Search results for: neural network models

Authors: Edwin Calderon-Mendoza, Patrick Schweitzer, Serge Weber

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Series arc faults appear frequently and unpredictably in low voltage distribution systems. Many methods have been developed to detect this type of faults and commercial protection systems such AFCI (arc fault circuit interrupter) have been used successfully in electrical networks to prevent damage and catastrophic incidents like fires. However, these devices do not allow series arc faults to be located on the line in operating mode. This paper presents a location algorithm for series arc fault in a low-voltage indoor power line in an AC 230 V-50Hz home network. The method is validated through simulations using the MATLAB software. The fault location method uses electrical parameters (resistance, inductance, capacitance, and conductance) of a 49 m indoor power line. The mathematical model of a series arc fault is based on the analysis of the V-I characteristics of the arc and consists basically of two antiparallel diodes and DC voltage sources. In a first step, the arc fault model is inserted at some different positions across the line which is modeled using lumped parameters. At both ends of the line, currents and voltages are recorded for each arc fault generation at different distances. In the second step, a fault map trace is created by using signature coefficients obtained from Kirchhoff equations which allow a virtual decoupling of the line’s mutual capacitance. Each signature coefficient obtained from the subtraction of estimated currents is calculated taking into account the Discrete Fast Fourier Transform of currents and voltages and also the fault distance value. These parameters are then substituted into Kirchhoff equations. In a third step, the same procedure described previously to calculate signature coefficients is employed but this time by considering hypothetical fault distances where the fault can appear. In this step the fault distance is unknown. The iterative calculus from Kirchhoff equations considering stepped variations of the fault distance entails the obtaining of a curve with a linear trend. Finally, the fault distance location is estimated at the intersection of two curves obtained in steps 2 and 3. The series arc fault model is validated by comparing current registered from simulation with real recorded currents. The model of the complete circuit is obtained for a 49m line with a resistive load. Also, 11 different arc fault positions are considered for the map trace generation. By carrying out the complete simulation, the performance of the method and the perspectives of the work will be presented.

Keywords: indoor power line, fault location, fault map trace, series arc fault

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Authors: Stephen Anim, Emmanuel O. Sarpong, Daniel Apaak

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This study investigates the relationship between morphological predictors and running ability, emphasizing gender-specific variations among male and female athletes in Cape Coast Metropolis (CCM), Ghana. The dynamic interplay between an athlete's physique and their performance capabilities holds particular relevance in the realm of sports science, influencing training methodologies and talent identification processes. The research aims to contribute comprehensive insights into the morphological determinants of running proficiency, with a specific focus on the local athletic community in Cape Coast Metropolis. Utilizing a correlational research design, a thorough analysis of morphological features, encompassing 22 morphological features including body weight, 6 measurements related to body length, 7 body girth, and knee diameter, and 7 skinfold measurements against 50m dash, among male and female athletes, was conducted. The study involved 420 athletes both male (N=210) and female (N=210) aged 16-22 from 10 Senior High Schools (SHS) in the Cape Coast Metropolis, providing a representative sample of the local athletic community. The collected data were statistically analysed using means and standard deviation, and stepwise multiple regression to determine how morphological variables contribute to and predict running proficiency outcomes. The investigation revealed that athletes from Senior High Schools (SHS) in Cape Coast Metropolis (CCM) exhibit well-developed physiques and sufficient fitness levels suitable for overall athletic performance, taking into account gender differences. Moreover, the findings suggested that approximately 77% of running ability could be attributed to morphological factors, leading to diverse predictive models for male and female athletes within SHS in CCM, Ghana. Consequently, these formulated equations hold promise for predicting running ability among young athletes, particularly in the context of SHS environments.

Keywords: body fat, body girth, body length, morphological features, running ability, senior high school

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Authors: Shanker Kalakotla, Krishna Mohan Gottumukkala

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Diabetes is a metabolic disorder characterized by hyperglycemia, carbohydrates, altered lipids and proteins metabolism. In recent research nanotechnology is a blazing field for the researchers; latterly there has been prodigious excitement in the nanomedicine and nano pharmacological area for the study of silver nanoparticles synthesis using natural products. Biological methods have been used to synthesize silver nanoparticles in presence of medicinally active antidiabetic plants, and this intention made us assess the biologically synthesized silver nanoparticles from the seed extract of Psoralea corylfolia using 1 mM silver nitrate solution. The synthesized herbal mediated silver nanoparticles (HMSNP’s) then subjected to various characterization techniques such as XRD, SEM, EDX, TEM, DLS, UV and FT-IR respectively. In current study, the silver nanoparticles tested for in-vitro anti-diabetic activity and possible toxic effects in healthy female albino mice by following OECD guidelines-425. Herbal mediated silver nanoparticles were successfully obtained from bioreduction of silver nitrate using Psoralea corylifolia plant extract. Silver nanoparticles have been appropriately characterized and confirmed using different types of equipment viz., UV-vis spectroscopy, XRD, FTIR, DLS, SEM and EDX analysis. From the behavioral observations of the study, the female albino mice did not show sedation, respiratory arrest, and convulsions. Test compounds did not cause any mortality at the dose level tested (i.e., 2000 mg/kg body weight) doses till the end of 14 days of observation and were considered safe. It may be concluded that LD50 of the HMSNPs was 2000mg/kg body weight. Since LD50 of the HMSNPs was 2000mg/kg body weight, so the preferred dose range for HMSNPs falls between the levels of 200 and 400 mg/kg. Further In-vivo pharmacological models and biochemical investigations will clearly elucidate the mechanism of action and will be helpful in projecting the currently synthesized silver nanoparticles as a therapeutic target in treating chronic ailments.

Keywords: herbal mediated silver nanoparticles, HMSNPs, toxicity of silver nanoparticles, PTP1B in-vitro anti-diabetic assay female albino mice, 425 OECD guidelines

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Authors: Jožef Ritonja, Bojan Grčar, Boštjan Polajžer

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In recent years, electricity trade between neighboring countries has become increasingly intense. Increasing power transmission over long distances has resulted in an increase in the oscillations of the transmitted power. The damping of the oscillations can be carried out with the reconfiguration of the network or the replacement of generators, but such solution is not economically reasonable. The only cost-effective solution to improve the damping of power oscillations is to use power system stabilizers. Power system stabilizer represents a part of synchronous generator control system. It utilizes semiconductor’s excitation system connected to the rotor field excitation winding to increase the damping of the power system. The majority of the synchronous generators are equipped with the conventional power system stabilizers with fixed parameters. The control structure of the conventional power system stabilizers and the tuning procedure are based on the linear control theory. Conventional power system stabilizers are simple to realize, but they show non-sufficient damping improvement in the entire operating conditions. This is the reason that advanced control theories are used for development of better power system stabilizers. In this paper, the adaptive control theory for power system stabilizers design and synthesis is studied. The presented work is focused on the use of model reference adaptive control approach. Control signal, which assures that the controlled plant output will follow the reference model output, is generated by the adaptive algorithm. Adaptive gains are obtained as a combination of the "proportional" term and with the σ-term extended "integral" term. The σ-term is introduced to avoid divergence of the integral gains. The necessary condition for asymptotic tracking is derived by means of hyperstability theory. The benefits of the proposed model reference adaptive power system stabilizer were evaluated as objectively as possible by means of a theoretical analysis, numerical simulations and laboratory realizations. Damping of the synchronous generator oscillations in the entire operating range was investigated. Obtained results show the improved damping in the entire operating area and the increase of the power system stability. The results of the presented work will help by the development of the model reference power system stabilizer which should be able to replace the conventional stabilizers in power systems.

Keywords: power system, stability, oscillations, power system stabilizer, model reference adaptive control

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Authors: Jessica Gu, Yu Chen

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Knowledge Management (KM) is undoubtable crucial to organizational value creation, learning, and adaptation. Although the rapidly growing KM domain has been fueled with full-fledged methodologies and technologies, studies on KM evolution that bridge the organizational performance and adaptation to the organizational environment are still rarely attempted. In particular, creation (or generation) and diffusion (or share/exchange) of knowledge are of the organizational primary concerns on the problem-solving perspective, however, the optimized distribution of knowledge creation and diffusion endeavors are still unknown to knowledge workers. This research proposed an agent-based model of knowledge creation and diffusion in an organization, aiming at elucidating how the intertwining knowledge flows at microscopic level lead to optimized organizational performance at macroscopic level through evolution, and exploring what exogenous interventions by the policy maker and endogenous adjustments of the knowledge workers can better cope with different environmental conditions. With the developed model, a series of simulation experiments are conducted. Both long-term steady-state and time-dependent developmental results on organizational performance, network and structure, social interaction and learning among individuals, knowledge audit and stocktaking, and the likelihood of choosing knowledge creation and diffusion by the knowledge workers are obtained. One of the interesting findings reveals a non-monotonic phenomenon on organizational performance under turbulent environment while a monotonic phenomenon on organizational performance under a stable environment. Hence, whether the environmental condition is turbulence or stable, the most suitable exogenous KM policy and endogenous knowledge creation and diffusion choice adjustments can be identified for achieving the optimized organizational performance. Additional influential variables are further discussed and future work directions are finally elaborated. The proposed agent-based model generates evidence on how knowledge worker strategically allocates efforts on knowledge creation and diffusion, how the bottom-up interactions among individuals lead to emerged structure and optimized performance, and how environmental conditions bring in challenges to the organization system. Meanwhile, it serves as a roadmap and offers great macro and long-term insights to policy makers without interrupting the real organizational operation, sacrificing huge overhead cost, or introducing undesired panic to employees.

Keywords: knowledge creation, knowledge diffusion, agent-based modeling, organizational performance, decision making evolution

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Authors: P. Annapurna, Cecil Ross, Sudhir Krishna, Sweta Srivastava

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Irradiation plays a pivotal role in cervical cancer treatment, however some tumors exhibit resistance to therapy while some exhibit relapse, due to better repair and enhanced resistance mechanisms operational in their cells. The present study aims to understand the signaling mechanism operational in resistance phenotype and in the present study we report the role of Rho GTPase associated protein kinase (ROCK) signaling in cervical carcinoma radio-resistance. ROCK signaling has been implicated in several tumor progressions and is important for DNA repair. Irradiation of spheroid cultures of SiHa cervical carcinoma derived cell line at 6Gy resulted in generation of resistant cells in vitro which had better clonogenic abilities and formed larger and more colonies, in soft agar colony formation assay, as compared to the non-irradiated cells. These cells also exhibited an enhanced motility phenotype. Cell cycle profiling showed the cells to be blocked in G2M phase with enhanced pCDC2 levels indicating onset of possible DNA repair mechanism. Notably, 3 days post-irradiation, irradiated cells showed increased ROCK2 translocation to the nucleus with enhanced protein expression as compared to the non-irradiated cells. Radio-sensitization of the resistant cells was enhanced using Y27632, an inhibitor to ROCK signaling. The treatment of resistant cells with Y27632 resulted in increased cell death upon further irradiation. This observation has been confirmed using inhibitory antibodies to ROCK1/2. Result show that both ROCK1/2 have a functional contribution in radiation resistance of cervical cancer cells derived from cell lines. Interestingly enrichment of stem like cells (Hoechst negative cells) was also observed upon irradiation and these cells were markedly sensitive to Y27632 treatment. Our results thus suggest the role of ROCK signaling in radio-resistance in cervical carcinoma. Further studies with human biopsies, mice models and mechanistic of ROCK signaling in the context of radio-resistance will clarify the role of this molecule further and allow for therapeutics development.

Keywords: cervical carcinoma, radio-resistance, ROCK signaling, cancer treatment

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Authors: Rui Fonseca-Pinto, Emanuel Silva, Rui Rijo, Ricardo Martinho, Bruno Carreira

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The sedentary lifestyle is associated to the development of chronic noncommunicable diseases (obesity, hypertension, Diabetes Mellitus Type 2) and the World Health Organization, given the evidence that physical activity is determinant for individual and collective health, defined the Physical Activity Level (PAL) as a vital signal. Strategies for increasing the practice of physical activity in all age groups have emerged from the various social organizations (municipalities, universities, health organizations, companies, social groups) by increasingly developing innovative strategies to promote motivation strategies and conditions to the practice of physical activity. The adaptation of cities to the new paradigms of sustainable mobility has provided the adaptation of urban training circles and mobilized citizens to combat sedentarism. This adaptation has accompanied the technological evolution and makes possible the use of mobile technology to monitor outdoor training programs and also, through the network connection (IoT), use the training data to make personalized recommendations. This work presents a physical activity counseling platform to be used in the physical maintenance circuits of urban centers, the MOVIDA.polis. The platform consists of a back office for the management of circuits and training stations, and for a mobile application for monitoring the user performance during workouts. Using a QRcode, each training station is recognized by the App and based on the individual performance records (effort perception, heart rate variation) artificial intelligence algorithms are used to make a new personalized recommendation. The results presented in this work were obtained during the proof of concept phase, which was carried out in the PolisLeiria training circuit in the city of Leiria (Portugal). It was possible to verify the increase in adherence to the practice of physical activity, as well as to decrease the interval between training days. Moreover, the AI-based recommendation acts as a partner in the training and an additional challenging factor. The platform is ready to be used by other municipalities in order to reduce the levels of sedentarism and approach the weekly goal of 150 minutes of moderate physical activity. Acknowledgments: This work was supported by Fundação para a Ciência e Tecnologia FCT- Portugal and CENTRO2020 under the scope of MOVIDA project: 02/SAICT/2016 – 23878.

Keywords: physical activity, mHealth, urban training circuits, health promotion

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Authors: Sharda Kumari

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As the Covid-19 pandemic continues to leave its mark on the global business landscape, companies have had to adapt to new realities and find ways to sustain their operations amid social distancing measures, government restrictions, and heightened public health concerns. This unprecedented situation has placed considerable stress on both employees and employers, underscoring the need for innovative approaches to manage the risks associated with Covid-19 transmission in the workplace. In response to these challenges, the pandemic has accelerated the adoption of digital technologies, with an increasing preference for remote interactions and virtual collaboration. Customer relationship management (CRM) systems have risen to prominence as a vital resource for organizations navigating the post-pandemic world, providing a range of benefits that include acquiring new customers, generating insightful consumer data, enhancing customer relationships, and growing market share. In the context of pandemic management, CRM systems offer three primary advantages: (1) integration features that streamline operations and reduce the need for multiple, costly software systems; (2) worldwide accessibility from any internet-enabled device, facilitating efficient remote workforce management during a pandemic; and (3) the capacity for rapid adaptation to changing business conditions, given that most CRM platforms boast a wide array of remotely deployable business growth solutions, a critical attribute when dealing with a dispersed workforce in a pandemic-impacted environment. These advantages highlight the pivotal role of CRM systems in helping organizations remain resilient and adaptive in the face of ongoing global challenges.

Keywords: healthcare, CRM, customer relationship management, customer experience, digital transformation, pandemic response, patient monitoring, patient management, healthcare automation, electronic health record, patient billing, healthcare information systems, remote workforce, virtual collaboration, resilience, adaptable business models, integration features, CRM in healthcare, telehealth, pandemic management

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Authors: Muhammad Ali Siddiquee, Md. Alauddin, Md. Omar Faruque, Zakir Hossain Howlader, Mohammad Asaduzzaman

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Rice bran (RB) and rice bran oil (RBO) are explored as prominent food components worldwide. In this study, fermented rice bran (FRB) was produced by employing edible gram-positive bacteria (Lactobacillus acidophilus, Lactobacillus bulgaricus, and Bifidobacterium bifidum) at 125 x 10⁵ spore g⁻¹ of rice bran, and investigated to evaluate nutritional quality. The crude rice bran oil (CRBO) was extracted from RB, and its quality was also investigated compared to market-available rice bran oil (MRBO) in Bangladesh. We found that fermentation of rice bran with lactic acid bacteria increased total proteins (29.52%), fat (5.38%), ash (48.47%), crude fiber (38.96%), and moisture (61.04%) and reduced the carbohydrate content (36.61%). We also found that essential amino acids (methionine, tryptophan, threonine, valine, leucine, lysine, histidine, and phenylalanine) and non-essential amino acids (alanine, aspartate, glycine, glutamine, proline, serine, and tyrosine) were increased in FRB except methionine and proline. Moreover, total phenolic content, tannin content, flavonoid content, and antioxidant activity were increased in FRB. The RBO analysis showed that γ-oryzanol content (10.00mg/g) was found in CRBO compared to MRBO (ranging from 7.40 to 12.70 mg/g) and Vitamin-E content 0.20% was found higher in CRBO compared to MRBO (ranging 0.097 to 0.12%). The total saturated (25.16%) and total unsaturated fatty acids (74.44%) were found in CRBO, whereas MRBO contained total saturated (22.08 to 24.13%) and total unsaturated fatty acids (71.91 to 83.29%), respectively. The physiochemical parameters were found satisfactory in all samples except acid value and peroxide value higher in CRBO. Finally, animal experiments showed that FRB and CRBO reduce the body weight, glucose, and lipid profile in high-fat diet-induced animal models. Thus, FRB and RBO could be value-added food supplements for human health.

Keywords: fermented rice bran, crude rice bran oil, amino acids, proximate composition, gamma-oryzanol, fatty acids, heavy metals, physiochemical parameters

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Authors: Jae-Yong Park, Yeo-Kyeong Lee, Hee-Sun Kim

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Purpose: This study aims at investigating the mechanical behaviors of mastication, according to various teeth movement. There are three masticatory cases which are general case and 2 cases of teeth movement. General case includes the common arrange of all teeth and 2 cases of teeth movement are that one is the half movement location case of molar teeth in no. 14 tooth seat after extraction of no. 14 tooth and the other is no. 14 tooth seat location case of molar teeth after extraction in the same case before. Materials and Methods: In order to analyze these cases, 3 dimensional finite element (FE) model of the skull were generated based on computed tomography images, 964 dicom files of 38 year old male having normal occlusion status. An FE model in general occlusal case was used to develop CAE procedure. This procedure was applied to FE models in other occlusal cases. The displacement controls according to loading condition were applied effectively to simulate occlusal behaviors in all cases. From the FE analyses, von Mises stress distribution of skull and teeth was observed. The von Mises stress, effective stress, had been widely used to determine the absolute stress value, regardless of stress direction and yield characteristics of materials. Results: High stress was distributed over the periodontal area of mandible under molar teeth when the mandible was transmitted to the coronal-apical direction in the general occlusal case. According to the stress propagation from teeth to cranium, stress distribution decreased as the distribution propagated from molar teeth to infratemporal crest of the greater wing of the sphenoid bone and lateral pterygoid plate in general case. In 2 cases of teeth movement, there were observed that high stresses were distributed over the periodontal area of mandible under teeth where they are located under the moved molar teeth in cranium. Conclusion: The predictions of the mechanical behaviors of general case and 2 cases of teeth movement during the masticatory process were investigated including qualitative validation. The displacement controls as the loading condition were applied effectively to simulate occlusal behaviors in 2 cases of teeth movement of molar teeth.

Keywords: cranium, finite element analysis, mandible, masticatory action, occlusal force

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Authors: Kholoud Abdulaziz, Kholoud Al-Najdi, Abdullah Kadri, Konstantinos E. Kakosimos

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The Middle East area is highly affected by air pollution induced by anthropogenic and natural phenomena. There is evidence that air pollution, especially particulates, greatly affects the population health. Many studies have raised a warning of the high concentration of particulates and their affect not just around industrial and construction areas but also in the immediate working and living environment. One of the methods to study air quality is continuous and periodic monitoring using active or passive samplers. Active monitoring and sampling are the default procedures per the European and US standards. However, in many cases they have been inefficient to accurately capture the spatial variability of air pollution due to the small number of installations; which eventually is attributed to the high cost of the equipment and the limited availability of users with expertise and scientific background. Another alternative has been found to account for the limitations of the active methods that is the passive sampling. It is inexpensive, requires no continuous power supply, and easy to assemble which makes it a more flexible option, though less accurate. This study aims to investigate and evaluate the use of passive sampling for particulate matter pollution monitoring in dry tropical climates, like in the Middle East. More specifically, a number of field measurements have be conducted, both indoors and outdoors, at Qatar and the results have been compared with active sampling equipment and the reference methods. The samples have been analyzed, that is to obtain particle size distribution, by applying existing laboratory techniques (optical microscopy) and by exploring new approaches like the white light interferometry to. Then the new parameters of the well-established model have been calculated in order to estimate the atmospheric concentration of particulates. Additionally, an extended literature review will investigate for new and better models. The outcome of this project is expected to have an impact on the public, as well, as it will raise awareness among people about the quality of life and about the importance of implementing research culture in the community.

Keywords: air pollution, passive samplers, interferometry, indoor, outdoor

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Authors: Jae Ni Jang, Young Uk Kim

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Background: Chat Generative Pre-training Transformer-3 (ChatGPT; San Francisco, California, Open Artificial Intelligence) is an artificial intelligence chatbot based on a large language model designed to generate human-like text. As the usage of ChatGPT is increasing among less knowledgeable patients, medical students, and anesthesia and pain medicine residents or trainees, we aimed to evaluate the accuracy of ChatGPT-3 responses to questions about the American Society of Anesthesiologists (ASA) classification based on patients’ underlying diseases and assess the quality of the generated responses. Methods: A total of 47 questions were submitted to ChatGPT using textual prompts. The questions were designed for ChatGPT-3 to provide answers regarding ASA classification in response to common underlying diseases frequently observed in adult patients. In addition, we created 18 questions regarding the ASA classification for pediatric patients and pregnant women. The accuracy of ChatGPT’s responses was evaluated by cross-referencing with Miller’s Anesthesia, Morgan & Mikhail’s Clinical Anesthesiology, and the American Society of Anesthesiologists’ ASA Physical Status Classification System (2020). Results: Out of the 47 questions pertaining to adults, ChatGPT -3 provided correct answers for only 23, resulting in an accuracy rate of 48.9%. Furthermore, the responses provided by ChatGPT-3 regarding children and pregnant women were mostly inaccurate, as indicated by a 28% accuracy rate (5 out of 18). Conclusions: ChatGPT provided correct responses to questions relevant to the daily clinical routine of anesthesiologists in approximately half of the cases, while the remaining responses contained errors. Therefore, caution is advised when using ChatGPT to retrieve anesthesia-related information. Although ChatGPT may not yet be suitable for clinical settings, we anticipate significant improvements in ChatGPT and other large language models in the near future. Regular assessments of ChatGPT's ASA classification accuracy are essential due to the evolving nature of ChatGPT as an artificial intelligence entity. This is especially important because ChatGPT has a clinically unacceptable rate of error and hallucination, particularly in pediatric patients and pregnant women. The methodology established in this study may be used to continue evaluating ChatGPT.

Keywords: American Society of Anesthesiologists, artificial intelligence, Chat Generative Pre-training Transformer-3, ChatGPT

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Authors: Zainab Algharibi, Julie McAdam, Catherine Fagan

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The purpose of this paper is to shed light on how Omani children in the first grade experience their needs during their transition to primary school. Theoretically, the paper was built on two perspectives: Dewey's concept of continuity of experience and the boundary objects introduced by Vygotsky (CHAT). The methodology of the study is based on the crucial role of children’s agency which is a very important activity as an educational tool to enhance the child’s participation in the learning process and develop their ability to face various issues in their life. Thus, the data were obtained from 45 children in grade one from 4 different primary schools using drawing and visual narrative activities, in addition to researcher observations during the start of the first weeks of the academic year for the first grade. As the study dealt with children, all of the necessary ethical laws were followed. This paper is considered original since it seeks to deal with the issue of children's transition from kindergarten to primary school in Oman, if not in the Arab region. Therefore, it is expected to fill an important gap in this field and present a proposal that will be a door for researchers to enter this research field later. The analysis of drawing and visual narrative was performed according to the social semiotics approach in two phases. The first is to read out the surface message “denotation,” while the second is to go in-depth via the symbolism obtained from children while they talked and drew letters and signs. This stage is known as “signified”; a video was recorded of each child talking about their drawing and expressing themself. Then, the data were organised and classified according to a cross-data network. Regarding the researcher observation analyses, the collected data were analysed according to the model was developed for the "grounded theory". It is based on comparing the recent data collected from observations with data previously encoded by other methods in which children were drawing alongside the visual narrative in the current study, in order to identify the similarities and differences, and also to clarify the meaning of the accessed categories and to identify sub-categories of them with a description of possible links between them. This is a kind of triangulation in data collection. The study came up with a set of findings, the most vital being that the children's greatest interest goes to their social and psychological needs, such as friends, their teacher, and playing. Also, their biggest fears are a new place, a new teacher, and not having friends, while they showed less concern for their need for educational knowledge and skills.

Keywords: children’s academic needs, children’s social needs, transition, primary school

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Authors: Elżbieta Turska

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Introduction: One of the most difficult times in a person’s life is adolescence. The experiences in this period may shape the future life of this person to a large extent. This is the reason why many young people experience sadness, dejection, hopelessness, sense of worthlessness, as well as losing interest in various activities and social relationships, all of which are often classified as mood disorders. As many as 15-40% adolescents experience depressed moods and for most of them they resolve and are not carried into adulthood. However, (5-6%) of those affected by mood disorders develop the depressive syndrome and as many as (1-3%) develop full-blown clinical depression. Materials: A large questionnaire was given to 2508 students, aged 13–16 years old, and one of its parts was the Burns checklist, i.e. the standard test for identifying depressed mood. The questionnaire asked about many aspects of the student’s life, it included a total of 53 questions, most of which had subquestions. It is important to note that the data suffered from many problems, the most important of which were missing data and collinearity. Aim: In order to identify the correlates of mood disorders we built predictive models which were then trained and validated. Our aim was not to be able to predict which students suffer from mood disorders but rather to explore the factors influencing mood disorders. Methods: The problems with data described above practically excluded using all classical statistical methods. For this reason, we attempted to use the following Artificial Intelligence (AI) methods: classification trees with surrogate variables, random forests and xgboost. All analyses were carried out with the use of the mlr package for the R programming language. Resuts: The predictive model built by classification trees algorithm outperformed the other algorithms by a large margin. As a result, we were able to rank the variables (questions and subquestions from the questionnaire) from the most to least influential as far as protection against mood disorder is concerned. Thirteen out of twenty most important variables reflect the relationships with parents. This seems to be a really significant result both from the cognitive point of view and also from the practical point of view, i.e. as far as interventions to correct mood disorders are concerned.

Keywords: mood disorders, adolescents, family, artificial intelligence

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Authors: Krunal Thakar

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Wire ropes combine high tensile strength and flexibility as compared to other general steel products. They are used in various application areas such as cranes, mining, elevators, bridges, cable cars, etc. The earliest reported use of wire ropes was for mining hoist application in 1830s. Over the period, there have been substantial advancement in the design of wire ropes for various application areas. Under operational conditions, wire ropes are subjected to varying tensile loads and bending loads resulting in material wear and eventual structural failure due to fretting fatigue. The conventional inspection methods to determine wire failure is only limited to outer wires of rope. However, till date, there is no effective mathematical model to examine the inter wire contact forces and wear characteristics. The scope of this paper is to present a computational simulation technique to evaluate inter wire contact forces and wear, which are in many cases responsible for rope failure. Two different type of ropes, IWRC-6xFi(29) and U3xSeS(48) were taken for structural strength evaluation and wear prediction. Both ropes have a double helix twisted wire profile as per JIS standards and are mainly used in cranes. CAD models of both ropes were developed in general purpose design software using in house developed formulation to generate double helix profile. Numerical simulation was done under two different load cases (a) Axial Tension and (b) Bending over Sheave. Different parameters such as stresses, contact forces, wear depth, load-elongation, etc., were investigated and compared between both ropes. Numerical simulation method facilitates the detailed investigation of inter wire contact and wear characteristics. In addition, various selection parameters like sheave diameter, rope diameter, helix angle, swaging, maximum load carrying capacity, etc., can be quickly analyzed.

Keywords: steel wire ropes, numerical simulation, material wear, structural strength, axial tension, bending over sheave

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Fazli Rahim Shinwari, Ulrich Dittmer

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Like many megacities around the world, Kabul is facing severe problems due to the rising frequency of urban flooding. Since 2001, Kabul is experiencing rapid population growth because of the repatriation of refugees and internal migration. Due to unplanned development, green areas inside city and hilly areas within and around the city are converted into new housing towns that had increased runoff. Trenches along the roadside comprise the unplanned drainage network of the city that drains the combined sewer flow. In rainy season overflow occurs, and after streets become dry, the dust particles contaminate the air which is a major cause of air pollution in Kabul city. In this study, a stormwater management model is introduced as a basis for a systematic approach to urban drainage planning in Kabul. For this purpose, Kabul city is delineated into 8 watersheds with the help of one-meter resolution LIDAR DEM. Storm, water management model, is developed for Wazirabad catchment by using available data and literature values. Due to lack of long term metrological data, the model is only run for hourly rainfall data of a rain event that occurred in April 2016. The rain event from 1st to 3rd April with maximum intensity of 3mm/hr caused huge flooding in Wazirabad Catchment of Kabul City. Model-estimated flooding at some points of the catchment as an actual measurement of flooding was not possible; results were compared with information obtained from local people, Kabul Municipality and Capital Region Independent Development Authority. The model helped to identify areas where flooding occurred because of less capacity of drainage system and areas where the main reason for flooding is due to blockage in the drainage canals. The model was used for further analysis to find a sustainable solution to the problem. The option to construct new canals was analyzed, and two new canals were proposed that will reduce the flooding frequency in Wazirabad catchment of Kabul city. By developing the methodology to develop a stormwater management model from digital data and information, the study had fulfilled the primary objective, and similar methodology can be used for other catchments of Kabul city to prepare an emergency and long-term plan for drainage system of Kabul city.

Keywords: urban hydrology, storm water management, modeling, SWMM, GEO-SWMM, GIS, identification of flood vulnerable areas, urban flooding analysis, sustainable urban drainage

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Authors: Eric Lacoste

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Laboratory animals are currently widely used as a model of human pathologies in dermatology such as atopic dermatitis (AD). These models provide a better understanding of the pathophysiology of this complex and multifactorial disease, the discovery of potential new therapeutic targets and the testing of the efficacy of new therapeutics. However, confirmation of the correct development of AD is mainly based on histology from skin biopsies requiring invasive surgery or euthanasia of the animals, plus slicing and staining protocols. However, there are currently accessible imaging technologies such as Optical Coherence Tomography (OCT), which allows non-invasive visualization of the main histological structures of the skin (like stratum corneum, epidermis, and dermis) and assessment of the dynamics of the pathology or efficacy of new treatments. Briefly, female immunocompetent hairless mice (SKH1 strain) were sensitized and challenged topically on back and ears for about 4 weeks. Back skin and ears thickness were measured using calliper at 3 occasions per week in complement to a macroscopic evaluation of atopic dermatitis lesions on back: erythema, scaling and excoriations scoring. In addition, OCT was performed on the back and ears of animals. OCT allows a virtual in-depth section (tomography) of the imaged organ to be made using a laser, a camera and image processing software allowing fast, non-contact and non-denaturing acquisitions of the explored tissues. To perform the imaging sessions, the animals were anesthetized with isoflurane, placed on a support under the OCT for a total examination time of 5 to 10 minutes. The results show a good correlation of the OCT technique with classical HES histology for skin lesions structures such as hyperkeratosis, epidermal hyperplasia, and dermis thickness. This OCT imaging technique can, therefore, be used in live animals at different times for longitudinal evaluation by repeated measurements of lesions in the same animals, in addition to the classical histological evaluation. Furthermore, this original imaging technique speeds up research protocols, reduces the number of animals and refines the use of the laboratory animal.

Keywords: atopic dermatitis, mouse model, oxzolone model, histology, imaging

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Authors: Glenda Wrenn, Juliet Muzere, Meldra Hall, Allyson Belton, Kisha Holden, Chanita Hughes-Halbert, Martha Kent, Bekh Bradley

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Understanding the help seeking decision making process and experiences of health disparity populations with posttraumatic stress disorder (PTSD) is central to development of trauma-informed, culturally centered, and patient focused services. Yet, little is known about the decision making process among adult Black women who are non-treatment seekers as they are, by definition, not engaged in services. Methods: Audiotaped interviews were conducted with 30 African American adult women with clinically significant PTSD symptoms who were engaged in primary care, but not in treatment for PTSD despite symptom burden. A qualitative interview guide was used to elucidate key themes. Independent coding of themes mapped to theory and identification of emergent themes were conducted using qualitative methods. An existing quantitative dataset was analyzed to contextualize responses and provide a descriptive summary of the sample. Results: Emergent themes revealed that active mental avoidance, the intermittent nature of distress, ambivalence, and self-identified resilience as undermining to help seeking decisions. Participants were stuck within the help-seeking phase of ‘recognition’ of illness and retained a sense of “it is my decision” despite endorsing significant social and environmental negative influencers. Participants distinguished ‘help acceptance’ from ‘help seeking’ with greater willingness to accept help and importance placed on being of help to others. Conclusions: Elucidation of the decision-making process from the perspective of non-treatment seekers has implications for outreach and treatment within models of integrated and specialty systems care. The salience of responses to trauma symptoms and stagnation in the help seeking recognition phase are findings relevant to integrated care service design and community engagement.

Keywords: culture, help-seeking, integrated care, PTSD

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Authors: Cait M. Henry, Sarah Jackson

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Abstract-This study is built from the culmination of four years of research into the cultural interpretation of Civil War heritage at a National Park Service (NPS) site, namely the Manassas National Battlefield Park, within an increasingly contentious political landscape surrounding the U.S. Civil War. Originating as questions regarding the relevancy of historic battlefields to the current culture within the United States soon evolved into more philosophical questions about what it means to feel welcome at a battlefield site, and what are considered appropriate actions and behaviors at what was once a mass gravesite. In trying to answer these questions, this work aims to critically analyze the confluence between the cultural authority of the NPS and collective memories of the U.S. Civil War. Operationalizing trauma as repeated violent acts within public spaces, the authors posit that the normalization of violence from white or white-passing men partially stems from the glorification of heroic white masculinity at National Park Service Civil War battlefield sites—especially those which also commemorate Confederate military strategy and prowess. From here the study moves outward to focus on the prevalence of heroic white masculinity within the nation’s current social zeitgeist, and particularly the notion that to take back masculinity one must utilize violence as a means of symbolic restoration from perceptions of white victimhood. The study ends with case studies of dark tourism framing at international battlefields as models for expanding heritage interpretation at the NPS site to foster narratives of empathy and responsibility within an increasingly contentious political landscape within the United States of America. Visitors do not leave Manassas National Battlefield Park with answers about the social and moral implications of the U.S. Civil War, but the tools for championing their own (predominantly white) heroic masculinity. As such, it is only logical that one common reaction when masculinity is symbolically threatened is to enact violence against Others as a restorative force within the United States.

Keywords: confederate heritage, military history, national park service, trauma, United States civil war

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Authors: A. Caicedo Padilla, J. Zambrano Nájera

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Cali, the capital of Valle del Cauca and the second city of Colombia, is located in the Cauca River Valley between the Western and Central Cordillera that is South West of the country. The topography of the city is mainly flat, but it is possibly to find mountains in the west. The city has increased urbanization during XX century, especially since 1958 when started a rapid growth due to migration of people from other parts of the region. Much of that population has settled in eastern of Cali, an area originally intended for cane cultivation and a zone of flood from Cauca River and its tributaries. Due to the unplanned migration, settling was inadequate and produced changes in natural dynamics of the basins, which has resulted in increases in runoff volumes, peak flows and flow velocities, that in turn increases flood risk. Sewerage networks capacity were not enough for this higher runoff volume, because in first term they were not adequately designed and built, causing its failure. This in turn generates increasingly recurrent floods generating considerable effects on the economy and development of normal activities in Cali. Thus, it becomes very important to know hydrological behavior of Urban Watersheds. This research aims to determine the impact of urbanization on hydrology of watersheds with very low slopes. The project aims to identify changes in natural drainage patterns caused by the changes made on landscape. From the identification of such modifications it will be defined the most critical areas due to recurring flood events in the city of Cali. Critical areas are defined as areas where the sewerage system does not work properly as surface runoff increases considerable with storm events, and floods are recurrent. The assessment will be done from the analysis of Geographic Information Systems (GIS) theme layers from CVC Environmental Institution of Regional Control in Valle del Cauca, hydrological data and disaster database developed by OSSO Corporation. Rainfall data from a network and historical stream flow data will be used for analysis of historical behavior and change of precipitation and hydrological response according to homogeneous zones characterized by EMCALI S.A. public utility enterprise of Cali in 1999.

Keywords: drainage systems, land cover changes, urban hydrology, urban planning

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Authors: Chia-Wen Wang, Patou Masika Musumari, Teeranee Techasrivichien, S. Pilar Suguimoto, Chang-Chuan Chan, Masako Ono-Kihara, Masahiro Kihara

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Background: In recent years, a particular form of bullying, referred to as 'cyberbullying' has emerged along with the rapid expansion of the Internet, social network services (SNSs) and smart phones. Many Asian countries, including Taiwan, are faced with both the cyberbullying and the traditional form of bullying. This study aims to explore Taiwanese adolescents’ experiences, perceptions and opinions regarding cyberbullying and traditional bullying through the perspective of victim, perpetrator, or witness. Method: This is a qualitative study using face-to-face in-depth interviews guided by a semi-structured questionnaire among high school students -aged 16 to 18 years- in Taipei, Taiwan. The participants were recruited through convenience sampling from five high schools between June and November 2016. Interviews were digitally recorded, transcribed, and analyzed using the thematic analysis approach. Results: Forty-eight participants were recruited, of which, 14 (29.2%) reported had ever experienced bullying. Specifically, 7 participants (14.6%) reported had ever been victims of cyberbullying, 1 (2%) had been victims of traditional bullying, and 6 (12.5%) had been victims of both cyber and traditional bullying. The majority (70.8%) reported had ever witnessed acts of bullying; however, none of the participants recognized had ever been a perpetrator of bullying. Cyberbullying mostly happens on social media (Facebook and Instagram) or LINE instant messaging application, and included upload and sharing of degrading pictures and videos of victims, as well as gossip and mean messages by the perpetrators. The anonymous and public nature of social media groups in schools made it easier to perpetrate bullying. The victim of traditional bullying reported being the target of verbal attack because of his physical appearance. Regardless of the type of bullying, victims reported feeling bad, angry, or depressed as a result of being bullied. Witnesses of both cyber- and traditional bullying cited physical appearance (e.g. having the big/flat bust or big butt, or overweight or obese) and disability as the most reasons of being a bullying victim. Conclusion: Both cyberbullying and traditional bullying had negative emotional and psychological impacts on victims. This study warrants further research to assess the extent of this phenomenon and understand the characteristics of perpetrators, victims, and witnesses to inform the design of tailored interventions using appropriate channels of dissemination.

Keywords: cyberbullying, traditional bullying, social media, adolescents

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Fouad Chebib, Marie Hogan, Ziad El-Zoghby, Maria Irazabal, Sarah Senum, Christina Heyer, Charles Madsen, Emilie Cornec-Le Gall, Atta Behfar, Barbara Ehrlich, Peter Harris, Vicente Torres

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Background: Mutations in PKD1 and PKD2, the genes encoding the proteins polycystin-1 (PC1) and polycystin-2 (PC2) cause autosomal dominant polycystic kidney disease (ADPKD). ADPKD is a systemic disease associated with several extrarenal manifestations. Animal models have suggested an important role for the polycystins in cardiovascular function. The aim of the current study is to evaluate the association of various cardiomyopathies in a large cohort of patients with ADPKD. Methods: Clinical data was retrieved from medical records for all patients with ADPKD and cardiomyopathies (n=159). Genetic analysis was performed on available DNA by direct sequencing. Results: Among the 58 patients included in this case series, 39 patients had idiopathic dilated cardiomyopathy (IDCM), 17 had hypertrophic obstructive cardiomyopathy (HOCM), and 2 had left ventricular noncompaction (LVNC). The mean age at cardiomyopathy diagnosis was 53.3, 59.9 and 53.5 years in IDCM, HOCM and LVNC patients respectively. The median left ventricular ejection fraction at initial diagnosis of IDCM was 25%. Average basal septal thickness was 19.9 mm in patients with HOCM. Genetic data was available in 19, 8 and 2 cases of IDCM, HOCM, and LVNC respectively. PKD1 mutations were detected in 47.4%, 62.5% and 100% of IDCM, HOCM and LVNC cases. PKD2 mutations were detected only in IDCM cases and were overrepresented (36.8%) relative to the expected frequency in ADPKD (~15%). The prevalence of IDCM, HOCM, and LVNC in our ADPKD clinical cohort was 1:17, 1:39 and 1:333 respectively. When compared to the general population, IDCM and HOCM was approximately 10-fold more prevalent in patients with ADPKD. Conclusions: In summary, we suggest that PKD1 or PKD2 mutations may predispose to idiopathic dilated or hypertrophic cardiomyopathy. There is a trend for patients with PKD2 mutations to develop the former and for patients with PKD1 mutations to develop the latter. Predisposition to various cardiomyopathies may be another extrarenal manifestation of ADPKD.

Keywords: autosomal dominant polycystic kidney (ADPKD), polycystic kidney disease, cardiovascular, cardiomyopathy, idiopathic dilated cardiomyopathy, hypertrophic cardiomyopathy, left ventricular noncompaction

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Authors: Jameelah Omolara Yaqub

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One of the main reasons for the existence of central bank is that it is believed that central banks have some influence on private sector decisions which will enable the Central Bank to achieve some of its objectives especially that of stable price and economic growth. By the assumption of the New Keynesian theory that prices are fully flexible in the short run, the central bank can temporarily influence real interest rate and, therefore, have an effect on real output in addition to nominal prices. There is, therefore, the need for the Central Bank to monitor, respond to, and influence private sector decisions appropriately. This thus shows that the Central Bank and the private sector will both affect and be affected by each other implying considerable interdependence between the sectors. The interdependence may be simultaneous or not depending on the level of information, readily available and how sensitive prices are to agents’ expectations about the future. The aim of this paper is, therefore, to determine whether the interdependence between asset prices and monetary policy are simultaneous or not and how important is this relationship. Studies on the effects of monetary policy have largely used VAR models to identify the interdependence but most have found small effects of interaction. Some earlier studies have ignored the possibility of simultaneous interdependence while those that have allowed for simultaneous interdependence used data from developed economies only. This study, therefore, extends the literature by using data from a developing economy where information might not be readily available to influence agents’ expectation. In this study, the direction of relationship among variables of interest will be tested by carrying out the Granger causality test. Thereafter, the interaction between asset prices and monetary policy in Nigeria will be tested. Asset prices will be represented by the NSE index as well as real estate prices while monetary policy will be represented by money supply and the MPR respectively. The VAR model will be used to analyse the relationship between the variables in order to take account of potential simultaneity of interdependence. The study will cover the period between 1980 and 2014 due to data availability. It is believed that the outcome of the research will guide monetary policymakers especially the CBN to effectively influence the private sector decisions and thereby achieve its objectives of price stability and economic growth.

Keywords: asset prices, granger causality, monetary policy rate, Nigeria

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Authors: E. Gouya Bozorg

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The issue of ranking of sports teams, in particular soccer teams is of primary importance in the professional sports. However, it is still based on classical statistics and models outside of area of mathematics. Rigorous mathematics and then statistics despite the expectation held of them have not been able to effectively engage in the issue of ranking. It is something that requires serious pathology. The purpose of this study is to change the approach to get closer to mathematics proper for using in the ranking. We recommend using theoretical mathematics as a good option because it can hermeneutically obtain the theoretical concepts and criteria needful for the ranking from everyday language of a League. We have proposed a framework that puts the issue of ranking into a new space that we have applied in soccer as a case study. This is an experimental and theoretical study on the issue of ranking in a professional soccer league based on theoretical mathematics, followed by theoretical statistics. First, we showed the theoretical definition of constant number Є = 1.33 or ‘golden number’ of a soccer league. Then, we have defined the ‘efficiency of a team’ by this number and formula of μ = (Pts / (k.Є)) – 1, in which Pts is a point obtained by a team in k number of games played. Moreover, K.Є index has been used to show the theoretical median line in the league table and to compare top teams and bottom teams. Theoretical coefficient of σ= 1 / (1+ (Ptx / Ptxn)) has also been defined that in every match between the teams x, xn, with respect to the ability of a team and the points of both of them Ptx, Ptxn, and it gives a performance point resulting in a special ranking for the League. And it has been useful particularly in evaluating the performance of weaker teams. The current theory has been examined for the statistical data of 4 major European Leagues during the period of 1998-2014. Results of this study showed that the issue of ranking is dependent on appropriate theoretical indicators of a League. These indicators allowed us to find different forms of ranking of teams in a league including the ‘special table’ of a league. Furthermore, on this basis the issue of a record of team has been revised and amended. In addition, the theory of ranking can be used to compare and classify the different leagues and tournaments. Experimental results obtained from archival statistics of major professional leagues in the world in the past two decades have confirmed the theory. This topic introduces a new theory for ranking of a soccer league. Moreover, this theory can be used to compare different leagues and tournaments.

Keywords: efficiency of a team, ranking, special table, theoretical mathematic

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Authors: Hamsasew Hankebo Lemago, Dóra Hessz, Zoltán Erdélyi, Imre Miklós Szilágyi

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Metal oxide inverse opals are a unique class of photocatalysts with a hierarchical structure that mimics the natural opal gemstone. They are composed of a network of interconnected pores, which provides a large surface area and efficient pathways for the transport of light and reactants. Atomic layer deposition (ALD) is a versatile technique for the synthesis of high-precision metal oxide thin films, including inverse opals. ALD allows for precise control over the thickness, composition, and morphology of the synthesized films, making it an ideal technique for the fabrication of photocatalysts with tailored properties. In this study, we report the synthesis of TiO2, ZnO, and Al2O3 inverse opal photocatalysts using thermal or plasma-enhanced ALD. The synthesized photocatalysts were characterized using a variety of techniques, including scanning electron microscopy (SEM)-energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), Raman spectroscopy, photoluminescence (PL), ellipsometry, and UV-visible spectroscopy. The results showed that the ALD-synthesized metal oxide inverse opals had a highly ordered structure and a tunable pore size. The PL spectroscopy results showed low recombination rates of photogenerated electron-hole pairs, while the ellipsometry and UV-visible spectroscopy results showed tunable optical properties and band gap energies. The photocatalytic activity of the samples was evaluated by the degradation of methylene blue under visible light irradiation. The results showed that the ALD-synthesized metal oxide inverse opals exhibited high photocatalytic activity, even under visible light irradiation. The composites photocatalysts showed even higher activity than the individual metal oxide inverse opals. The enhanced photocatalytic activity of the composites can be attributed to the synergistic effect between the different metal oxides. For example, Al2O3 can act as a charge carrier scavenger, which can reduce the recombination of photogenerated electron-hole pairs. The ALD-synthesized metal oxide inverse opals and their composites are promising photocatalysts for a variety of applications, such as wastewater treatment, air purification, and energy production. For example, they can be used to remove organic pollutants from wastewater, decompose harmful gases in the air, and produce hydrogen fuel from water.

Keywords: ALD, metal oxide inverse opals, composites, photocatalysis

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Authors: Moses Pinto, Ana Paula Monte

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The present research analyses the interactions between various categories of corporate social responsibility (CSR) that mediate the relationship between CSR and financial performance in Multinational Enterprises (MNE) in light of the present socio-political factors prevalent in the countries under observation. In the research it has been hypothesized that the absence of consensus in the empirical literature on the CSR–financial performance relationship may be explained by the existence of synergies (Complementarities) between the different CSR components. Upon investigation about whether such relationships exist, a final unbalanced panel sample of 1000 observations taken from 100 Multinational Enterprises per year functioning in the Schengen countries and one south east Asian country namely: India, over the span of 10 years i.e. from the year 2008 to 2018 has been analyzed. The empirical analysis used in the research methodology employs dynamic Panel Data in time series specifically, the system Generalized Method of Moments (GMM) which had been used to detect the varying degrees of relationships between the CSR and financial performance parameters in the background of the socio-political factors prevailing in the countries at the time and also taking into account the bilateral treaty obligations between the countries under observation. The econometric model has employed the financial ratio namely the Return on Assets (ROA) as an indicator of financial performance in order to gauge the internal performance and valuation of a firm as opposed to the Tobin’s Q that provides for the external evaluation of a firm’s financial performance which may not always be accurate. The various CSR dimensions have demonstrated significant correlations to the ‘ROA’ which include some negatively associated correlations and one positively associated correlation that is highly significant throughout the analysis of the observations, namely the correlation between the ‘ROA’ and the CSR dimension: ‘Environment’. The results provide a deeper insight in the synergistic CSR activities that managers could adapt into their Firm’s CSR strategy in order to enhance the ‘ROA’ and also to understand which interactions between the CSR dimensions can be adapted together due to their positively correlated association with each other and the ROA. The future lines of research would be inclined to investigate the effects of socio-political factors on the ROA of the MNEs through better designed econometric models.

Keywords: CSR, financial performance, complementarity, sociopolitical factors

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Authors: Rudolf Hrach, Stanislav Novak, Vera Hrachova

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Composite and nanocomposite films represent the class of promising materials and are often objects of the study due to their mechanical, electrical and other properties. The most interesting ones are probably the composite metal/dielectric structures consisting of a metal component embedded in an oxide or polymer matrix. Behaviour of composite films varies with the amount of the metal component inside what is called filling factor. The structures contain individual metal particles or nanoparticles completely insulated by the dielectric matrix for small filling factors and the films have more or less dielectric properties. The conductivity of the films increases with increasing filling factor and finally a transition into metallic state occurs. The behaviour of composite films near a percolation threshold, where the change of charge transport mechanism from a thermally-activated tunnelling between individual metal objects to an ohmic conductivity is observed, is especially important. Physical properties of composite films are given not only by the concentration of metal component but also by the spatial and size distributions of metal objects which are influenced by a technology used. In our contribution, a study of composite structures with the help of methods of computational physics was performed. The study consists of two parts: -Generation of simulated composite and nanocomposite films. The techniques based on hard-sphere or soft-sphere models as well as on atomic modelling are used here. Characterizations of prepared composite structures by image analysis of their sections or projections follow then. However, the analysis of various morphological methods must be performed as the standard algorithms based on the theory of mathematical morphology lose their sensitivity when applied to composite films. -The charge transport in the composites was studied by the kinetic Monte Carlo method as there is a close connection between structural and electric properties of composite and nanocomposite films. It was found that near the percolation threshold the paths of tunnel current forms so-called fuzzy clusters. The main aim of the present study was to establish the correlation between morphological properties of composites/nanocomposites and structures of conducting paths in them in the dependence on the technology of composite films.

Keywords: composite films, computer modelling, image analysis, nanocomposite films

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Authors: Nathaniel Bayode Eniolorunda, Murtala Abubakar Gada, Sheikh Danjuma Abubakar

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The challenge of erosion in the study area is persistent, suggesting the need for a better understanding of the mechanisms that drive it. Thus, the study evolved a predictive erosion model (RUSLE_Sok), deploying Remote Sensing (RS) and Geographical Information System (GIS) tools. The nature and pattern of the factors of erosion were characterized, while soil losses were quantified. Factors’ impacts were also measured, and the morphometry of gullies was described. Data on the five factors of RUSLE and distances to settlements, rivers and roads (K, R, LS, P, C, DS DRd and DRv) were combined and processed following standard RS and GIS algorithms. Harmonized World Soil Data (HWSD), Shuttle Radar Topographical Mission (SRTM) image, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Sentinel-2 image accessed and processed within the Google Earth Engine, road network and settlements were the data combined and calibrated into the factors for erosion modeling. A gully morphometric study was conducted at some purposively selected sites. Factors of soil erosion showed low, moderate, to high patterns. Soil losses ranged from 0 to 32.81 tons/ha/year, classified into low (97.6%), moderate (0.2%), severe (1.1%) and very severe (1.05%) forms. The multiple regression analysis shows that factors statistically significantly predicted soil loss, F (8, 153) = 55.663, p < .0005. Except for the C-Factor with a negative coefficient, all other factors were positive, with contributions in the order of LS>C>R>P>DRv>K>DS>DRd. Gullies are generally from less than 100m to about 3km in length. Average minimum and maximum depths at gully heads are 0.6 and 1.2m, while those at mid-stream are 1 and 1.9m, respectively. The minimum downstream depth is 1.3m, while that for the maximum is 4.7m. Deeper gullies exist in proximity to rivers. With minimum and maximum gully elevation values ranging between 229 and 338m and an average slope of about 3.2%, the study area is relatively flat. The study concluded that major erosion influencers in the study area are topography and vegetation cover and that the RUSLE_Sok well predicted soil loss more effectively than ordinary RUSLE. The adoption of conservation measures such as tree planting and contour ploughing on sloppy farmlands was recommended.

Keywords: RUSLE_Sok, Sokoto, google earth engine, sentinel-2, erosion

Procedia PDF Downloads 79