Search results for: social/critical model of disability

Authors: Avan Al-Saffar, Eun-Jin Kim

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Both the logistic growth model and the gompertz growth model are used to describe growth processes. Both models driven by perturbations in different cases are investigated using information theory as a useful measure of sustainability and the variability. Specifically, we study the effect of different oscillatory modulations in the system's parameters on the evolution of the system and Probability Density Function (PDF). We show the maintenance of the initial conditions for a long time. We offer Fisher information analysis in positive and/or negative feedback and explain its implications for the sustainability of population dynamics. We also display a finite amplitude solution due to the purely fluctuating growth rate whereas the periodic fluctuations in negative feedback can lead to break down the system's self-regulation with an exponentially growing solution. In the cases tested, the gompertz and logistic systems show similar behaviour in terms of information and sustainability although they develop differently in time.

Keywords: dynamical systems, fisher information, probability density function (pdf), sustainability

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Authors: Abimbola Mobolanle Adu, Marcus Tayo Akinlade

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This comprehensive study systematically dissects the intricate interplay between the removal of fuel subsidy and its multifaceted repercussions on Nigeria's educational system. Originating in the 1970s, the fuel subsidy policy initially conceived to curtail fuel costs and faced financial unsustainability. In 2023, President Bola Tinubu's administration announced its cessation. The resultant escalation in petroleum product prices precipitated challenges within the education sector, manifesting as heightened administrative costs, increased student fees, amplified dropout rates, and others. Employing a qualitative research methodology, grounded in Critical Theory, the study draws from diverse secondary sources and employs content analysis to unravel the intricate layers of this issue. Critical Theory provides a lens through which the power dynamics, socio-economic structures, and ideological influences shaping policy decisions can be critically examined, offering a deeper understanding of the multifaceted impact. Findings underscore the imperative for strategic interventions, advocating for investments in technology and the exploration of alternative energy sources. The paper concludes by emphasizing the pivotal role of education, advocating for nuanced policies to alleviate the impact on both private and public educational institutions. In essence, this research contributes nuanced insights into the labyrinthine dynamics between fuel subsidy policies and the educational sector, underscoring the exigency for meticulous interventions to fortify the nation's educational foundation.

Keywords: administration, education, fuel subsidy, policy, multilayered impact

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Authors: V. Jamuna, A. K. Chakravarty, C. S. Patil, Vijay Kumar, M. A. Mir, Rakesh Kumar

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Intense selection of buffaloes for milk production at organized herds of the country without giving due attention to fertility traits viz. pregnancy rate has lead to deterioration in their performances. Aim of study is to develop an optimum model for predicting pregnancy rate and to assess the level of pregnancy rate with respect to milk production Murrah buffaloes. Data pertaining to 1224 lactation records of Murrah buffaloes spread over a period 21 years were analyzed and it was observed that pregnancy rate depicted negative phenotypic association with lactation milk yield (-0.08 ± 0.04). For developing optimum model for pregnancy rate in Murrah buffaloes seven simple and multiple regression models were developed. Among the seven models, model II having only Service period as an independent reproduction variable, was found to be the best prediction model, based on the four statistical criterions (high coefficient of determination (R 2), low mean sum of squares due to error (MSSe), conceptual predictive (CP) value, and Bayesian information criterion (BIC). For standardizing the level of fertility with milk production, pregnancy rate was classified into seven classes with the increment of 10% in all parities, life time and their corresponding average pregnancy rate in relation to the average lactation milk yield (MY).It was observed that to achieve around 2000 kg MY which can be considered optimum for Indian Murrah buffaloes, level of pregnancy rate should be in between 30-50%.

Keywords: life time, pregnancy rate, production, service period, standardization

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Authors: Sun Jin Park, Kyung-Ja Cho

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This study focused on characteristics related to hasty behaviour. To investigate the relation between personal characteristics and hasty behaviour, 601 data were collected, 335 males and 256 females answered their own 'social avoidance and distress’, ‘anxiety’, ‘sensation seeking', 'hope', and ' hasty behaviour. And then 591 data were used for the analysis. The factor analysis resulted hasty behaviour consisted of 5 factors, time pressure, isolation, uncomfortable situation, boring condition, and expectation of reward. The result showed anxiety, sensation seeking, and hope related to hasty behaviour. Specifically, anxiety was involved in every hasty behaviour. This result means that psychological tension and worry are related to hasty behaviour in common. 'Social avoidance and distress', 'sensation seeking' and 'hope' influenced on hasty behaviour under time pressure, in isolation, in expectation of rewards respectively. This means that each factor of hasty behaviour has anxiety as its basis, expressed through a varied nature.

Keywords: hasty behaviour, social avoidance and distress, anxiety, sensation seeking, hope

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Authors: Kuo Chieh Chao, Thishani Amarathunga, Sangam Shrestha

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Rainfall induced slope failures are one of the most damaging and disastrous natural hazards which occur frequently in the world. This type of sliding mainly occurs in the zone above the groundwater level in silty/sandy soils. When the rainwater begins to infiltrate into the vadose zone of the soil, the negative pore-water pressure tends to decrease and reduce the shear strength of soil material. Climate change has resulted in excessive and unpredictable rainfall in all around the world, resulting in landslides with dire consequences to human lives and infrastructure. Such problems could be overcome by examining in detail the causes for such slope failures and recommending effective repair plans for vulnerable locations by considering future climatic change. The selected area for this study is located in the road rehabilitation section from Maubara to Mota Ain road in Timor-Leste. Slope failures and cracks have occurred in 2013 and after repairs reoccurred again in 2017 subsequent to heavy rains. Both observed and future predicted climate data analyses were conducted to understand the severe precipitation conditions in past and future. Observed climate data were collected from NOAA global climate data portal. CORDEX data portal was used to collect Regional Climate Model (RCM) future predicted climate data. Both observed and RCM data were extracted to location-based data using ArcGIS Software. Linear scaling method was used for the bias correction of future data and bias corrected climate data were assigned to GeoStudio Software. Precipitations of wet seasons (December to March ) in 2007 to 2013 is higher than 2001-2006 period and it is more than nearly 40% higher precipitation than usual monthly average precipitation of 160mm.The results of seepage analyses which were carried out using SEEP/W model with observed climate, clearly demonstrated that the pore water pressure within the fill slope was significantly increased due to the increase of the infiltration during the wet season of 2013.One main Regional Climate Models (RCM) was analyzed in order to predict future climate variation under two Representative Concentration Pathways (RCPs).In the projected period of 76 years ahead from 2014, shows that the amount of precipitation is considerably getting higher in the future in both RCP 4.5 and RCP 8.5 emission scenarios. Critical pore water pressure conditions during 2014-2090 were used in order to recommend appropriate remediation methods. Results of slope stability analyses indicated that the factor of safety of the fill slopes was reduced from 1.226 to 0.793 during the dry season to wet season in 2013.Results of future slope stability which were obtained using SLOPE/W model for the RCP emissions scenarios depict that, the use of tieback anchors and geogrids in slope protection could be effective in increasing the stability of slopes to an acceptable level during the wet seasons. Moreover, methods and procedures like monitoring of slopes showing signs or susceptible for movement and installing surface protections could be used to increase the stability of slopes.

Keywords: climate change, precipitation, SEEP/W, SLOPE/W, unsaturated soil

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Authors: Xinhuang Wu, Yousef Sardahi

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A hybrid and optimal multi-loop control structure combining linear and nonlinear control algorithms are introduced in this paper to regulate the position of a quadcopter unmanned aerial vehicle (UAV) driven by four brushless DC motors. To this end, a nonlinear mathematical model of the UAV is derived and then linearized around one of its operating points. Using the nonlinear version of the model, a sliding mode control is used to derive the control laws of the motor thrust forces required to drive the UAV to a certain position. The linear model is used to design two controllers, XG-controller and YG-controller, responsible for calculating the required roll and pitch to maneuver the vehicle to the desired X and Y position. Three attitude controllers are designed to calculate the desired angular rates of rotors, assuming that the Euler angles are minimal. After that, a many-objective optimization problem involving 20 design parameters and ten objective functions is formulated and solved by HypE (Hypervolume estimation algorithm), one of the widely used many-objective optimization algorithms approaches. Both stability and performance constraints are imposed on the optimization problem. The optimization results in terms of Pareto sets and fronts are obtained and show that some of the design objectives are competing. That is, when one objective goes down, the other goes up. Also, Numerical simulations conducted on the nonlinear UAV model show that the proposed optimization method is quite effective.

Keywords: optimal control, many-objective optimization, sliding mode control, linear control, cascade controllers, UAV, drones

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Authors: A. Yakub AbdurRaheem

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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 northeastern parts have ignited violence, bloodshed, refugee exodus and internal migration. Not only do the persistent attacks of the sect create widespread insecurity and fear, but 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 this 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 the prompt response, encourage community and neighborhood policing to ameliorate security challenges in Nigeria.

Keywords: social crisis, economy, resources, property market

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Authors: Inna Kornienko, Svetlana Guryeva, Natalia Danilova, Elena Petersen

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Drug toxicity often goes undetected until clinical trials, the most expensive and dangerous phase of drug development. Both human cell culture and animal studies have limitations that cannot be overcome by improvements in drug testing protocols. Tissue engineering is an emerging alternative approach to creating models of human malignant tumors for experimental oncology, personalized medicine, and drug discovery studies. This new generation of bioengineered tumors provides an opportunity to control and explore the role of every component of the model system including cell populations, supportive scaffolds, and signaling molecules. An area that could greatly benefit from these models is cancer research. Recent advances in tissue engineering demonstrated that decellularized tissue is an excellent scaffold for tissue engineering. Decellularization of donor organs such as heart, liver, and lung can provide an acellular, naturally occurring three-dimensional biologic scaffold material that can then be seeded with selected cell populations. Preliminary studies in animal models have provided encouraging results for the proof of concept. Decellularized Organs preserve organ microenvironment, which is critical for cancer metastasis. Utilizing 3D tumor models results greater proximity of cell culture morphological characteristics in a model to its in vivo counterpart, allows more accurate simulation of the processes within a functioning tumor and its pathogenesis. 3D models allow study of migration processes and cell proliferation with higher reliability as well. Moreover, cancer cells in a 3D model bear closer resemblance to living conditions in terms of gene expression, cell surface receptor expression, and signaling. 2D cell monolayers do not provide the geometrical and mechanical cues of tissues in vivo and are, therefore, not suitable to accurately predict the responses of living organisms. 3D models can provide several levels of complexity from simple monocultures of cancer cell lines in liquid environment comprised of oxygen and nutrient gradients and cell-cell interaction to more advanced models, which include co-culturing with other cell types, such as endothelial and immune cells. Following this reasoning, spheroids cultivated from one or multiple patient-derived cell lines can be utilized to seed the matrix rather than monolayer cells. This approach furthers the progress towards personalized medicine. As an initial step to create a new ex vivo tissue engineered model of a cancer tumor, optimized protocols have been designed to obtain organ-specific acellular matrices and evaluate their potential as tissue engineered scaffolds for cultures of normal and tumor cells. Decellularized biomatrix was prepared from animals’ kidneys, urethra, lungs, heart, and liver by two decellularization methods: perfusion in a bioreactor system and immersion-agitation on an orbital shaker with the use of various detergents (SDS, Triton X-100) in different concentrations and freezing. Acellular scaffolds and tissue engineered constructs have been characterized and compared using morphological methods. Models using decellularized matrix have certain advantages, such as maintaining native extracellular matrix properties and biomimetic microenvironment for cancer cells; compatibility with multiple cell types for cell culture and drug screening; utilization to culture patient-derived cells in vitro to evaluate different anticancer therapeutics for developing personalized medicines.

Keywords: 3D models, decellularization, drug discovery, drug toxicity, scaffolds, spheroids, tissue engineering

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Authors: Anne Tetens, Susan Andersen, Lars Ole Bonde, Pia Jeppesen, Katrine Rich Madsen

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Background: The World Health Organization (WHO) has emphasized the critical need for feasible and effective school-based mental health promotion interventions. High-quality music education in school has been suggested to promote well-being, inclusion, and positive relations, which are essential for children’s mental health. This study explores the potential of choir singing as a distinct approach to enhance children’s mental health within the school setting. ‘Everyone Can Sing’ is a class-based mental health promotion intervention for children in grades 0-3 (ages 5-10) in Danish primary school, which integrates choir singing into the students’ normal school schedule twice a week to promote mental health through the increase of school well-being, class coherence and social inclusion. The intervention uses trained choir leaders to lead the lessons in close collaboration with the class teacher, placing a distinct emphasis on well-being and the inclusive aspect of musical expression through body and voice. Aim: The aim of the study is to evaluate the feasibility of the Everyone Can Sing intervention with the specific objective to assess implementation and changes in mental health parameters, including school well-being, class coherence and social inclusion. Methodologies: The study is a feasibility study of a one-year intervention, which started in January 2024 and is being implemented in grades 0-3 (ages 5-10) across three different Danish primary schools. It is designed according to a mixed methods approach, including both quantitative and qualitative methods. Baseline questionnaires were obtained from students, parents and teachers, and follow-up is planned at 12 months. Participant observations of class choir and individual and group interviews with students, teachers, choir leaders, and school management are collected during the intervention period. The study uses the validated ‘Strengths and Difficulties Questionnaire’ for parent- and teacher-reports. The student questionnaire, which assesses school well-being, class coherence, social inclusion and indicators of mental health, was developed and validated for this study. Participant observations and interviews provide in-depth insights into the implementation process and participants’ experiences of the mental health-promoting potential of the intervention. Findings: The study included 41 classes across three schools (N=904) and questionnaire data from students (n=845, = 93%), teachers (n=890, = 98%), and parents (n=608, = 67%) at baseline. Follow-up data will be obtained in January 2025. While collection and analyses of data are still ongoing, preliminary implementation findings based on interviews and observations indicate high levels of engagement and acceptability. At 6 months into the intervention period, the study protocol is on track and suggests that the intervention is well-received. Further findings and analyses will be presented. The final results of the study will be used to decide whether the AKS intervention should proceed to a future, full-size effectiveness trial, return to refinement of the intervention or the evaluation design, or stop. Contributions: This study will provide valuable insights into new approaches to school-based mental health promotion initiatives. If feasible, the vision is to implement the intervention or elements of it in primary schools across all five Danish regions, potentially lowering the mental health burden.

Keywords: child mental health, early childhood, mental health promotion, mixed methods research, school-based intervention.

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Authors: Anna Paola Micheli, Anna Maria Calce, Loris Di Nallo

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Sustainable finance identifies the process that leads, in the adoption of investment decisions, to take into account environmental and social factors, with the aim of orienting investments towards sustainable and long-term activities. Considering that the topic is at the center of the interest of national agendas, long-term investments will no longer be analyzed only by looking at financial data, but environmental, social, and governance (ESG) factors will be increasingly important and will play a fundamental role in determining the risk and return of an investment. Although this perspective does not deny the orientation to profit, ESG mutual funds represent sustainable finance applied to the world of mutual funds. So the goal of this paper is to verify this attitude, in particular in the energy sector. The choice of the sector is not casual: ESG is the acronym for environmental, social, and governance, and energy companies are strictly related to the environmental theme. The methodology adopted leads to a comparison between a sample of ESG funds and a sample of ESG funds with similar characteristics, using the most important indicators of literature: yield, standard deviation, and Sharpe index. The analysis is focused on equity funds. Results that are partial, due to the lack of historicity, show a good performance of ESG funds, testifying how a sustainable approach does not necessarily mean lower profits. It is clear that these first findings do not involve an absolute preference for ESG funds in terms of performance because the persistence of results is requested. Furthermore, these findings are to be verified in other sectors and in bond funds.

Keywords: mutual funds, ESG, performance, energy

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Authors: Tanka Nath Dahal

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Community-based forestry is seen as a promising instrument for sustainable forest management (SFM) through the purposeful involvement of local communities. Globally, forest area managed by local communities is on the rise. However, transferring management responsibilities to forest users alone cannot guarantee the sustainability of forest management. A monitoring tool, that allows the local communities to track the progress of forest management towards the goal of sustainability, is essential. A case study, including six forest user groups (FUGs), two from each three community-based forestry models—community forestry (CF), buffer zone community forestry (BZCF), and collaborative forest management (CFM) representing three different physiographic regions, was conducted in Nepal. The study explores which community-based forest management model (CF, BZCF or CFM) is doing well in terms of sustainable forest management. The study assesses the overall performance of the three models towards SFM using locally developed criteria (four), indicators (26) and verifiers (60). This paper attempts to quantify the sustainability of the models using sustainability index for individual criteria (SIIC), and overall sustainability index (OSI). In addition, rating to the criteria and scoring of the verifiers by the FUGs were done. Among the four criteria, the FUGs ascribed the highest weightage to institutional framework and governance criterion; followed by economic and social benefits, forest management practices, and extent of forest resources. Similarly, the SIIC was found to be the highest for the institutional framework and governance criterion. The average values of OSI for CFM, CF, and BZCF were 0.48, 0.51 and 0.60 respectively; suggesting that buffer zone community forestry is the more sustainable model among the three. The study also suggested that the SIIC and OSI help local communities to quantify the overall progress of their forestry practices towards sustainability. The indices provided a clear picture of forest management practices to indicate the direction where they are heading in terms of sustainability; and informed the users on issues to pay attention to enhancing the sustainability of their forests.

Keywords: community forestry, collaborative management, overall sustainability, sustainability index for individual criteria

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Authors: Ahmad Dahlan, Aries Indrianto

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Conceptually, mudarabah is the practice of fiqh (jurisprudence) in the bank institutions business that became the basis of the economic development model of modern Islamic financial system. In mudarabah, profit and loss sharing mechanism are integrated between mudarabah on liability side (funding) with mudarabah on the asset side (financing). Islamic (Sharia) Bank is positioned as an intermediary institution like investment manager, although the bank is also involved in direct investment based on bank equity. In practice, mudarabah cannot be done as much as effective at financing because the dominance of debt-financing products. This is a major criticism among experts and Islamic banks practitioners. Ironically, the criticism gets less attention by practitioners of Islamic banks due to many factors. The epistemologies of Islamic banks prioritize shareholder values than stakeholder values, and social culture that has not been ready with the mudarabah totally.

Keywords: two tier mudarabah, intermediary institution, shareholder value, stakeholder value

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Authors: Habib Akbarzadeh Bengar, Mohammad Asadi Kiadehi, Ali Rameeh

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The result of the past earthquakes has shown that insufficient amount of stirrups and brittle behavior of concrete lead to the shear and flexural failure in reinforced concrete (RC) members. In this paper, an analytical model proposed to predict the nonlinear behavior of RC and SFRC elements and frames. In this model, some important parameter such as shear effect, varying axial load, and longitudinal bar buckling are considered. The results of analytical model were verified with experimental tests. The results of verification have shown that the proposed analytical model can predict the nonlinear behavior of RC and SFRC members and also frames accurately. In addition, the results have shown that use of steel fibers increased bearing capacity and ductility of RC frame. Due to this enhancement in shear strength and ductility, insufficient amount of stirrups, which resulted in shear failure, can be offset with usage of the steel fibers. In addition to the steps taken, to analyze the effects of fibers percentages on the bearing capacity and ductility of frames parametric studies have been performed to investigate of these effects.

Keywords: nonlinear analysis, SFRC frame, shear failure, varying an axial load

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Authors: Tugba Bayoglu

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Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

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Authors: Zohreh Khojasteh-Ghamari, Takashi Irohara

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One of the efficient ways in supply chain risk management is avoiding the interruption in Supply Chain (SC) before it occurs. Although the majority of the organizations focus on their first-tier suppliers to avoid risk in the SC, studies show that in only 60 percent of the disruption cases the reason is first tier suppliers. In the 40 percent of the SC disruptions, the reason is downstream SC, which is the second tier and lower. Due to the increasing complexity and interrelation of modern supply chains, the SC elements have become difficult to trace. Moreover, studies show that there is a vital need to better understand the integration of risk and visibility, especially in the context of multiple objectives. In this study, we propose a multi-objective programming model to avoid disruption in SC. The objective of this study is evaluating the effect of downstream SCV on managing supply chain risk. We propose a multi-objective mathematical programming model with the objective functions of minimizing the total cost and maximizing the downstream supply chain visibility (SCV). The decision variable is supplier selection. We assume there are several manufacturers and several candidate suppliers. For each manufacturer, our model proposes the best suppliers with the lowest cost and maximum visibility in downstream supply chain. We examine the applicability of the model by numerical examples. We also define several scenarios for datasets and observe the tendency. The results show that minimum visibility in downstream SC is needed to have a safe SC network.

Keywords: downstream supply chain, optimization, supply chain risk, supply chain visibility

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Authors: Hamed Saremi, Suzan Taghavy, Seyed Mohammad Hanif Sanjari, Mostafa Kahali

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One of the challenges in manufacturing and service companies to provide a product or service is recognized Brand to consumers in target markets. They provide most of their processes under the same capacity. But the constant threat of devastating internal and external resources to prevent a rise Brands and more companies are recognizing the stages are bankrupt. This paper has tried to identify and analyze effective indicators of brand equity and focuses on indicators and presents a model of intelligent create a model to prevent possible damage. In this study, the identified indicators of brand equity are based on literature study and according to expert opinions, set of indicators By techniques DEMATEL Then to used Multi-Step Adaptive Neural-Fuzzy Inference system (ANFIS) to design a multi-stage intelligent system for assessment of brand equity.

Keywords: brand, cosmetic product, ANFIS, DEMATEL

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Authors: M. A. Tayfun, M. A. Alkhalidi

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The exact theoretical expression describing the probability distribution of nonlinear sea-surface elevations derived from the second-order narrowband model has a cumbersome form that requires numerical computations, not well-disposed to theoretical or practical applications. Here, the same narrowband model is re-examined to develop a simpler closed-form approximation suitable for theoretical and practical applications. The salient features of the approximate form are explored, and its relative validity is verified with comparisons to other readily available approximations, and oceanic data.

Keywords: ocean waves, probability distributions, second-order nonlinearities, skewness coefficient, wave steepness

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Authors: Kushaal Selvarajah, Geetha Annavi, Mohd Noor Hisham Mohd Nadzir

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Sambar deer (Rusa unicolor) was uplisted from Least Concern to Vulnerable by the International Union for Conservation of Nature Red list in 2015 due to drastic population decline in the wild throughout its geographical range. Sambar deer is a valued prey for the highly endangered species such as the Malayan tiger. Ex-situ conservation efforts, i.e., captive breeding, initiated by local government to boost sambar deer numbers in captivity and to reintroduce into the wild to support a higher number of tigers, consistent with the goal of our National Tiger Conservation Action Plan. The reproductive success of sambar deer and their welfare management practices in captivity are important components for effective captive breeding programs. However, there is a lack of study carried out on sambar deer in recent years and their behavior in captivity. Three captive sites (Zoo Negara, Zoo Taiping, and Sungkai Conservation Centre) were selected and observed for an average of 40 days each site (6 hours/day). A Generalized Linear Model (GLM) was used to determine the correlation between social behavior and extrinsic parameters. A comparison between all three captive sites showed the strongest correlation in behavioral variability, followed by a time of observation. This proves that there is a difference between in behavioral consistency and frequency between herds across captive sites rising to the possibility of external factors that are influential. Time of day of observation also had significant influence on certain extrinsic parameters being skewed to morning observations and this could be due to an adaptive behavior to the feeding time in the captive sites being in the morning which caused the deer to be resting towards the afternoon. Extensive study need to be done on sambar deer to pinpoint the specifics and better understanding of these possible influential factors in their behavior.

Keywords: behaviour ecology, captivity, ex-situ conservation, husbandry

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Authors: Wipassorn Vinicchayakul, Pichaya Supanakoon, Sathaporn Promwong

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A human’s hand localization is revised by using radar cross section (RCS) measurements with a minimum root mean square (RMS) error matching algorithm on a touchless keypad mock-up model. RCS and frequency transfer function measurements are carried out in an indoor environment on the frequency ranged from 3.0 to 11.0 GHz to cover federal communications commission (FCC) standards. The touchless keypad model is tested in two different distances between the hand and the keypad. The initial distance of 19.50 cm is identical to the heights of transmitting (Tx) and receiving (Rx) antennas, while the second distance is 29.50 cm from the keypad. Moreover, the effects of Rx angles relative to the hand of human factor are considered. The RCS input parameters are compared with power loss parameters at each frequency. From the results, the performance of the RCS input parameters with the second distance, 29.50 cm at 3 GHz is better than the others.

Keywords: radar cross section, fingerprint-based localization, minimum root mean square (RMS) error matching algorithm, touchless keypad model

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Authors: Dawit Abay Tesfamariam

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Ethiopia’s Climate- Resilient Green Economy strategy focuses mainly on generating and utilization of Renewable Energy (RE). The data collected in 2016 by Ethiopian Electric Power (EEP) indicates that the intermittent RE sources on the grid from solar and wind energy were only 8 % of the total energy produced. On the other hand, the EEP electricity generation plan in 2030 indicates that 36 % of the energy generation share will be covered by solar and wind sources. Thus, a case study was initiated to model and compute the balance and consumption of electricity in three different scenarios: 2016, 2025, and 2030 using the Energy PLAN Model (EPM). Initially, the model was validated using the 2016 annual power-generated data to conduct the EPM analysis for two predictive scenarios. The EPM simulation analysis using EPM for 2016 showed that there was no significant excess power generated. Hence, the model’s results are in line with the actual 2016 output. Thus, the EPM was applied to analyze the role of energy storage in RE in Ethiopian grid systems. The results of the EPM simulation analysis showed there will be excess production of 402 /7963 MW average and maximum, respectively, in 2025. The excess power was dominant in all months except in the three rainy months of the year (June, July, and August). Consequently, based on the validated outcomes of EPM indicates, there is a good reason to think about other alternatives for the utilization of excess energy and storage of RE. Thus, from the scenarios and model results obtained, it is realistic to infer that; if the excess power is utilized with a storage mechanism that can stabilize the grid system; as a result, the extra RE generated can be exported to support the economy. Therefore, researchers must continue to upgrade the current and upcoming energy storage system to synchronize with RE potentials that can be generated from RE.

Keywords: renewable energy, storage, wind, energyplan

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Authors: Tatiana G. Smirnova, Stan G. Benjamin

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Rapid Update Cycle (RUC) land surface model (LSM) was a land-surface component in several generations of operational weather prediction models at the National Center for Environment Prediction (NCEP) at the National Oceanic and Atmospheric Administration (NOAA). It was designed for short-range weather predictions with an emphasis on severe weather and originally was intentionally simple to avoid uncertainties from poorly known parameters. Nevertheless, the RUC LSM, when coupled with the hourly-assimilating atmospheric model, can produce a realistic evolution of time-varying soil moisture and temperature, as well as the evolution of snow cover on the ground surface. This result is possible only if the soil/vegetation/snow component of the coupled weather prediction model has sufficient skill to avoid long-term drift. RUC LSM was first implemented in the operational NCEP Rapid Update Cycle (RUC) weather model in 1998 and later in the Weather Research Forecasting Model (WRF)-based Rapid Refresh (RAP) and High-resolution Rapid Refresh (HRRR). Being available to the international WRF community, it was implemented in operational weather models in Austria, New Zealand, and Switzerland. Based on the feedback from the US weather service offices and the international WRF community and also based on our own validation, RUC LSM has matured over the years. Also, a sea-ice module was added to RUC LSM for surface predictions over the Arctic sea-ice. Other modifications include refinements to the snow model and a more accurate specification of albedo, roughness length, and other surface properties. At present, RUC LSM is being tested in the regional application of the Unified Forecast System (UFS). The next generation UFS-based regional Rapid Refresh FV3 Standalone (RRFS) model will replace operational RAP and HRRR at NCEP. Over time, RUC LSM participated in several international model intercomparison projects to verify its skill using observed atmospheric forcing. The ESM-SnowMIP was the last of these experiments focused on the verification of snow models for open and forested regions. The simulations were performed for ten sites located in different climatic zones of the world forced with observed atmospheric conditions. While most of the 26 participating models have more sophisticated snow parameterizations than in RUC, RUC LSM got a high ranking in simulations of both snow water equivalent and surface temperature. However, ESM-SnowMIP experiment also revealed some issues in the RUC snow model, which will be addressed in this paper. One of them is the treatment of grid cells partially covered with snow. RUC snow module computes energy and moisture budgets of snow-covered and snow-free areas separately by aggregating the solutions at the end of each time step. Such treatment elevates the importance of computing in the model snow cover fraction. Improvements to the original simplistic threshold-based approach have been implemented and tested both offline and in the coupled weather model. The detailed description of changes to the snow cover fraction and other modifications to RUC soil and snow parameterizations will be described in this paper.

Keywords: land-surface models, weather prediction, hydrology, boundary-layer processes

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Authors: Girish Chavadappanavar

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The impact of climate on agriculture could result in problems with food security and may threaten the livelihood activities upon which much of the population depends. In the present study, the development of a statistical yield forecast model has been carried out for sugarcane production over Belagavi district, Karnataka using weather variables of crop growing season and past observed yield data for the period of 1971 to 2010. The study shows that this type of statistical yield forecast model could efficiently forecast yield 5 weeks and even 10 weeks in advance of the harvest for sugarcane within an acceptable limit of error. The performance of the model in predicting yields at the district level for sugarcane crops is found quite satisfactory for both validation (2007 and 2008) as well as forecasting (2009 and 2010).In addition to the above study, the climate variability of the area has also been studied, and hence, the data series was tested for Mann Kendall Rank Statistical Test. The maximum and minimum temperatures were found to be significant with opposite trends (decreasing trend in maximum and increasing in minimum temperature), while the other three are found in significant with different trends (rainfall and evening time relative humidity with increasing trend and morning time relative humidity with decreasing trend).

Keywords: climate impact, regression analysis, yield and forecast model, sugar models

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Authors: Cecília M. Antão, Paulo Jorge Nogueira

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Breast cancer (BC) is the first cause of cancer mortality among Portuguese women. This retrospective observational study aimed at identifying comorbidities associated with BC female patients admitted to Portuguese public hospitals (2010-2018), investigating the effect of comorbidities on BC mortality rate, and building a predictive model using logistic regression. Results showed that the BC mortality in Portugal decreased in this period and reached 4.37% in 2018. Adjusted odds ratio indicated that secondary malignant neoplasms of liver, of bone and bone marrow, congestive heart failure, and diabetes were associated with an increased chance of dying from breast cancer. Although the Lisbon district (the most populated area) accounted for the largest percentage of BC patients, the logistic regression model showed that, besides patient’s age, being resident in Bragança, Castelo Branco, or Porto districts was directly associated with an increase of the mortality rate.

Keywords: breast cancer, comorbidities, logistic regression, adjusted odds ratio

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Authors: Yushuai Wang, Feng Xu, Junbo Tan, Xueqian Wang, Bin Liang

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In this paper, a sensor fault-tolerant control (FTC) scheme using robust model predictive control (RMPC) and set theoretic fault detection and isolation (FDI) is extended to linear parameter varying (LPV) systems. First, a group of set-valued observers are designed for passive fault detection (FD) and the observer gains are obtained through minimizing the size of invariant set of state estimation-error dynamics. Second, an input set for fault isolation (FI) is designed offline through set theory for actively isolating faults after FD. Third, an RMPC controller based on state estimation for LPV systems is designed to control the system in the presence of disturbance and measurement noise and tolerate faults. Besides, an FTC algorithm is proposed to maintain the plant operate in the corresponding mode when the fault occurs. Finally, a numerical example is used to show the effectiveness of the proposed results.

Keywords: fault detection, linear parameter varying, model predictive control, set theory

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Authors: Majid Galoie, Khodadad Safavi, Abdolreza Karami Nejad, Reza Roshan

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Scour downstream of a flip bucket in a plunge pool is caused by impingement of water jet force. In order to reduce this force and consequently reduce scour hole depth, flip buckets may equip by dents. The minimum scour hole depth might be occurred by optimization of dents (number, shape, placement) on flip buckets. In this study, a comprehensive physical model has been developed and various options for dents have been investigated. The experimental data for each dent option such as scour hole depth, angle of impingement jet, piezometric pressure in tail-water and jet trajectory have been measured for various discharges. Finally, the best option can be found by analysis of the experimental results which has been expressed in this paper.

Keywords: scouring process, plunge pool, scour hole depth, physical model, flip bucket

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Authors: Christoph Köster

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Supplier selection is one of the key challenges in supply chain management and can be considered a multi-criteria decision-making (MCDM) problem. In the 1960s, it evolved from considering only economic criteria, such as price, quality, and performance, to including environmental and social criteria nowadays. Although receiving considerable attention from scholars and practitioners over the past decades, existing research has not considered governance criteria so far. This is, however, surprising, as ESG (environmental, social, and governance) criteria have gained considerable attention. In order to complement ESG criteria in the supplier selection process, this study investigates German DAX and MDAX companies and evaluates the impact of governance criteria along their supplier selection process. Moreover, it proposes a set of criteria for the respective process steps. Specifically, eleven criteria for the first process step and five criteria for the second process step are identified. This paper contributes to a better understanding of the supplier selection process by elucidating the relevance of governance criteria in the supplier selection process and providing a set of empirically developed governance criteria. These results can be applied by practitioners to complement the criteria set in the supplier selection process and thus balance economic, environmental, social, and governance targets.

Keywords: ESG, governance, sustainable supplier selection, sustainability

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Authors: Muhammad Abu-Khaizaran, Ahmad Faza’, Tariq Othman, Yahia Yousef

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This paper presents a study to provide sufficient and reliable information about constructing a Photovoltaic energy profile of the Birzeit University campus (BZU) based on the weather forecast. The developed Photovoltaic energy profile helps to predict the energy yield of the Photovoltaic systems based on the weather forecast and hence helps planning energy production and consumption. Two models will be developed in this paper; a Clear Sky Irradiance model and a Cloud-Cover Radiation model to predict the irradiance for a clear sky day and a cloudy day, respectively. The adopted procedure for developing such models takes into consideration two levels of abstraction. First, irradiance and weather data were acquired by a sensory (measurement) system installed on the rooftop of the Information Technology College building at Birzeit University campus. Second, power readings of a fully operational 51kW commercial Photovoltaic system installed in the University at the rooftop of the adjacent College of Pharmacy-Nursing and Health Professions building are used to validate the output of a simulation model and to help refine its structure. Based on a comparison between a mathematical model, which calculates Clear Sky Irradiance for the University location and two sets of accumulated measured data, it is found that the simulation system offers an accurate resemblance to the installed PV power station on clear sky days. However, these comparisons show a divergence between the expected energy yield and actual energy yield in extreme weather conditions, including clouding and soiling effects. Therefore, a more accurate prediction model for irradiance that takes into consideration weather factors, such as relative humidity and cloudiness, which affect irradiance, was developed; Cloud-Cover Radiation Model (CRM). The equivalent mathematical formulas implement corrections to provide more accurate inputs to the simulation system. The results of the CRM show a very good match with the actual measured irradiance during a cloudy day. The developed Photovoltaic profile helps in predicting the output energy yield of the Photovoltaic system installed at the University campus based on the predicted weather conditions. The simulation and practical results for both models are in a very good match.

Keywords: clear-sky irradiance model, cloud-cover radiation model, photovoltaic, weather forecast

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Authors: Taki Eddine Seghier, Mohd Hamdan Ahmad, Yaik-Wah Lim, Samuel Opeyemi Williams

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The assessment of building sustainability to achieve a specific green benchmark and the preparation of the required documents in order to receive a green building certification, both are considered as major challenging tasks for green building design team. However, this labor and time-consuming process can take advantage of the available Building Information Modeling (BIM) features such as material take-off and scheduling. Furthermore, the workflow can be automated in order to track potentially achievable credit points and provide rating feedback for several design options by using integrated Visual Programing (VP) to handle the stored parameters within the BIM model. Hence, this study proposes a BIM-based tool that uses Green Building Index (GBI) rating system requirements as a unique input case to evaluate the building sustainability in the design stage of the building project life cycle. The tool covers two key models for data extraction, firstly, a model for data extraction, calculation and the classification of achievable credit points in a green template, secondly, a model for the generation of the required documents for green building certification. The tool was validated on a BIM model of residential building and it serves as proof of concept that building sustainability assessment of GBI certification can be automatically evaluated and documented through BIM.

Keywords: green building rating system, GBRS, building information modeling, BIM, visual programming, VP, sustainability assessment

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Authors: Rebecca Laycock

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Many Urban Agriculture (UA) initiatives, including community/allotment gardens, Community Supported Agriculture, and community/social farms, depend on volunteers. However, initiatives supported or run by volunteers are often faced with a high turnover of labour as a result of the involvement of episodic volunteers (a term describing ad hoc, one-time, and seasonal volunteers), leading to challenges with maintaining project continuity and retaining skills/knowledge within the initiative. This is a notable challenge given that food growing is a knowledge intensive activity where the fruits of labour appear months or sometimes years after investment. Participatory Action Research (PAR) is increasingly advocated for in the field of UA as a solution-oriented approach to research, providing concrete results in addition to advancing theory. PAR is a cyclical methodological approach involving researchers and stakeholders collaboratively 'identifying' and 'theorising' an issue, 'planning' an action to address said issue, 'taking action', and 'reflecting' on the process. Through iterative cycles and prolonged engagement, the theory is developed and actions become better tailored to the issue. The demand for PAR in UA research means that understanding how to use PAR with episodic volunteers is of critical importance. The aim of this paper is to explore (1) the challenges of doing PAR in UA initiatives with episodic volunteers, and (2) how PAR can be harnessed to advance sustainable development of UA through theoretically-informed action. A 2.5 year qualitative PAR study on three English case study student-led food growing initiatives took place between 2014 and 2016. University UA initiatives were chosen as exemplars because most of their volunteers were episodic. Data were collected through 13 interviews, 6 workshops, and a research diary. The results were thematically analysed through eclectic coding using Computer-Assisted Qualitative Data Analysis Software (NVivo). It was found that the challenges of doing PAR with transient participants were (1) a superficial understanding of issues by volunteers because of short term engagement, resulting in difficulties ‘identifying’/‘theorising’ issues to research; (2) difficulties implementing ‘actions’ given those involved in the ‘planning’ phase often left by the ‘action’ phase; (3) a lack of capacity of participants to engage in research given the ongoing challenge of maintaining participation; and (4) that the introduction of the researcher acted as an ‘intervention’. The involvement of a long-term stakeholder (the researcher) changed the group dynamics, prompted critical reflections that had not previously taken place, and improved continuity. This posed challenges for providing a genuine understanding the episodic volunteering PAR initiatives, and also challenged the notion of what constitutes an ‘intervention’ or ‘action’ in PAR. It is recommended that researchers working with episodic volunteers using PAR should (1) adopt a first-person approach by inquiring into the researcher’s own experience to enable depth in theoretical analysis to manage the potentially superficial understandings by short-term participants; and (2) establish safety mechanisms to address the potential for the research to impose artificial project continuity and knowledge retention that will end when the research does. Through these means, we can more effectively use PAR to conduct solution-oriented research about UA.

Keywords: community garden, continuity, first-person research, higher education, knowledge retention, project management, transience, university

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Authors: Vahid Nourani, Atefeh Ashrafi

Abstract:

Prediction of treated wastewater quality is a matter of growing importance in water treatment procedure. In this way artificial neural network (ANN), as a robust data-driven approach, has been widely used for forecasting the effluent quality of wastewater treatment. However, developing ANN model based on appropriate input variables is a major concern due to the numerous parameters which are collected from treatment process and the number of them are increasing in the light of electronic sensors development. Various studies have been conducted, using different clustering methods, in order to classify most related and effective input variables. This issue has been overlooked in the selecting dominant input variables among wastewater treatment parameters which could effectively lead to more accurate prediction of water quality. In the presented study two ANN models were developed with the aim of forecasting effluent quality of Tabriz city’s wastewater treatment plant. Biochemical oxygen demand (BOD) was utilized to determine water quality as a target parameter. Model A used Principal Component Analysis (PCA) for input selection as a linear variance-based clustering method. Model B used those variables identified by the mutual information (MI) measure. Therefore, the optimal ANN structure when the result of model B compared with model A showed up to 15% percent increment in Determination Coefficient (DC). Thus, this study highlights the advantage of PCA method in selecting dominant input variables for ANN modeling of wastewater plant efficiency performance.

Keywords: Artificial Neural Networks, biochemical oxygen demand, principal component analysis, mutual information, Tabriz wastewater treatment plant, wastewater treatment plant

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