (AMFA) is presented for optimal operation of a typical MG with renewable energy sources (RESs) accompanied by a back-up Micro-Turbine/Fuel Cell/Battery hybrid power source to level the power mismatch or to store the energy surplus when it’s needed. The problem is formulated as a nonlinear constraint problem to minimize the total operating cost. The management of Energy storage system (ESS), economic load dispatch and operation optimization of distributed generation (DG) are simplified into a single-object optimization problem in the EMS. The proposed algorithm is tested on a typical grid-connected MG including WT/PV/Micro Turbine/Fuel Cell and Energy Storage Devices (ESDs) then its superior performance is compared with those from other evolutionary algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Fuzzy Self Adaptive PSO (FSAPSO), Chaotic Particle PSO (CPSO), Adaptive Modified PSO (AMPSO), and Firefly Algorithm (FA).

Keywords: microgrid, operation management, optimization, firefly algorithm (AMFA)

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Authors: Mohammadhadi Mirmohammadi, Reza Safian, Hossein Haddad

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This paper presents an innovative solution for complex multi-objective optimization problem which is a part of efforts toward maximizing rolling mill throughput and minimizing processing costs in tandem cold rolling. This computational intelligence based optimization has been applied to the rolling schedules of tandem cold rolling mill. This method involves the combination of two derivative-free optimization procedures in the form of nested loops. The first optimization loop is based on Improving Hit and Run method which focus on balance of power, force and reduction distribution in rolling schedules. The second loop is a real-coded genetic algorithm based optimization procedure which optimizes energy consumption and productivity. An experimental result of application to five stand tandem cold rolling mill is presented.

Keywords: derivative-free optimization, Improving Hit and Run method, real-coded genetic algorithm, rolling schedules of tandem cold rolling mill

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Authors: Meng-Hui Chen, Chen-Yu Kao, Chia-Yu Hsu, Pei-Chann Chang

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The main idea in this paper is using sequential pattern mining to find the information which is helpful for finding high performance solutions. By combining this information, it is defined as blocks. Using the blocks to generate artificial chromosomes (ACs) could improve the structure of solutions. Estimation of Distribution Algorithms (EDAs) is adapted to solve the combinatorial problems. Nevertheless many of these approaches are advantageous for this application, but only some of them are used to enhance the efficiency of application. Generating ACs uses patterns and EDAs could increase the diversity. According to the experimental result, the algorithm which we proposed has a better performance to solve the permutation flow-shop problems.

Keywords: combinatorial problems, sequential pattern mining, estimationof distribution algorithms, artificial chromosomes

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Authors: Muhammad S. Sajid, Asim Shamim, Muhammad Nisar Khan, Ashfaq A. Chatta, Muhammad Saqib

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Goats (Capra hircus) are a valued asset for resource poor farmers globally. But the parasitic infection especially Haemonchus contortus (Trichostrongylid), impact the health and production of goats globally. The present study intended to evaluate resilient and resistance to Haemonchus contortus in indigenous goat breeds (Teddy and Beetal) of Punjab, Pakistan. Out of 60, 30 goats of each breed were divided into 6 groups and each group contain five goats. Two group of each breed received challenged infection with 12000 and 18000 L3 (third stage) larvae of Haemonchus contortus under two infection protocol that is early and trickle and remaining two group of each breed was kept as control. Resilient and resistance of each breed was then measured on the basis of their phenotypic markers like: faecal egg counts, packed cell volume, FAMACHA score system, body weight, total protein, albumin and worm count on 2nd, 4th, 6th, and 8th week of post infection. Variation in response of each goat breeds to Haemonchus contortus was observed. Teddy breed showed significant (P < 0.05)resistance as compared to Beetal. It is probably first attempt to report an evaluation of goat breed response towards Haemonchus contortus in Pakistan. It was concluded that Teddy goats have a greater genetic tendency to resist against to the Haemonchus contortus infection and this breed could be kept and bred from the economic point of view. Evaluation of genetic markers are like: gene, protein expression, Immunoglobulin, Histamines and interleukins determination are recommended for future studies which can be helpful to be fined resistant breed of goats.

Keywords: goat, beetal, teddy, haemonchus contortus, resistance, resilience, phenotypic markers

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Authors: Emad Askar, Eldesoky Elsoaly, Mohamed Kamel, Hisham Kamel

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The objective of this article is to improve the passive vibration damping of solar array (SA) used in space structures, by the effective application of numerical optimization. A case study of a SA is used for demonstration. A finite element (FE) model was created and verified by experimental testing. Optimization was then conducted by implementing the FE model with the genetic algorithm, to find the optimal placement of aluminum circular patches, to suppress the first two bending mode shapes. The results were verified using experimental testing. Finally, a parametric study was conducted using the FE model where patch locations, material type, and shape were varied one at a time, and the results were compared with the optimal ones. The results clearly show that through the proper application of FE modeling and numerical optimization, passive vibration damping of space structures has been successfully achieved.

Keywords: damping optimization, genetic algorithm optimization, passive vibration damping, solar array vibration damping

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Authors: F. Varga, Z. Liber, J. Jakše, A. Turudić, Z. Šatović, I. Radosavljević, N. Jeran, M. Grdiša

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Dalmatian pyrethrum (Tanacetum cinerariifolium (Trevir.) Sch. Bip.; Asteraceae), a source of the commercially dominant plant insecticide pyrethrin, is a species endemic to the eastern Adriatic. Genetic diversity of T. cinerariifolium was previously studied using amplified fragment length polymorphism (AFLP) markers. However, microsatellite markers (single sequence repeats - SSRs) are more informative because they are codominant, highly polymorphic, locus-specific, and more reproducible, and thus are most often used to assess the genetic diversity of plant species. Dalmatian pyrethrum is an outcrossing diploid (2n = 18) whose large genome size and high repeatability have prevented the success of the traditional approach to SSR markers development. The advent of next-generation sequencing combined with the specifically developed method recently enabled the development of, to the author's best knowledge, the first set of SSRs for genomic characterization of Dalmatian pyrethrum, which is essential from the perspective of plant genetic resources conservation. To evaluate the effectiveness of the developed SSR markers in genetic differentiation of Dalmatian pyrethrum populations, a preliminary genetic diversity study was conducted on 30 individuals from three geographically distinct natural populations in Croatia (northern Adriatic island of Mali Lošinj, southern Adriatic island of Čiovo, and Mount Biokovo) based on 12 SSR loci. Analysis of molecular variance (AMOVA) by randomization test with 10,000 permutations was performed in Arlequin 3.5. The average number of alleles per locus, observed and expected heterozygosity, probability of deviations from Hardy-Weinberg equilibrium, and inbreeding coefficient was calculated using GENEPOP 4.4. Genetic distance based on the proportion of common alleles (DPSA) was calculated using MICROSAT. Cluster analysis using the neighbor-joining method with 1,000 bootstraps was performed with PHYLIP to generate a dendrogram. The results of the AMOVA analysis showed that the total SSR diversity was 23% within and 77% between the three populations. A slight deviation from Hardy-Weinberg equilibrium was observed in the Mali Lošinj population. Allele richness ranged from 2.92 to 3.92, with the highest number of private alleles observed in the Mali Lošinj population (17). The average observed DPSA between 30 individuals was 0.557. The highest DPSA (0.875) was observed between several pairs of Dalmatian pyrethrum individuals from the Mali Lošinj and Mt. Biokovo populations, and the lowest between two individuals from the Čiovo population. Neighbor-joining trees, based on DPSA, grouped individuals into clusters according to their population affiliation. The separation of Mt. Biokovo clade was supported (bootstrap value 58%), which is consistent with the previous study on AFLP markers, where isolated populations from Mt. Biokovo differed from the rest of the populations. The developed SSR markers are an effective tool for assessing the genetic diversity and structure of natural Dalmatian pyrethrum populations. These preliminary results are encouraging for a future comprehensive study with a larger sample size across the species' range. Combined with the biochemical data, these highly informative markers could help identify potential genotypes of interest for future development of breeding lines and cultivars that are both resistant to environmental stress and high in pyrethrins. Acknowledgment: This work has been supported by the Croatian Science Foundation under the project ‘Genetic background of Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir./ Sch. Bip.) insecticidal potential’- (PyrDiv) (IP-06-2016-9034) and by project KK.01.1.1.01.0005, Biodiversity and Molecular Plant Breeding, at the Centre of Excellence for Biodiversity and Molecular Plant Breeding (CoE CroP-BioDiv), Zagreb, Croatia.

Keywords: Asteraceae, genetic diversity, genomic SSRs, NGS, pyrethrum, Tanacetum cinerariifolium

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Authors: Su Xiaohan, Jin Chicheng, Liu Yijing, Burra Venkata Durga Kumar

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Energy-aware scheduling in real-time systems aims to minimize energy consumption, but issues related to resource reservation and timing constraints remain challenges. This study focuses on analyzing two scheduling algorithms, Fair-Share Scheduling (FFS) and Priority-Driven Preemptive Scheduling (PDPS), for solving these issues and energy-aware scheduling in real-time systems. Based on research on both algorithms and the processes of solving two problems, it can be found that Fair-Share Scheduling ensures fair allocation of resources but needs to improve with an imbalanced system load, and Priority-Driven Preemptive Scheduling prioritizes tasks based on criticality to meet timing constraints through preemption but relies heavily on task prioritization and may not be energy efficient. Therefore, improvements to both algorithms with energy-aware features will be proposed. Future work should focus on developing hybrid scheduling techniques that minimize energy consumption through intelligent task prioritization, resource allocation, and meeting time constraints.

Keywords: energy-aware scheduling, fair-share scheduling, priority-driven preemptive scheduling, real-time systems, optimization, resource reservation, timing constraints

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Authors: Zaid Jamal Saeed Almahmoud

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Smart grid is emerging as the future power grid, with smart techniques to optimize power consumption and electricity generation. Minimizing peak power consumption under a fixed delay requirement is a significant problem in the smart grid.For this problem, all appliances must be scheduled within a given finite time duration. We consider the problem of minimizing the peak demand under appliances constraints by scheduling power jobs with uniform release dates and deadlines. As the problem is known to be NP-hard, we analyze the performance of a version of the natural greedy heuristic for solving this problem. Our theoretical analysis and experimental results show that the proposed heuristic outperforms existing methods by providing a better approximation to the optimal solution.

Keywords: peak demand scheduling, approximation algorithms, smart grid, heuristics

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Authors: M. Dezvarei, S. Morovati

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In recent years, increasing usage of electrical energy provides a widespread field for investigating new methods to produce clean electricity with high reliability and cost management. Fuel cells are new clean generations to make electricity and thermal energy together with high performance and no environmental pollution. According to the expansion of fuel cell usage in different industrial networks, the identification and optimization of its parameters is really significant. This paper presents optimization of a proton exchange membrane fuel cell (PEMFC) parameters based on modified particle swarm optimization with real valued mutation (RVM) and clonal algorithms. Mathematical equations of this type of fuel cell are presented as the main model structure in the optimization process. Optimized parameters based on clonal and RVM algorithms are compared with the desired values in the presence and absence of measurement noise. This paper shows that these methods can improve the performance of traditional optimization methods. Simulation results are employed to analyze and compare the performance of these methodologies in order to optimize the proton exchange membrane fuel cell parameters.

Keywords: clonal algorithm, proton exchange membrane fuel cell (PEMFC), particle swarm optimization (PSO), real-valued mutation (RVM)

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Authors: Boukhatem Mohammed Belkaid, Lahdir Mourad

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In this paper, we propose a new encryption system for security issues meteorological images from Meteosat Second Generation (MSG), which generates 12 images every 15 minutes. The hybrid encryption scheme is based on AES and RSA algorithms to validate the three security services are authentication, integrity and confidentiality. Privacy is ensured by AES, authenticity is ensured by the RSA algorithm. Integrity is assured by the basic function of the correlation between adjacent pixels. Our system generates a unique password every 15 minutes that will be used to encrypt each frame of the MSG meteorological basis to strengthen and ensure his safety. Several metrics have been used for various tests of our analysis. For the integrity test, we noticed the efficiencies of our system and how the imprint cryptographic changes at reception if a change affects the image in the transmission channel.

Keywords: AES, RSA, integrity, confidentiality, authentication, satellite MSG, encryption, decryption, key, correlation

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Authors: Evgeny Pokushalov, Claire Garcia, Andrey Ponomarenko, John Smith, Michael Johnson, Inessa Pak, Evgenya Shrainer, Dmitry Kudlay, Leila Kasimova, Richard Miller

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This study evaluated the efficacy of an AI-guided dietary supplement regimen compared to a standard physician-guided regimen in managing Type 2 diabetes (T2D). A total of 160 patients were randomly assigned to either the AI-guided group (n=80) or the physician-guided group (n=80) and followed over 90 days. The AI-guided group received 5.3 ± 1.2 supplements per patient, while the physician-guided group received 2.7 ± 0.6 supplements per patient. The AI system personalized supplement types and dosages based on individual genetic and metabolic profiles. The AI-guided group showed a significant reduction in HbA1c levels from 7.5 ± 0.8% to 7.1 ± 0.7%, compared to a reduction from 7.6 ± 0.9% to 7.4 ± 0.8% in the physician-guided group (mean difference: -0.3%, 95% CI: -0.5% to -0.1%; p < 0.01). Secondary outcomes, including fasting plasma glucose, HOMA-IR, and insulin levels, also improved more in the AI-guided group. Subgroup analyses revealed that the AI-guided regimen was particularly effective in patients with specific genetic polymorphisms and elevated metabolic markers. Safety profiles were comparable between both groups, with no serious adverse events reported. In conclusion, the AI-guided dietary supplement regimen significantly improved glycemic control and metabolic health in T2D patients compared to the standard physician-guided approach, demonstrating the potential of personalized AI-driven interventions in diabetes management.

Keywords: Type 2 diabetes, AI-guided supplementation, personalized medicine, glycemic control, metabolic health, genetic polymorphisms, dietary supplements, HbA1c, fasting plasma glucose, HOMA-IR, personalized nutrition

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Authors: Muhammad Umair Shahid, Abdul Rehman, Mudassir Mukhtar, Muhammad Nauman

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The smart antenna is the prominent technology that has become known in recent years to meet the growing demands of wireless communications. In an overcrowded atmosphere, its application is growing gradually. A methodical evaluation of the performance of Fixed Beamforming algorithms for smart antennas such as Multiple Sidelobe Canceller (MSC), Maximum Signal-to-interference ratio (MSIR) and minimum variance (MVDR) has been comprehensively presented in this paper. Simulation results show that beamforming is helpful in providing optimized response towards desired directions. MVDR beamformer provides the most optimal solution.

Keywords: fixed weight beamforming, array pattern, signal to interference ratio, power efficiency, element spacing, array elements, optimum weight vector

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Authors: Yue-Tzu Yang, Shu-Ching Liao

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This study presents the numerical simulation of three-dimensional incompressible steady and laminar fluid flow and conjugate heat transfer of a trapezoidal microchannel heat sink using water as a cooling fluid in a silicon substrate. Navier-Stokes equations with conjugate energy equation are discretized by finite-volume method. We perform numerical computations for a range of 50 ≦ Re ≦ 600, 0.05W ≦ P ≦ 0.8W, 20W/cm2 ≦ ≦ 40W/cm2. The present study demonstrates the numerical optimization of a trapezoidal microchannel heat sink design using the response surface methodology (RSM) and the genetic algorithm method (GA). The results show that the average Nusselt number increases with an increase in the Reynolds number or pumping power, and the thermal resistance decreases as the pumping power increases. The thermal resistance of a trapezoidal microchannel is minimized for a constant heat flux and constant pumping power.

Keywords: microchannel heat sinks, conjugate heat transfer, optimization, genetic algorithm method

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Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

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In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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Authors: Prittesh Patel, Rushabh Shah, Krishnamurthy Ramar, Vakulbhushan Bhaskar

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The present research work aims at finding genetic differences in the genomes of sugarcane red rot isolates Colletotrichum falcatum Went using Random Amplified Polymorphic DNA (RAPD) and interspersed simple sequence repeat (ISSR) molecular markers. Ten isolates of C. falcatum isolated from different red rot infected sugarcane cultivars stalk were used in present study. The amplified bands were scored across the lanes obtained in 15 RAPD primes and 21 ISSR primes successfully. The data were analysed using NTSYSpc 2.2 software. The results showed 80.6% and 68.07% polymorphism in RPAD and ISSR analysis respectively. Based on the RAPD analysis, ten genotypes were grouped into two major clusters at a cut-off value of 0.75. Geographically distant C. falcatum isolate cfGAN from south Gujarat had a level of similarity with Coimbatore isolate cf8436 presented on separate clade of bootstrapped dendrograms. First and second cluster consisted of five and three isolates respectively, indicating the close relation among them. The 21 ISSR primers produced 119 distinct and scorable loci in that 38 were monomorphic. The number of scorable loci for each primer varied from 2 (ISSR822) to 8 (ISSR807, ISSR823 and ISSR15) with an average of 5.66 loci per primer. Primer ISSR835 amplified the highest number of bands (57), while only 16 bands were obtained by primers ISSR822. Four primers namely ISSR830, ISSR845, ISSR4 and ISSR15 showed the highest value of percentage of polymorphism (100%). The results indicated that both of the marker systems RAPD and ISSR, individually can be effectively used in determination of genetic relationship among C falcatum accessions collected from different parts of south Gujarat.

Keywords: Colletotrichum falcatum, ISSR, RAPD, Red Rot

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Authors: Ming Su, Ziqiang Mu

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This paper proposes a synthesis method for nonuniform linear antenna arrays that combine Gaussian process regression (GPR) and genetic algorithm (GA). In this method, the GPR model can be used to calculate the array radiation pattern in the presence of mutual coupling effects, and then the GA is used to optimize the excitations and locations of the elements so as to generate the desired radiation pattern. In this paper, taking a 9-element nonuniform linear array as an example and the desired radiation pattern corresponding to a Chebyshev distribution as the optimization objective, optimize the excitations and locations of the elements. Finally, the optimization results are verified by electromagnetic simulation software CST, which shows that the method is effective.

Keywords: nonuniform linear antenna arrays, GPR, GA, mutual coupling effects, active element pattern

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Authors: Biswabandhu Bankura, Srikanta Guria, Madhusudan Das

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Purpose: Thyroid peroxidase (TPO) is the key enzyme in the biosynthesis of thyroid hormones. We aimed to identify the spectrum of mutations in the TPO gene leading to hypothyroidism in the population of West Bengal to establish the genetic etiology of the disease. Methods: 200 hypothyroid patients (case) and their corresponding sex and age matched 200 normal individuals (control) were screened depending on their clinical manifestations. Genomic DNA was isolated from peripheral blood samples and TPO gene (Exon 7 to Exon 14) was amplified by PCR. The PCR products were subjected to sequencing to identify mutations. Results: Single nucleotide changes such as Glu 641 Lys, Asp 668 Asn, Thr 725 Pro, Asp 620 Asn, Ser 398 Thr, and Ala 373 Ser were found. Changes in the TPO were assayed in vitro to compare mutant and wild-type activities. Five mutants were enzymatically inactive in the guaiacol and iodide assays. This is a strong indication that the mutations are present at crucial positions of the TPO gene, resulting in inactivated TPO. Key Findings: The results of this study may help to develop a genetic screening protocol for goiter and hypothyroidism in the population of West Bengal.

Keywords: thyroid peroxidase, hypothyroidism, mutation, in vitro assay, transfection

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Authors: Biswabandhu Bankura, Srikanta Guria, Madhusudan Das

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Purpose: Thyroid peroxidase (TPO) is the key enzyme in the biosynthesis of thyroid hormones. We aimed to identify the spectrum of mutations in the TPO gene leading to hypothyroidism in the population of West Bengal to establish the genetic etiology of the disease. Methods: 200 hypothyroid patients (case) and their corresponding sex and age matched 200 normal individuals (control) were screened depending on their clinical manifestations. Genomic DNA was isolated from peripheral blood samples and TPO gene (Exon 7 to Exon 14) was amplified by PCR. The PCR products were subjected to sequencing to identify mutations. Results: Single nucleotide changes such as Glu 641 Lys, Asp 668 Asn, Thr 725 Pro, Asp 620 Asn, Ser 398 Thr, and Ala 373 Ser were found. Changes in the TPO were assayed in vitro to compare mutant and wild-type activities. Five mutants were enzymatically inactive in the guaiacol and iodide assays. This is a strong indication that the mutations are present at crucial positions of the TPO gene, resulting in inactivated TPO. Key Findings: The results of this study may help to develop a genetic screening protocol for goiter and hypothyroidism in the population of West Bengal.

Keywords: thyroid peroxidase, hypothyroidism, mutation, in vitro assay, transfection

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Authors: G. Gurguze, I. Turkoglu

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Today, the developing features of technological tools with limited energy resources have made it necessary to use energy efficiently. Energy management techniques have emerged for this purpose. As with every field, energy management is vital for robots that are being used in many areas from industry to daily life and that are thought to take up more spaces in the future. Particularly, effective power management in autonomous and multi robots, which are getting more complicated and increasing day by day, will improve the performance and success. In this study, robot management algorithms, usage of renewable and hybrid energy sources, robot motion patterns, robot designs, sharing strategies of workloads in multiple robots, road and mission planning algorithms are discussed for efficient use of energy resources by mobile robots. These techniques have been evaluated in terms of efficient use of existing energy resources and energy management in robots.

Keywords: energy management, mobile robot, robot administration, robot management, robot planning

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Authors: A. R. Manu, V. K. Agrawal, K. N. Balasubramanya Murthy

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Authentication is required in stored database systems so that only authorized users can access the data and related cloud infrastructures. This paper proposes an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. The proposed technique is likely to be more robust as the probability of breaking the password is extremely low. This framework uses a multi-modal biometric approach and SMS to enforce additional security measures with the conventional Login/password system. The robustness of the technique is demonstrated mathematically using a statistical analysis. This work presents the authentication system along with the user authentication architecture diagram, activity diagrams, data flow diagrams, sequence diagrams, and algorithms.

Keywords: design, implementation algorithms, performance, biometric approach

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Authors: Omar Nasr, Yasser Naguib, Mohamed Hafez

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This paper aims at providing an innovative solution for blind interference threshold estimation in an underlay cognitive network to be used in adaptive beamforming by secondary user Transmitter and Receiver. For the task of threshold estimation, blind detection of modulation and SNR are used. For the sake of beamforming several localization algorithms are compared to settle on best one for cognitive environment. Beamforming algorithms as LCMV (Linear Constraint Minimum Variance) and MVDR (Minimum Variance Distortion less) are also proposed and compared. The idea of just nulling the primary user after knowledge of its location is discussed against the idea of working under interference threshold.

Keywords: cognitive radio, underlay, beamforming, MUSIC, MVDR, LCMV, threshold estimation

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Authors: Yelin Zhao, Xinxiu Li, Martin Smelik, Oleg Sysoev, Firoj Mahmud, Dina Mansour Aly, Mikael Benson

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Background: Early diagnosis of pancreatic cancer is clinically challenging due to vague, or no symptoms, and lack of biomarkers. Polygenic risk score (PRS) scores may provide a valuable tool to assess increased or decreased risk of PC. This study aimed to develop such PRS by filtering genetic variants identified by GWAS using transcriptional programs identified by single-cell RNA sequencing (scRNA-seq). Methods: ScRNA-seq data from 24 pancreatic ductal adenocarcinoma (PDAC) tumor samples and 11 normal pancreases were analyzed to identify differentially expressed genes (DEGs) in in tumor and microenvironment cell types compared to healthy tissues. Pathway analysis showed that the DEGs were enriched for hundreds of significant pathways. These were clustered into 40 “programs” based on gene similarity, using the Jaccard index. Published genetic variants associated with PDAC were mapped to each program to generate program PRSs (pPRSs). These pPRSs, along with five previously published PRSs (PGS000083, PGS000725, PGS000663, PGS000159, and PGS002264), were evaluated in a European-origin population from the UK Biobank, consisting of 1,310 PDAC participants and 407,473 non-pancreatic cancer participants. Stepwise Cox regression analysis was performed to determine associations between pPRSs with the development of PC, with adjustments of sex and principal components of genetic ancestry. Results: The PDAC genetic variants were mapped to 23 programs and were used to generate pPRSs for these programs. Four distinct pPRSs (P1, P6, P11, and P16) and two published PRSs (PGS000663 and PGS002264) were significantly associated with an increased risk of developing PC. Among these, P6 exhibited the greatest hazard ratio (adjusted HR[95% CI] = 1.67[1.14-2.45], p = 0.008). In contrast, P10 and P4 were associated with lower risk of developing PC (adjusted HR[95% CI] = 0.58[0.42-0.81], p = 0.001, and adjusted HR[95% CI] = 0.75[0.59-0.96], p = 0.019). By comparison, two of the five published PRS exhibited an association with PDAC onset with HR (PGS000663: adjusted HR[95% CI] = 1.24[1.14-1.35], p < 0.001 and PGS002264: adjusted HR[95% CI] = 1.14[1.07-1.22], p < 0.001). Conclusion: Compared to published PRSs, scRNA-seq-based pPRSs may be used not only to assess increased but also decreased risk of PDAC.

Keywords: cox regression, pancreatic cancer, polygenic risk score, scRNA-seq, UK biobank

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Authors: Hichem Sassi, Tawfik Najeh, Noureddine Liouane

Abstract:

The localization information is crucial for the operation of WSN. There are principally two types of localization algorithms. The Range-based localization algorithm has strict requirements on hardware; thus, it is expensive to be implemented in practice. The Range-free localization algorithm reduces the hardware cost. However, it can only achieve high accuracy in ideal scenarios. In this paper, we locate unknown nodes by incorporating the advantages of these two types of methods. The proposed algorithm makes the unknown nodes select the nearest anchor using the Received Signal Strength Indicator (RSSI) and choose two other anchors which are the most accurate to achieve the estimated location. Our algorithm improves the localization accuracy compared with previous algorithms, which has been demonstrated by the simulating results.

Keywords: WSN, localization, DV-Hop, RSSI

Procedia PDF Downloads 360

Authors: Surabhi Maiti, Prajakta Tamhankar, Prachi Uttam Mehta

Abstract:

Since the accomplishment of the Human Genome Project, there has been an unparalled escalation in the sequencing of genomic data. This project has been the first major vault in the field of medical research, especially in genomics. This project won accolades by using a concept called Bigdata which was earlier, extensively used to gain value for business. Bigdata makes use of data sets which are generally in the form of files of size terabytes, petabytes, or exabytes and these data sets were traditionally used and managed using excel sheets and RDBMS. The voluminous data made the process tedious and time consuming and hence a stronger framework called Hadoop was introduced in the field of genetic sciences to make data processing faster and efficient. This paper focuses on using SPARK which is gaining momentum with the advancement of BigData technologies. Cloud Storage is an effective medium for storage of large data sets which is generated from the genetic research and the resultant sets produced from SPARK analysis.

Keywords: human genome project, Bigdata, genomic data, SPARK, cloud storage, Hadoop

Procedia PDF Downloads 259

Authors: Hesham Kozou

Abstract:

Sensorineural hearing loss (SNHL) poses a significant challenge due to limited access to the inner ear for therapies. Emerging treatments such as regenerative, genetic, and pharmacotherapies offer hope for addressing this condition. This study aims to highlight the potential of cochlear implants and emerging therapies in managing sensorineural hearing loss by improving access to the inner ear. The study is conducted through a review of relevant literature and research articles in the field of cochlear implants and emerging therapies for hearing loss. It outlines how advancements in cochlear implant technologies, electrodes, and surgical techniques can facilitate the delivery of therapies to the inner ear, potentially revolutionizing the treatment of sensorineural hearing loss. The study underscores the potential of cochlear implants and emerging therapies in revolutionizing the treatment landscape for sensorineural hearing loss, emphasizing the feasibility of curing this condition by leveraging technological advancements.

Keywords: therapies for hearing loss management, future of CI as a cochlear delivery channel, regenerative, genetic and pharmacotherapeutic management of hearing loss

Procedia PDF Downloads 48

Authors: R. Akbari, M. A. Ehyaei, R. Shahi Shavvon

Abstract:

Nowadays, solar energy is used for energy purposes such as the use of thermal energy for domestic, industrial and power applications, as well as the conversion of the sunlight into electricity by photovoltaic cells. In this study, the thermodynamic simulation of the solar Rankin cycle with phase change material (paraffin) was first studied. Then energy and exergy analyses were performed. For optimization, a single and multi-objective genetic optimization algorithm to maximize thermal and exergy efficiency was used. The parameters discussed in this paper included the effects of input pressure on turbines, input mass flow to turbines, the surface of converters and collector angles on thermal and exergy efficiency. In the organic Rankin cycle, where solar energy is used as input energy, the fluid selection is considered as a necessary factor to achieve reliable and efficient operation. Therefore, silicon oil is selected for a high-temperature cycle and water for a low-temperature cycle as an operating fluid. The results showed that increasing the mass flow to turbines 1 and 2 would increase thermal efficiency, while it reduces and increases the exergy efficiency in turbines 1 and 2, respectively. Increasing the inlet pressure to the turbine 1 decreases the thermal and exergy efficiency, and increasing the inlet pressure to the turbine 2 increases the thermal efficiency and exergy efficiency. Also, increasing the angle of the collector increased thermal efficiency and exergy. The thermal efficiency of the system was 22.3% which improves to 33.2 and 27.2% in single-objective and multi-objective optimization, respectively. Also, the exergy efficiency of the system was 1.33% which has been improved to 1.719 and 1.529% in single-objective and multi-objective optimization, respectively. These results showed that the thermal and exergy efficiency in a single-objective optimization is greater than the multi-objective optimization.

Keywords: exergy analysis, genetic algorithm, rankine cycle, single and multi-objective function

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Authors: Navab Karimi, Tohid Alizadeh

Abstract:

An intelligent vision-based system was designed to measure the quality and purity of raisins. A machine vision setup was utilized to capture the images of bulk raisins in ranges of 5-50% mixed pure-impure berries. The textural features of bulk raisins were extracted using Grey-level Histograms, Co-occurrence Matrix, and Local Binary Pattern (a total of 108 features). Genetic Algorithm and neural network regression were used for selecting and ranking the best features (21 features). As a result, the GLCM features set was found to have the highest accuracy (92.4%) among the other sets. Followingly, multiple feature combinations of the previous stage were fed into the second regression (linear regression) to increase accuracy, wherein a combination of 16 features was found to be the optimum. Finally, a Support Vector Machine (SVM) classifier was used to differentiate the mixtures, producing the best efficiency and accuracy of 96.2% and 97.35%, respectively.

Keywords: sun-dried organic raisin, genetic algorithm, feature extraction, ann regression, linear regression, support vector machine, south azerbaijan.

Procedia PDF Downloads 73

Authors: Reza Babajanivalashedi, Stefania Lo Feudo, Jean-Luc Dion

Abstract:

Liquid sloshing is a crucial problem for the dynamic of moving containers in the packaging industries. Sloshing issues have been so far mainly modeled within the framework of fluid dynamics or by using equivalent mechanical models with different kinds of movements and shapes of containers. Nevertheless, these approaches do not allow to determinate the shape of the free surface of the liquid in case of the irregular shape of the moving containers, so that experimental measurements may be required. If there is too much slosh in the moving tank, the liquid can be splashed out on the packages. So, the free surface oscillation must be controlled/reduced to eliminate the splashing. The purpose of this research is to propose an optimization algorithm for finding an optimum command law to reduce surface elevation. In the first step, the free surface of the liquid is simulated based on the separation variable and weak formulation models. Then Genetic and Gradient algorithms are developed for finding the optimum command law. The optimum command law is compared with existing command laws, and the results show that there is a significant difference in surface oscillation between optimum and existing command laws. This algorithm is applicable for different varieties of bottles in case of using the camera for detecting the liquid elevation, and it can produce new command laws for different kinds of tanks to reduce the surface oscillation and remove the splashing phenomenon.

Keywords: sloshing phenomenon, separation variables, weak formulation, optimization algorithm, command law

Procedia PDF Downloads 151