Search results for: climate change risk

Authors: Varsha Rainson

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Artificial intelligence (AI) has great potential and can be used as a powerful tool of application in various domains and sectors. But with the application of AI, there comes a wide spectrum of concerns around bias, accountability, transparency, and privacy. Hence, there is a need for responsible AI, which can uphold ethical and accountable practices to ensure that things are transparent and fair. The paper is a combination of AI and cultural heritage preservation, with a greater focus on India because of the rich cultural legacy that it holds. India’s cultural heritage in itself contributes to its identity and the economy. In this paper, along with discussing the impact culture holds on the Indian economy, we will discuss the threats that the cultural heritage is exposed to due to pollution, climate change and urbanization. Furthermore, the paper reviews some of the exciting applications of AI in cultural heritage preservation, such as 3-D scanning, photogrammetry, and other techniques which have led to the reconstruction of cultural artifacts and sites. The paper eventually moves into the potential risks and challenges that AI poses in cultural heritage preservation. These include ethical, legal, and social issues which are to be addressed by organizations and government authorities. Overall, the paper strongly argues the need for responsible AI and the important role it can play in preserving India’s cultural heritage while holding importance to value and diversity.

Keywords: responsible AI, cultural heritage, artificial intelligence, biases, transparency

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Authors: Dinebari Akpee, Friday Aabe Gaage, Florence Fred Nwaigwu

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Natural disasters like flood affect many parts of the world including developing countries like Nigeria. As a result, many human lives are lost, properties damaged and so much money is lost in infrastructure damages. These hazards and losses can be mitigated and reduced by providing reliable spatial information to the generality of the people through about flood risks through flood inundation maps. Flood inundation maps are very crucial for emergency action plans, urban planning, ecological studies and insurance rates. Nigeria experience her worst flood in her entire history this year. Many cities were submerged and completely under water due to torrential rainfall. Poor city planning, lack of effective development control among others contributes to the problem too. Geographic information system (GIS) can be used to visualize the extent of flooding, analyze flood maps to produce flood damaged estimation maps and flood risk maps. In this research, the under listed steps were taken in preparation of flood risk maps for the study area: (1) Digitization of topographic data and preparation of digital elevation model using ArcGIS (2) Flood simulation using hydraulic model and integration and (3) Integration of the first two steps to produce flood risk maps. The results shows that GIS can play crucial role in Flood disaster control and mitigation.

Keywords: flood disaster, risk maps, geographic information system, hazards

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Authors: Yilin Liao, Hewen Li, Paula McConvey

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Speed skaters often face a risk of concussion when they fall on the ice floor and impact crash mats during practices and competitive races. Several variables, including those related to the skater, the crash mat, and the impact position (body side/head/feet impact), are believed to influence the severity of the skater's concussion. While computer simulation modeling can be employed to analyze these accidents, the simulation process is time-consuming and does not provide rapid information for coaches and teams to assess the skater's injury risk in competitive events. This research paper promotes the exploration of the feasibility of using AI techniques for evaluating skater’s potential concussion severity, and to develop a fast concussion prediction tool using artificial neural networks to reduce the risk of treatment delays for injured skaters. The primary data is collected through virtual tests and physical experiments designed to simulate skater-mat impact. It is then analyzed to identify patterns and correlations; finally, it is used to train and fine-tune the artificial neural networks for accurate prediction. The development of the prediction tool by employing machine learning strategies contributes to the application of AI methods in sports science and has theoretical involvements for using AI techniques in predicting and preventing sports-related injuries.

Keywords: artificial neural networks, concussion, machine learning, impact, speed skater

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Authors: Juan A. Arzate, Funda C. Ertem, M. Nicolas Cruz-Bournazou, Peter Neubauer, Stefan Junne

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— One of the biggest challenges the world faces today is global warming that is caused by greenhouse gases (GHGs) coming from the combustion of fossil fuels for energy generation. In order to mitigate climate change, the European Union has committed to reducing GHG emissions to 80–95% below the level of the 1990s by the year 2050. Renewable technologies are vital to diminish energy-related GHG emissions. Since water and biomass are limited resources, the largest contributions to renewable energy (RE) systems will have to come from wind and solar power. Nevertheless, high proportions of fluctuating RE will present a number of challenges, especially regarding the need to balance the variable energy demand with the weather dependent fluctuation of energy supply. Therefore, biogas plants in this content would play an important role, since they are easily adaptable. Feedstock availability varies locally or seasonally; however there is a lack of knowledge in how biogas plants should be operated in a stable manner by local feedstock. This problem may be prevented through suitable control strategies. Such strategies require the development of convenient mathematical models, which fairly describe the main processes. Modelling allows us to predict the system behavior of biogas plants when different feedstocks are used with different loading rates. Life cycle assessment (LCA) is a technique for analyzing several sides from evolution of a product till its disposal in an environmental point of view. It is highly recommend to use as a decision making tool. In order to achieve suitable strategies, the combination of a flexible energy generation provided by biogas plants, a secure production process and the maximization of the environmental benefits can be obtained by the combination of process modelling and LCA approaches. For this reason, this study focuses on the biogas plant which flexibly generates required energy from the co-digestion of maize, grass and cattle manure, while emitting the lowest amount of GHG´s. To achieve this goal AMOCO model was combined with LCA. The program was structured in Matlab to simulate any biogas process based on the AMOCO model and combined with the equations necessary to obtain climate change, acidification and eutrophication potentials of the whole production system based on ReCiPe midpoint v.1.06 methodology. Developed simulation was optimized based on real data from operating biogas plants and existing literature research. The results prove that AMOCO model can successfully imitate the system behavior of biogas plants and the necessary time required for the process to adapt in order to generate demanded energy from available feedstock. Combination with LCA approach provided opportunity to keep the resulting emissions from operation at the lowest possible level. This would allow for a prediction of the process, when the feedstock utilization supports the establishment of closed material circles within a smart bio-production grid – under the constraint of minimal drawbacks for the environment and maximal sustainability.

Keywords: AMOCO model, GHG emissions, life cycle assessment, modelling

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Authors: Min Ju Kim, Beom Jin Park, Deuk Jae Sung, Na Yeon Han, Kichoon Sim

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Purpose: The purpose of this study is to determine the significant magnetic resonance (MR) imaging factors of lateral pelvic lymph node (LPLN) on the assessment of survival outcomes of neoadjuvant combined chemotherapy and radiation therapy (CRT) in patients with mid/low rectal cancer. Materials and Methods: The institutional review board approved this retrospective study of 63 patients with mid/low rectal cancer who underwent MR before and after CRT and patient consent was not required. Surgery performed within 4 weeks after CRT. The location of LPLNs was divided into following four groups; 1) common iliac, 2) external iliac, 3) obturator, and 4) internal iliac lymph nodes. The short and long axis diameters, numbers, shape (ovoid vs round), signal intensity (homogenous vs heterogenous), margin (smooth vs irregular), and diffusion-weighted restriction of LPLN were analyzed on pre- and post-CRT images. For treatment response using size, lymph node groups were defined as group 1) short axis diameter ≤ 5mm on both MR, group 2) > 5mm change into ≤ 5mm after CRT, and group 3) persistent size > 5mm before and after CRT. Clinical findings were also evaluated. The disease-free survival and overall survival rate were evaluated and the risk factors for survival outcomes were analyzed using cox regression analysis. Results: Patients in the group 3 (persistent size >5mm) showed significantly lower survival rates than the group 1 and 2 (Disease-free survival rates of 36.1% and 78.8, 88.8%, p < 0.001). The size response (group 1-3), multiplicity of LPLN, the level of carcinoembryonic antigen (CEA), patient’s age, T and N stage, vessel invasion, perineural invasion were significant factors affecting disease-free survival rate or overall survival rate using univariate analysis (p < 0.05). The persistent size (group 3) and multiplicity of LPLN were independent risk factors among MR imaging features influencing disease-free survival rate (HR = 10.087, p < 0.05; HR = 4.808, p < 0.05). Perineural invasion and T stage were shown as independent histologic risk factors (HR = 16.594, p < 0.05; HR = 15.891, p < 0.05). Conclusion: The persistent size greater than 5mm and multiplicity of LPLN on both pre- and post-MR after CRT were significant MR factors affecting survival outcomes in the patients with mid/low rectal cancer.

Keywords: rectal cancer, MRI, lymph node, combined chemoradiotherapy

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Authors: F. Moghtaderi, M. Burke, J. Troelsen

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There has been a significant decline in active travel as well as the massive increase use of car-dependent travel mode in many countries during past two decades. Evidential risks for people’s physical and mental health problems are followed by this increased use of motorized travel mode. These problems range from overweight and obesity to increasing air pollution. In response to these rising concerns, local councils and other interested organizations around the world have introduced a variety of initiatives regarding reduce the dominance of cars for the daily journeys. However, the nature of these kinds of interventions, which related to the human behavior, make lots of complexities. People’s travel behavior and changing this behavior, has two different aspects. People’s attitudes and perceptions toward the sustainable and healthy modes of travel, and motorized travel modes (especially private car use) is one these two aspects. The other one related to people’s behavior change processes. There are no comprehensive model in order to guide policy interventions to increase the level of succeed of such interventions. A comprehensive theoretical framework is required in accordance to facilitate and guide the processes of data collection and analysis to achieve the best possible guidelines for policy makers. Regarding this gaps in the travel behavior change research, this paper attempted to identify and suggest a multidimensional framework in order to facilitate planning interventions. A structured mixed-method is suggested regarding the expand the scope and improve the analytic power of the result according to the complexity of human behavior. In order to recognize people’s attitudes, a theory with the focus on people’s attitudes towards a particular travel behavior was needed. The literature around the theory of planned behavior (TPB) was the most useful, and had been proven to be a good predictor of behavior change. Another aspect of the research, related to the people’s decision-making process regarding explore guidelines for the further interventions. Therefore, a theory was needed to facilitate and direct the interventions’ design. The concept of the transtheoretical model of behavior change (TTM) was used regarding reach a set of useful guidelines for the further interventions with the aim to increase active travel and sustainable modes of travel. Consequently, a combination of these two theories (TTM and TPB) had presented as an appropriate concept to identify and design implemented travel behavior change interventions.

Keywords: behavior change theories, theoretical framework, travel behavior change interventions, urban research

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Authors: Jihene Jebeniani

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We proposed an approach combining both the techniques of experimental economy and the flexibility of discrete choice models in order to test the loss aversion. Our main objective was to test the loss aversion of the Cumulative Prospect Theory (CPT). We developed an experimental laboratory in the context of the financial investments that aimed to analyze the attitude towards the risk of the investors. The study uses the lotteries and is basing on econometric modeling. The estimated model was the ordered probit.

Keywords: risk aversion, behavioral finance, experimental economic, lotteries, cumulative prospect theory

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Authors: Mohammad Aziz Shah Mohamed Arip, Aslina Ahmad, Fauziah Mohd Sa'ad, Samsiah Mohd Jais, Syed Sofian Syed Salim

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This experimental study evaluates the effect of using Cognitive-Behavioral Therapy (CBT) and Multidimensional Self-Concept Model (MSCM) in a drug prevention programme to increase resiliency and reduce aggression among at-risk youth in Malaysia. A number of 60 (N=60) university students who were at-risk of taking drugs were involved in this study. Participants were identified with self-rating scales, Adolescent Resilience Attitude Scale (ARAS) and Aggression Questionnaire. Based on the mean score of these instruments, the participants were divided into the treatment group, and the control group. Data were analyzed using t-test. The finding showed that the mean score of resiliency was increased in the treatment group compared to the control group. It also shows that the mean score of aggression was reduced in the treatment group compared to the control group. Drug Prevention Programme was found to help in enhancing resiliency and reducing aggression among participants in the treatment group compared to the controlled group. Implications were given regarding the preventive actions on drug abuse among youth in Malaysia.

Keywords: drug prevention programme, cognitive-behavioral therapy (CBT), multidimensional self concept model (MSCM), resiliency, aggression, at-risk youth

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Authors: Peter Ugbedeojo Nelson

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Despite the tremendous advancements and knowledge acquisition around entrepreneurship orientation (EO) research, there may still be more to learn on how environmental dynamics would permute organizational processes and determine the extent to which success would be achieved. Using the contingency theory, we test a model that proposes a moderating influence of external relational capital and environmental hostility on the EO-performance effect of 423 managers/owners of small and medium scale enterprises. The hypotheses were tested using Hayes simultaneous regression, and the results showed that all EO dimensions (risk-taking, innovation, and performance) had a main effect on performance while the moderating variables interacted well with risk-taking (more than other EO dimensions) to improve performance. However, external relational capital, more than environmental hostility, influences the EO-performance relationship. Our findings highlight the differential ways that EO dimensions interact with environmental contingencies to influence performance. Further studies can examine how competitive aggressiveness and autonomy are moderated by external relational capital and environmental hostility.

Keywords: external relational capital, entrepreneurial orientation, risk-taking, innovation, proactiveness

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Authors: Muhammad Imran Din

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The aim of this study was to understand the interaction between multi-walled carbon nano tubes (MCNTs) and anticancer agents and evaluate the drug-loading ability of MCNTs. Batch adsorption experiments were carried out for adsorption of 5-Fluorouracil (5-FL) using MCNTs. The effect of various operating variables, viz., adsorbent dosage, pH, contact time and temperature for adsorption of 5-Fluorouracil (5-FL) has been studied. The Freundlich adsorption model was successfully employed to describe the adsorption process. It was found that the pseudo-second-order mechanism is predominant and the overall rate of the 5-Fluorouracil (5-FL) adsorption process appears to be controlled by the more than one-step. Thermodynamic parameters such as free energy change (ΔG°), enthalpy change (ΔH°) and entropy change (ΔS°) have been calculated respectively, revealed the spontaneous, endothermic and feasible nature of adsorption process. The results showed that carbon nano tubes were able to form supra molecular complexes with 5-Fluorouracil (5-FL) by π-π stacking and possessed favorable loading properties as drug carriers.

Keywords: drug, adsorption, anticancer, 5-Fluorouracil (5-FL)

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Authors: Hamed Rahmani, Wim Groot

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The term "youth not in employment, education or training (NEET)" refers to a combination of youth unemployment and school dropout. This study investigates the variables that increase the risk of becoming NEET in Iran. A selection bias-adjusted Probit model was employed using machine learning to identify these risk factors. We used cross-sectional data obtained from the Statistical Centre of Iran and the Ministry of Cooperatives Labour and Social Welfare that was taken from the labour force survey conducted in the spring of 2021. We look at years of education, work experience, housework, the number of children under the age of six in the home, family education, birthplace, and the amount of land owned by households. Results show that hours spent performing domestic chores enhance the likelihood of youth becoming NEET, and years of education and years of potential work experience decrease the chance of being NEET. The findings also show that female youth born in cities were less likely than those born in rural regions to become NEET.

Keywords: NEET youth, probit, CART, machine learning, unemployment

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Authors: Novita Linda Akbar, Elmeida Effendy, Mustafa M. Amin

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Background: The most common of psychotic disorders is schizophrenia. Vitamin D is made from sunlight, and in the skin from UVB radiation from sunlight. If people with Vitamin D deficiency is common severe mental illness such as schizophrenia.Schizophrenia is a chronic mental illness characterised by positive symptoms and negatives symptoms, such as hallucinations and delusions, flat affect and lack of motivation we can found. In patients with Schizophrenia maybe have several environmental risk factors for schizophrenia, such as season of birth, latitude, and climate has been linked to vitamin D deficiency. There is also relationship between the risk of schizophrenia and latitude, and with an increased incidence rate of schizophrenia seen at a higher latitude. Methods: This study was an analytical study, conducted in BLUD RS Jiwa Propinsi Sumatera Utara and RSUD Deli Serdang, the period in May 2016 and ended in June 2016 with a sample of the study 60 sample (20 patients live in the Highland and Lowland, 20 healthy controls). Inclusion criteria were schizophrenic patients both men and women, aged between 18 to 60 years old, acute phase no agitation or abstinence antipsychotic drugs for two weeks, live in the Highland and Lowland, and willing to participate this study. Exclusion criteria were history of other psychotic disorders, comorbidities with other common medical condition, a history of substance abuse. Sample inspection for serum vitamin D using ELFA method. Statistical analysis using numeric comparative T-independent test. Results: The results showed that average levels of vitamin D for a group of subjects living in areas of high land was 227.6 ng / mL with a standard deviation of 86.78 ng / mL, the lowest levels of vitamin D is 138 ng / mL and the highest 482 ng / mL. In the group of subjects who settled in the low lands seem mean vitamin D levels higher than the mountainous area with an average 237.8 ng / mL with a standard deviation of 100.16 ng / mL. Vitamin D levels are lowest and the highest 138-585 ng / mL. Conclusion and Suggestion: The results of the analysis using the Mann Whitney test showed that there were no significant differences between the mean for the levels of vitamin D based on residence subject with a value of p = 0.652.

Keywords: latitude, schizophrenia, Vitamin D, Sumatera Utara

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Authors: Jeremy Dixon

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Safeguarding adults forms a core part of social work practice. The Government in England and Wales has made efforts to standardise practices through The Care Act 2014. The Act states that local authorities have duties to make inquiries in cases where an adult with care or support needs is experiencing or at risk of abuse and is unable to protect themselves from abuse or neglect. Despite the importance given to safeguarding adults within law there remains little research about how social workers conduct such decisions on the ground. This presentation reports on findings from a pilot research study conducted within two social work teams in a Local Authority in England. The objective of the project was to find out how social workers interpreted safeguarding duties as laid out by The Care Act 2014 with a particular focus on how workers assessed and managed risk. Ethnographic research methods were used throughout the project. This paper focusses specifically on decisions made by workers in the assessment team. The paper reports on qualitative observation and interviews with five workers within this team. Drawing on governmentality theory, this paper analyses the techniques used by workers to manage risk from a distance. A high proportion of safeguarding referrals came from care workers or managers in residential care homes. Social workers conducting safeguarding assessments were aware that they had a duty to work in partnership with these agencies. However, their duty to safeguard adults also meant that they needed to view them as potential abusers. In making judgments about when it was proportionate to refer for a safeguarding assessment workers drew on a number of common beliefs about residential care workers which were then tested in conversations with them. Social workers held the belief that residential homes acted defensively, leading them to report any accident or danger. Social workers therefore encouraged residential workers to consider whether statutory criteria had been met and to use their own procedures to manage risk. In addition social workers carried out an assessment of the workers’ motives; specifically whether they were using safeguarding procedures as a shortcut for avoiding other assessments or as a means of accessing extra resources. Where potential abuse was identified social workers encouraged residential homes to use disciplinary policies as a means of isolating and managing risk. The study has implications for understanding risk within social work practice. It shows that whilst social workers use law to govern individuals, these laws are interpreted against cultural values. Additionally they also draw on assumptions about the culture of others.

Keywords: adult safeguarding, governmentality, risk, risk assessment

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Authors: Princes Ann E. Prieto, Denise F. Alpuerto, John Rafael C. Unlayao, Neil Concibido, Monet Concepcion Maguyon-Detras

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Failure Mode and Effects Analysis (FMEA) has been used in the virtual Process Hazard Analysis (PHA) of the Acetone production process through the dehydrogenation of isopropyl alcohol, for which very limited process risk assessment has been published. In this study, the potential failure modes, effects, and possible causes of selected major equipment in the process were identified. During the virtual FMEA mock sessions, the risks in the process were evaluated and recommendations to reduce and/or mitigate the process risks were formulated. The risk was estimated using the calculated risk priority number (RPN) and was classified into four (4) levels according to their effects on acetone production. Results of this study were also used to rank the criticality of equipment in the process based on the calculated criticality rating (CR). Bow tie diagrams were also created for the critical hazard scenarios identified in the study.

Keywords: chemical process safety, failure mode and effects analysis (FMEA), process hazard analysis (PHA), process safety management (PSM)

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Authors: Olga Plaza, Katarzyna Kosinska-Kaczynska, Stepan Feduniw, Dominika Pazdzior, Kinga Zebrowska, Katarzyna Kwiatkowska

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Introduction: The main causes of depression among pregnant women remain unclear. However, it is clear that pregnancy carries a higher risk of depression occurrence. Left untreated, prenatal depression can be a cause of serious both maternal and neonatal complications. Aim of the study: The aim of the study was to define potential risk factors of prenatal depression and to assess the frequency of its occurrence among pregnant women. Material and Methods: A prospective cross-sectional study was performed among 346 women. The self- composed questionnaire consisting of 46 questions, was distributed via the Internet between November 2017 and March 2018. The questionnaire contained the Edinburgh Postnatal Depression Scale (EPDS), in which the results of 13 and more points (out of 30) suggested possible prenatal depression. Statistical analysis was performed with Chi2 Pearson. P value < 0.05 was considered significant. Results: 37.57% (n=130) of women had a score of 13 or more points. Women with depressive symptoms (DS) reported lack of support from the partner (46.9% vs. 16.2%; p < 0.001) as well as other family members (40.8% vs. 14.4%; p < 0.001), current pregnancy being unplanned (21.5% vs. 12.5%; p=0.014) and low socio-economic status (10% vs. 0.9%; p < 0.001). Both early and advanced maternal age seemed to play a role in occurrence of DS: in women aged 17-24 40.8% declared symptoms (vs 28.7%; p < 0.01), in mothers aged ≥37 6.2% did (vs 0.5%; p < 0.001). Smoking during pregnancy was also more frequent among patients with DS (31.5% vs. 18.1%; p=0.004). Previous diagnosis of depression or other mood disorders significantly increased a chance of DS occurrence (respectively- 17.7% vs. 4.6%; p < 0.001 and 49.2% vs. 25%; p<0.001). Parental diagnosis of mood disorders and other mental disorders was also more frequent in this group of patients (respectively- 24.6% vs. 15.7%; p= 0.026 and 26.4% vs. 9.7%; p < 0.001). Only 23.8% of women with DS sought help from healthcare professionals, with 21.5% receiving pharmacological treatment. Conclusions: Pregnant women often report having DS. Evaluation of risk factors of DS and possible prenatal depression is essential in proper screening for depression among pregnant women.

Keywords: obstetrics, polish women, prenatal care, prenatal depression, risk factors

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Authors: Sourabh Harihar, Henk Jan Verhagen

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The nurturing of a mangrove ecosystem requires a protected coastal environment with adequate drainage of the soil substratum. In a conceptual design undertaken for a mangrove rejuvenation project along the eastern coast of Mumbai (India), various engineering alternatives have been thought of as a protective coastal structure and drainage system. One such design uses bamboo-pile walls in creating shielded compartments in the form of various layouts, coupled with bamboo drains. The bamboo-based design is found to be environmentally and economically advantageous over other designs like sand-dikes which are multiple times more expensive. Moreover, employing a natural material such as bamboo helps the structure naturally blend with the developing mangrove habitat, allaying concerns about dismantling the structure post mangrove growth. A cost-minimising and eco-friendly bamboo structure, therefore, promises to pave the way for large rehabilitation projects in future. As mangrove ecosystems in many parts of the world increasingly face the threat of destruction due to urban development and climate change, protective nature-based designs that can be built in a short duration are the need of the hour.

Keywords: bamboo, environment, mangrove, rehabilitation

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Authors: Syed Noaman Shah

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The current paper evaluates the effect of external public debt risk on the borrowing cost of private non-financial firms in euro zone. Further, the study also treats the impact of austerity measures on syndicated-loan spreads of private firm followed by euro area member states to revive the economic growth in the region. To test these hypotheses, we follow multivariate ordinary least square estimation method to assess the effect of external public debt on the borrowing cost of private firms. By using foreign syndicated-loan issuance data of non-financial private firms from 2005 to 2011, we attempt to gauge how the private financing cost varies with high levels of sovereign external debt prevalent in the euro zone. Our results suggest significant effect of external public debt on the borrowing cost of private firm. In particular, an increase in external public debt by one standard deviation from its sample mean raises syndicated-loan spread by 89 bps. Furthermore, weak creditor rights protection prevalent in member states deepens this effect. However, we do not find any significant effect of domestic public debt on the private sector borrowing cost. In addition, the results show significant effect of austerity measures on private financing cost, both in normal and in crisis period in the euro zone. In particular, one standard deviation change in fiscal consolidation conditional mean reduces the syndicated-loan spread by 22 bps. In turn, it indicates strong presence of credibility channel due to austerity measures in euro area region.

Keywords: corporate debt, fiscal consolidation, sovereign debt, syndicated-loan spread

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Authors: William Li

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Lane-change path planning is a crucial and yet complex task in autonomous driving. The traditional path planning approach based on a system of carefully-crafted rules to cover various driving scenarios becomes unwieldy as more and more rules are added to deal with exceptions and corner cases. This paper proposes to divide the entire path planning to two stages. In the first stage the ego vehicle travels longitudinally in the source lane to reach a safe state. In the second stage the ego vehicle makes lateral lane-change maneuver to the target lane. The paper derives the safe state conditions based on lateral lane-change maneuver calculation to ensure collision free in the second stage. To determine the acceleration sequence that minimizes the time to reach a safe state in the first stage, the paper proposes three schemes, namely, kinetic model based optimization, deep reinforcement learning, and 5G vehicle-to-vehicle (V2V) communications. The paper investigates these schemes via simulation. The model-based optimization is sensitive to the model assumptions. The deep reinforcement learning is more flexible in handling scenarios beyond the model assumed by the optimization. The 5G V2V eliminates uncertainty in predicting future behaviors of surrounding vehicles by sharing driving intents and enabling cooperative driving.

Keywords: lane change, path planning, autonomous driving, deep reinforcement learning, 5G, V2V communications, connected vehicles

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Authors: Jaffry Zakaria, Nor Azlina Hasbullah

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The research on water quality based on 'Water Quality Index' (WQI) has been on the run along Kampar River in Perak State of Malaysia. This study was conducted to achieve several key objective that determe the value of the parameters that were studied based on Water Quality Index (WQI). The parameters include Dissolved Oxygen (DO), pH, Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD) and Suspended Solids. In this study, three sampling stations were selected. Through observations from the researchers, several pollutions were found occurring along the research area such as the disposal of waste water directly without treatment from villagers, widespread dumping of solid waste and the development of the surrounding areas that contributed to the pollution of Sungai Kampar in Perak, Malaysia. Sungai Kampar is commonly used for water recreational activities as well as for bathing purposes. Results showed that Sungai Kampar is classified under category III. According to Interim National Water Quality Standard for Malaysia (INWQS), rivers in the third grade are clean but not suitable for river recreational activities. Therefore, there is a requirement to investigate and analysis the water quality of all white water rivers in Malaysia focusing on the area of water activities. The combination of technology and risk management based on risk assessments can help the recreational industry to survive in future.

Keywords: risk assessments, White Water River, water quality index (WQI), Interim National Water Quality Standard for Malaysia (INWQS)

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Authors: Fatma Kürüm Varolgüneş, Fatih Canan

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Mardin is one of the unique cities in Turkey with its rich cultural and historical heritage. Mardin’s traditional dwellings have been affected both by natural data such as climate and topography and by cultural data like lifestyle and belief. However, in the new settlements, housing is formed with modern approaches and unsuitable forms clashing with Mardin’s culture and environment. While the city is expanding, traditional textures are ignored. Thus, traditional settlements are losing their identity and are vanishing because of the rapid change and transformation. The main aim of this paper is to determine the physical and social data needed to define the characteristic features of Mardin’s old and new settlements. In this context, based on social and cultural data, old and new settlement formations of Mardin have been investigated from various aspects. During this research, the following methods have been utilized: observations, interviews, public surveys, literature review, as well as site examination via maps, photographs and questionnaire methodology. In conclusion, this paper focuses on how changes in the physical forms of cities affect the typology and the identity of cities, as in the case of Mardin.

Keywords: urban and local identity, historical city center, traditional settlements, Mardin

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Authors: Laatra Zemmouri, Said Boukhechem, Samia Haffaf, Mohamed Lafri

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A study was conducted in order to determine the prevalence and risk factors associated with abortion in ewes in the region of M’sila, located in central-eastern Algeria. A questionnaire was carried out to obtain information about the occurrence of abortion, sheep housing conditions, vaccination, feeding and management practices, and whether the farmers kept other livestock. This cross-sectional study was conducted for 36 months (between 2016 and 2019). A total of 71 sheep flocks were visited. Among 8168 ewes, we recorded 734 (8.99%) abortions and 3861 lambings. The risk factor analysis using multivariable logistic regression showed an association between abortion and vaccination against brucellosis (CI 95%= 2,76-1,35; p<0,001). Abortion decreased when dogs are owned (CI 95%= 0,36-0,84; p= 0.006), however, abortion increased with the presence of cats in farms (CI 95%= 1,24-2,8; p=0.003). There was a significant association between abortion and keeping goats (CI 95%= 1,18-2,40; p= 0.004), bovins (CI 95%= 0,3-0,68; p<0,001) and poultry CI 95%= 0,39-0,77; p= 0.001) in farms. Through this study, it is noticed that a strong association between the occurrence of abortion and estrus synchronization, stillbirth occurrence, and feed supplementation (p<0.05). Identification of the causes of abortion is an important task to reduce foetal losses and to improve livestock productivity.

Keywords: abortion, ewes, questionnaire, risk factors

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Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

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To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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Authors: Juan Sebastián Rivera Soriano, Rosa Urbano Gutiérrez

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The Shodan House and the Sarabhai House (Ahmedabad, India, 1954 and 1955, respectively) are considered some of the most important works of Le Corbusier produced in the last stage of his career. There are some academic publications that study the compositional and formal aspects of their architectural design, but there is no in-depth investigation into how the climatic conditions of this region were a determining factor in the design decisions implemented in these projects. This paper argues that Le Corbusier developed a specific architectural design strategy for these buildings based on scientific research on climate in the Indian context. This new language was informed by a pioneering study and interpretation of climatic data as a design methodology that would even involve the development of new design tools. This study investigated whether their use of climatic data meets values and levels of accuracy obtained with contemporary instruments and tools, such as Energy Plus weather data files and Climate Consultant. It also intended to find out if Le Corbusier's office’s intentions and decisions were indeed appropriate and efficient for those climate conditions by assessing these projects using BIM models and energy performance simulations from Design Builder. Accurate models were built using original historical data through archival research. The outcome is to provide a new understanding of the environment of these houses through the combination of modern building science and architectural history. The results confirm that in these houses, it was achieved a model of low energy consumption. This paper contributes new evidence not only on exemplary modern architecture concerned with environmental performance but also on how it developed progressive thinking in this direction.

Keywords: bioclimatic architecture, Le Corbusier, Shodan, Sarabhai Houses

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Authors: Alaa M. Younis, Ismail S. Ismail, Lamiaa I. Mohamedein, Shimaa F. Ahmed

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Sandy surface sediments collected from fourteen sites along the gulfs of Suez and Aqaba coasts, Egypt were analyzed for heavy metals including Iron, Manganese, Zinc, Chromium, Nickel, Lead, Copper and Cadmium in order to evaluate the pollution status and environmental risk assessment of the study area. The obtained results showed that the concentrations of investigated metals are represented in the following sequence; For Gulf of Aqaba sediments Fe > Mn > Zn > Pb > Cr > Ni > Cu > Cd. While for Gulf of Suez Sediments Fe > Mn > Pb > Zn > Cu > Cr > Ni > Cd. The degree of surface sediment contamination using Geo-accumulation index (I geo) and Metal Pollution Index (MPI) was computed. Higher MPI values were observed at the sites III (Nama Bay) and VIII (Rex Beach). According to Sediment quality guidelines (SQGs) approach, Pb and Cu in the gulf of Suez at station IX (Kabanon Beach) had probably adverse ecological effects to marine organisms.

Keywords: heavy metal, environmental risk, Suez gulf, Aqaba gulf

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Authors: Xianglu Tang, Zhenxue Jiang, Zhuo Li

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Characterization of shale multi scale heterogeneity is an important part to evaluate size and space distribution of shale gas reservoirs in sedimentary basins. The origin of shale heterogeneity has always been a hot research topic for it determines shale micro characteristics description and macro quality reservoir prediction. Shale multi scale heterogeneity was discussed based on thin section observation, FIB-SEM, QEMSCAN, TOC, XRD, mercury intrusion porosimetry (MIP), and nitrogen adsorption analysis from 30 core samples in Silurian Longmaxi formation. Results show that shale heterogeneity can be characterized by pore structure and mineral composition. The heterogeneity of shale pore is showed by different size pores at nm-μm scale. Macropores (pore diameter > 50 nm) have a large percentage of pore volume than mesopores (pore diameter between 2~ 50 nm) and micropores (pore diameter < 2nm). However, they have a low specific surface area than mesopores and micropores. Fractal dimensions of the pores from nitrogen adsorption data are higher than 2.7, what are higher than 2.8 from MIP data, showing extremely complex pore structure. This complexity in pore structure is mainly due to the organic matter and clay minerals with complex pore network structures, and diagenesis makes it more complicated. The heterogeneity of shale minerals is showed by mineral grains, lamina, and different lithology at nm-km scale under the continuous changing horizon. Through analyzing the change of mineral composition at each scale, random arrangement of mineral equal proportion, seasonal climate changes, large changes of sedimentary environment, and provenance supply are considered to be the main reasons that cause shale minerals heterogeneity from microcosmic to macroscopic. Due to scale effect, the change of shale multi scale heterogeneity is a discontinuous process, and there is a transformation boundary between homogeneous and in homogeneous. Therefore, a shale multi scale heterogeneity changing model is established by defining four types of homogeneous unit at different scales, which can be used to guide the prediction of shale gas distribution from micro scale to macro scale.

Keywords: heterogeneity, homogeneous unit, multiscale, shale

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Authors: Mohammad Rajabalinejad

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Safety is often seen as a requirement or a performance indicator through the design process, and this does not always result in optimally safe products or systems. This paper suggests integrating the best safety practices with the design process to enrich the exploration experience for designers and add extra values for customers. For this purpose, the commonly practiced safety standards and design methods have been reviewed and their common blocks have been merged forming Safety Cube. Safety Cube combines common blocks for design, hazard identification, risk assessment and risk reduction through an integral approach. An example application presents the use of Safety Cube for design of machinery.

Keywords: safety, safety cube, product, system, machinery, design

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Authors: T. Garba, Y. Y. Babanyara, T. O. Quddus, A. K. Mukatari

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Human activities make environmental parameters in order to keep on changing globally. While some changes are necessary and beneficial to flora and fauna, others have serious consequences threatening the survival of their natural habitat if these changes are not properly monitored and mitigated. In-situ assessments are characterized by many challenges due to the absence of time series data and sometimes areas to be observed or monitored are inaccessible. Satellites Remote Sensing provide us with the digital images of same geographic areas within a pre-defined interval. This makes it possible to monitor and detect changes of environmental phenomena. This paper, therefore, reviewed the commonly use changes detection techniques globally such as image differencing, image rationing, image regression, vegetation index difference, change vector analysis, principal components analysis, multidate classification, post-classification comparison, and visual interpretation. The paper concludes by suggesting the use of more than one technique.

Keywords: environmental phenomena, change detection, monitor, techniques

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Authors: Bandreddy Anand Babu, Srinivasa Rao Mandadi, C. Pradeep Reddy, N. Ramesh Babu

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In this paper quickly illustrate the correlation investigation of Auto-Regressive Integrated Moving and Average (ARIMA) and daptive Network Based Fuzzy Inference System (ANFIS) models done by climate estimating. The climate determining is taken from University of Waterloo. The information is taken as Relative Humidity, Ambient Air Temperature, Barometric Pressure and Wind Direction utilized within this paper. The paper is carried out by analyzing the exhibitions are seen by demonstrating of ARIMA and ANIFIS model like with Sum of average of errors. Versatile Network Based Fuzzy Inference System (ANFIS) demonstrating is carried out by Mat lab programming and Auto-Regressive Integrated Moving and Average (ARIMA) displaying is produced by utilizing XLSTAT programming. ANFIS is carried out in Fuzzy Logic Toolbox in Mat Lab programming.

Keywords: ARIMA, ANFIS, fuzzy surmising tool stash, weather forecasting, MATLAB

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Authors: Betül sönmez, Fatma Azizoğlu, S. Bilge Hapçıoğlu, Aytolan Yıldırım

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Background: Social innovativeness contains the procurement of a sustainable benefit for a number of problems from working conditions to education, social development, health, and from environmental control to climate change, as well as the development of new social productions and services. Objectives: This study was conducted to determine the correlation between the social innovation tendency of nursing and medical faculty students and value types. Methods and participants: The population of this correlational study consisted of third-year students studying at a medical faculty and a nursing faculty in a public university in Istanbul. Ethics committee approval and permission from the school administrations were obtained in order to conduct the study and voluntary participation of the students in the study was ensured. 524 questionnaires were obtained with a total return rate of 57.1% (65.0% in nurse student and 52.1% in physic students). The data of the study were collected by using the Portrait Values Questionnaire and a questionnaire containing the Social Innovativeness Scale. Results: The effect of the subscale scores of Portrait Values Questionnaire on the total score of Social Innovativeness Scale was 26.6%. In the model where a significance was determined (F=37.566; p<0.01), the highest effect was observed in the subscale of universalism. The effect of subscale scores obtained from the Portrait Values Questionnaire, as well as age, gender and number of siblings was 25% on the Social Innovativeness in nursing students and 30.8% in medical faculty students. In both models where a significance was determined (p<0.01), the nursing students had the values of power, universalism and kindness, whereas the medical faculty students had the values of self-direction, stimulation, hedonism and universalism showed the highest effect in both models. Conclusions: Universalism is the value with the highest effect upon the social innovativeness in both groups, which is an expected result by the nature of professions. The effect of the values of independent thinking and self-direction, as well as openness to change involving quest for innovation (stimulation), which are observed in medical faculty students, also supports the literature of innovative behavior. These results are thought to guide educators and administrators in terms of developing socially innovative behaviors.

Keywords: social innovativeness, portrait values questionnaire, nursing students, medical faculty students

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Authors: Paul Buchana, Patrick E. Mc Sharry

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In 2017 there will be about 38 wind farms in the North Sea belonging to 5 different countries. The North Sea is ideal for offshore wind power generation and is thus attractive to offshore wind energy developers and investors. With concerns about the potential for offshore wind turbines to sustain substantial damage as a result of extreme weather conditions, particularly windstorms, this poses a unique challenge to insurers and reinsurers as to adequately quantify the risk and offer appropriate insurance cover for these assets. The need to manage this risk also concerns regulators, who provide the oversight needed to ensure that if a windstorm or a series of storms occur in this area over a one-year time frame, the insurers of these assets in the EU remain solvent even after meeting consequent damage costs. In this paper, using available European windstorm data for the past 33 years and actual wind farm locations together with information pertaining to each of the wind farms (number of turbines, total capacity and financial value), we present a Monte Carlo simulation approach to assess the number of turbines that would be buckled in each of the wind farms using maximum wind speeds reaching each of them. These wind speeds are drawn from historical windstorm data. From the number of turbines buckled, associated financial loss and output capacity can be deduced. The results presented in this paper are targeted towards offshore wind energy developers, insurance and reinsurance companies and regulators.

Keywords: catastrophe modeling, North Sea wind farms, offshore wind power, risk analysis

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