Search results for: the health belief model

Authors: Maryam Maleki, Esther Mead, Mohammad Arani, Nitin Agarwal

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This study is conducted to examine how opposing viewpoints related to COVID-19 were diffused on Twitter. To accomplish this, six datasets using two epidemiological models, SIR (Susceptible, Infected, Recovered) and SEIZ (Susceptible, Exposed, Infected, Skeptics), were analyzed. The six datasets were chosen because they represent opposing viewpoints on the COVID-19 pandemic. Three of the datasets contain anti-subject hashtags, while the other three contain pro-subject hashtags. The time frame for all datasets is three years, starting from January 2020 to December 2022. The findings revealed that while both models were effective in evaluating the propagation trends of these polarizing viewpoints, the SEIZ model was more accurate with a relatively lower error rate (6.7%) compared to the SIR model (17.3%). Additionally, the relative error for both models was lower for anti-subject hashtags compared to pro-subject hashtags. By leveraging epidemiological models, insights into the propagation trends of polarizing viewpoints on Twitter were gained. This study paves the way for the development of methods to prevent the spread of ideas that lack scientific evidence while promoting the dissemination of scientifically backed ideas.

Keywords: mathematical modeling, epidemiological model, seiz model, sir model, covid-19, twitter, social network analysis, social contagion

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Authors: Justin Zhengjie Tan, Yang Zhao

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Adiabatic Rapid Passage, a popular method of achieving population inversion, is studied in a Rabi dimer model in the presence of noise which acts as a dissipative environment. The integration of the multi-Davydov D2 Ansatz into the time-dependent variational framework enables us to model the intricate quantum system accurately. By influencing the system with a driving field strength resonant with the energy spacing, the probability of adiabatic rapid passage, which is modelled after the Landau Zener model, can be derived along with several other observables, such as the photon population. The effects of a dissipative environment can be reproduced by coupling the system to a common phonon mode. By manipulating the strength and frequency of the driving field, along with the coupling strength of the phonon mode to the qubits, we are able to control the qubits and photon dynamics and subsequently increase the probability of Adiabatic Rapid Passage happening.

Keywords: quantum electrodynamics, adiabatic rapid passage, Landau-Zener transitions, dissipative environment

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Authors: E. D. Paul, O. F. Paul, J. E. Toryila, A. J. Salifu, C. E. Gimba

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Adsorption of Cd2+ ions from aqueous solution by Chitosan, a natural polymer, obtained from a mixture of the exoskeletons of Littorina littorea (Periwinkle) and Achatinoidea (Snail) was studied at varying adsorbent dose, contact time, metal ion concentrations, temperature and pH using batch adsorption method. The equilibrium adsorption isotherms were determined between 298 K and 345 K. The adsorption data were adjusted to Langmuir, Freundlich and the pseudo second order kinetic models. It was found that the Langmuir isotherm model most fitted the experimental data, with a maximum monolayer adsorption of 35.1 mgkg⁻¹ at 308 K. The entropy and enthalpy of adsorption were -0.1121 kJmol⁻¹K⁻¹ and -11.43 kJmol⁻¹ respectively. The Freundlich adsorption model, gave Kf and n values consistent with good adsorption. The pseudo-second order reaction model gave a straight line plot with rate constant of 1.291x 10⁻³ kgmg⁻¹ min⁻¹. The qe value was 21.98 mgkg⁻¹, indicating that the adsorption of Cadmium ion by the chitosan composite followed the pseudo-second order kinetic model.

Keywords: adsorption, chitosan, littorina littorea, achatinoidea, natural polymer

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Authors: Daniel Phillip Svozil, Eileen Petrie, Kristy Robson, Lee Baumgartner, Max Finlayson

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Recreational angling is recognized for its potential to improve health and wellbeing which has translated into policy initiatives to increase participation in the sport. However, these benefits have been examined mostly among voluntary participants. Thus, there is an assumption that recreational angling is perceived equally and that these benefits may be evident even to non-anglers. This paper reviews the published benefits to health and wellbeing of recreational angling and proposes an approach to systemically analyze interactions among the perceptions, socio-economic barriers, and knowledge of these benefits among people at different levels of participation (including non-participants). The outcomes of this study will assist in identifying the feasibility of recreational angling for improving health and wellbeing outcomes among participants (i.e., fishing may not be for everyone) and designing interventions that address the perceptions and socio-economic barriers among individuals that may benefit from participation in recreational angling.

Keywords: angling, health, wellbeing, connecting with nature

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Authors: Elackiya Sithamparanathan

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Chemical agents used during the Sri Lankan civil war continue to threaten human and environmental health as affected areas are re-settled. Bioremediation is a cost-effective and eco-friendly approach to degrading chemical agents, and has greater public acceptance than chemical degradation. Baseline data on contaminant distribution, environmental parameters, and indigenous microbes are required before bioremediation can commence. The culture and isolate of suitable microbes and enzymes should be followed by laboratory trials, before field application and long-term monitoring of contaminant concentration, soil parameters, microbial ecology, and public health to monitor environmental and public health. As local people are not aware of the persistence of warfare chemicals and do not understand the potential impacts on human health, community awareness programs are required. Active community participation, and collaboration with international and local agencies, would contribute to the success of bioremediation and the effective removal of chemical agents in war affected areas of Sri Lanka.

Keywords: bioremediation, environmental protection, human health, war affected regions in Sri Lanka

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Authors: Nurulhuda A. Manaf, Nor Najihah Zainal Abidin, Nur Amalina Jamaludin

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Coordinating service interactions are a vital part of developing distributed applications that are built up as networks of autonomous participants, e.g., software components, web services, online resources, involve a collaboration between a diverse number of participant services on different providers. The complexity in coordinating service interactions reflects how important the techniques and approaches require for designing and coordinating the interaction between participant services to ensure the overall goal of a collaboration between participant services is achieved. The objective of this research is to develop capability of steering a complex service interaction towards a desired outcome. Therefore, an efficient technique for modelling, generating, and verifying the coordination of service interactions is developed. The developed model describes service interactions using service choreographies approach and focusing on a declarative approach, advocating an Object Management Group (OMG) standard, Semantics of Business Vocabulary and Rules (SBVR). This model, namely, SBVR model for service choreographies focuses on a declarative deontic rule expressing both obligation and prohibition, which can be more useful in working with coordinating service interactions. The generated SBVR model is then be formulated and be transformed into Alloy model using Alloy Analyzer for verifying the generated SBVR model. The transformation of SBVR into Alloy allows to automatically generate the corresponding coordination of service interactions (service choreography), hence producing an immediate instance of execution that satisfies the constraints of the specification and verifies whether a specific request can be realised in the given choreography in the generated choreography.

Keywords: service choreography, service coordination, behavioural modelling, complex interactions, declarative specification, verification, model transformation, semantics of business vocabulary and rules, SBVR

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Authors: Dhaladhuli Pranavi, Amirtham Rajagopal

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There are various failure modes in ceramic matrix composites; notable ones are fiber breakage, matrix cracking and fiber matrix debonding. Crack nucleation and propagation in microstructure of such composites requires an understanding of interaction of crack with the multiple inclusion heterogeneous system and interfaces. In order to assess structural integrity, the material parameters especially of the interface that governs the crack growth should be determined. In the present work, a nonlocal phase field approach is proposed to model the crack interface interaction in such composites. Nonlocal approaches help in understanding the complex mechanisms of delamination growth and mitigation and operates at a material length scale. The performance of the proposed formulation is illustrated through representative numerical examples. The model proposed is implemented in the framework of the finite element method. Several parametric studies on interface crack interaction are conducted. The proposed model is easy and simple to implement and works very well in modeling fracture in composite systems.

Keywords: composite, interface, nonlocal, phase field

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Authors: Kassahun Birhanu Tadesse, Megersa Olumana Dinka

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Reliable future river flow information is basic for planning and management of any river systems. For data scarce river system having only a river flow records like the Waterval River, a univariate time series models are appropriate for river flow forecasting. In this study, a univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied for forecasting Waterval River flow using GRETL statistical software. Mean monthly river flows from 1960 to 2016 were used for modeling. Different unit root tests and Mann-Kendall trend analysis were performed to test the stationarity of the observed flow time series. The time series was differenced to remove the seasonality. Using the correlogram of seasonally differenced time series, different SARIMA models were identified, their parameters were estimated, and diagnostic check-up of model forecasts was performed using white noise and heteroscedasticity tests. Finally, based on minimum Akaike Information (AIc) and Hannan-Quinn (HQc) criteria, SARIMA (3, 0, 2) x (3, 1, 3)12 was selected as the best model for Waterval River flow forecasting. Therefore, this model can be used to generate future river information for water resources development and management in Waterval River system. SARIMA model can also be used for forecasting other similar univariate time series with seasonality characteristics.

Keywords: heteroscedasticity, stationarity test, trend analysis, validation, white noise

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Authors: Konesh Navsaria, Itumeleng Ramodumo

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The study explored university students’ perceptions of cannabis use on academic life at a higher education institution (HEI) in Nelson Mandela Bay, South Africa. Cannabis is described as the most commonly-used drug by youth, especially those who are in tertiary institutions. The use of cannabis has both negative and positive effects; this is evident in different areas of human functioning. Cannabis usage has been debated upon in courts regarding its legalization and decriminalization, and on the 18th of September 2018, the South African High Court decriminalized cannabis for personal use. Cannabis use has increased in academic settings, and this has raised concerns about how it affects the mental health of students. A qualitative approach was used for the study with an explorative, descriptive design. Purposive sampling was used to select 15 participants for the study. Data were collected using focused-group interviews, following ethical clearance from the HEI. The collected data were analyzed and interpreted using thematic analysis, and cognitive behavioural theory was used as the theoretical framework. The research findings indicated both positive and negative influences of cannabis use on mental health. Most participants who expressed positive effects have used cannabis before, whereas most participants with negative perspectives of cannabis use on mental health are non-cannabis users. The findings revealed that participants perceived that the quantity of cannabis smoked determined whether there was a positive or negative effect on mental health; that is, large doses of cannabis were perceived as having negative effects. The research findings also revealed that the legalization of cannabis is very likely to increase its use and also highlighted precautionary measures users take to avoid the substance’s negative effects on mental health.

Keywords: cannabis use, mental health, university students, legalization

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Authors: Areej Isam Barham

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Developing students’ number sense is an essential element in the learning of mathematics. Number sense is one of the foundational ideas in mathematics where students need to understand numbers, representing them in different ways, and realize the relationships among numbers. Number sense also reflects students’ understanding of the meaning of operations, how they related to one another, how to compute fluently and make reasonable estimates. Developing students’ number sense in the mathematics classroom requires good preparation for mathematics teachers, those who will direct their students towards the real understanding of numbers and its implementation in the learning of mathematics. This study describes the development of elementary prospective mathematics teachers’ number sense through a mathematics teaching methods course at Qatar University. The study examined the effect of using the Lesh model in enhancing mathematics prospective teachers’ number sense. Thirty-nine elementary prospective mathematics teachers involved in the current study. The study followed an experimental research approach, and quantitative research methods were used to answer the research questions. Pre-post number sense test was constructed and implemented before and after teaching by using the Lesh model. Data were analyzed using Statistical Packages for Social Sciences (SPSS). Descriptive data analysis and t-test were used to examine the impact of using the Lesh model in enhancing prospective teachers’ number sense. Finding of the study indicated poor number sense and limited numeracy skills before implementing the use of the Lesh model, which highly demonstrate the importance of the study. The results of the study also revealed a positive impact on the use of the Lesh model in enhancing prospective teachers’ number sense with statistically significant differences. The discussion of the study addresses different features and issues related to the participants’ number sense. In light of the study, the research presents recommendations and suggestions for the future development of mathematics prospective teachers’ number sense.

Keywords: number sense, Lesh model, prospective mathematics teachers, development of number sense

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Authors: Rosa Tsegaye Aga, Xuan Jiang, Pavel Vazquez Faci, Siqing Liu, Simon Rayner, Endalkachew Alemu, Markos Abebe

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Tuberculosis (TB) is a major cause of disease globally. In most cases, TB is treatable and curable, but only with the proper treatment. There is a time when drug-resistant TB occurs when bacteria become resistant to the drugs that are used to treat TB. Current strategies to identify drug-resistant TB bacteria are laboratory-based, and it takes a longer time to identify the drug-resistant bacteria and treat the patient accordingly. But machine learning (ML) and data science approaches can offer new approaches to the problem. In this study, we propose to develop an ML-based model to predict the antibiotic resistance phenotypes of TB isolates in minutes and give the right treatment to the patient immediately. The study has been using the whole genome sequence (WGS) of TB isolates as training data that have been extracted from the NCBI repository and contain different countries’ samples to build the ML models. The reason that different countries’ samples have been included is to generalize the large group of TB isolates from different regions in the world. This supports the model to train different behaviors of the TB bacteria and makes the model robust. The model training has been considering three pieces of information that have been extracted from the WGS data to train the model. These are all variants that have been found within the candidate genes (F1), predetermined resistance-associated variants (F2), and only resistance-associated gene information for the particular drug. Two major datasets have been constructed using these three information. F1 and F2 information have been considered as two independent datasets, and the third information is used as a class to label the two datasets. Five machine learning algorithms have been considered to train the model. These are Support Vector Machine (SVM), Random forest (RF), Logistic regression (LR), Gradient Boosting, and Ada boost algorithms. The models have been trained on the datasets F1, F2, and F1F2 that is the F1 and the F2 dataset merged. Additionally, an ensemble approach has been used to train the model. The ensemble approach has been considered to run F1 and F2 datasets on gradient boosting algorithm and use the output as one dataset that is called F1F2 ensemble dataset and train a model using this dataset on the five algorithms. As the experiment shows, the ensemble approach model that has been trained on the Gradient Boosting algorithm outperformed the rest of the models. In conclusion, this study suggests the ensemble approach, that is, the RF + Gradient boosting model, to predict the antibiotic resistance phenotypes of TB isolates by outperforming the rest of the models.

Keywords: machine learning, MTB, WGS, drug resistant TB

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Authors: Tolga Arda Eraslan

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The quality of the indoor environment is significant to occupants’ health, comfort, and productivity, as Covid-19 spread throughout the world, people started spending most of their time indoors. Since buildings are getting bigger, mechanical ventilation systems are widely used where natural ventilation is insufficient. Four primary tasks of a ventilation system have been identified indoor air quality, comfort, contamination control, and energy performance. To fulfill such requirements, air diffusers, which are a part of the ventilation system, have begun to enter our lives in different airflow distribution systems. Detailed observations are needed to assure that such devices provide high levels of comfort effectiveness and energy efficiency. This study addresses these needs. The objective of this article is to observe air characterizations of different air diffusers at different angles and their effect on people by the thermal comfort model in CFD simulation and to validate the outputs with the help of data results based on a simulated office room. Office room created to provide validation; Equipped with many thermal sensors, including head height, tabletop, and foot level. In addition, CFD simulations were carried out by measuring the temperature and velocity of the air coming out of the supply diffuser. The results considering the flow interaction between diffusers and surroundings showed good visual illustration.

Keywords: computational fluid dynamics, fanger’s model, predicted mean vote, thermal comfort

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Authors: Suwarno, D. Jongudomkarn

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Family Health Assessment (FHA) is a key process to identify the family health needs, family health problems, and family health history. Assessing the family health is not only from the assessment tool but also from health care provider especially Nurse. Nurses’ have duties to assess the family as holistic view and they have to increase their capacities (knowledge, skills and experiences) in FHA. Thus, the continuing nursing education-training program on using the KKU FHA Tool was aimed to enhance the participant nurses’ capacities in (FHA) based on such tool. The aim of this study was to evaluate the KKU FHA Tool training program on PCU nurses’ capacity before and after training program in Primary Care Unit Bantul, Yogyakarta. The Quasi-Experiment with one group pre-, post-test design as a research design with convenient sampling technique and one group pre- post test formula for Nurses who work in Six PCU Bantul, Yogyakarta as much as fourteen respondents. The research processes were used training program with module, video and handbook KKU FHA Tool, KKU FHA tool form and capacities questionnaires. It was analyzed by descriptive data, Kolmogorov-Smirnov and Paired Sample t-test. The overall comparing analysis of paired sample t-test revealed that the mean values of pre-test were 3.35 with SD 0.417, post-test was 3.86 with SD 0.154 and post-test in later two weeks was 4.00 with SD 0.243. It was found that the p value of among the pre-test, the intermediate post-test and the post–test in later two weeks were 0.000. The p value of the intermediate post-test and post-test in later two weeks was 0.053. KKU FHA Tool training program in PCU Bantul Yogyakarta was enhanced the participant nurses’ capacities significantly. In conclusion, we are recommending KKU FHA Tool forms have to develop and implement with qualitative research as complementary data in PCU Bantul Yogyakarta by Focus Group Discussion.

Keywords: family health assessment, KKU FHA tool, training program, nurses capacities

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Authors: Denis Nono, Catherine Abbo, Thomas Wenzel

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Introduction: The study explored socio-cultural perspectives of childhood disorders and its implications for health seeking. Emphasis was on exploring local understanding and perceptions and how these ideas affect health seeking. Study aim: To explore the socio-cultural perspectives of neuro-developmental disorders and its implications on health seeking behaviour. Methods: The methods used in this study included key informant interviews conducted with health professionals. Parents of the children aged (6-15 years) with neuro-developmental disorders were recruited from the hospital to participate in focus group discussion, participant observation and individual in-depth interviews. Results: The study found out that stigma extended from children to parents and caregivers who were also shunned by community members. Participants described their children as “a gift from God” others described them as “a test from God”. The communities perceive the disorders as a spiritual infliction and always insisted that the children be taken for Acholi cultural and traditional rituals to cleanse children and they believed that mental illness has spiritual linkages. Conclusion: This study gives unique insights into the perceptions of neuro-developmental disorders and health seeking behavior in Gulu District and neighboring communities. The results showed that communities linked disorders to spiritual affliction, misunderstandings between families, bewitching, and other supernatural forces. Some of the participants highly recommended biomedical approaches to prevention, management and control of the disorders.

Keywords: ethnography, health seeking, neuro-developmental disorders, socio-cultural

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Authors: Divya Kanchibhotla

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Of all the major health threats to emerge, none has challenged the very foundation of public health so profoundly as the rise of non-communicable diseases (NCD). Encouraging a holistic health approach encompasses the community’s well-being. Competent public health grounded with holistic health approach can lay a better foundation in the modern world. Yoga has been increasingly explored as an adjunct therapy to major disorders. This study explores the efficacy of Yoga as a tool for public health. A survey was administered to 5500 adults, and 300 teens were selected from 25 states of India. The study explored the differences in health, happiness, and sustainable living between Yoga-practitioners and Non-yoga practitioners. The study also explored the practice and habits of yoga practitioners (frequency, place, reasons to practice) and Health, Happiness, and Sustainable Living. The subjects were grouped based on age, education, experience in yoga (years of practice), and occupational background. The study population comprised of 54% males and 46% females. Majority of the respondents (59%) were from 18 to 30 years age group. The study indicated that 96.4% of the total respondents have heard of Yoga. However, only 46.8% of the total study population practice yoga (YP) and the rest 53.2% were non-practitioners (NP). From a perspective of how Yoga and health, 72.7% yoga practitioners asserted a peaceful and happy life, 71.9% yoga practitioners felt satisfaction in life, and 70.2 % yoga practitioners had satisfactory health. 61.9% of yoga practitioners report being vegetarian, not eating junk food, and not drinking alcohol than 38.1% Non-Practitioners population. 47% of yoga practitioners found themselves to be more sensitive to the environment compared to only 40% of non-practitioners. India has been witnessing an unprecedented rise in the NCDs, accounting for 61% deaths. The importance of yoga as an adjunct therapy for various disorders and diseases is gaining momentum across the globe. There are various studies on yoga that have indicated benefits of yoga as a unique holistic approach towards lifestyle and a consistent, complementary solution that could be adopted for long-term viability for a well being. The comprehensive study is the first of its kind that takes a holistic look at the prevalence of Yoga for public health in India. Our study is unique and stands out as it is detailed in its outlook with extensive coverage of almost the whole country (surveying 25 out of 29 states) and contemplates on the benefits to an individual at the grass-root level – physical, mental and social outlook. The insights from the study will enable the health care systems and grassroots organizations to make the holistic practice of Yoga accessible to spread sustainable living for a healthy community.

Keywords: non-communicable disease (NCD), sustainable development goal (SDG 3), public health, healthy living

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Authors: Muhammad Fakhrul Arrazi

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Ibn Taymiyyah is a great figure in Islam. His works have become the reference for many Muslims in implementing the fiqh of Ibadah and Muamalat. This article reviews the concepts that Ibn Taymiyyah has initiated in Halal and Haram, long before the books on Halal and Haram are written by contemporary scholars. There are at least four concepts of Halal and Haram ever spawned by Ibn Taymiyyah. First, the belief of a jurist (Faqih) in a matter that is Haram does not necessarily make the matter Haram. Haram arises from the Quran, Sunnah, Ijma’ and Qiyas as the tarjih. Due to the different opinions among the ulama, we should revisit this concept. Second, if a Muslim involves in a transaction (Muamalat), believes it permissible and gets money from such transaction, then it is legal for other Muslims to transact with the property of this Muslim brother, even if he does not believe that the transactions made by his Muslims brother are permissible. Third, Haram is divided into two; first is Haram because of the nature of an object, such as carrion, blood, and pork. If it is mixed with water or food and alters their taste, color, and smell, the food and water become Haram. Second is Haram because of the way it is obtained such as a stolen item and a broken aqad. If it is mixed with the halal property, the property does not automatically become Haram. Fourth, a treasure whose owners cannot be traced back then it is used for the benefit of the ummah. This study used the secondary data from the classics books by Ibn Taymiyyah, particularly those entailing his views on Halal and Haram. The data were then analyzed by using thematic and comparative approach. It is found that most of the concepts proposed by Ibn Taymiyyah in Halal and Haram correspond the majority’s views in the schools. However, some of his concepts are also in contrary to other scholars. His concepts will benefit the ummah, should it be applied to the contemporary issues.

Keywords: fiqh Muamalat, halal, haram, Ibn Taymiyyah

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Authors: Akshay Dirisala

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Humans had developed a highly organized and efficient civilization to live in by improving the basic needs of humans like housing, transportation, and utilities. These developments have made a huge impact on major environmental factors. Air pollution is one prominent environmental factor that needs to be addressed to maintain a sustainable and healthier lifestyle. Textiles have always been at the forefront of helping humans shield from environmental conditions. With the growth in the field of electronic textiles, we now have the capability of monitoring the atmosphere in real time to understand and analyze the environment that a particular person is mostly spending their time at. Integrating textiles with the particulate matter sensors that measure air quality and pollutants that have a direct impact on human health will help to understand what type of air we are breathing. This research idea aims to develop a textile product and a process of collecting the pollutants through particulate matter sensors, which are equipped inside a smart textile product and store the data to develop a machine learning model to analyze the health conditions of the person wearing the garment and periodically notifying them not only will help to be cautious of airborne diseases but will help to regulate the diseases and could also help to take care of skin conditions.

Keywords: air pollution, e-textiles, particulate matter sensors, environment, machine learning models

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Authors: S. K. Ashiquer Rahman

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Recently, oil has become more influential in almost every economic sector as a key material. As can be seen from the news, when there are some changes in an oil price or OPEC announces a new strategy, its effect spreads to every part of the economy directly and indirectly. That’s a reason why people always observe the oil price and try to forecast the changes of it. The most important factor affecting the price is its supply which is determined by the number of wildcats drilled. Therefore, a study about the number of wellheads and other economic variables may give us some understanding of the mechanism indicated by the amount of oil supplies. In this paper, we will consider a relationship between the number of wellheads and three key factors: the price of the wellhead, domestic output, and GNP constant dollars. We also add trend variables in the models because the consumption of oil varies from time to time. Moreover, this paper will use an econometrics method to estimate parameters in the model, apply some tests to verify the result we acquire, and then conclude the model.

Keywords: price, domestic output, GNP, trend variable, wildcat activity

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Authors: Benjamin Cramer, Josephine Chau, Helen Little, Erica Randle

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Play Streets provide a safe and open space for children to play and adults to socialize by closing residential streets to through traffic. While research on Play Streets has typically focused on physical activity outcomes in children, there is limited research on the psychosocial health externalities for the wider community. Charles Sturt, a local government area in Adelaide, South Australia, has been hosting Play Streets for several years. The current study is a mixed-methods evaluation of the Charles Sturt Play Streets, concerned with the perceived psychological and social impacts that Play Streets impact on the community. A combination of semi-structured interviews of Play Street organizers and participants will be conducted and analyzed using inductive thematic analysis. Pre-existing survey data will also be analyzed quantitatively and qualitatively to triangulate the findings of the qualitative interviews. The implications of this research are far-reaching, from informing local councils of any additional health benefits of Play Streets, expanding the growing literature on Play Streets beyond childhood physical activity, informing the development of city infrastructure, and advancing the Sustainability Development Goals of Good Health and Wellbeing, Reduced Inequalities, and Sustainable Cities and Communities.

Keywords: play streets, mental health, social health, community health

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Authors: John Olav Bjornestad, Bjorn Tore Johansen

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The number of people suffering from mental illnesses is increasing, and such illness is currently one of the major causes of disability and poor health. The reason for this is most likely a lack of physical activity. The purpose of this study was to discover if physical activity was an effective mode of treatment for psychiatric patients at an out-patient treatment facility. The study included an exploration of whether or not patients having physical activity included as an integral part of their treatment (to a greater degree than do patients who are physically inactive) would achieve 1) an improvement in their physical condition 2) a reduction in symptomatic pressure and 3) an increase in their health-related quality of life. The intervention period lasted a total of 12 weeks. The training group completed a minimum of 2 training sessions per week with an intensity of 60-75% of maximum heart rate. The participants’ health-related quality of life (SF-36), symptomatic pressure (SCL-90-R) and physical condition (UKK-walking test) were measured before and after intervention. Twenty participants were pre-tested, and out of this initial group, nine patients completed the intervention program and participated thereafter in post-testing. The results showed that participants on average improved their physical condition, reduced their symptomatic pressure and increased their health-related quality of life over the course of the intervention period. The training group experienced significant changes in their symptomatic pressure (the anxiety dimension) and health-related quality of life (the mental health dimension) from the pre-testing stage to the post-testing one. Furthermore, there was a significant connection between symptomatic pressure and health-related quality of life. The patients who were admitted to the psychiatric out-patient clinic were in a physical condition that was significantly poorer than that of persons of the same age in the remainder of the population. Experiences from the study and the relatively large defection from it demonstrate that there is a great need for close follow-up of psychiatric patients’ physical activity levels when physical activity and lifestyle changes are included as part of their treatment program.

Keywords: health-related quality, mental health, physical activity, physical condition

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Authors: K. Makangali, G. Tokysheva, A. Shoman

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Goat meat and goat meat products have garnered increasing attention within the realm of nutrition and health due to their potential to provide a myriad of benefits. This scientific article presents a comprehensive review of the health advantages associated with goat meat consumption and the products derived from it. The paper explores the nutritional content of goat meat, highlighting its favorable composition in terms of protein, essential minerals, and amino acids. It delves into the intricate balance of macronutrients, with lower fat and cholesterol levels compared to other meats, making goat meat a desirable choice for individuals seeking healthier dietary options.

Keywords: goat meat, amino acid, nutrition, meat products, meat

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Authors: Lilian A. Okeke, I. Okeke, N. Waziri, S. Balogun, P. Nguku, O. Fawole

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Background: Access to ante-natal care services promotes safe motherhood and delivery with improved maternal and neonatal outcome. We conducted this study to identify factors influencing the utilization of antenatal care (ANC) and health delivery services. Methods: We conducted a cross sectional study. Households were numbered and a one in three sample was selected using a systematic sampling method. One hundred and ninety eight women who were either pregnant or had previous deliveries were interviewed using pretested structured questionnaires to obtain information on their socio-demographic characteristics, and reasons for non-utilization of ANC and health delivery services. We performed univariate and bivariate analysis using Epi info version 3.5.3. Results: The age of respondents ranged from (17-55 years) with a median age of 29 years. One hundred and ninety two (97%) utilized antenatal care services. Ninety three (47.9%) attended ANC at second trimester. More than half (58.6%) had ≥ 4 visits to ANC. One hundred and thirty one (66.2%) had their last delivery at home by a traditional birth attendant. Factors associated with ANC and health facility delivery services utilization were: age group 45-55 (OR 0.01; 95% CI: 0.00-0.16) and > 55 years (OR 0.03; 95% CI: 0.00-0.60), wife’s educational status (OR 3.17; 95% CI: 1.66-8.30), husband’s permission (OR 11.8; 95% CI 2.19-63.62), and distance ≥ 5km (OR 0.33; 95% CI: 0.16-0.60). Conclusion: ANC services were well utilized. Most women did not book early and had their last delivery at home. Predictors of ANC use and health facility delivery were age, wife’s educational status, husband's permission and long distance from health facility. A one-day health sensitization of the benefits of ANC utilization and the dangers of delivering at home was implemented.

Keywords: ante natal care, health facility, delivery services, rural area, Plateau state

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Authors: Sabyasachi Behera, Shiv Kumar, Pramod Gautam, Anisur Rahman, Pawan Pathak, Rahul Bhadouria

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Background: The increasing proportion of population especially urban poor and vulnerable groups or groups with specific needs, with health indicators worse than their rural counterparts in India face various issues related with availability and quality of health care. The reasons are myriad, starting from information and awareness of the community, especially, in a scenario wherein the needs and challenges of floating and migrant urban populations remain poorly understood. Weak linkages between health care facilities and slum dwellers and vulnerable populations hinder the improvement of health services for urban poor. Method: To address this issue, TCIHC program is helping health department of Indore city of Madhya Pradesh to establish a referral mechanism with a dual approach: at both community and facility level. The former is based on the premise of ‘building social capital’, i.e. norms and networks within a community facilitating collective action, helps improve the demand and supply of health services at appropriate levels of care (Minus 2: Accredited Social Health Activist and Community Health Groups; Minus 1: Urban Health Nutrition Days; Zero: Urban Primary Health Center; Plus 1: secondary facility with BEmONC services; Plus 2: secondary facilities with CEmONC services; Plus 3: tertiary level facility) for the urban poor. The latter focuses on encouraging the provision of all services at various levels of service delivery points and stakeholders to function in a coordinated manner to ensure better health service availability and coverage in underserved slum areas. Results: This initiative has enhanced the utilization of community based, primary and secondary level services through defined referral pathways that are clearly known to a community dweller. Conclusion: An ideal referral mechanism should begin with referral at the community level wherein services of a frontline health care provider are accessed by them at their door-step, causing no delay in both understanding and decision on the health issues faced by them.

Keywords: levels of care, linkages, referral mechanism, service delivery

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Authors: Tina Wu, Andrew Martin

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The expansion of the Internet of Things (IoT) brings a new level of threat. Attacks on IoT are already being used by criminals to form botnets, launch Distributed Denial of Service (DDoS) and distribute malware. This opens a whole new digital forensic arena to develop forensic methodologies in order to have the capability to investigate IoT related crimes. However, existing proposed IoT forensic models are still premature requiring further improvement and validation, many lack details on the acquisition and analysis phase. This paper proposes an enhanced theoretical IoT digital forensic model focused on identifying and acquiring the main sources of evidence in a methodical way. In addition, this paper presents a theoretical acquisition framework of the different stages required in order to be capable of acquiring evidence from IoT devices.

Keywords: acquisition, Internet of Things, model, zoning

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Authors: Julio Franco

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Water is used, directly and indirectly, in all activities of the construction productive chain, making it a subject of worldwide relevance for sustainable development. The ongoing expansion of urban areas leads to a high demand for natural resources, which in turn cause significant environmental impacts. The present work proposes the application of BIM tools to assist the measurement of the water footprint (WF) of civil construction supplies. Data was inserted into the model as element properties, allowing them to be analyzed by element or in the whole model. The WF calculation was automated using parameterization in Autodesk Revit software. Parameterization was associated to the materials of each element in the model so that any changes in these elements directly alter the results of WF calculations. As a case study, we applied into a building project model to test the parameterized calculus of WF. Results show that the proposed parameterization successfully automated WF calculations according to design changes. We envision this tool to assist the measurement and rationalization of the environmental impact in terms of WF of construction projects.

Keywords: building information modeling, BIM, sustainable development, water footprint

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Authors: M. Duk, L. Grabowski, P. Magryta

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Today's very important element relating to air transport is the environment impact issues. Nowadays there are no emissions standards for turbine and piston engines used in air transport. However, it should be noticed that the environmental effect in the form of exhaust gases from aircraft engines should be as small as possible. For this purpose, R&D centers often use special software to simulate and to estimate the negative effect of engine working process. For cooperation between the Lublin University of Technology and the Polish aviation company WSK "PZL-KALISZ" S.A., to achieve more effective operation of the ASz62IR engine, one of such tools have been used. The AVL Boost software allows to perform 1D simulations of combustion process of piston engines. ASz62IR is a nine-cylinder aircraft engine in a radial configuration. In order to analyze the impact of its working process on the environment, the mathematical model in the AVL Boost software have been made. This model contains, among others, model of the operation cycle of the cylinders. This model was based on a volume change in combustion chamber according to the reciprocating movement of a piston. The simplifications that all of the pistons move identically was assumed. The changes in cylinder volume during an operating cycle were specified. Those changes were important to determine the energy balance of a cylinder in an internal combustion engine which is fundamental for a model of the operating cycle. The calculations for cylinder thermodynamic state were based on the first law of thermodynamics. The change in the mass in the cylinder was calculated from the sum of inflowing and outflowing masses including: cylinder internal energy, heat from the fuel, heat losses, mass in cylinder, cylinder pressure and volume, blowdown enthalpy, evaporation heat etc. The model assumed that the amount of heat released in combustion process was calculated from the pace of combustion, using Vibe model. For gas exchange, it was also important to consider heat transfer in inlet and outlet channels because of much higher values there than for flow in a straight pipe. This results from high values of heat exchange coefficients and temperature coefficients near valves and valve seats. A Zapf modified model of heat exchange was used. To use the model with the flight scenarios, the impact of flight altitude on engine performance has been analyze. It was assumed that the pressure and temperature at the inlet and outlet correspond to the values resulting from the model for International Standard Atmosphere (ISA). Comparing this model of operation cycle with the others submodels of the ASz62IR engine, it could be noticed, that a full analysis of the performance of the engine, according to the ISA conditions, can be made. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under

Keywords: aviation propulsion, AVL Boost, engine model, operation cycle, aircraft engine

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

Abstract:

Model updating method has received increasing attention in damage detection structures based on measured modal parameters. Therefore, a probability-based damage detection (PBDD) procedure based on a model updating procedure is presented in this paper, in which a one-stage model-based damage identification technique based on the dynamic features of a structure is investigated. The presented framework uses a finite element updating method with a Monte Carlo simulation that considers the uncertainty caused by measurement noise. Enhanced ideal gas molecular movement (EIGMM) is used as the main algorithm for model updating. Ideal gas molecular movement (IGMM) is a multiagent algorithm based on the ideal gas molecular movement. Ideal gas molecules disperse rapidly in different directions and cover all the space inside. This is embedded in the high speed of molecules, collisions between them and with the surrounding barriers. In IGMM algorithm to accomplish the optimal solutions, the initial population of gas molecules is randomly generated and the governing equations related to the velocity of gas molecules and collisions between those are utilized. In this paper, an enhanced version of IGMM, which removes unchanged variables after specified iterations, is developed. The proposed method is implemented on two numerical examples in the field of structural damage detection. The results show that the proposed method can perform well and competitive in PBDD of structures.

Keywords: enhanced ideal gas molecular movement (EIGMM), ideal gas molecular movement (IGMM), model updating method, probability-based damage detection (PBDD), uncertainty quantification

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Authors: Engida Yisma, Berhanu Dessalegn, Ayalew Astatkie, Nebreed Fesseha

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Background: The use of the partograph is a well-known best practice for quality monitoring of labour and subsequent prevention of obstructed and prolonged labour. However, a number of cases of obstructed labour do happen in health facilities due to poor quality of intrapartum care. Methods: A cross-sectional quantitative study assessed knowledge and utilization of partograph among obstetric care givers in public health institutions of Addis Ababa, Ethiopia using a structured interviewer administered questionnaire. The collected data was analyzed using SPSS version 16.0. Logistic regression analysis was used to identify factors associated with knowledge and use of partograph among obstetric care givers. Results: Knowledge about the partograph was fair: 189 (96.6%) of all the respondents correctly mentioned at least one component of the partograph, 104 (53.3%) correctly explained the function of alert line and 161 (82.6%) correctly explained the function of action line. The study showed that 112 (57.3%) of the obstetric care givers at public health institutions reportedly utilized partograph to monitor mothers in labour. The utilization of the partograph was significantly higher among obstetric care givers working in health centres (67.9%) compared to those working in hospitals (34.4%) [Adjusted OR = 3.63(95%CI: 1.81, 7.28)]. Conclusions: A significant percentage of obstetric care givers had fair knowledge of the partograph and why it is necessary to use it in the management of labour and over half of obstetric care givers reported use of the partograph to monitor mothers in labour. Pre-service and on-job training of obstetric care givers on the use of the partograph should be given emphasis. Mandatory health facility policy is also recommended to ensure safety of women in labour in public health facilities in Addis Ababa, Ethiopia.

Keywords: partograph, knowledge, utilization, obstetric care givers, public health institutions

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Authors: Lavina N. Bhaskar, Ashima Tiwari

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In the endeavour of connecting culture to stories, textile to narratives and people to material, authors analyse the impact of narratives in two popular Indian textiles namely - Mata Ni Pachedi and Pabuji Ki Phad. These textiles narrate people’s tale or Folk tale. Each textile has a style or format in which the story is told (and it is visual). Mata Ni Pachedi, when translated into the English language literally means behind the mother goddess. Mata Ni Pachedi is an Indian textile from the province of Gujarat which constitutes an entire temple of the goddess, with the idol herself in it. On the other hand, Pabuji ki Phad is scroll painting of folk deities of Rajasthan, narrated by Bhopas (the Priest singers of Rajasthan). These textiles narrate stories of ordinary people with extraordinary courage, of social reform, and people’s belief in the divine. Authors take to task their years of craft-cluster study conducted in the past and use existing literature to map their journey in the preliminary phase of research. And then carried out an ethnographic study by visiting the origins of these textiles in Rajasthan and Gujrat (in India), met artisans and their families who are still practicing these dying art form, in order to understand the format and impact of textile story-telling. This research paper talks about the narrative in Indian textiles; the stories in them, artisans and their life as metaphorical representations of the People in Mata Ni Pachedi and Pabuji Ki Phad.

Keywords: cultural derivatives, folk-tale, Indo-Narratives, Indology

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Authors: Kien-Trinh Thi Bui, Cuong Manh Nguyen

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In order to simulate and reproduce the operational characteristics of a dam visually, it is necessary to capture the displacement at different measurement points and analyze the observed movement data promptly to forecast the dam safety. The accuracy of forecasts is further improved by applying machine learning methods to data analysis progress. In this study, the horizontal displacement monitoring data of the Ialy hydroelectric dam was applied to machine learning algorithms: Gaussian processes, multi-layer perceptron neural networks, and the M5-rules algorithm for modelling and forecasting of horizontal displacement of the Ialy hydropower dam (Vietnam), respectively, for analysing. The database which used in this research was built by collecting time series of data from 2006 to 2021 and divided into two parts: training dataset and validating dataset. The final results show all three algorithms have high performance for both training and model validation, but the MLPs is the best model. The usability of them are further investigated by comparison with a benchmark models created by multi-linear regression. The result show the performance which obtained from all the GP model, the MLPs model and the M5-Rules model are much better, therefore these three models should be used to analyze and predict the horizontal displacement of the dam.

Keywords: Gaussian processes, horizontal displacement, hydropower dam, Ialy dam, M5-Rules, multi-layer perception neural networks

Procedia PDF Downloads 210