Search results for: genetic variations

Authors: Amar Khoukhi, Mohamed Shahab

Abstract:

This paper presents the optimal control problem of mobile robot motion as a nonlinear programming problem (NLP) and solved using a direct method of numerical optimal control. The NLP is initialized with a B-Spline for which node locations are optimized using a genetic search. The system acceleration inputs and sampling periods are considered as optimization variables. Different scenarios with different objectives weights are implemented and investigated. Interesting results are found in terms of complying with the expected behavior of a mobile robot system and time-energy minimization.

Keywords: multi-objective control, non-holonomic systems, mobile robots, nonlinear programming, motion planning, B-spline, genetic algorithm

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Authors: Wafa Al Jabri

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Background: In Middle Eastern Islamic Countries (MEICs), there is a high prevalence of genetic blood disorders (GBDs), particularly sickle cell disease and thalassemia. The GBDs are considered a major public health concern, especially with the increase in affected populations along with the associated psychological, social, and financial cost of management. Despite the availability of premarital screening services (PSS) that aim to identify the asymptomatic carriers of GBDs and provide genetic counseling to couples in order toreduce the prevalence of these diseases; yet, the success rate of PSS is very low due to religious and socio-cultural concerns. Purpose: This paper aims to highlight the factors that affect the success of PSS in MEICs. Methods: A literature review of articles located in CINAHL, PubMed, SCOPUS, and MedLinewas carried out using the following terms: “premarital screening,” “success,” “effectiveness,” and “ genetic blood disorders.” Second, a hand search of the reference lists and Google searches were conducted to find studies that did not exist in the primary database searches. Only studies which are conducted in MEICs countries and published in the last five years were included. Studies that were not published in English were excluded. Results: Fourteen articles were included in the review. The results showed that PSS in most of the MEICs was successful in achieving its objective of identifying high-risk marriages; however, the service failed to meetitsultimate goal of reducing the prevalence of GBDs. Various factors seem to hinder the success of PSS, including poor public awareness, late timing of the screening, culture and social stigma, religious beliefs, availability of prenatal diagnosis and therapeutic abortion, emotional factors, and availability of genetic counseling services. However, poor public awareness, late timing of the screening, and unavailability of adequate counseling services were the most common barriers identified. Conclusion: Overcoming the identified barriers by providing effective health education programs, offering the screening test to young adults at an earlier stage, and tailoring the genetic counseling would be crucial steps to provide a framework for an effective PSS in MEICs.

Keywords: premarital screening, success, effectiveness, and genetic blood disorders

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Authors: Sammy Kibor, Filip Huyghe, Marc Kochzius, James Kairo

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Goldstripe Sardinella, Sardinella gibbosa, (Bleeker, 1849) is a commercially and ecologically important small pelagic fish common in the Western Indian Ocean region. The present study aimed to assess genetic diversity and population structure of the species in the Kenya-Tanzania transboundary area using mtDNA and msDNA markers. Some 630 bp sequence in the mitochondrial DNA (mtDNA) Cytochrome C Oxidase I (COI) and five polymorphic microsatellite DNA loci were analyzed. Fin clips of 309 individuals from eight locations within the transboundary area were collected between July and December 2018. The S. gibbosa individuals from the different locations were distinguishable from one another based on the mtDNA variation, as demonstrated with a neighbor-joining tree and minimum spanning network analysis. None of the identified 22 haplotypes were shared between Kenya and Tanzania. Gene diversity per locus was relatively high (0.271-0.751), highest Fis was 0.391. The structure analysis, discriminant analysis of Principal component (DAPC) and the pair-wise (FST = 0.136 P < 0.001) values after Bonferroni correction using five microsatellite loci provided clear inference on genetic differentiation and thus evidence of population structure of S. gibbosa along the Kenya-Tanzania coast. This study shows a high level of genetic diversity and the presence of population structure (Φst =0.078 P < 0.001) resulting to the existence of four populations giving a clear indication of minimum gene flow among the population. This information has application in the designing of marine protected areas, an important tool for marine conservation.

Keywords: marine connectivity, microsatellites, population genetics, transboundary

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Authors: Agostinho Antunes

Abstract:

The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of varied species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: adaptation, animals, evolution, genomics

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Authors: Gordana Branković, Dejan Dodig, Vesna Pajić, Vesna Kandić, Desimir Knežević, Nenad Đurić

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The wheat grain quality properties are influenced by genotype, environmental conditions and genotype × environment interaction (GEI). The increasing request of more nutritious wheat products will direct future breeding programmes. Therefore, the aim of investigation was to determine: i) variability of the protein content (PC), wet gluten content (WG) and Zeleny sedimentation volume (ZS); ii) components of variance, heritability in a broad sense (hb2), and expected genetic advance as percent of mean (GAM) for PC, WG, and ZS; iii) correlations between PC, WG, ZS, and most important agronomic traits; in order to assess expected breeding success versus environmental impact for these quality traits. The plant material consisted of 30 genotypes of bread wheat (Triticum aestivum L. ssp. aestivum) and durum wheat (Triticum durum Desf.). The trials were sown at the three test locations in Serbia: Rimski Šančevi, Zemun Polje and Padinska Skela during 2010-2011 and 2011-2012. The experiments were set as randomized complete block design with four replications. The plot consisted of five rows of 1 m2 (5 × 0.2 m × 1 m). PC, WG and ZS were determined by the use of Near infrared spectrometry (NIRS) with the Infraneo analyser (Chopin Technologies, France). PC, WG and ZS, in bread wheat, were in the range 13.4-16.4%, 22.8-30.3%, and 39.4-67.1 mL, respectively, and in durum wheat, in the range 15.3-18.1%, 28.9-36.3%, 37.4-48.3 mL, respectively. The dominant component of variance for PC, WG, and ZS, in bread wheat, was genotype with the genetic variance/GEI variance (VG/VG × E) relation of 3.2, 2.9 and 1.0, respectively, and in durum wheat was GEI with the VG/VG × E relation of 0.70, 0.69 and 0.49, respectively. hb2 and GAM values for PC, WG and ZS, in bread wheat, were 94.9% and 12.6%, 93.7% and 18.4%, and 86.2% and 28.1%, respectively, and in durum wheat, 80.7% and 7.6%, 79.7% and 10.2%, and 74% and 11.2%, respectively. The most consistent through six environments, statistically significant correlations, for bread wheat, were between PC and spike length (-0.312 to -0.637); PC, WG, ZS and grain number per spike (-0.320 to -0.620; -0.369 to -0.567; -0.301 to -0.378, respectively); PC and grain thickness (0.338 to 0.566), and for durum wheat, were between PC, WG, ZS and yield (-0.290 to -0.690; -0.433 to -0.753; -0.297 to -0.660, respectively); PC and plant height (-0.314 to -0.521); PC, WG and spike length (-0.298 to -0.597; -0.293 to -0.627, respectively); PC, WG and grain thickness (0.260 to 0.575; 0.269 to 0.498, respectively); PC, WG and grain vitreousness (0.278 to 0.665; 0.357 to 0.690, respectively). Breeding success can be anticipated for ZS in bread wheat due to coupled high values for hb2 and GAM, suggesting existence of additive genetic effects, and also for WG in bread wheat, due to very high hb2 and medium high GAM. The small, and medium, negative correlations between PC, WG, ZS, and yield or yield components, indicate difficulties to select simultaneously for high quality and yield, depending on linkage for particular genetic arrangements to be broken by recombination.

Keywords: bread and durum wheat, genetic advance, protein and wet gluten content, Zeleny sedimentation volume

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Authors: Minjung Kim, Hyunkoo Kang, Jinkoo Kim

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In this study, a seismic retrofit scheme for a reinforced concrete shear wall structure using steel slit dampers was presented. The stiffness and the strength of the slit damper used in the retrofit were verified by cyclic loading test. A genetic algorithm was applied to find out the optimum location of the slit dampers. The effects of the slit dampers on the seismic retrofit of the model were compared with those of jacketing shear walls. The seismic performance of the model structure with optimally positioned slit dampers was evaluated by nonlinear static and dynamic analyses. Based on the analysis results, the simple procedure for determining required damping ratio using capacity spectrum method along with the damper distribution pattern proportional to the inter-story drifts was validated. The analysis results showed that the seismic retrofit of the model structure using the slit dampers was more economical than the jacketing of the shear walls and that the capacity spectrum method combined with the simple damper distribution pattern led to satisfactory damper distribution pattern compatible with the solution obtained from the genetic algorithm.

Keywords: seismic retrofit, slit dampers, genetic algorithm, jacketing, capacity spectrum method

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Authors: Alireza Lavaei, Alireza Lohrasbi, Mohammadali M. Shahlaei

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To reduce the overall time of structural optimization for earthquake loads two strategies are adopted. In the first strategy, a neural system consisting self-organizing map and radial basis function neural networks, is utilized to predict the time history responses. In this case, the input space is classified by employing a self-organizing map neural network. Then a distinct RBF neural network is trained in each class. In the second strategy, an improved genetic algorithm is employed to find the optimum design. A 72-bar space truss is designed for optimal weight using exact and approximate analysis for the El Centro (S-E 1940) earthquake loading. The numerical results demonstrate the computational advantages and effectiveness of the proposed method.

Keywords: optimization, genetic algorithm, neural networks, self-organizing map

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Authors: Saul A. Torres Z., Eduardo Liceaga C., Alfredo Arias M.

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We seek to develop a UAV for agricultural spraying at a maximum altitude of 5000 meters above sea level, with a payload of 100 liters of fumigant. For the developing the aerodynamic design of the aircraft is using computational tools such as the "Vortex Lattice Athena" software, "MATLAB", "ANSYS FLUENT", "XFoil" package among others. Also methods are being used structured programming, exhaustive analysis of optimization methods and search. The results have a very low margin of error, and the multi-objective problems can be helpful for future developments. Also we developed method for Stability Analysis (Lateral-Directional and Longitudinal).

Keywords: aerodynamics design, optimization, algorithm genetic, multi-objective problem, longitudinal stability, lateral-directional stability

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Authors: Mohamed Amine Ben Abdallah, Imed Khemili, Nizar Aifaoui

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This work denotes an insight into dynamic synthesis of multibody systems. A set of mechanism parameters design variable are synthetized based on a desired mechanism response, such as, velocity, acceleration and bodies deformations. Moreover, knowing the work space, for a robot, and mechanism response allow defining optimal parameters mechanism handling with the desired target response. To this end, evolutionary genetic algorithm has been deployed. A demonstrative example for imperfect mechanism has been treated, mainly, a slider crank mechanism with a flexible connecting rod. The transversal deflection of the connecting rod has been chosen as response to identify the mechanism design parameters.

Keywords: dynamic response, evolutionary genetic algorithm, flexible bodies, optimization

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Authors: Yasir Ali, Farhatullah

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The present study was conducted to estimate the genetic variability, heritability and genetic advance in six parental lines and their 56 genotypes derived from five introgressed brassica populations on the basis of morphological and biochemical traits. The experiment was laid out in a randomized complete block design with two replications at The University of Agriculture Peshawar-Pakistan during growing season of 2015-2016. The ANOVA of all traits of F5:6 populations showed highly significant differences (P ≤ 0.01) for all morphological and biochemical traits. Among F5:6 populations, the genotype 2(526) was earlier in flowering (108.65 days), and genotype 14(485) was earlier in maturity (170 days). Tallest plants (182.5 cm), largest main raceme (91.5 cm) and maximum number of pods (80.5) on main raceme were recorded for genotype 17(34). Maximum primary branches plant-1(6.2) and longest pods (10.26 cm) were recorded for genotype 15, while genotype 16(171) had more seeds pod⁻¹ (22) and gave maximum yield plant-1 (30.22 g). The maximum 100-seed weight (0.60 g) was observed for genotype 10(506) while high protein content (22.61%) was recorded for genotype 4(99). Maximum oil content (54.08 %) and low linoleic acid (7.07 %) were produced by genotype (12(138) and low glucosinolate (59.01 µMg⁻¹) was recorded for genotype 21(113). The genotype 27(303) having high oleic acid content (51.73 %) and genotype 1(209) gave low erucic acid (35.97 %). Among the F5:6 populations moderate to high heritability observed for all morphological and biochemical traits coupled with high genetic advance. Cluster analysis grouped the 56 F5:6 populations along their parental lines into seven different groups. Each group was different from the other group on the basis of morphological and biochemical traits. Moreover all the F5:6 populations showed sufficient variability. Genotypes 10(506) and 16(171) were superior for high seed yield⁻¹, 100-seeds weight, and seed pod⁻¹ and are recommended for future breeding program.

Keywords: Brassicaceae, biochemical characterization, introgression, morphological characterization

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Authors: Atilla Bayram

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This paper presents the trajectory tracking control of a spatial redundant hybrid manipulator. This manipulator consists of two parallel manipulators which are a variable geometry truss (VGT) module. In fact, each VGT module with 3-degress of freedom (DOF) is a planar parallel manipulator and their operational planes of these VGT modules are arranged to be orthogonal to each other. Also, the manipulator contains a twist motion part attached to the top of the second VGT module to supply the missing orientation of the endeffector. These three modules constitute totally 7-DOF hybrid (parallel-parallel) redundant spatial manipulator. The forward kinematics equations of this manipulator are obtained, then, according to these equations, the inverse kinematics is solved based on an optimization with the joint limit avoidance. The dynamic equations are formed by using virtual work method. In order to test the performance of the redundant manipulator and the controllers presented, two different desired trajectories are followed by using the computed force control method and a switching control method. The switching control method is combined with the computed force control method and genetic algorithm. In the switching control method, the genetic algorithm is only used for fine tuning in the compensation of the trajectory tracking errors.

Keywords: computed force method, genetic algorithm, hybrid manipulator, inverse kinematics of redundant manipulators, variable geometry truss

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Authors: Ramona Moldovan, Doina Cosman, Sebastian Moldovan, Radu Popp, Victor Pop

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MENTALICA is a project aimed at developing and evaluating a platform that can assist individuals diagnosed with severe mental disorders and their families in managing the consequences associated with severe mental disorders, recurrence risks, prevention strategies and treatment options. MENTALICA is a platform based on guidance issued by some of the most prominent scientific organizations in the world. In order to personalize the information provided, the program explores details about the personal and family history of mental disorders. MENTALICA summarizes the answers and gives respondents a personal assessment. This includes personalized information and support about schizophrenia, bipolar disorder and schizoaffective disorder. MENTALICA includes several modules: Family history tools, Risk assessment tools and Risk factor sheets, Practical guides for patients, Practical guides for families, Guidelines for clinicians. Currently, there are no available guidelines for genetic counselling for mental disorders. Respondents can print out their reports and discuss them with family members or their doctors. We will briefly present the current status of MENTALICA and its implications for patients, professionals and the community.

Keywords: genetic counseling, mental disorders, platform

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Authors: H. Naseh, M. Mirshams, M. Mirdamadian, H. R. Fazeley

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This paper presents an extension of fuzzy-genetic algorithm multi-objective optimization methodology that could effectively be used to find the overall satisfaction of objective functions (selecting the design variables) in the early stages of design process. The coupling of objective functions due to design variables in an engineering design process will result in difficulties in design optimization problems. In many cases, decision making on design variables conflicts with more than one discipline in system design. In space launch system conceptual design, decision making on some design variable (e.g. oxidizer to fuel mass flow rate O/F) in early stages of the design process is related to objective of liquid propellant engine (specific impulse) and Tanks (structure weight). Then, the primary application of this methodology is the design of a liquid propellant engine with the maximum specific impulse and cylindrical stiffened tank with the minimum weight. To this end, the design problem is established the fuzzy rule set based on designer's expert knowledge with a holistic approach. The independent design variables in this model are oxidizer to fuel mass flow rate, thickness of stringers, thickness of rings, shell thickness. To handle the mentioned problems, a fuzzy-genetic algorithm multi-objective optimization methodology is developed based on Pareto optimal set. Consequently, this methodology is modeled with the one stage of space launch system to illustrate accuracy and efficiency of proposed methodology.

Keywords: cylindrical stiffened tanks, multi-objective, genetic algorithm, fuzzy approach

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Authors: Santosh Kumar Suman, Vinod Kumar Giri

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The goal of this paper is to outline a speed controller of a DC motor by choice of a PID parameters utilizing genetic algorithms (GAs), the DC motor is extensively utilized as a part of numerous applications such as steel plants, electric trains, cranes and a great deal more. DC motor could be represented by a nonlinear model when nonlinearities such as attractive dissemination are considered. To provide effective control, nonlinearities and uncertainties in the model must be taken into account in the control design. The DC motor is considered as third order system. Objective of this paper three type of tuning techniques for PID parameter. In this paper, an independently energized DC motor utilizing MATLAB displaying, has been outlined whose velocity might be examined utilizing the Proportional, Integral, Derivative (KP, KI , KD) addition of the PID controller. Since, established controllers PID are neglecting to control the drive when weight parameters be likewise changed. The principle point of this paper is to dissect the execution of optimization techniques viz. The Genetic Algorithm (GA) for improve PID controllers parameters for velocity control of DC motor and list their points of interest over the traditional tuning strategies. The outcomes got from GA calculations were contrasted and that got from traditional technique. It was found that the optimization techniques beat customary tuning practices of ordinary PID controllers.

Keywords: DC motor, PID controller, optimization techniques, genetic algorithm (GA), objective function, IAE

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Authors: Agostinho Antunes

Abstract:

The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of selected marine animal species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: comparative genomics, adaptive evolution, bioinformatics, phylogenetics, genome mining

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Authors: Michael Aupetit, Mahmoud Al-ismail, Khaled Mohamed

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Cancer is a major public health problem all over the world. Breast cancer has the highest incidence rate over all cancers for women in Qatar making its study a top priority of the country. Human cancer is a dynamic disease that develops over an extended period through the accumulation of a series of genetic alterations. A Darwinian process drives the tumor cells toward higher malignancy growing the branches of a progression tree in the space of genes expression. Although it is not possible to track these genetic alterations dynamically for one patient, it is possible to reconstruct the progression tree from the aggregation of thousands of tumor cells’ genetic profiles from thousands of different patients at different stages of the disease. Analyzing the progression tree is a way to detect pivotal molecular events that drive the malignant evolution and to provide a guide for the development of cancer diagnostics, prognostics and targeted therapeutics. In this work we present the development of a Visual Analytic web platform CanVis enabling users to upload gene-expression data and analyze their progression tree. The server computes the progression tree based on state-of-the-art techniques and allows an interactive visual exploration of this tree and the gene-expression data along its branching structure helping to discover potential driver genes.

Keywords: breast cancer, progression tree, visual analytics, web platform

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Authors: Chethan Purushothama

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Coronary artery disease is one of the major causes of death in developing countries. The coronary arteries show wide range of variations and these variations have not been dealt with different population groups. The present study aims to focus on the pattern and variations of coronary artery in south Indian population. The study was performed to analyze the coronary artery dominance and divisions of main trunk of left coronary artery in 81 isolated adult human cadaveric hearts of South Indian population. The specimens were fixed in 10% formalin and were dissected manually. In our specimens, 74.1% of the hearts were right dominant, 11.1% were left dominant, and 14.8% were co-dominant. Bifurcation, trifurcation, and quadrifurcation of main trunk of left coronary artery were seen in 49.4%, 48.1%, and 2.5% cases respectively. The right dominant hearts had bifurcation, trifurcation and quadrifurcation of main trunk of left coronary artery in 46.7%, 50% and 3.3% hearts respectively. The left dominant hearts had bifurcation and trifurcation of main trunk of left coronary artery in 55.6% and 44.4% cases respectively. The co-dominant hearts had bifurcation and trifurcation of main trunk of left coronary artery in 58.3% and 41.7% respectively. Quadrifurcation of main trunk of left coronary artery were seen only in right dominant hearts. We believe that the data obtained from the present study are important to the interventional cardiologists and radiologists. The details obtained will also be helpful for the clinical anatomists.

Keywords: bifurcation, coronary artery, trifurcation, quadrifurcation

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Authors: Aurelien Boutin

Abstract:

In optical systems such as Variable Optical Delay Lines, where a collimated beam has to go back and forth, corner cubes are used in order to keep the reflected beam parallel to the incoming beam. However, the reflected beam can be laterally shifted, which will lead to losses. In this paper, we report on a patented optical design that allows keeping the reflected beam with the exact same position and direction whatever the displacement of the corner cube leading to zero losses. After explaining how the optical design works and theoretically allows to compensate for any defects in the translation of the corner cube, we will present the results of experimental comparisons between a standard layout (i.e., only corner cubes) and our optical layout. To compare both optical layouts, we used a fiber-to-fiber coupling setup. It consists of a couple of lights from one fiber to the other, thanks to two lenses. The ensemble [fiber+lense] is fixed and called a collimator so that the light is coupled from one collimator to another. Each collimator was precisely made in order to have a precise working distance. In the experiment, we measured and compared the Insertion Losses (IL) variations between both collimators with the distance between them (i.e., natural Gaussian beam coupling losses) and between both collimators in the different optical layouts tested, with the same optical length propagation. We will show that the IL variations of our setup are less than 0.05dB with respect to the IL variations of collimators alone.

Keywords: free-space optics, variable optical delay lines, optical cavity, auto-alignment

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Authors: Hamed K. Esfahani, Bithin Datta

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Transport of reactive chemical contaminant species in groundwater aquifers is a complex and highly non-linear physical and geochemical process especially for real life scenarios. Simulating this transport process involves solving complex nonlinear equations and generally requires huge computational time for a given aquifer study area. Development of optimal remediation strategies in aquifers may require repeated solution of such complex numerical simulation models. To overcome this computational limitation and improve the computational feasibility of large number of repeated simulations, Genetic Programming based trained surrogate models are developed to approximately simulate such complex transport processes. Transport process of acid mine drainage, a hazardous pollutant is first simulated using a numerical simulated model: HYDROGEOCHEM 5.0 for a contaminated aquifer in a historic mine site. Simulation model solution results for an illustrative contaminated aquifer site is then approximated by training and testing a Genetic Programming (GP) based surrogate model. Performance evaluation of the ensemble GP models as surrogate models for the reactive species transport in groundwater demonstrates the feasibility of its use and the associated computational advantages. The results show the efficiency and feasibility of using ensemble GP surrogate models as approximate simulators of complex hydrogeologic and geochemical processes in a contaminated groundwater aquifer incorporating uncertainties in historic mine site.

Keywords: geochemical transport simulation, acid mine drainage, surrogate models, ensemble genetic programming, contaminated aquifers, mine sites

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Authors: K. Ebrahimi, S. Shahid, H. Dehban

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Climate variability can affect surface water quality. The objective of present study is to assess the impacts of climate variability on water quality of Gorganroud River, Iran, over the time period 1971 to 2011. To achieve this aim, climate variability and water quality variations were studied involving a newly developed drought index (MRDI) and hysteresis curves, respectively. The results show that climate variability significantly affected surface water quality over the time. The existence of yearly internal variation and hysteresis phenomenon for pH and EC parameters was observed. It was found that though drought affected pH considerably, it could not affect EC significantly.

Keywords: climate variability, hysteresis curves, multi drought index, water quality

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Authors: A. Mansouri, F. Krim

Abstract:

This paper presents two techniques for DC motor parameters identification. We propose a numerical method using the adaptive extensive recursive least squares (AERLS) algorithm for real time parameters estimation. This algorithm, based on minimization of quadratic criterion, is realized in simulation for parameters identification of DC motor autoregressive moving average with extra inputs (ARMAX). As advanced technique, we use genetic algorithms (GA) identification with biased estimation for high dynamic performance speed regulation. DC motors are extensively used in variable speed drives, for robot and solar panel trajectory control. GA effectiveness is derived through comparison of the two approaches.

Keywords: ARMAX model, DC motor, AERLS, GA, optimization, parameter identification, PID speed regulation

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Authors: Benjamin A. Ha, Marco Morselli, Xinhui Paige Zhang, Elizabeth A. C. Heath-Heckman, Jonathan B. Puritz, David K. Jacobs

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Next-generation sequencing has enhanced the ability to acquire massive amounts of sequence data to address classic population genetic questions for non-model organisms. Targeted approaches allow for cost effective or more precise analyses of relevant sequences; although, many such techniques require a known genome and it can be costly to purchase probes from a company. This is challenging for non-model organisms with no published genome and can be expensive for large population genetic studies. Expressed exome capture sequencing (EecSeq) synthesizes probes in the lab from expressed mRNA, which is used to capture and sequence the coding regions of genomic DNA from a pooled suite of samples. A normalization step produces probes to recover transcripts from a wide range of expression levels. This approach offers low cost recovery of a broad range of genes in the genome. This research project expands on EecSeq to investigate if mRNA from one taxon may be used to capture relevant sequences from a series of increasingly less closely related taxa. For this purpose, we propose to use the endangered Northern Tidewater goby, Eucyclogobius newberryi, a non-model organism that inhabits California coastal lagoons. mRNA will be extracted from E. newberryi to create probes and capture exomes from eight other taxa, including the more at-risk Southern Tidewater goby, E. kristinae, and more divergent species. Captured exomes will be sequenced, analyzed bioinformatically and phylogenetically, then compared to previously generated phylogenies across this group of gobies. This will provide an assessment of the utility of the technique in cross-species studies and for analyzing low genetic variation within species as is the case for E. kristinae. This method has potential applications to provide economical ways to expand population genetic and evolutionary biology studies for non-model organisms.

Keywords: coastal lagoons, endangered species, non-model organism, target capture method

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Authors: Atefeh Esmailnejad, Gholam Reza Nikbakht Brujeni

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The major histocompatibility complex (MHC) is the best-characterized genetic region associated with susceptibility and/or resistance to a wide range of infectious diseases, autoimmune diseases and immune responses to vaccines. It has been demonstrated that there is an association between the MHC and resistance to Marek disease, Newcastle disease, Rous sarcoma tumor, Avian leucosis, Fowl cholera, Salmonellosis and Pasteurellosis in chicken. The present study evaluated the MHC polymorphism and its association with antibody response to Newcastle (ND) vaccine in Iranian native chickens. The MHC polymorphism was investigated using LEI0258 microsatellite locus by PCR-based fragment analysis. LEI0258 microsatellite marker is a genetic indicator for MHC, which is located on microchromosome 16 and strongly associated with serologically defined MHC haplotypes. Antibody titer against ND vaccine was measured by Haemaglutination Inhibition (HI) assay. Statistical analysis was performed using SPSS software (version 21). Total of 13 LEI0258 microsatellite alleles were identified in 72 samples which indicated a high genetic diversity in the population. The association study revealed a significant influence of MHC alleles on immune responses to Newcastle vaccine. 311 and 313 bp alleles were significantly associated with elevated immune responses to Newcastle vaccine (p<0.05). These results would be applicable in designing and improving the populations under selective breeding.

Keywords: chicken, LEI0258, MHC, Newcastle vaccine

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Authors: Ananthakrishna L. R., Ramesh D., Kumar Wodeyar, Kotresh A. M., Gururaj P. M.

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Malnad Gidda is the indigenous recognized cattle breed of Shivamogga District of Karnataka state, India is known for its disease resistance to many of the infectious diseases. There are 25 LRR (Leucine Rich Repeats) identified in bovine (Bos indicus) TLR9. The amino acid sequence of LRR is deduced to nucleotide sequence in BLASTx bioinformatic online tools. LRR2 to LRR10 are involved in pathogen recognition and binding in human TLR9 which showed a higher degree of nucleotide variations with respect to disease resistance to various pathogens. Hence, primers were designed to amplify the flanking sequences of LRR2 to LRR10, to discover the nucleotide variations if any, in Malnad Gidda breed of Cattle which is associated with disease resistance. The DNA isolated from peripheral blood mononuclear cells of ten Malnad Gidda cattle. A desired and specific amplification product of 0.8 kb was obtained at an annealing temperature of 56.6ᵒC. All the PCR products were sequenced on both sides by gene-specific primers. The sequences were compared with TLR9 sequence of cross breed cattle obtained from NCBI data bank. The sequence analysis between Malnad Gidda and crossbreed cattle revealed no nucleotide variations in the region LRR2 to LRR9 which shows the conserved in pathogen binding domain (LRR) of TLR9.

Keywords: leucine rich repeats, Malnad Gidda, cross breed, TLR9

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Authors: Damian Gordon, Paul Doyle, Anna Becevel, Tina Baloh

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The goal of this research is to explore the evolution of the concept of “blended learning” over a twenty-year period, to see whether or not the conceptualization has remained consistent or if it has become either more specific or more general. To achieve this goal, the term “blended learning” (and variations) was searched for in various bibliographical repositories for each year 2003-2022 to locate a highly cited paper that is not behind a paywall, to locate unique definitions that would be freely available to all academics each year. Each of the twenty unique definitions is explored to identify how they categorize both the Classroom Component and the Computer Component of blended learning, as well as identify which discipline each definition originates from and which country it comes from to see if there are any significant geographical variations. Based on this analysis, trends that appear in the definitions are noted, as well as an overall interpretation of the notion of “Blended Learning.”

Keywords: blended learning, definitions of blended learning, e-learning, thematic searches

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Authors: Abdolrasoul Daneshjoo

Abstract:

The purpose of this research was to study the effect of aerobic exercises with 75% heart beats on the amount of urea, uric acid and creatine in blood of Iranian soccer national U-23 players. 27 players were selected according to the following demographic specifications: age: 21.4±1.60 years old; weight: 68±9.4 kg; height: 174.2±8.6 cm. Urea, uric acid and creatine in blood are considered as dependent variations where as 40 minutes running on a track with maximum 75% heart beats are independent variations. Heart beat and blood pressure in rest time, age, height, and weight are considered as the controlled variations. Maximum heart beats are recorded under maximum exercises (8 minutes and 150-250 watt energy) on ergo meter. Then, in order to determine independent variations, 75% maximum heart beats are considered for each player. Blood is taken twice (before and after determining independence variation). Moreover, the players are given a few instructions to be fulfilled 24 hours before the main exercises. Laboratory analysis method for blood urea sample is deacetyl ammoniom, for uric acid Karvy test and for creatine pyric acid. 'T' formula is applied for analyzing statistical data in dependent groups with degree of freedom 7 (d.f=7) urea and uric acid contain P>0.01 and P>0.05 for creatine. 1. Aerobic exercise can effect on the concentration of urea of blood as well as uric acid and creatine in blood serum and increase the amount of them. 2. Urea of blood serum increases from 26.75±2.59 to 28.9±2.67 (25%) with 40 minutes running and 75% heart beat. 3. Aerobic exercise causes uric acid increase 12.5% from 5.7±0.52 (before exercise) to 6.1±0.71 (after exercise). Creatine of blood serum increases from 1.36±0.27 (before exercise) to 1.85±0.49 (after exercise). We came to this result that during aerobic exercise catabolism of protein substrate increases. Moreover, augmentation of urea, uric acid and creatine in blood serum as metabolic poisons causes disorder in kidney. Also, tendons and joints are affected by these poisons. Appropriate diet and exercise can prevent production of these poisons resulted from heavy exercise.

Keywords: aerobic exercise, urea, uric acid, creatine, blood, soccer national players

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Authors: Sukovatov K.Yu., Bezuglova N.N.

Abstract:

Winter precipitation variability over the Altai Krai was investigated by retrieving temporal patterns. The spectral singular analysis was used to describe the variance distribution and to reduce the precipitation data into a few components (modes). The associated time series were related to large-scale atmospheric and oceanic circulation indices by using lag cross-correlation and wavelet-coherence analysis. GPCC monthly precipitation data for rectangular field limited by 50-550N, 77-880E and monthly climatological circulation index data for the cold season were used to perform SSA decomposition and retrieve statistics for analyzed parameters on the time period 1951-2017. Interannual variability of winter precipitation over the Altai Krai are mostly caused by three natural factors: intensity variations of momentum exchange between mid and polar latitudes over the North Atlantic (explained variance 11.4%); wind speed variations in equatorial stratosphere (quasi-biennial oscillation, explained variance 15.3%); and surface temperature variations for equatorial Pacific sea (ENSO, explained variance 2.8%). It is concluded that under the current climate conditions (Arctic amplification and increasing frequency of meridional processes in mid-latitudes) the second and the third factors are giving more significant contribution into explained variance of interannual variability for cold season atmospheric precipitation over the Altai Krai than the first factor.

Keywords: interannual variability, winter precipitation, Altai Krai, wavelet-coherence

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Authors: Agostinho Antunes

Abstract:

The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of selected marine animal species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: marine genomics, evolutionary bioinformatics, human genome sequencing, genomic analyses

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Authors: Heiko Weiß, Andreas Meister, Christoph Ament, Nils Dreifke

Abstract:

Linear actuators are deployed in a wide range of applications. This paper presents the modeling and system identification of a variable excited linear direct drive (LDD). The LDD is designed based on linear hybrid stepper technology exhibiting the characteristic tooth structure of mover and stator. A three-phase topology provides the thrust force caused by alternating strengthening and weakening of the flux of the legs. To achieve best possible synchronous operation, the phases are commutated sinusoidal. Despite the fact that these LDDs provide high dynamics and drive forces, noise emission limits their operation in calm workspaces. To overcome this drawback an additional excitation of the magnetic circuit is introduced to LDD using additional enabling coils instead of permanent magnets. The new degree of freedom can be used to reduce force variations and related noise by varying the excitation flux that is usually generated by permanent magnets. Hence, an identified simulation model is necessary to analyze the effects of this modification. Especially the force variations must be modeled well in order to reduce them sufficiently. The model can be divided into three parts: the current dynamics, the mechanics and the force functions. These subsystems are described with differential equations or nonlinear analytic functions, respectively. Ordinary nonlinear differential equations are derived and transformed into state space representation. Experiments have been carried out on a test rig to identify the system parameters of the complete model. Static and dynamic simulation based optimizations are utilized for identification. The results are verified in time and frequency domain. Finally, the identified model provides a basis for later design of control strategies to reduce existing force variations.

Keywords: force variations, linear direct drive, modeling and system identification, variable excitation flux

Procedia PDF Downloads 353

Authors: Binder Hans

Abstract:

Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

Procedia PDF Downloads 125