Search results for: attack risk

Authors: Hiba Dakroub, Danilo Russo, Luca Cistrone, Francesco Serra, Giovanna Fusco, Esterina De Carlo, Maria Grazia Amoroso

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The question of the origin of SARS-CoV-2 and the cycle of transmission between humans and animals is still unanswered. One serious concern associated with the SARS-CoV-2 pandemic is that the virus might spill back from humans to wildlife, which would render some animal species reservoirs of the human virus. The aim of the present study is to monitor the potential risk of SARS-CoV-2 reverse infection from humans to bats, by performing bat surveillance from different sites in Central-Southern Italy. We collected 240 droppings or saliva from 129 bats and tested them using specific and general primers of SARS-COV-2 and coronaviruses respectively. All samples, including 127 nasal swabs and 113 fecal droppings resulted negative for SARS-COV-2, and these results were confirmed by testing the samples with the Droplet Digital PCR. Also, an end-point RT-PCR was performed and no sample showed specific bands. The absence of SARS-CoV-2 in the bats we surveyed is a first step towards a better understanding of reverse transmission to bats of this virus. We hope our first contribution will encourage the establishment of systematic surveillance of wildlife, and specifically bats, to help prevent reverse zoonotic episodes that would jeopardize human health as well as biodiversity conservation and management.

Keywords: coronaviruses, bats, zoonotic viruses, spillback, SARS-CoV-2

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Authors: Priya Kedia, Kiranmoy Das

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There is a rich literature on variable selection in regression setting. However, most of these methods assume normality for the response variable under consideration for implementing the methodology and establishing the statistical properties of the estimates. In many real applications, the distribution for the response variable may be non-Gaussian, and one might be interested in finding the best subset of covariates at some predetermined quantile level. We develop dynamic Bayesian approach for variable selection in quantile regression framework. We use a zero-inflated mixture prior for the regression coefficients, and consider the asymmetric Laplace distribution for the response variable for modeling different quantiles of its distribution. An efficient Gibbs sampler is developed for our computation. Our proposed approach is assessed through extensive simulation studies, and real application of the proposed approach is also illustrated. We consider the data from health and retirement study conducted by the University of Michigan, and select the important predictors when the outcome of interest is out-of-pocket medical cost, which is considered as an important measure for financial risk. Our analysis finds important predictors at different quantiles of the outcome, and thus enhance our understanding on the effects of different predictors on the out-of-pocket medical cost.

Keywords: variable selection, quantile regression, Gibbs sampler, asymmetric Laplace distribution

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Authors: Nadia Elouaer

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Tax revenue is the main state resource and one of the important variables in tax policy. Nevertheless, this resource is continually decreasing, so it is important to focus on the reasons for this decline. Several studies show that the taxpayer is reluctant to pay taxes, especially in countries at risk or in countries in transition, including Tunisia. This study focuses on the tax evasion behavior of a Tunisian taxpayer under the influence of his political beliefs, as well as the influence of different tax compliance variables. Using a questionnaire, a sample of 500 Tunisian taxpayers is used to examine the relationship between political beliefs and taxpayer affiliations and tax compliance variables, as well as the study of the causal link between political beliefs and fraudulent behavior. The data were examined using correlation, factor, and regression analysis and found a positive and statistically significant relationship between the different tax compliance variables and the tax evasion behavior. There is also a positive and statistically significant relationship between tax evasion and political beliefs and affiliations. The study of the relationship between political beliefs and compliance variables shows that they are closely related. The conclusion is to admit that tax evasion and political beliefs are closely linked, and the government should update its tax policy and modernize its administration in order to strengthen the credibility and disclosure of information in order to restore a relationship of trust between public authorities and the taxpayer.

Keywords: fiscal policy, political beliefs, tax evasion, taxpayer behavior

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Authors: Hien T. T. Ho, Tsunemi Watanabe

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The regulatory and market pressures on the restriction of nonylphenol and its ethoxylates in textile articles have confronted the textile manufacturers, particularly those in developing countries. This study aimed to examine the tentative behavior of the textile manufacturers in Vietnam from the perspectives of attitude and the perceptions of technical and organizational adaptabilities, risks, benefits, and barriers. Personal interviews were conducted with five technical specialists from four textile firms and one chemical supplier. The environmental regulatory and market situations regarding the chemical use in Vietnam were also described. The findings revealed two main opposing trends of chemical substitution depending on the market orientation of firms that governed the patterns of risk and benefit perception. The indirect influence of perceived adaptabilities on firm tentative behavior through perceived risks was elucidated, which initiated a conceptual model of firm’s behavior combining the organizational-based and the rational-based relationships. The intermediary role of non-governmental textile and garment industrial/ trade associations is highlighted to strengthen private firm’s informative capacity.

Keywords: firm behavior, institutional analysis, organizational adaptation, technical adaptation

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Authors: Hesham Osman

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The challenges facing aging urban infrastructure systems require a more holistic and comprehensive approach to their management. The large number of urban infrastructure renewal activities occurring in cities throughout the world leads to social, economic and environmental impacts on the communities in its vicinity. As such, a coordinated effort is required to streamline these activities. This paper presents a framework to enable temporal (time-based) coordination of water, sewer and road intervention activities. Intervention activities include routine maintenance, renewal, and replacement of physical assets. The coordination framework considers 1) Life-cycle costs, 2) Infrastructure level-of-service, and 3) Risk exposure to system operators. The model enables infrastructure asset managers to trade-off options of delaying versus bringing forward intervention activities of one system in order to be executed in conjunction with another co-located system in the right-of-way. The framework relies on a combination of meta-heuristics and goal-based optimization. In order to demonstrate the applicability of the framework, a case study for a major infrastructure corridor in Cairo, Egypt is taken as an example. Results show that the framework can be scaled-up to include other infrastructure systems located in the right-of-way like electricity, gas and telecom, provided that information can be shared among these entities.

Keywords: infrastructure, rehabilitation, construction, optimization

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

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Authors: Fahad Al Beyahi, Justin Thomas, Md Mamunur Rashid

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Various definitions of digital well-being have emerged in recent years, most of which center on the impacts -beneficial and detrimental- of digital technology on health and well-being (psychological, social, and financial). Other definitions go further, emphasizing the attainment of balance, viewing digital well-being as wholly subjective, the individual’s perception of optimal balance between the benefits and ills associated with online connectivity. Based on this broad conceptualization of digital well-being, we undertook a global survey measuring various dimensions of this emerging construct. The survey was administered across 35 nations and 7 world regions, with 1000 participants within each territory (N= 35000). Along with attitudinal, behavioral, and sociodemographic variables, the survey included measures of depression, anxiety, problematic social media use, gaming disorder, and other relevant metrics. Coupled with nation-level policy audits, these data were used to create a multinational (global) digital well-being index. Nations are ranked based on various dimensions of digital well-being, and predictive models are used to identify resilience and risk factors for problem technology use. In this paper, we will discuss key findings from the survey and the index. This work can inform public policy and shape our responses to the emerging implications of lives increasingly lived online and interconnected with digital technology.

Keywords: technology, health, behavioral addiction, digital wellbeing

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Authors: Ilhan Keskin, Hasan Bulent Kantarci

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In this study, one of the tools of Islamic financing known as “Sukuk” a non-interest bearing investment which has started to be implemented in Turkey and the world as a whole is discussed. In order to increase the vitality and efficiency of the economy, by taking lessons from the recent economic crisis new developments in the banking and investment sector are being expanded. The purpose of all investors is to obtain more revenue through the use of capital. The inability of traditional investment tools to meet the expectations of investors and the interest based financial system where one investor benefits at the expense of another there has been the need for a different, reliable and non-interest bearing financial market that is consistent with the Islamic rule. As a result an alternative and more reliable interest free financing tool “Sukuk” rental certificates covering people who are sensitive to Islamic rules, appeal to all segments, hidden remaining capital that contributes to the economy, reduce disparities in income distribution, common risk sharing system of profit and loss sharing has emerged. Today, for the structural countries by examining the state of the world market economy the applicability, enactment and future issues associated with this attractive kind of Islamic finance namely the “Sukuk” market has been explained.

Keywords: Islamic finance, islamic markets, non-interest bearing, rental certificates

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Authors: Nyasha Agnes Gurira, Petronella Katekwe

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Traditional management systems (TMS) are a vital source of knowledge for conserving cultural and natural heritage. TMS’s are renowned for their ability to preserve both tangible and intangible manifestations of heritage. They are a construct of the intricate relationship that exists between heritage and host communities, where communities are recognized as owners of heritage and so, set up management mechanisms to ensure its adequate conservation. Multiple heritage condition surveys were conducted to assess the effectiveness of using TMS in the conservation of both natural and cultural heritage. Surveys were done at Nharira Hills, Mahwemasimike, Dzimbahwe, Manjowe Rock art sites and Norumedzo forest which are heritage places in Zimbabwe. It assessed the state of conservation of the five case studies and assessed the role that host communities play in the management of these heritage places. It was revealed that TMS’s are effective in the conservation of natural heritage, however in relation to heritage forms with cultural manifestations, there are major disparities. These range from differences in appreciation and perception of value within communities leading to vandalism, over emphasis in the conservation of the intangible element as opposed to the tangible. This leaves the tangible element at risk. Despite these issues, TMS are a reliable knowledge base which enables more holistic conservation approaches for cultural and natural heritage.

Keywords: communities, cultural intangible, tangible heritage, traditional management systems, natural

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Authors: Sungwoo Park

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The paper attempts to investigate the correlation between climate change and migration that has caused violent disputes in some regions of the world. Recently, NGOs and educational institutions have proposed claims that migratory patterns and violent uprisings are intertwined with climate change. Thus, the paper is primarily concerned with collecting evidences provided from scholars, validating this significant connection between climate change and migration, and evaluating and suggesting current and future research approaches respectively to enhance the acknowledgment and protection of environmental refugees. In order to examine the linkage of environmental migration, primary sources, such as political speeches, and secondary sources like theses from environmental policy analysts, books, and reports are used. More specifically, the investigation focuses on an civil war in Syria to draw a connection between environmental migration and violent dispute that threatens the global security. The examination undertaken specifically analyzes examples where forced migration occurred due to climate change. In Bangladesh, Pakistan, and Kiribati, residents have been at risk of fleeing their countries because of abnormal climate patterns, such as the rise of sea level or an excessive heat stress. As the brutal uprising in Syria has proven that climate change can pose a significant threat to global security, correlation between climate change and migration is surely worth delving into.

Keywords: climate change, climate migration, global security, refugee crisis

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Authors: Jayati Das

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Kolkata, one of the fastest-growing metropolises in India, has been suffering from air pollution for many decades. Mismanagement of government and an increase in automobiles have been fuelling this problem. The study aims to portray the quality of air along with the influence of traffic flow and vehicular growth and the effects on human health. It further shows the correlation between the emission of pollution during weekdays and weekends with the help of a scatter diagram and trend line. An assessment of Kolkata air quality is done where the listed pollutants’ (RPM, SPM, NO2, and SO2) annual average concentrations are classified into four different categories. Our observed association between childhood Acute Respiratory disorder and early life exposure to traffic-related air pollutants is biologically plausible. The period of in utero and the first year of life is critical in the development of the immune and respiratory systems and potentially harmful effects of toxic pollutants during this period might result in the long-lasting impaired capacity to fight infections and increased risk of allergic manifestations. Up-to-date knowledge about the seasonal and spatial variation of asthma and studying the air quality of the area is done through Geographical Information System (GIS). Steps are taken by the government to control air pollution by alternative public transport like the metro and compulsory certification of period-driven vehicles which test for Carbon mono oxide.

Keywords: air pollution, asthma, GIS, hotspots, governance

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Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

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The use of Geographic Information System (GIS) tools in the analysis of traffic crash data can help to identify locations or hotspots with high instances or risk of traffic crashes. The identification of traffic crash hotspots can effectively improve road safety measures. Mapping of road traffic crash hotspots can help the concerned authorities to give priority and take targeted measures and improvements to the road structure at these locations to reduce traffic crashes and fatalities. In Oman, there are countless rural roads that have more risks for traveling vehicles compared to urban roads. The likelihood of traffic crashes as well as fatality rate may increase with the presence of risks that are associated with the rural type of community. In this paper, the traffic crash hotspots on rural roads in Oman are specified using spatial analysis methods in GIS and traffic crash data. These hotspots are ranked based on the frequency of traffic crash occurrence (i.e., number of traffic crashes) and the rate of fatalities. The result of this study presents a map visualization of locations on rural roads with high traffic crashes and high fatalities rates.

Keywords: road safety, rural roads, traffic crash, GIS tools

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Authors: H. Merhni, A. Sbiti, I. Ratbi, A. Sefiani

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The proximal spinal muscular atrophy (SMA) is a group of neuromuscular disorders characterized by progressive muscle weakness due to the degeneration and loss of anterior motor neurons of the spinal cord. Depending on the age of onset of symptoms and their evolution, four types of SMA, varying in severity, result in a mutations of the SMN gene (survival of Motor neuron). We have analyzed the DNA of 295 patients referred to our genetic counseling; since January 1996 until October 2014; for suspected SMA. The homozygous deletion of exon 7 of the SMN gene was found in 133 patients; of which, 40.6% were born to consanguineous parents. In countries like Morocco, where the frequency of heterozygotes for SMA is high, genetic testing should be offered as first-line and, after careful clinical assessment, especially in newborns and infants with congenital hypotonia unexplained and prognosis compromise. The molecular diagnosis of SMA allows a quick and certainly diagnosis, provide adequate genetic counseling for families at risk and suggest, for couples who want prenatal diagnosis. The analysis of the SMN gene is a perfect example of genetic testing with an excellent cost/benefit ratio that can be of great interest in public health, especially in low-income countries. We emphasize in this work for the benefit of the generalization of molecular diagnosis of SMA by the technique of PCR-enzymatic digestion in other centers in Morocco.

Keywords: Exon7, PCR-digestion, SMA, SMN gene

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Authors: Mao Ju

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The system of general counsel (GC) is an important governance structure designed for the construction of state-owned enterprises (SOEs) under the rule of law. This article is based on the setting of mergers and acquisitions (M&As) and takes the efficiency of M&As to examine the implementation effect of the system of GC for SOEs. Research has found that: (1) companies implementing the system of GC for SOEs have higher efficiency in M&As, manifested in better operational and market performance, and this effect depends on the professional ability and power of the GC. This indicates that the GC of SOEs has played a positive role in the decision-making process of M&As, which helps to improve the efficiency of M&As. (2) The impact of the GC of SOEs on the efficiency of M&As is heterogeneous, and this positive effect is mainly reflected in local and commercial SOEs. (3) The path of this impact is that the GC of SOEs can help reduce ineffective M&As in advance, enhance the ability to integrate M&As after the fact and reduce the risk of goodwill impairment and bankruptcy. This article reveals the impact of the construction of SOEs under the rule of law with the system of GC as the core of M&As activities, providing intuitive evidence for the implementation effect of the GC of SOEs. The research conclusion has important practical guiding value for comprehensively deepening the construction of the rule of SOEs under the rule of law and writing a good chapter on the Chinese path to modernization of SOEs.

Keywords: the system of general counsel, merger and acquisition efficiency, state-owned enterprises, mergers and acquisitions

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Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: Mohammad Lemar Zalmai, Osman Hurol Turkakin, Cemil Akcay, Ekrem Manisali

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Most of the construction projects are exposed to time and cost overruns due to various factors and this is a major problem. As a solution to this, the Earned Value Management (EVM) method is considered. EVM is a powerful and well-known method used in monitoring and controlling the project. EVM is a technique that project managers use to track the performance of their project against project baselines. EVM gives an early indication that either project is delayed or not, and the project is either over budget or under budget at any particular day by tracking it. Thus, it helps to improve the management control system of a construction project, to detect and control the problems in potential risk areas and to suggest the importance and purpose of monitoring the construction work. This paper explains the main parameters of the EVM system involved in the calculation of time and cost for construction projects. In this study, the project management software Primavera P6 is used to deals with the project monitoring process of a seven-storeyed (G+6) faculty building whose construction is in progress at Istanbul, Turkey. A comparison between the planned progress of construction activities and actual progress is performed, and the analysis results are interpreted. This case study justifies the benefits of using EVM for project cash flow analysis and forecasting.

Keywords: earned value management (EVM), construction cost management, construction planning, primavera P6, project management, project scheduling

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Authors: Muhamad Ammar Bin Mohd Asri, Muhammad Hamizan Bin Yusof, Muhammad Haziq Bin Abdul Khalil, Esman Hanief Bin Khairul Anuar, Muhammad Fikri Bin Ishak, Amril Azim Bin Mohd Norrahim, Muhammad Danial Fakhri Bin Fakhruddin, Muhammad Khairul Nizam in Hosnodin, Muhammad Ezzat Hariz Bin Norhisam

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Ergonomics is the science of creating and arranging workplaces, products, and systems to increase human performance, comfort, and safety. This study researched ergonomics as a solution for preventing workplace injuries, specifically musculoskeletal disorders, among employers and employees. The method will be used in this project is a literature review which means conducting a study about ergonomics with peer-reviewed journal articles and books. It focuses on employees and employers who are in one company on other departments under the protection of Occupational Safety and Health (OSHA). These solutions include ergonomic assessments, workplace design improvements, effective training and education, and the use of ergonomic tools and equipment. Employers can build workplaces that are safer and more productive by putting these solutions in place, and employees can work comfortably and prevent accidents from bad ergonomics. Overall, the paper highlights how crucial it is to take injury prevention measures and consider ergonomics at work.

Keywords: occupational safety and health, musculoskeletal disorders, ergonomic, ergonomic risk

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Urmi Khatri

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Capital asset pricing model (CAPM) draws a direct relationship between the risk and the expected rate of return. There was a criticism on the beta and the assumptions of CAPM, as they are not applicable in the real world. Fama French Three Factor Model and Fama French Five Factor Model have given different factors, which have an impact on the return of any asset like size, value, investment and profitability. This study proposes to see Capital Asset pricing Model through the lenses of the quality aspect. In the study, the six factors are studied. The Fama French Five Factor Model and addition of the quality dimension are studied. Here, Graham’s seven quality and quantity criteria are measured to determine the score of the sample firms. Thus, this study tries to check the model fit. The beta coefficient of the quality dimension and the R square value is seen to determine validity of the proposed model. The sample is drawn from the firms listed on Indian Stock Exchange (BSE). For the study, only nonfinancial firms are been selected. The time period of the study is from January 1999 to December 2019. Hence, the primary objective of the study is to check how robust the model becomes after giving the quality dimension to the capital asset pricing model in addition to the size, value, profitability and investment.

Keywords: asset pricing model, CAPM, Graham’s score, G-score, multifactor model, quality

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Authors: Mete Ulaş Aksoy

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In contemporary politics, the state of emergency has become a permanent and salient feature of politics. This study aims to clarify the anthropological and ontological dimensions of the permanent state of emergency. It pays special attention to the structural relation between the exception and play. Focusing on the play in the context of emergency and exception enables the recognition of the difference and sometimes the discrepancy between the exception and emergency, which has passed into oblivion because of the frequency and normalization of emergency situations. This study coins the term “ludic exception” in order to highlight the difference between the exceptions in which exuberance and paroxysm rule over the socio-political life and the permanent emergency that protects the authority with a sort of extra-legality. The main thesis of the study is that the ludic elements such as risk, conspicuous consumption, sacrificial gestures, agonism, etc. circumscribe the exceptional moments temporarily, preventing them from being routine and normal. The study also emphasizes the decline of ludic elements in modernity as the main factor in the transformation of the exceptions into permanent emergency situations. In the introduction, the relationship between play and exception is taken into consideration. In the second part, the study elucidates the concept of ludic exceptions and dwells on the anthropological examples of the ludic exceptions. In the last part, the decline of ludic elements in modernity is addressed as the main factor for the permanent emergency.

Keywords: emergency, exception, ludic exception, play, sovereignty

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Authors: H. Moalla, A. Frikha

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Multi-criteria decision aid methods consider decision problems where numerous alternatives are evaluated on several criteria. These methods are used to deal with perfect information. However, in practice, it is obvious that this information requirement is too much strict. In fact, the imperfect data provided by more or less reliable decision makers usually affect decision results since any decision is closely linked to the quality and availability of information. In this paper, a PROMETHEE-BELIEF approach is proposed to help multi-criteria decisions based on incomplete information. This approach solves problems with incomplete decision matrix and unknown weights within PROMETHEE method. On the base of belief function theory, our approach first determines the distributions of belief masses based on PROMETHEE’s net flows and then calculates weights. Subsequently, it aggregates the distribution masses associated to each criterion using Murphy’s modified combination rule in order to infer a global belief structure. The final action ranking is obtained via pignistic probability transformation. A case study of real-world application concerning the location of a waste treatment center from healthcare activities with infectious risk in the center of Tunisia is studied to illustrate the detailed process of the BELIEF-PROMETHEE approach.

Keywords: belief function theory, incomplete information, multiple criteria analysis, PROMETHEE method

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Authors: Seongryong Kang, Woonjin Kim, Sungjoo Lee

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Under the environment of fierce competition and globalized economy, international technology collaboration has gained increasing attention as a way to improve innovation efficiency. While international technology transfer helps a firm to acquire necessary technology in a short period of time, it also has a risk; embedding external technology from overseas partners may cause a transaction cost due to the regional, cultural and language barriers, which tend to offset the benefits of such transfer. Though a number of previous studies have focused on the effects of technology in-transfer on firm performance, few have conducted in the context of international technology transfer. To fill this gap, this study aims to investigate the impact of international technology in-transfer on firm performance – both innovation and financial performance, with a particular emphasis on the diversity and intensity of such transfer. To do this, we adopted technology balance payment (TBP) data of Korean firms from 2010 to 2011, where an intermediate regression analysis was used to identify the intermediate effects of absorptive capacity. The analysis results indicate that i) the diversity and intensity of international technology transfer influence innovation performance by improving R&D capability positively; and ii) the diversity has a positive impact but the intensity has a negative impact on financial performance through the intermediation of R&D intensity. The research findings are expected to provide meaningful implications for establishing global technology strategy and developing policy programs to facilitate technology transfer.

Keywords: diversity, intensity, international technology acquisition, performance, technology transfer

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Authors: Muhammad Umar Hassan

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Renal cell carcinoma is a subset of kidney cancer that arises in the lining of DCT and is present in parenchymal tissue. Diagnosis is based on lab reports, including urinalysis, renal function tests (RFTs), and electrolyte balance, along with imaging techniques. Organ failure and other complications have been commonly observed in these cases. Over the years, the presentation of patients has varied, so carcinoma was classified on the basis of site, shape, and consistency for detailed analysis. Lifestyle patterns and occupational history were inquired about and recorded. Methods: Data from 100 patients presenting to the oncology and nephrology department of Mayo Hospital in the year 2015-2020 were included in this retrospective study on a random basis. The study was specifically focused on three risk factors. Smoking, occupational exposures, and Hakim medicine are taken by the patient for any cause. After procurement of data, follow-up contacts of these patients were established, resulting in a detailed analysis of lifestyle. Conclusion: The inference drawn is a direct causal link between smoking, industrial workplace exposure, and Hakim medicine with the development of Renal Cell Carcinoma. It was shown in the majority of the patients and hence confirmed our hypothesis.

Keywords: renal cell carcinoma, kidney cancer, clear cell carcinoma

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Authors: Muna Mohamed Omer Mirghani

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This paper responds to one of the key national development strategies and a typical challenge in the Gash Basin as well as in different parts of Sudan, namely managing water scarcity in view of climate change impacts in minor water systems sustaining over 50% of the Sudan population. While now focusing on the Gash river basin, the ultimate aim is to replicate the same approach in similar water systems in central and west Sudan. The key objective of the paper is the identification of outcome-based water governance interventions in Gash Basin, guided by the global Sustainable Development Goal six (SDG 6 on water and sanitation) and the Sudan water resource policy framework. The paper concluded that improved water resources management of the Gash Basin is a prerequisite for ensuring desired policy outcomes of groundwater use and flood risk management purposes. Analysis of various water governance dimensions in the Gash indicated that the operationalization of a Basin-level institutional reform is critically focused on informed actors and adapted practices through knowledge and technologies along with the technical data and capacity needed to make that. Adapting the devolved Institutional structure at state level is recommended to strengthen the Gash basin regulatory function and improve compliance of groundwater users.

Keywords: water governance, Gash Basin, integrated groundwater management, Sudan

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Authors: Jing Yu Pan, Dahai Liu

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Airlines in the US have taken protective measures to battle the COVID-19 pandemic, with a mask mandate being the most important one, especially in the aircraft cabin. As the industry is recovering from the pandemic, mask-wearing will eventually become a personal choice during flight. Nevertheless, COVID-19 will continue to create uncertainty for a long time into the future, making it necessary to understand the attitude and voluntary use of masks by air travelers on airplanes even after masks are no longer mandatory. This study aimed to understand the relationship between demographic characteristics and mask-wearing intention in the US. For age, gender, income, educational, and ethnicity groups, this study examined three factors – subjective norms, risk avoidance, and information seeking and their influence on the mask-wearing intention onboard airplanes during COVID-19 and whether or not attitude toward masks was an important mediator. The results show that all demographic factors except gender could help to explain the group variations in factor impact and the mediating effect in mask-wearing intentions. In particular, Asian travelers had mask-wearing intentions that were not affected by attitude either directly or indirectly. These findings provide useful implications to enhance the health and safety of air travelers, especially in the US, where opposing views toward mask-wearing still widely exist.

Keywords: COVID-19, passenger demographics, aircraft cabin, mask-wearing intention, attitude as mediator

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Authors: Joachim Monkelbaan, Marcia Hale

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Now that global frameworks for sustainability governance (e.g. the Sustainable Development Goals, Paris Climate Agreement and Sendai Framework for Disaster Risk Reduction) are in place, the question is how these aspirations that represent major transitions can be put into practice. Water ‘infrasystems’ can play an especially significant role in strengthening regional sustainability. Infrasystems include both hard and soft infrastructure, such as pipes and technology for delivering water, as well as the institutions and governance models that direct its delivery. As such, an integrated infrasystems view is crucial for Integrative Water Management (IWM). Due to frequently contested ownership of and responsibility for water resources, these infrasystems can also play an important role in facilitating conflict and catalysing community empowerment, especially through participatory approaches to governance. In this paper, we analyze the water infrasystem of the Los Angeles region through the lens of global frameworks for sustainability governance. By complementing a solid overview of governance theories with empirical data from interviews with water actors in the LA metropolitan region (including NGOs, water managers, scientists and elected officials), this paper elucidates ways for this infrasystem to be better aligned with global sustainability frameworks. In addition, it opens up the opportunity to scrutinize the appropriateness of global frameworks when it comes to fostering sustainability action at the local level.

Keywords: governance, transitions, global frameworks, infrasystems

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Authors: Kwame Amoah

Abstract:

Artificial intelligence (AI) has the prospect of transforming project management, significantly improving efficiency and accuracy. By automating specific tasks with defined guidelines, AI can assist project managers in making better decisions and allocating resources efficiently, with possible risk mitigation. This study explores how AI is already impacting project management and likely future AI's impact on the field. The AI's reaction has been a divided opinion; while others picture it as a destroyer of jobs, some welcome it as an innovation advocate. Both sides agree that AI will be disruptive and revolutionize PM's functions. If current research is to go by, AI or some form will replace one-third of all learning graduate PM jobs by as early as 2030. A recent survey indicates AI spending will reach $97.9 billion by the end of 2023. Considering such a profound impact, the project management profession will also see a paradigm shift driven by AI. The study examines what the project management profession will look like in the next 5-10 years after this technological disruption. The research methods incorporate existing literature, develop trend analysis, and conduct structured interviews with project management stakeholders from North America to gauge the trend. PM professionals can harness the power of AI, ensuring a smooth transition and positive outcomes. AI adoption will maximize benefits, minimize adverse consequences, and uphold ethical standards, leading to improved project performance.

Keywords: project management, disruptive teacnologies, project management function, AL applications, artificial intelligence

Procedia PDF Downloads 83

Authors: Amirul Al-Ashraf Abdullah, Hema Ramachandran, Iszatty Ismail

Abstract:

Oleochemical industry in Malaysia has been diversifying significantly due to the abundant supply of both palm and kernel oils as raw materials as well as the high demand for downstream products such as fatty acids, fatty alcohols and glycerine. However, environmental awareness is growing rapidly in Malaysia because oleochemical industry is one of the palm-oil based industries that possess risk to the environment. Glycerine pitch is one of the scheduled wastes generated from the fatty acid plants in Malaysia and its discharge may cause a serious environmental problem. Therefore, it is imperative to find alternative applications for this waste glycerine. Consequently, the aim of this research is to explore the application of glycerine pitch as direct fermentation substrate in the biosynthesis of poly(3-hydroxybutyrate-co-4-hydroxybutyrate) [P(3HB-co-4HB)] copolymer, aiming to contribute toward the sustainable production of biopolymer in the world. Utilization of glycerine pitch (10 g/l) together with 1,4-butanediol (5 g/l) had resulted in the achievement of 40 mol% 4HB monomer with the highest PHA concentration of 2.91 g/l. Synthesis of yellow pigment which exhibited antimicrobial properties occurred simultaneously with the production of P(3HB-co-4HB) through the use of glycerine pitch as renewable carbon resource. Utilization of glycerine pitch in the biosynthesis of P(3HB-co-4HB) will not only contribute to reducing society’s dependence on non-renewable resources but also will promote the development of cost efficiency microbial fermentation towards biosustainability and green technology.

Keywords: biopolymer, glycerine pitch, natural pigment, P(3HB-co-4HB)

Procedia PDF Downloads 469

Authors: Ibrahim R. Elomari, Fin O'Flaherty, Ibrahim R. Elomari, Paul Lambert

Abstract:

Cathodic protection (CP) is a technique commonly used to arrest corrosion of steel in infrastructure. However, it is not generally used on high strength, pre-stressed tendons due to the risk of hydrogen generation, leading to possible embrittlement. This paper investigates its use in such circumstances where the applied protection potential is varied to determine if CP can be safely employed on pre-stressed tendons. Plain steel tendons measuring 5.4 mm diameter were pre-stressed in timber moulds and embedded in sand/cement mortar, formulated to represent gunite. Two levels of pre-stressing were investigated (400MPa and 1200MPa). Pre-corrosion of 0% (control), 3% and 6% target loss of cross-sectional area was applied to replicate service conditions. Impressed current cathodic protection (ICCP) was then applied to the tendons at two levels of potential to identify any effect on strength. Instant-off values up to -950mV were used for normal protection with values of -1100mV or more negative to achieve overprotection. Following the ICCP phase, the tendons were removed from the mortar, cleaned and weighed to confirm actual percentage of corrosion. Tensile tests were then conducted on the tendons. The preliminary results show the influence of normal levels and overprotection of CP on the ultimate strength of the tendons.

Keywords: pre-stressed concrete, corrosion, cathodic protection, hydrogen embrittlement

Procedia PDF Downloads 266

Authors: Nantakrit Yodpijit, Teppakorn Sittiwanchai

Abstract:

The number of older adults is rising rapidly. The world’s population becomes aging. Falls is one of common and major health problems in the elderly. Falls may lead to acute and chronic injuries and deaths. The fall-prone individuals are at greater risk for decreased quality of life, lowered productivity and poverty, social problems, and additional health problems. A number of studies on falls prevention using fall detection system have been conducted. Many available technologies for fall detection system are laboratory-based and can incur substantial costs for falls prevention. The utilization of alternative technologies can potentially reduce costs. This paper presents the new design and development of a wearable-based fall detection system using an Accelerometer and Gyroscope as motion sensors for the detection of body orientation and movement. Algorithms are developed to differentiate between Activities of Daily Living (ADL) and falls by comparing Threshold-based values with Artificial Neural Networks (ANN). Results indicate the possibility of using the new threshold-based method with neural network algorithm to reduce the number of false positive (false alarm) and improve the accuracy of fall detection system.

Keywords: aging, algorithm, artificial neural networks (ANN), fall detection system, motion sensorsthreshold

Procedia PDF Downloads 496