Search results for: genetic%20algorithm

Authors: Mustafa Ural, Can Bayseferogulari

Abstract:

In this work, radio frequency (RF) coupling between two HF antennas on a shipboard platform is minimized by determining an optimal antenna placement. Unlike the other works, the coupling is minimized not only at single frequency but over the whole frequency band of operation. Similarly, GAO and PSO, are used in order to determine optimal antenna placement. Throughout this work, outputs of two optimization techniques are compared with each other in terms of antenna placements and coupling results. At the end of the work, far-field radiation pattern performances of the antennas at their optimal places are analyzed in terms of directivity and coverage in order to see that.

Keywords: electromagnetic compatibility, antenna placement, optimization, genetic algorithm optimization, particle swarm optimization

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Authors: Debbarma Asis, Guha Chandan

Abstract:

Tumor Protein-53 (P53) is one of the tumor suppressor proteins. P53 regulates the cell cycle that conserves stability by preventing genome mutation. It is named so as it runs as 53-kilodalton (kDa) protein on Polyacrylamide gel electrophoresis although the actual mass is 43.7 kDa. Experimental evidence has indicated that P53 cancer mutants loses tumor suppression activity and subsequently gain oncogenic activities to promote tumourigenesis. Tumor-specific DNA has recently been detected in the plasma of breast cancer patients. Detection of tumor-specific genetic materials in cancer patients may provide a unique and valuable tumor marker for diagnosis and prognosis. Commercially available MDA-468 breast cancer cell line was used for the proposed study.

Keywords: tumor protein (P53), cancer mutants, MDA-468, tumor suppressor gene

Procedia PDF Downloads 457

Authors: Tareg Belali, Mosleh Abomughaid, Muhanad Alhujaily

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

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

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Authors: Ran Vir Singh, Anuj Chauhan, Subhodh Kumar, Rajesh Rathore, Satish Kumar, B Gopi, Sushil Kumar, Tarun Kumar, Ramji Yadav, Donna Phangchopi, Shoor Vir Singh

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Paratuberculosis caused by Mycobacterium avium subspecies paratuberculosis (MAP) is a chronic granulomatous enteritis affecting ruminants. It is responsible for significant economic losses in livestock industry worldwide. This organism is also of public health concern due to an unconfirmed link to Crohn’s disease. Susceptibility to paratuberculosis has been suggested to have genetic component with low to moderate heritability. Number of SNPs in various candidates genes have been observed to be affecting the susceptibility toward paratuberculosis. The objective of this study was to explore the association of various SNPs in the candidate genes and QTL region with MAP. A total of 117 SNPs from SLC11A1, IFNG, CARD15, TLR2, TLR4, CLEC7A, CD209, SP110, ANKARA2, PGLYRP1 and one QTL were selected for study. A total of 1222 cattle from various organized herds, gauhsalas and farmer herds were screened for MAP infection by Johnin intradermal skin test, AGID, serum ELISA, fecal microscopy, fecal culture and IS900 blood PCR. Based on the results of these tests, a case and control population of 200 and 183 respectively was established for study. A total of 117 SNPs from 10 candidate genes and one QTL were selected and validated/tested in our case and control population by PCR-RFLP technique. Data was analyzed using SAS 9.3 software. Statistical analysis revealed that, 107 out of 117 SNPs were not significantly associated with occurrence of MAP. Only SNP rs55617172 of TLR2, rs8193046 and rs8193060 of TLR4, rs110353594 and rs41654445 of CLEC7A, rs208814257of CD209, rs41933863 of ANKRA2, two loci {SLC11A1(53C/G)} and {IFNG (185 G/r) } and SNP rs41945014 in QTL region was significantly associated with MAP. Six SNP from 10 significant SNPs viz., rs110353594 and rs41654445 from CLEC7A, rs8193046 and rs8193060 from TLR4, rs109453173 from SLC11A1 rs208814257 from CD209 were validated in new case and control population. Out of these only one SNP rs8193046 of TLR4 gene was found significantly associated with occurrence of MAP in cattle. ODD ratio indicates that animals with AG genotype were more susceptible to MAP and this finding is in accordance with the earlier report. Hence it reaffirms that AG genotype can serve as a reliable genetic marker for indentifying more susceptible cattle in future selection against MAP infection in cattle.

Keywords: SNP, candidate genes, paratuberculosis, cattle

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Authors: Rachel Danielson, Brendan Bohannan, S.M. Tsai, Kyle Meyer, Jorge L.M. Rodrigues

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The Amazon Rainforest is a global diversity hotspot and crucial carbon sink, but approximately 20% of its total extent has been deforested- primarily for the establishment of cattle pasture. Understanding the impact of this large-scale disturbance on soil microbial community composition and activity is crucial in understanding potentially consequential shifts in nutrient or greenhouse gas cycling, as well as adding to the body of knowledge concerning how these complex communities respond to human disturbance. In this study, surface soils (0-10cm) were collected from three forests and three 45-year-old pastures in Rondonia, Brazil (the Amazon state with the greatest rate of forest destruction) in order to determine the impact of forest conversion on microbial communities involved in nitrogen fixation. Soil chemical and physical parameters were paired with measurements of microbial activity and genetic profiles to determine how community composition and process rates relate to environmental conditions. Measuring both the natural abundance of 15N in total soil N, as well as incorporation of enriched 15N2 under incubation has revealed that conversion of primary forest to cattle pasture results in a significant increase in the rate of nitrogen fixation by free-living diazotrophs. Quantification of nifH gene copy numbers (an essential subunit encoding the nitrogenase enzyme) correspondingly reveals a significant increase of genes in pasture compared to forest soils. Additionally, genetic sequencing of both nifH genes and transcripts shows a significant increase in the diversity of the present and metabolically active diazotrophs within the soil community. Levels of both organic and inorganic nitrogen tend to be lower in pastures compared to forests, with ammonium rather than nitrate as the dominant inorganic form. However, no significant or consistent differences in total, extractable, permanganate-oxidizable, or loss-on-ignition carbon are present between the two land-use types. Forest conversion is associated with a 0.5- 1.0 unit pH increase, but concentrations of many biologically relevant nutrients such as phosphorus do not increase consistently. Increases in free-living diazotrophic community abundance and activity appear to be related to shifts in carbon to nitrogen pool ratios. Furthermore, there may be an important impact of transient, low molecular weight plant-root-derived organic carbon on free-living diazotroph communities not captured in this study. Preliminary analysis of nitrogenase gene variant composition using NovoSeq metagenomic sequencing indicates that conversion of forest to pasture may significantly enrich vanadium-based nitrogenases. This indication is complemented by a significant decrease in available soil molybdenum. Very little is known about the ecology of diazotrophs utilizing vanadium-based nitrogenases, so further analysis may reveal important environmental conditions favoring their abundance and diversity in soil systems. Taken together, the results of this study indicate a significant change in nitrogen cycling and diazotroph community composition with the conversion of the Amazon Rainforest. This may have important implications for the sustainability of cattle pastures once established since nitrogen is a crucial nutrient for forage grass productivity.

Keywords: free-living diazotrophs, land use change, metagenomic sequencing, nitrogen fixation

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Authors: Bale Baidi Blaise, Gilles Marckmann, Liman Kaoye, Talaka Dya, Moustapha Bachirou, Gambo Betchewe, Tibi Beda

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This work highlights the capabilities of particles swarm optimization (PSO) method to identify parameters of hyperelastic models. The study compares this method with Genetic Algorithm (GA) method, Least Squares (LS) method, Pattern Search Algorithm (PSA) method, Beda-Chevalier (BC) method and the Levenberg-Marquardt (LM) method. Four classic hyperelastic models are used to test the different methods through parameters identification. Then, the study compares the ability of these models to reproduce experimental Treloar data in simple tension, biaxial tension and pure shear.

Keywords: particle swarm optimization, identification, hyperelastic, model

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Authors: Vassilios Moussas, Dimos N. Pantazis, Panagioths Stratakis

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The aim of this paper is to present the optimization methodology developed in the frame of a Coastal Transport Information System. The system will be used for the effective design of coastal transportation lines and incorporates subsystems that implement models, tools and techniques that may support the design of improved networks. The role of the optimization and decision subsystem is to provide the user with better and optimal scenarios that will best fulfill any constrains, goals or requirements posed. The complexity of the problem and the large number of parameters and objectives involved led to the adoption of an evolutionary method (Genetic Algorithms). The problem model and the subsystem structure are presented in detail, and, its support for simulation is also discussed.

Keywords: coastal transport, modeling, optimization

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Authors: Marija Milašinović-Šeremešić, Valentina Semenčenko, Milica Radosavljević, Dušanka Terzić, Ljiljana Mojović, Ljubica Dokić

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Maize (Zea mays L.) is one of the most important cereal crops, and as such, one of the most significant naturally renewable carbohydrate raw materials for the production of energy and multitude of different products. The main goal of the present study was to investigate a suitability of selected maize hybrids of different genetic background produced in Maize Research Institute ‘Zemun Polje’, Belgrade, Serbia, for starch, bioethanol and animal feed production. All the hybrids are commercial and their detailed characterization is important for the expansion of their different uses. The starches were isolated by using a 100-g laboratory maize wet-milling procedure. Hydrolysis experiments were done in two steps (liquefaction with Termamyl SC, and saccharification with SAN Extra L). Starch hydrolysates obtained by the two-step hydrolysis of the corn flour starch were subjected to fermentation by S. cerevisiae var. ellipsoideus under semi-anaerobic conditions. The digestibility based on enzymatic solubility was performed by the Aufréré method. All investigated ZP maize hybrids had very different physical characteristics and chemical composition which could allow various possibilities of their use. The amount of hard (vitreous) and soft (floury) endosperm in kernel is considered one of the most important parameters that can influence the starch and bioethanol yields. Hybrids with a lower test weight and density and a greater proportion of soft endosperm fraction had a higher yield, recovery and purity of starch. Among the chemical composition parameters only starch content significantly affected the starch yield. Starch yields of studied maize hybrids ranged from 58.8% in ZP 633 to 69.0% in ZP 808. The lowest bioethanol yield of 7.25% w/w was obtained for hybrid ZP 611k and the highest by hybrid ZP 434 (8.96% w/w). A very significant correlation was determined between kernel starch content and the bioethanol yield, as well as volumetric productivity (48h) (r=0.66). Obtained results showed that the NDF, ADF and ADL contents in the whole maize plant of the observed ZP maize hybrids varied from 40.0% to 60.1%, 18.6% to 32.1%, and 1.4% to 3.1%, respectively. The difference in the digestibility of the dry matter of the whole plant among hybrids (ZP 735 and ZP 560) amounted to 18.1%. Moreover, the differences in the contents of the lignocelluloses fraction affected the differences in dry matter digestibility. From the results it can be concluded that genetic background of the selected maize hybrids plays an important part in estimation of the technological value of maize hybrids for various purposes. Obtained results are of an exceptional importance for the breeding programs and selection of potentially most suitable maize hybrids for starch, bioethanol and animal feed production.

Keywords: bioethanol, biomass quality, maize, starch

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Authors: Y. I. Tretyakova, S. G. Shulkina, T. Y. Kravtsova, A. A. Antipova, N. Y. Kolomeets

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The research aimed to assess the functional significance of tumor necrosis factor-alpha (TNF-α) gene polymorphism at the -308G/A (rs1800629) region and vascular endothelial growth factor A (VEGFA) gene polymorphism at the -634G/C (rs 2010963) region in the development of ulcerative colitis (UC), focusing on patients from the Perm region, Russia. We examined 70 UC patients and 50 healthy donors during the active phase of the disease. Our focus was on TNF-α and VEGF concentration in the blood serum, as well as TNF-α and VEGFA gene polymorphisms at the -308G/А and -634G/C regions, respectively. We found that TNF-α and VEGF levels were significantly higher in patients with severe UC and high endoscopic activity compared to those with milder forms of the disease and low endoscopic activity. These tests could serve as additional non-invasive markers for assessing mucosal damage in the large intestine of UC patients. The frequency of allele variations in the TNF-α gene -308G/A (rs1800629) revealed a significantly higher occurrence of the unfavorable homozygote AA in UC patients compared to donors. Additionally, the major allele G and the allele pair GG were more frequent in patients with mild to moderate disease and 1-2 degree of endoscopic activity than in those with severe UC and 3-4 degree of endoscopic activity (χ2=14.19; p=0.000). We also observed a mutant allele A and the unfavorable homozygote AA associated with severe progressive UC. The occurrence of the mutant allele increased the risk of severe UC by 5 times (OR 5.03; CI 12.07-12.21). We did not find any significant differences in the frequency of the CC homozygote (χ2=1.02; p=0.6; OR=1.32) and the mutant allele C of the VEGFA gene -634G/C (rs 2010963) (χ2=0.01; p=0.913; OR=0.97) between groups of UC patients and healthy individuals. However, we detected that the mutant allele C and the unfavorable homozygote CC of the VEGFA gene were associated with more severe endoscopic changes in the colonic mucosa of UC patients (χ2=25,76; р=0,000; OR=0,15). The presence of the mutant allele increased the risk of severe UC by 6 times (OR 6,78; CI 3,13–14,7). We found a direct correlation between TNF-α and VEGFA gene polymorphisms, increased production of the same factors, disease severity, and endoscopic activity (р=0.000). Therefore, the presence of the mutant allele A and homozygote AA of the TNF-α gene at the -308G/A region and the mutant allele C and homozygote CC of the VEGFA gene at the -634G/C region are associated with risks related to an unfavorable clinical course of UC, frequent recurrences, and rapid progression. These findings should be considered when making prognoses regarding the clinical course of the disease and selecting treatment strategies. The presence of the homozygote AA in the TNF-α gene (rs1800629) is considered a sign of genetic predisposition to UC.

Keywords: gene polymorphism, TNF-α, ulcerative colitis, VEGF

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Authors: Rebecca Richards Steed, James Van Derslice, Ken Smith, Richard Medina, Amanda Bakian

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Elucidating gene-environment interactions for heritable disease outcomes is an emerging area of disease research, with genetic studies informing hypotheses for environment and gene interactions underlying some of the most confounding diseases of our time, like autism spectrum disorder (ASD). Geography has thus far played a key role in identifying environmental factors contributing to disease, but its use can be broadened to include genetic and environmental factors that have a synergistic effect on disease. Through the use of family pedigrees and disease outcomes with life-course residential histories, space-time clustering of generations at critical developmental windows can provide further understanding of (1) environmental factors that contribute to disease patterns in families, (2) susceptible critical windows of development most impacted by environment, (3) and that are most likely to lead to an ASD diagnosis. This paper introduces a retrospective case-control study that utilizes pedigree data, health data, and residential life-course location points to find space-time clustering of ancestors with a grandchild/child with a clinical diagnosis of ASD. Finding space-time clusters of ancestors at critical developmental windows serves as a proxy for shared environmental exposures. The authors refer to geographic life-course exposures as geographic legacies. Identifying space-time clusters of ancestors creates a bridge for researching exposures of past generations that may impact modern-day progeny health. Results from the space-time cluster analysis show multiple clusters for the maternal and paternal pedigrees. The paternal grandparent pedigree resulted in the most space-time clustering for birth and childhood developmental windows. No statistically significant clustering was found for adolescent years. These results will be further studied to identify the specific share of space-time environmental exposures. In conclusion, this study has found significant space-time clusters of parents, and grandparents for both maternal and paternal lineage. These results will be used to identify what environmental exposures have been shared with family members at critical developmental windows of time, and additional analysis will be applied.

Keywords: family pedigree, environmental exposure, geographic legacy, medical geography, transgenerational inheritance

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Authors: Zelikha Labbani

Abstract:

The in vitro isolated microspore culture is the most powerful androgenic pathway to produce doubled haploid plants in the short time. To deviate a microspore toward embryogenesis, a number of factors, different for each species, must concur at the same time and place. Once induced, the microspore undergoes numerous changes at different levels, from overall morphology to gene expression. Induction of microspore embryogenesis not only implies the expression of an embryogenic program, but also a stress-related cellular response and a repression of the gametophytic program to revert the microspore to a totipotent status. As haploid single cells, microspore became a strategy to achieve various objectives particularly in genetic engineering. In this communication we would show the most recent advances in the producing haploid embryos via in vitro isolated microspore culture.

Keywords: in vitro isolated microspore culture, success, haploid cells, bioinformatics, biomedicine

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Authors: Elif Gencturk, Ekin Yurdakul, Ahmet Y. Celik, Senol Mutlu, Kutlu O. Ulgen

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Yeast cells are generally used as a model system of eukaryotes due to their complex genetic structure, rapid growth ability in optimum conditions, easy replication and well-defined genetic system properties. Thus, yeast cells increased the knowledge of the principal pathways in humans. During fermentation, carbohydrates (hexoses and pentoses) degrade into some toxic by-products such as 5-hydroxymethylfurfural (5-HMF or HMF) and furfural. HMF influences the ethanol yield, and ethanol productivity; it interferes with microbial growth and is considered as a potent inhibitor of bioethanol production. In this study, yeast single cell behavior under HMF application was monitored by using a continuous flow single phase microfluidic platform. Microfluidic device in operation is fabricated by hot embossing and thermo-compression techniques from cyclo-olefin polymer (COP). COP is biocompatible, transparent and rigid material and it is suitable for observing fluorescence of cells considering its low auto-fluorescence characteristic. The response of yeast cells was recorded through Red Fluorescent Protein (RFP) tagged Nop56 gene product, which is an essential evolutionary-conserved nucleolar protein, and also a member of the box C/D snoRNP complexes. With the application of HMF, yeast cell proliferation continued but HMF slowed down the cell growth, and after HMF treatment the cell proliferation stopped. By the addition of fresh nutrient medium, the yeast cells recovered after 6 hours of HMF exposure. Thus, HMF application suppresses normal functioning of cell cycle but it does not cause cells to die. The monitoring of Nop56 expression phases of the individual cells shed light on the protein and ribosome synthesis cycles along with their link to growth. Further computational study revealed that the mechanisms underlying the inhibitory or inductive effects of HMF on growth are enriched in functional categories of protein degradation, protein processing, DNA repair and multidrug resistance. The present microfluidic device can successfully be used for studying the effects of inhibitory agents on growth by single cell tracking, thus capturing cell to cell variations. By metabolic engineering techniques, engineered strains can be developed, and the metabolic network of the microorganism can thus be manipulated such that chemical overproduction of target metabolite is achieved along with the maximum growth/biomass yield.  

Keywords: COP, HMF, ribosome biogenesis, thermoplastic microbioreactor, yeast

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Authors: Kostas Metaxiotis, Kostas Liagkouras

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This study presents an Expert System specially designed to be used with Multiobjective Evolutionary Algorithms (MOEAs) for the solution of the portfolio selection problem. The validation of the proposed hybrid System is done by using data sets from Hang Seng 31 in Hong Kong, DAX 100 in Germany and FTSE 100 in UK. The performance of the proposed system is assessed in comparison with the Non-dominated Sorting Genetic Algorithm II (NSGAII). The evaluation of the performance is based on different performance metrics that evaluate both the proximity of the solutions to the Pareto front and their dispersion on it. The results show that the proposed hybrid system is efficient for the solution of this kind of problems.

Keywords: expert systems, multi-objective optimization, evolutionary algorithms, portfolio selection

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Authors: Danni Cheng

Abstract:

Background: Preclinical and epidemiological studies have reported potential protective effects of low-density lipoprotein cholesterol (LDL-C) lowering drugs on head and neck squamous cell cancer (HNSCC) survival, but the causality was not consistent. Genetic variants associated with LDL-C lowering drug targets can predict the effects of their therapeutic inhibition on disease outcomes. Objective: We aimed to evaluate the causal association of genetically proxied cholesterol-lowering drug targets and circulating lipid traits with cancer survival in HNSCC patients stratified by human papillomavirus (HPV) status using two-sample Mendelian randomization (MR) analyses. Method: Single-nucleotide polymorphisms (SNPs) in gene region of LDL-C lowering drug targets (HMGCR, NPC1L1, CETP, PCSK9, and LDLR) associated with LDL-C levels in genome-wide association study (GWAS) from the Global Lipids Genetics Consortium (GLGC) were used to proxy LDL-C lowering drug action. SNPs proxy circulating lipids (LDL-C, HDL-C, total cholesterol, triglycerides, apoprotein A and apoprotein B) were also derived from the GLGC data. Genetic associations of these SNPs and cancer survivals were derived from 1,120 HPV-positive oropharyngeal squamous cell carcinoma (OPSCC) and 2,570 non-HPV-driven HNSCC patients in VOYAGER program. We estimated the causal associations of LDL-C lowering drugs and circulating lipids with HNSCC survival using the inverse-variance weighted method. Results: Genetically proxied HMGCR inhibition was significantly associated with worse overall survival (OS) in non-HPV-drive HNSCC patients (inverse variance-weighted hazard ratio (HR IVW), 2.64[95%CI,1.28-5.43]; P = 0.01) but better OS in HPV-positive OPSCC patients (HR IVW,0.11[95%CI,0.02-0.56]; P = 0.01). Estimates for NPC1L1 were strongly associated with worse OS in both total HNSCC (HR IVW,4.17[95%CI,1.06-16.36]; P = 0.04) and non-HPV-driven HNSCC patients (HR IVW,7.33[95%CI,1.63-32.97]; P = 0.01). A similar result was found that genetically proxied PSCK9 inhibitors were significantly associated with poor OS in non-HPV-driven HNSCC (HR IVW,1.56[95%CI,1.02 to 2.39]). Conclusion: Genetically proxied long-term HMGCR inhibition was significantly associated with decreased OS in non-HPV-driven HNSCC and increased OS in HPV-positive OPSCC. While genetically proxied NPC1L1 and PCSK9 had associations with worse OS in total and non-HPV-driven HNSCC patients. Further research is needed to understand whether these drugs have consistent associations with head and neck tumor outcomes.

Keywords: Mendelian randomization analysis, head and neck cancer, cancer survival, cholesterol, statin

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Authors: Ramin Javadzadeh

Abstract:

The particle swarm optimization are Meta heuristic optimization method, which are used for clustering and pattern recognition applications are abundantly. These algorithms in multimodal optimization problems are more efficient than genetic algorithms. A major drawback in these algorithms is their slow convergence to global optimum and their weak stability can be considered in various running of these algorithms. In this paper, improved Particle swarm optimization is introduced for the first time to overcome its problems. The fuzzy cellular automata is used for improving the algorithm efficiently. The credibility of the proposed approach is evaluated by simulations, and it is shown that the proposed approach achieves better results can be achieved compared to the Particle swarm optimization algorithms.

Keywords: cellular automata, cellular learning automata, local search, optimization, particle swarm optimization

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Authors: Abiodun Olayinka, Daniel Dzidzienyo, Pangirayi Tongoona, Samuel Offei, Edwige Gaby Nkouaya Mbanjo, Chiedozie Egesi, Ismail Yusuf Rabbi

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Cassava (Manihot esculenta Crantz) is a major source of starch for various industrial applications. However, the traditional cultivation and harvesting methods of cassava are labour-intensive and inefficient, limiting the supply of fresh cassava roots for industrial starch production. To achieve improved productivity and quality of fresh cassava roots through mechanized cultivation, cassava cultivars with compact plant architecture and moderate plant height are needed. Plant architecture-related traits, such as plant height, harvest index, stem diameter, branching angle, and lodging tolerance, are critical for crop productivity and suitability for mechanized cultivation. However, the genetics of cassava plant architecture remain poorly understood. This study aimed to identify the genetic bases of the relationships between plant architecture traits and productivity-related traits, particularly starch content. A panel of 453 clones developed at the International Institute of Tropical Agriculture, Nigeria, was genotyped and phenotyped for 18 plant architecture and productivity-related traits at four locations in Nigeria. A genome-wide association study (GWAS) was conducted using the phenotypic data from a panel of 453 clones and 61,238 high-quality Diversity Arrays Technology sequencing (DArTseq) derived Single Nucleotide Polymorphism (SNP) markers that are evenly distributed across the cassava genome. Five significant associations between ten SNPs and three plant architecture component traits were identified through GWAS. We found five SNPs on chromosomes 6 and 16 that were significantly associated with shoot weight, harvest index, and total yield through genome-wide association mapping. We also discovered an essential candidate gene that is co-located with peak SNPs linked to these traits in M. esculenta. A review of the cassava reference genome v7.1 revealed that the SNP on chromosome 6 is in proximity to Manes.06G101600.1, a gene that regulates endodermal differentiation and root development in plants. The findings of this study provide insights into the genetic basis of plant architecture and yield in cassava. Cassava breeders could leverage this knowledge to optimize plant architecture and yield in cassava through marker-assisted selection and targeted manipulation of the candidate gene.

Keywords: Manihot esculenta Crantz, plant architecture, DArtseq, SNP markers, genome-wide association study

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Authors: Shraddha Rane, Richard Warren, Stephen Eyre

Abstract:

L-23 is a pro-inflammatory molecule that signals T cells to release cytokines such as IL-17A and IL-22. Psoriasis is driven by a dysregulated immune response, within which IL-23 is now thought to play a key role. Genome-wide association studies (GWAS) have identified a number of genetic risk loci that support the involvement of IL-23 signalling in psoriasis; in particular a robust susceptibility locus at a gene encoding a subunit of the IL-23 receptor (IL23R) (Stuart et al., 2015; Tsoi et al., 2012). The lead psoriasis-associated SNP rs9988642 is located approximately 500 bp downstream of IL23R but is in tight linkage disequilibrium (LD) with a missense SNP rs11209026 (R381Q) within IL23R (r2 = 0.85). The minor (G) allele of rs11209026 is present in approximately 7% of the population and is protective for psoriasis and several other autoimmune diseases including IBD, ankylosing spondylitis, RA and asthma. The psoriasis-associated missense SNP R381Q causes an arginine to glutamine substitution in a region of the IL23R protein between the transmembrane domain and the putative JAK2 binding site in the cytoplasmic portion. This substitution is expected to affect the receptor’s surface localisation or signalling ability, rather than IL23R expression. Recent studies have also identified a psoriatic arthritis (PsA)-specific signal at IL23R; thought to be independent from the psoriasis association (Bowes et al., 2015; Budu-Aggrey et al., 2016). The lead PsA-associated SNP rs12044149 is intronic to IL23R and is in LD with likely causal SNPs intersecting promoter and enhancer marks in memory CD8+ T cells (Budu-Aggrey et al., 2016). It is therefore likely that the PsA-specific SNPs affect IL23R function via a different mechanism compared with the psoriasis-specific SNPs. It could be hypothesised that the risk allele for PsA located within the IL23R promoter causes an increase IL23R expression, relative to the protective allele. An increased expression of IL23R might then lead to an exaggerated immune response. The independent genetic signals identified for psoriasis and PsA in this locus indicate that different mechanisms underlie these two conditions; although likely both affecting the function of IL23R. It is very important to further characterise these mechanisms in order to better understand how the IL-23 receptor and its downstream signalling is affected in both diseases. This will help to determine how psoriasis and PsA patients might differentially respond to therapies, particularly IL-23 biologics. To investigate this further we have developed an in vitro model using CD4 T cells which express either wild type IL23R and IL12Rβ1 or mutant IL23R (R381Q) and IL12Rβ1. Model expressing different isotypes of IL23R is also underway to investigate the effects on IL23R expression. We propose to further investigate the variants for Ps and PsA and characterise key intracellular processes related to the variants.

Keywords: IL23R, psoriasis, psoriatic arthritis, SNP

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Authors: Abiodun Olayinka, Daniel Dzidzienyo, Pangirayi Tongoona, Samuel Offei, Edwige Gaby Nkouaya Mbanjo, Chiedozie Egesi, Ismail Yusuf Rabbi

Abstract:

Cassava (Manihot esculenta Crantz) is a major source of starch for various industrial applications. However, the traditional cultivation and harvesting methods of cassava are labour-intensive and inefficient, limiting the supply of fresh cassava roots for industrial starch production. To achieve improved productivity and quality of fresh cassava roots through mechanized cultivation, cassava cultivars with compact plant architecture and moderate plant height are needed. Plant architecture-related traits, such as plant height, harvest index, stem diameter, branching angle, and lodging tolerance, are critical for crop productivity and suitability for mechanized cultivation. However, the genetics of cassava plant architecture remain poorly understood. This study aimed to identify the genetic bases of the relationships between plant architecture traits and productivity-related traits, particularly starch content. A panel of 453 clones developed at the International Institute of Tropical Agriculture, Nigeria, was genotyped and phenotyped for 18 plant architecture and productivity-related traits at four locations in Nigeria. A genome-wide association study (GWAS) was conducted using the phenotypic data from a panel of 453 clones and 61,238 high-quality Diversity Arrays Technology sequencing (DArTseq) derived Single Nucleotide Polymorphism (SNP) markers that are evenly distributed across the cassava genome. Five significant associations between ten SNPs and three plant architecture component traits were identified through GWAS. We found five SNPs on chromosomes 6 and 16 that were significantly associated with shoot weight, harvest index, and total yield through genome-wide association mapping. We also discovered an essential candidate gene that is co-located with peak SNPs linked to these traits in M. esculenta. A review of the cassava reference genome v7.1 revealed that the SNP on chromosome 6 is in proximity to Manes.06G101600.1, a gene that regulates endodermal differentiation and root development in plants. The findings of this study provide insights into the genetic basis of plant architecture and yield in cassava. Cassava breeders could leverage this knowledge to optimize plant architecture and yield in cassava through marker-assisted selection and targeted manipulation of the candidate gene.

Keywords: manihot esculenta crantz, plant architecture, dartseq, snp markers, genome-wide association study

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Authors: M. H. Abedi, A. Jalilvand

Abstract:

The economic development benefits of wind energy may be the most tangible basis for the local and state officials’ interests. In addition to the direct salaries associated with building and operating wind projects, the wind energy industry provides indirect jobs and benefits. The optimal planning of a wind farm is one most important topic in renewable energy technology. Many methods have been implemented to optimize the cost and output benefit of wind farms, but the contribution of this paper is mentioning different types of service providers and also time of installation of wind turbines during planning horizon years. Genetic algorithm (GA) is used to optimize the problem. It is observed that an appropriate layout of wind farm can cause to minimize the different types of cost.

Keywords: renewable energy, wind farm, optimization, planning

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Authors: Rohit Mittal, Bright Keswani, Amit Mithal

Abstract:

This paper provides a sense about the application of computational intelligence techniques used to develop computer games, especially car racing. For the deep sense and knowledge of artificial intelligence, this paper is divided into various sections that is optimization, imitation, innovation and combining approach of optimization and imitation. This paper is mainly concerned with combining approach which tells different aspects of using fitness measures and supervised learning techniques used to imitate aspects of behavior. The main achievement of this paper is based on modelling player behaviour and evolving new game content such as racing tracks as single car racing on single track.

Keywords: evolution algorithm, genetic, optimization, imitation, racing, innovation, gaming

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Authors: Masoumeh Mofarrah, Amir NahanMoghadam

Abstract:

Higher oil prices and increasing oil demand are main reasons for great attention to Enhanced Oil Recovery (EOR). Comprehensive researches have been accomplished to develop, appraise, and improve EOR methods and their application. Recently, Artificial Intelligence (AI) gained popularity in petroleum industry that can help petroleum engineers to solve some fundamental petroleum engineering problems such as reservoir simulation, EOR project risk analysis, well log interpretation and well test model selection. This study presents a historical overview of most popular AI tools including neural networks, genetic algorithms, fuzzy logic, and expert systems in petroleum industry and discusses two case studies to represent the application of two mentioned AI methods for selecting an appropriate EOR method based on reservoir characterization infeasible and effective way.

Keywords: artificial intelligence, EOR, neural networks, expert systems

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Authors: Silvia Portarena, Chiara Anselmi, Chiara Baldacchini, Enrico Brugnoli

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Extra virgin olive oil (EVOO) is a complex matrix mainly composed by fatty acid and other minor compounds, among which carotenoids are well known for their antioxidative function that is a key mechanism of protection against cancer, cardiovascular diseases, and macular degeneration in humans. EVOO composition in terms of such constituents is generally the result of a complex combination of genetic, agronomical and environmental factors. To selectively improve the quality of EVOOs, the role of each factor on its biochemical composition need to be investigated. By selecting fruits from four different cultivars similarly grown and harvested, it was demonstrated that Raman spectroscopy, combined with chemometric analysis, is able to discriminate the different cultivars, also as a function of the harvest date, based on the relative content and composition of fatty acid and carotenoids. In particular, a correct classification up to 94.4% of samples, according to the cultivar and the maturation stage, was obtained. Moreover, by using gas chromatography and high-performance liquid chromatography as reference techniques, the Raman spectral features further allowed to build models, based on partial least squares regression, that were able to predict the relative amount of the main fatty acids and the main carotenoids in EVOO, with high coefficients of determination. Besides genetic factors, climatic parameters, such as light exposition, distance from the sea, temperature, and amount of precipitations could have a strong influence on EVOO composition of both major and minor compounds. This suggests that the Raman spectra could act as a specific fingerprint for the geographical discrimination and authentication of EVOO. To understand the influence of environment on EVOO Raman spectra, samples from seven regions along the Italian coasts were selected and analyzed. In particular, it was used a dual approach combining Raman spectroscopy and isotope ratio mass spectrometry (IRMS) with principal component and linear discriminant analysis. A correct classification of 82% EVOO based on their regional geographical origin was obtained. Raman spectra were obtained by Super Labram spectrometer equipped with an Argon laser (514.5 nm wavelenght). Analyses of stable isotope content ratio were performed using an isotope ratio mass spectrometer connected to an elemental analyzer and to a pyrolysis system. These studies demonstrate that RR spectroscopy is a valuable and useful technique for the analysis of EVOO. In combination with statistical analysis, it makes possible the assessment of specific samples’ content and allows for classifying oils according to their geographical and varietal origin.

Keywords: authentication, chemometrics, olive oil, raman spectroscopy

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Authors: Masoumeh Ali Pouri, Hamid Haj Seyyed Javadi

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Nowadays, cloud processing is one of the important issues in information technology. Since scheduling of tasks graph is an NP-hard problem, considering approaches based on undeterminisitic methods such as evolutionary processing, mostly genetic and cuckoo algorithms, will be effective. Therefore, an efficient algorithm has been proposed for scheduling of tasks graph to obtain an appropriate scheduling with minimum time. In this algorithm, the new approach is based on making the length of the critical path shorter and reducing the cost of communication. Finally, the results obtained from the implementation of the presented method show that this algorithm acts the same as other algorithms when it faces graphs without communication cost. It performs quicker and better than some algorithms like DSC and MCP algorithms when it faces the graphs involving communication cost.

Keywords: cloud computing, scheduling, tasks graph, chakoos algorithm

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Authors: Vipan Kumar Sohpal, Rajesh K Sharma

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Diminishing of conventional fuels and hysterical vehicles emission leads to deterioration of the environment, which emphasize the research to work on biofuels. Biofuels from different sources attract the attention of research due to low emission and biodegradability. Emission of carbon monoxide, carbon dioxide and H-C reduced drastically using Biofuels (B-20) combustion. Contrary to the conventional fuel, engine emission results indicated that nitrous oxide emission is higher in Biofuels. So this paper examines and compares the nitrogen oxide emission of Jatropha Curcus (JCO) B-20% blends with the vegetable oil. In addition to that computational analysis of crude non edible oil performed to assess the impact of composition on emission quality. In conclusion, JCO have the potential feedstock for the biodiesel production after the genetic modification in the plant.

Keywords: jatropha curcus, computational analysis, emissions, NOx biofuels

Procedia PDF Downloads 562

Authors: Ajay B. C., Meena H. N., Dagla M. C., Narendra Kumar, Makwana A. D., Bera S. K., Kalariya K. A., Singh A. L.

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The high-energy value, protein content and minerals makes peanut a rich source of nutrition at comparatively low cost. Basic information on genetics and inheritance of these mineral elements is very scarce. Hence, in the present study inheritance (using additive-dominance model) and association of mineral elements was studied in two peanut crosses. Dominance variance (H) played an important role in the inheritance of P, K, Fe and Zn in peanut pods. Average degree of dominance for most of the traits was greater than unity indicating over dominance for these traits. Significant associations were also observed among mineral elements both in F2 and F3 generations but pod yield had no associations with mineral elements (with few exceptions). Di-allele/bi-parental mating could be followed to identify high yielding and mineral dense segregates.

Keywords: correlation, dominance variance, mineral elements, peanut

Procedia PDF Downloads 398

Authors: Masoumeh Mofarrah, Amir NahanMoghadam

Abstract:

Higher oil prices and increasing oil demand are main reasons for great attention to Enhanced Oil Recovery (EOR). Comprehensive researches have been accomplished to develop, appraise and improve EOR methods and their application. Recently Artificial Intelligence (AI) gained popularity in petroleum industry that can help petroleum engineers to solve some fundamental petroleum engineering problems such as reservoir simulation, EOR project risk analysis, well log interpretation and well test model selection. This study presents a historical overview of most popular AI tools including neural networks, genetic algorithms, fuzzy logic and expert systems in petroleum industry and discusses two case studies to represent the application of two mentioned AI methods for selecting an appropriate EOR method based on reservoir characterization in feasible and effective way.

Keywords: artificial intelligence, EOR, neural networks, expert systems

Procedia PDF Downloads 388

Authors: Sadaf Salek

Abstract:

Introduction: Cats are susceptible to various health conditions, and one such ailment that can affect their oral health is epulis in their lips. Epulis refers to a benign tumor or growth that can develop in different areas of a cat's mouth, including the lips. While epulis is not life-threatening, it can still cause discomfort and affect a cat's overall quality of life. This essay aims to delve into the causes, symptoms, and treatment options for epulis in cat's lips, shedding light on this lesser-known oral condition. Causes: Epulis in a cat's lips can have several causes. Firstly, genetic predisposition plays a significant role, with certain breeds being more prone to developing these growths. Secondly, chronic irritation to the mouth, such as from dental diseases or foreign objects, can also contribute to the development of epulis. Lastly, hormonal imbalances, specifically an excess of estrogen, have been associated with the occurrence of these tumors in cats. Understanding these causes can help cat owners take preventive measures to reduce the risk of epulis in their feline companions. Symptoms: Identifying the symptoms of epulis in a cat's lips is vital for early intervention and effective treatment. The most common symptoms include swelling, redness, and the presence of a visible growth or lump on the lip. Cats with epulis may also exhibit drooling, difficulty eating, and a reluctance to groom themselves. Any change in eating habits or oral behavior should not be overlooked and prompt a visit to the veterinarian for a thorough examination. Treatment ptions: When it comes to treating epulis in a cat's lips, various options are available, depending on the size, location, and characteristics of the growth. The primary treatment involves surgical removal of the tumor. This procedure should be performed by a qualified veterinarian, ensuring complete excision of the mass while preserving as much healthy tissue as possible. In some cases, radiation therapy may be necessary, especially if the tumor is large or aggressive. Additionally, a veterinarian may recommend oral hygiene care and regular dental cleaning to prevent further growths and maintain the cat's oral health. Prevention and Care: Preventing epulis in a cat's lips is not always possible, especially if genetic factors are involved. However, certain preventive measures can minimize the risk of these growths. Maintaining good oral hygiene through regular brushing and the use of appropriate dental products can help prevent chronic irritation and dental diseases. Routine veterinary check-ups should also include thorough oral examinations to detect any abnormal growths or changes in the mouth at an early stage. Pet owners should be observant and seek veterinary care promptly for any signs of discomfort or changes in eating habits. Conclusion: Epulis in a cat's lips is a condition that requires attention and proper treatment. Understanding the causes, identifying symptoms, and exploring treatment options are of utmost importance to help improve a cat's oral health and overall well-being.

Keywords: fibroma, cat, lip, epulis

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Authors: Beata Lachtara, Renata Szewczyk, Katarzyna Bielinska, Kinga Wieczorek, Jacek Osek

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Listeria monocytogenes is an important human and animal pathogen that causes foodborne outbreaks. The bacteria may be present in different types of food: cheese, raw vegetables, sliced meat products and vacuum-packed sausages, poultry, meat, fish. The most common method, which has been used for the investigation of genetic diversity of L. monocytogenes, is PFGE. This technique is reliable and reproducible and established as gold standard for typing of L. monocytogenes. The aim of the study was characterization by molecular serotyping and PFGE analysis of L. monocytogenes strains isolated from fresh fish and fish products in Poland. A total of 301 samples, including fresh fish (n = 129) and fish products (n = 172) were, collected between January 2014 and March 2016. The bacteria were detected using the ISO 11290-1 standard method. Molecular serotyping was performed with PCR. The isolates were tested with the PFGE method according to the protocol developed by the European Union Reference Laboratory for L. monocytogenes with some modifications. Based on the PFGE profiles, two dendrograms were generated for strains digested separately with two restriction enzymes: AscI and ApaI. Analysis of the fingerprint profiles was performed using Bionumerics software version 6.6 (Applied Maths, Belgium). The 95% of similarity was applied to differentiate the PFGE pulsotypes. The study revealed that 57 of 301 (18.9%) samples were positive for L. monocytogenes. The bacteria were identified in 29 (50.9%) ready-to-eat fish products and in 28 (49.1%) fresh fish. It was found that 40 (70.2%) strains were of serotype 1/2a, 14 (24.6%) 1/2b, two (4.3%) 4b and one (1.8%) 1/2c. Serotypes 1/2a, 1/2b, and 4b were presented with the same frequency in both categories of food, whereas serotype 1/2c was detected only in fresh fish. The PFGE analysis with AscI demonstrated 43 different pulsotypes; among them 33 (76.7%) were represented by only one strain. The remaining 10 profiles contained more than one isolate. Among them 8 pulsotypes comprised of two L. monocytogenes isolates, one profile of three isolates and one restriction type of 5 strains. In case of ApaI typing, the PFGE analysis showed 27 different pulsotypes including 17 (63.0%) types represented by only one strain. Ten (37.0%) clusters contained more than one strain among which four profiles covered two strains; three had three isolates, one with five strains, one with eight strains and one with ten isolates. It was observed that the isolates assigned to the same PFGE type were usually of the same serotype (1/2a or 1/2b). The majority of the clusters had strains of both sources (fresh fish and fish products) isolated at different time. Most of the strains grouped in one cluster of the AscI restriction was assigned to the same groups in ApaI investigation. In conclusion, PFGE used in the study showed a high genetic diversity among L. monocytogenes. The strains were grouped into varied clonal clusters, which may suggest different sources of contamination. The results demonstrated that 1/2a serotype was the most common among isolates from fresh fish and fish products in Poland.

Keywords: Listeria monocytogenes, molecular characteristic, PFGE, serotyping

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Authors: P. Shrivastava, A. Shukla, K. Verma, S. Rungta

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Parkinson's disease is a chronic neurological disorder that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and tremors. Gait serve as a primary outcome measure for studies aiming at early recognition of disease. Using gait techniques, this paper implements efficient binary bat algorithm for an early detection of Parkinson's disease by selecting optimal features required for classification of affected patients from others. The data of 166 people, both fit and affected is collected and optimal feature selection is done using PSO and Bat algorithm. The reduced dataset is then classified using neural network. The experiments indicate that binary bat algorithm outperforms traditional PSO and genetic algorithm and gives a fairly good recognition rate even with the reduced dataset.

Keywords: parkinson, gait, feature selection, bat algorithm

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Authors: Ojiegbe Ikenna Nathan

Abstract:

Obesity is a medical condition in which excess body fat has accumulated to the extent that it leads to reduced life expectancy and or increased health problems. Obesity as a worldwide problem is seen clustered in the families and it moves from generation to generation. It causes some disabilities, mortality and morbidity if left unattended to. The predisposing factors to obesity are either genetic or environment in origin. Nevertheless, the main predisposing factor to obesity is the excessive consumption of food rich in low-density lipoprotein (LDL) such as organ meats, saturated fats etc. This low-density lipoprotein causes an increase in adipose tissue and complicates to obesity. There are varieties of obesity which one needs to take appropriate measures to avoid; such as android, gynoid and morbid obesity. Nonetheless, studies have shown that there is hope for the obese individuals, despite the cause, type and degree of their obesity. This is through the use of the different available treatment measures which increase in physical activities, caloric restrictions, drug therapy and surgical intervention.

Keywords: low-density, lipoprotein, culprit, obesity

Procedia PDF Downloads 383