Search results for: pollution contamination factors

Authors: Rachid Dris, Robin Treilles, Max Beaurepaire, Minh Trang Nguyen, Sam Azimi, Vincent Rocher, Johnny Gasperi, Bruno Tassin

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Microplastic sources and fluxes in urban catchments are only poorly studied. Most often, the approaches taken focus on a single source and only carry out a description of the contamination levels and type (shape, size, polymers). In order to gain an improved knowledge of microplastic inputs at urban scales, estimating and comparing various fluxes is necessary. The Laboratoire Eau, Environnement et Systèmes Urbains (LEESU), the Laboratoire Eau Environnement (LEE) and the SIAAP (Service public de l’assainissement francilien) initiated several projects to investigate different urban sources and flows of microplastics. A systemic approach is undertaken at the scale of Paris Megacity, and several compartments are considered, including atmospheric fallout, wastewater treatments plants, runoff and combined sewer overflows. These investigations are carried out within the Limnoplast and OPUR projects. Atmospheric fallout was sampled during consecutive periods ranging from 2 to 3 weeks with a stainless-steel funnel. Both wet and dry periods were considered. Different treatment steps were sampled in 2 wastewater treatment plants (Seine-Amont for activated sludge and Seine-Centre for biofiltration) of the SIAAP, including sludge samples. Microplastics were also investigated in combined sewer overflows as well as in stormwater at the outlet suburban catchment (Sucy-en-Brie, France) during four rain events. Samples are treated using hydroperoxide digestion (H₂O₂ 30 %) in order to reduce organic material. Microplastics are then extracted from the samples with a density separation step using NaI (d=1.6 g.cm⁻³). Samples are filtered on metallic filters with a porosity of 14 µm between steps to separate them from the solutions (H₂O₂ and NaI). The last filtration was carried out on alumina filters. Infrared mapping analysis (using a micro-FTIR with an MCT detector) is performed on each alumina filter. The resulting maps are analyzed using a microplastic analysis software simple, developed by Aalborg University, Denmark and Alfred Wegener Institute, Germany. Blanks were systematically carried out to consider sample contamination. This presentation aims at synthesizing the data found in the various projects. In order to carry out a systemic approach and compare the various inputs, all the data were converted into annual microplastic fluxes (number of microplastics per year), and extrapolated to the Parisian agglomeration. PP, PE and alkyd are the most prevalent polymers found in storm water samples. Rain intensity and microplastic concentrations did not show any clear correlation. Considering the runoff volumes and the impervious surface area of the studied catchment, a flux of 4*107–9*107 MPs.yr⁻¹.ha⁻¹ was estimated. Samples of wastewater treatment plants and atmospheric fallout are currently being analyzed in order to finalize this assessment. The representativeness of such samplings and uncertainties related to the extrapolations will be discussed and gaps in knowledge will be identified. The data provided by such an approach will help to prioritize future research as well as policy efforts.

Keywords: microplastics, atmosphere, wastewater, urban runoff, Paris megacity, urban waters

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Authors: T. Pradhan, P. Rijal, M. C. Regmi

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Background: Eclampsia is a multisystem disorder that involves vital organs and failure of these may lead to deterioration of maternal condition and hypoxia and acidosis of fetus resulting in high maternal and perinatal mortality and morbidity. Thus, evaluation of the contributing factors for this condition and its complications leading to maternal deaths should be the priority. Formulating the plan and protocol to decrease these losses should be our goal. Aims and Objectives: To evaluate the risk factors associated with adverse maternal and fetal outcome in patients with eclampsia and to correlate the risk factors associated with maternal and fetal morbidity and mortality. Methods: All patients with eclampsia admitted in Department of Obstetrics and Gynecology, B. P. Koirala Institute of Health Sciences were enrolled after informed consent from February 2013 to February 2014. Questions as per per-forma were asked to patients, and attendants like Antenatal clinic visits, parity, number of episodes of seizures, duration from onset of seizure to magnesium sulfate and the patients were followed as per the hospital protocol, the mode of delivery, outcome of baby, post partum maternal condition like maternal Intensive Care Unit admission, neurological impairment and mortality were noted before discharge. Statistical analysis was done using Statistical Package for the Social Sciences (SPSS 11). Mean and percentage were calculated for demographic variables. Pearson’s correlation test and chi-square test were applied to find the relation between the risk factors and the outcomes. P value less than 0.05 was considered significant. Results: There were 10,000 antenatal deliveries during the study period. Fifty-two patients with eclampsia were admitted. All of the patients were unbooked for our institute. Thirty-nine patients were antepartum eclampsia. Thirty-one patients required mechanical ventilator support. Twenty-four patients were delivered by emergency c-section and 21 babies were Low Birth Weight and there were 9 stillbirths. There was one maternal mortality and 45 patients were discharged with improvement but 3 patients had neurological impairment. Mortality was significantly related with number of seizure episodes and time interval between seizure onset and administration of magnesium sulphate. Conclusion: Early detection and management of hypertensive complicating pregnancy during antenatal clinic check up. Early hospitalization and management with magnesium sulphate for eclampsia can help to minimize the maternal and fetal adverse outcomes.

Keywords: eclampsia, maternal mortality, perinatal mortality, risk factors

Procedia PDF Downloads 169

Authors: Zain Ul Abadeen, Muhammad Zargham Khan, Muhammad Kashif Saleemi, Ahrar Khan, Ijaz Javed Hassan, Aisha Khatoon, Qasim Altaf

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Aflatoxins are secondary metabolites produced by toxigenic fungi, and there are four types of aflatoxins include AFB1, AFB2, AFG1 and AFG2. Aflatoxin B1 (AFB1) is considered as most toxic form. It is mainly responsible for the contamination of poultry feed and produces a condition called aflatoxicosis leads to immunosuppression in poultry birds. Saccharomyces cerevisiae is a single cell microorganism and acts as a source of growth factors, minerals and amino acids which improve the immunity and digestibility in poultry birds as probiotics. Saccharomyces cerevisiae is well recognized to cause the biological degradation of mycotoxins (toxin binder) because its cell wall contains β-glucans and mannans which specifically bind with aflatoxins and reduce their absorption or transfer them to some non-toxic compounds. The present study was designed to investigate the immunosuppressive effects of aflatoxins in broiler chicks and the reduction of severity of these effects by the use of Baker’s Yeast (Saccharomyces cerevisiae). One-day-old broiler chicks were procured from local hatchery and were divided into various groups (A-I). These groups were treated with different levels of AFB1 @ 400 µg/kg and 600 µg/kg along with different levels of Baker’s Yeast (Saccharomyces cerevisiae) 0.1% and 0.5 % in the feed. The total duration of the experiment was six weeks and different immunological parameters including the cellular immune response by injecting PHA-P (Phytohemagglutinin-P) in the skin of the birds, phagocytic function of mononuclear cells by Carbon clearance assay from blood samples and humoral immune response against intravenously injected sheep RBCs from the serum samples were determined. The birds from each group were slaughtered at the end of the experiment to determine the presence of gross lesions in the immune organs and these tissues were fixed in 10% neutral buffered formalin for histological investigations. The results showed that AFB1 intoxicated groups had reduced body weight gain, feed intake, organs weight and immunological responses compared to the control and Baker’s Yeast (Saccharomyces cerevisiae) treated groups. Different gross and histological degenerative changes were recorded in the immune organs of AFB1 intoxicated groups compared to control and Baker’s Yeast (Saccharomyces cerevisiae) treated groups. The present study concluded that Baker’s Yeast (Saccharomyces cerevisiae) addition in the feed helps to ameliorate the immunotoxigenic effects produced by AFB1 in broiler chicks.

Keywords: aflatoxins, body weight gain, feed intake, immunological response, toxigenic effect

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Authors: Pradip Kumar Das

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As the entire world continues its rapid move towards industrialization, it has seriously threatened mankind’s ability to maintain an ecological balance. Geographical and natural forces have a significant influence on the location of industries. Industrialization is the foundation stone of the development of any country, while the unplanned industrialization and discharge of waste by industries is the cause of environmental pollution. There is growing degree of awareness and concern globally among nations about environmental degradation or pollution. Environmental resources endowed by the gift of nature and not manmade are invaluable natural resources of a country like India. Any developmental activity is directly related to natural and environmental resources. Economic development without environmental considerations brings about environmental crises and damages the quality of life of present, as well as future generation. As corporate sectors in the global market, especially in India, are becoming anxious about environmental degradation, naturally more and more emphasis will be ascribed to how environment-friendly the outcomes are. Maintaining accounts of such environmental and natural resources in the country has become more urgent. Moreover, international awareness and acceptance of the importance of environmental issues has motivated the development of a branch of accounting called “Environmental Accounting”. Environmental accounting attempts to detect and focus the resources consumed and the costs rendered by an industrial unit to the environment. For the sustainable development of mankind, a healthy environment is indispensable. Gradually, therefore, in many countries including India, environment matters are being given top most priority. Accounting and disclosure of environmental matters have been increasingly manifesting as an important dimension of corporate accounting and reporting practices. But, as conventional accounting deals with mainly non-living things, the formulation of valuation, and measurement and accounting techniques for incorporating environment-related matters in the corporate financial statement sometimes creates problems for the accountant. In the light of this situation, the conceptual analysis of the study is concerned with the rationale of environmental accounting on the economy and society as a whole, and focuses the failures of the traditional accounting system. A modest attempt has been made to throw light on the environmental awareness in developing nations like India and discuss the problems associated with the implementation of environmental accounting. The conceptual study also reflects that despite different anomalies, environmental accounting is becoming an increasing important aspect of the accounting agenda within the corporate sector in India. Lastly, a conclusion, along with recommendations, has been given to overcome the situation.

Keywords: environmental accounting, environmental degradation, environmental management, environmental resources

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Authors: Weldegerima Gebremedhin Hagos

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Background: The Coronavirus disease of 2019 (COVID-19) is a catastrophic emerging global health threat caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). COVID-19 has a wide range of complications and sequels. It is devastating in developing countries, causing serious health and socioeconomic crises as a result of the increasingly overburdened healthcare system. Ethiopia reported the first case of SARS-CoV-2 on 13th March 2020, with community transmission ensuing by mid-May. The aim of this study was conducted to determine the prevalence of SARS-CoV-2 infection in Tigray, Ethiopia. Methods: Facility-based correctional study designs were used on a total of 380 study participants from March 2023 up to May 2023 in two general hospitals and one comprehensive specialized hospital in Tigray, Ethiopia. A pre-structured questionnaire was used to assess information regarding the socio-demographic, clinical data and other risk factors. A nasal swap was taken by trained health professionals, and the laboratory analysis was done by RT-PCR (quant studio 7-flex, applied biosystems) in Tigrai Health Research Institute and Mekelle University Medical Microbiology Research Laboratory. Result: The mean age of the study participants was 31 (SD+/-3.5) years, with 65% being male and 35% female. The overall seropositivity of sars-cov-2 among the study participants was 5.5%. The prevalence was higher in males (6.2%) than females which were (4.7%). Sars-cov-2 infection was significantly associated with a history of lack of vaccination (p-value 0.002). There was no significant association between seropositivity and demographic factors (P > 0.05). Conclusion: The seroprevalence of SARS-CoV-2 among the study participants is high. Those study participants with a previous history of vaccination have a low probability of developing COVID-19 infection. A low SARS-CoV-2 infection rate was recorded in those who frequently use masks.

Keywords: prevalence, SARS-CoV-2, infection, risk factors

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Authors: Loreta Kaklauskiene, Arturas Kaklauskas

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The Integrated Human Resources and Work Environment Management (HOWE) System optimises employee productivity, improves the work environment, and, at the same time, meets the employer’s strategic goals. The HOWE system has been designed to ensure an organisation can successfully compete in the global market, thanks to the high performance of its employees. The HOWE system focuses on raising workforce productivity and improving work conditions to boost employee performance and motivation. The methods used in our research are linear correlation, INVAR multiple criteria analysis, digital twin, and affective computing. The HOWE system is based on two patents issued in Lithuania (LT 6866, LT 6841) and one European Patent application (No: EP 4 020 134 A1). Our research analyses ways to make human resource management more efficient and boost labour productivity by improving and adapting a personalised work environment. The efficiency of human capital and labour productivity can be increased by applying personalised workplace improvement systems that can optimise lighting colours and intensity, scents, data, information, knowledge, activities, media, games, videos, music, air pollution, humidity, temperature, vibrations, and other workplace aspects. HOWE generates and maintains a personalised workspace for an employee, taking into account the person’s affective, physiological and emotional (APSE) states. The purpose of this project was to create a HOWE for the customisation of quality control in smart workspaces taking into account the user’s APSE states in an integrated manner as a single unit. This customised management of quality control covers the levels of lighting and colour intensities, scents, media, information, activities, learning materials, games, music, videos, temperature, energy efficiency, the carbon footprint of a workspace, humidity, air pollution, vibrations and other aspects of smart spaces. The system is based on Digital Twins technology, seen as a logical extension of BIM.

Keywords: human resource management, health economics, work environment, organizational behaviour and employee productivity, prosperity in work, smart system

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Authors: Junaid Hamid Bhat

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Background: Musculoskeletal disorders are one of the main causes of occupational illness. Mechanisms and the factors like repetitive work, physical effort and posture, endangering the risk of musculoskeletal disorders would now appear to have been properly identified. Teacher’s exposure to work-related musculoskeletal disorders appears to be insufficiently described in the literature. Little research has investigated the prevalence and risk factors of musculoskeletal disorders in teaching profession. Very few studies are available in this regard and there are no studies evident in India. Purpose: To determine the prevalence of musculoskeletal disorders and to identify and measure the association of such risk factors responsible for developing musculoskeletal disorders among school teachers. Methodology: An observational cross sectional study was carried out. 500 school teachers from primary, middle, high and secondary schools were selected, based on eligibility criteria. A signed consent was obtained and a self-administered, validated questionnaire was used. Descriptive statistics was used to compute the statistical mean and standard deviation, frequency and percentage to estimate the prevalence of musculoskeletal disorders among school teachers. The data analysis was done by using SPSS version 16.0. Results: Results indicated higher pain prevalence (99.6%) among school teachers during the past 12 months. Neck pain (66.1%), low back pain (61.8%) and knee pain (32.0%) were the most prevalent musculoskeletal complaints of the subjects. Prevalence of shoulder pain was also found to be high among school teachers (25.9%). 52.0% subjects reported pain as disabling in nature, causing sleep disturbance (44.8%) and pain was found to be associated with work (87.5%). A significant association was found between musculoskeletal disorders and sick leaves/absenteeism. Conclusion: Work-related musculoskeletal disorders particularly neck pain, low back pain, and knee pain, is highly prevalent and risk factors are responsible for the development of same in school teachers. There is little awareness of musculoskeletal disorders among school teachers, due to work load and prolonged/static postures. Further research should concentrate on specific risk factors like repetitive movements, psychological stress, and ergonomic factors and should be carried out all over the country and the school teachers should be studied carefully over a period of time. Also, an ergonomic investigation is needed to decrease the work-related musculoskeletal disorder problems. Implication: Recall bias and self-reporting can be considered as limitations. Also, cause and effect inferences cannot be ascertained. Based on these results, it is important to disseminate general recommendations for prevention of work-related musculoskeletal disorders with regards to the suitability of furniture, equipment and work tools, environmental conditions, work organization and rest time to school teachers. School teachers in the early stage of their careers should try to adapt the ergonomically favorable position whilst performing their work for a safe and healthy life later. Employers should be educated on practical aspects of prevention to reduce musculoskeletal disorders, since changes in workplace and work organization and physical/recreational activities are required.

Keywords: work related musculoskeletal disorders, school teachers, risk factors funding, medical and health sciences

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Authors: Chinnawat Satsananan

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The amount of heavy metals in our environment has been of great concern because of their toxicity when their concentration is more than the permissible level. These metals enter the environment by different ways such as industrial activities, soil pollution. We have used flame atomic absorption spectrometry technique for determination of the concentration of Co, Cd and Pb in different tissues of five samples of seafoods (mackerel, squid, mussels, scallops and shrimp). The concentrations of Co, Cd and Pb in all examined seafoods were less than the reported literature values (WHO). The results mentioned that the seafoods obtained from Thewet Market were safety to consumption and make the quality of life of people in the community look better.

Keywords: heavy metals, seafood, atomic absorption spectrometry, Bangkok

Procedia PDF Downloads 334

Authors: Richard Ren

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Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 127

Authors: Muhammad Kamran Hanif Khan, Fahad Mushtaq

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Background: In both developed and underdeveloped countries, coronary artery disease (CAD) is a serious cause of death and disability. Cardiovascular disease (CVD) is becoming more prevalent in emerging countries like Pakistan due to the spread and acceptance of Western lifestyles. Material and Methods: An observational cross-sectional investigation was conducted, and data collection relied on a random cluster sampling method. The sample size for this cross-sectional study was calculated using the following factors: estimated true proportion of 17.5%, desired precision of 2%, and confidence interval of 95%. The data for this study was collected from a sample of 1387 adults. Results: The average age of those living in rural areas is 55.24 years, compared to 52.60 years for those living in urban areas. The mean fasting blood glucose of the urban participants is 105.28 mg/dL, which is higher than the mean fasting blood glucose of the rural participants, which is 102.06 mg/dL. The mean total cholesterol of the urban participants is 192.20 mg/dL, which is slightly higher than the mean total cholesterol of the rural participants, which is 191.97 mg/dL. CAD prevalence is greater in urban areas than in rural areas. ECG abnormalities prevalence is 16.1% in females compared to 12.5% in men. Conclusion: The prevalence of CAD is more common in urban areas than in rural ones for all of the measures of CAD used in the study.

Keywords: CVD prevalence, CVD risk factors, rural area, urban area

Procedia PDF Downloads 79

Authors: Snezana Mugosa, Zoran Todorovic, Zoran Bukumiric, Ivan Radosavljevic, Natasa Djordjevic

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Introduction: Various studies have shown that the frequency of clopidogrel resistance ranges from 4-40%. The aim of this study was to provide in depth analysis of genetic and non-genetic factors that influence clopidogrel resistance in cardiology patients. Methods: We have conducted a prospective study in 200 hospitalized patients hospitalized at Cardiology Centre of the Clinical Centre of Montenegro. CYP2C19 genetic testing was conducted, and the PREDICT score was calculated in 102 out of 200 patients treated with clopidogrel in order to determine the influence of genetic and non-genetic factors on outcomes of interest. Adverse cardiovascular events and adverse reactions to clopidogrel were assessed during 12 months follow up period. Results: PREDICT score and CYP2C19 enzymatic activity were found to be statistically significant predictors of expressing lack of therapeutic efficacy of clopidogrel by multivariate logistic regression, without multicollinearity or interaction between the predictors (p = 0.002 and 0.009, respectively). Conclusions: Pharmacogenetics analyses that were done in the Montenegrin population of patients for the first time suggest that these analyses can predict patient response to the certain therapy. Stepwise approach could be used in assessing the clopidogrel resistance in cardiology patients, combining the PREDICT score, platelet aggregation test, and genetic testing for CYP2C19 polymorphism.

Keywords: clopidogrel, pharmacogenetics, pharmacotherapy, PREDICT score

Procedia PDF Downloads 351

Authors: Syeda Fatima Manzelat

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This chapter investigates the biodeterioration of parks in the UK caused by lichens, focusing on Campbell Park and Great Linford Manor Park in Milton Keynes. The study first isolates and identifies potent biodeteriogens responsible for potential biodeterioration in these parks, enumerating and recording different classes and genera of lichens known for their biodeteriorative properties. It then examines the implications of lichens on biodeterioration at historic sites within these parks, considering impacts on historic structures, the environment, and associated health risks. Conservation strategies and preventive measures are discussed before concluding.Lichens, characterized by their symbiotic association between a fungus and an alga, thrive on various surfaces including building materials, soil, rock, wood, and trees. The fungal component provides structure and protection, while the algal partner performs photosynthesis. Lichens collected from the park sites, such as Xanthoria, Cladonia, and Arthonia, were observed affecting the historic walls, objects, and trees. Their biodeteriorative impacts were visible to the naked eye, contributing to aesthetic and structural damage. The study highlights the role of lichens as bioindicators of pollution, sensitive to changes in air quality. The presence and diversity of lichens provide insights into the air quality and pollution levels in the parks. However, lichens also pose health risks, with certain species causing respiratory issues, allergies, skin irritation, and other toxic effects in humans and animals. Conservation strategies discussed include regular monitoring, biological and chemical control methods, physical removal, and preventive cleaning. The study emphasizes the importance of a multifaceted, multidisciplinary approach to managing lichen-induced biodeterioration. Future management practices could involve advanced techniques such as eco-friendly biocides and self-cleaning materials to effectively control lichen growth and preserve historic structures. In conclusion, this chapter underscores the dual role of lichens as agents of biodeterioration and indicators of environmental quality. Comprehensive conservation management approaches, encompassing monitoring, targeted interventions, and advanced conservation methods, are essential for preserving the historic and natural integrity of parks like Campbell Park and Great Linford Manor Park.

Keywords: biodeterioration, historic parks, algae, UK

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Authors: Maya Kagan, Michal Itzick, Patricia Tal-Katz

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Social workers hold a variety of roles and practices, and one of these involves the care, treatment, and rehabilitation of disabled people. The current study assesses the association between demographic factors, attitudes towards social workers, the stigma attached to seeking social worker help, perceived social support, and psychological distress - and the self-reported likelihood of seeking social worker help, among people with physical disabilities (PWPD) in Israel. Data collection utilized structured questionnaires, administered to a sample of 435 PWPD. Statistical analyses were done using SPSS software. The findings suggest that women, older respondents, people with more positive attitudes towards social workers, with higher levels of psychological distress and of social support, and with a lower level of stigma, reported a greater likelihood of seeking social worker help. The study's conclusion is that there are certain avoidance factors among PWPD that might discourage them from seeking professional social worker help. Therefore, it is important that social workers identify these factors and develop interventions aimed at encouraging PWPD to seek professional social worker help in case of need, and also develop practices adjusted to PWPD's unique needs.

Keywords: attitudes towards social workers, people with physical disabilities, perceived social support, psychological distress, seeking help, stigma

Procedia PDF Downloads 337

Authors: Se-Hwa Park, En-Kyung Han, Jae-Young Lim, Hye-Jung Ahn

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Purpose: The objective of this study is to provide basic data for understanding the substance of inpatient life with CRPS (Complex Regional Pain Syndrome) and developing efficient and effective nursing intervention. Methods: From September 2018 to November, we have interviewed 10 CRPS patients about inpatient experiences. To understand the implication of inpatient life experiences with CRPS and intrinsic structure, we have used the question: 'How about the inpatient experiences with CRPS'. For data analysis, the method suggested by Colaizzi was applied as a phenomenological method. Results: According to the analysis, the study participants' inpatient life process was structured in six categories: (a) breakthrough pain experience (b) the limitation of pain treatment, (c) worsen factors of pain during inpatient period, (d) treat method for pain, (e) positive experience for inpatient period, (f) requirements for medical team, family and people in hospital room. Conclusion: Inpatient with CRPS have experienced the breakthrough pain. They had expected immediate treatment for breakthrough pain, but they experienced severe pain because immediate treatment was not implemented. Pain-worsening factors which patients with CRPS are as follows: personal factors from negative emotions such as insomnia, stress, sensitive character, pain part touch or vibration stimulus on the bed, physical factors from high threshold or rapid speed during fast transfer, conflict with other people, climate factors such as humidity or low temperature, noise, smell, lack of space because of many visitors. Patients actively manage the pain committing into another tasks or diversion. And also, patients passively manage the pain, just suppress, give-up. They think positively about rehabilitation treatment. And they require the understanding and sympathy for other people, and emotional support, immediate intervention for medical team. Based on the results of this study, we suppose the guideline of systematic breakthrough pain management for the relaxation of sudden pain, using notice of informing caution for touch or vibration. And we need to develop non-medicine pain management nursing intervention.

Keywords: breakthrough pain, CRPS, complex regional pain syndrome, inpatient life experiences, phenomenological method

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Authors: R. A. Lahmer, A. P. Williams, S. Townsend, S. Baker, D. L. Jones

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Chitosan-arginine (Ch-arg) has been proposed as an anti-microbial agent to reduce the proliferation of spoilage and pathogenic bacteria within meat products destined for human consumption. In the current experiment its use as an antimicrobial packaging material was examined. Two different concentrations of chitosan-arginine (0.05 and 0.15 % w/w) were blended into a cellulose film (Ch-arg film). When placed in contact with chicken and beef juice inoculated with a lux-marked strain of E. coli O157, the film incorporating the highest Ch-arg concentration resulted in a small reduction of E. coli O157 in chicken juice; however, there was no effect of the Ch-arg film on E. coli O157 in beef juice. The lack of observed effect in the beef juice experiment we ascribe to insufficient surface-to-surface contact between the film and the bacteria in the beef juice and the greater presence of other Ch-arg reactive components in the juice (e.g. fats, blood cells). Results suggest that, in combination with other anti microbials, Ch-arg packaging may offers some potential for limiting the growth of pathogenic bacteria in foodstuffs; however, further research is needed to enhance their anti-microbial performance.

Keywords: cross-contamination, foodborne pathogen, polymer film, shelf life

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Authors: Haiping Ding, Rongchu Zhu, Zhenxia Song

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Local irregular topography has a great impact on earthquake ground motion. For scarp topography, using numerical simulation method, the influence extent and scope of the scarp terrain on scarp's upside and downside ground motion are discussed in case of different vertical incident SV waves. The results show that: (1) The amplification factor of scarp's upside region is greater than that of the free surface, while the amplification factor of scarp's downside part is less than that of the free surface; (2) When the slope angle increases, for x component, amplification factors of the scarp upside also increase, while the downside part decrease with it. For z component, both of the upside and downside amplification factors will increase; (3) When the slope angle changes, the influence scope of scarp's downside part is almost unchanged, but for the upside part, it slightly becomes greater with the increase of slope angle; (4) Due to the existence of the scarp, the z component ground motion appears at the surface. Its amplification factor increases for larger slope angle, and the peaks of the surface responses are related with incident waves. However, the input wave has little effects on the x component amplification factors.

Keywords: scarp topography, ground motion, amplification factor, vertical incident wave

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Authors: R. Noorani, K. Peerless, J. Mandrell, A. Lopez, R. Dalberto, M. Alzebaq

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Rapid prototyping (RP) is an additive manufacturing technology used in industry that works by systematically depositing layers of working material to construct larger, computer-modeled parts. A key challenge associated with this technology is that RP parts often feature undesirable levels of surface roughness for certain applications. To combat this phenomenon, an experimental technique called Design of Experiments (DOE) can be employed during the growth procedure to statistically analyze which RP growth parameters are most influential to part surface roughness. Utilizing DOE to identify such factors is important because it is a technique that can be used to optimize a manufacturing process, which saves time, money, and increases product quality. In this study, a four-factor/two level DOE experiment was performed to investigate the effect of temperature, layer thickness, infill percentage, and infill speed on the surface roughness of RP prototypes. Samples were grown using the sixteen different possible growth combinations associated with a four-factor/two level study, and then the surface roughness data was gathered for each set of factors. After applying DOE statistical analysis to these data, it was determined that layer thickness played the most significant role in the prototype surface roughness.

Keywords: rapid prototyping, surface roughness, design of experiments, statistical analysis, factors and levels

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Authors: Joseph Berlin P. Juanzon, Manuel M. Muhi

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Motivating SME-based construction firms to adopt different management systems is not a simple task, especially if they are not aware of the benefits that they will gain from the new process-based management system. The implementation of ISO 9001:2008, Quality Management System in the construction industry is an ongoing trend, more so in the Small and Medium Enterprise. However, the level of awareness and readiness of the construction industry in the Philippines is still low as compared to the neighboring countries in Asia and in the western countries where ISO 9001:2008 originated. The purpose of this research is to determine the significant factors that will motivate SME-based construction firms in the Philippines to implement ISO 9001:2008. A field study was conducted on SME based construction firms in the Philippines, wherein a total of 139 respondents out of the 613 SME-based construction firms in CALABARZON areas were surveyed. Results reveal that the three main factors that will motivate SME-based construction firms to implement ISO 9001:2008 are: - if required by their clients, - to qualify for bidding, and - to increase customer satisfaction. Therefore, based on the results and findings, a certification of ISO 9001:2008 from an accredited auditor shall be required by clients as a constituent in accrediting SME-based construction firms and to qualify for bidding.

Keywords: construction, ISO 9001:2008, quality management systems (QMS), small medium enterprise (SME)

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Authors: Carolina Mayen Huerta, Clara Ivanescu, Paloma Marcos

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Due to their unique geographic challenges and the imperative to combat climate change, Small Island Developing States (SIDS) are experiencing rapid growth in the renewable energy (RE) sector. However, women's representation in formal employment within this burgeoning field remains significantly lower than their male counterparts. Conventional methodologies often overlook critical geographic data that influence women's job prospects. To address this gap, this paper introduces a Multicriteria Evaluation (MCE) framework designed to identify spatially enabling environments and restrictions affecting women's access to formal employment and business opportunities in the SIDS' RE sector. The proposed MCE framework comprises 24 key factors categorized into four dimensions: Individual, Contextual, Accessibility, and Place Characterization. "Individual factors" encompass personal attributes influencing women's career development, including caregiving responsibilities, exposure to domestic violence, and disparities in education. "Contextual factors" pertain to the legal and policy environment, influencing workplace gender discrimination, financial autonomy, and overall gender empowerment. "Accessibility factors" evaluate women's day-to-day mobility, considering travel patterns, access to public transport, educational facilities, RE job opportunities, healthcare facilities, and financial services. Finally, "Place Characterization factors" enclose attributes of geographical locations or environments. This dimension includes walkability, public transport availability, safety, electricity access, digital inclusion, fragility, conflict, violence, water and sanitation, and climatic factors in specific regions. The analytical framework proposed in this paper incorporates a spatial methodology to visualize regions within countries where conducive environments for women to access RE jobs exist. In areas where these environments are absent, the methodology serves as a decision-making tool to reinforce critical factors, such as transportation, education, and internet access, which currently hinder access to employment opportunities. This approach is designed to equip policymakers and institutions with data-driven insights, enabling them to make evidence-based decisions that consider the geographic dimensions of disparity. These insights, in turn, can help ensure the efficient allocation of resources to achieve gender equity objectives.

Keywords: gender, women, spatial analysis, renewable energy, access

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Authors: Carolina Mayen Huerta, Clara Ivanescu, Paloma Marcos

Abstract:

Due to their unique geographic challenges and the imperative to combat climate change, Small Island Developing States (SIDS) are experiencing rapid growth in the renewable energy (RE) sector. However, women's representation in formal employment within this burgeoning field remains significantly lower than their male counterparts. Conventional methodologies often overlook critical geographic data that influence women's job prospects. To address this gap, this paper introduces a Multicriteria Evaluation (MCE) framework designed to identify spatially enabling environments and restrictions affecting women's access to formal employment and business opportunities in the SIDS' RE sector. The proposed MCE framework comprises 24 key factors categorized into four dimensions: Individual, Contextual, Accessibility, and Place Characterization. "Individual factors" encompass personal attributes influencing women's career development, including caregiving responsibilities, exposure to domestic violence, and disparities in education. "Contextual factors" pertain to the legal and policy environment, influencing workplace gender discrimination, financial autonomy, and overall gender empowerment. "Accessibility factors" evaluate women's day-to-day mobility, considering travel patterns, access to public transport, educational facilities, RE job opportunities, healthcare facilities, and financial services. Finally, "Place Characterization factors" enclose attributes of geographical locations or environments. This dimension includes walkability, public transport availability, safety, electricity access, digital inclusion, fragility, conflict, violence, water and sanitation, and climatic factors in specific regions. The analytical framework proposed in this paper incorporates a spatial methodology to visualize regions within countries where conducive environments for women to access RE jobs exist. In areas where these environments are absent, the methodology serves as a decision-making tool to reinforce critical factors, such as transportation, education, and internet access, which currently hinder access to employment opportunities. This approach is designed to equip policymakers and institutions with data-driven insights, enabling them to make evidence-based decisions that consider the geographic dimensions of disparity. These insights, in turn, can help ensure the efficient allocation of resources to achieve gender equity objectives.

Keywords: gender, women, spatial analysis, renewable energy, access

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Authors: Anjali Sharma, R. R. K. Sharma

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The purpose of this study is to examine relationships between personality factors and customer switching for services. Earlier research was directed towards establishing relationship between individual personality traits and customer switching variables considering five-factors model comprised of five personality dimensions (OCEAN), in which personality was not the only influencing factor. Moreover, these works were found to be focused on products and not services. In contrast, the current study is aimed at investigating role of personality using Myer Briggs Type indicator (MBTI) as well as Five-Big Factors, on customer switching and building the conceptual framework on services rather than products. MBTI also known as four opposite pairs or dichotomies of personality dimensions are studied using different levels Involvement (High, Low) of consumer and Value of service-offering (Value for money and Premium) as moderators associated with Consumer Switching. The study is unique in sense that consequences of these indicators of personality on switching behavior has never been studied using considering moderating effect of involvement and value of services. According to our prepositions for a more Extrovert, Intuitive Personality the switching is going to be high whereas the switching is going to be less for an Introvert, Judgmental kind of personality. Similarly, for a consumer with high Neuroticism and Agreeableness the switching would be less as compared to an Open and Conscious Personality type. These level differs with level of a consumer’s involvement and type of a service being offered based on its value.

Keywords: consumer switching, involvement, Myer Briggs personality type indicators, personality, value of service

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Authors: Malizgani Paul Chavula

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Background: Comprehensive sexuality education (CSE) plays a critical role in promoting youth and adolescents’ sexual and reproductive health and well-being. However, little is known about the enablers and barriers affecting the integration of CSE into educational programmes. The aim of this review is to explore positive and negative factors influencing the integration of CSE into national curricula and educational systems in low- and middle-income countries. Methods: We conducted a systematic literature review (January 2010 to August 2022). The results accord with the Preferred Reporting Items for Systematic Reviews and Meta-analysis standards for systematic reviews. Data were retrieved from the PubMed, Cochrane, Google Scholar, and Web of Hinari databases. The search yielded 431 publications, of which 23 met the inclusion criteria for full-text screening. The review is guided by an established conceptual framework that incorporates the integration of health innovations into health systems. Data were analyzed using a thematic synthesis approach. Results: The magnitude of the problem is evidenced by sexual and reproductive health challenges such as high teenage pregnancies, early marriages, and sexually transmitted infections. Awareness of these challenges can facilitate the development of interventions and the implementation and integration of CSE. Reported aspects of the interventions include core CSE content, delivery methods, training materials and resources, and various teacher-training factors. Reasons for adoption include perceived benefits of CSE, experiences and characteristics of both teachers and learners, and religious, social, and cultural factors. Broad system characteristics include strengthening links between schools and health facilities, school and community-based collaboration, coordination of CSE implementation, and the monitoring and evaluation of CSE. Ultimately, the availability of resources, national policies and laws, international agendas, and political commitment will impact upon the extent and level of integration. Conclusion: Social, economic, cultural, political, legal, and financial contextual factors influence the implementation and integration of CSE into national curricula and educational systems. Stakeholder collaboration and involvement in the design and appropriateness of interventions is critical.

Keywords: comprehensive sexuality education, factors, integration, sexual reproductive health rights

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Authors: Eleonora Sofilda, Ria Amalia, Muhammad Zilal Hamzah

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Foreign direct investment is one of the sources of financing or capital that important for a country, especially for developing countries. This investment also provides a great contribution to development through the transfer of assets, management improving, and transfer of technology in enhancing the economy of a country. In the other side currently in ASEAN countries emerge the interesting phenomenon where some big producers are re-locate their basic production among those countries. This research is aimed to analyze the factors that affect capital inflows of foreign direct investment into the 6 ASEAN countries (Indonesia, Malaysia, Singapore, Thailand, Philippines, and Vietnam) in period 2004-2012. This study uses panel data analysis to determine the factors that affect of foreign direct investment in 6 ASEAN. The factors that affect of foreign direct investment (FDI) are the gross domestic product (GDP), global competitiveness (GCI), interest rate, exchange rate and trade openness (TO). Result of panel data analysis show that three independent variables (GCI, GDP, and TO) have a significant effect to the FDI in 6 ASEAN Countries.

Keywords: foreign direct investment, the gross domestic product, global competitiveness, interest rate, exchange rate, trade openness, panel data analysis

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Authors: Jong-Hyo Park, Eunyoung Choi, Jae-Yeon Lim, Seon-Suk Lee, Yeong-Rong Koo, Ji-Ung Kwon, Kyung-Sung Kim, Jong-Ik Lee, Juhan Park, Hyun-Kyu Lee, Won-Kyoung Oh, Jisang Lee, Jiwon Choe

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Due to COVID-19, cyber violence among youths has soared as they spend more time online than before. In contrast to the deepening concerns, measurement tools that can assess the vulnerability of cyber violence in individual youths still need to be supplemented. The measurement tools lack consideration of various factors related to cyber violence among youths. Most of the tools are self-report questionnaires, and these adolescents' self-report questionnaire forms can underestimate the harmful behavior and overestimate the damage experience. Therefore, this study aims to develop a multi-report measurement tool for youths that can reliably measure individuals' ecological factors related to cyber violence. The literature review explored factors related to cyber violence, and the questions were constructed. The face validity of the questions was confirmed by conducting focus group interviews. Exploratory and confirmatory factor analyses (N=671) were also conducted for statistical validation. This study developed a multi-report measurement tool for cyber violence with 161 questions, consisting of six domains: online behavior, cyber violence awareness, victimization-perpetration-witness experience, coping efficacy (individuals, peers, teachers, and parents), psychological characteristics, and pro-social capabilities. In addition to self-report from a youth respondent, this measurement tool includes peers, teachers, and parents reporting for the respondent. It is possible to reliably measure the ecological factors of individual youths who are vulnerable or highly resistant to cyber violence. In schools, teachers could refer to the measurement results for guiding students, better understanding their cyber violence conditions, and assessing their pro-social capabilities. With the measurement results, teachers and police officers could detect perpetrators or victims and intervene immediately. In addition, this measurement tool could analyze the effects of the prevention and intervention programs for cyber violence and draw appropriate suggestions.

Keywords: adolescents, cyber violence, cyber violence measurement tool, measurement tool, multi-report measurement tool, youths

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Authors: Diqin Qi, Jiaming Li, Siman Li

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Based on the use of the three-point smoothing method for selectively processing original data columns, this paper establishes a group of grey GM(1,1) models to predict the concentration ranges of four major air pollutants in Shanghai from 2023 to 2024. The results indicate that PM₁₀, SO₂, and NO₂ maintain the national Grade I standards, while the concentration of PM₂.₅ has decreased but still remains within the national Grade II standards. Combining the forecast results, recommendations are provided for the Shanghai municipal government's efforts in air pollution prevention and control.

Keywords: atmospheric pollutant prediction, Grey GM(1, 1), model group, three-point smoothing method

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Authors: Muhammad Suradi, Sugiarto, Abdullah Latip

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Many roadside slope failures occur during the rainy season, particularly in the period of extreme rainfall along Connecting National Road of Salubatu-Mambi, West Sulawesi, Indonesia. These occurrences cause traffic obstacles and endanger people along and around the road. Research collaboration between P2JN (National Road Construction Board) West Sulawesi Province, who authorize to supervise the road condition, and Ujung Pandang State Polytechnic (Applied University) was established to cope with the landslide problem. This research aims to determine factors triggering roadside slope failures and their optimum stabilizing solution. To achieve this objective, site observation and soil investigation were carried out to obtain parameters for analyses of rainfall-induced slope instability and reinforcement design using the SV Flux and SV Slope software. The result of this analysis will be taken into account for the next analysis to get an optimum design of the slope reinforcement. The result indicates some factors such as steep slopes, sandy soils, and unvegetated slope surface mainly contribute to the slope failures during intense rainfall. With respect to the contributing factors as well as construction material and technology, cantilever/butressing retaining wall becomes the optimum solution for the roadside slope reinforcement.

Keywords: roadside slope, failure, rainfall, slope reinforcement, optimum solution

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Authors: Yusuf Garba Baba

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The construction industry and housing subsector are fraught with risks that have the potential of negatively impacting on the achievement of project objectives. The success or otherwise of most construction projects depends to large extent on how well these risks have been managed. The recent paradigm shift by the subsector to use of formal risk management approach in contrast to hitherto developed rules of thumb means that risks must not only be identified but also properly assessed and responded to in a systematic manner. The study focused on identifying risks associated with housing development projects and prioritisation assessment of the identified risks in order to provide basis for informed decision. The study used a three-step identification framework: review of literature for similar projects, expert consultation and questionnaire based survey to identify potential risk factors. Delphi survey method was employed in carrying out the relative prioritization assessment of the risks factors using computer-based Analytical Hierarchical Process (AHP) software. The results show that 19 out of the 50 risks significantly impact on housing development projects. The study concludes that although significant numbers of risk factors have been identified as having relevance and impacting to housing construction projects, economic risk group and, in particular, ‘changes in demand for houses’ is prioritised by most developers as posing a threat to the achievement of their housing development objectives. Unless these risks are carefully managed, their effects will continue to impede success in these projects. The study recommends the adoption and use of the combination of multi-technique identification framework and AHP prioritization assessment methodology as a suitable model for the assessment of risks in housing development projects.

Keywords: risk management, risk identification, risk analysis, analytic hierarchical process

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Authors: Farrah Anne Robert, Robert McClelland, Seng Kiat Kok

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Higher education service quality is widely regarded as key factors in the long term success of a higher education institution in attracting and retaining students. This research attempted to establish the impact of service quality on recruiting and retaining students in private higher education institutions (PHEI’s). 501 local and international students responded to a 49 item educational service measure questionnaire from PHEIs in Kuala Lumpur and Selangor, two states in Malaysia which together account for 60% of private colleges in Malaysia. Results from this research revealed that, inter-alia, facilities, employability, management and administration services, academic staff competence, curriculum and student overall experiences were key driving factors in attracting and retaining students. Lack of “campus-like building” facilities and lecturer’s effectiveness in delivering lectures were keys concerns in the provision of service quality by PHEI’s in Malaysia. Over the last decade, the Government of Malaysia has set a target of recruiting 200,000 international students to study in Malaysia by PHEI’s and PHEI’s have failed to achieve this target. This research suggests that service quality issues identified above are impacting efforts to recruit and retain both local and international students by PHEIs. The researcher recommends that further and detailed research be carried on these factors and its impact on recruitment and retention. PHEI administrators can benefit from this research by conducting an evaluation of service measures delivered in their institutions and take corrective measures. Prospective students can benefit from this study by including in their choice factors the “service quality delivery” of PHEI’s when deciding to enroll in a particular PHEI.

Keywords: higher education, recruitment, retention, service quality

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Authors: Li-Ching Chen

Abstract:

The case-control design has been widely applied in clinical and epidemiological studies to investigate the association between risk factors and a given disease. The retrospective design can be easily implemented and is more economical over prospective studies. To adjust effects for confounding factors, methods such as stratification at the design stage and may be adopted. When some major confounding factors are difficult to be quantified, a matching design provides an opportunity for researchers to control the confounding effects. The matching effects can be parameterized by the intercepts of logistic models and the conditional logistic regression analysis is then adopted. This study demonstrates an information-matrix-based goodness-of-fit statistic to test the validity of the logistic regression model for matched case-control data. The asymptotic null distribution of this proposed test statistic is inferred. It needs neither to employ a simulation to evaluate its critical values nor to partition covariate space. The asymptotic power of this test statistic is also derived. The performance of the proposed method is assessed through simulation studies. An example of the real data set is applied to illustrate the implementation of the proposed method as well.

Keywords: conditional logistic model, goodness-of-fit, information matrix, matched case-control studies

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Authors: Yamam Abuzinadah

Abstract:

Mental health literacy has become a very influential topic around the world due to the increase of mental health issues that have been reported through national research and surveys. Mental health literacy refers to the awareness, attitudes, beliefs, knowledge and skills when dealing with mental illness. This research explores mental health literacy in the Arabic and the ways culture informs perceptions of mental health in general. Also, the impact of mental health literacy on: help-seeking attitudes, relationships and community interactions. The outcomes of this research will contribute to raising mental health awareness among the Arabic community, develop and enhance mental health service provision and explore new ideas in regards to elevating mental health literacy in the Arabic community. This research aims to explore attitudes, beliefs, perspective, values and perceptions toward mental health in general among the Arabic community. It will also aim to highlight the factors contributing to theses beliefs, perspective, value and perception and accordingly the role these factors play in regards to awareness, services access, recovery and care provided from the family and the community. This thesis will aim to reflect a detailed theorisation and exploration of: (1) The impact of cultural factors on mental health literacy ie. attitudes, beliefs, knowledge and skills. (2) The ways culture informs perceptions of mental health literacy. (3) The impact of mental health literacy on: help-seeking behaviors, and relationships and community interactions.

Keywords: Arab, mental health, literacy, awareness

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