Search results for: trends and variability of rainfall

Authors: Duy Nguyen Do, Bart Julien Dewancker

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Many Soviet-style collective housing complexes (also known as KTT) were built since the 1960s in Hanoi to support the post-war population growth. Those low-rise buildings have created well-knitted, robust communities, so much to the point that in most complexes, all families in one housing block would know each other, occasionally interact and provide supports in need. To understand how the community of collective housing complexes have developed and maintained in order to adapt their advantages into modern housing designs, the study is executed on the site of Nguyen Cong Tru KTT. This is one of the oldest KTT in Hanoi, completed in 1954. The complex also has an unique characteristic that is closely related to its community: the symbiotic relationship with Hom – a flea market that has been co-developing with Nguyen Cong Tru KTT since its beginning. The research consists of three phases: the first phase is a sociological investigation with Nguyen Cong Tru KTT’s current residents and a site survey on the complex’s economic and architectural characteristics. In the second phase, the collected data is analyzed to find out people’s opinions with the KTT’s concerning their satisfaction with the current housing status, floor plan organization, community, the relationship between the KTT’s dedicated public spaces with the flea market and their usage. Simultaneously, the master plan and gathered information regarding current architectural characteristics of the complex are also inspected. On the third phase, the analyses’ results will provide information regarding the issues, positive trends and significant historical features of the complex’s architecture in order to generate suitable proposals for the redesigning project of Nguyen Cong Tru KTT, a design focused on vitalizing modern apartments’ communities.

Keywords: collective house community, collective house public space, community-focused, redesigning Nguyen Cong Tru KTT, sociological investigation

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Authors: Emeshaw Damtew Zebene, Edom Seife, Hagos Tesfay, Gurja Belay

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Background: cancer incidence and mortality has grown rapidly throughout the world. Aging of the population, urbanization, physical inactivity, economic growth followed by smoking and drinking contributed a lot for the increased incidence of cancer all over the globe. Objective: the aim of this study was to assess a one-year trend of cancer patients who underwent curative/radical radiotherapy at radiotherapy center, Tikur Anbessa specialized hospital, Ethiopia. Methodology: We performed a prospective descriptive study of cancer patients treated with LINAC at Tikur Anbessa specialized hospital, Addis Ababa, Ethiopia, from April 2021- March 2022. A standardized questionnaire was used to collect sociodemographic and clinical characteristics of the patients. Descriptive statistics and chi-square results were generated using SPSS version 24. The level of significance was obtained at 0.05. Results: Sixty-four (64) curative/radical patients-44 females and 20 males were analyzed. Majority, 27(42.2%), of the patients age range from 45 to 64, and 45(70%) of them were urban residents where a group of higher gynecologic cancer was observed.78% of the patients were with locally advanced cancer, and 54(84.4%) of them had no awareness about cancer. Generally, head & neck cancer were found the most prevalent cancer 20(31.3%), and the leading cause of cancer among women was cervical cancer 17(38.6%), where about half 7(15.9%) of them were HIV positive. Conclusion: Our finding revealed that most of curative/radical patients presented at a locally advanced stage of the disease. Hence, maintaining the already available teletherapy machines and installing additional radiotherapy centers may help in treating the patients at the early stage of the disease. Since almost all of our study participants did not have information about cancer, awareness raising mechanisms should be done. Additionally, understanding differences in cancer incidence between urban and rural is important. Key words: Cancer, Curative/radical, Radiotherapy, Tikur Anbessa Specialized Hospital

Keywords: cancer, curative/radical, radiotherapy, tkur anbessa specialized hospital

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Authors: Abdur Raheem, Ado Yakub

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Urban violence in the form of ethnic and religious conflicts have been on the increase in many African cities in the recent years of which most of them are the result of intense and bitter competition for political power, the control of limited economic, social and environmental resources. In Nigeria, the emergence of the Boko Haram insurgency in most parts of the north eastern parts have ignited violence, bloodshed, refuge exodus and internal migration. Not only do the persistent attacks of the sect create widespread insecurity and fear, it has also stifled normal processes of trade and investments most especially real property investment which is acclaimed to accelerate the economic cycle, thus the need to evolve strategies for an improved property market in such areas. This paper, therefore, examines the impact of these social crisis on effective and efficient utilization of real properties as a resource towards the development of the economy, using a descriptive analysis approach where particular emphasis was based on trends in residential housing values; volume of estimated property transactions and real estate investment decisions by affected individuals. Findings indicate that social crisis in the affected areas have been a clog on the wheels of property development and investment as properties worth hundreds of millions have been destroyed thereby having great impact on property values. Based on these findings, recommendations were made to include the need to strategically continue investing in property during such times, the need for Nigerian government to establish an active conflict monitoring and management unit for prompt response, encourage community and neighbourhood policing to ameliorate security challenges in Nigeria.

Keywords: social crisis, property market, economy, resources, north-eastern Nigeria

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Authors: Damian Czubak

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The Białowieża Forest is a very valuable natural area, included in the World Natural Heritage at UNESCO, where, due to infestation by the bark beetle (Ips typographus), norway spruce (Picea abies) have deteriorated. This catastrophic scenario led to an increase in fire danger. This was due to the occurrence of large amounts of dead wood and grass cover, as light penetrated to the bottom of the stands. These factors in a dry state are materials that favour the possibility of fire and the rapid spread of fire. One of the objectives of the study was to monitor the quantitative and qualitative changes of combustible material on the permanent decay plots of spruce stands from 2012-2022. In addition, the size of the area with highly flammable vegetation was monitored and a classification of the stands of the Białowieża Forest by flammability classes was made. The key factor that determines the potential fire hazard of a forest is combustible material. Primarily its type, quantity, moisture content, size and spatial structure. Based on the inventory data on the areas of forest districts in the Białowieża Forest, the average fire load and its changes over the years were calculated. The analysis was carried out taking into account the changes in the health status of the stands and sanitary operations. The quantitative and qualitative assessment of fallen timber and fire load of ground cover used the results of the 2019 and 2021 inventories. Approximately 9,000 circular plots were used for the study. An assessment was made of the amount of potential fuel, understood as ground cover vegetation and dead wood debris. In addition, monitoring of areas with vegetation that poses a high fire risk was conducted using data from 2019 and 2021. All sub-areas were inventoried where vegetation posing a specific fire hazard represented at least 10% of the area with species characteristic of that cover. In addition to the size of the area with fire-prone vegetation, a very important element is the size of the fire load on the indicated plots. On representative plots, the biomass of the land cover was measured on an area of 10 m2 and then the amount of biomass of each component was determined. The resulting element of variability of ground covers in stands was their flammability classification. The classification developed made it possible to track changes in the flammability classes of stands over the period covered by the measurements.

Keywords: classification, combustible material, flammable vegetation, Norway spruce

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Authors: Minu Bharati, Priyanka Rai, Satarupa Dutta, Dhiraj Saha

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Culex quinquefasciatus Say, is a mosquito of immense public health concern due to its role in transmission of filariasis, which is an endemic disease in 20 states and union territories of India, putting about 600 million people at the risk of infection. The main strategies to control filaria in India include anti-larval measures in urban areas, Indoor Residual Spray (IRS) in rural areas and mass diethylcarbamazine citrate (DEC) administration. Larval destruction measures and IRS are done with the use of insecticides. In this study, Susceptibility/ Resistance to insecticides were assessed in Culex quinquefasciatus mosquitoes collected from eight densely populated areas of Siliguri subdivision, which has a high rate of filarial infection. To unveil the insecticide susceptibility status of Culex quinquefasciatus, bioassays were performed on field-caught mosquitoes against two major groups of insecticides, i.e. Synthetic Pyrethroids (SPs): 0.05% deltamethrin and 0.05% lambda-cyhalothrin and Organophosphates (OPs): 5% malathion and temephos using World Health Organisation (WHO) discriminating doses. The knockdown rates and knockdown times (KDT50) were also noted against deltamethrin, lambda-cyhalothrin and malathion. Also, activities of major detoxifying enzymes, i.e. α-carboxylesterases, β-carboxylesterases and cytochrome P450 (CYP450) monooxygenases were determined to find the involvement of biochemical mechanisms in resistance phenomenon (if any). The results obtained showed that, majority of the mosquito populations were moderately to severely resistant against both the SPs and one OP, i.e. temephos. Whereas, most of the populations showed 100% susceptibility to malathion. The knockdown rates and KDT50 in response to above-mentioned insecticides showed significant variation among different populations. Variability in activities of carboxylesterases and CYP450 monooxygenases were also observed with hints of their involvement in contribution towards insecticide resistance in some of the tested populations. It may be concluded that, Culex quinquefasciatus has started developing resistance against deltamethrin, lambda-cyhalothrin and temephos in Siliguri subdivision. Malathion seems to hold the greatest potentiality for control of these mosquitoes in this area as revealed through this study. Adoption of Integrated mosquito management (IMM) strategy should be the prime objective of the concerned authorities to delimit the insecticide resistance phenomenon and filariasis infections.

Keywords: Culex quinquefasciatus, detoxifying enzymes, insecticide resistance, knockdown rate

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Authors: Tuba Senel Zor, Oktay Aslan

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With current trends in nanoscience and nanotechnology (NST), scientists have paid much attention to education and nanoliteracy in parallel with the developments on these fields. To understand the advances in NST research requires a population with a high degree of science literacy. All citizens should soon need nanoliteracy in order to navigate some of the important science-based issues faced to their everyday lives. While the fields of NST are advancing rapidly and raising their societal significance, general public’s awareness of these fields has remained at a low level. Moreover, students enrolled different education levels and teachers don’t have awareness at expected level. This problem may be stemmed from inadequate education and training. To remove the inadequacy, teachers have greatest duties and responsibilities. Especially science teachers at all levels need to be made aware of these developments and adequately prepared so that they are able to teach about these advances in a developmentally appropriate manner. If the teachers develop understanding and awareness of NST, they can also discuss the topic with their students. Therefore, the awareness and conceptual understandings of both the teachers who will teach science to students and the students who will be introduced about NST should be increased, and the necessary training should be provided. The aim of this study was to examine the effect of NST education on preservice science teachers’ awareness of NST. The study was designed in one group pre-test post-test quasi-experimental pattern. The study was conducted with 32 preservice science teachers attending the Elementary Science Education Program at a large Turkish university in central Anatolia. NST education was given during five weeks as two hours per week. Nanoscience and Nanotechnology Awareness Questionnaire was used as data collected tool and was implemented for pre-test and post-test. The collected data were analyzed using Statistical package for the Social Science (SPSS). The results of data analysis showed that there was a significant difference (z=6.25, p< .05) on NST awareness of preservice science teachers after implemented NST education. The results of the study indicate that NST education has an important effect for improving awareness of preservice science teachers on NST.

Keywords: awareness level, nanoliteracy, nanoscience and nanotechnology education, preservice science teachers

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Authors: Sani AbdulRahman Bala

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This empirical study delves into the realm of forensic accounting practices within the Nigerian Public Sector, seeking to quantitatively analyze their efficacy in addressing the persistent challenges of fraud and financial irregularities. With a focus on empirical data, this research employs a robust methodology to assess the current state of fraud in the Nigerian Public Sector and evaluate the performance of existing forensic accounting measures. Through quantitative analyses, including statistical models and data-driven insights, the study aims to identify patterns, trends, and correlations associated with fraudulent activities. The research objectives include scrutinizing documented fraud cases, examining the effectiveness of established forensic accounting practices, and proposing data-driven strategies for enhancing fraud detection and prevention. Leveraging quantitative methodologies, the study seeks to measure the impact of technological advancements on forensic accounting accuracy and efficiency. Additionally, the research explores collaborative mechanisms among government agencies, regulatory bodies, and the private sector by quantifying the effects of information sharing on fraud prevention. The empirical findings from this study are expected to provide a nuanced understanding of the challenges and opportunities in combating fraud within the Nigerian Public Sector. The quantitative insights derived from real-world data will contribute to the refinement of forensic accounting strategies, ensuring their effectiveness in addressing the unique complexities of financial irregularities in the public sector. The study's outcomes aim to inform policymakers, practitioners, and stakeholders, fostering evidence-based decision-making and proactive measures for a more resilient and fraud-resistant financial governance system in Nigeria.

Keywords: fraud, financial irregularities, nigerian public sector, quantitative investigation

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Authors: Chloé Kernaléguen, Laura Kundun, Tessie Lery, Ryan Laleg, Zhangyun Tan

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This study explores global disparities in respiratory syncytial virus (RSV) bronchiolitis incidence among children aged 0-2 years, focusing on the human development index (HDI) as a key determinant. RSV bronchiolitis poses a significant health risk to young children, influenced by factors, including socio-economic conditions captured by the HDI. Through a comprehensive systematic review and dataset selection (Switzerland, Brazil, United States of America), we formulated an HDI-SEIRS numerical model within the SEIRS framework. Results show variations in RSV bronchiolitis dynamics across countries, emphasizing the influence of HDI. Modelling reveals a correlation between higher HDI and increased bronchiolitis spread, notably in the USA and Switzerland. The ratios HDIcountry over HDImax strengthen this association, while climate disparities contribute to variations, especially in colder climates like the USA and Switzerland. The study raises the hypothesis of an indirect link between higher HDI and more frequent bronchiolitis, underlining the need for nuanced understanding. Factors like improved healthcare access, population density, mobility, and social behaviors in higher HDI countries might contribute to unexpected trends. Limitations include dataset quality and restricted RSV bronchiolitis data. Future research should encompass diverse HDI datasets to refine HDI's role in bronchiolitis dynamics. In conclusion, HDI-SEIRS models offer insights into factors influencing RSV bronchiolitis spread. While HDI is a significant indicator, its impact is indirect, necessitating a holistic approach to effective public health policies. This analysis sets the stage for further investigations into multifaceted interactions shaping bronchiolitis dynamics in diverse socio-economic contexts.

Keywords: bronchiolitis propagation, HDI influence, respiratory syncytial virus, SEIRS model

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Authors: Tamar Trop, Michal Roffeh

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One of the emerging trends in construction is installing an exterior “green wall” (GW). GW is an overarching and most common term for various techniques of incorporating greenery into buildings’ vertical elements, mainly facades. This green infrastructure yields numerous benefits for the urban environment, the public, and the buildings’ tenants and users, such as enhancing air quality and biodiversity, managing stormwater runoff, mitigating urban heat island and climate change, improving urban aesthetics and mental wellbeing, improving indoor comfort conditions, and saving energy. Yet, the penetration rate of GWs into the construction market, especially into the housing sector, is still very slow. Furthermore, the research regarding prospective homebuyers’ willingness to purchase and pay a price premium for GW apartments is scarce and does not refer to newly built buildings and specific GW types. This research aims to narrow these knowledge gaps by exploring the willingness of prospective homebuyers in Israel to purchase a newly built apartment with a hydroponic living wall, the size of the PP that they would be willing to pay for it, and the various factors ̶ knowledge-related, concern, economic, and personal ̶ that influence these motivations. A nationwide online survey was conducted among a sample of 514 adults using a structured questionnaire. Findings show that despite low familiarity with GWs and strong concerns about various kinds of nuisance, technical issues, and maintenance costs, potential homebuyers express a relatively high willingness to purchase and pay a significant price premium for such an apartment. The main motivations behind this willingness were found to be potential energy savings and governmental incentives. Study findings can contribute to a better understanding of the maturity of the housing market in Israel to adopt GWs and to better tailor intervention tools for increasing GWs’ uptake among potential homebuyers.

Keywords: green façade, green wall, living wall, willingness to pay

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Authors: Wiesława Klimek-Piotrowska, Mateusz K. Hołda, Mateusz Koziej, Katarzyna Piątek, Jakub Hołda

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Introduction: The coronary sinus venous system (CSVS), which has always been overshadowed by the coronary arterial tree, has recently begun to attract more attention. Since it is a target for clinicians the knowledge of its anatomy is essential. Cardiac resynchronization therapy, catheter ablation of cardiac arrhythmias, defibrillation, perfusion therapy, mitral valve annuloplasty, targeted drug delivery, and retrograde cardioplegia administration are commonly used therapeutic methods involving the CSVS. The great variability in the course of coronary veins and tributaries makes the diagnostic and therapeutic processes difficult. Our aim was to investigate detailed anatomy of most common clinically used CSVS`s structures: the coronary sinus with its ostium, great cardiac vein, posterior vein of the left ventricle, middle cardiac vein and oblique vein of the left atrium. Methodology: This is a prospective study of 70 randomly selected autopsied hearts dissected from adult humans (Caucasian) aged 50.1±17.6 years old (24.3% females) with BMI=27.6±6.7 kg/m2. The morphology of the CSVS was assessed as well as its precise measurements were performed. Results: The coronary sinus (CS) with its ostium was present in all hearts. The mean CS ostium diameter was 9.9±2.5mm. Considered ostium was covered by its valve in 87.1% with mean valve height amounted 5.1±3.1mm. The mean percentage coverage of the CS ostium by the valve was 56%. The Vieussens valve was present in 71.4% and was unicuspid in 70%, bicuspid in 26% and tricuspid in 4% of hearts. The great cardiac vein was present in all cases. The oblique vein of the left atrium was observed in 84.3% of hearts with mean length amounted 20.2±9.3mm and mean ostium diameter 1.4±0.9mm. The average length of the CS (from the CS ostium to the Vieussens valve) was 31.1±9.5mm or (from the CS ostium to the ostium of the oblique vein of the left atrium) 28.9±10.1mm and both were correlated with the heart weight (r=0.47; p=0.00 and r=0.38; p=0.006 respectively). In 90.5% the ostium of the oblique vein of the left atrium was located proximally to the Vieussens valve, in remaining cases was distally. The middle cardiac vein was present in all hearts and its valve was noticed in more than half of all the cases (52.9%). The posterior vein of the left ventricle was observed in 91.4% of cases. Conclusions: The CSVS is vastly variable and none of basic hearts parameters is a good predictor of its morphology. The Vieussens valve could be a significant obstacle during CS cannulation. Caution should be exercised in this area to avoid coronary sinus perforation. Because of the higher incidence of the presence of the oblique vein of the left atrium than the Vieussens valve, the vein orifice is more useful in determining the CS length.

Keywords: cardiac resynchronization therapy, coronary sinus, Thebesian valve, Vieussens valve

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Authors: Mary Ann L. Halliday, Zoengpari Gohain

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The stigma associated with HIV-AIDS negatively affect mental health and ability to effectively manage the disease. While the number of People living with HIV/AIDS (PLHIV) has been increasing day by day in Mizoram (a small north-eastern state in India), research on HIV/AIDS stigma has so far been limited. Despite the potential significance of Internalized HIV Stigma (IHS) in the lives of PLHIV, there has been very limited research in this area. It was therefore, felt necessary to explore the internalized HIV stigma, mental health, coping and perceived social support of PLHIV in Aizawl District, Mizoram. The present study was designed with the objectives to determine the degree of IHS, to study the relationship between the socio-demographic characteristics and level of IHS, to highlight the mental health status, coping strategies and perceived social support of PLHIV and to elucidate the relationship between these psychosocial variables. In order to achieve the objectives of the study, six hypotheses were formulated and statistical analyses conducted accordingly. The sample consisted of 300 PLWHA from Aizawl District, 150 males and 150 females, of the age group 20 to 70 years. Two- way classification of “Gender” (male and female) and three-way classification of “Level of IHS” (High IHS, Moderate IHS, Low IHS) on the dependent variables was employed, to elucidate the relationship between Internalized HIV Stigma, mental health, coping and perceived social support of PLHIV. The overall analysis revealed moderate level of IHS (67.3%) among PLHIV in Aizawl District, with a small proportion of subjects reporting high level of IHS. IHS was found to be significantly different on the basis of disclosure status, with the disclosure status of PLHIV accounting for 9% variability in IHS.  Results also revealed more or less good mental health among the participants, which was assessed by minimal depression (50.3%) and minimal anxiety (45%), with females with high IHS scoring significantly higher in both depression and anxiety (p<.01). Examination of the coping strategies of PLHIV found that the most frequently used coping styles were Acceptance (91%), Religion (84.3%), Planning (74.7%), Active Coping (66%) and Emotional Support (52.7%). High perception of perceived social support (48%) was found in the present study. Correlation analysis revealed significant positive relationships between IHS and depression as well as anxiety (p<.01), thus revealing that IHS negatively affects the mental health of PLHIV. Results however revealed that this effect may be lessened by the use of various coping strategies by PLHIV as well as their perception of social support.

Keywords: Aizawl, anxiety, depression, internalized HIV stigma, HIV/AIDS, mental health, mizoram, perceived social support

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Authors: Mustapha Babatunde, Bassam Tawabini, Ole John Nielson

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Air dispersion (AD) models such as AERMOD are important tools for estimating the environmental impacts of air pollutant emissions into the atmosphere from anthropogenic sources. The outcome of these models is significantly linked to the climate condition like air temperature, which is expected to differ in the future due to the global warming phenomenon. With projections from scientific sources of impending changes to the future climate of Saudi Arabia, especially anticipated temperature rise, there is a potential direct impact on the dispersion patterns of air pollutants results from AD models. To our knowledge, no similar studies were carried out in Saudi Arabia to investigate such impact. Therefore, this research investigates the effects of climate temperature change on air quality in the Dammam Metropolitan area, Saudi Arabia, using AERMOD coupled with Station data using Sulphur dioxide (SO₂) – as a model air pollutant. The research uses AERMOD model to predict the SO₂ dispersion trends in the surrounding area. Emissions from five (5) industrial stacks on twenty-eight (28) receptors in the study area were considered for the climate period (2010-2019) and future period of mid-century (2040-2060) under different scenarios of elevated temperature profiles (+1ᵒC, + 3ᵒC and + 5ᵒC) across averaging time periods of 1hr, 4hr and 8hr. Results showed that levels of SO₂ at the receiving sites under current and simulated future climactic condition fall within the allowable limit of WHO and KSA air quality standards. Results also revealed that the projected rise in temperature would only have mild increment on the SO₂ concentration levels. The average increase of SO₂ levels was 0.04%, 0.14%, and 0.23% due to the temperature increase of 1, 3, and 5 degrees, respectively. In conclusion, the outcome of this work elucidates the degree of the effects of global warming and climate changes phenomena on air quality and can help the policymakers in their decision-making, given the significant health challenges associated with ambient air pollution in Saudi Arabia.

Keywords: air quality, sulfur dioxide, dispersion models, global warming, KSA

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Authors: Imed Feki, Faouzi Msahli

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Selection of relevant parameters from a high dimensional process operation setting space is a problem frequently encountered in industrial process modelling. This paper presents a method for selecting the most relevant fabric physical parameters for each sensory quality feature. The proposed relevancy criterion has been developed using two approaches. The first utilizes a fuzzy sensitivity criterion by exploiting from experimental data the relationship between physical parameters and all the sensory quality features for each evaluator. Next an OWA aggregation procedure is applied to aggregate the ranking lists provided by different evaluators. In the second approach, another panel of experts provides their ranking lists of physical features according to their professional knowledge. Also by applying OWA and a fuzzy aggregation model, the data sensitivity-based ranking list and the knowledge-based ranking list are combined using our proposed percolation technique, to determine the final ranking list. The key issue of the proposed percolation technique is to filter automatically and objectively the relevant features by creating a gap between scores of relevant and irrelevant parameters. It permits to automatically generate threshold that can effectively reduce human subjectivity and arbitrariness when manually choosing thresholds. For a specific sensory descriptor, the threshold is defined systematically by iteratively aggregating (n times) the ranking lists generated by OWA and fuzzy models, according to a specific algorithm. Having applied the percolation technique on a real example, of a well known finished textile product especially the stonewashed denims, usually considered as the most important quality criteria in jeans’ evaluation, we separate the relevant physical features from irrelevant ones for each sensory descriptor. The originality and performance of the proposed relevant feature selection method can be shown by the variability in the number of physical features in the set of selected relevant parameters. Instead of selecting identical numbers of features with a predefined threshold, the proposed method can be adapted to the specific natures of the complex relations between sensory descriptors and physical features, in order to propose lists of relevant features of different sizes for different descriptors. In order to obtain more reliable results for selection of relevant physical features, the percolation technique has been applied for combining the fuzzy global relevancy and OWA global relevancy criteria in order to clearly distinguish scores of the relevant physical features from those of irrelevant ones.

Keywords: data sensitivity, feature selection, fuzzy logic, OWA operators, percolation technique

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Authors: Evren Ozgur, Kasim Kocak

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As a result of global warming and climate change, air temperature has increased and will continue to increase in the future. Increases in air temperatures have effects on a large number of variables in meteorology. One of the most important effects is the changes in the types of precipitation, especially in mid-latitudes. Because of increasing air temperatures, less snowfall was observed in the eastern parts of Turkey. Snowfall provides most of the water supply in spring and summer months, especially in mountainous regions of Turkey. When the temperature begins to increase in spring season, this snow starts to melt and plays an important role in agricultural purposes, drinking water supply and energy production. On the other hand, defining the snow season is very crucial especially in mountainous areas which have winter tourism opportunities. A reduction in the length of the snow season (LSS) in these regions will result in serious consequences in the long run. In the study, snow season was examined for 10 meteorological stations that are located above the altitude of 1000m. These stations have decreasing trends in the ratio of number of snowy days to total precipitation days considering earlier studies. Daily precipitation records with the observation period of 1971-2011 were used in the study. Then, the observation period was separated into 4 non-overlapping parts in order to identify decadal variations. Changes in the length of the snow season with increasing temperatures were obtained for these stations. The results of LSS were evaluated with the number of snowy days for each station. All stations have decreasing trend in number of snowy days for 1971-2011 period. In addition, seven of the results are statistically significant. Besides, decrease is observed regarding the length of snow season for studied stations. The decrease varies between 6.6 and 47.6 days according to decadal snow season averages of the stations.

Keywords: climate change, global warming, precipitation, snowfall, Turkey

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Authors: Zavkiddin Mirtoshev, Mirabbos Mirkamalov

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We have analyzed the time series of full disk integrated soft X-ray (SXR) and hard X-ray (HXR) emission from the solar corona during 2004 January 1 to 2009 December 31, covering the descending phase of solar cycle 23. We employed the daily X-ray index (DXI) derived from X-ray observations from the Solar X-ray Spectrometer (SOXS) mission in four different energy bands: 4-5.5; 5.5-7.5 keV (SXR) and 15-20; 20-25 keV (HXR). The application of Lomb-Scargle periodogram technique to the DXI time series observed by the Silicium detector in the energy bands reveals several short and intermediate periodicities of the X-ray corona. The DXI explicitly show the periods of 13.6 days, 26.7 days, 128.5 days, 151 days, 180 days, 220 days, 270 days, 1.24 year and 1.54 year periods in SXR as well as in HXR energy bands. Although all periods are above 70% confidence level in all energy bands, they show strong power in HXR emission in comparison to SXR emission. These periods are distinctly clear in three bands but somehow not unambiguously clear in 5.5-7.5 keV band. This might be due to the presence of Ferrum and Ferrum/Niccolum line features, which frequently vary with small scale flares like micro-flares. The regular 27-day rotation and 13.5 day period of sunspots from the invisible side of the Sun are found stronger in HXR band relative to SXR band. However, flare activity Rieger periods (150 and 180 days) and near Rieger period 220 days are very strong in HXR emission which is very much expected. On the other hand, our current study reveals strong 270 day periodicity in SXR emission which may be connected with tachocline, similar to a fundamental rotation period of the Sun. The 1.24 year and 1.54 year periodicities, represented from the present research work, are well observable in both SXR as well as in HXR channels. These long-term periodicities must also have connection with tachocline and should be regarded as a consequence of variation in rotational modulation over long time scales. The 1.24 year and 1.54 year periods are also found great importance and significance in the life formation and it evolution on the Earth, and therefore they also have great astro-biological importance. We gratefully acknowledge support by the Indian Centre for Space Science and Technology Education in Asia and the Pacific (CSSTEAP, the Centre is affiliated to the United Nations), Physical Research Laboratory (PRL) at Ahmedabad, India. This work has done under the supervision of Prof. Rajmal Jain and paper consist materials of pilot project and research part of the M. Tech program which was made during Space and Atmospheric Science Course.

Keywords: corona, flares, solar activity, X-ray emission

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Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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Authors: Mustapha Babatunde, Bassam Tawabini, Ole John Nielson

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Air dispersion (AD) models such as AERMOD are important tools for estimating the environmental impacts of air pollutant emissions into the atmosphere from anthropogenic sources. The outcome of these models is significantly linked to the climate condition like air temperature, which is expected to differ in the future due to the global warming phenomenon. With projections from scientific sources of impending changes to the future climate of Saudi Arabia, especially anticipated temperature rise, there is a potential direct impact on the dispersion patterns of air pollutants results from AD models. To our knowledge, no similar studies were carried out in Saudi Arabia to investigate such impact. Therefore, this research investigates the effects of climate temperature change on air quality in the Dammam Metropolitan area, Saudi Arabia, using AERMOD coupled with Station data using Sulphur dioxide (SO2) – as a model air pollutant. The research uses AERMOD model to predict the SO2 dispersion trends on the surrounding area. Emissions from five (5) industrial stacks, on twenty-eight (28) receptors in the study area were considered for the climate period (2010-2019) and future period of mid-century (2040-2060) under different scenarios of elevated temperature profiles (+1oC, + 3oC and + 5oC) across averaging time periods of 1hr, 4hr and 8hr. Results showed that levels of SO2 at the receiving sites under current and simulated future climactic condition fall within the allowable limit of WHO and KSA air quality standards. Results also revealed that the projected rise in temperature would only have mild increment on the SO2 concentration levels. The average increase of SO2 levels were 0.04%, 0.14%, and 0.23% due to the temperature increase of 1, 3, and 5 degrees respectively. In conclusion, the outcome of this work elucidates the degree of the effects of global warming and climate changes phenomena on air quality and can help the policymakers in their decision-making, given the significant health challenges associated with ambient air pollution in Saudi Arabia.

Keywords: air quality, sulphur dioxide, global warming, air dispersion model

Procedia PDF Downloads 114

Authors: Junfeng Yan, Wenkui Hou

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Prognostics and Health Management (PHM) is a technology to monitor the equipment status and predict impending faults. It is used to predict the potential fault and provide fault information and track trends of system degradation by capturing characteristics signals. So how to detect characteristics signals is very important. The select of test point plays a very important role in detecting characteristics signal. Traditionally, we use dependency model to select the test point containing the most detecting information. But, facing the large complicated system, the dependency model is not built so easily sometimes and the greater trouble is how to calculate the matrix. Rely on this premise, the paper provide a highly effective method to select test point without dependency model. Because signal flow model is a diagnosis model based on failure mode, which focuses on system’s failure mode and the dependency relationship between the test points and faults. In the signal flow model, a fault information can flow from the beginning to the end. According to the signal flow model, we can find out location and structure information of every test point and module. We break the signal flow model up into serial and parallel parts to obtain the final relationship function between the system’s testability or prediction metrics and test points. Further, through the partial derivatives operation, we can obtain every test point’s importance degree in determining the testability metrics, such as undetected rate, false alarm rate, untrusted rate. This contributes to installing the test point according to the real requirement and also provides a solid foundation for the Prognostics and Health Management. According to the real effect of the practical engineering application, the method is very efficient.

Keywords: false alarm rate, importance degree, signal flow model, undetected rate, untrusted rate

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Authors: Fiona Curran-Cournane

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Soil quality monitoring is a science-based soil management tool that assesses soil ecosystem health. A soil monitoring program in Auckland, New Zealand’s largest city, extends from 1995 to the present. The objective of this study was to firstly determine changes in soil parameters (basic soil properties and heavy metals) that were assessed from rural land in 1995-2000 and repeated in 2008-2012. The second objective was to determine differences in soil parameters across various land uses including native bush, rural (horticulture, pasture and plantation forestry) and urban land uses using soil data collected in more recent years (2009-2013). Across rural land, mean concentrations of Olsen P had significantly increased in the second sampling period and was identified as the indicator of most concern, followed by soil macroporosity, particularly for horticultural and pastoral land. Mean concentrations of Cd were also greatest for pastoral and horticultural land and a positive correlation existed between these two parameters, which highlights the importance of analysing basic soil parameters in conjunction with heavy metals. In contrast, mean concentrations of As, Cr, Pb, Ni and Zn were greatest for urban sites. Native bush sites had the lowest concentrations of heavy metals and were used to calculate a ‘pollution index’ (PI). The mean PI was classified as high (PI > 3) for Cd and Ni and moderate for Pb, Zn, Cr, Cu, As, and Hg, indicating high levels of heavy metal pollution across both rural and urban soils. From a land use perspective, the mean ‘integrated pollution index’ was highest for urban sites at 2.9 followed by pasture, horticulture and plantation forests at 2.7, 2.6, and 0.9, respectively. It is recommended that soil sampling continues over time because a longer spanning record will allow further identification of where soil problems exist and where resources need to be targeted in the future. Findings from this study will also inform policy and science direction in regional councils.

Keywords: heavy metals, pollution index, rural and urban land use, soil quality

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Authors: Remus Pravalie, Georgeta Bandoc

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Forests are crucial for humanity and biodiversity, through the various ecosystem services and functions they provide all over the world. Forest ecosystems are vital in Romania as well, through their various benefits, known as provisioning (food, wood, or fresh water), regulating (water purification, soil protection, carbon sequestration or control of climate change, floods, and other hazards), cultural (aesthetic, spiritual, inspirational, recreational or educational benefits) and supporting (primary production, nutrient cycling, and soil formation processes, with direct or indirect importance for human well-being) ecosystem services. These ecological benefits are of great importance in Romania, especially given the fact that forests cover extensive areas countrywide, i.e. ~6.5 million ha or ~27.5% of the national territory. However, the diversity and functionality of these ecosystem services fundamentally depend on certain key attributes of forests, such as biomass, which has so far not been studied nationally in terms of potential changes due to climate change and other driving forces. This study investigates, for the first time, changes in forest biomass in Romania in recent decades, based on a high volume of satellite data (Landsat images at high spatial resolutions), downloaded from the Google Earth Engine platform and processed (using specialized software and methods) across Romanian forestland boundaries from 1987 to 2018. A complex climate database was also investigated across Romanian forests over the same 32-year period, in order to detect potential similarities and statistical relationships between the dynamics of biomass and climate data. The results obtained indicated considerable changes in forest biomass in Romania in recent decades, largely triggered by the climate change that affected the country after 1987. Findings on the complex pattern of recent forest changes in Romania, which will be presented in detail in this study, can be useful to national policymakers in the fields of forestry, climate, and sustainable development.

Keywords: forests, biomass, climate change, trends, romania

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Authors: Tamanna Rimi

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A large body of literature has discussed the determinants of migration decision. However, the potential role of individual risk attitudes on migration decision has so far been overlooked. The research on migration literature has studied how the expected income differential influences migration flows for a risk neutral individual. However, migration takes place when there is no expected income differential or even the variability of income appears as lower than in the current location. This migration puzzle motivates a recent trend in the literature that analyzes how attitudes towards risk influence the decision to migrate. However, the significance of risk attitudes on migration decision has been addressed mostly in a theoretical perspective in the mainstream migration literature. The efficient outcome of labor market and overall economy are largely influenced by migration in many countries. Therefore, attitudes towards risk as a determinant of migration should get more attention in empirical studies. To author’s best knowledge, this is the first study that has examined the relationship between relative risk aversion and migration decision in US market. This paper considers movement across United States as a means of migration. In addition, this paper also explores the network effect due to the increasing size of one’s own ethnic group to a source location on the migration decision and how attitudes towards risk vary with network effect. Two ethnic groups (i.e. Asian and Hispanic) have been considered in this regard. For the empirical estimation, this paper uses two sources of data: 1) U.S. census data for social, economic, and health research, 2010 (IPUMPS) and 2) University of Michigan Health and Retirement Study, 2010 (HRS). In order to measure relative risk aversion, this study uses the ‘Two Sample Two-Stage Instrumental Variable (TS2SIV)’ technique. This is a similar method of Angrist (1990) and Angrist and Kruegers’ (1992) ‘Two Sample Instrumental Variable (TSIV)’ technique. Using a probit model, the empirical investigation yields the following results: (i) risk attitude has a significantly large impact on migration decision where more risk averse people are less likely to migrate; (ii) the impact of risk attitude on migration varies by other demographic characteristics such as age and sex; (iii) people with higher concentration of same ethnic households living in a particular place are expected to migrate less from their current place; (iv) the risk attitudes on migration vary with network effect. The overall findings of this paper relating risk attitude, migration decision and network effect can be a significant contribution addressing the gap between migration theory and empirical study in migration literature.

Keywords: migration, network effect, risk attitude, U.S. market

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Authors: Chu-Tzu Chen, Angela S. Huang, Yu-Min Chou, Chin-Hui Yang

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Dengue is a major public health concern throughout tropical and sub-tropical regions. Taiwan is located in the Pacific Ocean and overlying the tropical and subtropical zones. The island remains humid throughout the year and receives abundant rainfall, and the temperature is very hot in summer at southern Taiwan. It is ideal for the growth of dengue vectors and would be increasing the risk on dengue outbreaks. During the first half of the 20th century, there were three island-wide dengue outbreaks (1915, 1931, and 1942). After almost forty years of dormancy, a DEN-2 outbreak occurred in Liuchiu Township, Pingtung County in 1981. Thereafter, more dengue outbreaks occurred with different scales in southern Taiwan. However, there were more than ten thousands of dengue cases in 2014 and in 2015. It did not only affect human health, but also caused widespread social disruption and economic losses. The study would like to reveal the epidemiology of dengue on Taiwan, especially the severe outbreak in 2015, and try to find the effective interventions in dengue control including dengue vaccine development for the elderly. Methods: The study applied the Notifiable Diseases Surveillance System database of the Taiwan Centers for Disease Control as data source. All cases were reported with the uniform case definition and confirmed by NS1 rapid diagnosis/laboratory diagnosis. Results: In 2014, Taiwan experienced a serious DEN-1 outbreak with 15,492 locally-acquired cases, including 136 cases of dengue hemorrhagic fever (DHF) which caused 21 deaths. However, a more serious DEN-2 outbreak occurred with 43,419 locally-acquired cases in 2015. The epidemic occurred mainly at Tainan City (22,760 cases) and Kaohsiung City (19,723 cases) in southern Taiwan. The age distribution for the cases were mainly adults. There were 228 deaths due to dengue infection, and the case fatality rate was 5.25 ‰. The average age of them was 73.66 years (range 29-96) and 86.84% of them were older than 60 years. Most of them were comorbidities. To review the clinical manifestations of the 228 death cases, 38.16% (N=87) of them were reported with warning signs, while 51.75% (N=118) were reported without warning signs. Among the 87 death cases reported to dengue with warning signs, 89.53% were diagnosed sever dengue and 84% needed the intensive care. Conclusion: The year 2015 was characterized by large dengue outbreaks worldwide. The risk of serious dengue outbreak may increase significantly in the future, and the elderly is the vulnerable group in Taiwan. However, a dengue vaccine has been licensed for use in people 9-45 years of age living in endemic settings at the end of 2015. In addition to carry out the research to find out new interventions in dengue control, developing the dengue vaccine for the elderly is very important to prevent severe dengue and deaths.

Keywords: case fatality rate, dengue, dengue vaccine, the elderly

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Authors: Spandan Sahu, Amiya Kumar Pati, Kishanjit Kumar Khatua

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Vegetation plays a major role in deciding the flow parameters in an open channel. It enhances the aesthetic view of the revetments. The major types of vegetation in river typically comprises of herbs, grasses, weeds, trees, etc. The vegetation in an open channel usually consists of aquatic plants with complete submergence, partial submergence, floating plants. The presence of vegetative plants can have both benefits and problems. The major benefits of aquatic plants are they reduce the soil erosion, which provides the water with a free surface to move on without hindrance. The obvious problems are they retard the flow of water and reduce the hydraulic capacity of the channel. The degree to which the flow parameters are affected depends upon the density of the vegetation, degree of submergence, pattern of vegetation, vegetation species. Vegetation in open channel tends to provide resistance to flow, which in turn provides a background to study the varying trends in flow parameters having vegetative growth in the channel surface. In this paper, an experiment has been conducted on a meandering channel having sinuosity of 1.33 with rigid vegetation cover to investigate the effect on flow parameters, variation of manning’s n with degree of the denseness of vegetation, vegetation pattern and submergence criteria. The measurements have been carried out in four different cross-sections two on trough portion of the meanders, two on the crest portion. In this study, the analytical solution of Shiono and knight (SKM) for lateral distributions of depth-averaged velocity and bed shear stress have been taken into account. Dimensionless eddy viscosity and bed friction have been incorporated to modify the SKM to provide more accurate results. A mathematical model has been formulated to have a comparative analysis with the results obtained from Shiono-Knight Method.

Keywords: bed friction, depth averaged velocity, eddy viscosity, SKM

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Authors: Akaash Tawade, Manan Khattar, Lucas Spangher, Costas J. Spanos

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Many grids are increasing the share of renewable energy in their generation mix, which is causing the energy generation to become less controllable. Buildings, which consume nearly 33% of all energy, are a key target for demand response: i.e., mechanisms for demand to meet supply. Understanding the behavior of office workers is a start towards developing demand response for one sector of building technology. The literature notes that dynamic computational modeling can be predictive of individual action, especially given that occupant behavior is traditionally abstracted from demand forecasting. Recent work founded on Social Cognitive Theory (SCT) has provided a promising conceptual basis for modeling behavior, personal states, and environment using control theoretic principles. Here, an adapted linear dynamical system of latent states and exogenous inputs is proposed to simulate energy demand amongst office workers engaged in a social energy shifting game. The energy shifting competition is implemented in an office in Singapore that is connected to a minigrid of buildings with a consistent 'price signal.' This signal is translated into a 'points signal' by a reinforcement learning (RL) algorithm to influence participant energy use. The dynamic model functions at the intersection of the points signals, baseline energy consumption trends, and SCT behavioral inputs to simulate future outcomes. This study endeavors to analyze how the dynamic model trains an RL agent and, subsequently, the degree of accuracy to which load deferability can be simulated. The results offer a generalizable behavioral model for energy competitions that provides the framework for further research on transfer learning for RL, and more broadly— transactive control.

Keywords: energy demand forecasting, social cognitive behavioral modeling, social game, transfer learning

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Authors: Ayodeji Oluleye

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This study used Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) and reanalysis dataset of thirty years (1983-2012) to investigate the influence of the atmospheric circulation on dust transport during the Harmattan period over WestAfrica using TOMS data. The Harmattan dust mobilization and atmospheric circulation pattern were evaluated using a kernel density estimate which shows the areas where most points are concentrated between the variables. The evolution of the Inter-Tropical Discontinuity (ITD), Sea surface Temperature (SST) over the Gulf of Guinea, and the North Atlantic Oscillation (NAO) index during the Harmattan period (November-March) was also analyzed and graphs of the average ITD positions, SST and the NAO were observed on daily basis. The Pearson moment correlation analysis was also employed to assess the effect of atmospheric circulation on Harmattan dust transport. The results show that the departure (increased) of TOMS AI values from the long-term mean (1.64) occurred from around 21st of December, which signifies the rich dust days during winter period. Strong TOMS AI signal were observed from January to March with the maximum occurring in the latter months (February and March). The inter-annual variability of TOMSAI revealed that the rich dust years were found between 1984-1985, 1987-1988, 1997-1998, 1999-2000, and 2002-2004. Significantly, poor dust year was found between 2005 and 2006 in all the periods. The study has found strong north-easterly (NE) trade winds were over most of the Sahelianregion of West Africa during the winter months with the maximum wind speed reaching 8.61m/s inJanuary.The strength of NE winds determines the extent of dust transport to the coast of Gulf of Guinea during winter. This study has confirmed that the presence of the Harmattan is strongly dependent on theSST over Atlantic Ocean and ITD position. The locus of the average SST and ITD positions over West Africa could be described by polynomial functions. The study concludes that the evolution of near surface wind field at 925 hpa, and the variations of SST and ITD positions are the major large scale atmospheric circulation systems driving the emission, distribution, and transport of Harmattan dust aerosols over West Africa. However, the influence of NAO was shown to have fewer significance effects on the Harmattan dust transport over the region.

Keywords: atmospheric circulation, dust aerosols, Harmattan, West Africa

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Authors: Joseph F. Cabrera, Rachael Dela Cruz

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This study specifically examines patterns that define ethnoracially diverse neighborhoods. Ethnoracial diversity is important as it facilitates cross-racial interactions within neighborhoods which have been theorized to be associated with such outcomes as intergroup harmony, the reduction of racial and ethnic prejudice and discrimination, and increases in racial tolerance. Los Angeles (LA) is an ideal location to study ethnoracial spatial patterns as it is one of the most ethnoracially diverse cities in the world. A large influx of Latinos, as well as Asians, have contributed to LA’s urban landscape becoming increasingly diverse over several decades. Our dataset contains all census tracts in Los Angeles County in 2016 and incorporates Census and ACS demographic and spatial data. We quantify ethnoracial diversity using a derivative of Simpson’s Diversity Index and utilize this measure to test previous literature that suggests Latinos are one of the key drivers of changing ethnoracial spatial patterns in Los Angeles. Preliminary results suggest that there has been an overall increase in ethnoracial diversity in Los Angeles neighborhoods over the past sixteen years. Patterns associated with this trend include decreases in predominantly white and black neighborhoods, increases in predominantly Latino and Asian neighborhoods, and a general decrease in the white populations of the most diverse neighborhoods. A similar pattern is seen in neighborhoods with large Latino increases- a decrease in white population, but with an increase in Asian and black populations. We also found support for previous research that suggests increases in Latino and Asian populations act as a buffer, allowing for black population increases without a sizeable decrease in the white population. Future research is needed to understand the underlying causes involved in many of the patterns and trends highlighted in this study.

Keywords: race, race and interaction, racial harmony, social interaction

Procedia PDF Downloads 116

Authors: Aminul Haque, Quazi Zahangir Hossain, Dilshad Sharmin Chowdhury

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The human migration is getting growing concern around the world, and recurrent disasters and climate change impact have great influence on migration. Bangladesh is one of the disaster prone countries that/and has greater susceptibility to stress migration by recurrent disasters and climate change. The study was conducted to investigate the factors that have a strong influence on current migration and changing pattern of life and livelihood means of the southwest coastal part of Bangladesh. Moreover, the study also revealed a strong relationship between disasters and migration and appropriate policy concern. To explore this relation, both qualitative and quantitative methods were applied to a questionnaire survey at household level and simple random sampling technique used in the sampling process along with different secondary data sources for understanding policy concern and practices. The study explores the most influential driver of migration and its relationship with social, economic and environmental drivers. The study denotes that, the environmental driver has a greater effect on the intention of permanent migration (t=1.481, p-value=0.000) at the 1 percent significance level. The significant number of respondents denotes that abrupt pattern of cyclone, flood, salinity intrusion and rainfall are the most significant environmental driver to make a decision on permanent migration. The study also found that the temporary migration pattern has 2-fold increased compared to last ten (10) years. It also appears from the study that environmental factors have a great implication on the changing pattern of the occupation of the study area and it has reported that about 76% of the respondent now in the changing modality of livelihood compare to their traditional practices. The study bares that the migration has foremost impact on children and women by increasing hardship and creating critical social security. The exposure-route of permanent migration is not smooth indeed, these migrations creating urban and conflict in Chittagong hill tracks of Bangladesh. The study denotes that there is not any safeguard of the stress migrant on existing policy and not have any measures for safe migration and resettlement rather considering the emergency response and shelter. The majority of (98%) people believes that migration is not to be the adoption strategies, but contrary to this young group of respondent believes that safe migration could be the adaptation strategy which could bring a positive result compare to the other resilience strategies. On the other hand, the significant number of respondents uttered that appropriate policy measure could be an adaptation strategy for being the formation of a resilient community and reduce the migration by meaningful livelihood options with appropriate protection measure.

Keywords: environmental driver, livelihood, migration, resilience

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Authors: Frances Bernard Kominkiewicz

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Demonstrating the ability to build social justice and peace is integral in undergraduate and graduate education. Many disciplines are involved in peace education and peace studies, and the collaboration of those disciplines are examined in this paper. To the author’s best knowledge, no content analysis research previously existed regarding peace studies and peace education from a multidisciplinarity, interdisciplinarity, and transdisciplinarity perspective. Peacebuilding is taught through these approaches, which adds to the depth, breadth, and richness of peace education and peace studies. This paper presents a content analysis of academic peace studies programs and course descriptions. Variables studied include contributions and foci of disciplines in peace studies programs and students’ engagement in community peacebuilding. The social work discipline, for example, focuses on social and economic justice as one of the nine competencies that undergraduate and graduate students must attain before earning a Bachelor of Social Work degree or a Master of Social Work degree and becoming social work practitioners. Demonstrating the ability to build social justice and peace is integral in social work education. Peacebuilding is taught through such social work courses as conflict resolution, and social work practice with communities and organizations, and these courses are examined in this research through multidisciplinarity, interdisciplinarity, and transdisciplinarity approach. Peace and social justice are linked terms in various fields, including social work. Social justice is of paramount importance in social work programs, and social workers are trained to advocate for human rights and social, economic, and environmental justice. Social workers use knowledge of oppression, globally as well as nationally, in the practice of peace education and peace studies. Social work is at the forefront in advocating for social justice as a discipline and joins with other educators in strengthening the peacebuilding opportunities for students. The content analysis, conducted through a random sample of peace studies and peace education university and college programs in the United States, found that although courses teach the concepts of peace education and peace studies, courses often are not given these titles in the social work discipline. Therefore, this analysis also includes a discussion of the multidisciplinarity, interdisciplinarity, and transdisciplinarity approach to peace education, peace studies, and peacebuilding and the importance of these approaches in educating students about peace. The content analysis further found great variability in the number of disciplines involved in peace studies programs, the focus of those disciplines in peace education, the placement of peace studies and peace education within the university or college, and the number of courses and concentrations available in peace studies and peace education. In conclusion, the research points toward very robust and diverse approaches to peace education with opportunities for further research and discussion.

Keywords: content analysis, interdisciplinarity, multidisciplinarity, peace education programs

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Authors: Akhila Potluru

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Worldwide, more than 250 bodies of water are transboundary, meaning they cross the political boundaries of multiple countries. This creates a system of hydrological, economic, and social interdependence between communities reliant on these water sources. Transboundary water conflicts can occur as a result of this intense interdependence. Many factors contribute to the sparking of transboundary water conflicts, ranging from natural hydrological factors to hydro-political interactions. Previous attempts to predict transboundary water conflicts by analysing changes or trends in the contributing factors have typically failed because patterns in the data are hard to identify. However, there is potential for artificial intelligence and machine learning to fill this gap and identify future ‘hotspots’ up to a year in advance by identifying patterns in data where humans can’t. This research determines the extent to which AI can be used to predict and prevent transboundary water conflicts. This is done via a critical literature review of previous case studies and datasets where AI was deployed to predict water conflict. This research not only delivered a more nuanced understanding of previously undervalued factors that contribute toward transboundary water conflicts (in particular, culture and disinformation) but also by detecting conflict early, governance bodies can engage in processes to de-escalate conflict by providing pre-emptive solutions. Looking forward, this gives rise to significant policy implications and water-sharing agreements, which may be able to prevent water conflicts from developing into wide-scale disasters. Additionally, AI can be used to gain a fuller picture of water-based conflicts in areas where security concerns mean it is not possible to have staff on the ground. Therefore, AI enhances not only the depth of our knowledge about transboundary water conflicts but also the breadth of our knowledge. With demand for water constantly growing, competition between countries over shared water will increasingly lead to water conflict. There has never been a more significant time for us to be able to accurately predict and take precautions to prevent global water conflicts.

Keywords: artificial intelligence, machine learning, transboundary water conflict, water management

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Authors: Cody Stolle, Mojdeh Asadollahipajouh, Khaleb Pafford, Jada Iwuoha, Samantha White, Becky Mueller

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Battery-electric vehicles (BEVs) are growing in sales and popularity in the United States as an alternative to traditional internal combustion engine vehicles (ICEVs). BEVs are generally heavier than corresponding models of ICEVs, with large battery packs located beneath the vehicle floorpan, a “skateboard” chassis, and have front and rear crush space available in the trunk and “frunk” or front trunk. The geometrical and frame differences between the vehicles may lead to incompatibilities with gasoline vehicles during vehicle-to-vehicle crashes as well as run-off-road crashes with roadside barriers, which were designed to handle lighter ICEVs with higher centers-of-mass and with dedicated structural chasses. Crash data were collected from 10 states spanning a five-year period between 2017 and 2021. Vehicle Identification Number (VIN) codes were processed with the National Highway Traffic Safety Administration (NHTSA) VIN decoder to extract BEV models from ICEV models. Crashes were filtered to isolate only vehicles produced between 2010 and 2021, and the crash circumstances (weather, time of day, maximum injury) were compared between BEVs and ICEVs. In Washington, 436,613 crashes were identified, which satisfied the selection criteria, and 3,371 of these crashes (0.77%) involved a BEV. The number of crashes which noted a fire were comparable between BEVs and ICEVs of similar model years (0.3% and 0.33%, respectively), and no differences were discernable for the time of day, weather conditions, road geometry, or other prevailing factors (e.g., run-off-road). However, crashes involving BEVs rose rapidly; 31% of all BEV crashes occurred in just 2021. Results indicate that BEVs are performing comparably to ICEVs, and events surrounding BEV crashes are statistically indistinguishable from ICEV crashes.

Keywords: battery-electric vehicles, transportation safety, infrastructure crashworthiness, run-off-road crashes, ev crash data analysis

Procedia PDF Downloads 68