Search results for: candidate selection

Authors: Ebraheem Al-Jouri, Youssef Abu-Ahmad, Ramasamy Srinivasan

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The parasitoid, Diadegma semiclausum (Hymenoptera: Ichneumonidae) is one of the most effective exotic parasitoids of diamondback moth (DBM), Plutella xylostella in the lowland areas of Homs, Syria. Molecular evolution studies are useful tools to shed light on the molecular bases of insect geographical spread and adaptation to new hosts and environment and for designing better control strategies. In this study, molecular evolution analysis was performed based on the 42 nuclear internal transcribed spacer-2 (ITS2) sequences representing the D. semiclausum and eight other Diadegma spp. from Syria and worldwide. Possible recombination events were identified by RDP4 program. Four potential recombinants of the American D. insulare and D. fenestrale (Jeju) were detected. After detecting and removing recombinant sequences, the ratio of non-synonymous (dN) to synonymous (dS) substitutions per site (dN/dS=ɷ) has been used to identify codon positions involved in adaptive processes. Bayesian techniques were applied to detect selective pressures at a codon level by using five different approaches including: fixed effects likelihood (FEL), internal fixed effects likelihood (IFEL), random effects method (REL), mixed effects model of evolution (MEME) and Program analysis of maximum liklehood (PAML). Among the 40 positively selected amino acids (aa) that differed significantly between clades of Diadegma species, three aa under positive selection were only identified in D. semiclausum. Additionally, all D. semiclausum branches tree were highly found under episodic diversifying selection (EDS) at p≤0.05. Our study provide evidence that both recombination and positive selection have contributed to the molecular diversity of Diadegma spp. and highlights the significant contribution of D. semiclausum in adaptive evolution and influence the fitness in the DBM parasitoid.

Keywords: diadegma sp, DBM, ITS2, phylogeny, recombination, dN/dS, evolution, positive selection

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Authors: Chen Bo, Wen Zengping

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Based on the results of previous studies, we focus on the research of real ground motion selection and scaling method for structural performance-based seismic evaluation using nonlinear dynamic analysis. The input of earthquake ground motion should be determined appropriately to make them compatible with the site-specific hazard level considered. Thus, an optimized selection and scaling method are established including the use of not only Monte Carlo simulation method to create the stochastic simulation spectrum considering the multivariate lognormal distribution of target spectrum, but also a spectral shape parameter. Its applications in structural fragility analysis are demonstrated through case studies. Compared to the previous scheme with no consideration of the uncertainty of target spectrum, the method shown here can make sure that the selected records are in good agreement with the median value, standard deviation and spectral correction of the target spectrum, and greatly reveal the uncertainty feature of site-specific hazard level. Meanwhile, it can help improve computational efficiency and matching accuracy. Given the important infection of target spectrum’s uncertainty on structural seismic fragility analysis, this work can provide the reasonable and reliable basis for structural seismic evaluation under scenario earthquake environment.

Keywords: ground motion selection, scaling method, seismic fragility analysis, spectral shape

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Authors: Ravi Patel, Krishna K. Krishnan

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In global supply chains, appropriate and sustainable suppliers play a vital role in supply chain development and feasibility. In a larger organization with huge number of suppliers, it is necessary to divide suppliers based on their past history of quality and delivery of each product category. Since performance of any organization widely depends on their suppliers, well evaluated selection criteria and decision-making models lead to improved supplier assessment and development. In this paper, SCOR® performance evaluation approach and ISO standards are used to determine selection criteria for better utilization of supplier assessment by using hybrid model of Analytic Hierchchy Problem (AHP) and Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (FTOPSIS). AHP is used to determine the global weightage of criteria which helps TOPSIS to get supplier score by using triangular fuzzy set theory. Both qualitative and quantitative criteria are taken into consideration for the proposed model. In addition, a multi-product and multi-time period model is selected for order allocation. The optimization model integrates multi-objective integer linear programming (MOILP) for order allocation and a hybrid approach for supplier selection. The proposed MOILP model optimizes order allocation based on manufacturing process and product tolerances as per manufacturer’s requirement for quality product. The integrated model and solution approach are tested to find optimized solutions for different scenario. The detailed analysis shows the superiority of proposed model over other solutions which considered individual decision making models.

Keywords: AHP, fuzzy set theory, multi-criteria decision making, multi-objective integer linear programming, TOPSIS

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Authors: Rouhallah Bagheri, Morteza Mahmoudi, Hadi Moheb-Alizadeh

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In this paper, we develop a supplier selection and order allocation multi-objective model in stochastic environment in which purchasing cost, percentage of delivered items with delay and percentage of rejected items provided by each supplier are supposed to be stochastic parameters following any arbitrary probability distribution. To do so, we use dependent chance programming (DCP) that maximizes probability of the event that total purchasing cost, total delivered items with delay and total rejected items are less than or equal to pre-determined values given by decision maker. After transforming the above mentioned stochastic multi-objective programming problem into a stochastic single objective problem using minimum deviation method, we apply a genetic algorithm to get the later single objective problem solved. The employed genetic algorithm performs a simulation process in order to calculate the stochastic objective function as its fitness function. At the end, we explore the impact of stochastic parameters on the given solution via a sensitivity analysis exploiting coefficient of variation. The results show that as stochastic parameters have greater coefficients of variation, the value of objective function in the stochastic single objective programming problem is worsened.

Keywords: dependent chance programming, genetic algorithm, minimum deviation method, order allocation, supplier selection

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Authors: Abigail Tan, Heng Liang Tan, Vanessa Ding, James Hui, Eng Hin Lee, Andre Choo

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Introduction: Comparative oncology investigates the similarities in spontaneous carcinogenesis between humans and animals, in order to identify treatments that can benefit these patients. Companion animals (CA), like canines and felines, are of special interest when it comes to studying human cancers due to their exposure to the same environmental factors and develop tumours with similar features. The purpose of this study is to explore the cross-reactivity of monoclonal antibodies (mAbs) across cancers in humans and CA. Material and Methods: A panel of CA mAbs generated in the lab was screened on multiple human cancer cell lines through flow cytometry to identify for positive binders. Shortlisted candidates were then characterised by biochemical and functional assays e.g., antibody-drug conjugate (ADC) and western blot assays, including glycan studies. Results: Candidate mAb KP52 was generated from whole-cell immunisation using feline mammary carcinoma. KP52 showed strong positive binding to human cancer cells, such as breast cancer and ovarian cancer. Furthermore, KP52 demonstrated strong killing ( > 50%) as an ADC with Saporin as the payload. Western blot results revealed the molecular weight of the antigen targets to be approximately 45kD and 50kD under reduced conditions. Glycan studies suggest that the epitope is glycan in nature, specifically an O-linked glycan. Conclusion: Candidate mAb KP52 has a therapeutic potential as an ADC against feline mammary cancer, human ovarian cancer, human mammary cancer, human pancreatic cancer, and human gastric cancer.

Keywords: ADC, comparative oncology, mAb, therapeutic

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Authors: Antonios Paraskevas, Michael Madas

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For a university to maintain its international competitiveness in education, it is essential to recruit qualitative academic staff as it constitutes its most valuable asset. This selection demonstrates a significant role in achieving strategic objectives, particularly by emphasizing a firm commitment to the exceptional student experience and innovative teaching and learning practices of high quality. In this vein, the appropriate selection of academic staff establishes a very important factor of competitiveness, efficiency and reputation of an academic institute. Within this framework, our work demonstrates a comprehensive methodological concept that emphasizes the multi-criteria nature of the problem and how decision-makers could utilize our approach in order to proceed to the appropriate judgment. The conceptual framework introduced in this paper is built upon a hybrid neutrosophic method based on the Neutrosophic Analytical Hierarchy Process (N-AHP), which uses the theory of neutrosophy sets and is considered suitable in terms of a significant degree of ambiguity and indeterminacy observed in the decision-making process. To this end, our framework extends the N-AHP by incorporating the Neutrosophic Delphi Method (N-DM). By applying the N-DM, we can take into consideration the importance of each decision-maker and their preferences per evaluation criterion. To the best of our knowledge, the proposed model is the first which applies the Neutrosophic Delphi Method in the selection of academic staff. As a case study, it was decided to use our method for a real problem of academic personnel selection, having as the main goal to enhance the algorithm proposed in previous scholars’ work, and thus taking care of the inherent ineffectiveness which becomes apparent in traditional multi-criteria decision-making methods when dealing with situations alike. As a further result, we prove that our method demonstrates greater applicability and reliability when compared to other decision models.

Keywords: multi-criteria decision making methods, analytical hierarchy process, delphi method, personnel recruitment, neutrosophic set theory

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Authors: L. Lamola, E. Manolas, A. Krause

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Background: The incidence of childhood cancer incidence is increasing gradually in low-middle income countries, such as South Africa. Globally, there is an extensive range of familial- and hereditary-cancer syndromes, where underlying germline variants increase the likelihood of developing cancer in childhood. Next-Generation Sequencing (NGS) technologies have been key in determining the occurrence and genetic contribution of germline variants to paediatric cancer development. We aimed to design and evaluate a candidate gene panel specific to inherited cancer-predisposing genes to provide a comprehensive insight into the contribution of germline variants to childhood cancer. Methods: 32 paediatric patients (aged 0-18 years) diagnosed with a malignant tumour were recruited, and biological samples were obtained. After quality control, DNA was sequenced using an ion Ampliseq 50 candidate gene panel design and Ion Torrent S5 technologies. Sequencing variants were called using Ion Torrent Suite software and were subsequently annotated using Ion Reporter and Ensembl's VEP. High priority variants were manually analysed using tools such as MutationTaster, SIFT-INDEL and VarSome. Putative identified candidates were validated via Sanger Sequencing. Results: The patients studied had a variety of cancers, the most common being nephroblastoma (13), followed by osteosarcoma (4) and astrocytoma (3). We identified 10 pathogenic / likely pathogenic variants in 10 patients, most of which were novel. Conclusions: According to the literature, we expected ~10% of our patient population to harbour pathogenic or likely pathogenic germline variants, however, we reported about 3 times (~30%) more than we expected. Majority of the identified variants are novel; this may be because this is the first study of its kind in an understudied South African population.

Keywords: Africa, genetics, germline-variants, paediatric-cancer

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Authors: Edward K. Boahen, Brunel E. Bouya-Moko, Changda Wang

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The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with the feature selection. Research available on supervised learning (machine learning) has limitations with the feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this paper discusses the various behaviours of the OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by the previous schemes. We detailed our proposed optimized nonsymmetric deep auto-encoder (OPT_NDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using the NSL-KDD and KDDCUP'99 datasets in a graphical user interface enabled Weka application. The results obtained indicate that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection with an accuracy rate of 99.86%.

Keywords: computer security, network security, online social network, account compromisation

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Authors: Antonios Paraskevas, Michael Madas

Abstract:

For a university to maintain its international competitiveness in education, it is essential to recruit qualitative academic staff as it constitutes its most valuable asset. This selection demonstrates a significant role in achieving strategic objectives, particularly by emphasizing a firm commitment to exceptional student experience and innovative teaching and learning practices of high quality. In this vein, the appropriate selection of academic staff establishes a very important factor of competitiveness, efficiency and reputation of an academic institute. Within this framework, our work demonstrates a comprehensive methodological concept that emphasizes on the multi-criteria nature of the problem and on how decision makers could utilize our approach in order to proceed to the appropriate judgment. The conceptual framework introduced in this paper is built upon a hybrid neutrosophic method based on the Neutrosophic Analytical Hierarchy Process (N-AHP), which uses the theory of neutrosophy sets and is considered suitable in terms of significant degree of ambiguity and indeterminacy observed in decision-making process. To this end, our framework extends the N-AHP by incorporating the Neutrosophic Delphi Method (N-DM). By applying the N-DM, we can take into consideration the importance of each decision-maker and their preferences per evaluation criterion. To the best of our knowledge, the proposed model is the first which applies Neutrosophic Delphi Method in the selection of academic staff. As a case study, it was decided to use our method to a real problem of academic personnel selection, having as main goal to enhance the algorithm proposed in previous scholars’ work, and thus taking care of the inherit ineffectiveness which becomes apparent in traditional multi-criteria decision-making methods when dealing with situations alike. As a further result, we prove that our method demonstrates greater applicability and reliability when compared to other decision models.

Keywords: analytical hierarchy process, delphi method, multi-criteria decision maiking method, neutrosophic set theory, personnel recruitment

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Authors: Serhat Tüzün, Tufan Demirel

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The objective of the present study is to select the most suitable location for a wind power plant station through Choquet integral method. The problem of selecting the location for a wind power station was considered as a multi-criteria decision-making problem. The essential and sub-criteria were specified and location selection was expressed in a hierarchic structure. Among the main criteria taken into account in this paper are wind potential, technical factors, social factors, transportation, and costs. The problem was solved by using different approaches of Choquet integral and the best location for a wind power station was determined. Then, the priority weights obtained from different Choquet integral approaches are compared and commented on.

Keywords: multi-criteria decision making, choquet integral, fuzzy sets, location of a wind power plant

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Authors: Senem Suna

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Extraction of bioactive compounds from several food/food products comes as an important topic and new trend related with health promoting effects. As a result of the increasing interest in natural foods, different methods are used for the acquisition of these components especially polyphenols. However, special attention has to be paid to the selection of proper techniques or several processing technologies (supercritical fluid extraction, microwave-assisted extraction, ultrasound-assisted extraction, powdered extracts production) for each kind of food to get maximum benefit as well as the obtainment of phenolic compounds. In order to meet consumer’s demand for healthy food and the management of quality and safety requirements, advanced research and development are needed. In this review, advantages, and disadvantages of different extraction methods, their opportunities to be used in food industry and the effects of polyphenols are mentioned in details. Consequently, with the evaluation of the results of several studies, the selection of the most suitable food specific method was aimed.

Keywords: bioactives, extraction, powdered extracts, supercritical fluid extraction

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Authors: Sabrina S. W. Chan, Emily Schwartzman, Nicholas O. Rule

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Past literature showed mixed findings on how smiling affects a person’s chance of getting hired. On one hand, smiling suggests enthusiasm, cooperativeness, and enthusiasm, which can elicit positive impressions. On the other hand, smiling can suggest weaker professionalism or a filler to hide nervousness, which can lower a candidate’s perceived competence. Emotion expressions can also be perceived differently depending on the person’s gender and can activate certain gender stereotypes. Women especially face a double bind with respect to hiring decisions and smiling. Because women are socially expected to smile more, those who do not smile will be considered stereotype incongruent. This becomes a noisy signal to employers and may lower their chance of being hired. However, women’s smiling as a formality may also be an obstacle. They are more likely to put on fake smiles; but if they do, they are also likely to be perceived as inauthentic and over-expressive. This paper sought to investigate how smiling affects hiring decisions, and whether this relationship is moderated by gender. In Study 1, participants were shown a series of smiling and emotionally neutral face images, incorporated into fabricated LinkedIn profiles. Participants were asked to rate how hireable they thought that candidate was. Results showed that participants rated smiling candidates as more hireable than nonsmiling candidates, and that there was no difference in gender. Moreover, individuals who did not study business were more biased in their perceptions than those who did. Since results showed a trending favoritism over female targets, in suspect of desirability bias, a second study was conducted to collect implicit measures behind the decision-making process. In Study 2, a mouse-tracking design was adopted to explore whether participants’ implicit attitudes were different from their explicit responses on hiring. Participants asked to respond whether they would offer an interview to a candidate. Findings from Study 1 was replicated in that smiling candidates received more offers than neutral-faced candidates. Results also showed that female candidates received significantly more offers than male candidates but was associated with higher attractiveness ratings. There were no significant findings in reaction time or change of decisions. However, stronger hesitation was detected for responses made towards neutral targets when participants perceived the given position as masculine, implying a conscious attempt of making situational judgments (e.g., considering candidate’s personality and job fit) to override automatic processing (evaluations based on attractiveness). Future studies would look at how these findings differ for positions which are stereotypically masculine (e.g., surgeons) and stereotypically feminine (e.g., kindergarten teachers). Current findings have strong implications for developing bias-free hiring policies in workplace, especially for organizations who maintain online/hybrid working arrangements in the post-pandemic era. This also bridges the literature gap between face perception and gender discrimination, highlighting how engendered facial cues can affect individual’s career development and organization’s success in diversity and inclusion.

Keywords: engendered facial cues, face perception, gender stereotypes, hiring decisions, smiling, workplace discrimination

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Authors: Diteboho Xaba, Kolentino Mpeta, Tlotliso Qejoe

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This paper assesses the in-sample forecasting of the South African exchange rates comparing a linear ARIMA model and a SETAR model. The study uses a monthly adjusted data of South African exchange rates with 420 observations. Akaike information criterion (AIC) and the Schwarz information criteria (SIC) are used for model selection. Mean absolute error (MAE), root mean squared error (RMSE) and mean absolute percentage error (MAPE) are error metrics used to evaluate forecast capability of the models. The Diebold –Mariano (DM) test is employed in the study to check forecast accuracy in order to distinguish the forecasting performance between the two models (ARIMA and SETAR). The results indicate that both models perform well when modelling and forecasting the exchange rates, but SETAR seemed to outperform ARIMA.

Keywords: ARIMA, error metrices, model selection, SETAR

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for the classification of an unstructured format description for identification of file formats. The main contribution of this work is the employment of data mining techniques to support file format selection with just the unstructured text description that comprises the most important format features for a particular organisation. Subsequently, the file format indentification method employs file format classifier and associated configurations to support digital preservation experts with an estimation of required file format. Our goal is to make use of a format specification knowledge base aggregated from a different Web sources in order to select file format for a particular institution. Using the naive Bayes method, the decision support system recommends to an expert, the file format for his institution. The proposed methods facilitate the selection of file format and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and specifications of file formats. To facilitate decision-making, the aggregated information about the file formats is presented as a file format vocabulary that comprises most common terms that are characteristic for all researched formats. The goal is to suggest a particular file format based on this vocabulary for analysis by an expert. The sample file format calculation and the calculation results including probabilities are presented in the evaluation section.

Keywords: data mining, digital libraries, digital preservation, file format

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Authors: Feijoo E. Colomine Duran, Carlos E. Peñaloza Corredor

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There modeling component selection financial investment (Portfolio) a variety of problems that can be addressed with optimization techniques under evolutionary schemes. For his feature, the problem of selection of investment components of a dichotomous relationship between two elements that are opposed: The Portfolio Performance and Risk presented by choosing it. This relationship was modeled by Markowitz through a media problem (Performance) - variance (risk), ie must Maximize Performance and Minimize Risk. This research included the study and implementation of multi-objective evolutionary techniques to solve these problems, taking as experimental framework financial market equities Colombia Stock Exchange between 2009-2015. Comparisons three multiobjective evolutionary algorithms, namely the Nondominated Sorting Genetic Algorithm II (NSGA-II), the Strength Pareto Evolutionary Algorithm 2 (SPEA2) and Indicator-Based Selection in Multiobjective Search (IBEA) were performed using two measures well known performance: The Hypervolume indicator and R_2 indicator, also it became a nonparametric statistical analysis and the Wilcoxon rank-sum test. The comparative analysis also includes an evaluation of the financial efficiency of the investment portfolio chosen by the implementation of various algorithms through the Sharpe ratio. It is shown that the portfolio provided by the implementation of the algorithms mentioned above is very well located between the different stock indices provided by the Colombia Stock Exchange.

Keywords: finance, optimization, portfolio, Markowitz, evolutionary algorithms

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Authors: Magdalena Jablonska, Andrzej Falkowski

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The negativity effect is one of the most intriguing and well-studied psychological phenomena that can be observed in many areas of human life. The aim of the following study is to investigate how valence framing and positive and negative information about political candidates affect judgments about similarity to an ideal and bad politician. Based on the theoretical framework of features of similarity, it is hypothesized that negative features have a stronger effect on similarity judgments than positive features of comparable value. Furthermore, the mediating role of affect is tested. Method: One hundred sixty-one people took part in an experimental study. Participants were divided into 6 research conditions that differed in the reference point (positive vs negative framing) and the number of favourable and unfavourable information items about political candidates (a positive, neutral and negative candidate profile). In positive framing condition, the concept of an ideal politician was primed; in the negative condition, participants were to think about a bad politician. The effect of independent variables on similarity judgments, affective evaluation, and voting intention was tested. Results: In the positive condition, the analysis showed that the negative effect of additional unfavourable features was greater than the positive effect of additional favourable features in judgements about similarity to the ideal candidate. In negative framing condition, ANOVA was insignificant, showing that neither the addition of positive features nor additional negative information had a significant impact on the similarity to a bad political candidate. To explain this asymmetry, two mediational analyses were conducted that tested the mediating role of affect in the relationship between similarity judgments and voting intention. In both situations the mediating effect was significant, but the comparison of two models showed that the mediation was stronger for a negative framing. Discussion: The research supports the negativity effect and attempts to explain the psychological mechanism behind the positive-negative asymmetry. The results of mediation analyses point to a stronger mediating role of affect in the relationship between cognitive evaluation and voting intention. Such a result suggests that negative comparisons, leading to the activation of negative features, give rise to stronger emotions than positive features of comparable strength. The findings are in line with positive-negative asymmetry, however, by adopting Tversky’s framework of features of similarity, the study integrates the cognitive mechanism of the negativity effect delineated in the contrast model of similarity with its emotional component resulting from the asymmetrical effect of positive and negative emotions on decision-making.

Keywords: affect, framing, negativity effect, positive-negative asymmetry, similarity judgements

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Authors: Wafa’ Alma'Aitah, Khaled Almakadmeh

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this study presents an information retrieval system of using genetic algorithm to increase information retrieval efficiency. Using vector space model, information retrieval is based on the similarity measurement between query and documents. Documents with high similarity to query are judge more relevant to the query and should be retrieved first. Using genetic algorithms, each query is represented by a chromosome; these chromosomes are fed into genetic operator process: selection, crossover, and mutation until an optimized query chromosome is obtained for document retrieval. Results show that information retrieval with adaptive crossover probability and single point type crossover and roulette wheel as selection type give the highest recall. The proposed approach is verified using (242) proceedings abstracts collected from the Saudi Arabian national conference.

Keywords: genetic algorithm, information retrieval, optimal queries, crossover

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Authors: Lian Zeng

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Double-Spear 1-H2-1 (DS1-H2-1) is an oncolytic virus and an innovative biological drug candidate. The chemical composition of the drug product is a live attenuated West Nile virus (WNV) containing the human T cell costimulator (CD86) gene. After intratumoral injection, the virus can rapidly self-replicate in the injected site and lyse/kill the tumor by repeated infection among tumor cells. We also established xenograft tumor models in mice to evaluate the drug candidate's efficacy on those tumors. The results from preclinical studies on transplanted tumors in immunodeficient mice showed that DS1-H2-1 had significant oncolytic effects on human-origin cancers: it completely (100%) shrieked human glioma; limited human neuroblastoma growth reached as high as 95% growth inhibition rate (%TGITW). The safety data of preclinical animal experiments confirmed that DS1-H2-1 is safe as a biological drug for clinical use. In the preclinical drug efficacy experiment, virus-drug administration with different doses did not show abnormal signs and disease symptoms in more than 300 tested mice, and no side effects or death occurred through various administration routes. Intravenous administration did not cause acute infectious disease or other side effects. However, the replication capacity of the virus in tumor tissue via intravenous administration is only 1% of that of direct intratumoral administration. The direct intratumoral administration of DS1-H2-1 had a higher rate of viral replication. Therefore, choosing direct intratumoral injection can ensure both efficacy and safety.

Keywords: oncolytic virus, WNV-CD86, immunotherapy drugs, glioma, neuroblastoma

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Authors: Yasmine Ahmed Shemeis

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Determining the impact of productivity increases on wage levels is often difficult due to the unavailability of individual-level productivity data. Accordingly, we proxy for productivity using a self-perceived measure of health based on the postulated positive relationship between better health and productivity improvements. Using Egypt’s labour market data for the years 2012 and 2018 and utilizing a Maximum Likelihood Estimation method, we address two issues: the endogeneity of health in the estimation of wages and a sample selection bias. Our findings indicate the great value that better health has in enhancing wage levels in Egypt’s private sector. Also, we find that overlooking the endogeneity of health underestimates its effect on wages. Thus, the improvement of health states is likely to be beneficial in improving labour market outcomes in terms of wages as well as labour productivity in Egypt.

Keywords: labour, Productivity, Wages, Endogeneity, Sample Selection

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Authors: Jianan Sun, Ziwen Ye

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Multidimensional computerized adaptive testing (MCAT) is a popular research topic in psychometrics. It is important for practitioners to clearly know the item-trait patterns of administered items when a test like MCAT is operated. Item-trait pattern recognition refers to detecting which latent traits in a psychological test are measured by each of the specified items. If the item-trait patterns of the replenished items in MCAT item pool are well detected, the interpretability of the items can be improved, which can further promote the abilities of the examinees who attending the MCAT to be accurately estimated. This research explores to solve the item-trait pattern recognition problem of the replenished items in MCAT item pool from the perspective of statistical variable selection. The popular multidimensional item response theory model, multidimensional two-parameter logistic model, is assumed to fit the response data of MCAT. The proposed method uses the least absolute shrinkage and selection operator (LASSO) to detect item-trait patterns of replenished items based on the essential information of item responses and ability estimates of examinees collected from a designed MCAT procedure. Several advantages of the proposed method are outlined. First, the proposed method does not strictly depend on the relative order between the replenished items and the selected operational items, so it allows the replenished items to be mixed into the operational items in reasonable order such as considering content constraints or other test requirements. Second, the LASSO used in this research improves the interpretability of the multidimensional replenished items in MCAT. Third, the proposed method can exert the advantage of shrinkage method idea for variable selection, so it can help to check item quality and key dimension features of replenished items and saves more costs of time and labors in response data collection than traditional factor analysis method. Moreover, the proposed method makes sure the dimensions of replenished items are recognized to be consistent with the dimensions of operational items in MCAT item pool. Simulation studies are conducted to investigate the performance of the proposed method under different conditions for varying dimensionality of item pool, latent trait correlation, item discrimination, test lengths and item selection criteria in MCAT. Results show that the proposed method can accurately detect the item-trait patterns of the replenished items in the two-dimensional and the three-dimensional item pool. Selecting enough operational items from the item pool consisting of high discriminating items by Bayesian A-optimality in MCAT can improve the recognition accuracy of item-trait patterns of replenished items for the proposed method. The pattern recognition accuracy for the conditions with correlated traits is better than those with independent traits especially for the item pool consisting of comparatively low discriminating items. To sum up, the proposed data-driven method based on the LASSO can accurately and efficiently detect the item-trait patterns of replenished items in MCAT.

Keywords: item-trait pattern recognition, least absolute shrinkage and selection operator, multidimensional computerized adaptive testing, variable selection

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Authors: Omar Boutkhoum, Mohamed Hanine, Abdessadek Bendarag

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Sustainable economic growth is nowadays driving firms to extend toward the adoption of many green supply chain management (GSCM) solutions. However, the evaluation and selection of these solutions is a matter of concern that needs very serious decisions, involving complexity owing to the presence of various associated factors. To resolve this problem, a comparative analysis approach based on multi-criteria decision-making methods is proposed for adequate evaluation of sustainable supply chain management solutions. In the present paper, we propose an integrated decision-making model based on FAHP (Fuzzy Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) to contribute to a better understanding and development of new sustainable strategies for industrial organizations. Due to the varied importance of the selected criteria, FAHP is used to identify the evaluation criteria and assign the importance weights for each criterion, while TOPSIS and PROMETHEE methods employ these weighted criteria as inputs to evaluate and rank the alternatives. The main objective is to provide a comparative analysis based on TOPSIS and PROMETHEE processes to help make sound and reasoned decisions related to the selection problem of GSCM solution.

Keywords: GSCM solutions, multi-criteria analysis, decision support system, TOPSIS, FAHP, PROMETHEE

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Authors: Nivedita Paul

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Marriages in India are part and parcel of kinship and cultural practices. Marriage practices differ in India because of cross-regional diversities in social relations which itself has evolved as a result of causal relationship between space and culture. As the place is important for the formation of culture and other social structures, therefore there is regional differentiation in cultural practices and marital customs. Based on the cultural practices some scholars have divided India into North and South kinship regions where women in the North get married early and have lesser autonomy compared to women in the South where marriages are mostly consanguineous. But, the emergence of new modes and alternative strategies such as matrimonial advertisements becoming popular, as well as the increase in women’s literacy and work force participation, matchmaking process in India has changed to some extent. The present study uses data from Indian Human Development Survey II (2011-12) which is a nationally representative multitopic survey that covers 41,554 households. Currently married women of age group 15-49 in their first marriage; whose year of marriage is from the 1970s to 2000s have been taken for the study. Based on spouse selection experiences, the sample of women has been divided into three marriage categories-self, semi and family arranged. Women in self-arranged or love marriage is the sole decision maker in choosing the partner, in semi-arranged marriage or arranged marriage with consent both parents and women together take the decision, whereas in family arranged or arranged marriage without consent only parents take the decision. The main aim of the study is to show the spatial and regional variations in spouse selection decision making. The basis for regionalization has been taken from Irawati Karve’s pioneering work on kinship studies in India called Kinship Organization in India. India is divided into four kinship regions-North, Central, South and East. Since this work was formulated in 1953, some of the states have experienced changes due to modernization; hence these have been regrouped. After mapping spouse selection patterns using GIS software, it is found that the northern region has mostly family arranged marriages (around 64.6%), the central zone shows a mixed pattern since family arranged marriages are less than north but more than south and semi-arranged marriages are more than north but less than south. The southern zone has the dominance of semi-arranged marriages (around 55%) whereas the eastern zone has more of semi-arranged marriage (around 53%) but there is also a high percentage of self-arranged marriage (around 42%). Thus, arranged marriage is the dominant form of marriage in all four regions, but with a difference in the degree of the involvement of the female and her parents and relatives.

Keywords: spouse selection, consent, kinship, regional pattern

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Authors: Y. Kourd, D. Lefebvre

Abstract:

The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. This paper proposes a method of fault diagnosis based on a neuro-fuzzy hybrid structure. This hybrid structure combines the selection of threshold and decision tree. The validation of this method is obtained with the DAMADICS benchmark. In the first phase of the method, a model will be constructed that represents the normal state of the system to fault detection. Signatures of the faults are obtained with residuals analysis and selection of appropriate thresholds. These signatures provide groups of non-separable faults. In the second phase, we build faulty models to see the flaws in the system that cannot be isolated in the first phase. In the latest phase we construct the tree that isolates these faults.

Keywords: decision tree, residuals analysis, ANFIS, fault diagnosis

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Authors: Shen Jian, Hu Jie, Qi Jin, Liu Wei Jie, Chen Ji Yi, Peng Ying Hong

Abstract:

In order to settle the problem of acquiring case in biological related to design problems, a biometrics instance acquisition method based on text mining is presented. Through the construction of corpus text vector space and knowledge mining, the feature selection, similarity measure and case retrieval method of text in the field of biology are studied. First, we establish a vector space model of the corpus in the biological field and complete the preprocessing steps. Then, the corpus is retrieved by using the vector space model combined with the functional keywords to obtain the biological domain examples related to the design problems. Finally, we verify the validity of this method by taking the example of text.

Keywords: text mining, vector space model, feature selection, biologically inspired design

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Authors: Alieh Farshbaf

Abstract:

Introduction: Current anti-retroviral drugs have some restrictions for treatment of HIV-1 infection. The efficacy of retroviral drugs is not same in different infected patients and the virus rebound from latent reservoirs after stopping them. Recently, the engineering of stem cells and gene therapy provide new approaches to eliminate some drug problems by induction of resistance to HIV-1. Literature review: Up to now, AIDS-restriction genes (ARGs) were suitable candidate for gene and cell therapies, such as cc-chemokine receptor-5 (CCR5). In this manner, CCR5 provide effective cure in Berlin and Boston patients by inducing of HIV-1 resistance with allogeneic stem cell transplantation. It is showed that Zinc Finger Nuclease (ZFN) could induce HIV-1 resistance in stem cells of infected patients by homologous recombination or non-end joining mechanism and eliminate virus loading after returning the modified cells. Then, gene modification by HIV restriction factors, as TRIM5, introduced another gene candidate for HIV by interfering in infection process. These gene modifications/editing provided by stem cell futures that improve treatment in refractory disease such as HIV-1. Conclusion: Although stem cell transplantation has some complications, but in compare to retro-viral drugs demonstrated effective cure by elimination of virus loading. On the other hand, gene therapy is cost-effective for an infected patient than retroviral drugs payment in a person life-long. The results of umbilical cord blood stem cell transplantation showed that gene and cell therapy will be applied easier than previous treatment of AIDS with high efficacy.

Keywords: stem cell, AIDS, gene modification, cell engineering

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Authors: Ezeni Brzovska, Durdana Ozretic-Dosen

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The purpose of this paper is to deepen the understanding of the product cues that influence purchase decision for a specific product category – chocolate, and to identify demographic differences in the buying behavior. ANOVA was employed for analyzing the significance level for nine product cues, and the survey showed statistically significant differences among different age and gender groups, and between respondents with different levels of education. From the theoretical perspective, the study adds to the existing knowledge by contributing with the research results from the new environment (Southeast Europe, Macedonia), which has been neglected so far. Establishing the level of significance for the product cues that affect buying behavior in the chocolate consumption context might help managers to improve marketing decision-making, and better meet consumer needs through identifying opportunities for packaging innovations and/or personalization toward different target groups.

Keywords: chocolate consumption context, chocolate selection, demographic characteristics, product cues

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Authors: Paul W. Murray, Marco Barajas

Abstract:

Recent changes in supply chains, especially globalization and collaboration, have created new risks for enterprises of all sizes. A variety of complex frameworks, often based on enterprise risk management strategies have been presented under the heading of Supply Chain Risk Management (SCRM). The literature on promotes the benefits of a robust SCRM strategy; however, implementing SCRM is difficult and resource demanding for Large Enterprises (LEs), and essentially out of reach for Small and Medium Enterprises (SMEs). This research debunks the idea that SCRM is necessary for all enterprises and instead proposes a simple and effective Vendor Selection Template (VST). Empirical testing and a survey of supply chain practitioners provide a measure of validation to the VST. The resulting VSTis a valuable contribution because is easy to use, provides practical results, and is sufficiently flexible to be universally applied to SMEs.

Keywords: multiple regression analysis, supply chain management, risk assessment, vendor selection

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Authors: Atena Sadat Hosseini, Mohammadhossein Habibi

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Acute myeloid leukemia (AML) is the most typically diagnosed leukemia. In older adults, AML imposes a dismal outcome. AML originates with a dominant mutation, then adds collaborative, transformative mutations leading to myeloid transformation and clinical/biological heterogeneity. Several chemotherapeutic drugs are used for this cancer. These drugs are naturally associated with several side effects, and finding a more accurate molecular mechanism of these drugs can have a significant impact on the selection and better candidate of drugs for treatment. In this study, we evaluated bortezomibin myeloma cells using bioinformatics analysis and evaluation of RNA-Seq data. Then investigated the molecular pathways proteins- proteins interactions associated with this chemotherapy drug. A total of 658upregulated genes and 548 downregulated genes were sorted.AUF1 (hnRNP D0) binds and destabilizes mRNA, degradation of GLI2 by the proteasome, the role of GTSE1 in G2/M progression after G2 checkpoint, TCF dependent signaling in response to WNT demonstrated in upregulated genes. Besides insulin resistance, AKT phosphorylates targets in the nucleus, cytosine methylation, Longevity regulating pathway, and Signal Transduction of S1P Receptor were related to low expression genes. With respect to this results, HIST2H2AA3, RP11-96O20.4, ZED9, PRDX1, and DOK2, according to node degrees and betweenness elements candidates from upregulated genes. in the opposite side, PYURF, NRSN1, FGF23, UPK3BL, and STAG3 were a prominent role in downregulated genes. Sum up, Using in silico analysis in the present study, we conducted a precise study ofbortezomib molecular mechanisms in myeloma cells. so that we could take further evaluation to discovermolecular cancer therapy. Naturally, more additional experimental and clinical procedures are needed in this survey.

Keywords: myeloma cells, acute myeloid leukemia, bioinformatics analysis, bortezomib

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Authors: Othman E. Othman, Hassan R. Darwish, Amira M. Nowier

Abstract:

Lactoferrin (LF) is a multifunctional protein involved in economically production traits like milk protein composition and skeletal structure in small ruminants including sheep and goat. So, LF gene - with its genetic polymorphisms associated with production traits - is considered a candidate genetic marker used in marker-assisted selection in goats. This study aimed to identify the different alleles and genotypes of this gene in three Egyptian goat breeds using PCR-SSCP (polymerase chain reaction-single-strand conformation polymorphism) and DNA sequencing. Genomic DNA was extracted from 120 animals belonging to Barki, Zaraibi, and Damascus goat breeds. Using specific primers, PCR amplified 247-bp fragments from exon 2 of LF goat gene. The PCR products were subjected to Single-Strand Conformation Polymorphism (SSCP) technique. The results showed the presence of two genotypes GG and AG in the tested animals. The frequencies of both genotypes varied among the three tested breeds with the highest frequencies of GG genotype in all tested goat breeds. The sequence analysis of PCR products representing these two detected genotypes declared the presence of an SNP (single nucleotide polymorphisms) substitution (G/A) among G and A alleles of this gene. The association between different LF genotypes and milk composition as well as body measurement was estimated. The comparison showed that the animals possess AG genotypes are superior over those with GG genotypes for different parameters of milk protein compositions and skeletal structures. This finding declared that allele A of LF gene is considered the promising marker for the productive traits in goat. In conclusion, the Egyptian goat breeds will be needed to enhance their milk protein composition and growth trait parameters through the increasing of allele A frequency in their herds depending on the superior production traits of this allele in goats.

Keywords: lLactoferrin gene, PCR-SSCP, SNPs, Egyptian goat

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Authors: M. Mohemmed Sha, T. Manesh, A. Ahmed Mohamed Mustaq

Abstract:

In this corporate world, the technology of Web services has grown rapidly and its significance for the development of web based applications gradually rises over time. The success of Business to Business integration rely on finding novel partners and their services in a global business environment. But the selection of the most suitable Web service from the list of services with the identical functionality is more vital. The satisfaction level of the customer and the provider’s reputation of the Web service are primarily depending on the range it reaches the customer’s requirements. In most cases the customer of the Web service feels that he is spending for the service which is undelivered. This is because the customer always thinks that the real functionality of the web service is not reached. This will lead to change of the service frequently. In this paper, a framework is proposed to evaluate the Quality of Service (QoS) and its cost that makes the optimal correlation between each other. Also this research work proposes some management decision against the functional deviancy of the web service that are guaranteed at time of selection.

Keywords: web service, service level agreement, quality of a service, cost of a service, QoS, CoS, SOA, WSLA, WsRF

Procedia PDF Downloads 384