Search results for: Bayesian belief

Authors: Abdisalam Hassan Muse, Samuel Mwalili, Oscar Ngesa

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A generalized log-logistic distribution with variable shapes of the hazard rate was introduced and studied, extending the log-logistic distribution by adding an extra parameter to the classical distribution, leading to greater flexibility in analysing and modeling various data types. The proposed distribution has a large number of well-known lifetime special sub-models such as; Weibull, log-logistic, exponential, and Burr XII distributions. Its basic mathematical and statistical properties were derived. The method of maximum likelihood was adopted for estimating the unknown parameters of the proposed distribution, and a Monte Carlo simulation study is carried out to assess the behavior of the estimators. The importance of this distribution is that its tendency to model both monotone (increasing and decreasing) and non-monotone (unimodal and bathtub shape) or reversed “bathtub” shape hazard rate functions which are quite common in survival and reliability data analysis. Furthermore, the flexibility and usefulness of the proposed distribution are illustrated in a real-life data set and compared to its sub-models; Weibull, log-logistic, and BurrXII distributions and other parametric survival distributions with 3-parmaeters; like the exponentiated Weibull distribution, the 3-parameter lognormal distribution, the 3- parameter gamma distribution, the 3-parameter Weibull distribution, and the 3-parameter log-logistic (also known as shifted log-logistic) distribution. The proposed distribution provided a better fit than all of the competitive distributions based on the goodness-of-fit tests, the log-likelihood, and information criterion values. Finally, Bayesian analysis and performance of Gibbs sampling for the data set are also carried out.

Keywords: hazard rate function, log-logistic distribution, maximum likelihood estimation, generalized log-logistic distribution, survival data, Monte Carlo simulation

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Authors: Melek Göregenli, Işık Gürşimşek

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There has been a great deal of research in the past few decades examining attitudes toward homosexuals.Theoretic research has demonstrated that antihomosexual attitudes are expressed in cognitive, affective, behavioral and cultural components. Homophobia is generally defined as hostility towards or fear of LGBTI people, but can also refer to social and cultural ideologies which stigmatize homosexuality. Negative feelings or attitudes towards non-heterosexual behavior, identity, relationships and community can lead to homophobic behavior and is the root of the discrimination experienced by many lesbian, gay, bisexual and transgender (LGBTI) people. Since the increase in number of hate crimes during the last decade, there has been a sense of urgency to respond to the problem of hate violence in Turkey. The LGBTI Rights Association KAOS-GL indicated that the most of lesbian, gay, bisexual, travesty and transsexuals reported some form of victimization in their lifetimes based on their sexual orientation in Turkey. This study explored the relations between homophobia, right-wing authoritarianism, social dominance orientation and just world belief attitudes towards LGBTI individuals in a sample of 393 Turkish college students from Ege University in Izmir, Turkey. Data were collected with a questionnaire including the Homosexism Scale, the Right-Wing Authoritarianism Scale, Social Dominance Orientation Scale and Just World Belief Scale. Participants completed a questionnaire containing the attitude measures and other several questions related with the socio-demographic variables. Consistent with the previous finding males were more homophobic than females. Contrary to this finding the main effects of other demographic variables (age, income, place of birth, class) were not statistically significant except the department of participants. These findings imply that efforts to garner wide-ranging support for policies designed to change negative attitudes to LGBT people and to enhance the given awareness on homophobia. The results of the study were discussed in cross-cultural and social psychological perspective considering cultural and social values of Turkey and current political circumstances of the country.

Keywords: homophobia, just world belief, right-wing authoritarianism, social dominance orientation, Turkey

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Authors: Wanida Suwunniponth

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The purposes of this research were to investigate the perceived of a cultural image and loyalty of tourists toward the attraction at Banglumphu neighborhood in Bangkok and to study the relationship of the cultural image of Banglumphu community and loyalty to visit this area of the tourists. This study employed both quantitative approach and qualitative approach. In a quantitative research, a questionnaire was used to collect data from 300 systematic sampled tourists who visited Banglumphu area and the correlation analysis were used to analyze data. The results revealed that the overall tourists’ point of view toward Banglumphu cultural image was at a good level which lifestyle had the best image, followed by value and belief, physical dimension, community identity, tradition, and local wisdom. In addition, the overall aspect of tourists’ loyalty including satisfaction, word of mouths, and revisiting were at good levels which word of mouths received the highest value, followed by revisiting, and satisfaction, respectively. In addition, the relationship between cultural image in aspect on lifestyle, tradition, local wisdom, belief, community identity and loyalty to visit Banglumphu in each aspect on satisfaction, word of mouths, and revisiting were moderately correlated at the significant level of 0.05, except physical dimension was not correlated with each aspect of tourists’ loyalty.

Keywords: cultural tourism, image, loyalty, revisit

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Authors: Steven M. Graham, Anne V. Magee

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Most world religions have sacred texts and traditions that provide instruction about and definitions of marriage, family, and family duties and responsibilities. Given that religious fundamentalism (RF) is defined as the belief that these sacred texts and traditions are literally and completely true to the exclusion of other teachings, RF should be predictive of the attitudes one holds about these topics. The goals of the present research were to: (1) explore the extent to which people think that men and women can be happy without marriage, a significant sexual relationship, a long-term romantic relationship, and having children; (2) determine the extent to which RF is associated with these beliefs; and, (3) to determine how RF is associated with considering certain elements of a relationship to be necessary for thinking of that relationship as a marriage. In Study 1, participants completed a reliable and valid measure of RF and answered questions about the necessity of various elements for a happy life. Higher RF scores were associated with the belief that both men and women require marriage, a sexual relationship, a long-term romantic relationship, and children in order to have a happy life. In Study 2, participants completed these same measures and the pattern of results replicated when controlling for overall religiosity. That is, RF predicted these beliefs over and above religiosity. Additionally, participants indicated the extent to which a variety of characteristics were necessary to consider a particular relationship to be a marriage. Controlling for overall religiosity, higher RF scores were associated with the belief that the following were required to consider a relationship a marriage: religious sanctification, a sexual component, sexual monogamy, emotional monogamy, family approval, children (or the intent to have them), cohabitation, and shared finances. Interestingly, and unexpectedly, higher RF scores were correlated with less importance placed on mutual consent in order to consider a relationship a marriage. RF scores were uncorrelated with the importance placed on legal recognition or lifelong commitment and these null findings do not appear to be attributable to ceiling effects or lack of variability. These results suggest that RF constrains views about both the importance of marriage and family in one’s life and also the characteristics required to consider a relationship a proper marriage. This could have implications for the mental and physical health of believers high in RF, either positive or negative, depending upon the extent to which their lives correspond to these templates prescribed by RF. Additionally, some of these correlations with RF were substantial enough (> .70) that the relevant items could serve as a brief, unobtrusive measure of RF. Future research will investigate these possibilities.

Keywords: attitudes about marriage, fertility intentions, measurement, religious fundamentalism

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Authors: Demet Ozgur-Unluakin, Busenur Turkali, Ayse Karacaorenli

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Maintenance strategies can be classified into two types, which are reactive and proactive, with respect to the time of the failure and maintenance. If the maintenance activity is done after a breakdown, it is called reactive maintenance. On the other hand, proactive maintenance, which is further divided as preventive and predictive, focuses on maintaining components before a failure occurs to prevent expensive halts. Recently, the number of interacting components in a system has increased rapidly and therefore, the structure of the systems have become more complex. This situation has made it difficult to provide the right maintenance decisions. Herewith, determining effective decisions has played a significant role. In multi-component systems, many methodologies and strategies can be applied when a component or a system has already broken down or when it is desired to identify and avoid proactively defects that could lead to future failure. This study focuses on the comparison of various maintenance strategies on a multi-component dynamic system. Components in the system are hidden, although there exists partial observability to the decision maker and they deteriorate in time. Several predefined policies under corrective, preventive and predictive maintenance strategies are considered to minimize the total maintenance cost in a planning horizon. The policies are simulated via Dynamic Bayesian Networks on a multi-component system with different policy parameters and cost scenarios, and their performances are evaluated. Results show that when the difference between the corrective and proactive maintenance cost is low, none of the proactive maintenance policies is significantly better than the corrective maintenance. However, when the difference is increased, at least one policy parameter for each proactive maintenance strategy gives significantly lower cost than the corrective maintenance.

Keywords: decision making, dynamic Bayesian networks, maintenance, multi-component systems, reliability

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Authors: Ahmad Rabby

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The demographic trend analyses of Bombay-duck from time series catch data using CMSY and BSM for the first time in Bangladesh. During 2000-2018, CMSY indicates average lowest production in 2000 and highest in 2018. This has been used in the estimation of prior biomass by the default rules. Possible 31030 viable trajectories for 3422 r-k pairs were found by the CMSY analysis and the final estimates for intrinsic rate of population increase (r) was 1.19 year-1 with 95% CL= 0.957-1.48 year-1. The carrying capacity(k) of Bombay-duck was 283×103 tons with 95% CL=173×103 - 464×103 tons and MSY was 84.3×103tons year-1, 95% CL=49.1×103-145×103 tons year-1. Results from Bayesian state-space implementation of the Schaefer production model (BSM) using catch & CPUE data, found catchabilitiy coefficient(q) was 1.63 ×10-6 from lcl=1.27×10-6 to ucl=2.10×10-6 and r= 1.06 year-1 with 95% CL= 0.727 - 1.55 year-1, k was 226×103 tons with 95% CL=170×103-301×103 tons and MSY was 60×103 tons year-1 with 95% CL=49.9 ×103- 72.2 ×103 tons year-1. Results for Bombay-duck fishery management based on BSM assessment from time series catch data illustrated that, Fmsy=0.531 with 95% CL =0.364 - 0.775 (if B > 1/2 Bmsy then Fmsy =0.5r); Fmsy=0.531 with 95% CL =0.364-0.775 (r and Fmsy are linearly reduced if B < 1/2Bmsy). Biomass in 2018 was 110×103 tons with 2.5th to 97.5th percentile=82.3-155×103 tons. Relative biomass (B/Bmsy) in last year was 0.972 from 2.5th percentile to 97.5th percentile=0.728 -1.37. Fishing mortality in last year was 0.738 with 2.5th-97.5th percentile=0.525-1.37. Exploitation F/Fmsy was 1.39, from 2.5th to 97.5th percentile it was 0.988 -1.86. The biological reference points of B/BMSY was smaller than 1.0, while F/FMSY was higher than 1.0 revealed an over-exploitation of the fishery, indicating that more conservative management strategies are required for Bombay-duck fishery.

Keywords: biological reference points, catchability coefficient, carrying capacity, intrinsic rate of population increase

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Authors: Cecilia Perri, Vincenzo Corvello

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The aim of the present study is to investigate consumers' determinants of intention toward the adoption of Smart Grid solutions and technologies. Ajzen's Theory of Planned Behaviour (TPB) model is applied and tested to explain the formation of such adoption intention. An exogenous variable, taking into account the resistance to change of individuals, was added to the basic model. The elicitation study allowed obtaining salient modal beliefs, which were used, with the support of literature, to design the questionnaire. After the screening phase, data collected from the main survey were analysed for evaluating measurement model's reliability and validity. Consistent with the theory, the results of structural equation analysis revealed that attitude, subjective norm, and perceived behavioural control positively, which affected the adoption intention. Specifically, the variable with the highest estimate loading factor was found to be the perceived behavioural control, and, the most important belief related to each construct was determined (e.g., energy saving was observed to be the most significant belief linked with attitude). Further investigation indicated that the added exogenous variable has a negative influence on intention; this finding confirmed partially the hypothesis, since this influence was indirect: such relationship was mediated by attitude. Implications and suggestions for future research are discussed.

Keywords: adoption of innovation, consumers behaviour, energy management, smart grid, theory of planned behaviour

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Authors: Muhammad Asghar, Muhammad Ali, Farwah Batool

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Despite the general belief in Islam that figural representations should be avoided, particularly propagated by the Deobandis, a religious group influenced by Salafi and Wahhabi ideas, nevertheless the public interaction spaces such as Shops and offices are decorated with popular, mass-produced, modern devotional prints. This study seeks to focus on popular visual culture, its display in public interaction places such as shops and discusses how people establish relationships with images. The method adopted was basically ethnographic: to describe as precisely and completely as possible the phenomena to be studied, using the language and conceptual categories of the interlocutors themselves. This study has been enriched by ethnographic field research conducted during the months from October to December 2015 in the major cities of Punjab and their brief forays and surroundings where we explored how seeing upon images performs religious identity within the public space. The study examines the pattern of aesthetics and taste in the shops of especially common people whose sensibilities have not been refined or influenced by being exposed to any narrative or fine arts. Furthermore, it is our intention to question the general beliefs and opinions in the context of popular practices, the way in which people relate to these prints. The interpretations and analyses presented in this study illuminate how people create meaning through the display of such items of material culture in the immediate settings of their spaces. This study also seeks to demonstrate how popular Islam is practiced, transformed and understood through the display of popular representations of popular figures of piety like Sufi saints or their shrines are important to many believers and thus occupy important places in their shops. The findings are supported with empirical evidence and based on interviews with the shopkeepers, owners and office employees. Looking upon those popular modern devotional prints keeps people’s reverence of the personages alive. Because of their sacred themes they affect a relationship between the saint and the beholders as well as serve to symbolize and reinforce their belief since they become powerful loci of emotional attachment. Collectively such devotional prints satisfy a local taste to help people establish contact with God through the saints’ intercession in order to receive protection and benediction, and help in spiritual, mental and material problems. By putting all these facets of belief together we gain an insight into both the subjective and cognizant role that icons’ of saints play in the lives of believers. Their veneration through ingeniously contrived modern means of production makes a significant contribution to an understanding of how such imagery promotes a powerful belief in Sufi saints, which ultimately gives indications of how popular Islam is practiced and understood at its gross roots level.

Keywords: ethnographic field research, popular visual culture, protected space, religious identity

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Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

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Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

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Authors: Crystal Shackleford, Michael Pasek, Allon Vishkin, Jeremy Ginges

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In the Middle East, conflict is often viewed as religiously motivated. In this context, an important question is how we think the religion of the other drives their behavior. If people see conflicts as religious, they may expect the belief of the other to motivate intergroup bias. Beliefs about the motivations of the other impact how we engage with them. Conflict may result if actors believe the other’s religion promotes parochialism. To examine how actors on the ground in Israel-Palestine think about the God of the other as it relates to the other’s behavior towards them, we ran two studies in winter 2019 with an online sample of Jewish Israelis and fieldwork with Palestinians in the West Bank. We asked participants to predict the behavior of an outgroup member participating in an economic game task, dividing the money between themselves and another person, who is either an ingroup or outgroup member. Our experimental manipulation asks participants to predict the behavior of the other when the other is thinking of their God. Both Israelis and Palestinians believed outgroup members would show in-group favoritism, and that group members would give more to their in-group when thinking of their God. We also found that participants thought outgroup members would give more to their own ingroup when thinking of God. In other words, Palestinians predicted that Israelis would give more to fellow Israelis when thinking of God, but also more to Palestinians. Our results suggest that religious belief is seen to promote universal moral reasoning, even in a context with over 70 years of intense conflict. More broadly, this challenges the narrative that religion necessarily motivates intractable conflict.

Keywords: conflict, psychology, religion, meta-cognition, morality

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Authors: F. Ghazalnaz Sharifonnasabi, Iman Makhdoom

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Breast cancer is a serious health concern that affects many people around the world. According to a study published in the Breast journal, the global burden of breast cancer is expected to increase significantly over the next few decades. The number of deaths from breast cancer has been increasing over the years, but the age-standardized mortality rate has decreased in some countries. It’s important to be aware of the risk factors for breast cancer and to get regular check- ups to catch it early if it does occur. Machin learning techniques have been used to aid in the early detection and diagnosis of breast cancer. These techniques, that have been shown to be effective in predicting and diagnosing the disease, have become a research hotspot. In this study, we consider two deep learning approaches including: Multi-Layer Perceptron (MLP), and Convolutional Neural Network (CNN). We also considered the five-machine learning algorithm titled: Decision Tree (C4.5), Naïve Bayesian (NB), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) Algorithm and XGBoost (eXtreme Gradient Boosting) on the Breast Cancer Wisconsin Diagnostic dataset. We have carried out the process of evaluating and comparing classifiers involving selecting appropriate metrics to evaluate classifier performance and selecting an appropriate tool to quantify this performance. The main purpose of the study is predicting and diagnosis breast cancer, applying the mentioned algorithms and also discovering of the most effective with respect to confusion matrix, accuracy and precision. It is realized that CNN outperformed all other classifiers and achieved the highest accuracy (0.982456). The work is implemented in the Anaconda environment based on Python programing language.

Keywords: breast cancer, multi-layer perceptron, Naïve Bayesian, SVM, decision tree, convolutional neural network, XGBoost, KNN

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Authors: Diana F. Lopes, Jorge Simoes, José Martins, Eduardo Castro

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Health professionals are the keystone of any health system, by delivering health services to the population. Given the time and cost involved in training new health professionals, the planning process of the health workforce is particularly important as it ensures a proper balance between the supply and demand of these professionals and it plays a central role on the Health 2020 policy. In the past 40 years, the planning of the health workforce in Portugal has been conducted in a reactive way lacking a prospective vision based on an integrated, comprehensive and valid analysis. This situation may compromise not only the productivity and the overall socio-economic development but the quality of the healthcare services delivered to patients. This is even more critical given the expected shortage of the health workforce in the future. Furthermore, Portugal is facing an aging context of some professional classes (physicians and nurses). In 2015, 54% of physicians in Portugal were over 50 years old, and 30% of all members were over 60 years old. This phenomenon associated to an increasing emigration of young health professionals and a change in the citizens’ illness profiles and expectations must be considered when planning resources in healthcare. The perspective of sudden retirement of large groups of professionals in a short time is also a major problem to address. Another challenge to embrace is the health workforce imbalances, in which Portugal has one of the lowest nurse to physician ratio, 1.5, below the European Region and the OECD averages (2.2 and 2.8, respectively). Within the scope of the HEALTH 2040 project – which aims to estimate the ‘Future needs of human health resources in Portugal till 2040’ – the present study intends to get a comprehensive dynamic approach of the problem, by (i) estimating the needs of physicians and nurses in Portugal, by specialties and by quinquenium till 2040; (ii) identifying the training needs of physicians and nurses, in medium and long term, till 2040, and (iii) estimating the number of students that must be admitted into medicine and nursing training systems, each year, considering the different categories of specialties. The development of such approach is significantly more critical in the context of limited budget resources and changing health care needs. In this context, this study presents the drivers of the healthcare needs’ evolution (such as the demographic and technological evolution, the future expectations of the users of the health systems) and it proposes a Bayesian methodology, combining the best available data with experts opinion, to model such evolution. Preliminary results considering different plausible scenarios are presented. The proposed methodology will be integrated in a user-friendly decision support system so it can be used by politicians, with the potential to measure the impact of health policies, both at the regional and the national level.

Keywords: bayesian estimation, health economics, health workforce planning, human health resources planning

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Authors: Martins Y. Otache, John J. Musa, Abayomi I. Kuti, Mustapha Mohammed

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The performance of an artificial neural network (ANN) is contingent on a host of factors, for instance, the network optimisation scheme. In view of this, the study examined the general implications of the ANN training optimisation algorithm on its forecast performance. To this end, the Bayesian regularisation (Br), Levenberg-Marquardt (LM), and the adaptive learning gradient descent: GDM (with momentum) algorithms were employed under different ANN structural configurations: (1) single-hidden layer, and (2) double-hidden layer feedforward back propagation network. Results obtained revealed generally that the gradient descent with momentum (GDM) optimisation algorithm, with its adaptive learning capability, used a relatively shorter time in both training and validation phases as compared to the Levenberg- Marquardt (LM) and Bayesian Regularisation (Br) algorithms though learning may not be consummated; i.e., in all instances considering also the prediction of extreme flow conditions for 1-day and 5-day ahead, respectively especially using the ANN model. In specific statistical terms on the average, model performance efficiency using the coefficient of efficiency (CE) statistic were Br: 98%, 94%; LM: 98 %, 95 %, and GDM: 96 %, 96% respectively for training and validation phases. However, on the basis of relative error distribution statistics (MAE, MAPE, and MSRE), GDM performed better than the others overall. Based on the findings, it is imperative to state that the adoption of ANN for real-time forecasting should employ training algorithms that do not have computational overhead like the case of LM that requires the computation of the Hessian matrix, protracted time, and sensitivity to initial conditions; to this end, Br and other forms of the gradient descent with momentum should be adopted considering overall time expenditure and quality of the forecast as well as mitigation of network overfitting. On the whole, it is recommended that evaluation should consider implications of (i) data quality and quantity and (ii) transfer functions on the overall network forecast performance.

Keywords: streamflow, neural network, optimisation, algorithm

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Authors: Niroshan K. Walgama Wellalage, Tieling Zhang, Richard Dwight

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State-based Markov deterioration models (SMDM) sometimes fail to find accurate transition probability matrix (TPM) values, and hence lead to invalid future condition prediction or incorrect average deterioration rates mainly due to drawbacks of existing nonlinear optimization-based algorithms and/or subjective function types used for regression analysis. Furthermore, a set of separate functions for each condition state with age cannot be directly derived by using Markov model for a given bridge element group, which however is of interest to industrial partners. This paper presents a new approach for generating Homogeneous SMDM model output, namely, the Modified Weibull approach, which consists of a set of appropriate functions to describe the percentage condition prediction of bridge elements in each state. These functions are combined with Bayesian approach and Metropolis Hasting Algorithm (MHA) based Markov Chain Monte Carlo (MCMC) simulation technique for quantifying the uncertainty in model parameter estimates. In this study, factors contributing to rail bridge deterioration were identified. The inspection data for 1,000 Australian railway bridges over 15 years were reviewed and filtered accordingly based on the real operational experience. Network level deterioration model for a typical bridge element group was developed using the proposed Modified Weibull approach. The condition state predictions obtained from this method were validated using statistical hypothesis tests with a test data set. Results show that the proposed model is able to not only predict the conditions in network-level accurately but also capture the model uncertainties with given confidence interval.

Keywords: bridge deterioration modelling, modified weibull approach, MCMC, metropolis-hasting algorithm, bayesian approach, Markov deterioration models

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Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

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Authors: A. Ratika Thakur, B. A. K. Sinha , C. R. K. Pathak

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Reproductive Tract Infections are recognized as a serious global health problem with direct impact on women. In the developing countries, prevalence of RTI is much higher relative to other health problems. Women of the reproductive age group are socially, mentally and physically more vulnerable to infections. Also, it is a well established fact that RTI has prolonged complications in women rather than men. It causes ectopic pregnancy, pelvic inflammatory diseases, miscarriage and infertility in the long course. Women perspective about infections is less studied. In this view the study was carried out with an aim to determine knowledge, perception and belief of married women towards reproductive tract infection. The study was conducted in Junga village, District Shimla, Himachal Pradesh, India. 48 women were interviewed regarding awareness, beliefs and taboos related to reproductive tract infection. Other aspects like fertility history were also taken into account. The data were collected using interviews with the help of interview schedule and interview guide. Data were recorded in the form of narratives and case studies. The analysis was done using quantitative and qualitative analysis. It was found that a majority of women were not aware about the reasons of infection. Moreover cultural beliefs, perceptions and taboos made them more vulnerable and exposed to RTI. Economic dependency upon men, lack of control in barrier methods were some of the factors that contributed to delayed treatment of women. It was found that a majority of women suffering from RTIs were silently bearing the burden and underwent treatment when the case would not rest in their hands.

Keywords: belief, infection, perception, taboo, women

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Authors: M. B. Peter

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The Sacrament of Penance and Reconciliation has long been upheld, by the Catholic Church, as one of the Sacraments of healing, mainly due to the sense of peace, tranquility and psychological quiescence it accords the penitent upon receiving Sacramental absolution of sin through the action of the priest. This paper explores the Sacramental character of this practice and the psychological benefits of the celebration of the Sacrament. This is achieved in two parts: firstly, by the intellectual engagement of Sacred Scripture and the consolidated Sacred Tradition that the Catholic magisterium protects and, secondly, via a broad survey of the works of Carl Gustav Jung and Orval Hobart Mowrer regarding confession and forgiveness. The former will serve to demonstrate the Catholic belief of the divine institution of the Sacrament whilst the latter will demonstrate how this belief, coupled with the existing benefit of confessing guilt, collectively bolsters the Sacrament’s overall psychological efficacy. Fundamentally, the analysis of Jung and Mowrer’s works demonstrate that man, as a naturally religious being, has an inherent need for the confession of his wrong that he might be alleviated of psychological guilt in obtaining forgiveness of a (divinely ordained) minister who is sanctioned to absolve, i.e. the priest. The paper also presents the curative effect of the celebration of this Sacrament, illustrating how, without the act of confession, man remains in moral isolation from God and man; and, that with it, man is relieved of the mysterious feeling of guilt which lies at the root of his disquiet of mind and disturbance of will. Thus, the paper penultimately establishes how the Sacrament of Reconciliation is positioned in that place where psychology and theology meet: man’s sense of guilt. It is Jung’s views on confession and forgiveness that ultimately bridge the chasm between psychology and Christianity.

Keywords: Catholic, confession, Jung, Mowrer, penance, psychology, Sacrament of Reconciliation

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Authors: Nikolaos Papadimas, Joanna Bennett, Amir Sakhaei, Timothy Dodwell

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Composite modeling of consolidation processes is playing an important role in the process and part design by indicating the formation of possible unwanted prior to expensive experimental iterative trial and development programs. Composite materials in their uncured state display complex constitutive behavior, which has received much academic interest, and this with different models proposed. Errors from modeling and statistical which arise from this fitting will propagate through any simulation in which the material model is used. A general hyperelastic polynomial representation was proposed, which can be readily implemented in various nonlinear finite element packages. In our case, FEniCS was chosen. The coefficients are assumed uncertain, and therefore the distribution of parameters learned using Markov Chain Monte Carlo (MCMC) methods. In engineering, the approach often followed is to select a single set of model parameters, which on average, best fits a set of experiments. There are good statistical reasons why this is not a rigorous approach to take. To overcome these challenges, A hierarchical Bayesian framework was proposed in which population distribution of model parameters is inferred from an ensemble of experiments tests. The resulting sampled distribution of hyperparameters is approximated using Maximum Entropy methods so that the distribution of samples can be readily sampled when embedded within a stochastic finite element simulation. The methodology is validated and demonstrated on a set of consolidation experiments of AS4/8852 with various stacking sequences. The resulting distributions are then applied to stochastic finite element simulations of the consolidation of curved parts, leading to a distribution of possible model outputs. With this, the paper, as far as the authors are aware, represents the first stochastic finite element implementation in composite process modelling.

Keywords: data-driven , material consolidation, stochastic finite elements, surrogate models

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Authors: Nancy A. Delich, Stephen D. Roberts

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This case study explores using self-efficacy theory in counseling deaf and hard of hearing students in one California school district. Self-efficacy is described as the confidence a student has for performing a set of skills required to succeed at a specific task. When students need to learn a skill, self-efficacy can be a major factor in influencing behavioral change. Self-efficacy is domain specific, meaning that students can have high confidence in their abilities to accomplish a task in one domain, while at the same time having low confidence in their abilities to accomplish another task in a different domain. The communication isolation experienced by deaf and hard of hearing children and adolescents can negatively impact their belief about their ability to navigate life challenges. There is a need to address issues that impact deaf and hard of hearing students’ social-emotional development. Failure to address these needs may result in depression, suicidal ideation, and anxiety among other mental health concerns. Self-efficacy training can be used to address these socio-emotional developmental issues with this population. Four sources of experiences are applied during an intervention: (a) enactive mastery experience, (b) vicarious experience, (c) verbal persuasion, and (d) physiological and affective states. This case study describes the use of self-efficacy training with a coed group of 12 deaf and hard of hearing high school students who experienced bullying at school. Beginning with enactive mastery experience, the counselor introduced the topic of bullying to the group. The counselor educated the students about the different types of bullying while teaching them the terminology, signs and their meanings. The most effective way to increase self-efficacy is through extensive practice. To better understand these concepts, the students practiced through role-playing with the goal of developing self-advocacy skills. Vicarious experience is the perception that students have about their capabilities. Viewing other students advocating for themselves, cognitively rehearsing what actions they will and will not take, and teaching each other how to stand up against bullying can strengthen their belief in successfully overcoming bullying. The third source of self-efficacy beliefs is verbal persuasion. It occurs when others express belief in the capabilities of the student. Didactic training and pedagogic materials on bullying were employed as part of the group counseling sessions. The fourth source of self-efficacy appraisals is physiological and affective states. Students expect positive emotions to be associated with successful skilled performance. When students practice new skills, the counselor can apply several strategies to enhance self-efficacy while reducing and controlling emotional and physical states. The intervention plan incorporated all four sources of self-efficacy training during several interactive group sessions regarding bullying. There was an increased understanding around the issues of bullying, resulting in the students’ belief of their ability to perform protective behaviors and deter future occurrences. The outcome of the intervention plan resulted in a reduction of reported bullying incidents. In conclusion, self-efficacy training can be an effective counseling and teaching strategy in addressing and enhancing the social-emotional functioning with deaf and hard of hearing adolescents.

Keywords: counseling, self-efficacy, bullying, social-emotional development, mental health, deaf and hard of hearing students

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Authors: Shu-Yu Chung, Ying-Fang Wang, Shih-Min Wang

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To conduct long-term exposure assessments are important for workers exposed to chemicals with chronic effects. However, it usually encounters with several constrains, including cost, workers' willingness, and interference to work practice, etc., leading to inadequate long-term exposure data in the real world. In this study, an integrated approach was developed for conducting long-term exposure assessment for welding workers in a shipbuilding factory. A laboratory study was conducted to yield the fume generation rates under various operating conditions. The results and the measured environmental conditions were applied to the near field/far field (NF/FF) model for predicting long term fume exposures via the Monte Carlo simulation. Then, the predicted long-term concentrations were used to determine the prior distribution in Bayesian decision analysis (BDA). Finally, the resultant posterior distributions were used to assess the long-term exposure and serve as basis for initiating control strategies for shipbuilding workers. Results show that the NF/FF model was a suitable for predicting the exposures of metal contents containing in welding fume. The resultant posterior distributions could effectively assess the long-term exposures of shipbuilding welders. Welders' long-term Fe, Mn and Pb exposures were found with high possibilities to exceed the action level indicating preventive measures should be taken for reducing welders' exposures immediately. Though the resultant posterior distribution can only be regarded as the best solution based on the currently available predicting and monitoring data, the proposed integrated approach can be regarded as a possible solution for conducting long term exposure assessment in the field.

Keywords: Bayesian decision analysis, exposure assessment, near field and far field model, shipbuilding industry, welding fume

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Authors: Demet Ozgur-Unluakin, Busenur Turkali, S. Caglar Aksezer

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Since the age of industrialization, maintenance has always been a very crucial element for all kinds of factories and plants. With today’s increasingly developing technology, the system structure of such facilities has become more complicated, and even a small operational disruption may return huge losses in profits for the companies. In order to reduce these costs, effective maintenance planning is crucial, but at the same time, it is a difficult task because of the complexity of systems. The most important aspect of correct maintenance planning is to understand the structure of the system, not to ignore the dependencies among the components and as a result, to model the system correctly. In this way, it will be better to understand which component improves the system more when it is maintained. Undoubtedly, proactive maintenance at a scheduled time reduces costs because the scheduled maintenance prohibits high losses in profits. But the necessity of corrective maintenance, which directly affects the situation of the system and provides direct intervention when the system fails, should not be ignored. When a fault occurs in the system, if the problem is not solved immediately and proactive maintenance time is awaited, this may result in increased costs. This study proposes various maintenance methods with different efficiency measures under corrective maintenance strategy on a subsystem of a thermal power plant. To model the dependencies between the components, dynamic Bayesian Network approach is employed. The proposed maintenance methods aim to minimize the total maintenance cost in a planning horizon, as well as to find the most appropriate component to be attacked on, which improves the system reliability utmost. Performances of the methods are compared under corrective maintenance strategy. Furthermore, sensitivity analysis is also applied under different cost values. Results show that all fault effect methods perform better than the replacement effect methods and this conclusion is also valid under different downtime cost values.

Keywords: dynamic Bayesian networks, maintenance, multi-component systems, reliability

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Authors: Arkadiusz Gut, Robert Mirski

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The nativist-constructivist debate constitutes a considerable part of current research on mindreading. Peter Carruthers and his colleagues are known for their nativist position in the debate and take issue with constructivist views proposed by other researchers, with Henry Wellman, Alison Gopnik, and Ian Apperly at the forefront. More specifically, Carruthers together with Evan Westra propose a nativistic explanation of Theory of Mind Scale study results that Wellman et al. see as supporting constructivism. While allowing for development of the innate mindreading system, Westra and Carruthers base their argumentation essentially on a competence-performance gap, claiming that cross-cultural differences in Theory of Mind Scale progression as well as discrepancies between infants’ and toddlers’ results on verbal and non-verbal false-belief tasks are fully explainable in terms of acquisition of other, pragmatic, cognitive developments, which are said to allow for an expression of the innately present Theory of Mind understanding. The goal of the present paper is to bring together arguments against the view offered by Westra and Carruthers. It will be shown that even though Carruthers et al.’s interpretation has not been directly controlled for in Wellman et al.’s experiments, there are serious reasons to dismiss such nativistic views which Carruthers et al. advance. The present paper discusses the following issues that undermine Carruthers et al.’s nativistic conception: (1) The concept of innateness is argued to be developmentally inaccurate; it has been dropped in many biological sciences altogether and many developmental psychologists advocate for doing the same in cognitive psychology. Reality of development is a complex interaction of changing elements that is belied by the simplistic notion of ‘the innate.’ (2) The purported innate mindreading conceptual system posited by Carruthers ascribes adult-like understanding to infants, ignoring the difference between first- and second-order understanding, between what can be called ‘presentation’ and ‘representation.’ (3) Advances in neurobiology speak strongly against any inborn conceptual knowledge; neocortex, where conceptual knowledge finds its correlates, is said to be largely equipotential at birth. (4) Carruthers et al.’s interpretations are excessively charitable; they extend results of studies done with 15-month-olds to conclusions about innateness, whereas in reality at that age there has been plenty of time for construction of the skill. (5) Looking-time experiment paradigm used in non-verbal false belief tasks that provide the main support for Carruthers’ argumentation has been criticized on methodological grounds. In the light of the presented arguments, nativism in theory of mind research is concluded to be an untenable position.

Keywords: development, false belief, mindreading, nativism, theory of mind

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Authors: Emna Hlel, Salma Jamousi, Abdelmajid Ben Hamadou

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Every model for knowledge representation to model real-world applications must be able to cope with the effects of uncertain phenomena. One of main defects of classical ontology is its inability to represent and reason with uncertainty. To remedy this defect, we try to propose a method to construct probabilistic ontology for integrating uncertain information in an ontology modeling a set of basic publications DBLP (Digital Bibliography & Library Project) using a probabilistic model.

Keywords: classical ontology, probabilistic ontology, uncertainty, Bayesian network

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Authors: Fariyal Mir

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The largest minority group over Pakistan lives in the farthest region of KPK, Chitral, which enclosed all its people in one closet despite their diversity. Chitral is considered a tourist hub and piece of paradise on earth. The major attraction of Chitral is the Kalash valley, which is also known as the homeland of kafir or 'weavers of the black robes'. Kalash people are counted as the primitive pagan tribe who practice culture, beliefs, and a lifestyle which dated beyond and distinct from the rest of the region. Their religious belief is known to be as 'animism', which means that objects, places, and creatures all possess a distinct spiritual essence. They also believe that nature plays a highly significant and spiritual role in their daily life. As they have their different festivals like (a) Chilam Josh: celebrated in May to welcome spring, (b) Uchaw: which is observed in late August to ensure good crops of wheat, (c) Chanmos: which is being observed in December for more than two weeks, grand festival and is celebrated to welcome New Year. Their concept of purity and impurity is also very traditional and part of their religious belief as well. They used to call the man as pure 'Oshniru' (pure, holy) and woman as impure 'Chetu' (dirty, polluted, or contaminated). This study is based on ethnomethodology, which focuses on the way people make sense of their daily life. Their unique belief system connects them with the descendants of the armies of Alexander the Great, who called the Hindu Kush 'Parapamisus', meaning mountains over which eagles can fly. With time, their cultural system was molded into many ways, and the same is going on with the true beauty of Chitral in the form of conversion to Islam and adaptation of modern lifestyle. Ethnomethodology also supports this, that people are always good in their original form so they can be called the true representatives of their origin and cultural identity. It also argues that human society is based on the method of achieving and displaying not on the imposition of others' order and laws. So, everybody is obliged to respect and not to harm the beliefs and culture of all other human fellows. Some historians believe that these Kalash people are from Afghanistan and their origin is Saim which is known as Thailand, but those Kalash tribe from Afghanistan were forced to embrace Islam and only Pakistan keeps these people who own unique cultural values, ornaments and entire culture. Kalasha culture has been listed by UNESCO for consideration as World Heritage. It is necessary to save these people from the cultural invasion caused by modernity, forced religious conversion to maintain the pluralistic diversity of our country.

Keywords: Chitral, cultural identity, ethnomethodology, Kalasha culture

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Authors: Netanel Stern

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Artificial intelligence (AI) algorithms have emerged as powerful tools in the field of psychiatry, offering new possibilities for enhancing diagnosis and treatment outcomes. This article explores the utilization of AI algorithms in psychiatry, highlighting their potential to revolutionize patient care. Various AI algorithms, including machine learning, natural language processing (NLP), reinforcement learning, clustering, and Bayesian networks, are discussed in detail. Moreover, ethical considerations and future directions for research and implementation are addressed.

Keywords: AI, software engineering, psychiatry, neuroimaging

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Authors: Ali S. Gargoum

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Graphical modeling plays an important role in providing efficient probability calculations in high dimensional problems (computational efficiency). In this paper, we address one of such problems where we discuss fragmenting puff models and some distributional assumptions concerning models for the instantaneous, emission readings and for the fragmenting process. A graphical representation in terms of a junction tree of the conditional probability breakdown of puffs and puff fragments is proposed.

Keywords: graphical models, influence diagrams, junction trees, Bayesian nets

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Authors: Menglu Yang, Ani Beybutyan, Rocio Pina, Miguel Angel Soria

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Domestic violence against women is one of the most serious social problems in the world. Attitudes toward domestic violence against women play an important role in the perpetration of violence against women, the way that victims respond to the violence, and how the community responds to violence against women. China and Spain are countries which have been influenced by the culture which males hold power and dominance over the female for a long time. However, as more connected with other European countries, the legal enforcement related to domestic violence against women developed earlier in Spain, and consequently, social awareness of violence against women evolved differently in two countries. The present study aimed to explore and compare the attitudes toward domestic violence against women across China and Spain, and their influence factors, such as gender equality attitudes and coercive control. Totally 506 participants, 255 from China and 251 from Spain completed questionnaires, including attitudes toward domestic violence against women, definition of violence behavior, justification for violence, gender equity attitudes, and coercive control. Results demonstrated that Chinese participants were less aware of domestic violence against women issue but more agreed that such issue was a crime than Spanish participants. In addition to cultural difference, gender equality attitudes, coercive control, gender, and age also affected attitudes toward domestic violence against women. Our findings imply attitudes toward domestic violence against women differ from countries along with the difference in gender equity attitudes and coercive control; such a difference may arise from cultural, traditional belief and current justice system influence. Despite the developed justice system, male dominance culture may lead to maintain the belief that domestic violence is domestic and private issue which police and justice force may not get involved.

Keywords: cross-cultural differences, domestic violence, public attitudes, violence against women

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Authors: Amal Jmaii, Damien Rousseliere, Besma Belhadj

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We explore the relationship between internal migration and poverty in Tunisia. We present a methodology combining potential outcomes approach with multiple imputation to highlight the effect of internal migration on poverty states. We find that probability of being poor decreases when leaving the poorest regions (the west areas) to the richer regions (greater Tunis and the east regions).

Keywords: internal migration, potential outcomes approach, poverty dynamics, Tunisia

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Authors: Javed Y. Uppal

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The background of this study is the great degree of stress that the world is experiencing today, internationally among the countries, within a community among people, and even individually within one’s own self. The significance of the study is the attempt to find a solution of this stress in the philosophy of the olden times of Jalaluddin Rumi and comparatively recently of that of Allama Iqbal. The methodology adopted in this paper is firstly exploration of the perspectives of these philosophers that are being consolidated by a number of psychic and spiritual experts of today, who are being widely read but less followed. This paper further goes on presenting brief life sketches of Rumi and Iqbal. It expounds the key concepts proposed by them and the social change that was resulted in the times of the two above mentioned metaphysical philosophers. It is further amplified that with the recent advancements, in both metaphysics and the physical sciences, the gap between the two is closing down. Both Rumi and Iqbal emphasized their common essence. The old time's concepts, postulates, and philosophies are hence once again becoming valid. The findings of this paper are that the existence of human empathy, affection and mutual social attraction among humans is still valid. The positive inner belief system that dictates our thoughts and actions is vital. As a conclusion, empathy should enable us solving our problems collectively. We need to strengthen our inner communication system, to listen to the messages that come to our inner-selves. We need to get guidance and strength from them. We need to value common needs and purposes collectively to achieve results. Spiritual energy among us is to be harnessed and utilized. Connectivity is to be recognized to unify and strengthen ties among people. Mutual bonding at small and large group levels is to be employed for the survival of the disadvantaged, and sustainability of the empowering trends. With the above guidelines, hopefully, we can define a framework towards a brave and happy new humane world.

Keywords: belief system, connectivity, human empathy, inner-self, mutual bonding, spiritual energy

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Authors: Ju-Chun Chien

Abstract:

The Ottawa Charter for Health Promotion proposed that the role of health services should shift the focus from cure to prevention. Nowadays, besides having physical examinations, people could also conduct genetic tests to provide important information for diagnosing, treating, and/or preventing illnesses. However, because of the incompletion of the Chinese Genetic Database, people in Taiwan were still unfamiliar with genetic testing. The purposes of the present study were to: (1) Figure out people’s attitudes towards genetic testing. (2) Examine factors that influence people’s intention to pursue genetic testing by means of the Health Belief Model (HBM). A pilot study was conducted on 249 Taiwanese in 2017 to test the feasibility of the self-developed instrument. The reliability and construct validity of scores on the self-developed questionnaire revealed that this HBM-based questionnaire with 40 items was a well-developed instrument. A total of 542 participants were recruited and the valid participants were 535 (99%) between the ages of 20 and 86. Descriptive statistics, one-way ANOVA, two-way contingency table analysis, Pearson’s correlation, and stepwise multiple regression analysis were used in this study. The main results were that only 32 participants (6%) had already undergone genetic testing; moreover, their attitude towards genetic testing was more positive than those who did not have the experience. Compared with people who never underwent genetic tests, those who had gone for genetic testing had higher self-efficacy, greater intention to pursue genetic testing, had academic majors in health-related fields, had chronic and genetic diseases, possessed Catastrophic Illness Cards, and all of them had heard about genetic testing. The variables that best predicted people’s intention to pursue genetic testing were cues to action, self-efficacy, and perceived benefits (the three variables all correlated with one another positively at high magnitudes). To sum up, the HBM could be effective in designing and identifying the needs and priorities of the target population to pursue genetic testing.

Keywords: genetic testing, knowledge of GT, people in Taiwan, the health belief model

Procedia PDF Downloads 294