Search results for: causal inference

Authors: Kanae Suzuki

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Handheld video games are popular communication tools among Japanese elementary school students today. This study aims to examine the effects of the use of handheld video games on interpersonal relationships of the students in real and virtual worlds. A two-wave panel survey was conducted for students of ten elementary schools at an interval of approximately six months. The survey questionnaire included questions about the average amount of time spent playing a handheld video game during the past one month, the frequency of communication with players during game play, and the interpersonal relationships, such as the number of real and virtual friends the students have. A multiple regression model was constructed for 324 students to examine causal relationships. The results indicated that the more frequently the students communicated with other players while playing games, the number of the real friends tended to increase. In contrast, no significant effect of the total time spent playing games was found on interpersonal relationships. The findings suggested that communication during game play is an important factor for improving interpersonal relationships of this age group.

Keywords: communication, real friend, social adjustment, virtual friend

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Authors: Swathi M. Vanniarajan

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Reading research suggests that online contextual vocabulary comprehension while reading is an interactive and integrative process. One’s success in it depends on a variety of factors including the amount and the nature of available linguistic and nonlinguistic cues, his/her analytical and integrative skills, schema memory (content familiarity), and processing speed characterized along the continuum of controlled to automatic processing. The experiment reported here, conducted with 30 native speakers as one group and 30 nonnative speakers as another group (all graduate students), hypothesized that while working on (24) tasks which required them to comprehend an unfamiliar word in real time without backtracking, due to the differences in the nature of their respective reading processes, the nonnative subjects would be less able to construct the meanings of the unknown words by integrating the multiple but sufficient contextual cues provided in the text but the native subjects would be able to. The results indicated that there were significant inter-group as well as intra-group differences in terms of the quality of definitions given. However, when given additional time, while the nonnative speakers could significantly improve the quality of their definitions, the native speakers in general would not, suggesting that all things being equal, time is a significant factor for success in nonnative vocabulary and reading comprehension processes and that accuracy precedes automaticity in the development of nonnative reading processes also.

Keywords: reading, second language processing, vocabulary comprehension

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Authors: Farhad Shafiepour Motlagh, Narges Salehi

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Purpose: The purpose of this study was to support student strategies for virtual learning in the learning management system. Methodology: The research method was based on grounded theory. The statistical population included all the articles of the ten years 2022-2010, and the sampling method was purposeful to the extent of theoretical saturation (n=31 ). Data collection was done by referring to the authoritative scientific databases of Emerald, Springer, Elsevier, Google Scholar, Sage Publication, and Science Direct. For data analysis, open coding, axial coding, and selective coding were used. Results: The results showed that causal conditions include cognitive empowerment (comprehension, analysis, composition), emotional empowerment (learning motivation, involvement in the learning system, enthusiasm for learning), psychomotor empowerment (learning to master, internalizing learning skills, creativity in learning). Conclusion: Supporting students requires their empowerment in three dimensions: cognitive, emotional empowerment, and psychomotor empowerment. In such a way that by introducing them to enter the learning management system, the capacities of the system, the toolkit of learning in the system, improve the motivation to learn in them, and in such a case, by learning more in the learning management system, they will reach mastery learning.

Keywords: student support, virtual education, learning management system, electronic

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Authors: Ofosuhene O. Apenteng, Noor Azina Ismail

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Over the last several years, concern has developed over how to minimize the spread of HIV/AIDS epidemic in many countries. AIDS epidemic has tremendously stimulated the development of mathematical models of infectious diseases. The transmission dynamics of HIV infection that eventually developed AIDS has taken a pivotal role of much on building mathematical models. From the initial HIV and AIDS models introduced in the 80s, various improvements have been taken into account as how to model HIV/AIDS frameworks. In this paper, we present the impact of migration on the spread of HIV/AIDS. Epidemic model is considered by a system of nonlinear differential equations to supplement the statistical method approach. The model is calibrated using HIV incidence data from Malaysia between 1986 and 2011. Bayesian inference based on Markov Chain Monte Carlo is used to validate the model by fitting it to the data and to estimate the unknown parameters for the model. The results suggest that the migrants stay for a long time contributes to the spread of HIV. The model also indicates that susceptible individual becomes infected and moved to HIV compartment at a rate that is more significant than the removal rate from HIV compartment to AIDS compartment. The disease-free steady state is unstable since the basic reproduction number is 1.627309. This is a big concern and not a good indicator from the public heath point of view since the aim is to stabilize the epidemic at the disease equilibrium.

Keywords: epidemic model, HIV, MCMC, parameter estimation

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Authors: Najrullah Khan, Athar Ali Khan

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The Topp-Leone distribution was introduced by Topp- Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized exponential (TPGE) distribution. A real survival data set is used for illustrations. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools. The main aim of this paper is to describe and illustrate the Bayesian modelling approach to the analysis of survival data. Emphasis is placed on the modeling of data and the interpretation of the results. Crucial to this is an understanding of the nature of the incomplete or 'censored' data encountered. Analytic approximation and simulation tools are covered here, but most of the emphasis is on Markov chain based Monte Carlo method including independent Metropolis algorithm, which is currently the most popular technique. For analytic approximation, among various optimization algorithms and trust region method is found to be the best. In this paper, TPGE model is also used to analyze the lifetime data in Bayesian paradigm. Results are evaluated from the above mentioned real survival data set. The analytic approximation and simulation methods are implemented using some software packages. It is clear from our findings that simulation tools provide better results as compared to those obtained by asymptotic approximation.

Keywords: Bayesian Inference, JAGS, Laplace Approximation, LaplacesDemon, posterior, R Software, simulation

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Authors: Arkadiusz Urzędowski, Dorota Wójcicka-Migasiuk, Andrzej Sachajdak, Magdalena Paśnikowska-Łukaszuk

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Due to the impact of climate changes and inevitability to reduce greenhouse gases, the need to use low-carbon and sustainable construction has increased. In this work, it is investigated how texture of the surface building materials and radiative heat transfer phenomenon in flat multilayer can be correlated. Attempts to test the surface emissivity are taken however, the trustworthiness of measurement results remains a concern since sensor size and thickness are common problems. This paper presents an experimental method to studies surface emissivity with use self constructed thermal sensors and thermal imaging technique. The surface of building materials was modified by mechanical and chemical treatment affecting the reduction of the emissivity. For testing the shaping surface of materials and mapping its three-dimensional structure, scanning profilometry were used in a laboratory. By comparing the results of laboratory tests and performed analysis of 3D computer fluid dynamics software, it can be shown that a change in the surface coverage of materials affects the heat transport by radiation between layers. Motivated by recent advancements in variational inference, this publication evaluates the potential use a dedicated data processing approach, and properly constructed temperature sensors, the influence of the surface emissivity on the phenomenon of radiation and heat transport in the entire partition can be determined.

Keywords: heat transfer, surface roughness, surface emissivity, radiation

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Authors: Xinyuan Y. Song, Kai Kang

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Joint models for analyzing longitudinal and survival data are widely used to investigate the relationship between a failure time process and time-variant predictors. A common assumption in conventional joint models in the survival analysis literature is that all predictors are observable. However, this assumption may not always be supported because unobservable traits, namely, latent variables, which are indirectly observable and should be measured through multiple observed variables, are commonly encountered in the medical, behavioral, and financial research settings. In this study, a joint modeling approach to deal with this feature is proposed. The proposed model comprises three parts. The first part is a dynamic factor analysis model for characterizing latent variables through multiple observed indicators over time. The second part is a random coefficient trajectory model for describing the individual trajectories of latent variables. The third part is a proportional hazard model for examining the effects of time-invariant predictors and the longitudinal trajectories of time-variant latent risk factors on hazards of interest. A Bayesian approach coupled with a Markov chain Monte Carlo algorithm to perform statistical inference. An application of the proposed joint model to a study on the Alzheimer's disease neuroimaging Initiative is presented.

Keywords: Bayesian analysis, joint model, longitudinal data, time-to-event data

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Authors: Meida Laely Ramdani, Earmporn Thongkrajai, Dedy Purwito

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Lifestyle is one of the most important factors affecting health. Measurement of lifestyle behaviors is necessary for the identification of causal associations between unhealthy lifestyle and health outcomes. There was many instruments have been measured for lifestyle, but not specific for stroke recurrence. This study aimed to develop a new questionnaire of Lifestyle Adjustment Scale (LSAS) among recurrent stroke patients in Indonesia and to measure the reliability and validity of LSAS. The instrument consist of 33 items was developed from the responses of 30 recurrent stroke patients with the maximum age 60 years. Data was collected during October to November 2015. The properties of the instrument were evaluated by validity assessment and reliability measures. The content validity was judged adequate by a panel of five experts, with the result of I-CVI was 0.97. The Cronbach’s alpha analysis was carried out to measure the reliability of LSAS. The result showed that Cronbach’s alpha coefficient was 0.819. LSAS were classified under the domains of dietary habit, smoking habit, physical activity, and stress management. The results of Cronbach’s alpha coefficient for each subscale were 0.60, 0.39, 0.67, 0.65 and 0.76 respectively. LSAS instrument was valid and reliable therefore can be used as research tool among recurrent stroke patients. The development of this questionnaire has been adapted to the socio-cultural context in Indonesia.

Keywords: LSAS, recurrent stroke patients, lifestyle, Indonesia

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Authors: Endeshaw Assefa Derso, Maria Gabriella Campolo, Angela Alibrandi

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Objectives:Early childhood malnutrition can have long-term and irreversible effects on a child's health and development. This study uses the Bayesian method with spatial variation to investigate the flexible trends of metrical covariates and to identify communities at high risk of injury. Methods: Cross-sectional data on underweight are collected from the 2016 Ethiopian Demographic and Health Survey (EDHS). The Bayesian geo-additive model is performed. Appropriate prior distributions were provided for scall parameters in the models, and the inference is entirely Bayesian, using Monte Carlo Markov chain (MCMC) stimulation. Results: The results show that metrical covariates like child age, maternal body mass index (BMI), and maternal age affect a child's underweight non-linearly. Lower and higher maternal BMI seem to have a significant impact on the child’s high underweight. There was also a significant spatial heterogeneity, and based on IDW interpolation of predictive values, the western, central, and eastern parts of the country are hotspot areas. Conclusion: Socio-demographic and community- based programs development should be considered compressively in Ethiopian policy to combat childhood underweight malnutrition.

Keywords: bayesX, Ethiopia, malnutrition, MCMC, semi-parametric bayesian analysis, spatial distribution, P- splines

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Authors: R. Domínguez, A. Castro, N. Fernandez, F. Hidalgo, F. Ortiz

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Aims: Study musculoskeletal disorders produced by excess physical exertion in marines Introduction: Musculoskeletal injuries during military training are an important medical problem faced by military organizations throughout the world. Military occupations are physically demanding, which represents a high risk of injury "and subsequent disability, these injuries represent important risk factors for hospitalization, disability, and discharge Methodology: This is a causal correlational study in which data were collected in order to find a cause-effect relationship between the physical effort in marines during their career in the Chilean Navy and the musculoskeletal disorders that occur in some from them. Results:100% had experienced musculoskeletal pain in some part of the body and 73.52% of the respondents had experienced limitations in the ability to work, as a consequence forced to change jobs due to musculoskeletal pain. The neck, shoulders and the lumbar dorsal region were the regions with the highest prevalence of pain, as well as pain that limit the ability to work. Conclusion: Musculoskeletal injuries and illnesses related to injuries are common in marines, both in those who operate in campus Charles, as in another operational unit due to the nature of the work. Many of these injuries occur during physical training and sports and various studies have dealt with the descriptive epidemiology of musculoskeletal injuries in military personnel.

Keywords: physical effort, marines, musculoskeletal disorders produced (MSD), training

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Authors: Ahmed O. Babaleye, Rafet E. Kurt

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The global oil and gas industry is beginning to witness an increase in the number of installations moving towards decommissioning. Decommissioning of offshore installations is a complex, costly and hazardous activity, making safety one of the major concerns. Among existing removal options, complete and partial removal options pose the highest risks. Therefore, a dynamic risk model of the accidents from the two options is important to assess the risks on an overall basis. In this study, a risk-based safety model is developed to conduct quantitative risk analysis (QRA) for jacket structure systems failure. Firstly, bow-tie (BT) technique is utilised to model the causal relationship between the system failure and potential accident scenarios. Subsequently, to relax the shortcomings of BT, Bayesian Belief Networks (BBNs) were established to dynamically assess associated uncertainties and conditional dependencies. The BBN is developed through a similitude mapping of the developed bow-tie. The BBN is used to update the failure probabilities of the contributing elements through diagnostic analysis, thus, providing a case-specific and realistic safety analysis method when compared to a bow-tie. This paper presents the application of dynamic safety analysis to guide the allocation of risk control measures and consequently, drive down the avoidable cost of remediation.

Keywords: Bayesian belief network, offshore decommissioning, dynamic safety model, quantitative risk analysis

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Authors: Haruna Modibbo Usman, Mustapha Muktar, Nasiru Inuwa

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This paper examined the long run relationship between health outcomes and economic growth in Nigeria from 1961 to 2012. Using annual time series data, Augmented Dickey-Fuller (ADF) test is conducted to check the stochastic properties of the variables. Also, the long run relationship among the variables is confirmed based on Johansen Multivariate Cointegration approach whereas the long run and short run dynamics are observed using Vector Error Correction Mechanism (VECM). In addition, VEC Granger causality test is employed to examine the direction of causality among the variables. On the whole, the results obtained revealed the existence of a long run relationship between health outcomes and economic growth in Nigeria and that both life expectancy and crude death rate as measures of health are found to have a long run negative and statistically significant impact on the economic growth over the study period. This is further buttressed by the results of Granger causality test which indicated the existence of unidirectional causality running from life expectancy and crude death rate to economic growth. The study therefore, calls for governments at various levels to create preconditions for health improvements in Nigeria in order to boost the level of health outcomes.

Keywords: cointegration, economic growth, Granger causality, health outcomes, VECM

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Authors: Tewele Gerlase Haile

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Like any other country, Ethiopia's state government has reached today by undergoing many political changes. Until the last quarter of the 19th century, the aristocratic regimes of Ethiopia were using their infinite mystical power to shape the traditional public administrative institutions of the country. Mystical, feudal, social, and revolutionary political systems were used as sources of ruling power to the long-lasted monarchical, military and dictatorial regimes. For a country that is struggling to escape from the vicious cycle of poverty, famines, and civil wars, understanding how political regimes reform public policies and institutions is necessary for several reasons. A retrospective policy analysis approach is employed to determine how public policies are shaped by institutional factors and why the traditional public administration paradigm of Ethiopia continues to date despite regime changes. Using the experiences of political reforms practiced in four successive regimes (1916-2023), this retrospective analysis reveals a causal relationship among policy, institutional, and political failures. Moreover, Ethiopia's law-making and policy-making background significantly reflects the behavior of governments and their institutions. With a macro-level policy analysis in mind, the paper analyzes why the recent policy and institutional reforms twisted the country into unresolved military catastrophes.

Keywords: public administration, public policy, institutional reform, political structure

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Authors: Jane N. O'Sullivan

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Although it is widely believed that fertility decline has benefitted economic advancement, particularly in East and South-East Asian countries, the causal mechanisms for this stimulus are contested. Since the turn of this century, demographic dividend theory has been increasingly recognised, hypothesising that higher proportions of working-age people can contribute to economic expansion if conditions are met to employ them productively. Population growth rate, as a systemic condition distinct from age composition, has not been similar attention since the 1970s and has lacked methodology for quantitative assessment. This paper explores conceptual and empirical quantification of the burden of expanding physical capital to accommodate a growing population. In proof-of-concept analyses of Australia and the United Kingdom, actual expenditure on gross fixed capital formation was compiled over four decades and apportioned to maintenance/turnover or expansion to accommodate population growth, based on lifespan of capital assets and population growth rate. In both countries, capital expansion was estimated to cost 6.5-7.0% of GDP per 1% population growth rate. This opportunity cost impedes the improvement of per capita capacity needed to realise the potential of the working-age population. Economic modelling of demographic scenarios have to date omitted this channel of influence; the implications of its inclusion are discussed.

Keywords: age dependency, demographic dividend, infrastructure, population growth rate

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Authors: E. Cascarosa-Salillas, J. Pozuelo-Muñoz, C. Rodríguez-Casals, A. de Echave

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This study focuses on improving the understanding of the capillarity phenomenon among Primary and Secondary Education students. Despite being a common concept in daily life and covered in various subjects, students’ comprehension remains limited. This work explores inquiry-based teaching methods to build a conceptual foundation of capillarity by examining the forces involved. The study adopts an inquiry-based teaching approach supported by research emphasizing the importance of modeling in science education. Scientific modeling aids students in applying knowledge across varied contexts and developing systemic thinking, allowing them to construct scientific models applicable to everyday situations. This methodology fosters the development of scientific competencies such as observation, hypothesis formulation, and communication. The research was structured as a case study with activities designed for Spanish Primary and Secondary Education students aged 9 to 13. The process included curriculum analysis, the design of an activity sequence, and its implementation in classrooms. Implementation began with questions that students needed to resolve using available materials, encouraging observation, experimentation, and the re-contextualization of activities to everyday phenomena where capillarity is observed. Data collection tools included audio and video recordings of the sessions, which were transcribed and analyzed alongside the students' written work. Students' drawings on capillarity were also collected and categorized. Qualitative analyses of the activities showed that, through inquiry, students managed to construct various models of capillarity, reflecting an improved understanding of the phenomenon. Initial activities allowed students to express prior ideas and formulate hypotheses, which were then refined and expanded in subsequent sessions. The generalization and use of graphical representations of their ideas on capillarity, analyzed alongside their written work, enabled the categorization of capillarity models: Intuitive Model: A visual and straightforward representation without explanations of how or why it occurs. Simple symbolic elements, such as arrows to indicate water rising, are used without detailed or causal understanding. It reflects an initial, immediate perception of the phenomenon, interpreted as something that happens "on its own" without delving into the microscopic level. Explanatory Intuitive Model: Students begin to incorporate causal explanations, though still limited and without complete scientific accuracy. They represent the role of materials and use basic terms such as ‘absorption’ or ‘attraction’ to describe the rise of water. This model shows a more complex understanding where the phenomenon is not only observed but also partially explained in terms of interaction, though without microscopic detail. School Scientific Model: This model reflects a more advanced and detailed understanding. Students represent the phenomenon using specific scientific concepts like ‘surface tension,’ cohesion,’ and ‘adhesion,’ including structured explanations connecting microscopic and macroscopic levels. At this level, students model the phenomenon as a coherent system, demonstrating how various forces or properties interact in the capillarity process, with representations on a microscopic level. The study demonstrated that the capillarity phenomenon can be effectively approached in class through the experimental observation of everyday phenomena, explained through guided inquiry learning. The methodology facilitated students’ construction of capillarity models and served to analyze an interaction phenomenon of different forces occurring at the microscopic level.

Keywords: capillarity, inquiry-based learning, scientific modeling, primary and secondary education, conceptual understanding, Drawing analysis.

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Authors: Nyaris Pambudiyatno, Asto Buditjahjanto, Eppy Yundra, Arie Wardhono, Eko Hariadi

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Vocational education is part of the national education system that is prepared to produce graduates who have the skills and knowledge according to the needs and requirements required by the job. Vocational Education is a secondary education that prepares students to work in a particular field. The purpose of this study was to analyze and find out the effect of industrial work practice experience and career information on work readiness through work motivation. This type of research is causal research with a quantitative approach. The population in this study was 359 cadets of Aviation Polytechnic Surabaya. While the number of samples calculates using slovin calculations obtained by 189 cadets of Surabaya Aviation Polytechnic. The type of data used is quantitative data with the primary data source. Data collection techniques are by distributing questionnaires. Analysis of this study is with Lisrel. The findings prove that: (1) Industrial Work Experience experience has a positive and significant effect on work motivation; (2) Industrial Work Experience has a positive and significant impact on work readiness; (3) Career information has a positive and significant effect on job readiness; (4) Career information has a positive and significant impact on job readiness; Dan (5) Work motivation has a positive and significant effect on work readiness.

Keywords: career information, increase work readiness, industrial work experience, work motivation

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Authors: Tsion Tekalegn

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In Ethiopia, improved potato varieties are essential for food security, but smallholders' adoption of improved technologies limits their productivity. For this study, data was collected based on a structured questionnaire randomly collected from the 329 sample farmers (158 adopters and 171 non-adopters). We estimate the adoption of improved variety and causal impact using Endogenous Switching Regression (ESR), and a propensity Score Matching (PSM) was used to test the treatment effect. This helps us estimate the effect of improved potato variety on smallholder farmer income by controlling for the role of the selection bias problem stemming from both observed and unobserved heterogeneity. According to the result, key determinants influencing adoption include livestock ownership, access to extension services, and farming experience, which positively affect the likelihood of adopting improved varieties. In contrast, access to irrigation negatively correlates with adoption, suggesting that farmers with reliable water sources perceive less need for improved varieties. The ESR model result confirmed that improved potato variety adoption increases the smallholder farmer income with an estimated gain of 8.77%. Thus, to improve the potato variety of the farming households, the government should give due emphasis to potato production, and the extension services need to be strengthened.

Keywords: adoption, improved potato varieties, endogenous switching regression, Ethiopia

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Authors: Sonam Kelzang

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Background: Penetrating injuries as a result of traditional sports (Archery and Khuru) are commonly seen in Bhutan. To our knowledge, there is no study carried out looking into the data of penetrating injuries due to traditional sports. Aim: This is a retrospective analysis of cases of penetrating injuries as a result of traditional sports admitted to JDWNRH over the last 3 years to draw an inference on the pattern of injury and associated morbidity and mortality. Method: Data on penetrating injuries related to traditional sports (Archery and Khuru) were collected and reviewed over the period of 3 years. Assault cases were excluded. For each year we analysed age, sex, parts of the body affected, agent of injury and whether admission was required or not. Results: Out of the total 44 victims of penetrating injury by traditional sports (Archery and Khuru) between 2013 and 2015 (average of 15 cases of penetrating injuries per year). Eighty-five percent were male and 15% were female. Their age ranged from 4 yrs to 62 years. Sixty-one percent of the victims were in the working age group of 19-58 years; 30% of the victims were referred from various district hospitals; 38% of the victims needed admission; 42 % of the victims suffered injury to the head; and 54% of the injuries were caused by Khuru. Conclusion: Penetrating injuries due to traditional sports admitted to JDWNRH, Thimphu, remained same over the three years period despite safety regulations in place. Although there were no deaths during the last three years, morbidity still remains high.

Keywords: archery, Bhutan, Khuru, darts

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Authors: Sofia M. Karadimitriou, Kostas Triantafyllopoulos, Timothy Heaton

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Reduced dimension Dynamic Spatio-Temporal Models (DSTMs) jointly describe the spatial and temporal evolution of a function observed subject to noise. A basic state space model is adopted for the discrete temporal variation, while a continuous autoregressive structure describes the continuous spatial evolution. Application of such a DSTM relies upon the pre-selection of a suitable reduced set of basic functions and this can present a challenge in practice. In this talk, we propose an online estimation method for high dimensional spatio-temporal data based upon DSTM and we attempt to resolve this issue by allowing the basis to adapt to the observed data. Specifically, we present a wavelet decomposition in order to obtain a parsimonious approximation of the spatial continuous process. This parsimony can be achieved by placing a Laplace prior distribution on the wavelet coefficients. The aim of using the Laplace prior, is to filter wavelet coefficients with low contribution, and thus achieve the dimension reduction with significant computation savings. We then propose a Hierarchical Bayesian State Space model, for the estimation of which we offer an appropriate particle filter algorithm. The proposed methodology is illustrated using real environmental data.

Keywords: multidimensional Laplace prior, particle filtering, spatio-temporal modelling, wavelets

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Authors: Isha Saxena, Behzad Kazemtabrizi, Matthias C. M. Troffaes, Christopher Crabtree

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The calculations done at the beginning of the life of a wind farm are rarely reliable, which makes it important to conduct research and study the failure and repair rates of the wind turbines under various conditions. This miscalculation happens because the current models make a simplifying assumption that the failure/repair rate remains constant over time. This means that the reliability function is exponential in nature. This research aims to create a more accurate model using sensory data and a data-driven approach. The data cleaning and data processing is done by comparing the Power Curve data of the wind turbines with SCADA data. This is then converted to times to repair and times to failure timeseries data. Several different mathematical functions are fitted to the times to failure and times to repair data of the wind turbine components using Maximum Likelihood Estimation and the Posterior expectation method for Bayesian Parameter Estimation. Initial results indicate that two parameter Weibull function and exponential function produce almost identical results. Further analysis is being done using the complex system analysis considering the failures of each electrical and mechanical component of the wind turbine. The aim of this project is to perform a more accurate reliability analysis that can be helpful for the engineers to schedule maintenance and repairs to decrease the downtime of the turbine.

Keywords: reliability, bayesian parameter inference, maximum likelihood estimation, weibull function, SCADA data

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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: Krishna Mohan Bathula, Fatou Bintou Loucoubar, FNU Kaleemunnisa, Christelle Scharff, Mark Anthony De Castro

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Voice recognition algorithms such as automatic speech recognition and text-to-speech systems with African languages can play an important role in bridging the digital divide of Artificial Intelligence in Africa, contributing to the establishment of a fully inclusive information society. This paper proposes a Deep Learning model that can classify the user responses as inputs for an interactive voice response system. A dataset with Wolof language words ‘yes’ and ‘no’ is collected as audio recordings. A two stage Data Augmentation approach is adopted for enhancing the dataset size required by the deep neural network. Data preprocessing and feature engineering with Mel-Frequency Cepstral Coefficients are implemented. Convolutional Neural Networks (CNNs) have proven to be very powerful in image classification and are promising for audio processing when sounds are transformed into spectra. For performing voice response classification, the recordings are transformed into sound frequency feature spectra and then applied image classification methodology using a deep CNN model. The inference model of this trained and reusable Wolof voice response recognition system can be integrated with many applications associated with both web and mobile platforms.

Keywords: automatic speech recognition, interactive voice response, voice response recognition, wolof word classification

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Authors: Porntip Ruengtam

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This article is an extension of previous research presenting the relevant factors related to environmental perceptions, residential community, and the design of a healing environment, which have effects on the well-being and requirements of Thai elderly. Research methodology began with observations and interviews in three case studies in terms of the management processes and environment design of similar existing projects in Thailand. The interview results were taken to summarize with related theories and literature. A questionnaire survey was designed for data collection to confirm the factors of requirements in a residential community intended for the Thai elderly. A structural equation model (SEM) was formulated to explain the cause-effect factors for the requirements of a residential community for Thai elderly. The research revealed that the requirements of a residential community for Thai elderly were classified into three groups when utilizing a technique for exploratory factor analysis. The factors were comprised of (1) requirements for general facilities and activities, (2) requirements for facilities related to health and security, and (3) requirements for facilities related to physical exercise in the residential community. The results from the SEM showed the background of elderly people had a direct effect on their requirements for a residential community from various aspects. The results should lead to the formulation of policies for design and management of residential communities for the elderly in order to enhance quality of life as well as both the physical and mental health of the Thai elderly.

Keywords: elderly, environmental design, residential community, structural equation modeling

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Authors: Ming-Yang Guo, Cheng-Xian Wu, Wei-Xiang Chen, Chun-Yuan Lin, Yen-Jen Lin, Ann-Shyn Chiang

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With more and more Drosophila Driver and Neuron images, it is an important work to find the similarity relationships among them as the functional inference. There is a general problem that how to find a Drosophila Driver image, which can cover a set of Drosophila Driver/Neuron images. In order to solve this problem, the intersection/union region for a set of images should be computed at first, then a comparison work is used to calculate the similarities between the region and other images. In this paper, three encoding schemes, namely Integer, Boolean, Decimal, are proposed to encode each image as a one-dimensional structure. Then, the intersection/union region from these images can be computed by using the compare operations, Boolean operators and lookup table method. Finally, the comparison work is done as the union region computation, and the similarity score can be calculated by the definition of Tanimoto coefficient. The above methods for the region computation are also implemented in the multi-core CPUs environment with the OpenMP. From the experimental results, in the encoding phase, the performance by the Boolean scheme is the best than that by others; in the region computation phase, the performance by Decimal is the best when the number of images is large. The speedup ratio can achieve 12 based on 16 CPUs. This work was supported by the Ministry of Science and Technology under the grant MOST 106-2221-E-182-070.

Keywords: Drosophila driver image, Drosophila neuron images, intersection/union computation, parallel processing, OpenMP

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Authors: Ming Ma, Rui Li

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In the highly urbanized district, green open space is playing an important role in human’s health and wellbeing as a physical, aesthetic and natural environment resources. The aim of this paper is to close this gap through providing a comprehensive, qualitative meta-analysis of existing studies related to this issue. A systematic scoping of current quantitative research is conducted which mostly focused on cross-sectional survey and experimental studies. Health benefits from contact with green open space could be categorized into physical health, psychological health and social wellbeing. Mechanism for the health related to green open space could be clearly identified with the regard to natural restoration, physical activities and social capital. These results indicate a multiple pathways framework between the health benefits and mechanism. In order to support design and planning, the most evident relationship was picked up that people could psychologically benefit from green open space through outdoors physical activities. Additionally, three design and planning strategies are put forward. Various and multi-level contacts with green open space would be considered as an explanation of the pathway results and tie to bridge the health to design and planning. There is a need to carry out long-term research emphasizing on causal relationship between health and green open space through excluding cofounding factors such as self-selection.

Keywords: urban green open space, planning and design, health benefit, mechanism, pathway framework

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Authors: Zeren Li, Wenkai Song

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Shanghai experienced a 3-month lockdown in 2022. This unprecedented lockdown made local residents afraid, anxious and worried about the unpredictability of the future. During the lockdown, many unethical behaviors related to lockdown are noticed by the public. Our studies documented unethical behavior during this lockdown by moral hypocrisy and moral justification examined whether or not the lockdown makes people behave more unethically, and analyzed the relationship between negative emotions and unethical behavior. In Study 1, we recruited 240 participants from Shanghai (n = 120) and other cities (n = 120) to compare people in lockdown and non-lockdown areas. Surprisingly, we found that people in lockdown areas tend to behave more ethically, exhibiting less moral hypocrisy. In addition, residents of the lockdown area have significantly higher negative emotions (afraid, nervousness, upset, and feelings of uncertainty). In Study 2, we recruited 70 respondents from Shanghai and found that people behave relatively ethically in lockdown-related scenarios (negatively correlated with anxiety about the lockdown) with relatively less moral justification than in lockdown-unrelated scenarios. We propose that negative emotions may reduce unethical behavior that may exacerbate the causes (in our study, the lockdown) of these negative emotions. Experiments may help to establish the causal relationship and verify the model in future research.

Keywords: COVID-19, unethical behavior, emotion, anxiety, moral justification, moral hypocrisy, China

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Authors: Aishwarya Rai

Abstract:

This study explores the transformative influence of generative AI on startups, businesses, and industries. We will explore how large businesses can benefit in the area of customer operations, where AI-powered chatbots can improve self-service and agent effectiveness, greatly increasing efficiency. In marketing and sales, generative AI could transform businesses by automating content development, data utilization, and personalization, resulting in a substantial increase in marketing and sales productivity. In software engineering-focused startups, generative AI can streamline activities, significantly impacting coding processes and work experiences. It can be extremely useful in product R&D for market analysis, virtual design, simulations, and test preparation, altering old workflows and increasing efficiency. Zooming into the retail and CPG industry, industry findings suggest a 1-2% increase in annual revenues, equating to $400 billion to $660 billion. By automating customer service, marketing, sales, and supply chain management, generative AI can streamline operations, optimizing personalized offerings and presenting itself as a disruptive force. While celebrating economic potential, we acknowledge challenges like external inference and adversarial attacks. Human involvement remains crucial for quality control and security in the era of generative AI-driven transformative innovation. This talk provides a comprehensive exploration of generative AI's pivotal role in reshaping businesses, recognizing its strategic impact on customer interactions, productivity, and operational efficiency.

Keywords: generative AI, digital transformation, LLM, artificial intelligence, startups, businesses

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Authors: Amir Salamatzade, Marhamet HematPour

Abstract:

Due to the increasing importance of psychological factors in the incidence and exacerbation of chronic diseases such as multiple sclerosis, the aim of this study was to determine the difference between emotional regulation strategies and psychological symptoms in patients with multiple sclerosis and normal people. The research method was causal-comparative (post-event). The statistical population of this research included all patients with multiple sclerosis referred to the MS Association of Rasht in the first quarter of 2021, approximately 350 people. The study sample also included 120 people (60 patients with multiple sclerosis and 60 normal people) who were selected by the available sampling method and completed the emotional regulation and anxiety, depression, and stress Lavibund and Lavibund (1995) questionnaires. Data were analyzed using an independent t-test and multivariate variance analysis. The results showed that there was a significant difference between the mean of emotional regulation strategies and the components of emotional reassessment and emotional inhibition between the two groups of patients with multiple sclerosis and normal individuals (p < 0.01). There is a significant difference between the mean of psychological symptoms and the components of depression, anxiety, and stress in the two groups of patients with multiple sclerosis and normal individuals. (p < 0.01). Based on this, it can be concluded that patients with multiple sclerosis have lower levels of emotional regulation strategies and higher levels of psychological symptoms than normal individuals.

Keywords: emotional regulation strategies, psychological symptoms, multiple sclerosis, normal Individuals

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Authors: Inbal Peleg Koriat, Rachel Ben-Ari

Abstract:

The purpose of the present study was to test individual’s conflict management style in romantic relations as a function of their perception of the extent of procedural justice in their partner behavior, and to what extant this relationship is mediated by the quality of the relations. The research procedure included two studies: The first study was a correlative study with 160 participants in a romantic relation. The goal of the first study was to examine the mediation model with self-report questionnaires. The second study was an experimental study with 241 participants. The study was designed to examine the causal connection between perceived procedural justice (PPJ) and conflict management styles. Study 1 indicated a positive connection between PPJ and collaborative conflict management styles (integrating, compromising and obliging). In contrast, a negative connection was not found between PPJ and non-collaborative conflict management styles (avoiding, and dominating). In addition, perceived quality of the romantic relations was found to mediate the connection between PPJ and collaborative conflict management styles. Study 2 validated the finding of Study 1 by showing that PPJ leads the individual to use compromising and integrating conflict management styles. In contrast to Study 1, Study 2 shows that a low PPJ increases the individual’s tendency to use an avoiding conflict management style. The study contributes to the rather scarce research on PPJ role in conflict management in general and in romantic relations in particular. It can provide new insights into cognitive methods of coping with conflict that encourage transformation in the conflict and a way to grow and develop both individually and as a couple.

Keywords: conflict management style, marriage, procedural justice, romantic relations

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Authors: Mohammad Hossein Ranjbar, Mahdi Bagheri, B. Shivaraj

Abstract:

This study attempts to investigate the relationship between stock market of Iran and GCC countries stock exchanges. Eight markets were included: the stock market of Iran, Kuwait, Bahrain, Qatar, Saudi Arabia, Dubai, Abu Dhabi and Oman. Daily country market indices were collected from January 2005 to December 2010. The potential time-varying behaviors of long-run stock market relationship among selected markets are tested applying correlation test, Augmented Dick Fuller test (ADF), Bilateral and Multilateral Cointegration (Johansen), and the Granger Causality test. The findings suggest that stock market of Iran is negatively correlated with most of the selected markets in the whole duration. But contemporaneous correlations among the eight selected markets are increased positively in period of financial crises. Bilateral Cointegration between selected markets suggests that there is no integration between Tehran stock exchange and other selected markets. Among other markets, except the stock market of Dubai and Abu Dhabi as a one pair, are not cointegrated in whole, but in duration of financial crises integration between selected markets are increased. Finally, investigation of the casual relationship among eight financial markets suggests there are unidirectional and bidirectional causal relationship among some of stock market indices.

Keywords: financial crises, Middle East, stock market integration, Granger Causality test, ARDL test

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