ARTICLE | doi:10.20944/preprints202106.0710.v1
Online: 29 June 2021 (13:30:30 CEST)
In recent years, several industries have registered an impressive improvement in technological advances such as Internet of Things (IoT), e-commerce, vehicular networks, etc. These advances have sparked an increase in the volume of information that gets transmitted from different nodes of a computer network (CN). As a result, it is crucial to safeguard CNs against security threats and intrusions that can compromise the integrity of those systems. In this paper, we propose a machine mearning (ML) intrusion detection system (IDS) in conjunction with the Genetic Algorithm (GA) for feature selection. To assess the effectiveness of the proposed framework, we use the NSL-KDD dataset. Furthermore, we consider the following ML methods in the modelling process: decision tree (DT), support vector machine (SVM), random forest (RF), extra-trees (ET), extreme gradient boosting (XGB), and naïve Bayes (NB). The results demonstrated that using the GA algorithm has a positive impact on the performance of the selected classifiers. Moreover, the results obtained by the proposed ML methods were superior to existing methodologies.
ARTICLE | doi:10.20944/preprints202006.0028.v1
Online: 4 June 2020 (07:44:03 CEST)
Nowadays genetic algorithm (GA) is greatly used in engineering pedagogy as an adaptive technique to learn and solve complex problems and issues. It is a meta-heuristic approach that is used to solve hybrid computation challenges. GA utilizes selection, crossover, and mutation operators to effectively manage the searching system strategy. This algorithm is derived from natural selection and genetics concepts. GA is an intelligent use of random search supported with historical data to contribute the search in an area of the improved outcome within a coverage framework. Such algorithms are widely used for maintaining high-quality reactions to optimize issues and problems investigation. These techniques are recognized to be somewhat of a statistical investigation process to search for a suitable solution or prevent an accurate strategy for challenges in optimization or searches. These techniques have been produced from natural selection or genetics principles. For random testing, historical information is provided with intelligent enslavement to continue moving the search out from the area of improved features for processing of the outcomes. It is a category of heuristics of evolutionary history using behavioral science-influenced methods like an annuity, gene, preference, or combination (sometimes refers to as hybridization). This method seemed to be a valuable tool to find solutions for problems optimization. In this paper, the author has explored the GAs, its role in engineering pedagogies, and the emerging areas where it is using, and its implementation.
ARTICLE | doi:10.20944/preprints202110.0334.v1
Subject: Mathematics & Computer Science, Information Technology & Data Management Keywords: Nesting; cutting; irregular pattern; genetic algorithm; smart manufacturing
Online: 22 October 2021 (15:41:54 CEST)
In industrial environments, nesting consists in cutting or extracting pieces from a material sheet, with the purpose of minimizing the surface of the sheet used. This problem is present in different types of industries, such as shipping, aeronautics, woodworking, footwear, and so on. In this work, the aim is to find an acceptable solution to solve complex nesting problems. The research developed is oriented to sacrifice accuracy for speed so as to obtain robust solutions in less computational time. To achieve this, a greedy method and a genetic algorithm have been implemented, being the latter responsible for generating a sequence for the placement of the pieces, where each piece is placed in its current optimal position with the help of a representation system for both the pieces and the material sheet.
ARTICLE | doi:10.20944/preprints202301.0075.v1
Subject: Engineering, Biomedical & Chemical Engineering Keywords: EMG; optimization; genetic algorithm; deep learning
Online: 4 January 2023 (09:21:39 CET)
Hand gesture recognition has many valuable applications in engineering and health care. This study proposes a novel model which can accurately distinguish hand gestures using forearm muscles' surface electromyogram (sEMG) signals. A deep learning algorithm with hyper parameters impacting the final model’s accuracy and a convolutional neural network (CNN) were employed in the recognition stage. The number of convolutional layers, kernels per layer, and neurons in the dense layer were selected for optimization, while the remaining parameters, such as the learning rate, batch size, and number of epochs, were chosen based on trial and error and prior knowledge. The optimal values for the selected hyperparameters were obtained using a genetic algorithm to achieve maximum recognition accuracy. The UC2018 Dual-Myo database was used for training and testing the model based on EMG signals characterizing the activity of eight different hand gestures. The final structure of the model consisted of two convolutional layers with 131 and 28 kernels, a dense layer with 111 neurons, and a softmax layer with eight neurons. Upon optimizing the hyperparameters using the genetic algorithm, the accuracy of the proposed model increased from 91.86% to 96.4% at best and 95.3% on average in real-time applications and 99.6% in an offline mode. Future work is warranted towards improving the architecture and the computational cost.
ARTICLE | doi:10.20944/preprints202201.0430.v1
Subject: Engineering, Civil Engineering Keywords: Water distribution networks; Optimization; Genetic Algorithm; EPANET
Online: 28 January 2022 (08:53:05 CET)
Water distribution networks are vital infrastructure, needed for providing consumers with sufficient water of appropriate quality. The cost of construction, operation, and maintenance of such networks is extremely large. The problem of optimization of a water distribution network is governed by the type of water distribution network and the size of pipelines placed in the distribution network. This problem of the optimal diameter allocation of pipes in a distribution network has been heavily researched over the past few decades. This study describes the development of a computer program, ‘Smart Optimization Program for Water Distribution Networks’ (SOP–WDN), which applies Genetic Algorithm to the problem of the least-cost design of water distribution networks. SOP–WDN demonstrates the application of an evolutionary optimization technique, Genetic Algorithm, linked with a hydraulic simulation solver EPANET, for the optimal design of water distribution networks. The developed program was applied to three benchmark water distribution network optimization problems and produced consistently good results. SOP–WDN can be utilized as a tool for guiding engineers during the design and rehabilitation of water distribution pipelines.
ARTICLE | doi:10.20944/preprints202203.0399.v1
Subject: Mathematics & Computer Science, Artificial Intelligence & Robotics Keywords: microbiome; genetic algorithm; feature selection; human health; machine learning
Online: 31 March 2022 (08:00:03 CEST)
The relationship between the host and the microbiome, or the assemblage of microorganisms (including bacteria, archaea, fungi, and viruses), has been proven crucial for its health and disease development. The high dimensionality of microbiome datasets has often been addressed as a major difficulty for data analysis, such as the use of Machine Learning (ML) and Deep Learning (DL) models. Here we present BiGAMi, a bi-objective genetic algorithm fitness function for feature selection in microbial datasets to train high-performing phenotype classifiers. The proposed fitness function allowed us to build classifiers that outperformed the baseline performance estimated by the original studies by using as few as 0.04% to 2.32% features of the original dataset. In 19 out of 21 classification exercises, BiGAMi achieved its results by selecting 6-68% fewer features than the highest performance of a Sequential Forward Feature Selection algorithm. This study showed that the application of a bi-objective GA fitness function against microbiome datasets succeeded in selecting small subsets of bacteria whose contribution to understood diseases and the host state was already experimentally proven. Applying this feature selection approach to novel diseases is expected to quickly reveal the microbes most relevant to a specific condition.
Subject: Engineering, Electrical & Electronic Engineering Keywords: transient analysis; surge arrester allocation; genetic algorithm; ATP
Online: 1 September 2019 (09:59:23 CEST)
Lightning discharges in electric power networks generate voltage and current surges that are propagated through the electrical network causing damage and shutdowns in the electrical system. To protect the system against these phenomena, surge arresters are very effective and widely used by electrical utilities in their electric grids. This paper presents a methodology for optimized surge arrester allocation based on genetic algorithm (GA), creating a simulation environment in the software ATP (Alternative Transients Program) to implement the proposed methodology. The optimized allocation procedure is based on a fitness function that minimizes the cost of surge arresters and maximizes the number of protected equipment. To carry out this optimized arrester allocation procedure using ATP may demand too much processing time when running large distribution grids. To overcome this difficulty a procedure is proposed to obtain an overvoltage severity description of the grid and select the most critical electric nodes for the incidence of lightning discharges, in the GA allocation procedure. The case study is applied to the IEEE 123-bus electrical feeder to demonstrate the effectiveness of the proposed methodology.
ARTICLE | doi:10.20944/preprints201807.0164.v1
Subject: Engineering, Electrical & Electronic Engineering Keywords: PEM fuel cell; identification; genetic algorithm; model; LabVIEW
Online: 10 July 2018 (10:12:34 CEST)
PEM fuel cell is a technology successfully used in the production of energy from hydrogen, allowing the use of hydrogen as an energy vector. It is scalable for stationary and mobile applications. However, the technology demands more research. An important research topic is fault diagnosis and condition monitoring to improve the life and the efficiency and to reduce the operation costs of PEMFC devices. Consequently, there is a need of physical models that let deep analysis. These models must be accurate enough to represent the PEMFC behavior and to allow the identification of different internal signals of a PEM fuel cell. This work presents a PEM fuel cell model that uses the output temperature in a closed loop, so it can represent the thermal and the electrical behavior. The model is used to represent a NEXA Ballard 1.2 kW; therefore it is necessary to fit the coefficients to represent the real behavior. Five optimization algorithms were tested to fit the model, three of them were taken from literature and two were proposed. Finally, the model with the parameters identified was validated with real.
ARTICLE | doi:10.20944/preprints202201.0465.v1
Subject: Mathematics & Computer Science, Artificial Intelligence & Robotics Keywords: genetic algorithm; deep neural network; hidden layer; optimal architecture; intrusion detection
Online: 31 January 2022 (13:26:18 CET)
Computer network attacks are evolving in parallel with the evolution of hardware and neural network architecture. Despite major advancements in Network Intrusion Detection System (NIDS) technology, most implementations still depend on signature-based intrusion detection systems, which can’t identify unknown attacks. Deep learning can help NIDS to detect novel threats since it has a strong generalization ability. The deep neural network’s architecture has a significant impact on the model’s results. We propose a genetic algorithm based model to find the optimal number of hidden layers and the number of neurons in each layer of the deep neural network (DNN) architecture for the network intrusion detection binary classification problem. Experimental results demonstrate that the proposed DNN architecture shows better performance than classical machine learning algorithms at a lower computational cost.
ARTICLE | doi:10.20944/preprints202010.0303.v1
Subject: Mathematics & Computer Science, Algebra & Number Theory Keywords: fuzzy genetic algorithm; reachability property; deadlock; model checking
Online: 14 October 2020 (10:58:37 CEST)
model checking techniques are often used for the verification of software systems. Such techniques are accompanied with several advantages. However, state space explosion is one of the drawbacks to model checking. During recent years, several methods have been proposed based on evolutionary and meta-heuristic algorithms to solve this problem. In this paper, a hybrid approach is presented to cope with the SSE problem in model checking of systems modeled by GTS with an ample state space. Most of existence proposed methods that aim to verify systems are applied to detect deadlocks by graph transformations. The proposed approach is based on the fuzzy genetic algorithm and is designed to decline the safety property by verifying the reachability property and detecting deadlocks. In this solution, the state space of the system is searched by a fuzzy genetic algorithm to find the state in which the specified property is refuted/verified. To implement and evaluate the suggested approach, GROOVE is used as a powerful designing and model checking toolset in GTS. The experimental results indicate that the presented hybrid fuzzy method improves speed and performance by comparing other techniques
ARTICLE | doi:10.20944/preprints202008.0409.v1
Subject: Social Sciences, Marketing Keywords: innovation service; pricing model; multiobjective problem; genetic algorithm; negotiating strategies
Online: 19 August 2020 (10:26:06 CEST)
Service pricing is a bottleneck in the development of innovation services, as it is the issue of most concern between the suppliers and demanders. In this paper, a negotiation pricing model that is based on the multiobjective genetic algorithm is developed for innovation service pricing. Regarding the service pricing process as a multiobjective problem, the objective functions, which include the service price, service efficiency, and service quality, for suppliers and demanders are constructed. As the solution of a multiobjective problem is typically a series of alternatives, another negotiation process is necessary for determining the final decision. A learning strategy is adopted during the negotiation process to simulate reality. Finally, the model is implemented for an innovation service transaction, the objective of which is to identify the optimal price plan. The results demonstrate that the model can provide quantitative decision support for the pricing of an innovation service and ultimately yield a win-win result for both the supplier and demander of the innovation service. Furthermore, the influence of the parameters during the negotiation process is analyzed in detail. The effects of the learning strategy on accelerating the negotiation process, as well as the chosen of reasonable parameters are given.
ARTICLE | doi:10.20944/preprints201810.0464.v1
Subject: Mathematics & Computer Science, Artificial Intelligence & Robotics Keywords: genetic algorithms; trajectory planning; keyhole neurosurgery; risk assessment; medical imaging
Online: 22 October 2018 (04:40:10 CEST)
Keyhole neurosurgery implies reaching a target area inside the brain through an entry point specified by the neurosurgeon. In order to avoid complications, a risk assessment procedure must be done to establish the minimum risk trajectory from the entry point to the target area. The neurosurgeon establishes the risk values for the brain structure according to the type of intervention. The preset brain structure risk value is used to assess the risk value for each voxel of the brain. This paper proposes an improved risk assessment methodology based on the sum of N maximum risk values for each voxel. Then, risk assessment for a trajectory is done by adding the risk of all voxels that are part of the path. The safest trajectory is defined as the trajectory with the lower risk. Our proposed search trajectory methodology includes a Genetic Algorithm (GA) for finding the safest trajectories. The use of a GA drastically reduces the number of trajectories to analyze, speeding up the planning procedure. The achieved results were qualified by expert neurosurgeons as satisfactory. Our proposed method allows neurosurgeons to calibrate the surgical planning system by allowing them to establish the risk brain structure and the risk value for each structure.
ARTICLE | doi:10.20944/preprints202102.0364.v1
Subject: Engineering, Automotive Engineering Keywords: generating missed hydrograph; genetic algorithm; Reverse Flood Routing; Karun River; numerical FASTER model
Online: 17 February 2021 (10:09:36 CET)
Flood routing in flood forecasting issue, calculation the height of flood bands, determining the river boundaries, and estimation of protective facilities for flood –exposed building is applicable. In many cases, due to the lack of measuring stations, the status of the upstream flood generating hydrograph is not known. The purpose of this study is to present an integrated method comprising of an optimization model and a hydrodynamic numerical model for flood modeling to determine the upstream hydrograph using the provided hydrograph at the downstream measuring station of a river. The routing procedure consists of three steps: (1) generating a hypothetical upstream hydrograph using genetic algorithm method; (2) hydrodynamic modeling using a numerical simulation model for flood routing according to the hypothetical hydrograph which is generated in the first step; (3) compare the calculated and observed hydrograph in downstream by using a fitness function. This recommended procedure was named as Reverse Flood Routing Method (RFRM) and was then applied to Karun River, the largest river in Iran. Comparing the generated upstream hydrograph by the RFRM model with the corresponding measured hydrograph at Ahvaz hydrometric station, as an ungauged river location, shows the high accuracy of the recommended model in this study.
ARTICLE | doi:10.20944/preprints201906.0241.v1
Subject: Mathematics & Computer Science, Applied Mathematics Keywords: cabinet dryer; genetic algorithm; neural network; temperature; air velocity; moisture
Online: 24 June 2019 (10:05:50 CEST)
Nowadays industrial dryers are used instead of traditional methods for drying. In designing dryers suitable for controlling the process of drying and reaching a high quality product, it is necessary to predict the instantaneous moisture loss during drying. For this purpose, ten mathematical-experimental models with a neural network model based on the kinetic data of pistachio drying are studied. The data obtained from the cabinet dryer will be evaluated at four temperatures of inlet air and different air velocities. The pistachio seeds will be placed in a thin layer on an aluminum sheet on a drying tray and weighed by a scale attached to the computer at different times. In the neural network, data are divided into three parts: educational (60%), validation (20%) and test (20%). Finally, the best mathematical-experimental model using genetic algorithm and the best neural network structure for predicting instantaneous moisture are selected based on the least squared error and the highest correlation coefficient.
ARTICLE | doi:10.20944/preprints201912.0281.v1
Subject: Chemistry, Applied Chemistry Keywords: genetic algorithms; MOFs; metal-organic frameworks; molecular modelling; arrays
Online: 21 December 2019 (10:55:20 CET)
Gas sensor arrays, also known as electronic noses, leverage a diverse set of materials to identify the components of complex gas mixtures. Metal-organic frameworks (MOFs) have emerged as promising materials for electronic noses due to their high-surface areas and chemical as well as structural tunability. Using our recently reported genetic algorithm design approach, we examined a set of 50 MOFs and searched through the over 1.125x1015 unique array combinations to identify optimal arrays for the detection of CO2 in air. We found that despite individual MOFs having lower selectivity for O2 or N2 relative to CO2, intelligently selecting the right combinations of MOFs enabled accurate prediction of the concentrations of all components in the mixture (i.e. CO2, O2, N2). We also analyzed the physical properties of the elements in the arrays to develop an intuition for improving array design. Notably, we find that diversity among the surface areas in the MOFs leads to improved sensing. Consistent with the observation, we found that, as one might expect, the best arrays consistently had more structural diversity than the worst arrays.
ARTICLE | doi:10.20944/preprints201803.0199.v1
Subject: Engineering, Civil Engineering Keywords: Reservoir operation; SWAT; Genetic Algorithm; Urbanisation; Ganga River
Online: 23 March 2018 (15:07:22 CET)
Reservoirs are recognized as one of the most efficient infrastructure components in integrated water resources management and development. At present, with the ongoing advancement of social economy and requirement of water, the water resources shortage problem has worsened, and the operation of reservoirs, in terms of consumption of flood water, has become significantly important. Reservoirs perform both regulation of flood and integrated water resources management, in which the flood limited water level is considered as the most important parameter for trade-off between regulation of flood and conservation. To achieve optimal operating policies for reservoirs, large numbers of simulation and optimization models have been developed in the course of recent decades, which vary notably in their applications and working. Since each model has their own limitations, the determination of fitting model for derivation of reservoir operating policies is challenging and most often there is always a scope for further improvement as the selection of model depends on availability of data. Subsequently, assessment and evaluation associated with the operation of reservoir stays conventional. In the present study, the Soil and Water Assessment Tool (SWAT) models and a Genetic Algorithm model has been developed and applied to two reservoirs in Ganga River basin, India to derive the optimal operational policies. The objective function is set to minimize the annual sum of squared deviation form desired irrigation release and desired storage volume. The decision variables are release for irrigation and other demands (industrial and municipal demands), from the reservoir. As a result, a simulation-based optimization model was recommended for optimal reservoir operation, such as allocation of water, flood regulation, hydropower generation, irrigation demands and navigation and e-flows using a definite combination of decision variables. Since the rule curves are derived through random search it is found that the releases are same as that of demand requirements. Hence based on simulated result, in the present case study it is concluded that GA-derived policies are promising and competitive and can be effectively used operation of the reservoir.
ARTICLE | doi:10.20944/preprints201810.0335.v1
Subject: Engineering, Electrical & Electronic Engineering Keywords: unmanned aerial vehicles; genetic algorithm; mesh networks; optimization; MOEA; NSGA-II
Online: 16 October 2018 (06:16:42 CEST)
In the past, Unmanned Aerial Vehicles (UAVs) were mostly used in the military operations to prevent pilot losses. Nowadays, the fast technological evolution enables the production of a class of cost-effective UAVs which can service a plethora of public and civilian applications, specially when configured to work cooperatively to accomplish a task. However, designing a communication network among the UAVs is challenging task. In this article, we propose a centralized UAV placement strategy, where UAVs are used as flying access points forming a mesh network, providing connectivity to ground nodes deployed in a target area. The geographical placement of UAVs is optimized based on a Multi-Objective Evolutionary Algorithm (MOEA). The goal of the proposed scheme is to cover all ground nodes using a minimum number of UAVs, while maximizing the fulfillment of their data rate requirements. The UAVs can employ different data rates depending on the channel conditions, which are expressed by the Signal-to-Noise-Ratio (SNR). In this work, elitist Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is used to find a set of optimal positions to place UAVs, given the positions of the ground nodes. We evaluate the trade-off between the number of UAVs used to cover the target area and the data rate requirement of the ground nodes. Simulation results show that the proposed algorithm can optimize the UAV placement given the requirement and the positions of the ground nodes in the geographical area.
ARTICLE | doi:10.20944/preprints202109.0090.v1
Subject: Engineering, Electrical & Electronic Engineering Keywords: residential electricity distribution networks; renewable generation sources; energy storage; optimization; multipurpose algorithm; genetic algorithms
Online: 6 September 2021 (12:10:22 CEST)
The global climate change mitigation efforts have increased the efforts of national government to incentivize local households in adopting individual renewable energy as a mean to help reduce the usage of electricity generated using fossil fuels and to gain independence from the grid. Since the majority of residential generation is made by PV panels that generate electricity at off-peak hours, the optimal management of such installations often considers local storage that can defer the use of locally generated electricity at later times. On the other hand, the presence of distributed generation can affect negatively the operating conditions of low-voltage distribution networks. The energy stored in batteries located in optimal places in the network can be used by the utility to improve the operation of the network. This paper proposes a metaheuristic approach based on a Genetic Algorithm that considers three different scenarios of using energy storage for reducing the losses in the network. Prosumer and network operator priorities can be considered in different scenarios inside the same algorithm, to provide a comparative study of different priorities in storage placement. A case study performed on a real distribution network provides insightful results.
ARTICLE | doi:10.20944/preprints201806.0365.v1
Subject: Engineering, General Engineering Keywords: ARIMA model; data forecasting; multi-objective genetic algorithm; regression model
Online: 24 June 2018 (07:48:49 CEST)
The aim of this study has been to develop a novel two-level multi-objective genetic algorithm (GA) to optimize time series forecasting data for fans used in road tunnels by the Swedish Transport Administration (Trafikverket). Level 1 is for the process of forecasting time series cost data, while level 2 evaluates the forecasting. Level 1 implements either a multi-objective GA based on the ARIMA model or a multi-objective GA based on the dynamic regression model. Level 2 utilises a multi-objective GA based on different forecasting error rates to identify a proper forecasting. Our method is compared with using the ARIMA model only. The results show the drawbacks of time series forecasting using only the ARIMA model. In addition, the results of the two-level model show the drawbacks of forecasting using a multi-objective GA based on the dynamic regression model. A multi-objective GA based on the ARIMA model produces better forecasting results. In level 2, five forecasting accuracy functions help in selecting the best forecasting. Selecting a proper methodology for forecasting is based on the averages of the forecasted data, the historical data, the actual data and the polynomial trends. The forecasted data can be used for life cycle cost (LCC) analysis.
ARTICLE | doi:10.20944/preprints201712.0184.v1
Subject: Engineering, Control & Systems Engineering Keywords: distillation column; disturbance rejection; genetic algorithm; H∞ control; linear matrix inequalities; static output feedback
Online: 26 December 2017 (05:22:09 CET)
The current work addresses the control of two-input two-output (TITO) Wood and Berry model of a binary distillation column. The controller design problem is formulated in terms of multivariable H∞ control synthesis. The controller structure takes the form of simplest static output feedback (SOF) control. The controller synthesis is performed using a hybrid approach of blending linear matrix inequalities (LMI) and genetic algorithm (GA). The performance of the static output feedback controller is compared with three other controllers designed for Wood and Berry model available in the literature. The first simulation study is performed for the case of tracking a unit step command in the presence of a step change in output disturbance. A second simulation study is performed for rejecting a change in sinusoidal output disturbance.
ARTICLE | doi:10.20944/preprints202001.0312.v1
Subject: Keywords: ANFIS Genetic algorithm (GA); Singular Value Decomposition (SVD); bedload; machine learning; sediment transport; sensitivity analysis
Online: 26 January 2020 (07:48:52 CET)
Densimetric Froude (Fr) is the minimum velocity required to prevent sediment deposition in pipes. Prediction of Fr is of utmost importance in numerous applications in civil engineering. In this paper through using a new hybrid method. Genetic Algorithm (GA) is used for optimum selection of membership functions of Adaptive Neuro-Fuzzy Inference System (ANFIS), and Singular Value Decomposition (SVD) method is used to compute the linear parameters of ANFIS’s results section (ANFIS-GA/SVD). Also, two different target functions are known as training error (TE) and prediction error (PE) by Pareto curve, the trade-off between these functions is selected as the optimal modeling point. First, different models will be presented using the parameters affecting Fr prediction, classifying them in different groups; then the Fr parameter will be predicted for all the different models through utilizing three different sets of data and the ANFIS-GA/SVD technique. The results of the models indicate that the best Fr prediction is obtained when independent parameters such as volumetric sediment concentration (CV), ratio of median diameter of particle size to pipe diameter (d/D), ratio of median diameter of particle size to hydraulic radius (d/R) and overall friction factor of sediment (λs) use as input variables in prediction of Fr. A sensitivity analysis is also conducted for the purpose of examining the effect of each of the dimensionless parameters on Fr prediction accuracy. Comparing the results of the suggested models with the existing regression-based equations shows that ANFIS-GA/SVD (R2=0.986, MAPE=4.397, RMSE=0.206, SI=0.053, ρ=0.026, BIAS=-0.025) is more accurate than the rest of the models.
ARTICLE | doi:10.20944/preprints202003.0298.v1
Subject: Mathematics & Computer Science, Information Technology & Data Management Keywords: Data Mining; Breast Cancer; Hybrid Feature Selection; Machine learning; Support Vector Machine; Optimize Genetic Algorithm; boosting algorithms
Online: 19 March 2020 (11:13:15 CET)
Breast cancer is a significant health issue across the world. Breast cancer is the most widely-diagnosed cancer in women; early-stage diagnosis of disease and therapies increase patient safety. This paper proposes a synthetic model set of features focused on the optimization of the genetic algorithm (CHFS-BOGA) to forecast breast cancer. This hybrid feature selection approach combines the advantages of three filter feature selection approaches with an optimize Genetic Algorithm (OGA) to select the best features to improve the performance of the classification process and scalability. We propose OGA by improving the initial population generating and genetic operators using the results of filter approaches as some prior information with using the C4.5 decision tree classifier as a fitness function instead of probability and random selection. The authors collected available updated data from Wisconsin UCI machine learning with a total of 569 rows and 32 columns. The dataset evaluated using an explorer set of weka data mining open-source software for the analysis purpose. The results show that the proposed hybrid feature selection approach significantly outperforms the single filter approaches and principal component analysis (PCA) for optimum feature selection. These characteristics are good indicators for the return prediction. The highest accuracy achieved with the proposed system before (CHFS-BOGA) using the support vector machine (SVM) classifiers was 97.3%. The highest accuracy after (CHFS-BOGA-SVM) was 98.25% on split 70.0% train, remainder test, and 100% on the full training set. Moreover, the receiver operating characteristic (ROC) curve was equal to 1.0. The results showed that the proposed (CHFS-BOGA-SVM) system was able to accurately classify the type of breast tumor, whether malignant or benign.
ARTICLE | doi:10.20944/preprints201611.0033.v1
Subject: Mathematics & Computer Science, Information Technology & Data Management Keywords: genetic algorithms; parallel computation; computational complexity; algorithms; optimization techniques; traveling salesman problem; NP-Hard problems; Berlin-52 data set; machine learning; linear regression
Online: 7 November 2016 (04:57:46 CET)
This paper examines the correlation between numbers of computer cores in parallel genetic algorithms. The objective to determine the linear polynomial complementary equation in order represent the relation between number of parallel processing and optimum solutions. Model this relation as optimization function (f(x)) which able to produce many simulation results. F(x) performance is outperform genetic algorithms. Compression results between genetic algorithm and optimization function is done. Also the optimization function give model to speed up genetic algorithm. Optimization function is a complementary transformation which maps a TSP given to linear without changing the roots of the polynomials.
ARTICLE | doi:10.20944/preprints202211.0264.v1
Subject: Engineering, Automotive Engineering Keywords: charging infrastructure; e-mobility; electric vehicle; optimization; private electric car; transport simulation; distribution of charging Infrastructure; battery electric; genetic optimization; high-power charging
Online: 15 November 2022 (01:15:14 CET)
To enable the deployment of battery-electric vehicles (BEV) as passenger cars in the private transport sector, a suitable charging infrastructure is crucial. In this paper a methodology for efficient spatial distribution of charging infrastructure is evaluated by investigating a scenario with a market penetration of BEVs of 100 percent (around 1.3 million vehicles). It aims towards the development of various charging infrastructure scenarios - including public and private charging - which are suitable to cover the charging demand. Therefore, these scenarios are investigated in detail with focus on number of public charging points, their spatial distribution, the available charging power and the necessary capital costs. For the creation of those charging infrastructure scenarios a placement model is developed. It uses the data of a MATSim (Multi-Agent Transport Simulation) traffic simulation of the metropolitan area of Berlin to evaluate and optimize different distributions of charging infrastructure. The model uses a genetic algorithm and the principle of multi-objective optimization. The capital cost of the charging points and the mean detour car drivers must cover additionally are used as optimization criteria. Using these criteria should lead to cost efficient infrastructure solutions which provide high usability at the same time. The main advantage of the method selected is that multiple optimal solutions with different characteristics can be found and suitable solutions can be selected by using other criteria subsequently. The optimized charging infrastructure solutions show capital costs between 624 and 2950 million euro. Users must cover an additionally mean detour of 254m to 590m per charging process to reach an available charging point. According to the results a suitable ratio between charging points and vehicles is between 11:1 and 5:1. A share of fast charging infrastructure (>50kW) of less than ten percent seems to be sufficient, if it is situated at main traffic routes and highly frequented places.
ARTICLE | doi:10.20944/preprints202210.0481.v1
Subject: Mathematics & Computer Science, Applied Mathematics Keywords: Controlled Elitism Non-Dominated Sorting Genetic Algorithm; CENSGA; NSGA-II; Variable-length chromosome (VLC); metaheuristic; multi-objective optimization; Pulse vaccination; allocation; scheduling; planning
Online: 31 October 2022 (10:16:41 CET)
: Seasonal influenza (a.k.a flu) is responsible for considerable morbidity and mortality across the globe. The three recognized pathogens that cause epidemics during the winter season are influenza A, B and C. The influenza virus is particularly dangerous due to its mutability. Vaccines are an effective tool in preventing seasonal influenza, and their formulas are updated yearly according to WHO recommendations. However, in order to facilitate decision-making in the planning of the intervention, policymakers need information on the projected costs and quantities related to introducing the influenza vaccine, in order to help governments obtain an optimal allocation of the vaccine each year. In this paper, an approach based on a Controlled Elitism Non-Dominated Sorting Genetic Algorithm (CENSGA) model is introduced to optimize the allocation of influenza vaccination. A bi-objective model is formulated to control the infection volume, and reduce the unit cost of the vaccination campaign. An SIR (Susceptible–Infected–Recovered) model is employed for representing a potential epidemic. The model constraints are based on the epidemiological model, time management, and vaccine quantity. A two-phase optimization process is proposed: guardian control followed by contingent controls. The proposed approach is an evolutionary metaheuristic multi-objective optimization algorithm with a local search procedure based on a hash table. Moreover, in order to optimize the scheduling of a set of policies over a predetermined time to form a complete campaign, an extended CENSGA is introduced with a variable-length chromosome (VLC) along with mutation and crossover operations. To validate the applicability of the proposed CENSGA, it is compared with the classical Non-Dominated Sorting Genetic Algorithm (NSGA-II). The results are analyzed using graphical and statistical comparisons in terms of cardinality, convergence, distribution and spread quality metrics, illustrating that the proposed CENSGA is effective and useful for determining the optimal vaccination allocation campaigns.
REVIEW | doi:10.20944/preprints202007.0583.v1
Subject: Life Sciences, Genetics Keywords: genetic association studies; extreme phenotype; genetic epidemiology; tinnitus
Online: 24 July 2020 (13:43:00 CEST)
Exome sequencing has been commonly used in rare diseases by selecting multiplex families or singletons with an extreme phenotype (EP) to search for rare variants in coding regions. The EP strategy covers both extreme ends of a disease spectrum and it has been also used to investigate the contribution of rare variants to heritability in complex clinical traits. We have conducted a systematic review to find evidence supporting the use of EP strategies to search for rare variants in genetic studies of complex diseases, to highlight the contribution of rare variation to the genetic structure of multiallelic conditions. After performing the quality assessment of the retrieved records, we selected 19 genetic studies considering EP to demonstrate genetic association. All the studies successfully identified several rare variants, de novo mutations and many novel candidate genes were also identified by selecting an EP. There is enough evidence to support that the EP approach in patients with an early onset of the disease can contribute to the identification of rare variants in candidate genes or pathways involved in complex diseases. EP patients may contribute to a better understanding of the underlying genetic architecture of common heterogeneous disorders such as tinnitus or age-related hearing loss.
ARTICLE | doi:10.20944/preprints201804.0327.v2
Subject: Engineering, Electrical & Electronic Engineering Keywords: Overcurrent Relay (OCR); Genetic Algorithm (GA); Time Dial Setting (TDS); Plug Setting Multiplier (PSM); Optimal OCR setting and coordination and DigSILENT power factory
Online: 27 April 2018 (15:49:58 CEST)
This paper presents a study on optimization of Overcurrent relay (OCR) coordination protection scheme for Sustainable Standalone Hydrokinetic Renewable Energy (SHRE) distribution network at Batang Rajang river, located at Kapit Sarawak, Malaysia by turning river stream into power generation source. The purpose of the project is to develop rural electrification system for native long houses along the river. The research study is tested on a DigSILENT develop model of the SHRE distribution network and in accordance with all respectively unique parameters and relevant standards. Since this is a new standalone distribution system, an efficient and properly coordinated overcurrent protection system must be provided. Improper and miscoordination among OCRs result in maloperation of the protection system that can lead to false tripping and an unnecessary outage and power system instability. Thus, the objective of this work is to employ Genetic Algorithm (GA) technique in Matlab/Simulink for optimal overcurrent coordination and settings among all OCRs in the proposed distribution network in order to improve the speed of OCR tripping operation. The GA is used because the project is fast track and requiring the simplest method available. In this strategy, time dial setting (TDS) is optimized by using plug setting multiplier (PSM) as the constraint. The obtained results show a significant improvement of the relay operating time of 36.01% faster than that of conventional numerical technique during fault occurrence. Thus, an efficient and reliable overcurrent protection scheme has been achieved for the SHRE distribution network.
Subject: Life Sciences, Genetics Keywords: forensic genetic genealogy; investigative genetic genealogy; DNA; forensic DNA
Online: 1 August 2020 (16:29:22 CEST)
Forensic genetic genealogy, a technique leveraging new DNA capabilities and public genetic databases to identify suspects, raises specific considerations in a law enforcement context. Use of this technique requires consideration of its scientific and technical limitations, including the composition of current online datasets, and consideration of its scientific validity. Additionally, forensic genetic genealogy needs to be considered in the relevant legal context to determine the best way in which to make use of its potential to generate investigative leads while minimising its impact on individual privacy. This article presents these issues from an Australian perspective, with the observations and conclusions likely to be applicable to other jurisdictions.
CONCEPT PAPER | doi:10.20944/preprints202011.0387.v1
Subject: Arts & Humanities, Anthropology & Ethnography Keywords: genetic music; genetic code; music composition; steam disciplines; notch1 gene
Online: 13 November 2020 (15:34:47 CET)
In the present work we present a methodology for teaching the basis of the genetic code through music composition, with the aim to combine science and arts learning. The project was carried out by 155 students, the so-called MARGA Consortium, with ages comprised between 10 and 17 years from different public schools located in the Principality of Asturias, Spain. The different groups generated 8 different music works using a short genetic sequence obtained from the human notch1 gene, receptor of mutations leading to chronic lymphocytic leukemia.
ARTICLE | doi:10.20944/preprints201707.0047.v1
Subject: Life Sciences, Genetics Keywords: Festuca ovina L.; AFLP, genetic diversity; genetic barriers; environmental factors
Online: 18 July 2017 (10:05:56 CEST)
Glaciation and mountain orogeny have generated new ecologic opportunities for plants, favoring an increase in the speciation rate. Moreover, they also act as corridors or barriers for plant lineages and populations. High genetic diversity ensures that species are able to survive and adapt. Gene flow is one of the most important determinants of the genetic diversity and structure of out-crossed species, and it is easily affected by biotic and abiotic factors. The aim of this study was to characterize the genetic diversity and structure of an alpine species, Festuca ovina L., in Xingjiang, China. A total of 100 individuals from 10 populations were analyzed using six amplified fragment length polymorphism (AFLP) primer pairs. A total of 583 clear bands were generated, of which 392 were polymorphic; thus, the percentage of polymorphic bands (PPB) was 67.24%. The total and average genetic diversities were 0.2722 and 0.2006 (0.1686-0.2225), respectively. The unweighted group method with arithmetic mean (UPGMA) tree, principal coordinates analysis (PCoA) and STRUCTURE analyses revealed that these populations or individuals could be clustered into two groups. The analysis of molecular variance analysis (AMOVA) suggested that most of the genetic variance existed within a population, and the genetic differentiation (Fst) among populations was 20.71%. The Shannon differentiation coefficient (G’st) among populations was 0.2350. Limited gene flow (Nm = 0.9571) was detected across all sampling sites. The Fst and Nm presented at different levels under the genetic barriers due to fragmentation. The population genetic diversity was significant relative to environmental factors such as temperature, altitude and precipitation.
REVIEW | doi:10.20944/preprints202012.0738.v1
Subject: Life Sciences, Biochemistry Keywords: Next generation sequencing; Genetic disorders; Genomic medicine; Genetic counseling; Rare diseases
Online: 29 December 2020 (16:47:01 CET)
Genetic disorders are preeminent determinants of infant mortality. The inherited pediatric-onset genetic disorders have consequential stress on child growth and development: several congenital, complex and rare disorders with indistinguishable clinical symptoms where diagnosis always remains a challenging task. Traditional diagnosis methods include biochemical tests followed by chromosomal microarray and sequencing of a single gene or panel of genes. These methods had several limitations, but with the advent of whole-exome sequencing (WES), genetic testing has become cost-effective and transformative. Exome sequencing has been known for its effectiveness, which appropriately elucidates and distinguishes the heterogeneous disorders to avoid misdiagnosis and decode the underlying genetic alterations. WES has led to discovering genes and genomic variants in a broad spectrum of diseases, including autism, epilepsy, congenital heart diseases, neurodevelopmental diseases, cancer, nephrotic disorders, neural tube defects and fetal structural anomalies. WES is significant in producing immense genomic biomarkers that can be made as appropriate pharmacogenomic targets for drug therapy. In this article, we analyze the recent exploration of WES technology to revolutionize not only the process of genetic variation and disease detection but also the convention of preventative and targeted drug discovery.
REVIEW | doi:10.20944/preprints202012.0144.v1
Subject: Life Sciences, Biochemistry Keywords: Antimicrobial resistance; blaCTX-M-15; genetic environment; mobile genetic elements; Africa
Online: 7 December 2020 (12:49:16 CET)
The most widely distributed blaCTX-M gene on a global scale is blaCTX-M-15. The dissemination has been associated with clonal spread and different types of mobile genetic elements. This study aimed to review and describe the genetic environments of blaCTX-M-15 gene detected from Enterobacteriaceae in published literature from Africa. A literature search for relevant articles was done through PubMed, and Google Scholars electronic databases, 43 articles from 17 African countries were included in the review based on the eligibility criteria. Insertion sequences were reported as part of the genetic environment of blaCTX-M-15 gene in 32 studies, integrons in 13 studies, and plasmids in 23 studies. In this review, five insertion sequences including ISEcp1, IS26, orf447, IS903, and IS3 have been detected associated with the genetic environment of blaCTX-M-15 in Africa. Seven different genetic patterns were seen in blaCTX-M-15 genetic environment. Insertion sequence ISEcp1 was commonly located upstream of the end of the blaCTX-M-15 gene while insertion sequence orf477 was located downstream. In some studies, ISEcp1 was truncated upstream of blaCTX-M-15 by insertion sequences IS26 and IS3. Class 1 integron (Intl1) was most reported to be associated with blaCTX-M-15 (13 studies), with Intl1/dfrA17–aadA5 being the most common gene cassette array. IncFIA-FIB-FII multi-replicons and IncHI2 replicon types were the most common plasmid replicon types that horizontally transfer blaCTX-M-15 gene. Aminoglycoside modifying enzymes, and plasmid-mediated quinolone resistance genes were commonly collocated with blaCTX-M-15 gene on plasmids. This review revealed the predominant role of ISEcp1, Intl1and IncF plasmid in the mobilization and continental dissemination of the blaCTX-M-15 gene in Africa.
REVIEW | doi:10.20944/preprints202001.0276.v1
Subject: Biology, Entomology Keywords: genetic improvement; genetic variation; heritability; systematic review; biocontrol agent; life history traits
Online: 24 January 2020 (10:39:55 CET)
The concept of genetic improvement in relation to biological control involves the exploitation of natural genetic variation for the benefit of existing biological control agents (BCAs). Despite recent calls for this process to be adopted in biological control research, there is no clear overview of the current state of research into genetic variation within a biological control context, including quantifiable estimates such as narrow-sense heritability (h2). In this systematic review, we aim to determine the current state of research on the genetic variation of biological control traits in natural enemies. After the searching process, screening for papers that can deliver on our research question reduced the initial 2,927 search hits to only a mere 69 papers for data extraction. Of these, the majority (73.6%) did not report quantitative values for genetic variation. Extracting the traits measured in these papers, we categorized them according to two approaches; the first related to fitness components, and the second related to biological control importance. This systematic review highlights the need for more rigorous reporting of the quantitative values of genetic variation to enable the successful genetic improvement of biological control agents.
ARTICLE | doi:10.20944/preprints202212.0099.v1
Subject: Biology, Animal Sciences & Zoology Keywords: Genetic parameters, (Co)variance components, Mecheri sheep, Animal models, Maternal genetic influence, Inbreeding
Online: 6 December 2022 (10:03:11 CET)
Determining genetic and non-genetic sources of variation in a breed is vital for the formulation of strategies for its conservation and improvement. The present study was aimed at estimating the (co)variance components and genetic parameters of Mecheri sheep by fitting six different animal models in the restricted maximum likelihood method, with a preliminary investigation on the performance of animals for non-genetic sources of variation. A total of 2616 lambs were studied, and varying levels of significance were found for the effect of period, season, parity of dam and birth type on different body weight traits. Direct heritability estimates derived from the best animal model for body weight at birth, 3 months, 6 months, 9 months and 12 months were 0.21, 0.24, 0.10, 0.15 and 0.09, respectively, and maternal heritabilities of the corresponding traits were 0.12, 0.05, 0.04, 0.04 and 0.04, respectively. The genetic correlations between body weight traits were all positive and moderate to strong except for birth weight with the other body weight traits. The significance of non-genetic factors studied in this work demanded a correction to improve the accuracy of the direct selection of lambs for body weight traits. The estimated genetic parameters identified the weaning weight as a selection criterion for the improvement in body weight of Mecheri lambs at different ages. Inbred individuals accounted for approximately 13% of the total population in the Mecheri sheep population studied. There were 877 founders in the population, and the actual effective size of the population was 128.48. The population's mean generation interval was 3.26. The mean inbreeding values ranged from 0.005 to 0.010 across generations. The population's average relatedness ranged from 0.001 to 0.014 across generations. Individual inbreeding was found to be 0.45 per cent for the entire population and 3.4 per cent for the inbred population.
ARTICLE | doi:10.20944/preprints202107.0509.v1
Subject: Biology, Anatomy & Morphology Keywords: Perilla crop; genetic resources; morphological traits; principal component analysis; SSR marker; genetic variation
Online: 22 July 2021 (08:04:28 CEST)
Using morphological characteristics and SSR markers, we evaluated the morphological and genetic variation of 200 Perilla accessions collected from the five regions of South Korea and other region. In morphological characteristics analysis, particularly, leaf color, stem color, degree of pubescence, leaf size were found to be useful for distinguishing the characteristics of native Perilla accessions cultivated in South Korea. A total of 137 alleles were identified in the 20 simple sequence repeat (SSR) markers, and the number of alleles per locus ranged from 3 to 13, and the average number of alleles per locus was 6.85. The average gene diversity (GD) was 0.649, with a range of 0.290-0.828. From analysis of SSR markers, accessions from the Jeolla-do and Gyeongsang-do regions showed comparatively high genetic diversity values compared with those from other regions in South Korea. In the unweighted pair group method with arithmetic mean (UPGMA) analysis, the 200 Perilla accessions were found to cluster into three major groups and an outgroup with a genetic similarity of 42%, and did not showed a clear geographic structure from the five regions of South Korea. Therefore, it is believed that landrace Perilla seeds are frequently exchanged by farmers through various routes between the five regions of South Korea. The results of this study are expected to provide useful information for conservation of these genetic resources and selection of useful resources for the development of varieties for seeds and leafy vegetables of cultivated var. frutescens of Perilla crop in South Korea.
REVIEW | doi:10.20944/preprints202206.0284.v1
Online: 21 June 2022 (04:49:04 CEST)
Within microeukaryotes, genetic and functional variation sometimes accumulate more quickly than morphological differences. To understand the evolutionary history and ecology of such lineages, it is key to examine diversity at multiple levels of organization. In the dinoflagellate family Symbiodiniaceae, which can form endosymbioses with cnidarians (e.g., corals, octocorals, sea anemones, jellies), other marine invertebrates (e.g., sponges, molluscs, flatworms), and protists (e.g., foraminifera), molecular data have been used extensively over the past three decades to describe phenotypes and to make evolutionary and ecological inferences. Despite advances in Symbiodiniaceae genomics, a lack of consensus among researchers with respect to interpreting genetic data has slowed progress in the field and acted as a barrier to reconciling observations. Here, we identify key challenges regarding the assessment and interpretation of Symbiodiniaceae genetic diversity across three levels: species, populations, and communities. We summarize areas of agreement and highlight techniques and approaches that are broadly accepted. In areas where debate remains, we identify unresolved issues and discuss technologies and approaches that can help to fill knowledge gaps related to genetic and phenotypic diversity. We also discuss ways to stimulate progress, in particular by fostering a more inclusive and collaborative research community. We hope that this perspective will inspire and accelerate coral reef science by serving as a resource to those designing experiments, publishing research, and applying for funding related to Symbiodiniaceae and their symbiotic partnerships.
REVIEW | doi:10.20944/preprints201912.0021.v1
Subject: Life Sciences, Molecular Biology Keywords: protein 0th-order structure; origin of gene; origin of protein; origin of genetic code; GNC primeval genetic code hypothesis; SNS primitive genetic code hypothesis
Online: 3 December 2019 (11:10:12 CET)
Understanding the mechanism, how entirely new (EntNew) gene/protein or the first ancestral gene/protein of a family was created, should be one of the most important issues in the biological sciences. However, the mechanism is totally unknown still now. On the other hand, it is well known that mature protein is generally rigid and one catalytic center exists on the protein. Creation of such a mature EntNew gene/protein should be, of course, carried out through random process, because it cannot be designed in advance. However, the EntNew gene/protein never be created by random polymerization of the respective monomeric units, because of the extraordinary large sequence diversities of ~10180 and ~10130, respectively. Protein 0th-order structure or a specific amino acid composition, in which immature but water-soluble protein can be produced even through random process, holds the key for solving the difficult problem. As it was fragmentally described in the previous papers how and where EntNew gene/protein was created, I describe in detail in this review three processes generating EntNew gene/protein with some flexibility under three genetic codes, the universal genetic code, SNS primitive code and GNC primeval code, and discuss why the mature gene/protein could be created through the processes.
ARTICLE | doi:10.20944/preprints202212.0234.v1
Subject: Life Sciences, Virology Keywords: reassortant virus; recombinant virus; chimeric virus; genetic engineering; reverse genetic; SARS-CoV-2; COVID-19
Online: 13 December 2022 (08:47:51 CET)
Due to the fact that to date, the question of the origin of SARS-CoV-2 has not been resolved yet, the author analyzed the main advances in the development of genetic engineering of viruses that took place before the onset of the COVID-19 pandemic. The first artificial genetically modified viruses could appear in nature in the mid-1950s. The technique of nucleic acid hybridization was developed by the end-1960s. In the late 1970s, a method called the "reverse genetics" emerged to synthesize RNA and DNA molecules. In the early 1980-s, it became possible to combine the genes of different viruses and insert the genes of one virus into the genome of another virus. Since that time, the production of vector vaccines began. Currently, by modern technologies one can assemble any virus based on the nucleotide sequence available in the virus database or designed by a computer as a virtual model.Scientists around the world are invited to answer the call of Neil Harrison and Jeffrey Sachs of Columbia University, for a thorough and independent investigation into the origin of SARS-CoV-2. Only a full understanding of the origin of the new virus can minimize the likelihood of a similar pandemic in the future.
ARTICLE | doi:10.20944/preprints202201.0414.v1
Subject: Medicine & Pharmacology, Other Keywords: Giardia duodenalis; Assemblages; Epidemiology; Genetic diversity
Online: 27 January 2022 (11:18:33 CET)
Gut protozoan parasites are neglected and not targeted by specific control initiatives and this have led to a knowledge gap concerning their regional diversity and epidemiology. The present study aims to explore Giardia duodenalis genetic diversity and assess the epidemiologic scenario of subclinical infections in different Brazilian biogeographic regions. Cross-sectional surveys (n=1,334 subjects) were conducted in the Amazon, Cerrado, Semiarid and Atlantic Forest. Microscopy of non-diarrheal feces and nucleotide sequencing of a β-giardin gene fragment were performed. Twenty-seven (52.9%) β-giardin sequences were characterized as assemblage A and 24 (47.1%) as assemblage B. In Amazon, assemblage B was the most frequently detected with 2 novel sub-assemblages. Assemblage A predominated in the extra-Amazon region, with 5 novel sub-assemblages. Prevalence rates reached 17.8% in Amazon, 8.8% in Atlantic Forest, 7.4% in Cerrado and 2.3% in the Semiarid. People living in poverty and extreme poverty presented significantly higher positivity rates, reaching 11.9% and 14.5%, respectively. Giardiasis tended to be more frequent in stunted (21.6%) than in eutrophic children (12.9%). In conclusion, subclinical giardiasis in endemic in Brazilian communities in different biogeographic regions, presenting high genetic diversity and a heterogeneous genotypic distribution.
ARTICLE | doi:10.20944/preprints202111.0533.v1
Subject: Life Sciences, Genetics Keywords: chloroplast; genetic resources; genomics capirona; phylogenomics
Online: 29 November 2021 (12:32:24 CET)
Capirona (Calycophyllum spruceanum Benth.) belongs to subfamily Ixoroideae, one of de major lineages in the Rubiaceae family, and is an important timber tree, with origin in the Amazon Basin and has widespread distribution in Bolivia, Peru, Colombia, and Brazil. In this study, we obtained the first complete chloroplast (cp) genome of capirona from department of Madre de Dios located in the Peruvian Amazon. High-quality genomic DNA was used to construct librar-ies. Pair-end clean reads were obtained by PE 150 library and the Illumina HiSeq 2500 platform. The complete cp genome of C. spruceanum has a 154,480 bp in length with typical quadripartite structure, containing a large single copy (LSC) region (84,813 bp) and a small single-copy (SSC) region (18,101 bp), separated by two inverted repeat (IR) regions (25,783 bp). The annotation of C. spruceanum cp genome predicted 87 protein-coding genes (CDS), 8 ribosomal RNA (rRNA) genes, 37 transfer RNA (tRNA) genes and 01 pseudogene. A total of 41 simple sequence repeats (SSR) of this cp genome were divided into mononucleotides (29), dinucleotides (5), trinucleotides (3), and tetranucleotide (4). Most of these repeats were distributed in the noncoding regions. Whole chloroplast genome comparison with the other six Ixoroideae species revealed that the small single copy and large single copy regions showed more divergence than invert regions. Finally, phylogenetic analysis resolved that C. spruceanum is a sister species to Emmenopterys henryi, and confirms its position within the subfamily Ixoroideae. This study reports for the first time the genome organization, gene content, and structural features of the chloroplast genome of C. spruceanum, providing valuable information for genetic and evolutionary studies in the genus Calycophyllum and beyond.
ARTICLE | doi:10.20944/preprints202103.0692.v1
Subject: Engineering, Civil Engineering Keywords: Genetic algorithms, structures, algorithms, generative design
Online: 29 March 2021 (12:50:16 CEST)
The prevalence of algorithms and computational tools in the modern-day has intersected with nearly every field. Generative design, specifically those using genetic algorithms, is an increasingly effective, yet cost efficient way to generate architectural designs in modern engineering. Thus, we adopt a genetic algorithm model in pursuit of maximizing the durability of a structure when it is stressed while minimizing the material cost. After the model is formulated, the algorithm is able to approximate with high accuracy the load a small-scale structure is able to bear, as well as iterate upon its designs to maximize a fitness function.
Subject: Life Sciences, Genetics Keywords: Genetic affinity; STR; Rajasthan; Heterozygosity; Polymorphic
Online: 21 June 2020 (14:12:03 CEST)
Rajasthan is a state located in the north-western part of India and it has been cited as a major route of human migration since ancient times. The present study was conducted to find out the genetic affinity of Rajasthani population with the population living in its east and the west. In particular, we compared them with the population of Pakistan which shares the common geographical boundary with the Rajasthan while also having a look at their inter and intra population affinities with the population belonging to other Indian states. We investigated the genetic structure and population parameters of Rajasthani populations obtained for twenty polymorphic autosomal STR loci from 669 unrelated individuals belonging to its three population groups including Mina, Gujjar and the admixed population of Rajasthan. The studied populations showed a wide range of genetic diversity and besides the genetic structure of the studied populations, it was found that the average heterozygosity value was highest among the populations of Rajasthan, possibly, because of gene flow from different directions. Various statistical analyses suggested that the Rajasthani populations had a higher affinity with the North Indian populations rather than with the Pakistani population.
Online: 28 November 2019 (09:38:55 CET)
The current framework of evolutionary theory postulates that evolution relies on random mutations generating a diversity of phenotypes on which natural selection acts. This framework was established using a top-down approach as it originated from Darwinism, which is based on observations made on complex multicellular organisms, and then modified to fit a DNA-centric view. In this article, I argue that, based on a bottom-up approach starting from the physicochemical properties of nucleic and amino acid polymers, we should reject the facts that: i) natural selection plays a dominant role in evolution, and ii) the probability of mutations is independent of the generated phenotype. I will show that the adaptation of a phenotype to an environment does not correspond to organism fitness but rather corresponds to maintaining the genome stability and integrity. In a stable environment, the phenotype maintains the stability of its originating genome, and both (genome and phenotype) are reproduced identically. In an unstable environment (i.e., corresponding to variations in physicochemical parameters above a physiological range), the phenotype no longer maintains the stability of its originating genome but instead influences its variations. Indeed, environment- and cellular-dependent physicochemical parameters define the probability of mutations in terms of frequency, nature and location in a genome. Evolution is non-deterministic because it relies on probabilistic physicochemical rules, and evolution is driven by a bidirectional interplay between genome and phenotype, the phenotype ensuring the stability of the genotype in a cellular and environment physicochemical parameter-depending manner.
ARTICLE | doi:10.20944/preprints201911.0349.v1
Online: 28 November 2019 (03:24:39 CET)
Bemisia tabaci (Gennadius) is a polyphagous, highly destructive pest capable of vectoring viruses in most agricultural crops. Currently, information on the distribution and genetic diversity of B. tabaci in South Sudan is not available. The objectives of this study were to investigate the genetic variability of B. tabaci infesting sweet potato and cassava in South Sudan. Field surveys were conducted between August 2017 and July and August 2018 in 10 locations in Juba County, Central Equatoria State, South Sudan. Sequences of mitochondrial DNA cytochrome oxidase I (mtCOI) were used to determine the phylogenetic relationships between sampled B. tabaci. Six distinct genetic groups of B. tabaci were identified including three non-cassava haplotypes (Mediterranean (MED), Indian Ocean (IO) and Uganda) and three cassava haplotypes (Sub-Saharan Africa 1 sub-group 1 (SSA1-SG1), SSA1-SG3 and SSA2). MED predominated on sweet potato and SSA2 on cassava in all the sampled locations. The Uganda haplotype was also widespread, occurring in five of the sampled locations. This study provides important information on the diversity of B. tabaci species in South Sudan. A comprehensive assessment of the genetic diversity, geographical distribution, population dynamics and host range of B. tabaci species in South Sudan is vital for its effective management.
ARTICLE | doi:10.20944/preprints201806.0201.v1
Online: 13 June 2018 (11:17:04 CEST)
Human genetic studies have long been vastly Eurocentric, raising a key question about the generalizability of these study findings to other populations. Because humans originated in Africa, these populations retain more genetic diversity, and yet individuals of African descent have been tremendously underrepresented in genetic studies. The diversity in Africa affords ample opportunities to improve fine-mapping resolution for associated loci, discover novel genetic associations with phenotypes, build more generalizable genetic risk prediction models, and better understand the genetic architecture of complex traits and diseases subject to varying environmental pressures. Thus, it is both ethically and scientifically imperative that geneticists globally surmount challenges that have limited progress in African genetic studies to date while meaningfully including African investigators, as greater inclusivity and enhanced research capacity affords enormous opportunities to accelerate genomic discoveries that translate more effectively to all populations. We review the advantages and challenges of studying the genetic architecture of complex traits and diseases in Africa. For example, with greater genetic diversity comes greater ancestral heterogeneity; this higher level of understudied diversity can yield novel genetic findings, but some methods that assume homogeneous population structure and work well in European populations may work less well in the presence of greater diversity and heterogeneity in African populations. Consequently, we advocate for methodological development that will accelerate studies important for all populations, especially those currently underrepresented in genetics.
REVIEW | doi:10.20944/preprints202301.0197.v1
Subject: Behavioral Sciences, Behavioral Neuroscience Keywords: Biomarkers; Genetic; Suicidal behavior; Suicide; Mexican; Genomic.
Online: 11 January 2023 (10:34:57 CET)
Suicide is defined as the action of harming oneself with the intention of dying. It is estimated that worldwide one suicide occurs every 40 seconds, making it a major health problem. Studies in families have suggested that suicide has a genetic component, around the world studies have been carried out in search of genetic variants associated with suicidal behavior, these variants could be useful as potential biomarkers to identify people at risk of suicide. In this area in Mexico, some studies of variants in genes related to neurotransmission and other important pathways have been carried out and a possible association of variants located in genes has been suggested: SLC6A4, SAT-1, TPH-2, ANKK1, GSHR, SCARA50, RGS10, STK33, COMT, and FKBP5. This systematic review shows the genetic studies on the Mexican population. This article contributes by compiling the existing information on genetic variants and genes associated with suicidal behavior, said variants in the future could be used as potential biomarkers to identify people at risk of suicide.
ARTICLE | doi:10.20944/preprints202103.0400.v1
Subject: Medicine & Pharmacology, Allergology Keywords: Lipid metabolism; NAFLD; genetic variants; PSRC1; HCC
Online: 15 March 2021 (16:30:15 CET)
Background and Aims: Dyslipidemia and cardiovascular diseases (CAD) are comorbidities of nonalcoholic fatty liver disease (NAFLD), which ranges from steatosis to hepatocellular carcinoma (HCC). The rs599839 A>G variant, in the CELSR2-PSRC1-SORT1 cluster, has been associated CAD, but its impact on metabolic traits and liver damage in NAFLD has not been investigated yet. Methods: We evaluated the effect of the rs599839 variant in 1426 NAFLD patients (Overall cohort) of whom 131 have HCC (NAFLD-HCC), in 500,000 individuals from the UK Biobank Cohort (UKBBC) and in 366 HCC samples from The Cancer Genome Atlas (TCGA). Hepatic PSRC1, SORT1 and CELSR2 expressions were evaluated by RNAseq (n=125). Results: The rs599839 variant was associated with reduced circulating LDL, carotid intima-media thickness, carotid plaques and hypertension (p<0.05) in NAFLD patients and with protection against dyslipidemia in UKBBC. The G allele was associated with higher risk of HCC and advanced tumor stage (p<0.05) in the Overall cohort. Hepatic PSRC1, SORT1 and CELSR2 expressions were increased in NAFLD patients carrying the rs599839 variant (p<0.0001). SORT1 mRNA levels negatively correlated with circulating lipids and with those of genes involved in lipoprotein turnover (p<0.0001). Conversely, PSRC1 expression was positively related to that of genes implicated in cell proliferation (p<0.0001). In TCGA, PSRC1 over-expression promoted more aggressive HCC development (p<0.05). Conclusions: In sum, the rs599839 A>G variant improves dyslipidemia thus protecting against CAD in NAFLD patients, but as one it might promote HCC development by modulating SORT1 and PSRC1 expressions which impact on lipid metabolism and cell proliferation, respectively
Subject: Life Sciences, Biochemistry Keywords: evolution; darwinism; genetic code; RNA; homoestasis; physics
Online: 6 January 2021 (15:06:41 CET)
The physics–biology continuum relies on the fact that life emerged from prebiotic molecules. Here, I argue that life emerged from the physical coupling between the synthesis of nucleic acids and the synthesis of amino acid polymers. Owing to this physical coupling, amino acid polymers (or proto-phenotypes) maintained the physicochemical parameter equilibria (proto-homeostasis) in the immediate environment of their encoding nucleic acids (or proto-genomes). This protected the proto-genome physicochemical integrity (i.e., atomic composition) from environmental physicochemical stresses, and therefore increased the probability of reproducing the proto-genome without variation. From there, genomes evolved depending on the biological activities they generated in response to environmental fluctuations. Thus, a genome generating an internal environment whose physicochemical parameters guarantee homeostasis and genome integrity has a higher probability to be reproduced without variation and therefore to reproduce the same phenotype in offspring. Otherwise, the genome is modified by the imbalances of the internal physicochemical parameters it generates, until new emerging biological activities maintain homeostasis. In sum, evolution depends on feedforward and feedback loops between genome and phenotype, since the internal physicochemical conditions that a genome generates in response to environmental fluctuations in turn either guarantee the stability or direct the variation of the genome.
ARTICLE | doi:10.20944/preprints202012.0003.v2
Subject: Life Sciences, Biochemistry Keywords: DNA repair; NHEJ; synthetic lethality; genetic interaction
Online: 15 December 2020 (10:41:58 CET)
Non-homologous end-joining (NHEJ) is a major DNA repair pathway in mammalian cells that recognizes, processes and fixes DNA damages throughout the cell cycle, and is specifically important for homeostasis of post-mitotic neurons and developing lymphocytes. Neuronal apoptosis increases in the mice lacking NHEJ factors Ku70 and Ku80. Inactivation of other NHEJ genes, either Xrcc4 or Lig4, leads to massive neuronal apoptosis in the central nervous system (CNS) that correlates with embryonic lethality in mice. Inactivation of either Paxx, Mri or Dna-pkcs NHEJ gene results in normal CNS development due to compensatory effects of Xlf. Combined inactivation of Xlf/Paxx, Xlf/Mri and Xlf/Dna-pkcs, however, results in late embryonic lethality and high levels of apoptosis in CNS. To determine the impact of NHEJ factors on early stages of neurodevelopment, we isolated neural stem and progenitor cells from mouse embryos and investigated proliferation, self-renewal and differentiation capacity of these cells lacking either Xlf, Paxx, Dna-pkcs, Xlf/Paxx or Xlf/Dna-pkcs. We found that XLF, DNA-PKcs and PAXX maintain the neural stem and progenitor cell populations and neurodevelopment in mammals, which is particularly evident in the double knockout models.
ARTICLE | doi:10.20944/preprints202009.0653.v1
Subject: Life Sciences, Biochemistry Keywords: ionizing radiation; radiation resistance; genetic mechanisms; microorganisms
Online: 26 September 2020 (17:24:56 CEST)
Nuclear pollution is an urgent environmental issue as a consequence of rapid industrialization and nuclear accidents in the past. Remediation of nuclear polluted sites using microbial vital activity (bioremediation) is a promising approach to recover contaminated areas in an environmentally friendly and cost-saving way. At the same time, the number of known bacterial and archaeal species able to withstand extremely high doses of ionizing radiation is steadily growing every year, together with growing knowledge about mechanisms of radioresistance. This opens up new opportunities for developing new biotechnological solutions. However, these data are often not systemized and it can be difficult to access. Here, we present the Determinants of Radioresistance Database, or DetR DB (http://extremebiolab.com/detr-db/), gathering a comprehensive catalog of radioresistant microbes and their molecular and genetic determinants of enhanced ionizing radiation tolerance. The database provides search tools including taxonomy, common gene name, and BLAST. DetR DB will be a useful tool for research community by facilitating the extraction of the necessary information to help further analysis of radiation-resistant mechanisms.
Subject: Life Sciences, Genetics Keywords: COVID-19; severe symptoms; inactivation; genetic diversity
Online: 16 April 2020 (09:15:49 CEST)
The rapid spread of the coronavirus disease 2019 (COVID-19) is a serious threat to public health systems globally and is subsequently, a cause of anxiety and panic within human society. Understanding the mechanisms and reducing the chances of having severe symptoms from COVID-19 will play an essential role in treating the disease, and become an urgent task to calm the panic. However, the COVID-19 test developed to identify virus carriers is unable to predict symptom development in individuals upon infection. Experiences from other plagues in human history and COVID-19 statistics suggest that genetic factors may determine the compliance with the virus, i.e., severe, mild, and asymptomatic. Here, a hypothesis is put forward based on the epidemiological characteristics and traits of COVID-19, and our gene expression analysis. It proposes that COVID-19 inactivation in the blood by blocking virus entry into other internal organs for reproduction through the blood circulation after lung cell invasion prevents severe symptoms. Additionally, we investigated a genetic connection between candidate genes and severe COVID-19 symptoms through the utilization of strategies combining hypothesis and data-driven approaches. A list of genes and important SNPs that require further investigation to aid the screening of individuals who may suffer severe illness if exposed to the virus is present. Those individuals should be intensively safeguarded and prioritised for treatment. Concurrently to further research on the COVID-19 pathogenesis, our results also offer a new research strategy for pandemic prevention and health maintenance.
Subject: Life Sciences, Genetics Keywords: genetic diversity; Dioscorea praehensilis; SSR markers; Ghana
Online: 8 March 2020 (14:55:19 CET)
Dioscorea praehensilis Berth is one of the wild yam species resistance to many yam disease (yam anthracnose disease and yam mosaic virus) grow in Ghana especially in the cocoa grown regions of the country. It is a crucial crop that has been known to contribute to poverty reduction and food gap. Genetic diversity in this yam species has been discovered to be eroding and neglected. In this study we evaluated the genetic diversity among 43 D. praehensilis collected from Ghana using simple sequence repeat (SSR). Using 11 SSR marker, a total of 99 number of alleles were generated with an average of 8.48 alleles per locus. The mean gene diversity was 0.81, mean polymorphism information content was 0.82 while mean Shannon information index was 1.94. Principal coordinate analysis (PCoA) revealed a contribution of 40.16% of the first three coordinate axes and grouped the 43 morphotypes into 2 groups while hierarchical cluster through UPGMA revealed the presence of 3 main clusters. Molecular variance (AMOVA) alongside the Fst revealed low genetic diversity and differentiation among accessions and population. Result of this study assess the genetic diversity and will facilitate the use D. praehensilis as sources of resistance gene into yam breeding program.
COMMUNICATION | doi:10.20944/preprints201912.0176.v1
Online: 12 December 2019 (12:43:13 CET)
The rapid and extensive loss of biodiversity globally has resulted in an increased urgency to capture and conserve the diversity which is present, including genetic diversity within species. However, for many species there is currently no detailed genetic data available to inform the collection and use of material held in ex situ collections and this can hamper the consideration of genetic issues and reduce the likelihood collection represent the diversity present. Even in the absence of direct genetic data, however, it is possible to consider genetic issues using the existing theoretical and empirical evidence-based and biological, ecological and demographic data for a given species. Here a framework to facilitate the consideration of genetic diversity and genetic issues, even where genetic data is lacking, is presented.
ARTICLE | doi:10.20944/preprints201811.0046.v1
Subject: Life Sciences, Genetics Keywords: DNA replication, DNA repair, genetic recombination, mutagenesis
Online: 2 November 2018 (10:19:18 CET)
Covalent DNA protein crosslinks (DPCs) are common lesions that block replication. We examine here the consequence of DPCs on mutagenesis involving replicational template-switch reactions in Escherichia coli. 5-azacytidine (5azaC) is a potent mutagen for template-switching, dependent on DNA cytosine methylase (Dcm), implicating the trapped Dcm-DNA covalent complex as the initiator for mutagenesis. The leading strand of replication is more mutable than the lagging strand, explained by blocks to the replicative helicase and/or fork regression. We find that template-switch mutagenesis induced by 5-azaC does not require DSB repair via RecABCD. The ability to induce the SOS response is anti-mutagenic by an unknown mechanism. Mutants in recB, but not recA, exhibit high constitutive rates of template-switching and we suggest that RecBCD-mediated DNA degradation prevents template-switching associated with fork regression. A mutation in the DnaB fork helicase also promotes high levels of template-switching. We also find that other DPC-inducers, formaldehyde (a non-specific crosslinker) and ciprofloxacin (a topoisomerase II poison) are also strong mutagens for template-switching. Induction of mutations and genetic rearrangements that occur by template-switching may constitute a previously unrecognized component of the genotoxicity and genetic instability promoted by DPCs.
REVIEW | doi:10.20944/preprints201807.0089.v1
Subject: Medicine & Pharmacology, Other Keywords: multidisciplinary; Gaucher; genotype/phenotype correlation; genetic counselling
Online: 5 July 2018 (08:51:35 CEST)
Managing the multisystemic symptoms of type I Gaucher Disease (GD) requires a multidisciplinary team approach that includes disease-specific treatments, as well as supportive care. This involves a range of medical specialists, general practitioners, supportive care providers, and patients. Phenotype classification and the setting of treatment goals are important for optimizing the management of type I GD, and providing personalized care. The ability to classify disease severity using validated measurement tools allows the standardization of patient monitoring, and the measurement of disease progression and treatment response. Defining treatment goals is useful to provide a benchmark for assessing treatment response, and managing the expectations of patients and their families. Although treatment goals will vary depending on disease severity, they include the stabilization, improvement or reversal (if possible) of clinical manifestations. Enzyme replacement therapy (ERT) is the standard care for patients with type I GD, but a novel substrate reduction therapy (SRT), Eliglustat has demonstrated safety and efficacy in selected patients. To ensure that treatment goals are being achieved, regular, comprehensive follow up is necessary.
ARTICLE | doi:10.20944/preprints201806.0329.v1
Subject: Life Sciences, Genetics Keywords: Alzheimer’s disease; Parkinson’s disease; Genetic testing; bioethics
Online: 21 June 2018 (04:38:35 CEST)
Over the last decade, advances in our understanding about the genetic architecture of complex traits and common diseases, have increased our ability to perform susceptibility genetic testing for diseases in asymptomatic individuals. These technological developments raise complex ethical, legal and social considerations. Here we discuss a series of ethical issues associated with susceptibility genetic testing for Alzheimer's and Parkinson's disease. These include, amongst others, informed consent, disclosure of results and unexpected findings, mandatory screening, privacy and confidentiality, and stigma and genetic discrimination. As knowledge of the genetic basis of these diseases continues growing, and as genetic testing becomes more widespread, we anticipate that it will become increasingly important for scientists and clinicians to engage in the conversation about the ethical, social and policy implications of these technologies.
REVIEW | doi:10.20944/preprints201806.0191.v1
Subject: Life Sciences, Genetics Keywords: rare disease; functional genomics; genetic variant validation
Online: 12 June 2018 (12:36:08 CEST)
Many insights into human disease have been built on experimental results in Drosophila, and research in fruit flies is often justified on the basis of its predictive value for questions related to human health. Additionally, there is now a growing recognition of the value of Drosophila for the study of rare human genetic diseases, either as a means of validating the causative nature of a candidate genetic variant found in patients, or as a means of obtaining functional information about a novel disease-linked gene when there is little known about it. For these reasons, funders in the US, Europe, and Canada have launched targeted programs to link human geneticists working on discovering new rare disease loci with researchers who work on the counterpart genes in Drosophila and other model organisms. Several of these initiatives are described here, as are a number of output publications that validate this new approach.
ARTICLE | doi:10.20944/preprints201803.0215.v1
Online: 26 March 2018 (10:35:00 CEST)
In the international scenario of agriculture, Brazil stands out as the main producer and consumer of common bean (Phaseolus vulgaris L.) The increase in the productive potential of the crop is mainly due to breeding programs. The objective of this study was to estimate genetic parameters, predict genotypic values with REML/BLUP (Restricted Maximum Likelihood/Best Linear Unbiased Prediction) and, based on these values, study the variability in common bean cultivars with carioca and black grain. Twenty three agromorphological descriptors were evaluated, among them grain yield. Deviance analysis detected significant differences between the cultivars in both groups. Selective accuracy (Ac) was considered high for most of the traits. Broad-sense heritability (hg2 ) ranged from 0.05 to 0.72, but it was low for the trait yield (YLD). In the carioca grain group, the hg2 values for the traits related to plant morphology were higher than in the black group. Nevertheless, the hg2 values in the black group were higher in relation to the pod and seed traits. The correlations for YLD were moderate but different in the two commercial groups studied. In the black group, variables related to the seed morphology were correlated with grain yield, and in the carioca group, traits related to seed quantity. Based on the groupings, variability among the cultivars was observed. Three distinct clusters were formed for the carioca group and four for the black group. Based on the predicted genetic values, genetic variability and the most adapted and stable cultivars were detected among the cultivars in the studied environments.
ARTICLE | doi:10.20944/preprints201707.0005.v1
Subject: Engineering, Control & Systems Engineering Keywords: Acrobot; Artificial Intelligence; SARSA; PWM; Genetic Algorithm
Online: 4 July 2017 (16:12:37 CEST)
An acrobot is a planar robot with a passive actuator in its first joint. The control problem of the acrobot tries to make it rise from the rest position to the inverted pendulum position. This control problem can be divided in the swing-up problem, when the robot has to rise itself through swinging up as a human acrobat does, and the balancing problem, when the robot has to maintain itself on the inverted pendulum position. We have developed three controllers for the swing-up problem applied to two types of motors: small and big. For small motors, we used the SARSA controller and the PD with a trajectory generator. For big motors, we propose a new controller to control the acrobot, a PWM controller. All controllers except SARSA are tuned using a Genetic Algorithm.
REVIEW | doi:10.20944/preprints202212.0453.v1
Subject: Biology, Agricultural Sciences & Agronomy Keywords: wheat; resistance; leaf rust; genetic loci; genome-wide
Online: 23 December 2022 (08:11:48 CET)
Due to the global warming and dynamic changes in pathogenic virulence, leaf rust caused by Puccinia triticina has greatly expanded its epidermic region and become a severe threat to global wheat production. Genetic bases of wheat resistance to leaf rust mainly relies on the leaf rust resistance (Lr) gene or quantitative trait locus (QLr). Although these genetic loci have been insensitively studied during the last two decades, an updated overview of Lr/QLr in a genome-wide level is urgently needed. This review summarized recent progresses in genetic studies of wheat resistance to leaf rust. Wheat germplasms with great potentials in genetic improvement of resistance to leaf rust were highlighted. Key information about the genetic loci carrying Lr/QLr were summarized. A genome-wide chromosome distribution map for all the Lr/QLr was generated based on the released wheat reference genome. In conclusion, this review has provided valuable sources for both wheat breeders and researchers to understand the genetics of resistance to leaf rust in wheat.
ARTICLE | doi:10.20944/preprints202212.0427.v1
Subject: Earth Sciences, Environmental Sciences Keywords: Plankton; Monitoring; Harmful algae; microscopic; genetic; Western Channel
Online: 22 December 2022 (11:34:13 CET)
Plankton monitoring by microscopy offers long-term ecological perspective of plankton com-munities but different detection approaches are biased uniquely. Genetic identification of marine plankton has become standard but is still not used in routine monitoring. This study assessed the diversity of plankton taxa using 18S high throughput sequencing from 2011-2012 from small-volume (~200ml) samples from the Water and Microplankton Sampler (WaMS) deployed on the Continuous Plankton Recorder platform (CPR). The 18S-HTS survey revealed a bias towards heterotrophic taxa, and phototrophs under 10µm within the photosynthetic community. In comparison with phytoplankton microscopic counts from the CPR survey and Western Channel Observatory station L4, only 8-12 taxonomic families were common to all three surveys, with a bias towards larger diatoms and dinoflagellate taxa in microscopy surveys. The WaMS survey detected a contrasting but complementary taxa set to that of microscopic surveys. Additional Quantitative PCR was carried out on the picoeukaryotic pelagophyte, Aureococcus anophagefferens, and the nanoeukaryotic potential harmful algae, Pseudo-nitzschia delicatissima, from 2011-2013. This confirmed the persistence presence of A. anophagefferens in the Western Channel and an elevated abundance of both species in 2011. Species specific seasonality were distinct from those of aggregrate phytoplankton groups.
REVIEW | doi:10.20944/preprints202212.0210.v1
Subject: Biology, Agricultural Sciences & Agronomy Keywords: Maize; drought; landrace; climate-change; crop genetic resources
Online: 13 December 2022 (01:07:51 CET)
To meet an ever global population's food demand, crop yields must be sustained and increased. Drought, which is getting harsher as a result of global warming, is largely impeding the agricultural productivity. Maize is widely used as food and animal feed in many regions of the world, but its yields are largely effected by drought and heat stress. Historical data on climate change predicts that drought and heat stress becoming major threat for maize cultivation in coming years, which will have huge impact on food security of the world especially in Africa and Asia. Thus there is an immense necessary to develop drought tolerant and climate resilient maize to feed the predicted population of the world. Availability and accessibility of crop genetic resources plays a huge role in development of drought-tolerant maize cultivars. A huge genetic resources of maize, including its landraces and crop wild relatives (CWR) have been reported naturally and many of them have stored in National and International gene banks globally. Conventional breeding methods have been tremendously increased maize yields, but these methods frequently fall short of achieving the demand for improved drought stress resistance. In this article, we have briefly discussed about impact of climate variability on crop production, maize yield losses due to drought, drought tolerance in maize landraces and CWR, and origin and evolution of Mexican landraces. This information may help in utilization of these potential resources in various pre-breeding programs.
ARTICLE | doi:10.20944/preprints202211.0244.v1
Subject: Life Sciences, Molecular Biology Keywords: aromatic rice; salt screening; RAPD marker; genetic diversity
Online: 14 November 2022 (07:43:36 CET)
Salinity is abiotic stress, which causes adverse environmental conditions for rice cultivation. In particular, local aromatic rice cultivation is heavily influenced by soil salinity stress, which has an impact on global food security. This study aimed to screen local aromatic rice genotypes in a hydroponics experiment using Yoshida solutions to evaluate the effect of increasing NaCl concentrations on the early growth stages of rice seedlings. Genetic diversity along with phylogenetic relationship was assessed using the random amplified polymorphic DNA (RAPD) markers. Out of 20 RAPD markers, 17 markers produced reproducible polymorphic bands. Individuals of all genotypes shared 88 (89.80%) of the 98 total RAPD elements amplified. The genetic distance-focused similarity index ranged from 0.05 to 0.94. The highest genetic distance (0.94) was discovered between genotypes Nayanmoni and Kalijira Barisal, and the lowest was between Badshabhog and Kataribhog (0.05). In addition, the OPS 3(510bp) and OPA 14(1100bp) markers could be used to identify salt-tolerant genotypes. According to genetic distance, the salt stress tolerant check genotype, Pokkali was genetically related to Chinigura as well as Kalijira Barisal. This study established a simple and consistent method for evaluating variability across various aromatic rice genotypes, which will benefit in genotype selection for breeding salinity stress tolerant aromatic rice varieties in Bangladesh.
REVIEW | doi:10.20944/preprints202211.0106.v1
Subject: Life Sciences, Genetics Keywords: Keywords: chloroplast genetic engineering; Homologus recombination; ORF; photosynthesis
Online: 7 November 2022 (04:31:29 CET)
Abstract: Chloroplast is a new hotspot in the field of plant transformation system of plant genetic engineering. Initially developed in Chlamydomonas and tobacco, it is now feasible in a broad range of species. They exploit the homologous recombination and segregation pathways acting on chloroplast genomes and are based on direct repeats, transient co-integration or co-transformation and segregation of trait and marker genes. Foreign site-specific recombinases and their target sites provide an alternative and effective method for removing marker genes from plastids.Chloroplast genetic engineering has many advantages over nuclear genetic enginering, especially site-specific introduction of foreign genes ,leading to the absence of gene siliency and positon effect,which providing the available to explore the regulation and mechanism of chloroplast genes`expression in vitro .It also can identify the structure and function of the chloroplast genome , the expression of chloroplast affect the nulear genome. In this paper, the basic methodology of chloroplast transformation, the current techniques and applications, and the future possibilities for Chloroplast genetic engineering was reviewed[1-3].
ARTICLE | doi:10.20944/preprints202207.0332.v1
Subject: Biology, Ecology Keywords: Plankton; Monitoring; Harmful algae; microscopic; genetic; Western Channel
Online: 22 July 2022 (03:33:40 CEST)
Plankton monitoring by microscopy offers long-term ecological perspective of plankton communities but is biased towards those organisms that can be distinguished using the microscope. Genetic identification of marine plankton has become standard but is still not used. This study is a comprehensive study genetically measured taxa in the Western Channel of UK using a small-volume automated water sampler deployed on the CPR platform. The study present one year of high-throughput sequencing data focussing on smaller plankton and separate community to that measured by microscopy that can complement each other for a holistic view of plankton. Quantitative tests of two harmful algae show relatively high abundance of the Pelagophyte Aureococcus anophagefferens during 2011 with low nitrite levels. Three years of Pseudo-nitzschia delicatissima quantitative monitoring also shows a greater abundance of this potentially harmful taxa in 2011. Flow cytometry reveals distinct seasonal cycles with distinct timings.
REVIEW | doi:10.20944/preprints202112.0331.v1
Subject: Life Sciences, Biochemistry Keywords: Genetic code expansion; unnatural amino acid; fluorescence imaging
Online: 21 December 2021 (12:42:35 CET)
Genetic code expansion has emerged as an enabling tool to provide insight into functions of understudied proteinogenic species such as small proteins and peptides, and to probe protein biophysics in the cellular context. Here we discuss recent technical advances and applications of genetic code expansion in cellular imaging of complex mammalian protein species, along with considerations and challenges upon using the method.
ARTICLE | doi:10.20944/preprints202105.0606.v1
Subject: Biology, Anatomy & Morphology Keywords: Chi-squared; Genetic ratios; Progenies; Selfing; Variability analysis
Online: 25 May 2021 (10:34:35 CEST)
The present cultivated enset clonal landraces in Ethiopia originated from few wild progenitors. However, enset has a mixed mode of reproduction in which, the wild enset reproduces sexually through seeds, while cultivated enset is generally propagated vegetatively. The objective of this study was to understand the genetic structures of enset cultivars and estimate their genetic variability by evaluating the morphological data generated from progenies of cultivated and wild enset clones. Hence, seeds collected from six cultivated and four wild enset genotypes were used for this study. Data on four qualitative and six quantitative morphological traits were recorded from the progenies of the 10 enset genotypes. Progenies of seven enset genotypes segregated with 3:1 genetic ratio while progenies of the remaining genotypes segregated differently for the qualitative traits considered. With regard to the quantitative traits, the progenies of the 10 enset genotypes differed significantly for five of the six traits except pseudostem length. Generally the cultivated clones performed better than the wild types. This study demonstrated the possibility of creating genetic variation through selfing of the existing clones of enset for traits of interest and makes improvements either through selection or crossing the elite types to develop novel cultivar
ARTICLE | doi:10.20944/preprints202105.0305.v1
Subject: Life Sciences, Biochemistry Keywords: ISSR; Rosa spp.; DNA fingerprinting; genotypes; genetic diversity
Online: 13 May 2021 (14:01:21 CEST)
Genetic diversity is inevitable in making any crop improvement program successful. DNA fingerprinting technology to assess the genetic relationship among the selected genotypes for identification and cataloging of different species and cultivars of roses is a promising tool for Rosa genomes. The inter-simple sequence repeats markers (ISSRs) were used to investigate the genetic diversity among twenty-one diverse Rosa genotypes belonging to two different species, Rosa hybrida and R. damascena, and three distinct groups of rose varieties, namely Hybrid Tea, Floribunda, and Damask roses. Twenty-four ISSR primers yielded a total of 280 scorable amplified fragments from 250-1800 bp in length, from which 244 were polymorphic, resulting in an average of 86.4% polymorphism. UPGMA cluster analysis based on Jaccard’s pairwise similarity coefficient values ranged from 0.264 to 0.818, clearly distinguished different species and genotypes, grouping them into three distinct clusters. The results confirmed a high degree of variation in the rose germplasm studied highlighting the potential of improvement in roses for the ornamental and perfume industry.
REVIEW | doi:10.20944/preprints202104.0461.v1
Subject: Life Sciences, Genetics Keywords: Germplasm; Genetic plant resources; Preservation; Propagation; in vitro
Online: 19 April 2021 (11:28:31 CEST)
Germplasm is a valuable natural resource in plant diversity that is crucial for its potential use. It provides knowledge about a species genetic composition. Germplasm protection strategies are not just planting hope threatened with extinction, they preserve medicinal and other essential plants on which survival rests. The successful use of genetic plant resources necessitates diligent collection, storage, analysis, documentation, and germplasm exchange. Slow growth cultures, cryopreservation, pollen and DNA banks, botanic gardens, genetic reserves and farmer’s fields are few conservation techniques. However, usage of an in vitro procedure with any chance of genetic instability leads to the destruction of the entire substance. Improved understanding of basic regeneration biology would, in turn, undoubtedly increase the capacity to regenerate plants from in vitro harvested explants, thus expanding selection possibilities. Germplasm conservation seeks to conserve endangered and vulnerable plant species worldwide for future proliferation and development; it is also the bedrock of agricultural production.
ARTICLE | doi:10.20944/preprints202102.0470.v1
Subject: Engineering, Civil Engineering Keywords: Smooth rectangular channel; Tsallis entropy; Genetic Programming (GP)
Online: 22 February 2021 (13:09:13 CET)
One of the most important subjects of hydraulic engineering is the reliable estimation of the transverse distribution in rectangular channel of bed and wall shear stresses. This study makes use of the Tsallis entropy, Genetic Programming (GP) and (ANFIS) methods to assess the shear stress distribution (SSD) in rectangular channel. To evaluate the results of the Tsallis entropy, GP and ANFIS models, laboratory observations were used in which shear stress was measured using an optimized Preston tube. This is then used to measure the SSD in various aspect ratios in the rectangular channel. To investigate the shear stress percentage, 10 data series with a total of 112 different data for were used. The results of the sensitivity analysis show that the most influential parameter for the SSD in smooth rectangular channel is the dimensionless parameter B/H, Where the transverse co-ordinate is B, and the flow depth is H. With the parameters (b/B), (B/H) for the bed and (z/H), (B/H) for the wall as inputs, the modeling of the GP was better than the other one. Based on the analysis, it can be concluded that the use of GP and ANFIS algorithms is more effective in estimating shear stress in smooth rectangular channels than the Tsallis entropy-based equations.
ARTICLE | doi:10.20944/preprints202003.0119.v1
Subject: Life Sciences, Biotechnology Keywords: black rice; transcriptome sequencing; genic SSRs; genetic diversity
Online: 7 March 2020 (09:03:34 CET)
Study in black rice has gain prominence in recent times due to its high nutritive value, curative effect, and anti-oxidant properties. However, its poor agronomic traits, including low yield necessitates the incorporation of the colour-grain trait into elite varieties through plant breeding techniques. SSR markers play an important role in plant identification and breeding. Here, the generation of reference-based transcriptome, annotation of transcriptome datasets, and a large set of simple sequence repeat (SSR) markers derived from Black rice have been described. In all 28664 SSRs were predicted in 34978 (48.59%) expressed transcripts. However, 7068 (20.20%) transcripts were found to have more than one SSR. The identified SSRs were dominated by tri-nucleotide and tetra-nucleotide repeats representing about 54.11% and 33.31% respectively, of total SSRs. Validation of selected markers associated with anthocyanin trait performed across different black rice accessions established the reliability of the process used for mining SSR markers. The SSR markers identified in this study could be used to select varieties with desired traits, and to investigate the genetic mechanism underlying anthocyanin accumulation in the pericarps of black rice. Furthermore, the findings from this study may prove beneficial in future genetic diversity studies, primer development, and selective breeding programs.
ARTICLE | doi:10.20944/preprints201908.0010.v1
Subject: Engineering, Mechanical Engineering Keywords: genetic algorithm; Kalina cycle; energy efficiency; Exergy efficiency;
Online: 1 August 2019 (06:13:45 CEST)
In this paper, a thermodynamic investigation is done on a Kalina-flash cycle. This work is initially validated with the Kalina cycle power plant, Wich is commissioned in Husavic. Low-temperature Kalina-flash is considered for this study. This cycle is working with the ammonia-water mixture. The Kalina-flash cycle was optimized in the view of exergy and thermal efficiency. A multi-objective genetic algorithm is used to accomplish optimization. The optimum values of the objective functions are observed to be 40.20 and 11.70% respectively. At last, The influence of the separator inlet dryness fraction, basic ammonia mass fraction, temperature and flash pressure ratio on the first and second law efficiencies are analysed.
ARTICLE | doi:10.20944/preprints201904.0321.v1
Subject: Life Sciences, Genetics Keywords: chickpea; genetic diversity; linkage disequilibrium; DArTseq-SNP markers
Online: 29 April 2019 (07:56:52 CEST)
Characterization of genetic diversity, population structure and linkage disequilibrium is prerequisite for proper management of breeding programs and conservation of genetic resources. In this study, 186 chickpea genotypes including advanced “Kabuli” breeding lines and Iranian landrace “Desi” chickpea genotypes were genotyped using DArTseq-Based SNP markers. Out of 3339 SNPs, 1152 markers with known chromosomal position were selected for genome diversity analysis. The number of mapped SNP markers varied from 52 (LG8) to 378 (LG4), with an average of 144 SNPs per linkage group. The chromosome size that covered by SNPs varied from 16236.36 kbp (LG8) to 67923.99 kbp (LG5), while LG4 showed higher number of SNPs, with an average of 6.56 SNPs per Mbp. Polymorphism information content (PIC) value of SNP markers ranged from 0.05 to 0.50, with an average of 0.32, while the markers on LG4, LG6 and LG8 showed higher mean PIC value than average. Un-weighted Neighbor Joining cluster analysis and Bayesian-based model population structure grouped chickpea genotypes into four distinct clusters. Principal component analysis (PCoA) and Discriminant Analysis of Principal Component (DAPC) results were consistent with that of the cluster and population structure analysis. Linkage disequilibrium (LD) was extensive and LD decay in chickpea germplasm was relatively low. A few markers showed r2≥0.8, while 2961 pairs of markers showed complete LD (r2=1) and a huge LD block was observed on LG4. High genetic diversity and low kinship value between pairs of genotypes suggesting the presence of a high genetic diversity among studied chickpea genotypes. This study also demonstrated the efficiency of DArTseq-based SNP genotyping for large scale genome analysis in chickpea. The genotypic markers provided in this study are useful for various association mapping studies when combined with phenotypic data of different traits such as seed yield, abiotic and biotic stresses and therefore can be efficiently used in breeding programs to improve chickpea.
ARTICLE | doi:10.20944/preprints201811.0603.v1
Subject: Medicine & Pharmacology, Other Keywords: CCHFV, CD24, nucleocapsid, genetic adjuvant, immunogenicity, IFNAR-/- mice
Online: 27 November 2018 (12:15:59 CET)
Crimean Congo hemorrhagic fever virus (CCHFV) is the causative agent of a globally-spread tick-borne zoonotic infection with an eminent risk of fatal human disease. Imminent public health threat posed by disseminated virus activity and lack of an approved therapeutic make CCHFV an urgent target for vaccine development. We described the construction of a DNA vector expressing nucleocapsid protein (N) of CCHFV (pV-N13) and investigated its potential to stimulate cytokine and total/specific antibody responses in BALB/c and challenge experiment in IFNAR-/- mice. Due to lack of sufficient antibody stimulation towards N protein, we have selected CD24 protein as a potential adjuvant which has proliferative effect on B and T cells. Overall, our N expressing construct when administered solely or in combination with pCD24 vector elicited significant cellular and humoral responses in BALB/c, despite variations in particular cytokines and total antibodies. However, the stimulated antibodies produced due to expression of N protein have shown no neutralizing ability in VNA. Furthermore, challenge experiments were revealed protection potential of N expressing construct in IFNAR -/- mice model. In conclusion, we have shown that CD24 has prominent effect as a genetic adjuvant when co-delivers with a synergic foreign gene expressing vector. Besides, targeting of S segment of CCHFV can be considered as a practical way in developing vaccine against this virus due to its ability to induce immune response which leads to protection in challenge assays in IFN-gamma defective mice models.
ARTICLE | doi:10.20944/preprints201805.0089.v1
Subject: Biology, Agricultural Sciences & Agronomy Keywords: agrobiodiversity; vegetables; plant genetic resources; Italy; safeguarding; landraces
Online: 4 May 2018 (09:34:09 CEST)
The study attempts, above all, to provide a summary, with a strictly scientific basis, about the strategies of conservation of autochthonous agrobiodiversity followed in Italy. A special focus is dedicated on vegetables and, therefore, could represent a contribution to improve the national strategy for the safeguarding of its agrobiodiversity in general. The paper offers also an outlook on the most critical factors of the ex situ conservation and some actions which need to be taken. Some examples of ‘novel’ recovered neglected crops are also given. Finally a case study is proposed: ‘Mugnolicchio’, a neglected race of Brassica oleracea L., cultivated in Altamura (Ba) in southern Italy. ‘Mugnolicchio’ might be considered as an early step in the evolution of broccoli (B. oleracea L. var. italica Plenck) like ‘Mugnoli’ another neglected race described from Salento (Apulia).
ARTICLE | doi:10.20944/preprints201705.0109.v1
Subject: Biology, Plant Sciences Keywords: Turnip mosaic virus; Potyvirus; Genetic structure; Population; China
Online: 15 May 2017 (11:38:11 CEST)
Turnip mosaic virus (TuMV) is one of the most widespread and economically important virus infecting both crop and ornamental species of the family Brassicaceae. TuMV isolates can be classified to five phylogenetic lineages, basal-B, basal-BR, Asian-BR, world-B and Orchis. To understand the genetic structure of TuMV from radish in China, the 3′-terminal genome of 90 TuMV isolates were determined and analyzed with other Chinese isolates available. The results showed that the Chinese TuMV isolates from radish formed three groups: Asian-BR, basal-BR and world-B. More than half of these isolates (52.54%) were clustered to basal-BR group, and could be further divided into three sub-groups. The TuMV basal-BR isolates in the sub-groups I and II were genetically homologous with Japanese ones, while those in sub-group III formed a distinct lineage. Sub-populations of TuMV basal-BR II and III were new emergent and in a state of expansion. The Chinese TuMV radish populations were under negative selection. Gene flow between TuMV populations from Tai’an, Weifang and Changchun was frequent.
REVIEW | doi:10.20944/preprints202301.0519.v1
Subject: Medicine & Pharmacology, Oncology & Oncogenics Keywords: ovarian cancer; machine learning; germ line; genetic risk scores
Online: 28 January 2023 (06:58:55 CET)
Ovarian cancers are curable by surgical resection when discovered early enough. Unfortunately, most ovarian cancers are diagnosed in the later stages. One strategy to identify early ovarian tumors is to screen women who have the highest risk scores. This mini review summarizes the accuracy of different methods used to assess the risk of developing ovarian cancer, including family history, BRCA genetic tests, and polygenic risk scores. The accuracy of these is compared to the maximum theoretical accuracy, revealing a substantial gap. We suggest that this gap, or missing heritability, could be caused by epistatic interactions between genes. An alternative approach to computing genetic risk scores, using chromosomal-scale length variation should incorporate epistatic interactions. Future research in this area should focus on this and other alternative methods of characterizing genomes.
REVIEW | doi:10.20944/preprints202209.0263.v1
Subject: Life Sciences, Biotechnology Keywords: rice; nutrient elements; toxic elements; phenotypic variance; genetic basis
Online: 19 September 2022 (05:31:22 CEST)
Rice (Oryza sativa L.) is primary dietary source for half of the global population that comprising both essential nutrients and toxic heavy metal elements for human health. A number of nutrients are required within the diet and generally lacking in human diets, and need to biofortify into the rice grains, such as iron (Fe), zinc (Zn), calcium (Ca), potassium (K), sodium (Na), magnesium (Mg), phosphorus (P), copper (Cu), iodine (I), selenium (Se), and Sulphur (S). Meanwhile, some elements are toxic to human, including arsenic (As), cadmium (Cd), chromium (Cr), cobalt (Co), mercury (Hg), manganese (Mn), nickel (Ni), and lead (Pb) which need to be eliminated from the rice grains. This article reviews the aspects of phenotypic variation of grain elemental concentration in the diverse rice genotypes, relationship of environmental conditions and rice grain elemental accumulation, correlation between rice grain elemental content and others agronomic traits, and also genetic basis of grain elemental concentration in rice. All of these aspects are important to develop rice varieties with a balanced elemental nutrients and lower toxic heavy metal elements. Enhancing the concentration of essential mineral elements and reducing the accumulation of toxic elements in the rice grain are important to improve the rice quality for human health in addressing mineral deficiency and toxicity that could be accomplished by using plant breeding, agronomic, and genetic engineering approaches.
ARTICLE | doi:10.20944/preprints202204.0029.v1
Subject: Life Sciences, Microbiology Keywords: Lacticaseibacillus species; probiotic potential; genetic traits; presence in genomes
Online: 6 April 2022 (04:54:20 CEST)
This study aimed to exploring the intra-species distribution of genetic characters that favor the persistence in the gastrointestinal tract (GIT) and host interaction of bacteria belonging to the species Lacticaseibacillus genus. These bacterial species comprise commercial probiotics with the widest use among consumers and strains naturally occurring in GIT and in fermented food. Since little is known on the distribution of genetic traits for adhesion capacity, polysaccharide production, biofilm formation, utilization of substrates critically important for survival in GIT, that influence probiotic characteristics, a list of genetic determinants involved in such functions was created by a search for specific genes involved in the above aspects in the genome the extensively characterized probiotic L. rhamnosus GG. The presence/absence and variability of each gene in other Lacticaseibacillus spp. genomes was assessed by alignment with the publicly available fully annotated genome sequences. Eighty-two gene loci were compared, and 49 of these were found to be absent in some genomes in a species or strain-specific mode. A set of genes was found to be conserved, indicating that all strains of the genus may exert some probiotic effects. Among the variable loci a taurine utilization operon and a α-L-fucosidase were examined for presence/absence in 26 strains isolated from infant feces by PCR based tests. Results were variable among the isolates, though their common origin indicated the capacity to survive in the intestinal niche. This study indicated that the capacity to exert probiotic actions of Lacticaseibacillus spp. depends on a conserved set of genes and is enhanced by variable genetic factors whose role is only in part elucidated. The selection of strains of the most promising probiotic candidates to be used in food is feasible by analyzing presence/absence of a set of variable traits.
REVIEW | doi:10.20944/preprints202203.0295.v1
Subject: Life Sciences, Other Keywords: Urinary schistosomiasis; Schistosoma haematobium; sub-Saharan Africa; Genetic Diversity
Online: 22 March 2022 (04:25:24 CET)
: Urinary schistosomiasis caused by the parasite Schistosoma haematobium is the most common form of schistosomiasis. This parasite has a high potential for genetic exchange within parasite populations giving rise to the genetic diversity that is important for its survival. Genetic differ-ences may lead to some parasite strains being more immunogenic which may have a negative impact on management and control of schistosomiasis. Therefore, understanding these genetic differences in the parasite may lead to better management of the disease. A literature search was done on PubMed, African Journals online and Google scholar using predefined search terms such as urinary schistosomiasis, S. haematobium, genetic diversity in sub-Saharan Africa in com-bination with Boolean operators (AND, OR). The search included studies published from 2000-2020 that emphasised on genetic diversity of Schistosoma haematobium in sub-Saharan Africa. Sixteen studies from 18 sub-Saharan African countries that met the inclusion criteria were se-lected. Most studies conducted in these countries showed a high genetic diversity of Schistosoma haematobium studies with microsatellite markers being the most commonly used method for ge-netic diversity determination. Fisher’s exact test showed that the distribution of genetic diversity in sub-Saharan African regions was not statistically significant (p=0.768). The highest number of studies on genetic diversity of Schistosoma haematobium were conducted in West Africa with Ni-geria and Zimbabwe in Southern Africa conducting the most studies, 4/36 (11%) each. Results obtained show the need for continued monitoring of genetic variations in Schistosoma haemato-bium in sub- Saharan Africa. This will aid in understanding the epidemiology of disease, ad-vancing novel treatment and vaccine strategies.
REVIEW | doi:10.20944/preprints202108.0514.v1
Subject: Keywords: radish; breeding; interspecific hybridization; molecular breeding; genomics; genetic engineering
Online: 26 August 2021 (16:46:36 CEST)
Radish is an annual herbaceous root crop, fruit, and oil crop plant belonging to the Cruciferae family. The important traits for radish breeding include high yield, early maturity, late bolting, pungency, cold-hardiness, drought resistance, heat tolerance, and soil adaptability. For successful radish production, need to the understand nature and behavior of the flower, and very important to identify the S haplotypes of parental lines to produce F1 hybrids based on self-incompatibility to get rid of laborious hand emasculation in radish. In radish some desirable genes are not present within varieties. Therefore, further breeding programmes depend on inter-specific and intra-specific hybridization, which has a vital role in genomic studies and crop improvement by introducing desirable agronomic characters. It is essential to acquire detailed genetic information on chromosomes and information on inheritance. Genomics is now at the core of crop improvement, and radish crop is exploited to study the underlying differences in genotypes. But some monogenic characters are improved by genetic engineering. A three-decade span following the first documented instance of genetic engineering has witnessed its application's unprecedented growth. Researchers have successfully produced transgenic radishes with various agronomic characteristics over the last decade.
Subject: Medicine & Pharmacology, Allergology Keywords: germline testing; NGS; breast cancer; genetic counselling; risk assessment
Online: 7 July 2021 (13:14:58 CEST)
The use of multi-gene panels for germline testing in breast cancer enables the estimation of cancer risk and guides risk-reducing management options for tested individuals and their family members. We performed an analysis in our clinical database to identify breast cancer patients undergoing genetic testing with positive reports. We reviewed positive results with respect to the different levels of information provided in the reports; risk estimation and management, cascade family testing, information from secondary findings and actionable information for treatment decision-making. A total of 415 positive test reports were identified with 57.1%, 18.1%, 10.8% and 13.5% of individuals having pathogenic/likely pathogenic variants in high (BRCA1, BRCA2, PALB2, PTEN, TP53), moderate (ATM, CHEK2, NBN), low (BARD1, BRIP1, CHEK2, MLH1, MSH2, MSH6, NF1, RAD51C) and with insufficient evidence for breast cancer risk genes (FANCA, FANCM, NBN, MRE11, PMS2, RAD50, RAD51B, XRCC2, MUTYH), respectively. 6.7% of individuals were double heterozygotes with two pathogenic variants. Germline findings in 92% of individuals are linked to evidence-based treatment information and receive risk estimates for predisposition to breast and/or other cancer types. The use of germline findings for treatment decision making expands the indication of genetic testing to include individuals that could benefit from targeted treatments.
ARTICLE | doi:10.20944/preprints202106.0162.v1
Subject: Life Sciences, Biochemistry Keywords: Amazon forest; capirona; molecular markers; genetic diversity; population structure
Online: 7 June 2021 (10:06:14 CEST)
Capirona (Calycophyllum spruceanum Benth) is a tree species of commercial importance widely distributed in South American forests and is traditionally used for its medicinal properties and wood quality. Studies on this tree species have been focused mainly on wood properties, propagation and growth. Genetic studies on capirona are very limited to date. Today it is possible to explore genetic diversity and population structure in a fast and reliable manner by using molecular markers. We here used 10 Random Amplified Polymorphic DNAs (RAPDs) markers to analyze genetic diversity and population structure of 59 samples of capirona that were sampled from four provinces located in the eastern region of the Peruvian amazon. A total of 186 bands were manually scored, generating a 59 x 186 presence/absence matrix. We used R software to calculate genetic distances based on provesti coefficient. A dendrogram was generated using the UPGMA clustering algorithm and showed four groups that correspond to the geographic origin of the capirona samples. Similarly, a discriminant analysis of principal components (DAPC) confirmed that capirona is grouped into four clusters. However, we also noticed few accessions are intermingled. Genetic diversity estimation was conducted considering the four groups (populations) identified by adegenet package in R. Nei's genetic diversity estimate varied from 0.26 to 0.39 and Shannon index ranged from 2.48 to 2.83. AMOVA analysis revealed the greatest variation exist within populations (69.7%) and indicated that variability among populations is 31.5%. To our best knowledge, this is the first investigation employing molecular markers in capirona in Peru considering their natural distribution, and sheds light towards its modern genetic improvement and for the sustainable management of forests in Peru.
ARTICLE | doi:10.20944/preprints202105.0465.v1
Subject: Life Sciences, Biochemistry Keywords: DArTSeq markers; genetic diversity; Rhodes grass (Chloris gayana); subset
Online: 20 May 2021 (09:46:57 CEST)
Rhodes grass (Chloris gayana Kunth) is one of the most important forage grasses used throughout the tropical and subtropical regions of the world. Enhancing the conservation and use of genetic resources requires the development of knowledge and understanding about the existing global diversity of the species. In this study, 104 Rhodes grass accessions, held in trust in the ILRI forage genebank, were characterized using DArTSeq markers to evaluate the genetic diversity and population structure, and to develop representative subsets, of the collection. The genotyping produced 193,988 SNP and 142,522 SilicoDArT markers with an average polymorphic information content of 0.18 and 0.26, respectively. Hierarchical clustering using selected informative markers showed the presence of two and three main clusters using SNP and SilicoDArT markers, respectively, with a cophenetic correction coefficient of 82 %. Bayesian population structure analysis also showed the presence of two main subpopulations using both marker types indicating the existence of significant genetic variation in the collection. A representative subset, containing 21 accessions from diverse origins, was developed using the SNP markers. In general, the results revealed substantial genetic diversity in the Rhodes grass collection and the generated molecular information, together with the developed subset, should help enhance the management, use and improvement of Rhodes grass germplasm in the future.
Subject: Biology, Anatomy & Morphology Keywords: wheat; plant height; grain traits; Wheat50K; genetic map; QTL
Online: 22 April 2021 (10:20:48 CEST)
Plant height is significantly correlated with grain traits, which is a component of wheat yield. The purpose of this study is to investigate the main QTLs that control plant height and grain-related traits in multiple environments. In this study, we constructed a high-density genetic linkage map using the Wheat50K SNP Array to map quantitative trait loci (QTLs) for these traits in 198 recombinant inbred lines (RILs). The two ends of the chromosome were identified as re-combination-rich areas in all chromosomes except chromosome 1B. The middle area of the chro-mosomes was identified as the recombination-barren area. Both the genetic map and the physical map showed a significant correlation when p=0.001, with a correlation coefficient between 0.63 and 0.99. However, there was almost no recombination between 1RS and 1BS. In terms of plant height, 1RS contributed to the reduction of plant height by 3.43cm. In terms of grain length, 1RS contributed to the elongation of grain by 0.11mm. A total of 43 QTLs were identified, including 8 QTLs for Plant height(PH), 11 QTLs thousand grain weight(TGW), 15 QTLs for grain length(GL),and 9 QTLs for grain width(GW), which explained 1.36%–33.08% of the phenotypic variation. Seven were environment-stable QTLs, including two loci Qph.nwafu-4B and Qph.nwafu-4D that determined plant height. The explanation rates of phenotypic variation were 7.39%-12.26% and 20.11%-27.08%, respectively. One QTL, Qtgw.nwafu-4B, which influenced TGW, showed an explanation rate of 3.43%-6.85% for phenotypic variation, two co-segregating KASP markers were developed, the physical locations corresponding to KASP_AX-109316968 and KASP_AX-109519968 were 25.888344 MB and 25.847691 MB. Another QTL, Qgw.nwafu-4D, which determined grain width, had an explanation rate of 3.43%-6.85%. Three loci that affected the grain length were Qgl.nwafu-5A, Qgl.nwafu-5D.2 and Qgl.nwafu-6B, illustrating the explana-tion rates of phenotypic variation as 6.72%-9.59%, 5.62%-7.75%, and 6.68%-10.73%, respectively. Two QTL clusters were identified on chromosomes 4B and 4D.
ARTICLE | doi:10.20944/preprints202104.0300.v1
Subject: Biology, Anatomy & Morphology Keywords: Fusarium head blight; deoxynivalenol; triticale; genetic resistance; disease evaluation
Online: 12 April 2021 (12:49:38 CEST)
Fusarium Head Blight (FHB) is a destructive disease affecting the grain yield and quality of wheat, barley, rye and triticale. Developing varieties with genetic resistance is integral to successfully managing FHB. However, significant knowledge gap exists in the genetic diversity present in triticale for FHB resistance. This information is critical for breeding new varieties of triticale as its production continues to increase. In the present study, a set of 298 winter triticale accessions from a worldwide collection were screened for their type-2 FHB resistance in an artificially inoculated misted nursery with high levels of inoculum density. Most of the triticale accessions were susceptible to FHB, and only 8% of accessions showed resistance in the field nursery screening. The resistant accessions identified in the nursery screening were selected and further screened for three years in greenhouse conditions. Seven accessions were found to show robust FHB resistance over the three years of greenhouse testing. Thirteen accessions showed significantly lower levels of Deoxynivalenol accumulation when compared to the susceptible triticale control. The accessions identified in the study will be useful in triticale and wheat breeding programs for enhancing FHB resistance and reducing DON accumulation.
REVIEW | doi:10.20944/preprints202103.0209.v1
Subject: Life Sciences, Biochemistry Keywords: Genetic Mapping; Vascular system; Embryogenesis; Vascular disorder; PIk3CA gene
Online: 8 March 2021 (10:43:40 CET)
Term vascular dysfunctional refers to a wide spectrum of vascular abnormalities including pathogenesis of tumors, their proliferation and leading to malfunctioned conditions. The treatment of most of the vascular anomalies including peripheral arterial disease and cardiac disease is multi factor procedure which include the embolic therapy, laser-based treatments and coagulation are all plating important role in managing the disease associated with vascular breakdown. The research proposal defines the treatment and diagnosis procedures involved in treatment of vascular abnormalities with a deep emphasis on techniques, efficiency and complications resulted from various other procedure and use of mapping and sequencing techniques based on genetics of variants of selected genes PIk3CA which will ultimately be more effective.
ARTICLE | doi:10.20944/preprints202012.0209.v1
Subject: Biology, Anatomy & Morphology Keywords: Plasmodium vivax; Duffy Negatives; Africa; Molecular epidemiology; Genetic relatedness
Online: 8 December 2020 (20:30:36 CET)
Recent studies indicated that Plasmodium vivax can infect Duffy-negative individuals, but the varied diagnostic and methodological approaches have limited our ability to characterize P. vivax across Africa. Here, we utilized a standardized approach to compare epidemiological and genetic attributes of P. vivax from Botswana, Ethiopia, and Sudan, where Duffy-positive and Duffy-negative individuals coexist. Among 1,215 febrile patients, the proportions of Duffy negativity range from 20-36% in East Africa to 84% in Southern Africa. Considerable differences were observed in P. vivax prevalence among Duffy-negative populations ranging from averaged 9.2% in Sudan to 86% in Botswana. P. vivax parasite density in Duffy-negative infections is significantly lower than in Duffy-positive infections. Phylogenetic analyses of 229 PvDBP sequences indicated that Duffy-negative P. vivax were not monophyletic but occurred in multiple well-supported clades, suggesting independent origins. Duffy-negative Africans are clearly not resistant to P. vivax and the public health significance should no longer be neglected.
Subject: Medicine & Pharmacology, Allergology Keywords: Mutation; Epigenetic; Genetic; Neoplastic transformation; Stem cell; Tumor classification
Online: 30 November 2020 (08:26:34 CET)
There are many theories of carcinogenesis arguing against the orthodox mutation theory, debating on such as “epigenetic alteration” that is inheritable and yet, theoretically, reversible. Our integrated theory describes that any extracellular, intracellular, or intranuclear stressors, mutagenic or not, can initiate a lengthy tumorigenesis to engender a benign or malignant tumor, but the aberrations directly establishing cellular immortality and autonomy may be epigenetic or genetic alterations in the genomic DNA. A neoplasm is considered a semi-new organism with autonomy; it therefore should have genetic mutations to be “new”. We may be able to direct cancer cells towards differentiation as a remedy, because the extracellular milieu may control the phenotype of a cell and the tissue or organ made of the cell’s progenies, and the cytoplasm of a cell may override the nucleus in the phenotypic control. However, the nucleus retains the capacity to manifest itself if allowed by the microenvironment, which then allows the already reversed cells to revert back to tumor cells again. Neoplasms are malignant if they bear epigenetic or genetic anomalies in mutator genes defined as those whose alterations allow or accelerate alterations to occur in other genes, whereas neoplasms are benign if they bear epigenetic or genetic aberrations only in non-mutator genes. It is imperative to identify the immediate tumor-causing cellular alterations defined as those directly responsible for immortality and autonomy, and for treatment purposes to identify the extracellular and intracellular factors that control the phenotype of cancer cells.
REVIEW | doi:10.20944/preprints202010.0149.v1
Subject: Biology, Anatomy & Morphology Keywords: breeding; diversity; genetic engineering; genomics; male sterility; melon; QTLs
Online: 7 October 2020 (09:22:33 CEST)
Melon (Cucumis melo L.) a member of family Cucurbitaceae is extensively cultivated for its fleshy fruits. Based on the specific agro-climatic zones of cultivation as well as concerning the regional preferences, melon displays significant variability phenotypic and biochemical attributes. Below, an effort is put forth to considerably evaluate the scope of achievements while in the growth as well as the enactment of melon breeding programs by employing the newest solutions. Melon breeding has achieved critical milestones throughout the previous century, and we hope this trend will go on to persist down the road. However, studies have to determine new genetic information for genes associated with the challenges imposed by climate change. The identification of valuable hereditary and also metabolic variability in the form of landraces and melon wild relatives will be useful for harvest diversification and also for the broadening of the cultivated melon genetic base. Whereas, considerable information on genomics, and melon metabolomics, is beneficial for dissecting the basis of the inheritance of important traits and their impact on the former characteristics. Overall, we hope the manuscript is going to serve as a crucial resource for the melon breeders.
Subject: Biology, Anatomy & Morphology Keywords: Non-genetic change; translation errors; phenotypic variability; adaptation; evolution
Online: 6 October 2020 (15:16:03 CEST)
The notion that there is a one to one mapping from genotype to phenotype was overturned a long time ago. Along with genotype and environment, ‘non-genetic changes’ orchestrated by altered RNA and protein molecules also guide the development of phenotype. The idea that there is a route through which changes in phenotype can lead to changes in genotype impinges on several phenomena of molecular, developmental, evolutionary and applied interest. Phenotypic changes that do not alter the underlying DNA sequence have been studied across model systems (eg: DNA and histone modifications, RNA editing, prion formation) and are known to play an important role in short term adaptation. However, because of their transient nature and unstable inheritance, the role of such changes in long term evolution has remained controversial. I classify and review three ways in which non-genetic changes can influence genotype and impact cellular fitness across generations, with an emphasis on the enticing idea that they may act as stepping stones for genetic adaptation. I focus on work from microbial systems and attempt to highlight recent experiments and models that bear on this idea. Overall, I review evidence which suggests that non-genetic changes can impact phenotype via their influence on the genotype, and thus play a role in evolutionary change.
REVIEW | doi:10.20944/preprints202009.0279.v1
Subject: Biology, Other Keywords: selection; mutation; genetic drift; adaptation; ploidy drive; genome instability
Online: 13 September 2020 (11:48:30 CEST)
Ploidy is a significant type of genetic variation, describing the number of chromosome sets per cell. Ploidy evolves in natural populations, clinical populations, and lab experiments, particularly in fungi. Despite a long history of theoretical work on this topic, predicting how ploidy will evolve has proven difficult, as it is often unclear why one ploidy state outperforms another. Here, we review what is known about contemporary ploidy evolution in diverse fungal species through the lens of population genetics. As with typical genetic variants, ploidy evolution depends on the rate that new ploidy states arise by mutation, natural selection on alternative ploidy states, and random genetic drift. However, ploidy variation also has unique impacts on evolution, with the potential to alter chromosomal stability, the rate and patterns of point mutation, and the nature of selection on all loci in the genome. We discuss how ploidy evolution depends on these general and unique factors and highlight areas where additional experimental evidence is required to comprehensively explain the ploidy transitions observed in the field and the lab.
ARTICLE | doi:10.20944/preprints202009.0145.v1
Subject: Life Sciences, Genetics Keywords: NHEJ; Cernunnos; Cyren; pro-B cells; lymphocyte; genetic interaction
Online: 6 September 2020 (15:50:10 CEST)
Non-homologous end-joining (NHEJ) is a DNA repair pathway required to detect, process, and ligate DNA double-stranded breaks (DSBs) throughout the cell cycle. The NHEJ pathway is necessary for V(D)J recombination in developing B and T lymphocytes. During NHEJ, Ku70 and Ku80 form a heterodimer that recognizes DSBs and promotes recruitment and function of downstream factors PAXX, MRI, DNA-PKcs, Artemis, XLF, XRCC4, and LIG4. Mutations in several known NHEJ genes result in severe combined immunodeficiency (SCID). Inactivation of Mri, Paxx or Xlf in mice results in normal or mild phenotype, while combined inactivation of Xlf/Mri, Xlf/Paxx, or Xlf/Dna-pkcs leads to late embryonic lethality. Here, we describe three new mouse models. We demonstrate that deletion of Trp53 rescues embryonic lethality in mice with combined deficiencies of Xlf and Mri. Furthermore, Xlf-/-Mri-/-Trp53+/- and Xlf-/-Paxx-/-Trp53+/- mice possess reduced body weight, severely reduced mature lymphocyte counts, and accumulation of progenitor B cells. We also report that combined inactivation of Mri/Paxx results in live-born mice with modest phenotype, and combined inactivation of Mri/Dna-pkcs results in embryonic lethality. Therefore, we conclude that XLF is functionally redundant with MRI and PAXX during lymphocyte development in vivo. Moreover, Mri genetically interacts with Dna-pkcs and Paxx.
ARTICLE | doi:10.20944/preprints202003.0079.v1
Subject: Engineering, Control & Systems Engineering Keywords: micro segmented genetic algorithm; multicore embedded system; parallel processing
Online: 5 March 2020 (03:23:59 CET)
This paper presents a novel micro-segmented genetic algorithm (μsGA) to identify the best solution for the locomotion of a quadruped robot designed on a rectangular ABS plastic platform. We compare our algorithm with three similar algorithms found in the specialized literature: a standard genetic algorithm (GA), a micro-genetic algorithm (μGA), and a micro artificial immune system (μAIS). The quadruped robot prototype guarantees the same conditions for each test. The platform was developed using 3D printing for the structure and can accommodate the mechanisms, sensors, servomechanisms as actuators. It also has an internal battery and a multicore embedded system (mES) to process and control the robot locomotion. This research proposes a μsGA that segments the individual into specific bytes. μGA techniques are applied to each segment to reduce the processing time; the same benefits as the GA are obtained, while the use of a computer and the high computational resources characteristic of the GA are avoided. This is the reason why some research in robot locomotion is limited to simulation. The results show that the performance of μsGA is better than the three other algorithms (GA, μGA and AIS). The processing time was reduced using a mES architecture that enables parallel processing, meaning that the requirements for resources and memory were reduced. This research solves the problem of continuous locomotion of a quadruped robot, and gives a feasible solution with real performance parameters using a μsGA bio-micro algorithm and a mES architecture.
REVIEW | doi:10.20944/preprints201911.0286.v1
Subject: Life Sciences, Genetics Keywords: diversity; conservation; animal genetic resources; indigenous pigs; southern Africa
Online: 24 November 2019 (14:47:39 CET)
Pig genetic resources in Africa originate from different regions. Genetic analysis has shown a strong phylogeographic pattern with the pigs on the eastern parts showing a high frequency of alleles from the Far East while the ones on the western parts show a strong European influence. This highlights the influence of trade routes on the genetic legacy of African pigs. They have, however, since adapted to the local environments to produce unique populations with unique attributes. Most of the pigs are now reared in resource-constrained smallholdings under free-range conditions. They are largely owned by women who spread ownership of the resource through kinship networks. Very little work has been done to characterize, conserve and sustainably utilize pig genetic resources in Southern Africa. The risk status of the breeds together with population numbers, distribution and other attributes are largely unknown. This paper proposes several strategies for the sustainable utilization of the pig genetic resources: a market-driven in situ conservation program and two complementary ex situ strategies. In addition, the possibility of community-based breed improvement programs is discussed.
Subject: Life Sciences, Genetics Keywords: Sickle cell disease; genetic disorder; fetal hemoglobin; hemoglobinopathy; Tanzania
Online: 20 September 2019 (11:47:39 CEST)
Sickle cell disease (SCD) is a blood disorder caused by a point mutation on the beta globin gene resulting in the synthesis of abnormal hemoglobin. Fetal hemoglobin (HbF) reduces disease severity, but the levels vary from one individual to another. Most research has focused on common variants which differ across populations and hence do not fully account for HbF variation. To investigate rare and common variants influencing HbF levels in SCD, we performed targeted next generation sequencing covering exonic and other significant fetal hemoglobin-associated loci, including BCL11A, MYB, HOXA9, HBB, HBG1, HBG2, CHD4, KLF1, MBD3, ZBTB7A and PGLYRP1. Results revealed a range of functionally relevant genetic variants. Notably, there were significantly more deletions in individuals with high HbF levels (11% vs 0.9%). We identified frameshift deletion in individuals with high HbF levels and frameshift insertions in individuals with low HbF. CHD4 and MBD3 genes, interacting in the same sub-network, were identified to have a significant number of pathogenic or non-synonymous mutations in individuals with low HbF levels, suggesting an important role of epigenetic pathways in the regulation of HbF synthesis. This study provides new insights in selecting essential variants associated with extreme HbF levels in SCD.
ARTICLE | doi:10.20944/preprints201805.0144.v1
Subject: Life Sciences, Molecular Biology Keywords: citrus breeding; diversity; genetic similarity; Lime; molecular markers; PCR
Online: 9 May 2018 (11:05:37 CEST)
Acid lime [Citrus aurantifolia (Christm.) Swingle] is a fruit crop, enriched with high commercial value and is cultivated in 60 out of 75 districts representing all geographical landscapes of Nepal. Lack of high yielding cultivars is probably one of the main reason for its extremely reduced productivity which warrants a deep understanding of genetic diversity in existing germplasm. Hereby, we aim to access the genetic diversity of acid lime germplasm cultivated at 3-different ecological gradients of eastern Nepal employing PCR-based Inter-Simple Sequence Repeats markers (ISSR). Altogether, 21 polymorphic ISSR markers were used to assess the genetic diversity in 60 acid lime cultivars sampled from different geographical locations. Analysis of binary data matrix was performed on the basis of bands obtained, scoring of the data was done accordingly, and principal coordinate analysis and phenogram were constructed using different computer algorithms. ISSR profiling yielded 234 amplicons, of which 87.18% were found to be polymorphic. The number of amplified fragments ranged from 7-18 with amplicon size ranging from 250-3200 bp. The NTSYS based Cluster analysis using UPGMA algorithm taking Dice Similarity coefficient separated 60 accessions into 2-major and 3-minor clusters. The genetic diversity analysis revealed the highest for Terai and the lowest for High-hill zone. Cluster I comprised of accessions from High-hill and Mid-hill regions revealing the close genetic relationship, whereas cluster II comprised of accessions from all three agro-ecological zones and the exotic varieties. Furthermore, our results revealed the accessions harvested from different geographical gradients were not genetically distinct, but highest diversity was observed in Terai accessions in comparison to the regions belonging to the High and Mid-hills. Thus, our data indicate that the ISSR provides a better option for evaluating the genetic diversity of Nepalese Acid Lime cultivars and furnished significant information, assisting parental selection in current and future breeding programs and germplasm conservation which ultimately may help to provide a technological breakthrough for the farmers of the developing country like Nepal.
ARTICLE | doi:10.20944/preprints201712.0129.v1
Subject: Engineering, Automotive Engineering Keywords: semi-active suspension; feed energy; parameter optimization; genetic algorithm
Online: 19 December 2017 (06:53:01 CET)
In order to coordinate the damping performance and energy regenerative performance of energy regenerative suspension, this paper proposes a structure of vehicle semi-active energy regenerative suspension with electro-hydraulic actuator (EHA). In light of the proposed concept, a specific energy regenerative scheme is designed and the mechanical properties test is carried out. Based on the test results, the parameter identification for the system model is conducted using recursive least squares algorithm. On the basis of system principle, the nonlinear model of the semi-active energy regenerative suspension with EHA is built. Meanwhile, LQG control strategy of the system is designed. And then the influence of the main parameters of EHA on the damping performance and energy regenerative performance of suspension is analyzed. Finally, the main parameters of EHA actuator are optimized via genetic algorithm. The test results show that when sinusoidal is input at the frequency of 2Hz and the amplitude of 30mm, the spring mass acceleration RMS value of optimized EHA semi-active energy regenerative suspension is reduced by 22.23% and energy regenerative power RMS value is increased by 40.51%, which means while meeting the requirements of certain vehicle ride comfort and driving safety, energy regenerative performance is improved significantly.
ARTICLE | doi:10.20944/preprints201705.0081.v1
Subject: Engineering, Electrical & Electronic Engineering Keywords: optimization; simulated annealing; genetic algorithm; power losses; power consumption
Online: 9 May 2017 (10:45:49 CEST)
In this paper a variable’s involved in assessing the quality of a distributed generation system are reviewed, aiming to minimize the electric power losses (unused power consumption) and optimize the voltage profile. To provide this assessment, several experiments have been made to the IEEE 34-bus test case and various actual test cases with the respect of multiple DG units. The possibility and effectiveness of the proposed algorithm for optimal placement and sizing of DG in distribution systems have been verified. Finally, four algorithms were trailed: simulated annealing (SA), hybrid genetic algorithm (HGA), genetic algorithm (GA) and variable neighbourhood search. The HGA algorithm was found to produce the best solution at a cost of longer processing time.
ARTICLE | doi:10.20944/preprints201607.0015.v1
Subject: Mathematics & Computer Science, Numerical Analysis & Optimization Keywords: Redundancy Allocation Problem, Genetic Algorithm, Simulated Annealing, Greedy Algorithm
Online: 9 July 2016 (05:13:42 CEST)
We present a very computationally light and fast approximation algorithm and then verify it with genetic algorithm and simulated annealing. We show that our algorithm is on par with GA and SA in terms of output produced while having a tightly bounded time complexity. Our algorithm works best when there is a strong positive correlation between the reliability of a component and its cost. We present two algorithms with the same essence. One of them is system cost bounded and the other is target reliability bounded. Our proposed algorithm works on a subsystem level redundancy instead of component level redundancy.