Search results for: evolutionary genetics

Authors: Masoud Sheidaei, Mohammad-Reza Kordasti, Fahimeh Koohdar

Abstract:

Calotropis procera (Aiton) W.T.Aiton, (Apocynaceae), is an economically and medicinally important plant species which is an evergreen, perennial shrub growing in arid and semi-arid climates, and can tolerate very low annual rainfall (150 mm) and a dry season. The plant can also tolerate temperature ran off 20 to30°C and is not frost tolerant. This plant species prefers free-draining sandy soils but can grow also in alkaline and saline soils.It is found at a range of altitudes from exposed coastal sites to medium elevations up to 1300 m. Due to morpho-physiological adaptations of C. procera and its ability to tolerate various abiotic stresses. This taxa can compete with desirable pasture species and forms dense thickets that interfere with stock management, particularly mustering activities. Caloteropis procera grows only in southern part of Iran where in comprises a limited number of geographical populations. We used different population genetics and r landscape analysis to produce data on geographical populations of C. procera based on molecular genetic study using SCoT molecular markers. First, we used spatial principal components (sPCA), as it can analyze data in a reduced space and can be used for co-dominant markers as well as presence / absence data as is the case in SCoT molecular markers. This method also carries out Moran I and Mantel tests to reveal spatial autocorrelation and test for the occurrence of Isolation by distance (IBD). We also performed Random Forest analysis to identify the importance of spatial and geographical variables on genetic diversity. Moreover, we used both RDA (Redundency analysis), and LFMM (Latent factor mixed model), to identify the genetic loci significantly associated with geographical variables. A niche modellng analysis was carried our to predict present potential area for distribution of these plants and also the area present by the year 2050. The results obtained will be discussed in this paper.

Keywords: population genetics, landscape genetic, Calotreropis procera, niche modeling, SCoT markers

Procedia PDF Downloads 62

Authors: Luciana Salomon

Abstract:

The Andes hold one of the highest plant species diversity in the world. How such diversity originated is one of the most intriguing questions in studies addressing the pattern of plant diversity worldwide. Recently, the explosive adaptive radiations found in high Andean groups have been pointed as major triggers of this spectacular diversity. The Andes are one of the most species-rich area for the largest genus from the Asteraceae family, Senecio. There, the genus presents an incredible variation in growth form and ecological niche space. If this diversity of Andean Senecio can be explained by a monophyletic origin and subsequent radiation has not been tested up to now. Previous studies trying to disentangle the evolutionary history of some Andean Senecio struggled with the relatively low resolution and support of the phylogenies, which is indicative of recently radiated groups. Using Hyb-Seq, a powerful approach is available to address phylogenetic questions in groups whose evolutionary histories are recent and rapid. This approach was used for Senecio to build a phylogenetic backbone on which to study the mechanisms shaping its hyper-diversity in the Andes, focusing on Senecio ser. Culcitium, an exclusively Andean and well circumscribed group presenting large morphological variation and which is widely distributed across the Andes. Hyb-Seq data for about 130 accessions of Seneciowas generated. Using standard data analysis work flows and a newly developed tool to utilize paralogs for phylogenetic reconstruction, robustness of the species treewas investigated. Fully resolved and moderately supported species trees were obtained, showing Senecio ser. Culcitium as monophyletic. Within this group, some species formed well-supported clades congruent with morphology, while some species would not have exclusive ancestry, in concordance with previous studies showing a geographic differentiation. Additionally, paralogs were detected for a high number of loci, indicating duplication events and hybridization, known to be common in Senecio ser. Culcitium might have lead to hybrid speciation. The rapid diversification of the group seems to have followed a south-north distribution throughout the Andes, having accelerated in the conquest of new habitats more recently available: i.e., Montane forest, Paramo, and Superparamo.

Keywords: evolutionary radiations, andes, paralogy, hybridization, senecio

Procedia PDF Downloads 103

Authors: Farnaz Yusuf, Naseem A. Gaur

Abstract:

The increase in environmental concerns, rapid depletion of fossil fuel reserves and intense interest in achieving energy security has led to a global research effort towards developing renewable sources of fuels. Second generation biofuels have attracted more attention recently as the use of lignocellulosic biomass can reduce fossil fuel dependence and is environment-friendly. Xylose is the main pentose and second most abundant sugar after glucose in lignocelluloses. Saccharomyces cerevisiae does not readily uptake and use pentose sugars. For an economically feasible biofuel production, both hexose and pentose sugars must be fermented to ethanol. Therefore, it is important to develop S. cerevisiae host platforms with more efficient xylose utilization. This work aims to construct a xylose fermenting yeast strains with engineered oxido-reductative pathway for xylose metabolism. Engineered strain was further improved by adaptive evolutionary engineering approach. The engineered strain is able to grow on xylose as sole carbon source with the maximum ethanol yield of 0.39g/g xylose and productivity of 0.139g/l/h at 96 hours. The further improvement in strain development involves over expression of pentose phosphate pathway and protein engineering of xylose reductase/xylitol dehydrogenase to change their cofactor specificity in order to reduce xylitol accumulation.

Keywords: biofuel, lignocellulosic biomass, saccharomyces cerevisiae, xylose

Procedia PDF Downloads 184

Authors: Amir Bastani

Abstract:

The result of the research in the field of human behavioural genetics demonstrates a genetic contribution of behavioural differences in aggression, violence, drug and substance abuse, antisocial personality disorder and other related traits. As the field of human behavioural genetics progresses and achieves credibility, the criminal accused continue to use its types of evidence into the criminal law. One of the most important genetic factors which controls certain neurotransmitters like dopamine and serotonin is the Monoamine Oxidase Acid A (MAOA) gene, known as the 'warrior gene'. The high-profile study by Caspi and colleagues in 2002 showed that the combination between one type of variation of the MAOA gene and childhood maltreatment noticeably predisposes a person to antisocial behaviour. Moreover, further scientific research shows that individuals with the MAOA gene have to some degree difficulties in controlling their impulses. Based on the evidence of MAOA, some criminal accused claimed difficulties in self-control. In the first case – the famous case of Mobley – the court rejected the MAOA evidence on the ground of the lack of scientific support. In contrast, in other cases after the Mobley trial, courts accepted the evidence of MAOA. In this paper, the issue of lack of impulse control produced by the MAOA gene and cases which relied on the MAOA evidence and successfully being accepted will be reviewed in detail. Finally, the anticipation of the paper for the future use of the MAOA evidence in criminal cases will be presented.

Keywords: genetic defence, criminal responsibility, MAOA, self-control

Procedia PDF Downloads 441

Authors: Boyun Lee

Abstract:

This study aims to discuss whether anthropomorphism some scientists tend to use in cross-species comparison can be justified epistemologically, especially in the primate mind-reading debate. Concretely, this study critically analyzes Elliott Sober’s argument about mind-reading hypothesis (MRH), an anthropomorphic hypothesis which states that nonhuman primates (e.g., chimpanzee) are mind-readers like humans. Although many scientists consider anthropomorphism as an error and choosing anthropomorphic hypothesis like MRH without any definite evidence invalid, Sober advocates that anthropomorphism is supported by cladistic parsimony that suggests choosing the simplest hypothesis postulating the minimum number of evolutionary changes, which can be justified epistemologically in the mind-reading debate. However, his argument has several problems. First, Reichenbach’s theorem which Sober uses in process of showing that MRH has the higher likelihood than its competing hypothesis, behavior-reading hypothesis (BRH), does not fit in the context of inferring the evolutionary relationship. Second, the phylogenetic tree Sober supports is one of the possible scenarios of MRH, and even without this problem, it is difficult to prove that the possibility nonhuman primate species and human share mind-reading ability is higher than the possibility of the other case, considering how evolution occurs. Consequently, it seems hard to justify anthropomorphism of MRH under Sober’s argument. Some scientists and philosophers say that anthropomorphism sometimes helps observe interesting phenomena or make hypotheses in comparative biology. Nonetheless, we cannot determine that it provides answers about why and how the interesting phenomena appear or which of the hypotheses is better, at least the mind-reading debate, under the current state.

Keywords: anthropomorphism, cladistic parsimony, comparative biology, mind-reading debate

Procedia PDF Downloads 140

Authors: E. Tandis, E. Assareh

Abstract:

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

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

Procedia PDF Downloads 283

Authors: Yasaman Mohammadi

Abstract:

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

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

Procedia PDF Downloads 40

Authors: Younis Elhaddad, Alfonso Ortega

Abstract:

Oil production by means of gas lift is a standard technique in oil production industry. To optimize the total amount of oil production in terms of the amount of gas injected is a key question in this domain. Different methods have been tested to propose a general methodology. Many of them apply well-known numerical methods. Some of them have taken into account the power of evolutionary approaches. Our goal is to provide the experts of the domain with a powerful automatic searching engine into which they can introduce their knowledge in a format close to the one used in their domain, and get solutions comprehensible in the same terms, as well. These proposals introduced in the genetic engine the most expressive formal models to represent the solutions to the problem. These algorithms have proven to be as effective as other genetic systems but more flexible and comfortable for the researcher although they usually require huge search spaces to justify their use due to the computational resources involved in the formal models. The first step to evaluate the viability of applying our approaches to this realm is to fully understand the domain and to select an instance of the problem (gas lift optimization) in which applying genetic approaches could seem promising. After analyzing the state of the art of this topic, we have decided to choose a previous work from the literature that faces the problem by means of numerical methods. This contribution includes details enough to be reproduced and complete data to be carefully analyzed. We have designed a classical, simple genetic algorithm just to try to get the same results and to understand the problem in depth. We could easily incorporate the well mathematical model, and the well data used by the authors and easily translate their mathematical model, to be numerically optimized, into a proper fitness function. We have analyzed the 100 curves they use in their experiment, similar results were observed, in addition, our system has automatically inferred an optimum total amount of injected gas for the field compatible with the addition of the optimum gas injected in each well by them. We have identified several constraints that could be interesting to incorporate to the optimization process but that could be difficult to numerically express. It could be interesting to automatically propose other mathematical models to fit both, individual well curves and also the behaviour of the complete field. All these facts and conclusions justify continuing exploring the viability of applying the approaches more sophisticated previously proposed by our research group.

Keywords: evolutionary automatic programming, gas lift, genetic algorithms, oil production

Procedia PDF Downloads 140

Authors: Bawa Yusuf Muhammad, Musa Abubakar Kana, Aminatu Abdulrahman, Kerry Goetz

Abstract:

Background: Inherited eye diseases are disorders that affect globally, 1 in 1000 people. The six main world populations have created databases containing information on eye genotypes. Aim: The aim of the scoping review was to mine and present the available information to date on the genetics of inherited eye diseases within the African continent. Method: Literature Search Strategy was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). PubMed and Google Scholar searched for articles on inherited eye diseases from inception to 20th June 2022. Both Original and review articles that report on inherited, genetic or developmental/congenital eye diseases within the African Continent were included in the research. Results: A total of 1162 citations were obtained, but only 37 articles were reviewed based on the inclusion and exclusion criteria. The highest output of publications on inherited eye diseases comes from South Africa and Tunisia (about 43%), followed by Morocco and Egypt (27%), then Sub-Saharan Africa and North Africa (13.50%), while the remaining articles (16.5%) originated from Nigeria, Ghana, Mauritania Cameroon, Zimbabwe and combined article between Zimbabwe and Cameroon. Glaucoma and inherited retinal disorders represent the most studied diseases, followed by Albinism and congenital cataracts, respectively. Conclusion: Despite the growing research from Tunisia, Morocco, Egypt and South Africa, Sub-Saharan Africa remains almost a virgin region to explore the genetics of eye diseases.

Keywords: inherited eye diseases, Africa, scoping review, longitudinal eye study

Procedia PDF Downloads 23

Authors: Arfan Ali Nagra, Tariq Shahzad, Meshal Alharbi, Khalid Masood Khan, Muhammad Mugees Asif, Taher M. Ghazal, Khmaies Ouahada

Abstract:

Gene selection is an essential step for the classification of microarray cancer data. Gene expression cancer data (DNA microarray) facilitates computing the robust and concurrent expression of various genes. Particle swarm optimization (PSO) requires simple operators and less number of parameters for tuning the model in gene selection. The selection of a prognostic gene with small redundancy is a great challenge for the researcher as there are a few complications in PSO based selection method. In this research, a new variant of PSO (Self-inertia weight adaptive PSO) has been proposed. In the proposed algorithm, SIW-APSO-ELM is explored to achieve gene selection prediction accuracies. This new algorithm balances the exploration capabilities of the improved inertia weight adaptive particle swarm optimization and the exploitation. The self-inertia weight adaptive particle swarm optimization (SIW-APSO) is used to search the solution. The SIW-APSO is updated with an evolutionary process in such a way that each particle iteratively improves its velocities and positions. The extreme learning machine (ELM) has been designed for the selection procedure. The proposed method has been to identify a number of genes in the cancer dataset. The classification algorithm contains ELM, K- centroid nearest neighbor (KCNN), and support vector machine (SVM) to attain high forecast accuracy as compared to the start-of-the-art methods on microarray cancer datasets that show the effectiveness of the proposed method.

Keywords: microarray cancer, improved PSO, ELM, SVM, evolutionary algorithms

Procedia PDF Downloads 55

Authors: Silvia Boschetti, Jakub Binter, Robin Kopecký, Lenka PříPlatová, Jaroslav Flegr

Abstract:

A strict dichotomy was present between religion and science, but recently, cognitive science focusses on the impact of supernatural beliefs on cognitive processes such as pattern recognition. It has been hypothesized that cognitive and perceptual processes have been under evolutionary pressures that ensured amplified perception of patterns, especially when in stressful and harsh conditions. The pattern detection in religious and non-religious individuals after induction of negative, anxious mood shall constitute a cornerstone of the general role of anxiety, cognitive bias, leading towards or against the by-product hypothesis, one of the main theories on the evolutionary studies of religion. The apophenia (tendencies to perceive connection and meaning on unrelated events) and perception of visual patterns (or pateidolia) are of utmost interest. To capture the impact of culture and upbringing, a comparative study of two European countries, the Czech Republic (low organized religion participation, high esoteric belief) and Italy (high organized religion participation, low esoteric belief), are currently in the data collection phase. Outcomes will be presented at the conference. A battery of standardized questionnaires followed by pattern recognition tasks (the patterns involve color, shape, and are of artificial and natural origin) using an experimental method involving the conditioning of (controlled, laboratory-induced) stress is taking place. We hypothesize to find a difference between organized religious belief and personal (esoteric) belief that will be alike in both of the cultural environments.

Keywords: culture, esoteric belief, pattern perception, religiosity

Procedia PDF Downloads 160

Authors: Lavanya Ratnabala, Robinroy Peter, E. Y. A. Charles

Abstract:

This research paper addresses the challenges of exploration and navigation in unknown environments from an evolutionary swarm robotics perspective. Path formation plays a crucial role in enabling cooperative swarm robots to accomplish these tasks. The paper presents a method called the sub-goal-based path formation, which establishes a path between two different locations by exploiting visually connected sub-goals. Simulation experiments conducted in the Argos simulator demonstrate the successful formation of paths in the majority of trials. Furthermore, the paper tackles the problem of inter-collision (traffic) among a large number of robots engaged in path formation, which negatively impacts the performance of the sub-goal-based method. To mitigate this issue, a task allocation strategy is proposed, leveraging local communication protocols and light signal-based communication. The strategy evaluates the distance between points and determines the required number of robots for the path formation task, reducing unwanted exploration and traffic congestion. The performance of the sub-goal-based path formation and task allocation strategy is evaluated by comparing path length, time, and resource reduction against the A* algorithm. The simulation experiments demonstrate promising results, showcasing the scalability, robustness, and fault tolerance characteristics of the proposed approach.

Keywords: swarm, path formation, task allocation, Argos, exploration, navigation, sub-goal

Procedia PDF Downloads 20

Authors: Khizar Samiullah Samiullah, Riffat Yasin, Khurrum Feroz, Omer Draz, Memmona Nazish

Abstract:

New fossil remains of artiodactyl have been recovered from three Late Miocene localities, Lava, Dhok Bun Ameer Khatoon and Hasnoot. These localities belong to lower and middle Siwalik Hills of Pakistan, the Chinji and Dhok Pathan Formation respectively and are remarkably rich in fossils of artiodactyl. The fauna mainly comprises various families of order Artiodactyla; Cervidae, Equidea, Proboscidea, Giraffidea, Rhinocerotidae, Tragulidea, Suidae and Primates. In Chinji Formation Lava and Dhok Bun Ameer Khatoon are located in district Chakwal while in Upper Dhok Pathan Formation the best fossils exposure site is Hasnoot which is located in District Jhelum, Punjab, Pakistan. Specimens described and discussed here include right and left maxilla, isolated upper premolars and molars which have been collected during extensive fieldwork. After morphological and comparative analysis the collection is attributed to Giraffokeryx, Giraffa, Listriodon, Dorcatherium, Selenoportax and Pachyportax. In this study evolutionary status, taxonomy and biogeographical distribution as well as the relationship of different Artiodactyls have been discussed comprehensively. The Palaeoenvironmental studies reveal the persistence of mosaics of diverse habitats ranging from tropical evergreen forest to subtropical ones, closed seasonal woodlands to wooded savannas during the deposition of these outcrops.

Keywords: Artiodactyla, fossil dentition, late Miocene, lower and middle Siwaliks

Procedia PDF Downloads 220

Authors: Kalangi Rodrigo

Abstract:

The term Neuroecology elucidates the study of customizable variation in cognition and the brain. Subject marked the birth since 1980s, when researches began to apply methods of comparative evolutionary biology to cognitive processes and the underlying neural mechanisms of cognition. In Archaeology and Anthropology, we observe behaviors such as social learning skills, innovative feeding and foraging, tool use and social manipulation to determine the cognitive processes of ancient mankind. Depending on the brainstem size was used as a control variable, and phylogeny was controlled using independent contrasts. Both disciplines need to enriched with comparative literature and neurological experimental, behavioral studies among tribal peoples as well as primate groups which will lead the research to a potential end. Neuroecology examines the relations between ecological selection pressure and mankind or sex differences in cognition and the brain. The goal of neuroecology is to understand how natural law acts on perception and its neural apparatus. Furthermore, neuroecology will eventually lead both principal disciplines to Ethology, where human behaviors and social management studies from a biological perspective. It can be either ethnoarchaeological or prehistoric. Archaeology should adopt general approach of neuroecology, phylogenetic comparative methods can be used in the field, and new findings on the cognitive mechanisms and brain structures involved mating systems, social organization, communication and foraging. The contribution of neuroecology to archaeology and anthropology is the information it provides on the selective pressures that have influenced the evolution of cognition and brain structure of the mankind. It will shed a new light to the path of evolutionary studies including behavioral ecology, primate archaeology and cognitive archaeology.

Keywords: Neuroecology, Archaeology, Brain Evolution, Cognitive Archaeology

Procedia PDF Downloads 96

Authors: Francesca Schiavello

Abstract:

This work aims to create a hybrid algorithm, combining Quantum Approximate Optimization Algorithm (QAOA) with an Evolutionary Algorithm (EA) in the place of traditional gradient based optimization processes. QAOA’s were first introduced in 2014, where, at the time, their algorithm performed better than the traditional best known classical algorithm for Max-cut graphs. Whilst classical algorithms have improved since then and have returned to being faster and more efficient, this was a huge milestone for quantum computing, and their work is often used as a benchmarking tool and a foundational tool to explore variants of QAOA’s. This, alongside with other famous algorithms like Grover’s or Shor’s, highlights to the world the potential that quantum computing holds. It also presents the reality of a real quantum advantage where, if the hardware continues to improve, this could constitute a revolutionary era. Given that the hardware is not there yet, many scientists are working on the software side of things in the hopes of future progress. Some of the major limitations holding back quantum computing are the quality of qubits and the noisy interference they generate in creating solutions, the barren plateaus that effectively hinder the optimization search in the latent space, and the availability of number of qubits limiting the scale of the problem that can be solved. These three issues are intertwined and are part of the motivation for using EAs in this work. Firstly, EAs are not based on gradient or linear optimization methods for the search in the latent space, and because of their freedom from gradients, they should suffer less from barren plateaus. Secondly, given that this algorithm performs a search in the solution space through a population of solutions, it can also be parallelized to speed up the search and optimization problem. The evaluation of the cost function, like in many other algorithms, is notoriously slow, and the ability to parallelize it can drastically improve the competitiveness of QAOA’s with respect to purely classical algorithms. Thirdly, because of the nature and structure of EA’s, solutions can be carried forward in time, making them more robust to noise and uncertainty. Preliminary results show that the EA algorithm attached to QAOA can perform on par with the traditional QAOA with a Cobyla optimizer, which is a linear based method, and in some instances, it can even create a better Max-Cut. Whilst the final objective of the work is to create an algorithm that can consistently beat the original QAOA, or its variants, due to either speedups or quality of the solution, this initial result is promising and show the potential of EAs in this field. Further tests need to be performed on an array of different graphs with the parallelization aspect of the work commencing in October 2023 and tests on real hardware scheduled for early 2024.

Keywords: evolutionary algorithm, max cut, parallel simulation, quantum optimization

Procedia PDF Downloads 31

Authors: Sven Tackenberg, Sönke Duckwitz, Andreas Petz, Christopher M. Schlick

Abstract:

This paper introduces an extension to the well-established Resource-Constrained Project Scheduling Problem (RCPSP) to apply it to complex maintenance problems. The problem is to assign technicians to a team which has to process several tasks with multi-level skill requirements during a work shift. Here, several alternative activities for a task allow both, the temporal shift of activities or the reallocation of technicians and tools. As a result, switches from one valid work process variant to another can be considered and may be selected by the developed evolutionary algorithm based on the present skill level of technicians or the available tools. An additional complication of the observed scheduling problem is that the locations of the construction sites are only temporarily accessible during a day. Due to intensive rail traffic, the available time slots for maintenance and repair works are extremely short and are often distributed throughout the day. To identify efficient working periods, a first concept of a Bayesian network is introduced and is integrated into the extended RCPSP with pre-emptive and non-pre-emptive tasks. Thereby, the Bayesian network is used to calculate the probability of a maintenance task to be processed during a specific period of the shift. Focusing on the domain of maintenance of the railway infrastructure in metropolitan areas as the most unproductive implementation process at construction site, the paper illustrates how the extended RCPSP can be applied for maintenance planning support. A multi-criteria evolutionary algorithm with a problem representation is introduced which is capable of revising technician-task allocations, whereas the duration of the task may be stochastic. The approach uses a novel activity list representation to ensure easily describable and modifiable elements which can be converted into detailed shift schedules. Thereby, the main objective is to develop a shift plan which maximizes the utilization of each technician due to a minimization of the waiting times caused by rail traffic. The results of the already implemented core algorithm illustrate a fast convergence towards an optimal team composition for a shift, an efficient sequence of tasks and a high probability of the subsequent implementation due to the stochastic durations of the tasks. In the paper, the algorithm for the extended RCPSP is analyzed in experimental evaluation using real-world example problems with various size, resource complexity, tightness and so forth.

Keywords: maintenance management, scheduling, resource constrained project scheduling problem, genetic algorithms

Procedia PDF Downloads 207

Authors: Masoud Sheidai

Abstract:

Biologists with a special field of population genetics and phylogeny have different research tasks such as populations’ genetic variability and divergence, species relatedness, the evolution of genetic and morphological characters, and identification of DNA SNPs with adaptive potential. To tackle these problems and reach a concise conclusion, they must use the proper and efficient statistical and bioinformatic methods as well as suitable genetic and morphological characteristics. In recent years application of different bioinformatic and statistical methods, which are based on various well-documented assumptions, are the proper analytical tools in the hands of researchers. The species delineation is usually carried out with the use of different clustering methods like K-means clustering based on proper distance measures according to the studied features of organisms. A well-defined species are assumed to be separated from the other taxa by molecular barcodes. The species relationships are studied by using molecular markers, which are analyzed by different analytical methods like multidimensional scaling (MDS) and principal coordinate analysis (PCoA). The species population structuring and genetic divergence are usually investigated by PCoA and PCA methods and a network diagram. These are based on bootstrapping of data. The Association of different genes and DNA sequences to ecological and geographical variables is determined by LFMM (Latent factor mixed model) and redundancy analysis (RDA), which are based on Bayesian and distance methods. Molecular and morphological differentiating characters in the studied species may be identified by linear discriminant analysis (DA) and discriminant analysis of principal components (DAPC). We shall illustrate these methods and related conclusions by giving examples from different edible and medicinal plant species.

Keywords: GWAS analysis, K-Means clustering, LFMM, multidimensional scaling, redundancy analysis

Procedia PDF Downloads 91

Authors: T. C. C. Soo, S. Bhassu

Abstract:

Unlike the common presence of both innate and adaptive immunity in vertebrates, crustaceans, in particular, shrimps, have been discovered to possess only innate immunity. This further emphasizes the importance of innate immunity within shrimps in pathogenic resistance. Under the study of pathogenic immune challenge, different shrimp species actually exhibit varying degrees of immune resistance towards the same pathogen. Furthermore, even within the same shrimp species, different batches of challenged shrimps can have different strengths of immune defence. Several important pathways are activated within shrimps during pathogenic infection. One of them is JAK-STAT pathway that is activated during bacterial, viral and fungal infections by which STAT(Signal Transducer and Activator of Transcription) gene is the core element of the pathway. Based on theory of Central Dogma, the genomic information is transmitted in the order of DNA, RNA and protein. This study is focused in uncovering the important evolutionary patterns present within the DNA (non-coding region) and RNA (coding region). The three shrimp species involved are Macrobrachium rosenbergii, Penaeus monodon and Litopenaeus vannamei which all possess commercial significance. The shrimp species were challenged with a famous penaeid shrimp virus called white spot syndrome virus (WSSV) which can cause serious lethality. Tissue samples were collected during time intervals of 0h, 3h, 6h, 12h, 24h, 36h and 48h. The DNA and RNA samples were then extracted using conventional kits from the hepatopancreas tissue samples. PCR technique together with designed STAT gene conserved primers were utilized for identification of the STAT coding sequences using RNA-converted cDNA samples and subsequent characterization using various bioinformatics approaches including Ramachandran plot, ProtParam and SWISS-MODEL. The varying levels of immune STAT gene activation for the three shrimp species during WSSV infection were confirmed using qRT-PCR technique. For one sample, three biological replicates with three technical replicates each were used for qRT-PCR. On the other hand, DNA samples were important for uncovering the structural variations within the genomic region of STAT gene which would greatly assist in understanding the STAT protein functional variations. The partially-overlapping primers technique was used for the genomic region sequencing. The evolutionary inferences and event predictions were then conducted through the Bayesian Inference method using all the acquired coding and non-coding sequences. This was supplemented by the construction of conventional phylogenetic trees using Maximum likelihood method. The results showed that adaptive evolution caused STAT gene sequence mutations between different shrimp species which led to evolutionary divergence event. Subsequently, the divergent sites were correlated to the differing expressions of STAT gene. Ultimately, this study assists in knowing the shrimp species innate immune variability and selection of disease resistant shrimps for breeding purpose. The deeper understanding of STAT gene evolution from the perspective of both purifying and adaptive approaches not only can provide better immunological insight among shrimp species, but also can be used as a good reference for immunological studies in humans or other model organisms.

Keywords: gene evolution, JAK-STAT pathway, immunology, STAT gene

Procedia PDF Downloads 119

Authors: Nazish Badar

Abstract:

In early 2009, Pandemic type A (H1N1) Influenza virus emerged globally. Since then, it has continued circulation causing considerable morbidity and mortality. The purpose of this study was to evaluate the evolutionary changes in Influenza A (H1N1) pdm09 viruses from 2009-15 and their relevance with the current vaccine viruses. Methods: Respiratory specimens were collected with influenza-like illness and Severe Acute Respiratory Illness. Samples were processed according to CDC protocol. Sequencing and phylogenetic analysis of Haemagglutinin (HA) and neuraminidase (NA) genes was carried out comparing representative isolates from Pakistan viruses. Results: Between Jan2009 - Feb 2016, 1870 (13.2%) samples were positive for influenza A out of 14086. During the pandemic period (2009–10), Influenza A/ H1N1pdm 09 was the dominant strain with 366 (45%) of total influenza positives. In the post-pandemic period (2011–2016), a total of 1066 (59.6%) cases were positive Influenza A/ H1N1pdm 09 with co-circulation of different Influenza A subtypes. Overall, the Pakistan A(H1N1) pdm09 viruses grouped in two genetic clades. Influenza A(H1N1)pdm09 viruses only ascribed to Clade 7 during the pandemic period whereas viruses belong to clade 7 (2011) and clade 6B (2015) during the post-pandemic years. Amino acid analysis of the HA gene revealed mutations at positions S220T, I338V and P100S specially associated with outbreaks in all the analyzed strains. Sequence analyses of post-pandemic A(H1N1)pdm09 viruses showed additional substitutions at antigenic sites; S179N,K180Q (SA), D185N, D239G (CA), S202A (SB) and at receptor binding sites; A13T, S200P when compared with pandemic period. Substitution at Genetic markers; A273T (69%), S200P/T (15%) and D239G (7.6%) associated with severity and E391K (69%) associated with virulence was identified in viruses isolated during 2015. Analysis of NA gene revealed outbreak markers; V106I (23%) among pandemic and N248D (100%) during post-pandemic Pakistan viruses. Additional N-Glycosylation site; HA S179N (23%), NA I23T(7.6%) and N44S (77%) in place of N386K(77%) were only found in post-pandemic viruses. All isolates showed histidine (H) at position 275 in NA indicating sensitivity to neuraminidase inhibitors. Conclusion: This study shows that the Influenza A(H1N1)pdm09 viruses from Pakistan clustered into two genetic clades, with co-circulation of some variants. Certain key substitutions in the receptor binding site and few changes indicative of virulence were also detected in post-pandemic strains. Therefore, it is imperative to continue monitoring of the viruses for early identification of potential variants of high virulence or emergence of drug-resistant variants.

Keywords: Influenza A (H1N1) pdm09, evolutionary analysis, post pandemic period, Pakistan

Procedia PDF Downloads 180

Authors: Martin Pellon Consunji

Abstract:

Due to the rise in popularity of Bitcoin and other crypto assets as a store of wealth and speculative investment, there is an ever-growing demand for automated trading tools, such as bots, in order to gain an advantage over the market. Traditionally, trading in the stock market was done by professionals with years of training who understood patterns and exploited market opportunities in order to gain a profit. However, nowadays a larger portion of market participants are at minimum aided by market-data processing bots, which can generally generate more stable signals than the average human trader. The rise in trading bot usage can be accredited to the inherent advantages that bots have over humans in terms of processing large amounts of data, lack of emotions of fear or greed, and predicting market prices using past data and artificial intelligence, hence a growing number of approaches have been brought forward to tackle this task. However, the general limitation of these approaches can still be broken down to the fact that limited historical data doesn’t always determine the future, and that a lot of market participants are still human emotion-driven traders. Moreover, developing markets such as those of the cryptocurrency space have even less historical data to interpret than most other well-established markets. Due to this, some human traders have gone back to the tried-and-tested traditional technical analysis tools for exploiting market patterns and simplifying the broader spectrum of data that is involved in making market predictions. This paper proposes a method which uses neuro evolution techniques on both sentimental data and, the more traditionally human-consumed, technical analysis data in order to gain a more accurate forecast of future market behavior and account for the way both automated bots and human traders affect the market prices of Bitcoin and other cryptocurrencies. This study’s approach uses evolutionary algorithms to automatically develop increasingly improved populations of bots which, by using the latest inflows of market analysis and sentimental data, evolve to efficiently predict future market price movements. The effectiveness of the approach is validated by testing the system in a simulated historical trading scenario, a real Bitcoin market live trading scenario, and testing its robustness in other cryptocurrency and stock market scenarios. Experimental results during a 30-day period show that this method outperformed the buy and hold strategy by over 260% in terms of net profits, even when taking into consideration standard trading fees.

Keywords: neuro-evolution, Bitcoin, trading bots, artificial neural networks, technical analysis, evolutionary algorithms

Procedia PDF Downloads 93

Authors: Luis Lara-Valencia, Mateo Ramirez-Acevedo, Daniel Caicedo, Jose Brito, Yosef Farbiarz

Abstract:

Controlling wind-induced vibrations as well as aerodynamic forces, is an essential part of the structural design of tall buildings in order to guarantee the serviceability limit state of the structure. This paper presents a numerical investigation on the optimal design parameters of a Tuned Inerter Damper (TID) based system for the control of wind-induced vibration in tall buildings. The control system is based on the conventional TID, with the main difference that its location is changed from the ground level to the last two story-levels of the structural system. The TID tuning procedure is based on an evolutionary cultural algorithm in which the optimum design variables defined as the frequency and damping ratios were searched according to the optimization criteria of minimizing the root mean square (RMS) response of displacements at the nth story of the structure. A Monte Carlo simulation was used to represent the dynamic action of the wind in the time domain in which a time-series derived from the Davenport spectrum using eleven harmonic functions with randomly chosen phase angles was reproduced. The above-mentioned methodology was applied on a case-study derived from a 37-story prestressed concrete building with 144 m height, in which the wind action overcomes the seismic action. The results showed that the optimally tuned TID is effective to reduce the RMS response of displacements up to 25%, which demonstrates the feasibility of the system for the control of wind-induced vibrations in tall buildings.

Keywords: evolutionary cultural algorithm, Monte Carlo simulation, tuned inerter damper, wind-induced vibrations

Procedia PDF Downloads 117

Authors: Tahsin A. H. Nishat, Raquib Ahsan

Abstract:

Sensitivity analysis of design parameters of the optimization procedure can become a significant factor while designing any structural system. The objectives of the study are to analyze the sensitivity of deck slab thickness parameter obtained from both the conventional and optimum design methodology of pre-stressed post-tensioned I-girder and deck system and to compare the relative significance of slab thickness. For analysis on conventional method, the values of 14 design parameters obtained by the conventional iterative method of design of a real-life I-girder bridge project have been considered. On the other side for analysis on optimization method, cost optimization of this system has been done using global optimization methodology 'Evolutionary Operation (EVOP)'. The problem, by which optimum values of 14 design parameters have been obtained, contains 14 explicit constraints and 46 implicit constraints. For both types of design parameters, sensitivity analysis has been conducted on deck slab thickness parameter which can become too sensitive for the obtained optimum solution. Deviations of slab thickness on both the upper and lower side of its optimum value have been considered reflecting its realistic possible ranges of variations during construction. In this procedure, the remaining parameters have been kept unchanged. For small deviations from the optimum value, compliance with the explicit and implicit constraints has been examined. Variations in the cost have also been estimated. It is obtained that without violating any constraint deck slab thickness obtained by the conventional method can be increased up to 25 mm whereas slab thickness obtained by cost optimization can be increased only up to 0.3 mm. The obtained result suggests that slab thickness becomes less sensitive in case of conventional method of design. Therefore, for realistic design purpose sensitivity should be conducted for any of the design procedure of girder and deck system.

Keywords: sensitivity analysis, optimum design, evolutionary operations, PC I-girder, deck system

Procedia PDF Downloads 107

Authors: Rinat Arbel-Goren, Joel Stavans

Abstract:

Cell-to-cell variations in transcript or protein abundance, called noise, may give rise to phenotypic variability between isogenic cells, enhancing the probability of survival under stress conditions. These variations may be introduced by post-transcriptional regulatory processes such as non-coding, small RNAs stoichiometric degradation of target transcripts in bacteria. We study the iron homeostasis network in Escherichia coli, in which the RyhB small RNA regulates the expression of various targets as a model system. Using fluorescence reporter genes to detect protein levels and single-molecule fluorescence in situ hybridization to monitor transcripts levels in individual cells, allows us to compare noise at both transcript and protein levels. The experimental results and computer simulations show that extrinsic noise buffers through a feed-forward loop configuration the increase in variability introduced at the transcript level by iron deprivation, illuminating the important role that extrinsic noise plays during stress. Surprisingly, extrinsic noise also decouples of fluctuations of two different targets, in spite of RyhB being a common upstream factor degrading both. Thus, phenotypic variability increases under stress conditions by the decoupling of target fluctuations in the same cell rather than by increasing the noise of each. We also present preliminary results on the adaptation of cells to prolonged iron deprivation in order to shed light on the evolutionary role of post-transcriptional downregulation by small RNAs.

Keywords: cell-to-cell variability, Escherichia coli, noise, single-molecule fluorescence in situ hybridization (smFISH), transcript

Procedia PDF Downloads 139

Authors: Ali Mohammadi Bolban Abad, Fariborz Ahmadi

Abstract:

Optimization in manufacture is a method to use limited resources to obtain the best performance and reduce waste. In this paper a new algorithm based on eurygaster life is introduced to obtain a plane in which task order and completion time of resources are defined. Evaluation results show our approach has less make span when the resources are allocated with some products in comparison to genetic algorithm.

Keywords: evolutionary computation, genetic algorithm, particle swarm optimization, NP-Hard problems, production scheduling

Procedia PDF Downloads 352

Authors: Jarmila Bernasovska, Pavel Ružbarský, Ivan Bernasovsky, Regina Lohajová Behulová

Abstract:

The paper presents the results of the application of molecular genetics methods in sport research, with special emphasis on the most advanced methods and trends in diagnosing of motoric predispositions for the sake of identifying talented children. Genetic tests differ in principle from the traditional motoric tests, because the DNA of an individual does not change during life. Genetics is important in determining the capacity of an individual and for professional sport level. Genetic information can be used for individual genetic predispositions in early childhood. The phenotypes are influenced by a combination of genetic and environmental factors. The aim of the presented study was to examine physical condition, coordination skills, motoric docility and to determine the frequency of ACTN3 (R577X) gene in Romany children from Eastern Slovakia and compared their motoric performance with non-Romany children. This paper is not looking just for a performance, but also its association to genetic predispositions in relation to ACTN3 gene and its R577X polymorphism. Genotype data were obtained from 175 Romany children from 6 to 15 years old and 218 non-Romany children at the same age from Eastern Slovakia. Biological material for genetic analyses comprised samples of buccal swabs. Genotypes were determined using Real Time High resolution melting PCR method (Rotor Gene 6000 Corbett and LightCycler 480 Roche). Romany children of analyzed group legged to non-Romany children at the same age in all the compared tests. The % distribution of R and X alleles in children was different from controls. The frequency of XX genotype was 11,45% which is comparable to a frequency of an Indian population. Data were analysed with the ANOVA statistical programme and parametric and nonparametric tests. This work was supported by grants APVV-0716-10, ITMS 26220120023 and ITMS 26220120041.

Keywords: ACTN3 gene, R577X polymorphism, Romany children, sport performance, Slovakia

Procedia PDF Downloads 429

Authors: I. Boroňová, J.Bernasovská, J. Kľoc, Z. Tomková, E. Petrejčíková, D. Gabriková, S. Mačeková

Abstract:

Osteoporosis is a complex health disease characterized by low bone mineral density, which is determined by an interaction of genetics with metabolic and environmental factors. Current research in genetics of osteoporosis is focused on identification of responsible genes and polymorphisms. TNFRSF11B gene plays a key role in bone remodeling. The aim of this study was to investigate the genotype and allele distribution of A163G (rs3102735) osteoprotegerin gene promoter and G1181C (rs2073618) osteoprotegerin first exon polymorphisms in the group of 180 unrelated postmenopausal women with diagnosed osteoporosis and 180 normal controls. Genomic DNA was isolated from peripheral blood leukocytes using standard methodology. Genotyping for presence of different polymorphisms was performed using the Custom Taqman®SNP Genotyping assays. Hardy-Weinberg equilibrium was tested for each SNP in the groups of participants using the chi-square (χ2) test. The distribution of investigated genotypes in the group of patients with osteoporosis were as follows: AA (66.7%), AG (32.2%), GG (1.1%) for A163G polymorphism; GG (19.4%), CG (44.4%), CC (36.1%) for G1181C polymorphism. The distribution of genotypes in normal controls were follows: AA (71.1%), AG (26.1%), GG (2.8%) for A163G polymorphism; GG (22.2%), CG (48.9%), CC (28.9%) for G1181C polymorphism. In A163G polymorphism the variant G allele was more common among patients with osteoporosis: 17.2% versus 15.8% in normal controls. Also, in G1181C polymorphism the phenomenon of more frequent occurrence of C allele in the group of patients with osteoporosis was observed (58.3% versus 53.3%). Genotype and allele distributions showed no significant differences (A163G: χ2=0.270, p=0.605; χ2=0.250, p=0.616; G1181C: χ2= 1.730, p=0.188; χ2=1.820, p=0.177). Our results represents an initial study, further studies of more numerous file and associations studies will be carried out. Knowing the distribution of genotypes is important for assessing the impact of these polymorphisms on various parameters associated with osteoporosis. Screening for identification of “at-risk” women likely to develop osteoporosis and initiating subsequent early intervention appears to be most effective strategy to substantially reduce the risks of osteoporosis.

Keywords: osteoporosis, real-time PCR method, SNP polymorphisms

Procedia PDF Downloads 302

Authors: A. V. Varfolomeeva, N. S. Tkachenko, A. G. Tishchenko

Abstract:

The problem of violation of internal validity in studies of psychological structures is considered. The role of epistemological attitudes of researchers in the planning of research within the methodology of the system-evolutionary approach is assessed. Alternative programs of psychological research involving representatives of different biological species are presented. On the example of the results of two research series the variants of solving the problem are discussed.

Keywords: epistemological attitudes, experimental design, validity, psychological structure, learning

Procedia PDF Downloads 91

Authors: Mariana Lima, Rodrigo Silva, Victor Stange, Teodiano Bastos

Abstract:

Due to the high reliability reached by DNA tests, since the 1980s this kind of test has allowed the identification of a growing number of criminal cases, including old cases that were unsolved, now having a chance to be solved with this technology. Currently, the use of genetic profiling databases is a typical method to increase the scope of genetic comparison. Forensic laboratories must process, analyze, and generate genetic profiles of a growing number of samples, which require time and great storage capacity. Therefore, it is essential to develop methodologies capable to organize and minimize the spent time for both biological sample processing and analysis of genetic profiles, using software tools. Thus, the present work aims the development of a software system solution for laboratories of forensics genetics, which allows sample, criminal case and local database management, minimizing the time spent in the workflow and helps to compare genetic profiles. For the development of this software system, all data related to the storage and processing of samples, workflows and requirements that incorporate the system have been considered. The system uses the following software languages: HTML, CSS, and JavaScript in Web technology, with NodeJS platform as server, which has great efficiency in the input and output of data. In addition, the data are stored in a relational database (MySQL), which is free, allowing a better acceptance for users. The software system here developed allows more agility to the workflow and analysis of samples, contributing to the rapid insertion of the genetic profiles in the national database and to increase resolution of crimes. The next step of this research is its validation, in order to operate in accordance with current Brazilian national legislation.

Keywords: database, forensic genetics, genetic analysis, sample management, software solution

Procedia PDF Downloads 346

Authors: Arash Gharibi

Abstract:

Mankind has always used models to solve problems. Essentially, models are simplified versions of reality, whose need stems from having to deal with complexity; many processes or phenomena are too complex to be described completely. Thus a fundamental model requirement is that it contains the characteristic features that are essential in the context of the problem to be solved or described. Models are used in virtually every scientific domain to deal with various problems. During the recent decades, the number of models has increased exponentially. Publication of models as part of original research has traditionally been in in scientific periodicals, series, monographs, agency reports, national journals and laboratory reports. This makes it difficult for interested groups and communities to stay informed about the state-of-the-art. During the modeling process, many important decisions are made which impact the final form of the model. Without a record of these considerations, the final model remains ill-defined and open to varying interpretations. Unfortunately, the details of these considerations are often lost or in case there is any existing information about a model, it is likely to be written intuitively in different layouts and in different degrees of detail. In order to overcome these issues, different domains have attempted to implement their own approaches to preserve their models’ information in forms of model documentation. The most frequently cited model documentation approaches show that they are domain specific, not to applicable to the existing models and evolutionary flexibility and intrinsic corrections and improvements are not possible with the current approaches. These issues are all because of a lack of unified standards for model documentation. As a way forward, this research will propose a new standard for capturing and managing models’ information in a unified way so that interoperability and reusability of models become possible. This standard will also be evolutionary, meaning members of modeling realm could contribute to its ongoing developments and improvements. In this paper, the current 3 of the most common metamodels are reviewed and according to pros and cons of each, a new metamodel is proposed.

Keywords: metamodel, modeling, interoperability, reuse

Procedia PDF Downloads 171

Authors: Zewdneh Zana Zate

Abstract:

The study focuses on the evolutionary and ecological genomics of both wild and cultivated Coffea arabica L. at its center of origin, Ethiopia, aiming to uncover how this vital species may withstand future climate changes. Utilizing bioclimatic models, we project the future distribution of Arabica under varied climate scenarios for 2050 and 2080, identifying potential conservation zones and immediate risk areas. Through whole-genome resequencing of accessions from Ethiopian gene banks, this research assesses genetic diversity and divergence between wild and cultivated populations. It explores relationships, demographic histories, and potential hybridization events among Coffea arabica accessions to better understand the species' origins and its connection to parental species. This genomic analysis also seeks to detect signs of natural or artificial selection across populations. Integrating these genomic discoveries with ecological data, the study evaluates the current and future ecological and genomic vulnerabilities of wild Coffea arabica, emphasizing necessary adaptations for survival. We have identified key genomic regions linked to environmental stress tolerance, which could be crucial for breeding more resilient Arabica varieties. Additionally, our ecological modeling predicted a contraction of suitable habitats, urging immediate conservation actions in identified key areas. This research not only elucidates the evolutionary history and adaptive strategies of Arabica but also informs conservation priorities and breeding strategies to enhance resilience to climate change. By synthesizing genomic and ecological insights, we provide a robust framework for developing effective management strategies aimed at sustaining Coffea arabica, a species of profound global importance, in its native habitat under evolving climatic conditions.

Keywords: coffea arabica, climate change adaptation, conservation strategies, genomic resilience

Procedia PDF Downloads 13