Search results for: uncertain volatility

Authors: Gulfam Hasan, Ijaz Ashraf, Saleem Ashraf, Muhammad Rafay Muzammil, Salman Asghar, Shafiq-Ur-Rehman Zia

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The word “climate change” has become the most popular term when anyone observes any uncertain climate variation in their respective region. Asian countries are more prone to the impact of this phenomenon, and Pakistan is the leading affected country. Last few years, governments all over the world have been trying to cater to this issue for the best entrust of their population, especially agriculture. Now the farmers in Pakistan are fully aware of the term “climate change” and are more concerned about its solutions. On the other hand, developed countries like the USA are setting a benchmark for developing countries in every sphere of life. Based on cultural and other variations, the research was carried out to identify the behavior of farmers regarding the same issue. Cross-sectional survey research was designed for an in-depth study of relevant research questions. Face-to-face interviews were conducted in Pakistan, while virtual and face-to-face interviews were conducted in the Indiana State of the USA. The results of the present study and the responses of farmers were very interesting. The common climate change mitigation strategies suggested by farmers of both countries were less use of motor vehicles (replacement with bicycles in the circle of 10 Km), less dependency on chemical fertilizers (increased use of Manure, Bio-fertilizer, Compost), and plantation of the tree. The difference of opinion was in less government interest, lack of farmers’ education, political instability (views of Pakistani farmers), awareness of local communities, self-satisfaction, and economic disparities (views of USA farmers). Based on the given evidence, it was recommended that there is a dire need to address the climate change issue all over the world without discrimination of race, color, region, or religion. Because it will affect not only agriculture but also the real effect will be on HUMANITY.

Keywords: climate change, mitigation strategies, forests, biodiversity

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Authors: Dong Wu, Michael Grenn

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Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

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Authors: Helen L. Hein, Joachim Schwarte

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As a pillar of sustainable development, ecology has become an important milestone in research community, especially due to global challenges like climate change. The ecological performance of products can be scientifically conducted with life cycle assessments. In the construction sector, significant amounts of CO₂ emissions are assigned to the energy used for building heating purposes. Therefore, sustainable construction materials for insulating purposes are substantial, whereby aerogels have been explored intensively in the last years due to their low thermal conductivity. Therefore, the WALL-ACE project aims to develop an aerogel-based thermal insulating plaster that would achieve minor thermal conductivities. But as in the early stage of development phases, a lot of information is still missing or not yet accessible, the ecological performance of innovative products bases increasingly on uncertain data that can lead to significant deviations in the results. To be able to predict realistically how meaningful the results are and how viable the developed products may be with regard to their corresponding respective market, these deviations however have to be considered. Therefore, a classification method is presented in this study, which may allow comparing the ecological performance of modern products with already established and competitive materials. In order to achieve this, an alternative calculation method was used that allows computing with lower and upper bounds to consider all possible values without precise data. The life cycle analysis of the considered products was conducted with an interval arithmetic based calculation method. The results lead to the conclusion that the interval solutions describing the possible environmental impacts are so wide that the result usability is limited. Nevertheless, a further optimization in reducing environmental impacts of aerogels seems to be needed to become more competitive in the future.

Keywords: aerogel-based, insulating material, early development phase, interval arithmetic

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Authors: Fatemeh Haghiralsadat, Mohadese Hashemi, Elham Akhoundi Kharanaghi, Mojgan Yazdani, Mahboobe Sharafodini, Omid Javani

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Niosomes are colloidal particles formed from the self-assembly of non-ionic surfactants in aqueous medium resulting in closed bilayer structures. As a consequence of this hydrophilic and hydrophobic structure, niosomes have the capacity to entrap compounds of different solubilities. Niosomes are promising vehicle for drug delivery which protect sensitive drugs and improve the therapeutic index of drugs by restricting their action to target cells. Essential oils are complex mixtures of volatile compounds such as terpenoids, phenol-derived aromatic components that have been used for many biological properties including bactericidal, fungicidal, insecticidal, antioxidant, anti-tyrosinase and other medicinal properties. Encapsulation of essential oils in niosomes can be an attractive method to overcome their limitation such as volatility, easily decomposition by heat, humidity, light, or oxygen. Cuminum cyminum L. (Cumin) is an aromatic plant included in the Apiaceae family and is used to flavor foods, added to fragrances, and for medical preparations which is indigenous to Egypt, the Mediterranean region, Iran and India. The major components of the Cumin oil were reported as cuminaldehyde, γ -terpinene, β-pinene, p-cymene, p-mentha-1, 3-dien-7-al, and p-mentha-1, 4-dien-7-al which provide the antimicrobial and antioxidant activity. The aim of this work was to formulate Cumin essential oil-loaded niosomes to improve water solubility of natural product and evaluate its physico-chemical features and stability. Cumin oil was obtained through steam distillation using a clevenger-type apparatus and GC/MS was applied to identify the main components of the essential oil. Niosomes were prepared by using thin film hydration method and nanoparticles were characterized for particle size, dispersity index, zeta potential, encapsulation efficiency, in vitro release, and morphology.

Keywords: Cuminum cyminum L., Cumin, niosome, essential oil, encapsulation

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Authors: Farahnaz Karami

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Routing is an important, challenging task in mobile ad hoc networks due to node mobility, lack of central control, unstable links, and limited resources. An ant colony has been found to be an attractive technique for routing in Mobile Ad Hoc Networks (MANETs). However, existing swarm intelligence based routing protocols find an optimal path by considering only one or two route selection metrics without considering correlations among such parameters making them unsuitable lonely for routing real time applications. Fuzzy logic combines multiple route selection parameters containing uncertain information or imprecise data in nature, but does not have multipath routing property naturally in order to provide load balancing. The objective of this paper is to design a routing algorithm using fuzzy logic and ant colony that can solve some of routing problems in mobile ad hoc networks, such as nodes energy consumption optimization to increase network lifetime, link failures rate reduction to increase packet delivery reliability and providing load balancing to optimize available bandwidth. In proposed algorithm, the path information will be given to fuzzy inference system by ants. Based on the available path information and considering the parameters required for quality of service (QoS), the fuzzy cost of each path is calculated and the optimal paths will be selected. NS2.35 simulation tools are used for simulation and the results are compared and evaluated with the newest QoS based algorithms in MANETs according to packet delivery ratio, end-to-end delay and routing overhead ratio criterions. The simulation results show significant improvement in the performance of these networks in terms of decreasing end-to-end delay, and routing overhead ratio, and also increasing packet delivery ratio.

Keywords: mobile ad hoc networks, routing, quality of service, ant colony, fuzzy logic

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Authors: Nikolaos Papadimas, Joanna Bennett, Amir Sakhaei, Timothy Dodwell

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Composite modeling of consolidation processes is playing an important role in the process and part design by indicating the formation of possible unwanted prior to expensive experimental iterative trial and development programs. Composite materials in their uncured state display complex constitutive behavior, which has received much academic interest, and this with different models proposed. Errors from modeling and statistical which arise from this fitting will propagate through any simulation in which the material model is used. A general hyperelastic polynomial representation was proposed, which can be readily implemented in various nonlinear finite element packages. In our case, FEniCS was chosen. The coefficients are assumed uncertain, and therefore the distribution of parameters learned using Markov Chain Monte Carlo (MCMC) methods. In engineering, the approach often followed is to select a single set of model parameters, which on average, best fits a set of experiments. There are good statistical reasons why this is not a rigorous approach to take. To overcome these challenges, A hierarchical Bayesian framework was proposed in which population distribution of model parameters is inferred from an ensemble of experiments tests. The resulting sampled distribution of hyperparameters is approximated using Maximum Entropy methods so that the distribution of samples can be readily sampled when embedded within a stochastic finite element simulation. The methodology is validated and demonstrated on a set of consolidation experiments of AS4/8852 with various stacking sequences. The resulting distributions are then applied to stochastic finite element simulations of the consolidation of curved parts, leading to a distribution of possible model outputs. With this, the paper, as far as the authors are aware, represents the first stochastic finite element implementation in composite process modelling.

Keywords: data-driven , material consolidation, stochastic finite elements, surrogate models

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Authors: Shadreck Muchaku, Grey Magaiza, Jerit Dube

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The high insolvency rate of female-led emerging enterprises in the Southern African mountain region reflects the various vulnerabilities that exist. Although this is the case, there is a limited understanding of how these vulnerabilities influence entrepreneurship failure. This paper focuses on female entrepreneurs because of their role in economic development. Emerging female entrepreneurs in this region often operate in uncertain environments, which makes it difficult for them to thrive. The form and nature of entrepreneurial opportunities rural women of the Afro Montane region engage in are largely unsustainable as a lot of women struggle with confidence, and they need help with understanding their skills. However, there is still a gap in the existing literature on women entrepreneurship resilience and vulnerability reduction in the Afromontane. Furthermore, a major problem is the lack of empirical studies on this matter and limited studies indicating a general profile of emerging female entrepreneurs in this region. This systematic literature review attempts to fill in the gap of knowledge on entrepreneurship resilience and vulnerability reduction of emerging female entrepreneurs in the Afromontane regions and other similar precarious environments. In this review, we focus much on highlighting the nexus between entrepreneurship resilience and vulnerability reduction of emerging female entrepreneurs in academic literature through a chronological dispersal of publications in developing countries. This review adopts an ATLAS ti.22 software-based thematic analysis to analyze results obtained from reviewed academic journal articles. As research on entrepreneurship resilience and vulnerability reduction is still developing in the Sothern African mountain region, the results of this review will contribute to the body of literature and provide recommendations and a foundation for future research. This systematic review paper provides valuable insights and methodological approaches to scholarship in a nascent area of emerging female entrepreneurs in the Afromontane.

Keywords: entrepreneurship resiliency, vulnerability reduction, female entrepreneurs, mountain regions

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Authors: Zeliha Ustun, Mustafa Ersoz

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In the study, a traditional herbal supplement black cumin seed (Nigella sativa) oil properties has been studied to protect the main quality parameters by a new supplement application. Black cumin seed and its oil is used as a dietary supplement and preferred traditional remedy in Africa, Asia and Middle East for centuries. Now it has been consuming by millions of people in America and Europe as natural supplements and/or phytotherapeutic agents to support immune system, asthma, allergic rinnitis etc. by the scientists’ advices. With the study, it is aimed to prove that soft gelatin capsules are a new and more practical way of usage for Nigella sativa oil that has a longer stability. With the study soft gelatin capsules formulation has been developed to protect cold pressed black cumin seed oil physicochemical properties for a longer period. The product design has been developed in laboratory and implemented in pilot scale soft gelatin capsule manufacturing. Physicochemical properties (peroxide value, free fatty acids, fatty acid composition, refractive index, iodine value, saponification value, unsaponifiable matters) of Nigella sativa oil soft gelatin capsules and Nigella sativa oil in liquid form in amber glass bottles have been compared and followed for 8 months. The main parameters for capsules and liquid form found that for free fatty acids 2.29±0.03, 3.92±0.11 % oleic acid, peroxide 23.11±1.18, 27.85±2.50 meqO2/kg, refractive index at 20 0C 1.4738±0.00, 1.4737±0.00, soap 0 ppm, moisture and volatility 0.32±0.01, 0.36±0.01 %, iodine value 123.00±0.00, 122.00±0.00 wijs, saponification value 196.25±0.46, 194.13±0.35 mg KOH/g and unsaponifiable matter 7.72±0.13, 6.88±0.36 g/kg respectively. The main fatty acids are found that linoleic acid 56.17%, oleic acid 24.64%, palmitic acid 11,94 %. As a result, it is found that cold pressed Nigella sativa oil soft gelatin capsules physicochemical properties are more stable than the Nigella sativa oil stored in glass bottles.

Keywords: black cumin seed (Nigella sativa) oil, cold press, nutritional supplements, soft gelatin capsule

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Authors: Iahtasham Khan, Vania Lucia De Assis Santana, Marcilia Maria Alves De Souza, Mabel Hanna Vance Harrop, Fernando Leandro Dos Santos, Cecília Maria Souza Leão E. Silva, Pedro Paulo Silveira, Marcelo Brasil, Marcus Vinícius, Hélio Cordeiro Manso Filho, Muhammad Younus, Aman Ullah Khan

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Glanders ranks high on clinical lists in some regions of Brazil as a cause of respiratory and lymphatic disease in equids. Glanders is caused by Burkolderia mallei (B. mallei) Gram-negative bacterium. B. mallei was first biological agent used in World War I in 20th century. The complement fixation test (CFT) is a serodiagnostic tool prescribed by the World Organization for Animal Health (OIE)for the diagnosis of glanders in the international trade of equids. The aim of the present study was to monitor the serological responses in equines naturally infected with B. mallei using the CFT. A total of 574 equids were tested with CFT, 30 days apart in a total of 12 samplings. One hundred thirty-four sera tested negative in all samplings; 192 sera tested positive in one sampling and 125 sera tested positive in two or more samplings. Remaining 123 samples showed uncertain results. Thus, CFT results can vary over a period of time. These variations could be the consequence of the effects of the natural immune response in each animal. The findings of the present study demonstrate difficulties regarding the simultaneous implementation of CFT and test and slaughter policies to eradicate glanders. Another constraint to control this disease is the presence of carrier/transitory CFT-negative animals, which are a potential source of disease in glanders-free areas. Serodiagnostic tests of higher sensitivity and specificity like immunobloat should be implemented to achieve success in the eradication of glanders.

Keywords: glanders, equids, horses, immunological, mules

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Authors: Jean Berger, Mohamed Barkaoui

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Discrete search path planning in time-constrained uncertain environment relying upon imperfect sensors is known to be hard, and current problem-solving techniques proposed so far to compute near real-time efficient path plans are mainly bounded to provide a few move solutions. A new information-theoretic –based open-loop decision model explicitly incorporating false alarm sensor readings, to solve a single agent military logistics search-and-delivery path planning problem with anticipated feedback is presented. The decision model consists in minimizing expected entropy considering anticipated possible observation outcomes over a given time horizon. The model captures uncertainty associated with observation events for all possible scenarios. Entropy represents a measure of uncertainty about the searched target location. Feedback information resulting from possible sensor observations outcomes along the projected path plan is exploited to update anticipated unit target occupancy beliefs. For the first time, a compact belief update formulation is generalized to explicitly include false positive observation events that may occur during plan execution. A novel genetic algorithm is then proposed to efficiently solve search path planning, providing near-optimal solutions for practical realistic problem instances. Given the run-time performance of the algorithm, natural extension to a closed-loop environment to progressively integrate real visit outcomes on a rolling time horizon can be easily envisioned. Computational results show the value of the approach in comparison to alternate heuristics.

Keywords: search path planning, false alarm, search-and-delivery, entropy, genetic algorithm

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Authors: Alina Fedossova, Jose Jorge Sierra Molina

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SIP problems are part of non-classical optimization. There are problems in which the number of variables is finite, and the number of constraints is infinite. These are semi-infinite programming problems. Most algorithms for semi-infinite programming problems reduce the semi-infinite problem to a finite one and solve it by classical methods of linear or nonlinear programming. Typically, any of the constraints or the objective function is nonlinear, so the problem often involves nonlinear programming. An investment portfolio is a set of instruments used to reach the specific purposes of investors. The risk of the entire portfolio may be less than the risks of individual investment of portfolio. For example, we could make an investment of M euros in N shares for a specified period. Let yi> 0, the return on money invested in stock i for each dollar since the end of the period (i = 1, ..., N). The logical goal here is to determine the amount xi to be invested in stock i, i = 1, ..., N, such that we maximize the period at the end of ytx value, where x = (x1, ..., xn) and y = (y1, ..., yn). For us the optimal portfolio means the best portfolio in the ratio "risk-return" to the investor portfolio that meets your goals and risk ways. Therefore, investment goals and risk appetite are the factors that influence the choice of appropriate portfolio of assets. The investment returns are uncertain. Thus we have a semi-infinite programming problem. We solve a semi-infinite optimization problem of portfolio selection using the outer approximations methods. This approach can be considered as a developed Eaves-Zangwill method applying the multi-start technique in all of the iterations for the search of relevant constraints' parameters. The stochastic outer approximations method, successfully applied previously for robotics problems, Chebyshev approximation problems, air pollution and others, is based on the optimal criteria of quasi-optimal functions. As a result we obtain mathematical model and the optimal investment portfolio when yields are not clear from the beginning. Finally, we apply this algorithm to a specific case of a Colombian bank.

Keywords: outer approximation methods, portfolio problem, semi-infinite programming, numerial solution

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Authors: Dorna Kargar, Mehrasa Masih

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Due to its special geological and geographical conditions, Iran has always been exposed to various natural hazards. Earthquake is one of the natural hazards with random nature that can cause significant financial damages and casualties. This is a serious threat, especially in areas with active faults. Therefore, considering the population density in some parts of the country, locating and zoning high-risk areas are necessary and significant. In the present study, seismic hazard assessment via probabilistic and deterministic method for Tehran, the capital of Iran, which is located in Alborz-Azerbaijan province, has been done. The seismicity study covers a range of 200 km from the north of Tehran (X=35.74° and Y= 51.37° in LAT-LONG coordinate system) to identify the seismic sources and seismicity parameters of the study region. In order to identify the seismic sources, geological maps at the scale of 1: 250,000 are used. In this study, we used Kijko-Sellevoll's method (1992) to estimate seismicity parameters. The maximum likelihood estimation of earthquake hazard parameters (maximum regional magnitude Mmax, activity rate λ, and the Gutenberg-Richter parameter b) from incomplete data files is extended to the case of uncertain magnitude values. By the combination of seismicity and seismotectonic studies of the site, the acceleration with antiseptic probability may happen during the useful life of the structure is calculated with probabilistic and deterministic methods. Applying the results of performed seismicity and seismotectonic studies in the project and applying proper weights in used attenuation relationship, maximum horizontal and vertical acceleration for return periods of 50, 475, 950 and 2475 years are calculated. Horizontal peak ground acceleration on the seismic bedrock for 50, 475, 950 and 2475 return periods are 0.12g, 0.30g, 0.37g and 0.50, and Vertical peak ground acceleration on the seismic bedrock for 50, 475, 950 and 2475 return periods are 0.08g, 0.21g, 0.27g and 0.36g.

Keywords: peak ground acceleration, probabilistic and deterministic, seismic hazard assessment, seismicity parameters

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Authors: Yen-Jong Chen, Jei-An Su

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Public use facilities provide the basic infrastructure supporting the needs of urban sustainable development. These facilities include roads (streets), parking areas, green spaces, public schools, and city parks. However, how to acquire land with the proper location and size still remains uncertain in a capitalist economy where land is largely privately owned, such as in cities in Taiwan. The issue concerning the proper acquisition of reserved land for local public facilities (RLPF) policies has been continuously debated by the Taiwanese government for more than 30 years. Lately, the government has been re-evaluating projects connected with existing RLPF policies from the viewpoints of the needs of local residents, including the living environments of older adults. This challenging task includes addressing the requests of official bureau administrators, citizens whose property rights and current use status are affected, and other stakeholders, along with the means of development. To simplify the decision to acquire or release public land, we selected only public facilities that are needed for living in the local community, including parks, green spaces, plaza squares, and land for kindergartens, schools, and local stadiums. This study categorized these spaces as the community’s “leisure public facilities” (LPF). By constructing an accessibility index of the services of such multi-function facilities, we computed and produced a GIS map of spatial buffer zones for each LPF. Through these procedures, the service needs provided by each LPF were clearly identified. We then used spatial buffer zone envelope mapping to evaluate these service areas. The results obtained can help decide which RLPF should be acquired or released so that community services can be maximized under a limited budget.

Keywords: urban public facilities, community demand, accessibility, spatial buffer zone, Taiwan

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Authors: S. Jeyarajan

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Concept of knowledge is discovered from conducted study for successive Competition in Sri Lankan Non-State Higher Educational Institutes. The Concept discovered out of collected Knowledge Management Practices from Emerald inside likewise reputed literatures and of Non-State Higher Educational sector. A test is conducted to reveal existences and its reason behind of these collected practices in Sri Lankan Non-State Higher Education Institutes. Further, unavailability of such study and uncertain on number of participants for data collection in the Sri Lankan context contributed selection of research method as qualitative method, which used attributes of Delphi Method to manage those likewise uncertainty. Data are collected under Dramaturgical Method, which contributes efficient usage of the Delphi method. Grounded theory is selected as data analysis techniques, which is conducted in intermixed discourse to manage different perspectives of data that are collected systematically through perspective and modified snowball sampling techniques. Data are then analysed using Grounded Theory Development Techniques in Intermix discourses to manage differences in Data. Consequently, Agreement in the results of Grounded theories and of finding in the Foreign Study is discovered in the analysis whereas present study conducted as Qualitative Research and The Foreign Study conducted as Quantitative Research. As such, the Present study widens the discovery in the Foreign Study. Further, having discovered reason behind of the existences, the Present result shows Concept for Knowledge from Sri Lankan Non-State sector to manage higher educational Institutes in successful manner.

Keywords: adherence of snowball sampling into perspective sampling, Delphi method in qualitative method, grounded theory development in intermix discourses of analysis, knowledge management for success of higher educational institutes

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Authors: T. Hansen

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Many consumers are uncertain of what financial borrowing behavior may serve their interests in the best way. This is important since consumers’ risky financial decisions may not only negatively affect their short-term liquidity but may haunt them for years after they are made. Obviously, this is especially critical for young adults who often carry large amounts of student loans or credit card debt, which in turn may hinder their future ability to obtain financial healthiness. Even though factors such as financial knowledge, attitudes towards risk, gender, and motivations of borrowing, among others, are known to influence consumer borrowing behavior, no existing model comprehensibly describes the mechanisms behind young adults’ risky borrowing behavior. This is unfortunate since a better understanding of the relationships between such factors and young adults’ risky borrowing behavior may be of value to financial service providers and financial authorities aiming to improve young adults’ borrowing behavior. This research extends prior research by developing a conceptual framework for the purpose of understanding young adults’ risky borrowing behavior. The study is based on two survey samples comprising 488 young adults aged 18-25 who have not obtained a risky loan (sample 1) and 214 young adults aged 18-25 who already have obtained a risky loan (sample 2), respectively. The results suggest several psychological, sociological, and behavioral factors that may influence young adults’ intentional risky borrowing behavior, which in turn is shown to affect actualized risky borrowing behavior. We also found that the relationship between intentional risky borrowing behavior and actualized risky borrowing behavior is negatively moderated by perceived risk – but not by perceived complexity. In particular, the results of this study indicate that public policy makers, banks and financial educators should seek to eliminate less desirable social norms on how to behave financially. In addition, they should seek to enhance young adults’ risky borrowing perceived risk, thereby preventing that intentional risky borrowing behavior translates into actualized risky behavior.

Keywords: financial services, risky borrowing behavior, young adults, financial knowledge, social norms, perceived risk, financial trust, public financial policy

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Authors: Layal Mansour

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The aim of this paper is to identify whether oil price volatility or geopolitical risks can predict future financial stress periods or economic recessions in Kuwait. We construct the first Financial Stress Index for Kuwait (FSIK) that includes informative vulnerable indicators of the main financial sectors: the banking sector, the equities market, and the foreign exchange market. The study covers the period from 2000 to 2020, so it includes the two recent most devastating world economic crises with oil price fluctuation: the Covid-19 pandemic crisis and Ukraine-Russia War. All data are taken by the central bank of Kuwait, the World Bank, IMF, DataStream, and from Federal Reserve System St Louis. The variables are computed as the percentage growth rate, then standardized and aggregated into one index using the variance equal weights method, the most frequently used in the literature. The graphical FSIK analysis provides detailed information (by dates) to policymakers on how internal financial stability depends on internal policy and events such as government elections or resignation. It also shows how monetary authorities or internal policymakers’ decisions to relieve personal loans or increase/decrease the public budget trigger internal financial instability. The empirical analysis under vector autoregression (VAR) models shows the dynamic causal relationship between the oil price fluctuation and the Kuwaiti economy, which relies heavily on the oil price. Similarly, using vector autoregression (VAR) models to assess the impact of the global geopolitical risks on Kuwaiti financial stability, results reveal whether Kuwait is confronted with or sheltered from geopolitical risks. The Financial Stress Index serves as a guide for macroprudential regulators in order to understand the weakness of the overall Kuwaiti financial market and economy regardless of the Kuwaiti dinar strength and exchange rate stability. It helps policymakers predict future stress periods and, thus, address alternative cushions to confront future possible financial threats.

Keywords: Kuwait, financial stress index, causality test, VAR, oil price, geopolitical risks

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Authors: C. John Thomas, Sabitha Jannet

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The review concentrates on mental health wellbeing at workplace to create a safe work environment. The purpose of the study is to find the existing gaps in occupational health in the manufacturing sector. Mental wellbeing is important because it is an essential component of human life and influences our emotions, attitudes, and feelings. In the workplace, mental wellbeing can encourage a culture of safety and avoid accidents. An environment where individuals are comfortable voicing themselves and being themselves. More technically, when individuals have psychological protection at work, without regard for humiliation or punishment, they feel relaxed expressing complaints and errors. They are sure they are going to speak up and not humiliate, neglect, or accuse them. Once they are uncertain about something, they know they are going to ask questions. They are inclined to trust their colleagues and respect them. The reviews were considered through keywords and health-related topics. There are different characteristics of mental wellbeing in the literature and how it impacts the workplace. There is also a possibility that their personal lives will have an impact. In every occupation, however, there is widespread acknowledgment that psychosocial hazards are an important health risk for workers, yet in many workplaces, the focus remains on physical hazards. It is alleged that the understating of workplace psychosocial hazards is primarily due to the perception that they present a more difficult and complex challenge when compared to other health and safety issues. Others, however, allege it is the paucity of awareness about psychosocial hazards and their alleviation that explains their relative neglect. The other researchers focused that following global trends, it is believed that psychosocial hazards must be minimized within our workplaces and that there is a requirement for workplace interventions to reduce psychological harm and promote mental health for all the workman employees to achieve zero harm. In common, this literature review compares various results of the individual studies on their research methods and finding to fill gaps.

Keywords: mental health wellbeing, occupational health, psychosocial hazards, safety culture, safety management systems, workman employee, workplace safety

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Authors: Rajinder Singh, Ram Valluru

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Chain Ladder (CL) method, Expected Loss Ratio (ELR) method and Bornhuetter-Ferguson (BF) method, in addition to more complex transition-rate modeling, are commonly used actuarial reserving methods in general insurance. There is limited published research about their relative performance in the context of Mortgage Insurance (MI). In our experience, these traditional techniques pose unique challenges and do not provide stable claim estimates for medium to longer term liabilities. The relative strengths and weaknesses among various alternative approaches revolve around: stability in the recent loss development pattern, sufficiency and reliability of loss development data, and agreement/disagreement between reported losses to date and ultimate loss estimate. CL method results in volatile reserve estimates, especially for accident periods with little development experience. The ELR method breaks down especially when ultimate loss ratios are not stable and predictable. While the BF method provides a good tradeoff between the loss development approach (CL) and ELR, the approach generates claim development and ultimate reserves that are disconnected from the ever-to-date (ETD) development experience for some accident years that have more development experience. Further, BF is based on subjective a priori assumption. The fundamental shortcoming of these methods is their inability to model exogenous factors, like the economy, which impact various cohorts at the same chronological time but at staggered points along their life-time development. This paper proposes an alternative approach of parametrizing the loss development curve and using logistic regression to generate the ultimate loss estimate for each homogeneous group (accident year or delinquency period). The methodology was tested on an actual MI claim development dataset where various cohorts followed a sigmoidal trend, but levels varied substantially depending upon the economic and operational conditions during the development period spanning over many years. The proposed approach provides the ability to indirectly incorporate such exogenous factors and produce more stable loss forecasts for reserving purposes as compared to the traditional CL and BF methods.

Keywords: actuarial loss reserving techniques, logistic regression, parametric function, volatility

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Authors: Khawaja A. Wahaj Wani, Aykut Erkal

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Pakistan's construction industry, a key player in economic development, has experienced remarkable growth. However, the surge in activities has been accompanied by dangerous working conditions, attributed to legislative gaps and flaws. Unhealthy construction practices, uncertain site conditions, and hazardous environments contribute to a concerning rate of injuries and fatalities. The principal aim of this research study is to undertake a thorough evaluation based on the assessment of the current situation of Health & Safety policies and the surveys performed by stakeholders of Pakistan with the aim of providing solution-centric methodologies for the enforcement of health and safety regulations within construction companies operating on project sites. Recognizing the pivotal role that the construction industry plays in bolstering a nation's economy, it is imperative to address the pressing need for heightened awareness among site engineers and laborers. The study adopts a robust approach, utilizing questionnaire surveys and interviews. As an exclusive investigative study, it encompasses all stakeholders: clients, consultants, contractors, and subcontractors. Targeting PEC-registered companies. Safety performance was assessed through the examination of sixty safety procedures using SPSS-18. A high Cronbach's alpha value of 0.958 ensures data reliability, and non-parametric tests were employed due to the non-normal distribution of data. The safety performance evaluation revealed significant insights. "Using Hoists and Cranes" and "Precautionary Measures (Shoring and Excavation)" exhibited commendable safety levels. Conversely, "Trainings on Safety" displayed a lower safety performance, alongside areas such as "Safety in Contract Documentation," "Meetings for Safety," and "Worker Participation," indicating room for improvement. These findings provide stakeholders with a detailed understanding of current safety measures within Pakistan's construction industry.

Keywords: construction industry, health and safety regulations, Pakistan, risk management

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Authors: Anita Lazurko, Laszlo Pinter, Jeremy Richardson

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Uncertain climate projections, multiple possible development futures, and a financing gap create challenges for water infrastructure decision making. In contrast to conventional predict-plan-act methods, an emerging decision paradigm that enables social-ecological resilience supports decisions that are appropriate for uncertainty and leverage social, ecological, and economic multifunctionality. Concurrently, water infrastructure project finance plays a powerful role in sustainable infrastructure development but remains disconnected from discourse in socio-ecological resilience. At the time of research, a project to transfer water from Lesotho to Botswana through South Africa in the Orange-Senqu River Basin was at the pre-feasibility stage. This case was analysed through documents and interviews to investigate how uncertainty and multifunctionality are conceptualised and considered in decisions for the resilience of water infrastructure and to explore bridging concepts that might allow project finance to better enable socio-ecological resilience. Interviewees conceptualised uncertainty as risk, ambiguity and ignorance, and multifunctionality as politically-motivated shared benefits. Numerous efforts to adopt emerging decision methods that consider these terms were in use but required compromises to accommodate the persistent, conventional decision paradigm, though a range of future opportunities was identified. Bridging these findings to finance revealed opportunities to consider a more comprehensive scope of risk, to leverage risk mitigation measures, to diffuse risks and benefits over space, time and to diverse actor groups, and to clarify roles to achieve multiple objectives for resilience. In addition to insights into how multiple decision paradigms interact in real-world decision contexts, the research highlights untapped potential at the juncture between socio-ecological resilience and project finance.

Keywords: socio-ecological resilience, finance, multifunctionality, uncertainty

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Authors: Cristina Munoz-Shuguli, Francisco Rodriguez, Julio Bruna, M. Jose Galotto, Abel Guarda

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The microbial contamination in fruits due to the presence of fungal is the most important cause of their deterioration and loss. The development of active food packaging materials with antifungal properties has been proposed as an innovative strategy in order to prevent this problem. In this way, natural compounds as the essential oils or their derivatives, also called volatile compounds (VC), can be incorporated in the food packaging materials to control the fungal growth during fruit packaging. However, if the VC is incorporated directly in the packaging material, it is released very fast due to VC high volatility. For this reason, the formation of inclusion complexes through the encapsulation of VC into beta-cyclodextrin (β-CD) and their incorporation in package materials is an alternative to maintain an antifungal atmosphere around the packaged fruits for longer times. In this context, the aim of this work was to develop inclusion complexes based in β-CD and VC (β-CD:VC) for further application in the antifungal food packaging materials development. β-CD:VC inclusion complexes were obtained with two different molar ratios 2:1 and 1:1, through co-precipitation method. The entrapment efficiency of β-CD:VC as well the release of antifungal compound from inclusion complexes exposed to different relative humidity (25, 50, and 97 %) to headspace were determined by gaseous chromatography (GC). Also, thermal and antimicrobial properties of β-CD:VC were determined through thermogravimetric analysis (TGA) and antifungal assays against Botrytis cinerea, respectively. GC results showed that β-CD:VC 2:1 had a higher entrapment efficiency than β-CD:VC 1:1, with values of 75.5 ± 3.71 % and 59.6 ± 1.51 %, respectively. It was probably because during the synthesis of β-CD:VC 1:1, there was less molecular space to the movement of VC molecules. Furthermore, the release of VC from β-CD:VC was directly related with the relative humidity. High amount of VC was released when the inclusion complexes were exposed to high humidity, possibly due to the interactions between the water molecules and the β-CD hydrophilic wall. On the other hand, a better thermal stability of VC in inclusion complexes allowed to verify its effective encapsulation into β-CD. Finally, antimicrobial assays showed that the inclusion complexes had a high antifungal activity at very low concentrations. Therefore, the results obtained in this work allow suggesting the β-CD:VC inclusion complexes as potential candidates to the development of fruit antifungal packaging materials, which activity is relative humidity dependent.

Keywords: Botrytis cinerea, fruit packaging, headspace release, volatile compounds

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Authors: Ali Göksenli, Barlas Eryürek

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In this study, failure analysis of pipe system at a micro hydroelectric power plant is investigated. Failure occurred at the pipe system in the powerhouse during shut down operation of the water flow by a valve. This locking had caused a sudden shock wave, also called “Water-hammer effect”, resulting in noise and inside pressure increase. After visual investigation of the effect of the shock wave on the system, a circumference crack was observed at the pipe flange weld region. To establish the reason for crack formation, calculations of pressure and stress values at pipe, flange and welding seams were carried out and concluded that safety factor was high (2.2), indicating that no faulty design existed. By further analysis, pipe system and hydroelectric power plant was examined. After observations it is determined that the plant did not include a ventilation nozzle (air trap), that prevents the system of sudden pressure increase inside the pipes which is caused by water-hammer effect. Analyses were carried out to identify the influence of water-hammer effect on inside pressure increase and it was concluded that, according Jowkowsky’s equation, shut down time is effective on inside pressure increase. The valve closing time was uncertain but by a shut down time of even one minute, inside pressure would increase by 7.6 bar (working pressure was 34.6 bar). Detailed investigations were also carried out on the assembly of the pipe-flange system by considering technical drawings. It was concluded that the pipe-flange system was not installed according to the instructions. Two of five weld seams were not applied and one weld was carried out faulty. This incorrect and inadequate weld seams resulted in; insufficient connection of the pipe to the flange constituting a strong notch effect at weld seam regions, increase in stress values and the decrease of strength and safety factor

Keywords: failure analysis, hydroelectric plant, crack, shock wave, welding seam

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Authors: Luis Amador Jimenez, Md. Shohel Amin

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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.

Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization

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Authors: Camilla Elphick, Graham Hole, Samuel Hutton, Graham Pike

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Pupil size has been found to change irrespective of luminosity, suggesting that it can be used to make inferences about cognitive processes, such as cognitive load. To see whether identifying a target requires a different cognitive load to rejecting distractors, the effect of viewing a target (compared with viewing distractors) on pupil size was investigated using a sequential video lineup procedure with two lineup sessions. Forty one participants were chosen randomly via the university. Pupil sizes were recorded when viewing pre target distractors and post target distractors and compared to pupil size when viewing the target. Overall, pupil size was significantly larger when viewing the target compared with viewing distractors. In the first session, pupil size changes were significantly different between participants who identified the target (Hits) and those who did not. Specifically, the pupil size of Hits reduced significantly after viewing the target (by 26%), suggesting that cognitive load reduced following identification. The pupil sizes of Misses (who made no identification) and False Alarms (who misidentified a distractor) did not reduce, suggesting that the cognitive load remained high in participants who failed to make the correct identification. In the second session, pupil sizes were smaller overall, suggesting that cognitive load was smaller in this session, and there was no significant difference between Hits, Misses and False Alarms. Furthermore, while the frequency of Hits increased, so did False Alarms. These two findings suggest that the benefits of including a second session remain uncertain, as the second session neither provided greater accuracy nor a reliable way to measure it. It is concluded that pupil size is a measure of face recognition strength in the first session of a target present lineup procedure. However, it is still not known whether cognitive load is an adequate explanation for this, or whether cognitive engagement might describe the effect more appropriately. If cognitive load and cognitive engagement can be teased apart with further investigation, this would have positive implications for understanding eyewitness identification. Nevertheless, this research has the potential to provide a tool for improving the reliability of lineup procedures.

Keywords: cognitive load, eyewitness identification, face recognition, pupillometry

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Authors: Umashankar Morya, Somnath Basu

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Metalloids like arsenic are often present as contaminants in industrial effluents. Removal of the same is essential before the safe discharge of the wastewater into the environment. Otherwise, these pollutants tend to percolate into aquifers over a period of time and contaminate drinking water sources. Several adsorbents, including metal powders, carbon nanotubes and zeolites, are being used for this purpose, with varying degrees of success. However, most of these solutions are not only costly but also not always readily available. This restricts their use, especially among financially weaker communities. Slag generated globally from primary steelmaking operations exceeds 200 billion kg every year. Some of it is utilized for applications like road construction, filler in reinforced concrete, railway track ballast and recycled into iron ore agglomeration processes. However, these usually involve low-value addition, and a significant amount of the slag still ends up in a landfill. However, there is a strong possibility that the constituents in the steelmaking slag may immobilize metalloid contaminants present in wastewater through a combination of adsorption and precipitation of insoluble product(s). Preliminary experiments have already indicated that exposure to basic oxygen steelmaking slag does reduce pollutant concentration in wastewater. In addition, the slag is relatively inexpensive and available in large quantities and in several countries across the world. Investigations on the mechanism of interactions at the water-solid interfaces have been in progress for some time. However, at the same time, there are concerns about the possibility of leaching of metal ions from the slag particles in concentrations greater than what exists in the water bodies where the “treated” wastewater would eventually be discharged. The effect of such leached ions on the aquatic flora and fauna is yet uncertain. This has prompted the present investigation, which focuses on the leaching of metal ions from steelmaking slag particles in contact with wastewater, and the influence of these ions on the removal of contaminant species. Experiments were carried out to quantify the leaching behavior of different ionic species upon exposure of the slag particles to simulated wastewater, both with and without specific metalloid contaminants.

Keywords: slag, water, metalloid, heavy metal, wastewater

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Authors: Baburao Ganpat Apte, Gajodhar

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Introduction: diopathic Parkinson’s disease (PD) is the most common neurodegenerative disorder. Early PD may present a diagnostic challenge with broad differential diagnoses that are not associated with striatal dopamine deficiency. This test was performed by using special type of radioactive precursor which was made available through our logistics. 131I-TOPA L-6-[131I] Iodo-3,4-Trihydroxyphenylalnine (131I -TOPA) is a positron emission tomography (PET) agent that measures the uptake of dopamine precursors for assessment of presynaptic dopaminergic integrity and has been shown to accurately reflect the sign of nervous mind going in patients suffers from monoaminergic disturbances in PD. Both qualitative and quantitative analyses of the scans were performed. Therefore, the early clinical diagnosis alone may be accurate and this reinforces the importance of functional imaging targeting the patholigically of the disease process. The patient’s medical records were then assessed for length of follow-up, response to levotopa, clinical course of sickness, and usually though of symptoms at time of 131I -TOPA PET. A respective analysis was carried out for all patients that gone through 131I -TOPA PET brain scan for motor symptoms suspicious for PD between 2000 - 2006. The eventual diagnosis by the referring neurologist, movement therapist, physiotherapist, was used as the accurate measurements in standard for further analysis. In this study, our goal to illustrate our local experience to determine the accuracy of 131I -TOPA PET for diagnosis of PD. We studied a total of 48 patients. Of the 25 scans, it found that one was a false negative, 40 were true positives, and 7 were true negatives. The resultant values are Sensitivity 90.4% (95% CI: 100%-71.3%), Specificity 100% (92% CI: 100%-58.0%), PPV 100% (91% CI 100%-75.7%), and NPV 80.5% (95% CI: 92.5%-48.5%). Result: Twenty-three patients were found in the initial query, and 1 were excluded (2 uncertain diagnosis, 2 inadequate follow-up). Twenty-eight patients (28 scans) remained with 15 males (62%) and 8 females (30%). All the patients had a clinical follow-up of at least 3 years, however the median length of follow-up was 5.5 years (range: 2-8 years). The median age at scan time was 51.2 years (range: 35-75)

Keywords: 18F-TOPA, petct, parkinson’s disease, cardiac

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Authors: Keng H. Kong, Louis C. Tan, Wing L. Aw, Kay Y. Tay

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Background: Fatigue is a common problem in patients with Parkinson's disease, with reported prevalence of up to 70%. Fatigue can be disabling and has adverse effects on patients' quality of life. There is currently no satisfactory treatment of fatigue. Acupuncture is effective in the treatment of fatigue, especially that related to cancer. Its role in Parkinson's disease-related fatigue is uncertain. Aims: To evaluate the clinical efficacy of acupuncture treatment in Parkinson's disease-related fatigue. Hypothesis: We hypothesize that acupuncture is effective in alleviating Parkinson's disease-related fatigue. Design: A single center, randomized, controlled study with two parallel arms. Participants: Forty participants with idiopathic Parkinson's disease will be enrolled. Interventions: Participants will be randomized to receive verum (real) acupuncture or placebo acupuncture. The retractable non-invasive sham needle will be used in the placebo group. The intervention will be administered twice a week for five weeks. Main outcome measures: The primary outcome will be the change in general fatigue score of the multidimensional fatigue inventory at week 5. Secondary outcome measures include other subscales of the multidimensional fatigue inventory, movement disorders society-unified Parkinson's disease rating scale, Parkinson's disease questionnaire-39 and geriatric depression scale. All outcome measures will be assessed at baseline (week 0), completion of intervention (week 5) and 4 weeks after completion of intervention (week 9). Results: To date, 23 participants have been recruited and nine have completed the study. The mean age is 63.5±14.2 years, mean duration of Parkinson’s disease is 6.4±1.8 years and mean MDS-UPDRS score is 8.3±2.8. The mean general fatigue score of the multidimensional fatigue inventory is 13.5±4.6. No significant adverse event related to acupuncture is noted. Potential significance: If the results are as expected, this study will provide preliminary scientific evidence for the efficacy of acupuncture in Parkinson's Disease-related fatigue, and opens the door for a larger multicentre trial to be performed. In the longer term, it may lead to the integration of acupuncture in the care of patients with Parkinson's disease.

Keywords: acupuncture, fatigue, Parkinson's disease, trial

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Authors: Michael A. Sprayberry, Vincent C. Paquit

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Process parameter optimization in metal powder bed electron beam melting (MPBEBM) is crucial to ensure the technology's repeatability, control, and industry-continued adoption. Despite continued efforts to address the challenges via the traditional design of experiments and process mapping techniques, there needs to be more successful in an on-the-fly optimization framework that can be adapted to MPBEBM systems. Additionally, data-intensive physics-based modeling and simulation methods are difficult to support by a metal AM alloy or system due to cost restrictions. To mitigate the challenge of resource-intensive experiments and models, this paper introduces a Multi-Objective Reinforcement Learning (MORL) methodology defined as an optimization problem for MPBEBM. An off-policy MORL framework based on policy gradient is proposed to discover optimal sets of beam power (P) – beam velocity (v) combinations to maintain a steady-state melt pool depth and phase transformation. For this, an experimentally validated Eagar-Tsai melt pool model is used to simulate the MPBEBM environment, where the beam acts as the agent across the P – v space to maximize returns for the uncertain powder bed environment producing a melt pool and phase transformation closer to the optimum. The culmination of the training process yields a set of process parameters {power, speed, hatch spacing, layer depth, and preheat} where the state (P,v) with the highest returns corresponds to a refined process parameter mapping. The resultant objects and mapping of returns to the P-v space show convergence with experimental observations. The framework, therefore, provides a model-free multi-objective approach to discovery without the need for trial-and-error experiments.

Keywords: additive manufacturing, metal powder bed fusion, reinforcement learning, process parameter optimization

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Authors: Mehrdad Abkenari, Orod Zarrinkafsh, Mohsen Ramezan Shirazi

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Construction projects initiate in complicated dynamic environments and, due to the close relationships between project parameters and the unknown outer environment, they are faced with several uncertainties and risks. Success in time, cost and quality in large scale construction projects is uncertain in consequence of technological constraints, large number of stakeholders, too much time required, great capital requirements and poor definition of the extent and scope of the project. Projects that are faced with such environments and uncertainties can be well managed through utilization of the concept of risk management in project’s life cycle. Although the concept of risk is dependent on the opinion and idea of management, it suggests the risks of not achieving the project objectives as well. Furthermore, project’s risk analysis discusses the risks of development of inappropriate reactions. Since evaluation and prioritization of construction projects has been a difficult task, the network structure is considered to be an appropriate approach to analyze complex systems; therefore, we have used this structure for analyzing and modeling the issue. On the other hand, we face inadequacy of data in deterministic circumstances, and additionally the expert’s opinions are usually mathematically vague and are introduced in the form of linguistic variables instead of numerical expression. Owing to the fact that fuzzy logic is used for expressing the vagueness and uncertainty, formulation of expert’s opinion in the form of fuzzy numbers can be an appropriate approach. In other words, the evaluation and prioritization of construction projects on the basis of risk factors in real world is a complicated issue with lots of ambiguous qualitative characteristics. In this study, evaluated and prioritization the risk parameters and factors with fuzzy logy method by combination of three method DEMATEL (Decision Making Trial and Evaluation), ANP (Analytic Network Process) and TOPSIS (Technique for Order-Preference by Similarity Ideal Solution) on Construction Management.

Keywords: fuzzy logy, risk, prioritization, assessment

Procedia PDF Downloads 587

Authors: Abhinav Kumar Rajverma, Arun Kumar Misra, Abhijeet Chandra

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Family involvement in business is universal across countries, with varying characteristics. Firms of developed economies have diffused ownership structure; however, that of emerging markets have concentrated ownership structure, having resemblance with that of family firms. Optimization of dividend payout and leverage are very crucial for firm’s valuation. This paper studies dividend paying behavior of National Stock Exchange listed Indian firms from financial year 2007 to 2016. The final sample consists of 422 firms and of these more than 49% (207) are family firms. Results reveal that family firms pay lower dividend and are more leveraged compared to non-family firms. This unique data set helps to understand dividend behavior and capital structure of sample firms over a long-time period and across varying family ownership concentration. Using panel regression models, this paper examines factors affecting dividend payout and capital structure and establishes a link between the two using Two-stage Least Squares regression model. Profitability shows a positive impact on dividend and negative impact on leverage, confirming signaling and pecking order theory. Further, findings support bankruptcy theory as firm size has a positive relation with dividend and leverage and volatility shows a negative relation with both dividend and leverage. Findings are also consistent with agency theory, family ownership concentration has negative relation with both dividend payments and leverage. Further, the impact of family ownership control confirms the similar finding. The study further reveals that firms with high family ownership concentration (family control) do have an impact on determining the level of private benefits. Institutional ownership is not significant for dividend payments. However, it shows significant negative relation with leverage for both family and non-family firms. Dividend payout and leverage show mixed association with each other. This paper provides evidence of how varying level of family ownership concentration and ownership control influences the dividend policy and capital structure of firms in an emerging market like India and it can have significant contribution towards understanding and formulating corporate dividend policy decisions and capital structure for emerging economies, where majority of firms exhibit behavior of family firm.

Keywords: dividend, family firms, leverage, ownership structure

Procedia PDF Downloads 274