Search results for: the health belief model

Authors: John Vergara, Giuseppe Palmese

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Fundamental studies aimed at elucidating the key contributions to corrosion performance are needed to make progress toward effective and environmentally compliant corrosion control. Epoxy/amine systems are typically employed as barrier coatings for corrosion control. However, the hardening agents used for coating applications can be very complex, making fundamental studies of water and oxygen permeability challenging to carry out. Creating model building blocks for epoxy/amine coatings is the first step in carrying out these studies. We will demonstrate the synthesis and characterization of model amine building blocks from saturated fatty acids and simple amines such as diethylenetriamine (DETA) and Bis(3-aminopropyl)amine. The structure-property relationship of thermosets made from these model amines and Diglycidyl ether of bisphenol A (DGBEA) will be discussed.

Keywords: building block, amine, synthesis, characterization

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Authors: Joyraj Chakraborty, Geoffrey Ottoy, Jean-Pierre Goemaere, Lieven De Strycker

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Sensor swarms can be a cost-effectieve and more user-friendly alternative for location based service systems in different application like health-care. To increase the lifetime of such swarm networks, the energy consumption should be scaled to the required localization accuracy. In this paper we have investigated some parameter for energy model that couples localization accuracy to energy-related sensor parameters such as signal length,Bandwidth and sample frequency. The goal is to use the model for the localization of undetermined environmental sounds, by means of wireless acoustic sensors. we first give an overview of TDOA-based localization together with the primary sources of TDOA error (including reverberation effects, Noise). Then we show that in localization, the signal sample rate can be under the Nyquist frequency, provided that enough frequency components remain present in the undersampled signal. The resulting localization error is comparable with that of similar localization systems.

Keywords: sensor swarms, localization, wireless sensor swarms, scalable energy

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Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

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Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

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Authors: Haidy S. Ghali, Engy Serag, A. Samer Ezeldin

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Copper is an essential raw material used in the construction industry. During the year 2021 and the first half of 2022, the global market suffered from a significant fluctuation in copper raw material prices due to the aftermath of both the COVID-19 pandemic and the Russia-Ukraine war, which exposed its consumers to an unexpected financial risk. Thereto, this paper aims to develop two ANN-LSTM price prediction models, using Python, that can forecast the average monthly copper prices traded in the London Metal Exchange; the first model is a multivariate model that forecasts the copper price of the next 1-month and the second is a univariate model that predicts the copper prices of the upcoming three months. Historical data of average monthly London Metal Exchange copper prices are collected from January 2009 till July 2022, and potential external factors are identified and employed in the multivariate model. These factors lie under three main categories: energy prices and economic indicators of the three major exporting countries of copper, depending on the data availability. Before developing the LSTM models, the collected external parameters are analyzed with respect to the copper prices using correlation and multicollinearity tests in R software; then, the parameters are further screened to select the parameters that influence the copper prices. Then, the two LSTM models are developed, and the dataset is divided into training, validation, and testing sets. The results show that the performance of the 3-Month prediction model is better than the 1-Month prediction model, but still, both models can act as predicting tools for diverse economic situations.

Keywords: copper prices, prediction model, neural network, time series forecasting

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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Authors: Xiuguo Zhao, He Li, Alireza Yazdani, Xiaoning Zheng, Xinxi Xu

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Wound infected poses a serious threat to the surgery on the patient during the process of surgery. Understanding the bacteria-carrying particles (BCPs) transportation and deposition in the open surgical wound model play essential role in protecting wound against being infected. Therefore BCPs transportation and deposition in the surgical wound model were investigated using force-coupling method (FCM) based computational fluid dynamics. The BCPs deposition in the wound was strongly associated with BCPs diameter and concentration. The results showed that the rise on the BCPs deposition was increasing not only with the increase of BCPs diameters but also with the increase of the BCPs concentration. BCPs deposition morphology was impacted by the combination of size distribution, airflow patterns and model geometry. The deposition morphology exhibited the characteristic with BCPs deposition on the sidewall in wound model and no BCPs deposition on the bottom of the wound model mainly because the airflow movement in one direction from up to down and then side created by laminar system constructing airflow patterns and then made BCPs hard deposit in the bottom of the wound model due to wound geometry limit. It was also observed that inertial impact becomes a main mechanism of the BCPs deposition. This work may contribute to next study in BCPs deposition limit, as well as wound infected estimation in surgical-site infections.

Keywords: BCPs deposition, computational fluid dynamics, force-coupling method (FCM), numerical simulation, open surgical wound model

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Authors: Maryam Gallab, Hafida Bouloiz, Youness Chater, Mohamed Tkiouat

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The aim of this paper is to present a model based on multi-agent systems in order to manage the maintenance activities and to ensure the reliability and availability of machines just with the required resources (operators, tools). The interest of the simulation is to solve the complexity of the system and to find results without cost or wasting time. An implementation of the model is carried out on the AnyLogic platform to display the defined performance indicators.

Keywords: maintenance, complexity, simulation, multi-agent systems, AnyLogic platform

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Authors: Mona Almanasef, Dalia Almaghaslah, Geetha Kandasamy, Rajalakshimi Vasudevan, Sadia Batool

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Background: Community pharmacists are one of the most accessible healthcare practitioners worldwide and their services are used by a large proportion of the population. Expanding the roles of community pharmacists could contribute to reducing pressure on general health practice and other areas of health services. This research aimed to evaluate the contribution of community pharmacists in the provision of public health services and to investigate the perceived barriers to the provision of these services in Saudi Arabia. Materials and Methods: This study followed a cross-sectional design using an online anonymous self-administered questionnaire. The study took place in the Asir region, Saudi Arabia, between September 2019 and February 2020. A convenience sampling strategy was used to select and recruit the study participants. The questionnaire was adapted from previous research and involved three sections: demographics, involvement in public health services and barriers to practicing public health roles. Results: The total number of respondents was 193. The proportion of respondents who reported that they were “very involved” or “involved” in each service was 61.7% for weight management, 60.6% for sexual health, 57.5% for healthy eating, 53.4% for physical activity promotion, 51.3% for dental health, 46.1% for smoking cessation, 39.4% for screening for diabetes, 35.7% for screening for hypertension, 31.1% for alcohol dependence and drug misuse counseling, 30.6% for screening for dyslipidaemia, and 21.8% for vaccination and immunization. Most of the barriers in the current research were rated as having low relevance to the provision of public health services. Conclusion: Findings in the current research suggest that community pharmacists in the Asir region have varying levels of involvement in public health roles. Further research needs to be undertaken to understand the barriers to the provision of public health services and what strategies would be beneficial for enhancing the public health role of community pharmacists in Saudi Arabia.

Keywords: community pharmacist, public health, Asir region, Saudi Arabia

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Authors: Assad Maalouf, Lunjin Lu, James Lynott

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We design and implement a precise model of string operations using finite state machine transformers and state transformers to approximate the values string variables can take throughout the execution of the program.We use our model to analyze Android program string variables. Our experimental results show that our string analysis is very efficient at detecting the contextual effect of string operations on the string variables. Our model proved to be very useful when it came to verifying statements about the string variables of the program.

Keywords: abstract interpretation, android, static analysis, string analysis

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Authors: Maryam Saeidi, Ehsan Motamedian, Seyed Abbas Shojaosadati

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Zymomonas mobilis is known as an example of the uncoupled growth phenomenon. This microorganism also has a unique metabolism that degrades glucose by the Entner–Doudoroff (ED) pathway. In this paper, a genome-scale metabolic model including 434 genes, 757 reactions and 691 metabolites was reconstructed to simulate uncoupled growth and study its effect on flux distribution in the central metabolism. The model properly predicted that ATPase was activated in experimental growth yields of Z. mobilis. Flux distribution obtained from model indicates that the major carbon flux passed through ED pathway that resulted in the production of ethanol. Small amounts of carbon source were entered into pentose phosphate pathway and TCA cycle to produce biomass precursors. Predicted flux distribution was in good agreement with experimental data. The model results also indicated that Z. mobilis metabolism is able to produce biomass with maximum growth yield of 123.7 g (mol glucose)-1 if ATP synthase is coupled with growth and produces 82 mmol ATP gDCW-1h-1. Coupling the growth and energy reduced ethanol secretion and changed the flux distribution to produce biomass precursors.

Keywords: genome-scale metabolic model, Zymomonas mobilis, uncoupled growth, flux distribution, ATP dissipation

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Authors: Mokshida Bhat

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This paper examines the representation of patriarchy in the movies 'Qala' and 'Black Swan' and how it affects the mental health of women. Both movies portray female characters who are subject to patriarchal attitudes and structures that limit their choices and opportunities and contribute to negative mental health outcomes. In 'Qala' the central character Qala confronts the patriarchal attitudes of her family and community, which contribute to feelings of frustration and despair. In 'Black Swan' the main character Nina is subject to the demands and expectations of a patriarchal system that leads to anxiety, paranoia, and disconnection from her own body and emotions. Both movies highlight the harmful impact of patriarchal attitudes on women's mental health, including feelings of disempowerment, objectification, and self-doubt. The paper suggests that these negative outcomes can be addressed through a rejection of patriarchal norms and an assertion of one's own agency and identity. Overall, this paper demonstrates the importance of recognizing the role of patriarchy in contributing to mental health struggles for women and the need for more diverse and empowering representations of women in media.

Keywords: patriarchy, mental health, depression, PTSD, mental health in Indian cinema, patriarchy in Indian cinema, feminism and patriarchy, sexism

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Authors: Zachary Smith, Riette Bloomfield, Taylor Dukate, Joshua Halterman, Noah Phillips

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College students have stressful lives, classes, work, and home life; it all adds up to anxiety and stress. Most students can manage the stress, but some can’t and need help. Mental health issues are on the rise among college-age students, which could lead to other health issues, depression, or even suicidal thoughts. There needs to be an outlet for these students, and one suggestion is participating in sports or exercise/recreation activities. “Strong body, strong mind” is a concept that has been researched for many decades now. While that has been preached, depression and anxiety have still been at an all-time high in college students within the last five years. College students are expected to stay on top of their academic coursework, obtain and keep relationships, adjust to living independently, and economic strain. As p oor mental health becomes inherent, struggles academically, dropping out of school, becoming involved in immoral situations, or as far as committing suicide, can be seen shortly after. This research proposal examines the positive impact of sports on students' mental health in post-secondary education programs. The study aims to investigate how participation in college sports can alleviate stress, anxiety, and depression, improve mood and focus, and contribute to better academic performance. With the increasing prevalence of mental health issues among college students and the growing emphasis on mental health awareness, this research is significant for understanding and managing collegiate sports programs. Overall, sports help with mental and physical health for all ages.

Keywords: mental health, sports, college students, recreation programs

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Authors: Mohd Yusri Ibrahim

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Although it is known that interpersonal skills are essential for personal development, the debate however continues as to how to measure those skills, especially in youths. This study was conducted to develop a measurement model of interpersonal skills by suggesting three construct namely personal, skills and relationship; six function namely self, perception, listening, conversation, emotion and conflict management; and 30 behaviours as indicators. This cross-sectional survey by questionnaires was applied in east side of peninsula of Malaysia for 150 respondents, and analyzed by structural equation modelling (SEM) by AMOS. The suggested constructs, functions and indicators were consider accepted as measurement elements by observing on regression weight for standard loading, average variance extracted (AVE) for convergent validity, square root of AVE for discriminant validity, composite reliability (CR), and at least three fit indexes for model fitness. Finally, a measurement model of interpersonal skill for youth was successfully developed.

Keywords: interpersonal communication, interpersonal skill, youth, communication skill

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Authors: Mohd Asrul Affedi, Nyi Nyi Naing

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Overdispersion is present in count data, and basically when a phenomenon happened, a Negative Binomial (NB) is commonly used to replace a standard Poisson model. Analysis of count data event, such as mortality cases basically Poisson regression model is appropriate. Hence, the model is not appropriate when existing a zero values. The zero-inflated negative binomial model is appropriate. In this article, we modelled the mortality cases as a dependent variable by age categorical. The objective of this study to determine existing overdispersion in mortality data of AIDS co-infection patients in Kelantan.

Keywords: negative binomial death rate, overdispersion, zero-inflation negative binomial death rate, AIDS

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Authors: Marzena Świgoń

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Nowadays, graduates should be prepared for serious challenges in the internal and external labor market. The notion that a degree is a “passport to employment” has been relegated to the past. In the last few years a phenomenon in the form of the increasing unemployment of highly educated young people in EU countries, including Poland has been observed. Empirical studies were conducted among Polish students in the scope of the so-called self-perceived employability review. In this study, a special scale was used which consisted of 19 statements regarding five components: student’s perception of university; field of study; self-belief; state of the external labor market; and, personal knowledge management. The respondent group consisted of final-year master’s students of International Relations at the University of Warmia and Mazury in Olsztyn, Poland. The findings of the empirical studies were compiled using statistical methods: descriptive statistics and inferential statistics. In general, in light of the conducted studies, the self-perceived employability of the Polish students was not high. Limitations of the studies were discussed, as well as the implications for future research in the scope of the students’ employability.

Keywords: self-perceived employability, students of international relations, university students, students employability

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Authors: Hari Pulapaka

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This paper defines and develops the notion of a traceability index for food and may be used by any consumer (restaurant, distributor, average consumer etc.). The concept is then extended to a region's food system as a way to measure how well a regional food system utilizes its own bounty or at least, is connected to its food sources. With increasing emphases on the sustainability of aspects of regional and ultimately, the global food system, it is reasonable to accept that if we know how close (in relative terms) an end-user of a set of ingredients (as they traverse through the maze of supply chains) is from the sources, we may be better equipped to evaluate the quality of the set as measured by any number of qualitative and quantitative criteria. We propose a mathematical model which may be adapted to a number of contexts and sizes. Two hypothetical cases of different scope are presented which highlight how the model works as an evaluator of steps between an end-user and the source(s) of the ingredients they consume. The variables in the model are flexible enough to be adapted to other applications beyond food systems.

Keywords: food, traceability, supply chain, mathematical model

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Authors: L. Ramirez, E. Guillén, J. Sánchez

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Some of the main goals about telecare such as monitoring, treatment, telediagnostic are deployed with the integration of applications with specific appliances. In order to achieve a coherent model to integrate software, hardware, and healthcare systems, different telehealth models with Internet of Things (IoT), cloud computing, artificial intelligence, etc. have been implemented, and their advantages are still under analysis. In this paper, we propose an integrated model based on IoT architecture and cloud computing telehealth center. Analytics module is presented as a solution to control an ideal diagnostic about some diseases. Specific features are then compared with the recently deployed conventional models in telemedicine. The main advantage of this model is the availability of controlling the security and privacy about patient information and the optimization on processing and acquiring clinical parameters according to technical characteristics.

Keywords: analytics, telemedicine, internet of things, cloud computing

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Authors: Gamze Ozel, Selen Cakmakyapan

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We introduce a new model called the Marshall-Olkin Rayleigh distribution which extends the Rayleigh distribution using Marshall-Olkin transformation and has increasing and decreasing shapes for the hazard rate function. Various structural properties of the new distribution are derived including explicit expressions for the moments, generating and quantile function, some entropy measures, and order statistics are presented. The model parameters are estimated by the method of maximum likelihood and the observed information matrix is determined. The potentiality of the new model is illustrated by means of real life data set.

Keywords: Marshall-Olkin distribution, Rayleigh distribution, estimation, maximum likelihood

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Authors: Sharifirad M., Poursaeed A., Lashgarara F., Mirdamadi S. M.

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Introduction: Paddy farming has been reported as one of the most important causes of non-fatal injuries and occupational accidents among farmers. The ignorance of the health of farmers can cause harm to farmers and lead to disability. As a result, these health consequences can result in less exploitation and economic growth in households. Therefore, this study aimed to determine the general health status of paddy field workers in Mazandaran province, Iran. Materials & Methods: This cross-sectional descriptive study evaluated 384 paddy farmers in Mazandaran province, Iran, who were selected using stratified random sampling. The required data were collected using the standard questionnaire of GHQ-28 with four domains of somaticsymptoms, anxiety and insomnia, social dysfunction, and symptoms of depression. The obtained data were then analyzed using SPSS software (version 25) through Spearman, Kendall, Mann-Whitney, and Kruskal-Wallis tests. Findings: The highest number of participants in this study was in the age group of 50-59 years, with a mean age of 46.9 years. According to the results, the total general health score was obtained at 64.3% for the subjects. Moreover, the scores of four areas of general health were determined at 91.1% (depression symptoms), 73.4% (social dysfunction), 48.7% (anxiety symptoms and insomnia), and 47.1% (somatic symptoms) in descending order. Discussions& Conclusions: The general health of the studied population was not in a good range. In addition, the most observed disorder in the general health of paddy farmers was related to the symptoms of depression, followed by somatic symptoms.

Keywords: general-health, mazandaran, paddyfield

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Authors: Deginet Aklilu, Tianqi Wang, Endwoke Amsalu, Wei Feng, Zhiwei Li, Xia Li, Lixin Tao, Yanxia Luo, Moning Guo, Xiangtong Liu, Xiuhua Guo

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Extreme temperature-related cardiovascular diseases (CVDs) have become a growing public health concern. However, the impact of temperature on the cause of specific CVDs has not been well studied in the study area. The objective of this study was to assess the impact of temperature on cause-specific cardiovascular hospital admissions in Beijing, China. We obtained data from 172 large general hospitals from the Beijing Public Health Information Center Cardiovascular Case Database and China. Meteorological Administration covering 16 districts in Beijing from 2013 to 2017. We used a time-stratified case crossover design with a distributed lag nonlinear model (DLNM) to derive the impact of temperature on CVD in hospitals back to 27 days on CVD admissions. The temperature data were stratified as cold (extreme and moderate ) and hot (moderate and extreme ). Within five years (January 2013-December 2017), a total of 460,938 (male 54.9% and female 45.1%) CVD admission cases were reported. The exposure-response relationship for hospitalization was described by a "J" shape for the total and cause-specific. An increase in the six-day moving average temperature from moderate hot (30.2 °C) to extreme hot (36.9 °C) resulted in a significant increase in CVD admissions of 16.1%(95% CI = 12.8%-28.9%). However, the effect of cold temperature exposure on CVD admissions over a lag time of 0-27 days was found to be non significant, with a relative risk of 0.45 (95% CI = 0.378-0.55) for extreme cold (-8.5 °C)and 0.53 (95% CI = 0.47-0.60) for moderate cold (-5.6 °C). The results of this study indicate that exposure to extremely high temperatures is highly associated with an increase in cause-specific CVD admissions. These finding may guide to create and raise awareness of the general population, government and private sectors regarding on the effects of current weather conditions on CVD.

Keywords: admission, Beijing, cardiovascular diseases, distributed lag non linear model, temperature

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Authors: David P. Horton, Gary Lynch-Wood

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Western populations are aging, prone to various lifestyle health problems, and increasing their demand for health and social care services. This demand has created enormous fiscal and regulatory challenges. In response, government institutions have deployed strategies of behavior modification to encourage people to exercise greater personal responsibility over their health and care needs (i.e., welfare responsibilisation). Policy strategies are underpinned by the assumption that people if properly supported, will make better health and lifestyle selections. Not only does this absolve governments of the responsibility for meeting all health and care needs, but it also enables government institutions to assert fiscal control over welfare spending. Looking at the regulation of health and social care in the UK, the authors identify and outline a suite of regulatory tools that are designed to extract and manage the resources of health and social care services users and to encourage them to make (‘better’) use of these resources. This is important for our understanding of how health and social care regulation is responding to ongoing social and economic challenges. It is also important because there has been a failure to systematically examine the relevance of resources for regulation, which is surprising given that resources are crucial to how and whether regulation succeeds or fails. In particular, drawing from the regulatory welfare state concept, the authors analyse the key legal and regulatory changes and mechanisms that have been introduced since the 2008 financial crisis, focusing on critical measures such as the Health and Social Care Act and regulations introduced under the National Health Service Act. The authors show how three types of user resources (i.e., tangible, labor, and data) are being used to assert fiscal control and increase welfare responsibilisation. Amongst other things, the paper concludes that service users have become more than rule followers and targets of behavioral modification; rather, they are producers of resources that regulatory systems have come to rely on.

Keywords: health care, regulation, resources, social care

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Authors: H. Shokouhmand, H. Sobhani, B. Sajadi, M. Degheh

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In recent years, experimental and numerical investigation of water UV reactors has increased significantly. The main drawback of experimental methods is confined and expensive survey of UV reactors features. In this study, a CFD model utilizing the eulerian-lagrangian framework is applied to analysis the disinfection performance of a closed conduit reactor which contains four UV lamps perpendicular to the flow. A discrete ordinates (DO) model was employed to evaluate the UV irradiance field. To investigate the importance of each of lamps on the inactivation performance, in addition to the reference model (with 4 bright lamps), several models with one or two bright lamps in various arrangements were considered. All results were reported in three inactivation kinetics. The results showed that the log inactivation of the two central bright lamps model was between 88-99 percent, close to the reference model results. Also, whatever the lamps are closer to the main flow region, they have more effect on microbial inactivation. The effect of some operational parameters such as water flow rate, inlet water temperature, and lamps power were also studied.

Keywords: Eulerian-Lagrangian framework, inactivation kinetics, log inactivation, water UV reactor

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Authors: Hong-Ming Chen

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This work considers the resolution of the Hull and White interest rate model with the jump process. A deterministic process is adopted to model the random behavior of interest rate variation as deterministic perturbations, which is depending on the time t. The Brownian motion and jumps uncertainty are denoted as the integral functions piecewise constant function w(t) and point function θ(t). It shows that the interest rate function and the yield function of the Hull and White interest rate model with jump process can be obtained by solving a nonlinear semi-infinite programming problem. A relaxed cutting plane algorithm is then proposed for solving the resulting optimization problem. The method is calibrated for the U.S. treasury securities at 3-month data and is used to analyze several effects on interest rate prices, including interest rate variability, and the negative correlation between stock returns and interest rates. The numerical results illustrate that our approach essentially generates the yield functions with minimal fitting errors and small oscillation.

Keywords: optimization, interest rate model, jump process, deterministic

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Authors: Zhaoxin Luo, Michael Zhu

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In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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Authors: Madhvi Bhayani

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Introduction: Due to the rapid pace of urbanization, the urban health issues have become one of the significant threats to future development in India. It also poses serious repercussions on the citizen’s health. As urbanization in India is increasing at an unprecedented rate and it has generated the urban health crisis among the city dwellers especially the urban poor. The increasing proportion of the urban poor and vulnerable to the health indicators worse than the rural counterparts, they face social and financial barriers in accessing healthcare services and these conditions make human health at risk. The Local as well as the State and National governments are alike tackling with the challenges of urbanization as it has become very essential for the government to provide the basic necessities and better infrastructure that make life in cities safe and healthy. Thus, the paper argues that if no major realistic steps are taken with immediate effect, the citizens will face a huge burden of health hazards. Aim: This paper attempts to analyze the current infrastructure, government planning, and its future policy, it also discusses the challenges and outcomes of urbanization on health and its impact on it and it will also predict the future trend with regard to disease burden in the urban areas. Methods: The paper analyzes on the basis of the secondary data by taking into consideration the connection between the Rapid Urbanization and Public Health Challenges, health and health care system and its services delivery to the citizens especially to the urban poor. Extensive analyses of government census reports, health information and policy, the government health-related schemes, urban development and based on the past trends, the future status of urban infrastructure and health outcomes are predicted. The social-economic and political dimensions are also taken into consideration from regional, national and global perspectives, which are incorporated in the paper to make realistic predictions for the future. Findings and Conclusion: The findings of the paper show that India suffers a lot due to the double burden of rapidly increasing in diseases and also growing health inequalities and disparities in health outcomes. Existing tools of governance of urban health are falling short to provide the better health care services. They need to strengthen the collaboration and communication among the state, national and local governments and also with the non-governmental partners. Based on the findings the policy implications are then described and areas for future research are defined.

Keywords: health care, urbanization, urban health, service delivery

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Authors: Paul Dallyn, Ashraf El-Hamalawi, Alessandro Palmeri, Bob Knight

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In order to better understand the long term implications of the grout wear failure mode in large-diameter plain-sided grouted connections, a numerical model has been developed and calibrated that can take advantage of existing operational plant data to predict the wear accumulation for the actual load conditions experienced over a given period, thus limiting the need for expensive monitoring systems. This model has been derived and calibrated based on site structural condition monitoring (SCM) data and supervisory control and data acquisition systems (SCADA) data for two operational wind turbine generator substructures afflicted with this challenge, along with experimentally derived wear rates.

Keywords: grouted connection, numerical model, offshore structure, wear, wind energy

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Authors: Vasti Oelofse, Niekie van der Merwe, Dorita du Toit

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This study addresses the need for a unified best practice model for Physical Education across BRICS nations, as current research primarily offers individual country recommendations. Drawing on relevant literature within the framework of Bronfenbrenner’s Ecological Systems Theory, as well as data from open-ended questionnaires completed by Physical Education experts from the BRICS countries, , the study develops a best practice model based on identified challenges and effective practices in Physical Education. A model is proposed that incorporates flexible and resource-efficient strategies tailored to address PE challenges specific to these countries, enhancing outcomes for learners, empowering teachers, and fostering systemic collaboration among BRICS members. The proposed model comprises six key areas: “Curriculum and policy requirements”, “General approach”, “Theoretical basis”, “Strategies for presenting content”, “Teacher training”, and “Evaluation”. The “Strategies for presenting program content” area addresses both well-resourced and poorly resourced schools, adapting curriculum, teaching strategies, materials, and learner activities for varied socio-economic contexts. The model emphasizes a holistic approach to learner development, engaging environments, and continuous teacher training. A collaborative approach among BRICS countries, focusing on shared best practices and continuous improvement, is vital for the model's successful implementation, enhancing Physical Education programs and outcomes across these nations.

Keywords: BRICS countries, physical education, best practice model, ecological systems theory

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Authors: Helena Baffoe

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The US has developed numerous programs over the past 50 years to enhance the lives of those who suffer from mental health illnesses and substance abuse, as well as the effectiveness of their treatments. Despite these advances over the past 50 years, there hasn't been a corresponding improvement in American public attitudes and beliefs about mental health disorders and substance abuse. Highly publicized acts of violence frequently elicit comments that blame the perpetrator's perceived mental health disorder since such people are thought to be substance abusers. Despite these strong public beliefs and perception about mental disorder and substance abuse, concreate empirical evidence that entail this perception is lacking, and evidence of their effectiveness has not been integrated. A rich data was collected from Substance Abuse and Mental Health Services Administration (SAMHSA) with a hypothesis that people who are diagnosed with a mental health disorder are likely to be diagnosed with substance abuse using logit regression analysis and Instrumental Variable. It was found that depressive, anxiety, and trauma/stressor mental disorders constitute the most common mental disorder in the United States, and the study could not find statistically significant evidence that being diagnosed with these leading mental health disorders in the United States does necessarily imply that such a patient is diagnosed with substances abuse. Thus, the public has a misconception of mental health and substance abuse issues, and social workers' responsibilities are outlined in order to assist ameliorate this attitude and perception.

Keywords: mental health disorder, substance abuse, role of a social worker, evidence based research

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Authors: Tarek M. Alguhane, Ayman H. Khalil, Nour M. Fayed, Ayman M. Ismail

Abstract:

An existing RC building in Madinah is seismically evaluated with and without infill wall. Four model systems have been considered i. e. model I (no infill), model IIA (strut infill-update from field test), model IIB (strut infill- ASCE/SEI 41) and model IIC (strut infill-Soft storey-ASCE/SEI 41). Three dimensional pushover analyses have been carried out using SAP 2000 software incorporating inelastic material behavior for concrete, steel and infill walls. Infill wall has been modeled as equivalent strut according to suggested equation matching field test measurements and to the ASCE/SEI 41 equation. The effect of building modeling on the performance point as well as capacity and demand spectra due to EQ design spectrum function in Madinah area has been investigated. The response modification factor (R) for the 5 story RC building is evaluated from capacity and demand spectra (ATC-40) for the studied models. The results are summarized and discussed.

Keywords: infill wall, pushover analysis, response modification factor, seismic assessment

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Authors: André Jesus, Yanjie Zhu, Irwanda Laory

Abstract:

Structural health monitoring is one of the most promising technologies concerning aversion of structural risk and economic savings. Analysts often have to deal with a considerable variety of uncertainties that arise during a monitoring process. Namely the widespread application of numerical models (model-based) is accompanied by a widespread concern about quantifying the uncertainties prevailing in their use. Some of these uncertainties are related with the deterministic nature of the model (code uncertainty) others with the variability of its inputs (parameter uncertainty) and the discrepancy between a model/experiment (systematic uncertainty). The actual process always exhibits a random behaviour (observation error) even when conditions are set identically (residual variation). Bayesian inference assumes that parameters of a model are random variables with an associated PDF, which can be inferred from experimental data. However in many Bayesian methods the determination of systematic uncertainty can be problematic. In this work systematic uncertainty is associated with a discrepancy function. The numerical model and discrepancy function are approximated by Gaussian processes (surrogate model). Finally, to avoid the computational burden of a fully Bayesian approach the parameters that characterise the Gaussian processes were estimated in a four stage process (modular Bayesian approach). The proposed methodology has been successfully applied on fields such as geoscience, biomedics, particle physics but never on the SHM context. This approach considerably reduces the computational burden; although the extent of the considered uncertainties is lower (second order effects are neglected). To successfully identify the considered uncertainties this formulation was extended to consider multiple responses. The efficiency of the algorithm has been tested on a small scale aluminium bridge structure, subjected to a thermal expansion due to infrared heaters. Comparison of its performance with responses measured at different points of the structure and associated degrees of identifiability is also carried out. A numerical FEM model of the structure was developed and the stiffness from its supports is considered as a parameter to calibrate. Results show that the modular Bayesian approach performed best when responses of the same type had the lowest spatial correlation. Based on previous literature, using different types of responses (strain, acceleration, and displacement) should also improve the identifiability problem. Uncertainties due to parametric variability, observation error, residual variability, code variability and systematic uncertainty were all recovered. For this example the algorithm performance was stable and considerably quicker than Bayesian methods that account for the full extent of uncertainties. Future research with real-life examples is required to fully access the advantages and limitations of the proposed methodology.

Keywords: bayesian, calibration, numerical model, system identification, systematic uncertainty, Gaussian process

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