Search results for: linear regression models

Authors: Kong Ngai Pei

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The argument scheme approach to argumentation has two components. One is to identify the recurrent patterns of inferences used in everyday discourse. The second is to devise critical questions to evaluate the inferences in these patterns. Although this approach is intuitive and contains many insightful ideas, it has been noted to be not free of problems. One is that due to its disavowing the probability calculus, it cannot give the exact strength of an inference. In order to tackle this problem, thereby paving the way to a more complete normative account of argument strength, it has been proposed, the most promising way is to combine the scheme-based approach with Bayesian networks (BNs). This paper pursues this line of thought, attempting to combine three common schemes, Appeal to Ignorance, Composition, and Division, with BNs. In the first part, it is argued that most (if not all) formulations of the critical questions corresponding to these schemes in the current argumentation literature are incomplete and not very informative. To remedy these flaws, more thorough and precise formulations of these questions are provided. In the second part, how to use graphical idioms (e.g. measurement and synthesis idioms) to translate the schemes as well as their corresponding critical questions to graphical structure of BNs, and how to define probability tables of the nodes using functions of various sorts are shown. In the final part, it is argued that many misuses of these schemes, traditionally called fallacies with the same names as the schemes, can indeed be adequately accounted for by the BN models proposed in this paper.

Keywords: appeal to ignorance, argument schemes, Bayesian networks, composition, division

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Authors: Kseniia Zviagintseva, Brett Buttliere

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Science is fundamentally a problem-solving enterprise, and scientists pay more attention to the negative things, that cause them dissonance and negative affective state of uncertainty or contradiction. While this is agreed upon by philosophers of science, there are few empirical demonstrations. Here we examine the keywords from those papers published by PLoS in 2014 and show with several sentiment analyzers that negative keywords are studied more than positive keywords. Our dataset is the 927,406 keywords of 32,870 scientific articles in all fields published in 2014 by the journal PLOS ONE (collected from Altmetric.com). Counting how often the 47,415 unique keywords are used, we can examine whether those negative topics are studied more than positive. In order to find the sentiment of the keywords, we utilized two sentiment analysis tools, Hu and Liu (2004) and SentiStrength (2014). The results below are for Hu and Liu as these are the less convincing results. The average keyword was utilized 19.56 times, with half of the keywords being utilized only 1 time and the maximum number of uses being 18,589 times. The keywords identified as negative were utilized 37.39 times, on average, with the positive keywords being utilized 14.72 times and the neutral keywords - 19.29, on average. This difference is only marginally significant, with an F value of 2.82, with a p of .05, but one must keep in mind that more than half of the keywords are utilized only 1 time, artificially increasing the variance and driving the effect size down. To examine more closely, we looked at those top 25 most utilized keywords that have a sentiment. Among the top 25, there are only two positive words, ‘care’ and ‘dynamics’, in position numbers 5 and 13 respectively, with all the rest being identified as negative. ‘Diseases’ is the most studied keyword with 8,790 uses, with ‘cancer’ and ‘infectious’ being the second and fourth most utilized sentiment-laden keywords. The sentiment analysis is not perfect though, as the words ‘diseases’ and ‘disease’ are split by taking 1st and 3rd positions. Combining them, they remain as the most common sentiment-laden keyword, being utilized 13,236 times. More than just splitting the words, the sentiment analyzer logs ‘regression’ and ‘rat’ as negative, and these should probably be considered false positives. Despite these potential problems, the effect is apparent, as even the positive keywords like ‘care’ could or should be considered negative, since this word is most commonly utilized as a part of ‘health care’, ‘critical care’ or ‘quality of care’ and generally associated with how to improve it. All in all, the results suggest that negative concepts are studied more, also providing support for the notion that science is most generally a problem-solving enterprise. The results also provide evidence that negativity and contradiction are related to greater productivity and positive outcomes.

Keywords: bibliometrics, keywords analysis, negativity bias, positive and negative words, scientific papers, scientometrics

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Authors: E. Elgohary, R. Abdelazyz

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The research aims to clarify the effect of the marketing culture on improving the e-service quality for foreign and domestic information technology companies in the Arab Republic of Egypt. So the researcher sought to include the dimensions of the marketing culture, which are (customer service, management style, sales mission, internal communications, technology, wages and rewards, innovation) as measures of marketing culture for its effect on improving the e-service quality in this research. The research population consists of employees and customers of the companies under study. The research problem was the following question: What is the effect of the actual application of marketing culture on improving the e-service quality? To answer that, three main hypotheses were adopted, and they were tested by statistical means for the data collected through a questionnaire prepared and distributed for this purpose. Accordingly, the research presented a set of results, the most important of which are: the need to pay attention to the dimensions of the marketing culture to improve the e-service quality, foreign companies were the most popular companies in applying the marketing culture compared to local companies. The research also recommends designing a system to continuously measure the performance of electronic service providers and work on spreading the culture of innovation among employees, linking reward programs to the extent of commitment to applying the elements of marketing culture while doing business.

Keywords: marketing culture, e-service quality, measurement models, quality measurements

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Authors: Filippo Verre

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This paper explores Turkey’s role as an influential waterpower in the Middle East, emphasizing the Peace Water Pipeline Project (PWPP) as a paradigm of hydro solidarity rather than conventional water diplomacy. Hydro solidarity transcends the strategic and often competitive nature of water diplomacy, highlighting cooperative, inclusive, and mutually beneficial approaches to water resource management. The PWPP, which aimed to transport freshwater from Turkey’s Manavgat River to several water-scarce nations in the Middle East, exemplifies this ethos. By providing a reliable water supply to address the chronic shortages in the region, the project underscored Turkey’s commitment to fostering regional cooperation, stability, and collective well-being through shared water resources. This paper provides an in-depth analysis of the Peace Water Pipeline Project, examining its technical specifications, environmental impact, and political implications. It discusses how the project’s foundation on principles of hydro solidarity could facilitate stronger regional ties, mitigate water-related conflicts, and promote sustainable development. By prioritizing collective benefits over unilateral gains, Turkey’s approach exemplified a transformative model of resource sharing that could inspire similar initiatives globally. This paper argues that the Peace Water Pipeline Project serves as a crucial case study in demonstrating how shared natural resources can be leveraged to build trust, enhance cooperation, and achieve common goals in a geopolitically volatile region. The findings emphasize the importance of adopting hydro solidarity as a guiding principle for future transboundary water projects, showcasing how collaborative water management can play a pivotal role in fostering peace, security, and sustainable development in the Middle East and beyond. This research is based on a mixed methodological approach combining qualitative and quantitative methods. The most relevant qualitative methods will involve Case Studies and Content Analysis. Concretely, the Friendship Dam Project (FDP) between Turkey and Syria will be mentioned to underline the importance of hydro solidarity approaches as opposed to water diplomacy. Analyzing this case aims to identify factors that contribute to successful hydro solidarity agreements, such as effective communication channels, trust-building measures, and adaptive management practices. Concerning Content Analysis, reviewing and analyzing policy documents, treaties, media reports, and public statements will help identify the official narratives and discourses surrounding the PWPP. This method fully comprehends how different stakeholders frame the issues and what solutions they propose. The quantitative methodology used in this research, which complements the qualitative approaches, involves economic valuation, which quantifies the PWPP’s economic impacts on Turkey and the Middle Eastern region. This includes assessing the cost of construction and maintenance and the financial benefits derived from improved water access and reduced conflict. Hydrological modelling will also be used as a quantitative research method. Using hydrological models to simulate the water flow and distribution scenarios helps quantify the pipeline’s potential impacts on water resources. By assessing the sustainability of water extraction and predicting how changes in water availability might affect different regions, these models play a crucial role in this research, shedding light on the impact of transboundary infrastructures on water management.

Keywords: hydro-solidarity, Middle East, transboundary water management, peace water pipeline project, water scarcity

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Authors: H. Mokaddem, D. Miroud, N. Azouaou, F. Si-Ahmed, Z. Sadaoui

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The synthesis and characterization of activated carbon from local lignocellulosic precursor (Algerian alfa) was carried out for the removal of cationic dyes from aqueous solutions. The effect of the production variables such as impregnation chemical agents, impregnation ratio, activation temperature and activation time were investigated. Carbon obtained using the optimum conditions (CaCl2/ 1:1/ 500°C/2H) was characterized by various analytical techniques scanning electron microscopy (SEM), infrared spectroscopic analysis (FTIR) and zero-point-of-charge (pHpzc). Adsorption tests of methylene blue on the optimal activated carbon were conducted. The effects of contact time, amount of adsorbent, initial dye concentration and pH were studied. The adsorption equilibrium examined using Langmuir, Freundlich, Temkin and Redlich–Peterson models reveals that the Langmuir model is most appropriate to describe the adsorption process. The kinetics of MB sorption onto activated carbon follows the pseudo-second order rate expression. The examination of the thermodynamic analysis indicates that the adsorption process is spontaneous (ΔG ° < 0) and endothermic (ΔH ° > 0), the positive value of the standard entropy shows the affinity between the activated carbon and the dye. The present study showed that the produced optimal activated carbon prepared from Algerian alfa is an effective low-cost adsorbent and can be employed as alternative to commercial activated carbon for removal of MB dye from aqueous solution.

Keywords: activated carbon, adsorption, cationic dyes, Algerian alfa

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Authors: Benjamas Penboon, Zachary Zimmer, Aree Jampaklay

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Cambodia is a country where labor migration has been consistently high. Coupled with advancing labor opportunities in urban areas, a function partly of globalization, this is resulting in massive migration out of rural areas. This is particularly true in Cambodia where there are high migration and a very large proportion of adult children living some distant from their parents. This paper explores characteristics associated with migrant providing support to parents in rural Cambodia. With reference to perspectives of family altruism and solidarity, this analysis particularly focusses on how a series of variables representing family integration and residential location associates with intergenerational monetary and instrumental support from migrants. The study hypothesizes that migrants are more likely to provide support when parents are in need, and there are no alternative means of support. Data come from The Rural Household Survey (N=3,713), part of the 2011 Cambodian Rural Urban Migration Project (CRUMP). Multilevel multinomial models indicate international migrants are likely to give money, while internal migrants are likely to provide both money and instrumental support, especially when migrants have no sibling and their parent in poor health status. In addition, employed migrants are two times providing monetary compared to those unemployed. Findings elucidate the decision to which and why support occurs more often when no other source of support exists and also depends on the ability to provide of migrants themselves.

Keywords: migration, left-behind parent, intergenerational relations, support, rural, Cambodia

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Authors: Arsalan Hassan Pour, Mansoureh Jeihani, Samira Ahangari

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Distracted driving has been one of the most integral concerns surrounding our daily use of vehicles since the invention of the automobile. While much attention has been recently given to cell phones related distraction, commercial billboards along roads are also candidates for drivers' visual and cognitive distractions, as they may take drivers’ eyes from the road and their minds off the driving task to see, perceive and think about the billboard’s content. Using a driving simulator and a head-mounted eye-tracking system, speed change, acceleration, deceleration, throttle response, collision, lane changing, and offset from the center of the lane data along with gaze fixation duration and frequency data were collected in this study. Some 92 participants from a fairly diverse sociodemographic background drove on a simulated freeway in Baltimore, Maryland area and were exposed to three different billboards to investigate the effects of billboards on drivers’ behavior. Participants glanced at the billboards several times with different frequencies, the maximum of which occurred on the billboard with the highest cognitive load. About 74% of the participants didn’t look at billboards for more than two seconds at each glance except for the billboard with a short visible area. Analysis of variance (ANOVA) was performed to find the variations in driving behavior when they are invisible, readable, and post billboards area. The results show a slight difference in speed, throttle, brake, steering velocity, and lane changing, among different areas. Brake force and deviation from the center of the lane increased in the readable area in comparison with the visible area, and speed increased right after each billboard. The results indicated that billboards have a significant effect on driving performance and visual attention based on their content and visibility status. Generalized linear model (GLM) analysis showed no connection between participants’ age and driving experience with gaze duration. However, the visible distance of the billboard, gender, and billboard content had a significant effect on gaze duration.

Keywords: ANOVA, billboards, distracted driving, drivers' behavior, driving simulator, eye-Tracking system, GLM

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Authors: H.-H. Doh, J.-M. Yu, Y.-J. Kwon, J.-H. Shin, H.-W. Kim, S.-H. Nam, D.-H. Lee

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This paper suggests a decision tree based approach for flexible job shop scheduling with multiple process plans, i. e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decision variables are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. As an extension of the priority scheduling approach that selects the best priority rule combination after many simulation runs, this study suggests a decision tree based approach in which a decision tree is used to select a priority rule combination adequate for a specific system state and hence the burdens required for developing simulation models and carrying out simulation runs can be eliminated. The decision tree based scheduling approach consists of construction and scheduling modules. In the construction module, a decision tree is constructed using a four-stage algorithm, and in the scheduling module, a priority rule combination is selected using the decision tree. To show the performance of the decision tree based approach suggested in this study, a case study was done on a flexible job shop with reconfigurable manufacturing cells and a conventional job shop, and the results are reported by comparing it with individual priority rule combinations for the objectives of minimizing total flow time and total tardiness.

Keywords: flexible job shop scheduling, decision tree, priority rules, case study

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Authors: Estibe Dagne Mekonnen

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In recent years, the prevalence of undernourishment was 30 percent for sub-Saharan Africa, compared with 16 percent for Asia and the Pacific (Ali, 2011). In Ethiopia, almost 40 percent of the total population in the country and 57 percent of Addis Ababa population lives below the international poverty line of US$ 1.25 per day (UNICEF, 2009). This study aims to analyze the determinant of household food secrity in Addis Ababa city administration. Primary data were collected from a survey of 256 households in the selected sub-city, namely Addis Ketema, Arada, and Kolfe Keranio, in the year 2022. Both Purposive and multi-stage cluster random sampling procedures were employed to select study areas and respondents. Descriptive statistics and order logistic regression model were used to test the formulated hypotheses. The result reveals that out of the total sampled households, 25% them were food secured, 13% were mildly food insecure, 26% were moderately food insecure and 36% were severely food insecure. The study indicates that household family size, house ownership, household income, household food source, household asset possession, household awareness on inflation, household access to social protection program, household access to credit and saving and household access to training and supervision on food security have a positive and significant effect on the likelihood of household food security status. However, marital status of household head, employment sector of household head, dependency ratio and household’s nonfood expenditure has a negative and significant influence on household food security status. The study finally suggests that the government in collaboration with financial institutions and NGO should work on sustaining household food security by creating awareness, providing credit, facilitate rural-urban linkage between producer and consumer and work on urban infrastructure improvement. Moreover, the governments also work closely and monitor consumer good suppliers, if possible find a way to subsidize consumable goods to more insecure households and make them to be food secured. Last but not least, keeping this country’s peace will play a crucial role to sustain food security.

Keywords: determinants, household, food security, order logit model, Addis Ababa

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Authors: Xiang-Yao Zheng, Jen-Cheng Wang, Joe-Air Jiang

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Improving the line ampacity while using existing power grids is an important issue that electricity dispatchers are now facing. Using the information provided by the dynamic thermal rating (DTR) of transmission lines, an overhead power grid can operate safely. However, dispatchers usually lack real-time DTR information. Thus, this study proposes a long-short-term memory (LSTM)-based method, which is one of the neural network models. The LSTM-based method predicts the DTR of lines using the weather data provided by Central Weather Bureau (CWB) of Taiwan. The possible thermal bottlenecks at different locations along the line and the margin of line ampacity can be real-time determined by the proposed LSTM-based prediction method. A case study that targets the 345 kV power grid of TaiPower in Taiwan is utilized to examine the performance of the proposed method. The simulation results show that the proposed method is useful to provide the information for the smart grid application in the future.

Keywords: electricity dispatch, line ampacity prediction, dynamic thermal rating, long-short-term memory neural network, smart grid

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Authors: K. Kannapathi-Naidoo

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The higher education landscape has undergone changes in the past decade, with concepts such as blended learning, online learning, and hybrid models appearing more frequently in research and practice. The year 2020 marked a mass migration from face-to-face learning and more traditional forms of education to online learning in higher education institutions across the globe due to the Covid-19 pandemic. As a result, contact learning students and lecturing staff alike were thrust into the world of online learning at an unprecedented pace. Traditional modes of learning had to be amended, and pedagogical strategies required adjustments. This study was located within a compulsory first-year academic literacy module in a higher education institution. The study aimed to explore students’ learning preferences between online, face-face, and blended learning within the context of academic literacy. Data was collected through online qualitative questionnaires administered to 150 first-year students, which were then analysed thematically. The findings of the study revealed that 48.5% of the participants preferred a blended learning approach to academic literacy. The main themes that emerged in support of their preference were best of both worlds, flexibility, productivity, and lecturer accessibility. As a result, this paper advocates for the blended learning approach for academic literacy skills-based modules.

Keywords: academic literacy, blended learning, online learning, student learning preferences

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Authors: Enoch F. Sam, Kris Brijs, Stijn Daniels, Tom Brijs, Geert Wets

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Notwithstanding the growing body of literature that recognises the importance of personal safety to public transport (PT) users, it remains unclear what PT users consider regarding their safety. In this study, we explore the criteria PT users in Ghana use to assess bus safety. This knowledge will afford a better understanding of PT users’ risk perceptions and assessments which may contribute to theoretical models of PT risk perceptions. We utilised phenomenological research methodology, with data drawn from 61 purposively sampled participants. Data collection (through focus group discussions and in-depth interviews) and analyses were done concurrently to the point of saturation. Our inductive data coding and analyses through the constant comparison and content analytic techniques resulted in 4 code categories (conceptual dimensions), 27 codes (safety items/criteria), and 100 quotations (data segments). Of the number of safety criteria participants use to assess bus safety, vehicle condition, driver’s marital status, and transport operator’s safety records were the most considered. With each criterion, participants rightly demonstrated its respective relevance to bus safety. These findings imply that investment in and maintenance of safer vehicles, and responsible and safety-conscious drivers, and prioritization of passengers’ safety are key-targets for public bus/minibus operators in Ghana.

Keywords: safety evaluations, public bus/minibus, passengers, phenomenology, Ghana

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Authors: Rahul Paul, Kedar Nath Das

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The field of machine learning (ML) is experiencing rapid development, resulting in a multitude of theoretical advancements and extensive practical implementations across various disciplines. The objective of ML is to facilitate the ability of machines to perform cognitive tasks by leveraging knowledge gained from prior experiences and effectively addressing complex problems, even in situations that deviate from previously encountered instances. Reinforcement Learning (RL) has emerged as a prominent subfield within ML and has gained considerable attention in recent times from researchers. This surge in interest can be attributed to the practical applications of RL, the increasing availability of data, and the rapid advancements in computing power. At the same time, optimization algorithms play a pivotal role in the field of ML and have attracted considerable interest from researchers. A multitude of proposals have been put forth to address optimization problems or improve optimization techniques within the domain of ML. The necessity of a thorough examination and implementation of optimization algorithms within the context of ML is of utmost importance in order to provide guidance for the advancement of research in both optimization and ML. This article provides a comprehensive overview of the application of metaheuristic evolutionary optimization algorithms in conjunction with RL to address a diverse range of scientific challenges. Furthermore, this article delves into the various challenges and unresolved issues pertaining to the optimization of RL models.

Keywords: machine learning, reinforcement learning, loss function, evolutionary optimization techniques

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Authors: Nishant Parashar, Sawan S. Sinha, Balaji Srinivasan

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We perform an investigation of the unclosed terms in the evolution equation of the velocity gradient tensor (VGT) in compressible decaying turbulent flow. Velocity gradients in a compressible turbulent flow field influence several important nonlinear turbulent processes like cascading and intermittency. In an attempt to understand the dynamics of the velocity gradients various researchers have tried to model the unclosed terms in the evolution equation of the VGT. The existing models proposed for these unclosed terms have limited applicability. This is mainly attributable to the complex structure of the higher order gradient terms appearing in the evolution equation of VGT. We investigate these higher order gradients using the data from direct numerical simulation (DNS) of compressible decaying isotropic turbulent flow. The gas kinetic method aided with weighted essentially non-oscillatory scheme (WENO) based flow- reconstruction is employed to generate DNS data. By applying neural-network to the DNS data, we map the structure of the unclosed higher order gradient terms in the evolution of the equation of the VGT with VGT itself. We validate our findings by performing alignment based study of the unclosed higher order gradient terms obtained using the neural network with the strain rate eigenvectors.

Keywords: compressible turbulence, neural network, velocity gradient tensor, direct numerical simulation

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Authors: Maomao Cao

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Background and aims While the association between higher consumption of fish and lower liver cancer risk has been confirmed, however, the association between specific fish intake and liver cancer risk remains unknown. We aimed to identify the association between specific fish consumption and the risk of liver cancer. Methods: Based on a community-based seropositive hepatitis B cohort involving 18404 individuals, face to face interview was conducted by a standardized questionnaire to acquire baseline information. Three common fish types in this study were analyzed, including freshwater fish, sea fish, and small fish (shrimp, crab, conch, and shell). All participants received liver cancer screening, and possible cases were identified by CT or MRI. Multivariable logistic models were applied to estimate the odds ratio (OR) and 95% confidence intervals (CI). Multivariate multiple imputations were utilized to impute observations with missing values. Results: 179 liver cancer cases were identified. Consumption of freshwater fish and sea fish at least once a week had a strong inverse association with liver cancer risk compared with the lowest intake level, with an adjusted OR of 0.53 (95% CI, 0.38-0.75) and 0.38 (95% CI, 0.19-0.73), respectively. This inverse association was also observed after the imputation. There was no statistically significant association between intake of small fish and liver cancer risk (OR=0.58, 95%, CI 0.32-1.08). Conclusions: Our findings suggest that consumption of freshwater fish and sea fish at least once a week could reduce liver cancer risk.

Keywords: cross-sectional study, fish intake, liver cancer, risk factor

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Authors: Julie A. Baldwin, Robert T. Trotter, Mark Remiker, C. Loren Buck, Amanda Aguirre, Trudie Milner, Emma Torres, Frank A. von Hippel

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Introduction: In the past, there have been concerns about contaminants in the water sources in Yuma, Arizona, including the Colorado River. Prolonged exposure to contaminants, such as perchlorate and heavy metals, can lead to deleterious health effects in humans. This project examined the association between the concentration of environmental contaminants and patient health outcomes in Yuma residents, using a community-engaged approach to data collection. Methods: A community-engaged design allowed community partners and researchers to establish joint research goals, recruit participants, collect data, and formulate strategies for dissemination of findings. Key informant interviews were conducted to evaluate adherence to models of community-based research. Results: The training needs, roles, and expectations of community partners varied based on available resources, prior research experience, and perceived research challenges and ways to address them. Conclusions: Leveraging community-engaged approaches for studies of environmental contamination in marginalized communities can expedite recruitment efforts and stimulate action that can lead to improved community health.

Keywords: community engaged research, environmental contaminants, underserved populations, health equity

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Authors: Zafer Cakmak, Birol Bulut, Cengiz Taskiran

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Technological advances, the world becoming smaller and increasing world population increase our interdependence with individuals that we maybe never meet face to face. It is impossible for the modern individuals to escape global developments and their impact. Furthermore, it is very unlikely for the global societies to turn back from the path they are in. These effects of globalization in fact encumber the humankind at a certain extend. We succumb to these responsibilities for we desire a better future, a habitable world and a more peaceful life. In the present study, global responsibility levels of the participants were measured and the significance of global reactions that individuals have to develop on global issues was reinterpreted under the light of the existing literature. The study was conducted with general survey model, one of the survey methodologies General survey models are surveys conducted on the whole universe or a group, sample or sampling taken from the universe to arrive at a conclusion about the universe, which includes a high number of elements. The study was conducted with data obtained from 350 pre-service teachers attending 2016 spring semester to determine 'Global Social Responsibility' levels of social studies pre-service teachers based on several variables. Collected data were analyzed using SPSS 21.0 software. T-test and ANOVA were utilized in the data analysis.

Keywords: social studies, globalization, global social responsibility, education

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Authors: Yinghui Shang, Ziqing Zhou, Rong Han, Hang Wang, Xiaodi Liu, Yong Yang

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The design of advanced amorphous solids, such as metallic glasses, with targeted properties through artificial intelligence signifies a paradigmatic shift in physical metallurgy and materials technology. Here, we developed a machine-learning architecture that facilitates the generation of metallic glasses with targeted multifunctional properties. Our architecture integrates the state-of-the-art unsupervised generative adversarial network model with supervised models, allowing the incorporation of general prior knowledge derived from thousands of data points across a vast range of alloy compositions, into the creation of data points for a specific type of composition, which overcame the common issue of data scarcity typically encountered in the design of a given type of metallic glasses. Using our generative model, we have successfully designed copper-based metallic glasses, which display exceptionally high hardness or a remarkably low modulus. Notably, our architecture can not only explore uncharted regions in the targeted compositional space but also permits self-improvement after experimentally validated data points are added to the initial dataset for subsequent cycles of data generation, hence paving the way for the customized design of amorphous solids without human intervention.

Keywords: metallic glass, artificial intelligence, mechanical property, automated generation

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Authors: Oti Ibiam, Alexanda O. Kalu

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Human Resource Accounting is the process of identifying and measuring data about human resources and communicating this information to interested parties in order to meaningful investment decisions. In recent time, firms focus has shifted to human resource accounting so as to ensure efficiency and effectiveness in their operations. This study focused on the effect of human resource accounting on the financial performance of Banks in Nigerian. The problem that led to the study revolves around the current trend whereby Nigeria banks do not efficiently account for the input of human resource in their annual statement, thereby instead of capitalizing human resources in their statement of financial position; they expend it in their income statement thereby reducing their profit after tax. The broad objective of this study is to determine the extent to which human resource accounting affects the financial performance and value of Nigerian Banks. This study is therefore considered significant because, there are still universally, grey areas to be sorted out on the subject matter of human resources accounting. In the bid to achieve the study objectives, the researcher gathered data from sixteen commercial banks. Data were collected from both primary and secondary sources using an ex-post facto research design. The data collected were then tabulated and analyzed using the multiple regression analysis. The result of hypothesis one revealed that there is a significant relationship between Capitalized Human Resource Cost and post capitalization Profit before tax of banks in Nigeria. The finding of hypothesis two revealed that the association between Capitalized Human Resource Cost and post capitalization Net worth of banks in Nigeria is significant. The finding in Hypothesis three reveals that there is a significant difference between pre and post capitalization profit before tax of banks in Nigeria. The study concludes that human resources accounting positively influenced financial performance of banks in Nigeria within the period under study. It is recommended that standards should be set for human resources identification and measurement in the banking sector and also the management of commercial banks in Nigeria should have a proper appreciation of human resource accounting. This will enable managers to take right decision regarding investment in human resource. Also, the study recommends that policies on enhancing the post capitalization profit before tax of banks in Nigeria should pay great attention to capitalized human resources cost, net worth and total asset as the variables significantly influenced post capitalization profit before tax of the studied banks in Nigeria. The limitation of the study centers on the limited number of years and companies that was adopted for the study.

Keywords: capitalization, human resources cost, profit before tax, net worth

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Authors: M. Aboudalle, Le Btth, M. Sari, F. Meftah

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In parallel with the appearance of new materials, brick masonry had and still has an essential part of the construction market today, with new technical challenges in designing bricks to meet additional requirements. Being used in structural applications, predicting the performance of clay brick masonry allows a significant cost reduction, in terms of practical experimentation. The behavior of masonry walls depends on the behavior of their elementary components, such as bricks, joints, and coatings. Therefore, it is necessary to consider it at different scales (from the scale of the intrinsic material to the real scale of the wall) and then to develop appropriate models, using numerical simulations. The work presented in this paper focuses on the mechanical characterization of the terracotta material at ambient temperature. As a result, the static Young’s modulus obtained from the flexural test shows different values in comparison with the compression test, as well as with the dynamic Young’s modulus obtained from the Impulse excitation of vibration test. Moreover, the Young's modulus varies according to the direction in which samples are extracted, where the values in the extrusion direction diverge from the ones in the orthogonal directions. Based on these results, hollow bricks can be considered as transversely isotropic bimodulus material.

Keywords: bimodulus material, hollow clay brick, ımpulse excitation of vibration, transversely isotropic material, young’s modulus

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Authors: George McMillan

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This paper introduces the methodology to create a baseline equation for the philosophical and social sciences in the behavioral-political-economic-demographic sequence. The two major ideological political-economic philosophies (Hume-Smith and Marx-Engels) are systematized into competing integrated three dimensional behavioral-political-economic models. The paper argues that Hume-Smith’s empathy-sympathy behavioral assumptions are a sufficient starting point to create the integrated causal model sought by Tooby and Cosmides. The author then shows that the prerequisite advances in psychology and demographic studies now exist to generate the universal economic theory sought by von Neumann-Morgenstern and the integrated behavioral-economic method of Gintis—a psychological (i.e., behavioral) socio-economic model. By updating Hume-Smith’s work with a modern understanding of psychology, as presented by Fromm and others, a new integrated societal model as postulated by Harsanyi can be created that intertwines the social and psychological sciences. The author argues that this fundamentally psychology-based model also can serve as a baseline equation for all social sciences as desired by Kant and Mach, as well as the ahistorical (psychological) philosophic model noted by Husserl, Heidegger, Tillich, and Strauss. The author concludes with a discussion of the necessary next steps to generating a detailed model that fuses these disciplines.

Keywords: Unified Social Theory

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Authors: Angela Maria Fasnacht

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Detection of anomalies due to contaminants’ presence, also known as early detection systems in water treatment plants, has become a critical point that deserves an in-depth study for their improvement and adaptation to current requirements. The design of these systems requires a detailed analysis and processing of the data in real-time, so it is necessary to apply various statistical methods appropriate to the data generated, such as Spearman’s Correlation, Factor Analysis, Cross-Correlation, and k-fold Cross-validation. Statistical analysis and methods allow the evaluation of large data sets to model the behavior of variables; in this sense, statistical treatment or analysis could be considered a vital step to be able to develop advanced models focused on machine learning that allows optimized data management in real-time, applied to early detection systems in water treatment processes. These techniques facilitate the development of new technologies used in advanced sensors. In this work, these methods were applied to identify the possible correlations between the measured parameters and the presence of the glyphosate contaminant in the single-pass system. The interaction between the initial concentration of glyphosate and the location of the sensors on the reading of the reported parameters was studied.

Keywords: glyphosate, emergent contaminants, machine learning, probes, sensors, predictive

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Authors: Olanrewaju Kafayat, O., Salman Kabir, K.

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The role of organic agriculture in providing food and income is now gaining wider recognition (Van Elzakker et al 2007). The increasing public concerns about food safety issues on the use of fertilizers, pesticide residues, growth hormones, GM organisms, and increasing awareness of environmental quality issues have led to an expanding demand for environmentally friendly products (Thompson, 1998; Rimal et al., 2005). As a result national governments are concerned about diet and health, and there has been renewed recognition of the role of public policy in promoting healthy diets, thus to provide healthier, safer, more confident citizens (Poole et al., 2007), With these benefits, a study into organic vegetables is very vital to all the major stakeholders. This study analyzed the willingness of consumers to pay for organic vegetables in Oyo state, Nigeria. Primary data was collected with the aid of structured questionnaire administered to 168 respondents. These were selected using multistage random sampling. The first stage involved the selection two (2) ADP zones out of the three (3) ADP zones in Oyo state, The second stage involved the random selection of two (2) local government areas each out of the two (2) ADP zones which are; Ibadan South West and Ogbomoso North and random selection of 4 wards each from the local government areas. The third stage involved random selection of 42 household each from of the local government areas. Descriptive statistics, the principal component analysis, and the logistic regression were used to analyze the data. Results showed 55 percent of the respondents were female while 80 percent were  50 years. 74 percent of the respondents agreed that organic vegetables are of better quality. 31 percent of the respondents were aware of organic vegetables as against 69 percent who were not aware. From the logistic model, educational attainment, amount spent on organic vegetables monthly, better quality of organic vegetables and accessibility to organic vegetables were significant and had a positive relationship on willingness to pay for organic vegetable. The variables that were significant and had a negative relationship with WTP are less attractiveness of organic vegetables and household size of the respondents. This study concludes that consumers with higher level of education were more likely to be aware and willing to pay for organic vegetables than those with low levels of education, the study therefore recommends creation of awareness on the relevance of consuming organic vegetables through effective marketing and educational campaigns.

Keywords: consumers awareness, willingness to pay, organic vegetables, Oyo State

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Authors: Fariba Tadayon, Elmira Hassanlou, Hasan Bagheri, Mostafa Jafarian

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Heavy metals are released into water, plants, soil, and food by natural and human activities. Lead has toxic roles in the human body and may cause serious problems even in low concentrations, since it may have several adverse effects on human. Therefore, determination of lead in different samples is an important procedure in the studies of environmental pollution. In this work, an ultrasonic assisted-ionic liquid based-liquid-liquid microextraction (UA-IL-DLLME) procedure for the determination of lead in zucchini, pomegranate, and lettuce has been established and developed by using flame atomic absorption spectrometer (FAAS). For UA-IL-DLLME procedure, 10 mL of the sample solution containing Pb2+ was adjusted to pH=5 in a glass test tube with a conical bottom; then, 120 μL of 1-Hexyl-3-methylimidazolium hexafluoro phosphate (CMIM)(PF6) was rapidly injected into the sample solution with a microsyringe. After that, the resulting cloudy mixture was treated by ultrasonic for 5 min, then the separation of two phases was obtained by centrifugation for 5 min at 3000 rpm and IL-phase diluted with 1 cc ethanol, and the analytes were determined by FAAS. The effect of different experimental parameters in the extraction step including: ionic liquid volume, sonication time and pH was studied and optimized simultaneously by using Response Surface Methodology (RSM) employing a central composite design (CCD). The optimal conditions were determined to be an ionic liquid volume of 120 μL, sonication time of 5 min, and pH=5. The linear ranges of the calibration curve for the determination by FAAS of lead were 0.1-4 ppm with R2=0.992. Under optimized conditions, the limit of detection (LOD) for lead was 0.062 μg.mL-1, the enrichment factor (EF) was 93, and the relative standard deviation (RSD) for lead was calculated as 2.29%. The levels of lead for pomegranate, zucchini, and lettuce were calculated as 2.88 μg.g-1, 1.54 μg.g-1, 2.18 μg.g-1, respectively. Therefore, this method has been successfully applied for the analysis of the content of lead in different food samples by FAAS.

Keywords: Dispersive liquid-liquid microextraction, Central composite design, Food samples, Flame atomic absorption spectrometry.

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Authors: Pankhuri Dagaonkar, Charumani Singh, Poornima Krothapalli, Krishna Karthik

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The backbone of any retail e-commerce success story is a unique design of supply chain network, providing the business an unparalleled speed and scalability. Primary goal of the supply chain strategy is to meet customer expectation by offering fastest deliveries while keeping the cost minimal. Meeting this objective at the large market that India provides is the problem statement that we have targeted here. There are many models and optimization techniques focused on network design to identify the ideal facility location and size, optimizing cost and speed. In this paper we are presenting a tactical approach to optimize cost of an existing network for a predefined speed. We have considered both forward and reverse logistics of a retail e-commerce supply chain consisting of multiple fulfillment (warehouse) and delivery centers, which are connected via sortation nodes. The mathematical model presented here determines if the shipment from a node should get sorted directly for the last mile delivery center or it should travel as consolidated package to another node for further sortation (resort). The objective function minimizes the total cost by varying the resort percentages between nodes and provides the optimal resource allocation and number of sorts at each node.

Keywords: distribution strategy, mathematical model, network design, supply chain management

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Authors: Abdelgawad, Salah El-Tahawy

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This paper aimed to establish econometrical equation models for the Nile delta region in Egypt, which will represent a basement for future predictions of Lumpy skin disease outbreaks and its pathway in relation to climate change. Data of lumpy skin disease (LSD) outbreaks were collected from the cattle farms located in the provinces representing the Nile delta region during 1 January, 2015 to December, 2015. The obtained results indicated that there was a significant association between the degree of the LSD outbreaks and the investigated climate factors (temperature, wind speed, and humidity) and the outbreaks peaked during the months of June, July, and August and gradually decreased to the lowest rate in January, February, and December. The model obtained depicted that the increment of these climate factors were associated with evidently increment on LSD outbreaks on the Nile Delta of Egypt. The model validation process was done by the root mean square error (RMSE) and means bias (MB) which compared the number of LSD outbreaks expected with the number of observed outbreaks and estimated the confidence level of the model. The value of RMSE was 1.38% and MB was 99.50% confirming that this established model described the current association between the LSD outbreaks and the change on climate factors and also can be used as a base for predicting the of LSD outbreaks depending on the climatic change on the future.

Keywords: LSD, climate factors, Nile delta, modeling

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Authors: Esra Polat

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Partial Least Squares Discriminant Analysis (PLSDA) is a statistical method for classification and consists a classical Partial Least Squares Regression (PLSR) in which the dependent variable is a categorical one expressing the class membership of each observation. PLSDA can be applied in many cases when classical discriminant analysis cannot be applied. For example, when the number of observations is low and when the number of independent variables is high. When there are missing values, PLSDA can be applied on the data that is available. Finally, it is adapted when multicollinearity between independent variables is high. The aim of this study is to determine the economic and/or demographic indicators, which are effective in grouping the 28 European Union (EU) member countries and 7 candidate countries (including potential candidates Bosnia and Herzegovina (BiH) and Kosova) by using the data set obtained from database of the World Bank for 2014. Leaving the political issues aside, the analysis is only concerned with the economic and demographic variables that have the potential influence on country’s eligibility for EU entrance. Hence, in this study, both the performance of PLSDA method in classifying the countries correctly to their pre-defined groups (candidate or member) and the differences between the EU countries and candidate countries in terms of these indicators are analyzed. As a result of the PLSDA, the value of percentage correctness of 100 % indicates that overall of the 35 countries is classified correctly. Moreover, the most important variables that determine the statuses of member and candidate countries in terms of economic indicators are identified as 'external balance on goods and services (% GDP)', 'gross domestic savings (% GDP)' and 'gross national expenditure (% GDP)' that means for the 2014 economical structure of countries is the most important determinant of EU membership. Subsequently, the model validated to prove the predictive ability by using the data set for 2015. For prediction sample, %97,14 of the countries are correctly classified. An interesting result is obtained for only BiH, which is still a potential candidate for EU, predicted as a member of EU by using the indicators data set for 2015 as a prediction sample. Although BiH has made a significant transformation from a war-torn country to a semi-functional state, ethnic tensions, nationalistic rhetoric and political disagreements are still evident, which inhibit Bosnian progress towards the EU.

Keywords: classification, demographic indicators, economic indicators, European Union, partial least squares discriminant analysis

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Authors: Greg Turner, Bin Lu, Cheer-Sun Yang

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As computing technology advances, smartphone applications can assist in student learning in a pervasive way. For example, the idea of using a mobile apps for the PA Common Trees, Pests, Pathogens, in the field as a reference tool allows middle school students to learn about trees and associated pests/pathogens without bringing a textbook. In the past, some researches study the mobile software Mobile Application Software Development Life Cycle (MADLC) including traditional models such as the waterfall model, or more recent Agile Methods. Others study the issues related to the software development process. Very little research is on the development of three heterogenous mobile systems simultaneously in a small university where the availability of developers is an issue. In this paper, we propose to use a hybride model of Waterfall Model and the Agile Model, known as the Relay Race Methodology (RRM) in practice, to reflect the concept of racing and relaying for scheduling. Based on the development project, we observe that the modeling of the transition between any two phases is manifested naturally. Thus, we claim that the RRM model can provide a de fecto rather than a de jure basis for the core concept in the MADLC. In this paper, the background of the project is introduced first. Then, the challenges are pointed out followed by our solutions. Finally, the experiences learned and the future work are presented.

Keywords: agile methods, mobile apps, software process model, waterfall model

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Authors: M. A. Talha, M. Osman Gani, M. Ferdows

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This paper focuses on the study of two dimensional magnetohydrodynamic (MHD) steady incompressible viscous Williamson nanofluid with exponential internal heat generation containing gyrotactic microorganism over a stretching sheet. The governing equations and auxiliary conditions are reduced to a set of non-linear coupled differential equations with the appropriate boundary conditions using similarity transformation. The transformed equations are solved numerically through spectral relaxation method. The influences of various parameters such as Williamson parameter γ, power constant λ, Prandtl number P_r, magnetic field parameter M, Peclet number P_e, Lewis number Le, Bioconvection Lewis number Lb, Brownian motion parameter Nb, thermophoresis parameter Nt, and bioconvection constant σ are studied to obtain the momentum, heat, mass and microorganism distributions. Moment, heat, mass and gyrotactic microorganism profiles are explored through graphs and tables. We computed the heat transfer rate, mass flux rate and the density number of the motile microorganism near the surface. Our numerical results are in better agreement in comparison with existing calculations. The Residual error of our obtained solutions is determined in order to see the convergence rate against iteration. Faster convergence is achieved when internal heat generation is absent. The effect of magnetic parameter M decreases the momentum boundary layer thickness but increases the thermal boundary layer thickness. It is apparent that bioconvection Lewis number and bioconvection parameter has a pronounced effect on microorganism boundary. Increasing brownian motion parameter and Lewis number decreases the thermal boundary layer. Furthermore, magnetic field parameter and thermophoresis parameter has an induced effect on concentration profiles.

Keywords: convection flow, similarity, numerical analysis, spectral method, Williamson nanofluid, internal heat generation

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Authors: Patti Kastanias, Wei Wang, Karyn Mackenzie, Sandra Robinson, Susan Wnuk

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Obesity is a worldwide epidemic and is recognized as a chronic disease. Pain in the obese individual is a multidimensional issue. An increase in BMI is positively correlated with pain incidence and severity, especially in central obesity where individuals are twice as likely to have chronic pain. Both obesity and chronic pain are also associated with mood disorders. Pain is worse among obese individuals with depression and anxiety. Bariatric surgery provides patients with an effective solution for long-term weight loss and associated health problems. However, not much is known about acute and chronic pain after bariatric surgery and its contributing factors, including mood disorders. Nurse practitioners (NPs) at one large multidisciplinary bariatric surgery centre led two studies to examine acute and chronic pain and pain management over time after bariatric surgery. The purpose of the initial study was to examine the incidence and severity of acute and chronic pain after bariatric surgery. The aim of the secondary study was to further examine chronic pain, specifically looking at psychological factors that influence severity or incidence of both neuropathic and somatic pain as well as changes in opioid use. The initial study was a prospective, longitudinal study where patients having bariatric surgery at one surgical center were followed up to 6 months postop. Data was collected at 7 time points using validated instruments for pain severity, pain interference, and patient satisfaction. In the second study, subjects were followed longitudinally starting preoperatively and then at 6 months and 1 year postoperatively to capture changes in chronic pain and influencing variables over time. Valid and reliable instruments were utilized for all major study outcomes. In the first study, there was a trend towards decreased acute post-operative pain over time. The incidence and severity of chronic pain was found to be significantly reduced at 6 months post bariatric surgery. Interestingly, interference of chronic pain in daily life such as normal work, mood, and walking ability was significantly improved at 6 months postop however; this was not the case with sleep. Preliminary results of the secondary study indicate that pain severity, pain interference, anxiety and depression are significantly improved at 6 months postoperatively. In addition, preoperative anxiety, depression and emotional regulation were predictive of pain interference, but not pain severity. The results of our regression analyses provide evidence for the impact of pre-existing psychological factors on pain, particularly anxiety in obese populations.

Keywords: bariatric surgery, mood disorders, obesity, pain

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