Search results for: age-structured forest population

Authors: Emine Şahin, Murat Soner Balcıoğlu

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The aim of this study was to determine the growth hormone (bGH) gene polymorphism in the Holstein cattle growing around Antalya in Turkey. In order to determine the bGH-AluI polymorphism, polymerase chain reaction - restriction fragment length polymorphism (PCR-RFLP) method was performed. A 891 bp fragment of bGH was amplified and two types of alleles C and D for bGH were observed. In this study, the frequencies of C and D alleles were 0.8438 and 0.1562, respectively. The genotype frequencies for CC, CD and DD were 0.787, 0.191 and 0.022, respectively. According to the results of the chi-square test, a significant deviation from the Hardy-Weinberg equilibrium was not determined for the bGH locus in the population.

Keywords: Growth Hormone Gene, Holstein , Polymorphism, RFLP

Procedia PDF Downloads 375

Authors: Kumar Ashwini, Nayak C. Vinod

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Sudden unexpected death in epilepsy (SUDEP) is a rarity. Each year, about one in 150 epileptics, whose seizures are not controlled, may die of SUDEP. It is a leading cause of death in young adults with uncontrolled seizures. Understanding the genetic basis for SUDEP, is crucial given that the rate of sudden death in epilepsy patients is 20 fold that of the general population. We encountered one such case of a young male, a known epileptic, who was brought dead after a sudden collapse. We hereby present a poster discussing the autopsy findings of this case and also highlighting the importance of understanding the genetic basis of SUDEP.

Keywords: sudden death, epilepsy, genetic, autopsy

Procedia PDF Downloads 375

Authors: James Ladzekpo

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Background: The urgent need to identify new pharmacological targets for diabetes treatment and prevention has been amplified by the disease's extensive impact on individuals and healthcare systems. A deeper insight into the biological underpinnings of diabetes is crucial for the creation of therapeutic strategies aimed at these biological processes. Current predictive models based on genetic variations fall short of accurately forecasting diabetes. Objectives: Our study aims to pinpoint key epigenetic factors that predispose individuals to diabetes. These factors will inform the development of an advanced predictive model that estimates diabetes risk from genetic profiles, utilizing state-of-the-art statistical and data mining methods. Methodology: We have implemented a recursive feature elimination with cross-validation using the support vector machine (SVM) approach for refined feature selection. Building on this, we developed six machine learning models, including logistic regression, k-Nearest Neighbors (k-NN), Naive Bayes, Random Forest, Gradient Boosting, and Multilayer Perceptron Neural Network, to evaluate their performance. Findings: The Gradient Boosting Classifier excelled, achieving a median recall of 92.17% and outstanding metrics such as area under the receiver operating characteristics curve (AUC) with a median of 68%, alongside median accuracy and precision scores of 76%. Through our machine learning analysis, we identified 31 genes significantly associated with diabetes traits, highlighting their potential as biomarkers and targets for diabetes management strategies. Conclusion: Particularly noteworthy were the Gradient Boosting Classifier and Multilayer Perceptron Neural Network, which demonstrated potential in diabetes outcome prediction. We recommend future investigations to incorporate larger cohorts and a wider array of predictive variables to enhance the models' predictive capabilities.

Keywords: diabetes, machine learning, prediction, biomarkers

Procedia PDF Downloads 58

Authors: Sokkhey Phauk, Takeo Okazaki

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The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

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Authors: Estibe Dagne Mekonnen

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In recent years, the prevalence of undernourishment was 30 percent for sub-Saharan Africa, compared with 16 percent for Asia and the Pacific (Ali, 2011). In Ethiopia, almost 40 percent of the total population in the country and 57 percent of Addis Ababa population lives below the international poverty line of US$ 1.25 per day (UNICEF, 2009). This study aims to analyze the determinant of household food secrity in Addis Ababa city administration. Primary data were collected from a survey of 256 households in the selected sub-city, namely Addis Ketema, Arada, and Kolfe Keranio, in the year 2022. Both Purposive and multi-stage cluster random sampling procedures were employed to select study areas and respondents. Descriptive statistics and order logistic regression model were used to test the formulated hypotheses. The result reveals that out of the total sampled households, 25% them were food secured, 13% were mildly food insecure, 26% were moderately food insecure and 36% were severely food insecure. The study indicates that household family size, house ownership, household income, household food source, household asset possession, household awareness on inflation, household access to social protection program, household access to credit and saving and household access to training and supervision on food security have a positive and significant effect on the likelihood of household food security status. However, marital status of household head, employment sector of household head, dependency ratio and household’s nonfood expenditure has a negative and significant influence on household food security status. The study finally suggests that the government in collaboration with financial institutions and NGO should work on sustaining household food security by creating awareness, providing credit, facilitate rural-urban linkage between producer and consumer and work on urban infrastructure improvement. Moreover, the governments also work closely and monitor consumer good suppliers, if possible find a way to subsidize consumable goods to more insecure households and make them to be food secured. Last but not least, keeping this country’s peace will play a crucial role to sustain food security.

Keywords: determinants, household, food security, order logit model, Addis Ababa

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Authors: Arun Dhakal, Geoff Cockfield

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This paper examines the emission potential of different farming practices that the farmers have adopted in Dhanusha District of Nepal and scope of these practices in climate change mitigation. Which practice is more climate-smarter is the question that this aims to address through a life cycle assessment (LCA) of greenhouse gas (GHG) emissions. The LCA was performed to assess if there is difference in emission potential of broadly two farming systems (agroforestry–based and traditional agriculture) but specifically four farming systems. The required data for this was collected through household survey of randomly selected households of 200. The sources of emissions across the farming systems were paddy cultivation, livestock, chemical fertilizer, fossil fuels and biomass (fuel-wood and crop residue) burning. However, the amount of emission from these sources varied with farming system adopted. Emissions from biomass burning appeared to be the highest while the source ‘fossil fuel’ caused the lowest emission in all systems. The emissions decreased gradually from agriculture towards the highly integrated agroforestry-based farming system (HIS), indicating that integrating trees into farming system not only sequester more carbon but also help in reducing emissions from the system. The annual emissions for HIS, Medium integrated agroforestry-based farming system (MIS), LIS (less integrated agroforestry-based farming system and subsistence agricultural system (SAS) were 6.67 t ha-1, 8.62 t ha-1, 10.75 t ha-1 and 17.85 t ha-1 respectively. In one agroforestry cycle, the HIS, MIS and LIS released 64%, 52% and 40% less GHG emission than that of SAS. Within agroforestry-based farming systems, the HIS produced 25% and 50% less emissions than those of MIS and LIS respectively. Our finding suggests that a tree-based farming system is more climate-smarter than a traditional farming. If other two benefits (carbon sequestered within the farm and in the natural forest because of agroforestry) are to be considered, a considerable amount of emissions is reduced from a climate-smart farming. Some policy intervention is required to motivate farmers towards adopting such climate-friendly farming practices in developing countries.

Keywords: life cycle assessment, greenhouse gas, climate change, farming systems, Nepal

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Authors: Mihaela Munteanu (Pila), Silvius Stanciu

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This paper presents the aspects of the official control of fishery in the Republic of Moldova. Currently, the regulations and the activity of national institutions with responsibilities in the field of food quality are in a process of harmonization with the European rules, aiming at European integration, quality improvement and providing a higher level of food safety. The National Agency for Food Safety is the main national body with responsibilities in the field of food safety. In the field of fishery products, the Agency carries out an intensive activity of informing the citizen and controlling the products marketed. The paper presents the dangers related to the consumption of fish and fishery products traded on the national market, the sanitary-veterinary inspections conducted by the profile institution and the improper situations identified. The national market of fishery products depends largely on imports, mainly focused on ocean fish. The research carried out has shown that during the period 2011-2018, following the inspections carried out on fishery products traded on the national market, a number of inconsistencies have been identified. Thus, indigenous products were frequently detected with sensory characteristics unfit for consumption, and being commercialized in inappropriate locations or contaminated with chemical pollutants. On import products controlled, the most frequent inconsistent situations have been represented by inconsistent sensory aspects and by parasite contamination. Taking into account the specific aspects of aquatic products, including the high level of alterability, special conditions of growth, marketing, culinary preparation and consumption are necessary in order to decrease the risk of disease over the population. Certificates, attestations and other documents certifying the quality of batches, completed by additional laboratory examinations, are necessary in order to increase the level of confidence on the quality of products marketed in the Republic. The implementation of various control procedures and mechanisms at national level, correlated with the focused activity of the specialized institutions, can decrease the risk of contamination and avoid cases of disease on the population due to the consumption of fishery products.

Keywords: fishery products, food safety, quality control, Republic of Moldova

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Authors: Zahra Mila Elmi, Mahsa Khanekheshi

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Almost half of the population and potential manpower in the country and rural areas are women. Manpower especially educated people, plays an important role in the production and economic growth. Also, the potential of rural areas to create employment should not be overlooked. In this research, the effects of socio-economic and demographic factors on women's economic participation in rural areas of Iran's provinces will be studied. Therefore, this study was performed by using the results of the rural households income and expenditure surveys -has been taken in 2016- in the framework of pseudo panel data. This study used the logit model and the maximum likelihood method to study the rural women's participation, with 28,265 observations. Results show the inverted U-shaped relationship between age and the probability of female participation; In other words, young women are more likely to participate in labor markets more than the other groups. Divorced and single woman has more chance of participation in comparison with who was being married. With increasing the divorce rate and singleness in Iran, economic policymakers must provide appropriate solutions for this challenge in the coming years. On the base of the results, being a student and the presence of an infant under the age of 6 in the household has a negative effect on the possibility of women's participation in the labor market. The women's education level has a U-shaped relationship with their participation rate. Illiteracy and high education have a strong positive effect on the economic participation of rural women. This shows the dual labor market for women in Iran. Illiterate women are attracted to service jobs, and educated woman are more attracted to education and health jobs. Increasing household income has a small but positive and significant effect on the probability of rural female participation. In the overlook, due to the frequency of the women population in the age group of 25 to 35 years, and more willingness of women in the age 35 to 44 years to participate in the labor market, and studying ofa significant portion of the rural women, the increase of rural female participation is expected in the years ahead. Thus, it is expected policy maker to create new job opportunities for the employment of educated women and take the necessary plan to improve the current situation for women.

Keywords: female participation rate, rural area, provincial data, pseudo-panel data method

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Authors: Sarah E. Casey

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Epilepsy is the most common neurological disorder in children and approximately one-third of children with epilepsy have seizures that are uncontrolled on anticonvulsants alone. Cannabidiol is shown to be an effective treatment at reducing the amount of breakthrough seizures experienced by children with drug resistant epilepsy. Improvements in quality of life and overall condition were noted during cannabidiol treatment. Adverse side effects were experienced and were generally mild to moderate in nature. Additional double-blind, controlled studies with a more diverse sample population and standardized dosing are needed to ensure the efficacy and safety of cannabidiol use in children with drug resistant epilepsy.

Keywords: cannabis, drug resistant epilepsy, children, epilepsy

Procedia PDF Downloads 225

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 130

Authors: Mahnaz Khalafehnilsaz, Rozina Rahnama

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Introduction: The elderly population is growing rapidly, and with this growth comes an increased demand for healthcare services. Artificial intelligence (AI) has the potential to revolutionize the delivery of healthcare services to the elderly population. In this study, the various ways in which AI is used to create health content for elderly people and its transformative impact on the healthcare industry will be explored. Method: A systematic review of the literature was conducted to identify studies that have investigated the role of AI in creating health content specifically for elderly people. Several databases, including PubMed, Scopus, and Web of Science, were searched for relevant articles published between 2000 and 2022. The search strategy employed a combination of keywords related to AI, personalized health content, and the elderly. Studies that utilized AI to create health content for elderly individuals were included, while those that did not meet the inclusion criteria were excluded. A total of 20 articles that met the inclusion criteria were identified. Finding: The findings of this review highlight the diverse applications of AI in creating health content for elderly people. One significant application is the use of natural language processing (NLP), which involves the creation of chatbots and virtual assistants capable of providing personalized health information and advice to elderly patients. AI is also utilized in the field of medical imaging, where algorithms analyze medical images such as X-rays, CT scans, and MRIs to detect diseases and abnormalities. Additionally, AI enables the development of personalized health content for elderly patients by analyzing large amounts of patient data to identify patterns and trends that can inform healthcare providers in developing tailored treatment plans. Conclusion: AI is transforming the healthcare industry by providing a wide range of applications that can improve patient outcomes and reduce healthcare costs. From creating chatbots and virtual assistants to analyzing medical images and developing personalized treatment plans, AI is revolutionizing the way healthcare is delivered to elderly patients. Continued investment in this field is essential to ensure that elderly patients receive the best possible care.

Keywords: artificial intelligence, health content, older adult, healthcare

Procedia PDF Downloads 71

Authors: Gebreslassie Gebru, Gurja Belay, Minister Birhanie, Mulalem Zenebe, Tadelle Dessie, Adriana Vallejo-Trujillo, Olivier Hanotte

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Livestock must adapt to changing environmental conditions, which can result in either phenotypic plasticity or irreversible phenotypic change. In this study, we combine Ecological Niche Modelling (ENM) and Phenotypic Distribution Modelling (PDM) to provide a comprehensive framework for understanding the ecological and phenotypic characteristics of indigenous chicken (Gallus gallus domesticus) ecotypes. This approach helped us to classify these ecotypes, differentiate their phenotypic traits, and identify associations between environmental variables and adaptive traits. We measured 297 adult indigenous chickens from various agro-ecologies, including 208 females and 89 males. A subset of the 22 measured traits was selected using stepwise selection, resulting in seven traits for each sex. Using ENM, we identified four agro-ecologies potentially harbouring distinct phenotypes of indigenous Tigray chickens. However, PDM classified these chickens into three phenotypical ecotypes. Chickens grouped in ecotype-1 and ecotype-3 exhibited superior adaptive traits compared to those in ecotype-2, with significant variance observed. This high variance suggests a broader range of trait expression within these ecotypes, indicating greater adaptation capacity and potentially more diverse genetic characteristics. Several environmental variables, such as soil clay content, forest cover, and mean temperature of the wettest quarter, were strongly associated with most phenotypic traits. This suggests that these environmental factors play a role in shaping the observed phenotypic variations. By integrating ENM and PDM, this study enhances our understanding of indigenous chickens' ecological and phenotypic diversity. It also provides valuable insights into their conservation and management in response to environmental changes.

Keywords: adaptive traits, agro-ecology, appendage, climate, environment, imagej, morphology, phenotypic variation

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Authors: Lizinis Cassendra Frederick Dony, Jirom Jeremy Frederick Dony, Andrew Nicholas, Dewi Binti Tajuddin

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Starting and surviving a business is influenced by various entrepreneurship socio-economics activities. The study revealed that some of the entrepreneurs are not registered under SME but running own business as an intermediary with the private organization entrusted as “Self-Employed.” SME is known as “Small Medium Enterprise” contributes growth in Malaysia. Therefore, the entrepreneurialism business interest and entrepreneurial intention enhancing new spurring production, expanding employment opportunities, increasing productivity, promoting exports, stimulating innovation and providing new avenue in the business market place. This study has identified the unique contribution to the full understanding of complex mechanisms through entrepreneurship obstacles and education impacts on happiness and well-being to society. Moreover, “Ethnic” term has defined as a curious meaning refers to a classification of a large group of people customs implies to ancestral, racial, national, tribal, religious, linguistic and cultural origins. It is a social phenomenon.1 According to Sabah data population is amounting to 2,389,494 showed the predominant ethnic group being the Kadazan Dusun (18.4%) followed by Bajau (17.3%) and Malays (15.3%). For the year 2010, data statistic immigrants population report showed the amount to 239,765 people which cover 4% of the Sabahan’s population.2 Sabah has numerous group of talented entrepreneurs. The business environment among the minority ethnics are influenced with the business sentiment competition. The literature on ethnic entrepreneurship recognizes two main type entrepreneurships: the middleman and enclave entrepreneurs. According to Adam Smith,3 there are evidently some principles disposition to admire and maintain the distinction business rank status and cause most universal business sentiments. Due to credit barriers competition, the minority ethnics are losing the business market and since 2014, many illegal immigrants have been found to be using permits of the locals to operate businesses in Malaysia.4 The development of small business entrepreneurship among the minority ethnics in Sabah evidenced based variety of complex perception and differences concepts. The studies also confirmed the effects of heterogeneity on group decision and thinking caused partly by excessive pre-occupation with maintaining cohesiveness and the presence of cultural diversity in groups should reduce its probability.5 The researchers proposed that there are seven success determinants particularly to determine the involvement of minority ethnics comparing to the involvement of the immigrants in Sabah. Although, (SMEs) have always been considered the backbone of the economy development, the minority ethnics are often categorized it as the “second-choice.’ The study showed that illegal immigrants entrepreneur imposed a burden on Sabahan social programs as well as the prison, court and health care systems. The tension between the need for cheap labor and the impulse to protect Malaysian in Sabah workers, entrepreneurs and taxpayers, among the subjects discussed in this study. This is clearly can be advantages and disadvantages to the Sabah economic development.

Keywords: entrepreneurial firms, self-employed, immigrants, minority ethnic, economic impacts

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Authors: Berfu Guley Goren, Ayse Lale Berkoz

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The aim of the study is to analyze the concept of universal design and accessibility to make the city which allows equality and independence for individuals. In the content of the study, literature researches and observations of samples in Istanbul, Turkey are analyzed. As a result proposals are going to be developed to create the cities which are designed for everyone. In globalization process, in cities, population have been increasing dramatically with social and economic activities. Medical developments have been effective in prolonging human life and the disability that comes with aging has also increased in parallel with the disabled population. Nowadays disability is an important phenomenon. Because approximately 1 billion people live with disabilities. The heterogeneous structure formed by the rapid gathering of individuals with different social, economic and physical characteristics in the cities creates great spatial diversity and richness in the cities with different needs brought together. Unlike the cultural and physical wealth in these places and the potential to integrate and diversify the urban people, unfortunately, the designs in practice cause the urban areas to break apart, the urbanities to tear themselves apart, to interfere with their communication and interactions. The social and physical structure of the city is important to feel belonging to the urban society. In most cities when an observation is made, obstructions for people with disabilities can be seen in urban physical structure and design. With these obstructions, people with disabilities cannot live in urban space, and they are desolated in urban life. The city, which offers equal opportunity, the relation between economic development, social justice and built environment must be planned synchronous. Isolation and stigmatization must be abolished by regulations, activities of awareness and universal urban design. Without regard to social, economical and physical features every individual has the same right, which is using the freedom of movement. Supporting freedom of movement of every individual may be ensured by universal design and its principles. So urban spaces are going to be for every individual. For equal opportunity in urban services, urban design must be the focus on every individual including people with disabilities. In built environment practices, democratic suitable spaces should be created. In this respect, urban planners, architects, political decision-makers and other relevant actors should work together and should think very versatile.

Keywords: disability, equality, universal design, urban design

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Authors: Cherrie Mae S. Sia, Noel J. Belonguel, Jarungchai Anton S. Vatanagul

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Background: Parkinson’s disease (PD) is a chronic progressive, neurodegenerative disorder known for its motor symptoms such as bradykinesia, resting tremor, muscle rigidity, and postural instability. Patients with PD also experience non-motor symptoms (NMS) such as depression, fatigue, and sleep disturbances that are most of the time unrecognized by clinicians. This may be due to the lack of spontaneous reports from the patients or partly because of the lack of systematic questioning from the healthcare professional. There is limited data with regards to these NMS especially that of Filipino patients with PD. Objectives: This study aims to determine the non-motor symptoms of Filipino patients with Parkinson’s disease. Materials and Methods: This is a prospective, cohort study involving thirty-four patients of Filipino-descent diagnosed with PD in three out-patient clinics in Cebu City from April to September 2014. Each patient was interviewed using the Non-Motor Symptom Scale (NMSS). A Cebuano version of the NMSS was also provided for the non-English speaking patients. Interview time was approximately ten to fifteen minutes for each respondent. Results: Of the thirty-four patients with Parkinson’s disease, majority was noted to be males (N=19) and the disease was noted to be more prevalent in patients with a mean age of 62 (SD±9) years old. Hypertension (59%) and diabetes mellitus (29%) were the common co-morbidities in the study population. All patients presented more than one NMS, with insomnia (41.2%), poor memory (23.5%) and depression (14.7%) being the first non-motor symptoms to occur. Symptoms involving mood/cognition (mean=2.21), and attention/memory (mean=2.05) were noted to be the most frequent and of moderate severity. Based on the NMSS, the symptoms that were noted to be mild and often to occur were those that involved the mood/cognition (score=3.84), attention/memory (score=3.50), and sleep/fatigue (score=3.00) domains. Levodopa-Carbidopa, Ropinirole, and Pramipexole were the most frequently used medications in the study population. Conclusion: Non-motor symptoms (NMS) are common in patients with Parkinson’s disease (PD). They appear at the time of diagnosis of PD or even before the motor symptoms manifest. The earliest non-motor symptoms to occur are insomnia, poor memory, and depression. Those pertaining to mood/cognition and attention/memory are the most frequent NMS and they are of moderate severity. Identifying these NMS by doing a questionnaire-guided interview such as the Non-Motor Symptom Scale (NMSS) before they can become more severe and affect the patient’s quality of life is a must for every clinician caring for a PD patient. Early treatment and control of these NMS can then be given, hence, improving the patient’s outcome and prognosis.

Keywords: non motor symptoms, Parkinson's Disease, insomnia, depression

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Authors: Sk Ajim Ali

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The present study is an attempt to overview on the major environmental and health impacts due to hazardous waste generation and poor management. In present scenario, not only hazardous waste, but as a common term ‘Waste’ is one of the acceptable and thinkable environmental issues. With excessive increasing population, industrialization and standardization of human’s life style heap in extra waste generation which is directly or indirectly related with hazardous waste generation. Urbanization and population growth are solely responsible for establishing industrial sector and generating various Hazardous Waste (HW) and concomitantly poor management practice arising adverse effect on environment and human health. As compare to other Indian state, West Bengal is not too much former in HW generation. West Bengal makes a rank of 7th in HW generation followed by Maharashtra, Gujarat, Tamil Nadu, U.P, Punjab and Andhra Pradesh. During the last 30 years, the industrial sectors in W.B have quadrupled in size, during 1995 there were only 440 HW generating Units in West Bengal which produced 129826 MTA hazardous waste but in 2011, it rose up into 609 units and it produced about 259777 MTA hazardous waste. So, the notable thing is that during a 15 year interval there increased 169 waste generating units but it produced about 129951 MTA of hazardous waste. Major chemical industries are the main sources of HW and causes of adverse effect on the environment and human health. HW from industrial sectors contains heavy metals, cyanides, pesticides, complex aromatic compounds (i.e. PCB) and other chemical which are toxic, flammable, reactive, and corrosive and have explosive properties which highly affect the surrounding environment and human health in and around he disposal sites. The main objective of present study is to highlight on the sources and components of hazardous waste in West Bengal and impacts of improper HW management on health and environment. This study is carried out based on a secondary source of data and qualitative method of research. The secondary data has been collected annual report of WBPCB, WHO’s report, research paper, article, books and so on. It has been found that excessive HW generation from various sources and communities has serious health hazards that lead to the spreading of infectious disease and environmental change.

Keywords: environmental impacts, existing HW generation and management practice, hazardous waste (HW), health impacts, recommendation and planning

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Authors: Mohammad Atiqur Rahman

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The study aimed at inventorying the threatened biodiversity of Bangladesh and assessing the rate of loss of biodiversity caused due to environmental degradation for conservation management. The impact assessment of environmental depletion and rate of biodiversity loss determination have been made by a long term field investigation, examination of preserved herbarium specimens and survey of relevant floristic literature following the IUCN’s threatened criteria of assessing Red List Plants under the Flora Bangladesh Project. Biodiversity of Bangladesh, as evaluated, has been affected to a large extent during the last four and half decades due to spontaneous environmental degradation caused by frequent occurrence of cyclonic storms and tidal bores since 1970 and flooding, draught, unilateral diversion of trans-boundary waters by operating Farakka Barrage since 1975, indiscriminate destruction and over exploitation of natural resources, unplanned development and industrialization, overpopulation etc. Depletion of world’s largest mangrove biodiversity in Sundarbans, coastal and island biodiversity in southern part, agro-biodiversity and agro-fisheries all over the country, Haor and wetland biodiversity of plain lands, terrestrial and forest biodiversity in central and eastern hilly part of Bangladesh, as assessed, have greatly been occurred at a higher rate due to environmental degradation which in turn affect directly or indirectly the economy, food security and environmental health of the country. Complete inventory of 30 plant families resulted in the recognition of 45.18% species of Bangladesh as threatened environmentally and 13.23% species as possibly extinct from the flora since these have neither been reported or could be traced in the field for more than 100 years. The rate of extinction is determined to be 2.65% per 20 years. Hence the study indicates that the loss of biodiversity and environmental degradation in Bangladesh occurring at an alarming rate. The study focuses on the issues of environment, the extent of loss of different plant biodiversities in Bangladesh, prioritizing and implementing national conservation strategies for sustainable management of the environment.

Keywords: Bangladesh, biodiversity, conservation, environmental management

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Authors: Tommaso Adamo, Gianpaolo Ghiani, Antonio Domenico Grieco, Emanuela Guerriero

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Batch production plants provide a wide range of scheduling problems. In pharmaceutical industries a batch process is usually described by a recipe, consisting of an ordering of tasks to produce the desired product. In this research work we focused on pharmaceutical production processes requiring the culture of a microorganism population (i.e. bacteria, yeasts or antibiotics). Several sources of uncertainty may influence the yield of the culture processes, including (i) low performance and quality of the cultured microorganism population or (ii) microbial contamination. For these reasons, robustness is a valuable property for the considered application context. In particular, a robust schedule will not collapse immediately when a cell of microorganisms has to be thrown away due to a microbial contamination. Indeed, a robust schedule should change locally in small proportions and the overall performance measure (i.e. makespan, lateness) should change a little if at all. In this research work we formulated a constraint programming optimization (COP) model for the robust planning of antibiotics production. We developed a discrete-time model with a multi-criteria objective, ordering the different criteria and performing a lexicographic optimization. A feasible solution of the proposed COP model is a schedule of a given set of tasks onto available resources. The schedule has to satisfy tasks precedence constraints, resource capacity constraints and time constraints. In particular time constraints model tasks duedates and resource availability time windows constraints. To improve the schedule robustness, we modeled the concept of (a, b) super-solutions, where (a, b) are input parameters of the COP model. An (a, b) super-solution is one in which if a variables (i.e. the completion times of a culture tasks) lose their values (i.e. cultures are contaminated), the solution can be repaired by assigning these variables values with a new values (i.e. the completion times of a backup culture tasks) and at most b other variables (i.e. delaying the completion of at most b other tasks). The efficiency and applicability of the proposed model is demonstrated by solving instances taken from Sanofi Aventis, a French pharmaceutical company. Computational results showed that the determined super-solutions are near-optimal.

Keywords: constraint programming, super-solutions, robust scheduling, batch process, pharmaceutical industries

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Authors: Emmanuel Olasope Bamigboye, Ismail Oladeji Oladosu

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Local people of south-western Nigeria like in other climes, continue to be confronted with the vagaries of changing environments. Through the modification of existing practice and shifting resource base, their strategies for coping with change have enabled them to successfully negotiate the shifts in climate change and the environment. This article analyses indigenous adaptation strategies for climate change with a view to enhancing sustainable crop farming in south –western Nigeria. Multi-stage sampling procedure was used to select 340 respondents from the two major ecological zones (Forest and Derived Savannah) for good geographical spread. The article draws on mixed methods of qualitative research, literature review, field observations, informal interview and multinomial logit regression to capture choice probabilities across the various options of climate change adaptation options among arable crop farmers. The study revealed that most 85.0% of the arable crop farmers were males. It also showed that the use of local climate change adaptation strategies had no relationship with the educational level of the respondents as 77.3% had educational experiences at varying levels. Furthermore, the findings showed that seven local adaptation strategies were commonly utilized by arable crop farmers. Nonetheless, crop diversification, consultation with rainmakers and involvement in non-agricultural ventures were prioritized in the order of 1-3, respectively. Also, multinomial logit analysis result showed that at p ≤ 0.05 level of significance, household size (P<0.08), sex (p<0.06), access to loan(p<0.16), age(p<0.07), educational level (P<0.17) and functional extension contact (P<0.28) were all important in explaining the indigenous climate change adaptation utilized by the arable crops farmers in south-western Nigeria. The study concluded that all the identified local adaptation strategies need to be integrated into the development process for sustainable climate change adaptation.

Keywords: crop diversification, climate change, adaptation option, sustainable, small farmers

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Authors: Avijit Mahala

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Present study is primarily concerned with the physical processes and status of land degradation in a tropical plateau fringe. Chotanagpur plateau is one of the most water erosion related degraded areas of India. The granite gneiss geological formation, low to medium developed soil cover, undulating lateritic uplands, high drainage density, low to medium rainfall (100-140cm), dry tropical deciduous forest cover makes the Silabati River basin a truly representative of the tropical environment. The different physical factors have been taken for land degradation study includes- physiographic formations, hydrologic characteristics, and vegetation cover. Water erosion, vegetal degradation, soil quality decline are the major processes of land degradation in study area. Granite-gneiss geological formation is responsible for developing undulating landforms. Less developed soil profile, low organic matter, poor structure of soil causes high soil erosion. High relief and sloppy areas cause unstable environment. The dissected highland causes topographic hindrance in productivity. High drainage density and frequency in rugged upland and intense erosion in sloppy areas causes high soil erosion of the basin. Decreasing rainfall and increasing aridity (low P/PET) threats water stress condition. Green biomass cover area is also continuously declining. Through overlaying the different physical factors (geological formation, soil characteristics, geomorphological characteristics, etc.) of considerable importance in GIS environment the varying intensities of land degradation areas has been identified. Middle reaches of Silabati basin with highly eroded laterite soil cover areas are more prone to land degradation.

Keywords: land degradation, tropical environment, lateritic upland, undulating landform, aridity, GIS environment

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Authors: Yasser Y. Lenis, Daniela Garcia Gonzalez, Cristian Solarte Bacca, Diego F. Carrillo González, Amy Jo Montgomery, Dursun Barrios

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Introduction: Artificial insemination in bovines helps to promote genetic improvement and can positively impact the rural economy. The Colombian armed conflict has forced a large portion of the rural population to abandon their territory, affecting their education, family integration, and economics. Justification: The achievement of education in rural populations was one of the Millennium Development Goals (MDGs) made by the United Nations. During the last World Summit on Sustainable Development (WSSD), it was concluded that most of the world’s poor, illiterate and undernourished population lives in rural areas; therefore, access to education is considered one of the most significant challenges for governments in countries with developing economies. Objectives: To study the effects of training in artificial insemination and rural management on the perception of knowledge and the level of knowledge in rural residents affected by the armed conflict in Nariño, Colombia. Methods: The perception of knowledge and the theoretical-practical knowledge of 63 rural residents were evaluated on the topics of bovine agribusiness management, artificial insemination, and genetic improvement through the application of three surveys. 1) evaluated the perceived level of knowledge each rural resident had about each topic using the Likert scale, 2) evaluated the theoretical knowledge before training, and 3) evaluated the theoretical knowledge upon completion of training. Results/discussion: Of the surveyed rural residents, 54% stated that they knew how business management improved the performance of their bovine agribusiness, 54% answered the pre-training knowledge test correctly, while 83% correctly answered the post-training knowledge test. Only 6% of surveyed residents perceived that they had prior knowledge of artificial insemination and reproductive anatomy topics. Before training, 35% of surveyed residents answered correctly on these topics, while upon completion of training, 65% answered correctly. Regarding genetic improvement, 11% of participating rural residents stated that they knew this subject. The correct answers on this topic went from 57% to 89% before and post-training. Conclusion: Rural extension programs contribute to closing knowledge gaps in relation to the use of reproductive biotechnologies and bovine management in rural areas affected by armed conflict.

Keywords: agribusiness, insemination, knowledge, reproduction

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Authors: Yusuke Katayama, Tetsuhisa Kitamura, Kosuke Kiyohara, Sumito Hayashida, Taku Iwami, Takashi Kawamura, Takeshi Shimazu

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Background: Recently, the number of ambulance dispatches has been increasing in Japan and it is, therefore, difficult to accept emergency patients to hospitals smoothly and appropriately because of the limited hospital capacity. To facilitate the request for patient transport by ambulances and hospital acceptance, the emergency information system using information technology has been built up and introduced in various communities. However, its effectiveness has not been insufficiently revealed in Japan. In 2013, we developed a smartphone application system that enables the emergency-medical-service (EMS) personnel to share information about on-scene ambulance and hospital situation. The aim of this study was to assess the introduction effect of this application for EMS system in Osaka City, Japan. Methods: This study was a retrospective study with population-based ambulance records of Osaka Municipal Fire Department. This study period was six years from January 1, 2010 to December 31, 2015. In this study, we enrolled emergency patients that on-scene EMS personnel conducted the hospital selection for them. The main endpoint was difficulty in hospital acceptance at the scene. The definition of difficulty in hospital acceptance at the scene was to make >=5 phone calls by EMS personnel at the scene to each hospital until a decision to transport was determined. The definition of the smartphone application group was emergency patients transported in the period of 2013-2015 after the introduction of this application, and we assessed the introduction effect of smartphone application with multivariable logistic regression model. Results: A total of 600,526 emergency patients for whom EMS personnel selected hospitals were eligible for our analysis. There were 300,131 smartphone application group (50.0%) in 2010-2012 and 300,395 non-smartphone application group (50.0%) in 2013-2015. The proportion of the difficulty in hospital acceptance was 14.2% (42,585/300,131) in the smartphone application group and 10.9% (32,819/300,395) in the non-smartphone application group, and the difficulty in hospital acceptance significantly decreased by the introduction of the smartphone application (adjusted odds ration; 0.730, 95% confidence interval; 0.718-0.741, P<0.001). Conclusions: Sharing information between ambulance and hospital by introducing smartphone application at the scene was associated with decreasing the difficulty in hospital acceptance. Our findings may be considerable useful for developing emergency medical information system with using IT in other areas of the world.

Keywords: difficulty in hospital acceptance, emergency medical service, infomation technology, smartphone application

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Authors: Gholamreza Nuei, Faisal Ahmad Shah

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The way religion defines people’s identity is quite important in the majority of Muslim countries. Yet, in most such countries the number of Muslims converting to other religions is not documented. The present research investigates a population of Iranians who have converted to Christianity and live in Malaysia. This article focuses on this subgroup of ex-Muslims with the aim of providing a window into how they experience and justify their conversion. The data was collected in Kuala Lumpur, Malaysia. It was carried out through in-depth interviews with 13 people; also 45 people answered a questionnaire (quantitative). The research findings revealed some of the typical religious, social and personal reasons behind the conversion of this group of "ex-Muslims".

Keywords: conversion from Islam to Christianity, apostasy, Iran, Malaysia

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Authors: P. Defossez, J. M. Bonnefond, D. Garrigou, P. Trichet, F. Danjon

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Windstorm damage to European forests has ecological, social and economic consequences of major importance. Most trees during storms are uprooted. While a large amount of work has been done over the last decade on understanding the aerial tree response to turbulent wind flow, much less is known about the root-soil interface, and the impact of soil moisture and root-soil system fatiguing on tree uprooting. Anchorage strength is expected to be reduced by water-logging and heavy rain during storms due to soil strength decrease with soil water content. Our paper is focused on the maritime pine cultivated on sandy soil, as a representative species of the Forêt des Landes, the largest cultivated forest in Europe. This study aims at providing knowledge on the effects of soil saturation on root anchorage. Pulling experiments on trees were performed to characterize the resistance to wind by measuring the critical bending moment (Mc). Pulling tests were performed on 12 maritime pines of 13-years old for two unsaturated soil conditions that represent the soil conditions expected in winter when wind storms occur in France (w=11.46 to 23.34 % gg⁻¹). A magnetic field digitizing technique was used to characterize the three-dimensional architecture of root systems. The soil mechanical properties as function of soil water content were characterized by laboratory mechanical measurements as function of soil water content and soil porosity on remolded samples using direct shear tests at low confining pressure ( < 15 kPa). Remarkably Mc did not depend on w but mainly on the root system morphology. We suggested that the importance of soil water conditions on tree anchorage depends on the tree size. This study gives a new insight on young tree anchorage: roots may sustain by themselves anchorage, whereas adhesion between roots and surrounding soil may be negligible in sandy soil.

Keywords: roots, sandy soil, shear strength, tree anchorage, unsaturated soil

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Authors: Saeid Gharechelou, Ryutaro Tateishi

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Earthquake is an inevitable catastrophic natural disaster. The damages of buildings and man-made structures, where most of the human activities occur are the major cause of casualties from earthquakes. A comparison of optical and SAR data is presented in the case of Kathmandu valley which was hardly shaken by 2015-Nepal Earthquake. Though many existing researchers have conducted optical data based estimated or suggested combined use of optical and SAR data for improved accuracy, however finding cloud-free optical images when urgently needed are not assured. Therefore, this research is specializd in developing SAR based technique with the target of rapid and accurate geospatial reporting. Should considers that limited time available in post-disaster situation offering quick computation exclusively based on two pairs of pre-seismic and co-seismic single look complex (SLC) images. The InSAR coherence pre-seismic, co-seismic and post-seismic was used to detect the change in damaged area. In addition, the ground truth data from field applied to optical data by random forest classification for detection of damaged area. The ground truth data collected in the field were used to assess the accuracy of supervised classification approach. Though a higher accuracy obtained from the optical data then integration by optical-SAR data. Limitation of cloud-free images when urgently needed for earthquak evevent are and is not assured, thus further research on improving the SAR based damage detection is suggested. Availability of very accurate damage information is expected for channelling the rescue and emergency operations. It is expected that the quick reporting of the post-disaster damage situation quantified by the rapid earthquake assessment should assist in channeling the rescue and emergency operations, and in informing the public about the scale of damage.

Keywords: Sentinel-1A data, Landsat-8, earthquake damage, InSAR, rapid damage monitoring, 2015-Nepal earthquake

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Authors: Baptiste Brodard

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In Switzerland, as well as in other European countries, specific social issues related to Muslims have recently emerged in public debates. In addition to the question of terrorism and radicalization, Muslim migrant populations are highly affected by social problems such as crime, poverty, marginalization, and overrepresentation in prisons. This situation has drawn the state’s attention to the need for implementing new responses to the challenges of religious extremism, crime, and social exclusion particularly involving Muslims. While local authorities have begun to implement trainings and projects to tackle these new social issues, Muslim grassroots associations have developed some initiatives to address the needs of the population, mainly focusing on problems related to Islam and Muslims but also addressing the rest of the population. Finally, some local authorities have acknowledged the need for these alternative initiatives as well as their positive contributions to society. The study is based on a Ph.D. research grounded on a case study of three Islamic networks in Switzerland, including various local organizations tackling social exclusion and religious radicalization through innovative grassroots projects. Using an ethnographic approach, it highlights, on the one hand, the specificities of such organizations by exploring the role of Islamic norms within the social work practices. On the other hand, it focuses on the inclusion of such faith-based projects within the mainstream society, observing the relationships between Islamic organisations and both the state and other civil society organizations. Finally, the research study aims to identify some innovative ways and trends of social work involving the inclusion of community key actors within the process. Results showed similar trends with Islamic social work developed in other European countries such as France and the United Kingdom, but also indicate a range of specificities linked to the Swiss socio-political context, which shapes the involvement of religious actors in different ways. By exploring faith-based commitment to addressing concrete social issues, the study finally contributes to shedding light on the link between Islam, social work and activism within the European context.

Keywords: exclusion, Islam, Muslims, social work, Switzerland

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Authors: Tiago Sigal Linhares, Ana Amélia Nascimento da Silva Bones, Juliana Miola, McArthur Alexander Barrow, Airton Tetelbom Stein

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Introduction: As a result of increased globalization and changing migration trends, it is expected that a significant portion of People Living with HIV/AIDS (PLWHA) will change their place of residence over time. In order to provide better health care, monitor the HIV epidemic and plan urban public health care and policies, there is a growing need to formulate a strategy for monitoring PLWHA care, location and migration patterns. The Porto Alegre District is characterized by a high prevalence of PLWHA and is considered one of the epicenters of HIV epidemic in Latin America. Objectives: The aim of this study is to create a digital and easily editable map in order to create a visual representation of the location of PLWHA and to monitor their migration within the city and the country in an effort to promote longitudinal care. Methods: This Experience Report used Google Maps Map Creator to generate an active digital map showing the location and changes in residence of 165 PLWHA who received care at two Primary Health Care (PHC) clinics, which attended an estimated population of five thousand patients, in downtown Porto Alegre over the last four years. Their current addresses were discovered in the unified Brazilian health care system digital records (e-SUS) and updated on the map. Results: A digital map with PLWHA current residence location was created. It was possible to demonstrate visually areas with a large concentration of PLWHA and the migration of the population within the city as wells as other cities, regions and states. Conclusions: An easily reproducible and free map could aid in PLWHA monitoring, urban public health planning, target interventions and situational diagnosis. Moreover, a visual representation of PLWHA location and migration could help bring more attention and investments to areas with geographic inequities or higher prevalence of PLWHA. It also enables notification of local PHC units of monitored patients inside their area, which are in clinical risk or with treatment abandonment through active case findings, improving the care of PLWHA.

Keywords: health care, medical public health, theoretical and conceptual innovations, urban public health

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Authors: Varinder Kaur Gambhir, Neema Gupta, Sonal Tickoo Chaudhuri

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Bengaluru, a rapidly growing metropolis in India, with a population of 12.5 million citizens, generates 5,757 metric tonnes of solid waste per day. Despite their invaluable contribution to waste management, society and the economy, waste pickers face significant stigma, suspicion and contempt and are left with a sense of shame about their work. In this context, BBC Media Action was funded by the H&M Foundation to develop a 3-year multi-phase social media campaign to shift perceptions of waste picking and informal waste pickers amongst the Bengaluru population. Research has been used to inform project strategy and adaptation, at all stages. Formative research to inform campaign strategy used mixed methods– 14 focused group discussions followed by 406 online surveys – to explore people’s knowledge of, and attitudes towards waste pickers, and identify potential barriers and motivators to changing perceptions. Use of qualitative techniques like metaphor maps (using bank of pictures rather than direct questions to understand mindsets) helped establish the invisibility of informal waste pickers, and the quantitative research enabled audience segmentation based on attitudes towards informal waste pickers. To pretest the campaign idea, eight I-GDs (individual interaction followed by group discussions) were conducted to allow interviewees to first freely express their feelings individually, before discussing in a group. Robert Plucthik’s ‘wheel of emotions’ was used to understand audience’s emotional response to the content. A robust monitoring and evaluation is being conducted (baseline and first phase of monitoring already completed) using a rotating longitudinal panel of 1,800 social media users (exposed and unexposed to the campaign), recruited face to face and representative of the social media universe of Bengaluru city. In addition, qualitative in-depth interviews are being conducted after each phase to better understand change drivers. The research methodology and ethical protocols for impact evaluation have been independently reviewed by an Institutional Review Board. Formative research revealed that while waste on the streets is visible and is of concern to the public, informal waste pickers are virtually ‘invisible’, for most people in Bengaluru Pretesting research revealed that the creative outputs evoked emotions like acceptance and gratitude towards waste-pickers, suggesting that the content had the potential to encourage attitudinal change. After the first phase of campaign, social media analytics show that #Invaluables content reached at least 2.6 million unique people (21% of the Bengaluru population) through Facebook and Instagram. Further, impact monitoring results show significant improvements in spontaneous awareness of different segments of informal waste pickers ( such as sorters at scrap shops or dry waste collection centres -from 10% at baseline to 16% amongst exposed and no change amongst unexposed), recognition that informal waste pickers help the environment (71% at baseline to 77% among exposed and no change among unexposed) and greater discussion about informal waste pickers among those exposed (60%) as against not exposed (49%). Using the insights from this research, the planned social media intervention is designed to increase the visibility of and appreciation for the work of waste pickers in Bengaluru, supporting a more inclusive society.

Keywords: awareness, discussion, discrimination, informal waste pickers, invisibility, social media campaign, waste management

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Authors: Emmanuel Maiyanga

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Access to sufficiently good quality freshwater has been a global challenge, but more notably in low-income countries, particularly in the Sub-Saharan countries, which Nigeria is one. Urban population is soaring, especially in many low-income countries, the existing centralised water supply infrastructures are ageing and inadequate, moreover in households peoples’ lifestyles have become more water-demanding. So, people mostly device coping strategies where municipal supply is perceived to have failed. This development threatens the futures of groundwater and calls for a review of management strategy and research approach. The various issues associated with water demand management in low-income countries and Nigeria, in particular, are well documented in the literature. However, the way people use water daily in households and the reasons they do so, and how the situation is constructing demand among the middle-class population in Abuja Nigeria is poorly understood. This is what this research aims to unpack. This is achieved by using the social practices research approach (which is based on the Theory of Practices) to understand how this situation impacts on the shared groundwater resource. A qualitative method was used for data gathering. This involved audio-recorded interviews of householders and water professionals in the private and public sectors. It also involved observation, note-taking, and document study. The data were analysed thematically using NVIVO software. The research reveals the major household practices that draw on the water on a domestic scale, and they include water sourcing, body hygiene and sanitation, laundry, kitchen, and outdoor practices (car washing, domestic livestock farming, and gardening). Among all the practices, water sourcing, body hygiene, kitchen, and laundry practices, are identified to impact most on groundwater, with impact scale varying with household peculiarities. Water sourcing practices involve people sourcing mostly from personal boreholes because the municipal water supply is perceived inadequate and unreliable in terms of service delivery and water quality, and people prefer easier and unlimited access and control using boreholes. Body hygiene practices reveal that every respondent prefers bucket bathing at least once daily, and the majority bathe twice or more every day. Frequency is determined by the feeling of hotness and dirt on the skin. Thus, people bathe to cool down, stay clean, and satisfy perceived social, religious, and hygiene demand. Kitchen practice consumes water significantly as people run the tap for vegetable washing in daily food preparation and dishwashing after each meal. Laundry practice reveals that most people wash clothes most frequently (twice in a week) during hot and dusty weather, and washing with hands in basins and buckets is the most prevalent and water wasting due to soap overdose. The research also reveals poor water governance as a major cause of current inadequate municipal water delivery. The implication poor governance and widespread use of boreholes is an uncontrolled abstraction of groundwater to satisfy desired household practices, thereby putting the future of the shared aquifer at great risk of total depletion with attendant multiplying effects on the people and the environment and population continues to soar.

Keywords: boreholes, groundwater, household water practices, self-supply

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Authors: Varsha Salian, Shama Rao, N. Narendra, B. Mohana Kumar

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Evolving evidence proposes the existence of a highly tumorigenic subpopulation of undifferentiated, self-renewing cancer stem cells, responsible for exhibiting resistance to conventional anti-cancer therapy, recurrence, metastasis and heterogeneous tumor formation. Importantly, the mechanisms exploited by cancer stem cells to resist chemotherapy are very less understood. Oral squamous cell carcinoma (OSCC) is one of the most regularly diagnosed cancer types in India and is associated commonly with alcohol and tobacco use. Therefore, the isolation and in vitro characterization of cancer stem-like cells from patients with OSCC is a critical step to advance the understanding of the chemoresistance processes and for designing therapeutic strategies. With this, the present study aimed to establish and characterize cancer stem-like cells in vitro from OSCC. The primary cultures of cancer stem-like cell lines were established from the tissue biopsies of patients with clinical evidence of an ulceroproliferative lesion and histopathological confirmation of OSCC. The viability of cells assessed by trypan blue exclusion assay showed more than 95% at passage 1 (P1), P2 and P3. Replication rate was performed by plating cells in 12-well plate and counting them at various time points of culture. Cells had a more marked proliferative activity and the average doubling time was less than 20 hrs. After being cultured for 10 to 14 days, cancer stem-like cells gradually aggregated and formed sphere-like bodies. More spheroid bodies were observed when cultured in DMEM/F-12 under low serum conditions. Interestingly, cells with higher proliferative activity had a tendency to form more sphere-like bodies. Expression of specific markers, including membrane proteins or cell enzymes, such as CD24, CD29, CD44, CD133, and aldehyde dehydrogenase 1 (ALDH1) is being explored for further characterization of cancer stem-like cells. To summarize the findings, the establishment of OSCC derived cancer stem-like cells may provide scope for better understanding the cause for recurrence and metastasis in oral epithelial malignancies. Particularly, identification and characterization studies on cancer stem-like cells in Indian population seem to be lacking thus provoking the need for such studies in a population where alcohol consumption and tobacco chewing are major risk habits.

Keywords: cancer stem-like cells, characterization, in vitro, oral squamous cell carcinoma

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