Search results for: Markov jump diffusion model

Authors: Gayani Ranawake

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Effective communication is widely regarded as an important aspect of any discipline. This particular study deals with written communication in science. Writing conventions and linguistic choices play a key role in conveying the message effectively to a target audience. Scientists are responsible for conveying their findings or research results not only to their discourse community but also to the general public. Recognizing appropriate linguistic choices is crucial since they vary depending on the target audience. The majority of scientists can communicate effectively with their discourse community, but public engagement seems more challenging to them. There is a lack of research into the language use of scientists, and in particular how it varies by discipline and audience (genre). A better understanding of the different linguistic conventions used in effective science writing by scientists for scientists and by scientists for the public will help to guide scientists who are familiar with their discourse community norms to write effectively for the public. This study investigates the differences and similarities of linguistic choices in biology articles written by scientists for their discourse community and biology magazine articles written by scientists and science communicators for the general public. This study is a part of a larger project investigating linguistic differences in different genres of science academic writing. The sample for this particular study is composed of 20 research articles from the journal Biological Reviews and 20 magazine articles from the magazine Australian Popular Science. Differences in the linguistic devices were analyzed using Hyland’s metadiscourse model for academic writing proposed in 2005. The frequency of the usage of interactive resources (transitions, frame markers, endophoric markers, evidentials and code glosses) and interactional resources (hedges, boosters, attitude markers, self-mentions and engagement markers) were compared and contrasted using the NVivo textual analysis tool. The results clearly show the differences in the frequency of usage of interactional and interactive resources in the two disciplines under investigation. The findings of this study provide a reference guide for scientists and science writers to understand the differences in the linguistic choices between the two genres. This will be particularly helpful for scientists who are proficient at writing for their discourse community, but not for the public.

Keywords: discourse analysis, linguistic choices, metadiscourse, science writing

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Authors: M. Bolacali

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The aim of the study is to determine the effect of immunocastration vaccine administration at different doses on fattening performance of feedlot Holstein bulls. Bopriva® is a vaccine that stimulates the animals' own immune system to produce specific antibodies against gonadotropin releasing factor (GnRF). Ninety four Holstein male calves (309.5 ± 2.58 kg body live weight and 267 d-old) assigned to the 4 treatments. Control group; 1 mL of 0.9% saline solution was subcutaneously injected to intact bulls on 1st and 60th days of the feedlot as placebo. On the same days of the feedlot, Bopriva® at two doses of 1 mL and 1 mL for Trial-1 group, 1.5 mL, and 1.5 mL for Trial-2 group, 1.5 mL, and 1 mL for Trial-3 group were subcutaneously injected to bulls. The study was conducted in a private establishment in the Sirvan district of Siirt province and lasted 180 days. The animals were weighed at the beginning of fattening and at 30-day intervals to determine their live weights at various periods. The statistical analysis for normal distribution data of the treatment groups was carried out with the general linear model procedure of SPSS software. The fattening initial live weight in Control, Trial-1, Trial-2 and Trial-3 groups was respectively 309.21, 306.62, 312.11, and 315.39 kg. The fattening final live weight was respectively 560.88, 536.67, 548.56, and 548.25 kg. The daily live weight gain during the trial was respectively 1.40, 1.28, 1.31, and 1.29 kg/day. The cold carcass yield was respectively 51.59%, 50.32%, 50.85%, and 50.77%. Immunocastration vaccine administration at different doses did not affect the live weights and cold carcass yields of Holstein male calves reared under intensive conditions (P > 0.05). However, it was determined to reduce fattening performance between 61-120 days (P < 0.05) and 1-180 days (P < 0.01). In addition, it was determined that the best performance among the vaccine-treated groups occurred in the group administered a 1.5 mL of vaccine on the 1st and 60th study days. In animals, castration is used to control fertility, aggressive and sexual behaviors. As a result, the fact that stress is induced by physical castration in animals and active immunization against GnRF maintains performance by maximizing welfare in bulls improves carcass and meat quality and controls unwanted sexual and aggressive behavior. Considering such features, it may be suggested that immunocastration vaccine with Bopriva® can be administered as a 1.5 mL dose on the 1st and 60th days of the fattening period in Holstein bulls.

Keywords: anti-GnRF, fattening, growth, immunocastration

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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

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Authors: Danying Gu, Xiaoyan Li, Yuanlei He

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As a knowledge-intensive industry, nuclear industry highly values the importance of safety and quality. The life cycle of a NPP (Nuclear Power Plant) can last 100 years from the initial research and design to its decommissioning. How to implement the high-quality knowledge management and how to contribute to a more safe, advanced and economic NPP (Nuclear Power Plant) is the most important issue and responsibility for knowledge management. As the lead of nuclear industry, nuclear research and design institute has competitive advantages of its advanced technology, knowledge and information, DKM (Design Knowledge Management) of nuclear research and design institute is the core of the knowledge management in the whole nuclear industry. In this paper, the study and practice on DKM and knowledge transfer across the life cycle of a new-built NPP in China is introduced. For this digital intelligent NPP, the whole design process is based on a digital design platform which includes NPP engineering and design dynamic analyzer, visualization engineering verification platform, digital operation maintenance support platform and digital equipment design, manufacture integrated collaborative platform. In order to make all the design data and information transfer across design, construction, commissioning and operation, the overall architecture of new-built digital NPP should become a modern knowledge management system. So a digital information transfer model across the NPP life cycle is proposed in this paper. The challenges related to design knowledge transfer is also discussed, such as digital information handover, data center and data sorting, unified data coding system. On the other hand, effective delivery of design information during the construction and operation phase will contribute to the comprehensive understanding of design ideas and components and systems for the construction contractor and operation unit, largely increasing the safety, quality and economic benefits during the life cycle. The operation and maintenance records generated from the NPP operation process have great significance for maintaining the operating state of NPP, especially the comprehensiveness, validity and traceability of the records. So the requirements of an online monitoring and smart diagnosis system of NPP is also proposed, to help utility-owners to improve the safety and efficiency.

Keywords: design knowledge management, digital nuclear power plant, knowledge transfer, life cycle

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Authors: Larasati Zuhro, Ida F Priyanto

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Background: In March 2020, Indonesia started to be affected by Covid-19, and the number of victims increased slowly but surely until finally, the highest number of victims reached the highest—about 50,000 persons—for the daily cases in the middle of 2021. Like other institutions, schools and universities were suddenly closed in March 2020, and students had to change their ways of studying from face-to-face to online. This sudden changed affected students and faculty, including LIS students and faculty because they never experienced online classes in Indonesia due to the previous regulation that academic and school activities were all conducted onsite. For almost two years, school and academic activities were held online. This indeed has affected the way students learned and faculty delivered their courses. This raises the question of whether students are now ready for their new learning activities due to the covid-19 disruption. Objectives: this study was conducted to find out the impact of covid-19 pandemic on the LIS learning process and the effectiveness of online classes for students of LIS in Indonesia. Methodology: This was qualitative research conducted among LIS students at UIN Sunan Kalijaga, Yogyakarta, Indonesia. The population are students who were studying for masters’program during covid-19 pandemic. Results: The study showed that students were ready with the online classes because they are familiar with the technology. However, the Internet and technology infrastructure do not always support the process of learning. Students mention slow WIFI is one factor that causes them not being able to study optimally. They usually compensate themselves by visiting a public library, a café, or any other places to get WIFI network. Noises come from the people surrounding them while they are studying online.Some students could not concentrate well when attending the online classes as they studied at home, and their families sometimes talk to other family members, or they asked the students while they are attending the online classes. The noise also came when they studied in a café. Another issue is that the classes were held in shorter time than that in the face-to-face. Students said they still enjoyed the onsite classes instead of online, although they do not mind to have hybrid model of learning. Conclusion: Pandemic of Covid-19 has changed the way students of LIS in Indonesia learn. They have experienced a process of migrating the way they learn from onsite to online. They also adapted their learning with the condition of internet access speed, infrastructure, and the environment. They expect to have hybrid classes in the future.

Keywords: learning, LIS students, pandemic, covid-19

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Authors: Mohammed Abdullah Alshahrani

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The research focuses on investigating the use of partial least squares (PLS) methodology for addressing challenges associated with high-dimensional correlated data. Recent technological advancements have led to experiments producing data characterized by a large number of variables compared to observations, with substantial inter-variable correlations. Such data patterns are common in chemometrics, where near-infrared (NIR) spectrometer calibrations record chemical absorbance levels across hundreds of wavelengths, and in genomics, where thousands of genomic regions' copy number alterations (CNA) are recorded from cancer patients. PLS serves as a widely used method for analyzing high-dimensional data, functioning as a regression tool in chemometrics and a classification method in genomics. It handles data complexity by creating latent variables (components) from original variables. However, applying PLS can present challenges. The study investigates key areas to address these challenges, including unifying interpretations across three main PLS algorithms and exploring unusual negative shrinkage factors encountered during model fitting. The research presents an alternative approach to addressing the interpretation challenge of predictor weights associated with PLS. Sparse estimation of predictor weights is employed using a penalty function combining a lasso penalty for sparsity and a Cauchy distribution-based penalty to account for variable dependencies. The results demonstrate sparse and grouped weight estimates, aiding interpretation and prediction tasks in genomic data analysis. High-dimensional data scenarios, where predictors outnumber observations, are common in regression analysis applications. Ordinary least squares regression (OLS), the standard method, performs inadequately with high-dimensional and highly correlated data. Copy number alterations (CNA) in key genes have been linked to disease phenotypes, highlighting the importance of accurate classification of gene expression data in bioinformatics and biology using regularized methods like PLS for regression and classification.

Keywords: partial least square regression, genetics data, negative filter factors, high dimensional data, high correlated data

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Authors: Merih Welay Welesilassie

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Understanding educators' readiness to incorporate AI tools into their teaching methods requires comprehensively examining the influencing factors. This understanding is crucial, given the potential of these technologies to personalise learning experiences, improve instructional effectiveness, and foster innovative pedagogical approaches. This study evaluated factors affecting teachers' adoption of AI tools in their English language instruction by extending the Technology Acceptance Model (TAM) to encompass digital readiness support, perceived risk, and trust. A cross-sectional quantitative survey was conducted with 128 English language teachers, supplemented by qualitative data collection from 15 English teachers. The structural mode analysis indicated that implementing AI tools in Ethiopian higher education was notably influenced by digital readiness support, perceived ease of use, perceived usefulness, perceived risk, and trust. Digital readiness support positively impacted perceived ease of use, usefulness, and trust while reducing safety and privacy risks. Perceived ease of use positively correlated with perceived usefulness but negatively influenced trust. Furthermore, perceived usefulness strengthened trust in AI tools, while perceived safety and privacy risks significantly undermined trust. Trust was crucial in increasing educators' willingness to adopt AI technologies. The qualitative analysis revealed that the teachers exhibited strong content and pedagogical knowledge but needed more technology-related knowledge. Moreover, It was found that the teachers did not utilise digital tools to teach English. The study identified several obstacles to incorporating digital tools into English lessons, such as insufficient digital infrastructure, a shortage of educational resources, inadequate professional development opportunities, and challenging policies and governance. The findings provide valuable guidance for educators, inform policymakers about creating supportive digital environments, and offer a foundation for further investigation into technology adoption in educational settings in Ethiopia and similar contexts.

Keywords: digital readiness support, AI acceptance, risk, trust

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Authors: Georgios P. Georgiou

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Infants are able to discriminate a number of sound contrasts in most languages. However, this ability is not available in adults who might face difficulties in discriminating accurately second language sound contrasts as they filter second language speech through the phonological categories of their native language. For example, Spanish speakers often struggle to perceive the difference between the English /ε/ and /æ/ because both vowels do not exist in their native language; so they assimilate these vowels to the closest phonological category of their first language. The present study aims to uncover the perceptual patterns of Arabic adult speakers in regard to the vowels of their second language (Greek). Still, there is not any study that investigates the perception of Greek vowels by Arabic speakers and, thus, the present study would contribute to the enrichment of the literature with cross-linguistic research in new languages. To the purpose of the present study, 15 native speakers of Egyptian Arabic who permanently live in Cyprus and have adequate knowledge of Greek as a second language passed through vowel assimilation and vowel contrast discrimination tests (AXB) in their second language. The perceptual stimuli included non-sense words that contained vowels in both stressed and unstressed positions. The second language listeners’ patterns were analyzed through the Perceptual Assimilation Model which makes testable hypotheses about the assimilation of second language sounds to the speakers’ native phonological categories and the discrimination accuracy over second language sound contrasts. The results indicated that second language listeners assimilated pairs of Greek vowels in a single phonological category of their native language resulting in a Category Goodness difference assimilation type for the Greek stressed /i/-/e/ and the Greek stressed-unstressed /o/-/u/ vowel contrasts. On the contrary, the members of the Greek unstressed /i/-/e/ vowel contrast were assimilated to two different categories resulting in a Two Category assimilation type. Furthermore, they could discriminate the Greek stressed /i/-/e/ and the Greek stressed-unstressed /o/-/u/ contrasts only in a moderate degree while the Greek unstressed /i/-/e/ contrast could be discriminated in an excellent degree. Two main implications emerge from the results. First, there is a strong influence of the listeners’ native language on the perception of the second language vowels. In Egyptian Arabic, contiguous vowel categories such as [i]-[e] and [u]-[o] do not have phonemic difference but they are subject to allophonic variation; by contrast, the vowel contrasts /i/-/e/ and /o/-/u/ are phonemic in Greek. Second, the role of stress is significant for second language perception since stressed vs. unstressed vowel contrasts were perceived in a different manner by the Greek listeners.

Keywords: Arabic, bilingual, Greek, vowel perception

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Authors: Gulnaz Erkomaishvili

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The article analyzes the modern level of industrial production in Georgia, shows the export-import of industrial products and evaluates the results of the activities of institutions implementing industrial policy. The research showed us that the level of development of industry in the country and its export potential are quite low. The article concludes that in the modern phase of industrial development, the country should choose a model focused on technological development and maximum growth of export potential. Objectives. The aim of the research is to develop an economic policy that promotes the development of industry and to look for ways to implement it effectively. Methodologies This paper uses general and specific methods, in particular, analysis, synthesis, induction, deduction, scientific abstraction, comparative and statistical methods, as well as experts’ evaluation. In-depth interviews with experts were conducted to determine quantitative and qualitative indicators; Publications of the National Statistics Office of Georgia are used to determine the regularity between analytical and statistical estimations. Also, theoretical and applied research of international organizations and scientist-economists are used. Contributions Based on the identified challenges in the area of industry, recommendations for the implementation of an active industrial policy in short and long term periods were developed. In particular: the government's priority orientation of industrial development; paying special attention to the processing industry sectors that Georgia has the potential to produce; supporting the development of scientific fields; Determination of certain benefits for those investors who invest money in industrial production; State partnership with the private sector, manifested in the fight against bureaucracy, corruption and crime, creating favorable business conditions for entrepreneurs; Coordination between education - science - production should be implemented in the country. Much attention should be paid to basic scientific research, which does not require purely commercial returns in the short term, science should become a real productive force; Special importance should be given to the creation of an environment that will support the expansion of export-oriented production; Overcoming barriers to entry into export markets.

Keywords: industry, sectoral structure of industry, exsport-import of industrial products, industrial policy

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Authors: Ahmad Haidar

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Modern economic systems are characterized by growing complexity, and addressing their challenges requires innovative approaches. This study examines the implications of artificial intelligence (AI) on unemployment in Europe from a macroeconomic perspective, employing data modeling techniques to understand the relationship between AI integration and labor market dynamics. To understand the AI-unemployment nexus comprehensively, this research considers factors such as sector-specific AI adoption, skill requirements, workforce demographics, and geographical disparities. The study utilizes a panel data model, incorporating data from European countries over the last two decades, to explore the potential short-term and long-term effects of AI implementation on unemployment rates. In addition to investigating the direct impact of AI on unemployment, the study also delves into the potential indirect effects and spillover consequences. It considers how AI-driven productivity improvements and cost reductions might influence economic growth and, in turn, labor market outcomes. Furthermore, it assesses the potential for AI-induced changes in industrial structures to affect job displacement and creation. The research also highlights the importance of policy responses in mitigating potential negative consequences of AI adoption on unemployment. It emphasizes the need for targeted interventions such as skill development programs, labor market regulations, and social safety nets to enable a smooth transition for workers affected by AI-related job displacement. Additionally, the study explores the potential role of AI in informing and transforming policy-making to ensure more effective and agile responses to labor market challenges. In conclusion, this study provides a comprehensive analysis of the macroeconomic implications of AI on unemployment in Europe, highlighting the importance of understanding the nuanced relationships between AI adoption, economic growth, and labor market outcomes. By shedding light on these relationships, the study contributes valuable insights for policymakers, educators, and researchers, enabling them to make informed decisions in navigating the complex landscape of AI-driven economic transformation.

Keywords: artificial intelligence, unemployment, macroeconomic analysis, european labor market

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Authors: Zhizhong Yuan, Lili Wang, Chenya Zheng, Wuqi Yang

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How to encourage and support peer-to-peer (P2P) network lending, and effectively monitor the risk of P2P network lending, has become the focus of the Chinese government departments, industrialists, experts and scholars in recent years. The reason is that this convenient online micro-credit service brings a series of credit risks and other issues. Avoiding the risks brought by the P2P network lending model, it can better play a benign role and help China's small and medium-sized private enterprises with vigorous development to solve the capital needs; otherwise, it will bring confusion to the normal financial order. As a form of financial services, P2P network lending has injected new blood into China's non-government finance in the past ten years, and has found a way out for idle funds and made up for the shortage of traditional financial services in China. However, it lacks feasible measures in credit evaluation and government supervision. This paper collects a large amount of data about P2P network lending of China. The data collection comes from the official media of the Chinese government, the public achievements of existing researchers and the analysis and collation of correlation data by the authors. The research content of this paper includes literature review; the current situation of China's P2P network lending development; the risk analysis of P2P network lending in China; the risk prevention strategy of P2P network lending in China. The focus of this paper is to try to find a specific program to strengthen supervision and avoid risks from the perspective of government regulators, operators of P2P network lending platform, investors and users of funds. These main measures include: China needs to develop self-discipline organization of P2P network lending industry and formulate self-discipline norms as soon as possible; establish a regular information disclosure system of P2P network lending platform; establish censorship of credit rating of borrowers; rectify the P2P network lending platform in compliance through the implementation of bank deposition. The results and solutions will benefit all the P2P network lending platforms, creditors, debtors, bankers, independent auditors and government agencies of China and other countries.

Keywords: peer-to-peer(P2P), regulation, risk prevention, supervision

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Authors: Ursula D. C. Resende, Fabiano S. Bicalho, Sandro T. M. Gonçalves

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The growing demand for cheap and clean energy sources have been motivated by the study and development of distinct technologies and devices able to provide different amounts of energy. In order to supply energy for small loads, the energy from the electromagnetic spectrum can be harvested. This possibility is particularly interesting because this kind of energy is constantly available in the environment and the number of radiofrequency sources is permanently increasing, due to advances in telecommunications services. A rectenna, which is a combination of an antenna and a rectifier circuit, is an equipment that can efficiently perform the electromagnetic energy harvesting. However, since the amount of electromagnetic energy available in the environment is very small, limited values of power can be harvested by the rectenna. Therefore, several technical strategies have been investigated in order to increase this amount of power. In this work, a metamaterial electromagnetic lens is used to improve the electromagnetic energy harvesting. The rectenna investigated was designed and optimized to charge a Li-Ion battery using the electromagnetic energy from an internet Wi-Fi commercial router model TL-WR841HP operating in 2.45 GHz with maximal output power equal to 18 dBm. The rectenna consists of a high directive antenna, a double voltage rectifier circuit and a metamaterial lens. The printed antenna, constituted of two rectangular radiator elements, was projected and optimized by using the Computer Simulation Software (CST) in order to obtain high directivities and values of S11 parameter below -10 dB in 2.45 GHz. The antenna was printed over a double-sided copper fiberglass substrate, FR4, with characterized relative electric permittivity εr = 4.3 and tangent of losses δ = 0.01. The rectifier circuit, which incorporates a circuit for impedance matching and uses the Schottky diode HSMS-2852, was projected and optimized by using Advanced Design Software (ADS) and built over the same FR4 substrate. The metamaterial cell is composed of two Square Split Ring Resonator (S-SRR) and a thin wire in order to operate with negative values of εr and relative magnetic permeability in 2.45 GHz. In order to evaluate the performance of the purposed rectenna two experimental charging tests were performed, one without and other with the metamaterial lens. The result obtained demonstrate that the electromagnetic lens was able to significantly increase the levels of electric current delivered to the battery, approximately 44%.

Keywords: electromagnetic energy harvesting, electromagnetic lens, metamaterial, rectenna

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Authors: Nalinee B. Suryawanshi, Vinay M. Bhandari, Laxmi Gayatri Sorokhaibam, Vivek V. Ranade

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Deep desulphurization of transportation fuels is a major environmental concern all over the world and recently prescribed norms for the sulphur content require below 10 ppm sulphur concentrations in fuels such as diesel and gasoline. The existing technologies largely based on catalytic processes such as hydrodesulphurization, oxidation require newer catalysts and demand high cost of deep desulphurization whereas adsorption based processes have limitations due to lower capacity of sulphur removal. The present work is an attempt to provide alternatives for the existing methodologies using a newer non-catalytic process based on hydrodynamic cavitation. The developed process requires appropriate combining of organic and aqueous phases under ambient conditions and passing through a cavitating device such as orifice, venturi or vortex diode. The implosion of vapour cavities formed in the cavitating device generates (in-situ) oxidizing species which react with the sulphur moiety resulting in the removal of sulphur from the organic phase. In this work, orifice was used as a cavitating device and deep desulphurization was demonstrated for removal of thiophene as a model sulphur compound from synthetic fuel of n-octane, toluene and n-octanol. The effect of concentration of sulphur (up to 300 ppm), nature of organic phase and effect of pressure drop (0.5 to 10 bar) was discussed. A very high removal of sulphur content of more than 90% was demonstrated. The process is easy to operate, essentially works at ambient conditions and the ratio of aqueous to organic phase can be easily adjusted to maximise sulphur removal. Experimental studies were also carried out using commercial diesel as a solvent and the results substantiate similar high sulphur removal. A comparison of the two cavitating devices- one with a linear flow and one using vortex flow for effecting pressure drop and cavitation indicates similar trends in terms of sulphur removal behaviour. The developed process is expected to provide an attractive environmental engineering alternative for deep desulphurization of transportation fuels.

Keywords: cavitation, petroleum, separation, sulphur removal

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Authors: Ione Loots, Marco van Dijk, Jay Bhagwan

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Historically, South Africa had various small-scale hydropower installations in remote areas that were not incorporated in the national electricity grid. Unfortunately, in the 1960s most of these plants were decommissioned when Eskom, the national power utility, rapidly expanded its grid and capability to produce cheap, reliable, coal-fired electricity. This situation persisted until 2008, when rolling power cuts started to affect all citizens. This, together with the rising monetary and environmental cost of coal-based power generation, has sparked new interest in small-scale hydropower development, especially in remote areas or at locations (like wastewater treatment works) that could not afford to be without electricity for long periods at a time. Even though South Africa does not have the same, large-scale, hydropower potential as some other African countries, significant potential for micro- and small-scale hydropower is hidden in various places. As an example, large quantities of raw and potable water are conveyed daily under either pressurized or gravity conditions over large distances and elevations. Due to the relative water scarcity in the country, South Africa also has more than 4900 registered dams of varying capacities. However, institutional capacity and skills have not been maintained in recent years and therefore the identification of hydropower potential, as well as the development of micro- and small-scale hydropower plants has not gained significant momentum. An assessment model and decision support system for low head hydropower development has been developed to assist designers and decision makers with first-order potential analysis. As a result, various potential sites were identified and many of these sites were situated at existing infrastructure like weirs, barrages or pipelines. One reason for the specific interest in existing infrastructure is the fact that capital expenditure could be minimized and another is the reduced negative environmental impact compared to greenfield sites. This paper will explore the case study of retrofitting an unconventional and innovative hydropower plant to the outlet of a wastewater treatment works in South Africa.

Keywords: low head hydropower, retrofitting, small-scale hydropower, wastewater treatment works

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Authors: Gongbing Shan, Shiming Li, Zhao Zhang, Bingjun Wan

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Badminton originated in ancient civilizations in Europe and Asia more than 2000 years ago. Presently, it is played almost everywhere with estimated 220 million people playing badminton regularly, ranging from professionals to recreational players; and it is the second most played sport in the world after soccer. In Asia, the popularity of badminton and involvement of people surpass soccer. Unfortunately, scientific researches on badminton skills are hardly proportional to badminton’s popularity. A search of literature has shown that the literature body of biomechanical investigations is relatively small. One of the dominant skills in badminton is the forehand overhead smash, which consists of 1/5 attacks during games. Empirical evidences show that one has to adjust the body position in relation to the coming shuttlecock to produce a powerful and accurate smash. Therefore, positioning is a fundamental aspect influencing smash quality. A search of literature has shown that there is a dearth/lack of study on this fundamental aspect. The goals of this study were to determine the influence of positioning and training experience on smash quality in order to discover information that could help learn/acquire the skill. Using a 10-camera, 3D motion capture system (VICON MX, 200 frames/s) and 15-segment, full-body biomechanical model, 14 skilled and 15 novice players were measured and analyzed. Results have revealed that the body positioning has direct influence on the quality of a smash, especially on shuttlecock release angle and clearance height (passing over the net) of offensive players. The results also suggest that, for training a proper positioning, one could conduct a self-selected comfort position towards a statically hanged shuttlecock and then step one foot back – a practical reference marker for learning. This perceptional marker could be applied in guiding the learning and training of beginners. As one gains experience through repetitive training, improved limbs’ coordination would increase smash quality further. The researchers hope that the findings will benefit practitioners for developing effective training programs for beginners.

Keywords: 3D motion analysis, biomechanical modeling, shuttlecock release speed, shuttlecock release angle, clearance height

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Authors: Salina Yahya Saddick

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Ovarian cancer remains the most lethal gynecological malignancy due to the lack of highly sensitive and specific screening tools for detection of early-stage disease. The OSE provides the progenitor cells for 90% of human ovarian cancers. Recent morphologic, immunohistochemical and molecular genetic studies have led to the development of a new paradigm for the pathogenesis and origin of epithelial ovarian cancer (EOC) based on a ualistic model of carcinogenesis that divides EOC into two broad categories designated Types I and II which are characterized by specific mutations, including KRAS, BRAF, ERBB2, CTNNB1, PTEN PIK3CA, ARID1A, and PPPR1A, which target specific cell signaling pathways. Type 1 tumors rarely harbor TP53. type I tumors are relatively genetically stable and typically display a variety of somatic sequence mutations that include KRAS, BRAF, PTEN, PIK3CA CTNNB1 (the gene encoding beta catenin), ARID1A and PPP2R1A but very rarely TP53 . The cancer stem cell (CSC) hypothesis postulates that the tumorigenic potential of CSCs is confined to a very small subset of tumor cells and is defined by their ability to self-renew and differentiate leading to the formation of a tumor mass. Potential protein biomarker miRNA, are promising biomarkers as they are remarkably stable to allow isolation and analysis from tissues and from blood in which they can be found as free circulating nucleic acids and in mononuclear cells. Recently, genomic anaylsis have identified biomarkers and potential therapeutic targets for ovarian cancer namely, FGF18 which plays an active role in controlling migration, invasion, and tumorigenicity of ovarian cancer cells through NF-κB activation, which increased the production of oncogenic cytokines and chemokines. This review summarizes update information on epithelial ovarian cancers and point out to the most recent ongoing research.

Keywords: epithelial ovarian cancers, somatic sequence mutations, cancer stem cell (CSC), potential protein, biomarker, genomic analysis, FGF18 biomarker

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Authors: Suleman Bawa, Ayiku Emmanuel Lartey

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Purpose - This paper aims to examine the association between knowledge capital and multinational firms’ innovation management. We again explored the impact of transboundary investment and assimilative capacity between knowledge capital and multinational firms’ innovation management. The vital position of knowledge capital and multinational firms’ innovation management in today’s increasingly volatile environment coupled with fierce competition has been extensively acknowledged by academics and industry investment capitals. Design/methodology/approach - The theoretical association model and an empirical correlation analysis were constructed based on relevant research using data collected from 19 multinational firms in Ghana as the subject, and path analysis was constructed using SPSS 22.0 and AMOS 24.0 to test the formulated hypotheses. Findings - Varied conclusions are drawn consequential from theoretical inferences and empirical tests. For multinational firms, knowledge capital relics positively significant to multinational firms’ innovation management. Multinational firms with advanced knowledge capital likely spawn greater corporations’ innovation management. Second, transboundary investment efficiently intermediates the association between knowledge physical capital, knowledge interactive capital, and corporations’ innovation management. At the same time, this impact is insignificant between knowledge of empirical capital and corporations’ innovation management. Lastly, the impact of transboundary investment and assimilative capacity on the association between knowledge capital and corporations’ innovation management is established. We summarized the implications for managers based on our outcomes. Research limitations/implications - Multinational firms must dynamically build knowledge capital to augment corporations’ innovation management. Conversely, knowledge capital motivates multinational firms to implement transboundary investment and cultivate assimilative capacity. Accordingly, multinational firms can efficiently exploit diverse information to augment their corporate innovation management. Practical implications – This paper presents a comprehensive justification of knowledge capital and manufacturing firms’ innovation management by exploring the impact of transboundary investment and assimilative capacity within the manufacturing industry, its sequential progress, and its associated challenges. Originality/value – This paper is amongst the first to find empirical results to back knowledge capital and manufacturing firms’ innovation management by exploring the impact of transboundary investment and assimilative capacity within the manufacturing industry. Additionally, aligning knowledge as a coordinative instrument is a significant input to our discernment in this area.

Keywords: knowledge capital, transboundary investment, innovation management, assimilative capacity

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Authors: Shih Yu Pan, Pao Chen Hung, Chuan Yao Lin, Charles C.-K. Chou, Yu Chi Lin, Kai Hsien Chi

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This study analyzed 16 atmospheric PAHs species which were controlled by USEPA and IARC. To measure the concentration of PAHs, four rural sampling sites and two urban sampling sites were selected in Central Taiwan during spring and summer. In central Taiwan, the rural sampling stations were located in the downstream of Da-An River, Da-Jang River, Wu River and Chuo-shui River. On the other hand, the urban sampling sites were located in Taichung district and close to the roadside. Ambient air samples of both vapor phase and particle phase of PAHs compounds were collected using high volume sampling trains (Analitica). The sampling media were polyurethane foam (PUF) with XAD2 and quartz fiber filters. Diagnostic ratio, Principal component analysis (PCA), Positive Matrix Factorization (PMF) models were used to evaluate the apportionment of PAHs in the atmosphere and speculate the relative contribution of various emission sources. Because of the high temperature and low wind speed, high PAHs concentration in the atmosphere was observed. The total PAHs concentration, especially in vapor phase, had significant change during summer. During the sampling periods the total PAHs concentration of atmospheric at four rural and two urban sampling sites in spring and summer were 3.70±0.40 ng/m3,3.40±0.63 ng/m3,5.22±1.24 ng/m3,7.23±0.37 ng/m3,7.46±2.36 ng/m3,6.21±0.55 ng/m3　; 15.0± 0.14 ng/m3,18.8±8.05 ng/m3,20.2±8.58 ng/m3,16.1±3.75 ng/m3,29.8±10.4 ng/m3,35.3±11.8 ng/m3, respectively. In order to identify PAHs sources, we used diagnostic ratio to classify the emission sources. The potential sources were diesel combustion and gasoline combustion in spring and summer, respectively. According to the principal component analysis (PCA), the PC1 and PC2 had 23.8%, 20.4% variance and 21.3%, 17.1% variance in spring and summer, respectively. Especially high molecular weight PAHs (BaP, IND, BghiP, Flu, Phe, Flt, Pyr) were dominated in spring when low molecular weight PAHs (AcPy, Ant, Acp, Flu) because of the dominating high temperatures were dominated in the summer. Analysis by using PMF model found the sources of PAHs in spring were stationary sources (34%), vehicle emissions (24%), coal combustion (23%) and petrochemical fuel gas (19%), while in summer the emission sources were petrochemical fuel gas (34%), the natural environment of volatile organic compounds (29%), coal combustion (19%) and stationary sources (18%).

Keywords: PAHs, source identification, diagnostic ratio, principal component analysis, positive matrix factorization

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Authors: Tsega Asresa Mengistu, Getahun Tigistu

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Computer vision is an artificial intelligence subfield that allows computers and systems to retrieve meaning from digital images. It is applied in various fields of study self-driving cars, video surveillance, agriculture, Quality control, Health care, construction, military, and everyday life. Aromatic and medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, and other natural health products for therapeutic and Aromatic culinary purposes. Herbal industries depend on these special plants. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs, and going to export not only industrial raw materials but also valuable foreign exchange. There is a lack of technologies for the classification and identification of Aromatic and medicinal plants in Ethiopia. The manual identification system of plants is a tedious, time-consuming, labor, and lengthy process. For farmers, industry personnel, academics, and pharmacists, it is still difficult to identify parts and usage of plants before ingredient extraction. In order to solve this problem, the researcher uses a deep learning approach for the efficient identification of aromatic and medicinal plants by using a convolutional neural network. The objective of the proposed study is to identify the aromatic and medicinal plant Parts and usages using computer vision technology. Therefore, this research initiated a model for the automatic classification of aromatic and medicinal plants by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides the root, flower and fruit, latex, and barks. The study was conducted on aromatic and medicinal plants available in the Ethiopian Institute of Agricultural Research center. An experimental research design is proposed for this study. This is conducted in Convolutional neural networks and Transfer learning. The Researcher employs sigmoid Activation as the last layer and Rectifier liner unit in the hidden layers. Finally, the researcher got a classification accuracy of 66.4 in convolutional neural networks and 67.3 in mobile networks, and 64 in the Visual Geometry Group.

Keywords: aromatic and medicinal plants, computer vision, deep convolutional neural network

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Authors: A. Assad, T. Zayed

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Water networks (WNs) are responsible of providing adequate amounts of safe, high quality, water to the public. As other critical infrastructure systems, WNs are subjected to deterioration which increases the number of breaks and leaks and lower water quality. In Canada, 35% of water assets require critical attention and there is a significant gap between the needed and the implemented investments. Thus, the need for efficient rehabilitation programs is becoming more urgent given the paradigm of aging infrastructure and tight budget. The first step towards developing such programs is to formulate a Performance Index that reflects the current condition of water assets along with its criticality. While numerous studies in the literature have focused on various aspects of condition assessment and reliability, limited efforts have investigated the criticality of such components. Critical water mains are those whose failure cause significant economic, environmental or social impacts on a community. Inclusion of criticality in computing the performance index will serve as a prioritizing tool for the optimum allocating of the available resources and budget. In this study, several social, economic, and environmental factors that dictate the criticality of a water pipelines have been elicited from analyzing the literature. Expert opinions were sought to provide pairwise comparisons of the importance of such factors. Subsequently, Fuzzy Logic along with Analytical Network Process (ANP) was utilized to calculate the weights of several criteria factors. Multi Attribute Utility Theories (MAUT) was then employed to integrate the aforementioned weights with the attribute values of several pipelines in Montreal WN. The result is a criticality index, 0-1, that quantifies the severity of the consequence of failure of each pipeline. A novel contribution of this approach is that it accounts for both the interdependency between criteria factors as well as the inherited uncertainties in calculating the criticality. The practical value of the current study is represented by the automated tool, Excel-MATLAB, which can be used by the utility managers and decision makers in planning for future maintenance and rehabilitation activities where high-level efficiency in use of materials and time resources is required.

Keywords: water networks, criticality assessment, asset management, fuzzy analytical network process

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Authors: Helida Thays Gomes Soares, Conceicao De Maria Pinheiro Correia, Fabiano Maciel Soares, Kleymer Silva

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There is great discussion around populational increase in urban areas of the global south, and, consequently, the growth of inappropriate housing and the different ways humans have found to solve housing problems around the world. Sao Luís, the capital of the state of Maranhao is a good example. The 1.6 million inhabitant metropole is a colonial tropical city that shelters 22% of the population of Maranhão, brazilian state that still carries the scars of slavery in past centuries. In 2016, Brazilian Institute of Geography and Statistic found that 20% of Maranhão’s inhabitants were living in houses with external walls made of non-durable materials, like recycled wood, cardboard or soil. Out of this problematic, this study aims to propose interventions not only in the physical structure of irregular housing, but also to serve as a guide to intervene in the way eco-friendly, communitarian housing is seen by extreme poor zones inside metropolitan regions around big cities in the global south. The adaptation and reuse of industrial containers from the Harbor of Itaqui for housing is also an aim of the project. The great volume of discarded industrial containers may be an opportunity to solve housing deficit in the city. That way, through field research in São Luís’ neighborhoods mostly occupied by inappropriate housing, the study intends to raise ethnographical and physical values that help to shape new uses of industrial containers and recycled building materials, bringing the community into the process of shaping new-housing for local housing programs, changing the mindset of a concrete/brick model of building. The study used a general feasibility analysis of local engineers regarding strength of the locally used container for construction purposes, and also researched in-loco the current impressions of risky areas inhabitants of housing, traditional housing and the role they played as city shapers, evaluating their perceptions of what means to live and how their houses represent their personality.

Keywords: container housing, civil construction, housing deficit, participatory design, sustainability

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Authors: Suchart Tripopsakul

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This paper uses data from the Global Entrepreneurship Monitor (GEM) to investigate the difference of attitudes towards entrepreneurial intention (EI). EI is generally assumed to be the single most relevant predictor of entrepreneurial behavior. The aim of this paper is to examine a range of attitudes effect on individual’s intent to start a new venture. A cross-cultural comparison between Asia and Europe is used to further investigate the possible differences between potential entrepreneurs from these distinct national contexts. The empirical analysis includes a GEM data set of 10 countries (n = 10,306) which was collected in 2013. Logistic regression is used to investigate the effect of individual’s attitudes on EI. Independent variables include individual’s perceived capabilities, the ability to recognize business opportunities, entrepreneurial network, risk perceptions as well as a range of socio-cultural attitudes. Moreover, a cross-cultural comparison of the model is conducted including six ASEAN (Malaysia, Indonesia, Philippines, Singapore, Vietnam and Thailand) and four European nations (Spain, Sweden, Germany, and the United Kingdom). The findings support the relationship between individual’s attitudes and their entrepreneurial intention. Individual’s capability, opportunity recognition, networks and a range of socio-cultural perceptions all influence EI significantly. The impact of media attention on entrepreneurship and was found to influence EI in ASEAN, but not in Europe. On the one hand, Fear of failure was found to influence EI in Europe, but not in ASEAN. The paper develops and empirically tests attitudes toward Entrepreneurial Intention between ASEAN and Europe. Interestingly, fear of failure was found to have no significant effect in ASEAN, and the impact of media attention on entrepreneurship and was found to influence EI in ASEAN. Moreover, the resistance of ASEAN entrepreneurs to the otherwise high rates of fear of failure and high impact of media attention are proposed as independent variables to explain the relatively high rates of entrepreneurial activity in ASEAN as reported by GEM. The paper utilizes a representative sample of 10,306 individuals in 10 countries. A range of attitudes was found to significantly influence entrepreneurial intention. Many of these perceptions, such as the impact of media attention on entrepreneurship can be manipulated by government policy. The paper also suggests strategies by which Asian economy in particular can benefit from their apparent high impact of media attention on entrepreneurship.

Keywords: an entrepreneurial intention, attitude, GEM, ASEAN and Europe

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Authors: Marine Kobalava

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The article analyzes the level of Georgia's tourism potential usage during the pandemic. The conclusion is drawnthat Georgia, as a tourism brand, is in a significant crisis at this stage, revenues from this sector have been substantially reduced, communication with potential customers is interrupted, no international marketing and PR communication strategies have been developed for the post-pandemic period. In order to rehabilitate the tourism industry of Georgia, it is considered vital to take measures using international marketing and PR communication strategies adjusted to the needs of the sectorthat will improve the use of tourism potential and stimulate the development of the sector. The goal of the research is to identify the factors hindering the use of tourism potential in the direction of international marketing and PR communication strategies in the post-pandemic period and to develop recommendations on ways to solve them. Research methods. The paper uses various theoretical and methodological tools of research, including Bibliographic research has been conducted on the main research issues; Analysis, synthesis, induction, and other methods are used to select and group data, identify similarities and differences, and identify trends; Endogenous and exogenous factors affecting the field of tourism have been studied by means of SWOT and PESTEL analyzes. A comparison model is used to analyze the strategy documents. Primary accounting materials are obtained from the National Statistics Office and the relevant ministries. Based on the results of the research, the directions of correct positioning of tourism products and marketing communication in the post-pandemic period have been developed. It is substantiated that a short-term international marketing strategy should include: probable goals of communication, maintaining a position on a potential traveler's “radar,” focusing communication on key motivating factors (gastronomy, winemaking, folklore, protected areas, mountainous regions). From a marketing point of view, it is important: holding international marketing events, compiling a list of target countries, formation of stimulus mechanisms, development of incentive programs for international tour operators, etc. The paper draws conclusions about the problems of using the tourism potential, recommendations on ways to solve this problems through international marketing and PR communication strategies are offered

Keywords: PR communication, international marketing strategy, tourism potential, post-pandemic period

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Authors: Niyti, Aman Deep, Rajesh Kharab, Sahila Chopra, Raj. K. Gupta

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Relatively long-lived transactinide elements (i.e., elements with atomic number Z≥104) up to Z = 108 have been produced in nuclear reactions between low Z projectiles (C to Al) and actinide targets. Cross sections have been observed to decrease steeply with increasing Z. Recently, production cross sections of several picobarns have been reported for comparatively neutron-rich nuclides of 112 through 118 produced via hot fusion reactions with 48Ca and actinide targets. Some of those heavy nuclides are reported to have lifetimes on the order of seconds or longer. The relatively high cross sections in these hot fusion reactions are not fully understood and this has renewed interest in systematic studies of heavy-ion reactions with actinide targets. The main aim of this work is to understand the dynamics hot fusion reactions 18O+ 248Cm and 22Ne+244Pu (carried out at RIKEN and TASCA respectively) using the collective clusterization technique, carried out by undertaking the decay of the compound nucleus 266Rf∗ into 4n, 5n and 6n neutron evaporation channels. Here we extend our earlier study of the excitation functions (EFs) of 266Rf∗, formed in fusion reaction 18O+248Cm, based on Dynamical Cluster-decay Model (DCM) using the pocket formula for nuclear proximity potential, to the use of other nuclear interaction potentials derived from Skyrme energy density formalism (SEDF) based on semiclassical extended Thomas Fermi (ETF) approach and also study entrance channel effects by considering the synthesis of 266Rf* in 22Ne+244Pu reaction. The Skyrme forces used are the old force SIII, and new forces GSkI and KDE0(v1). Here, the EFs for the production of 260Rf, 261Rf and 262Rf isotope via 6n, 5n and 4n decay channel from the 266Rf∗ compound nucleus are studied at Elab = 88.2 to 125 MeV, including quadrupole deformations β2i and ‘hot-optimum’ orientations θi. The calculations are made within the DCM where the neck-length ∆R is the only parameter representing the relative separation distance between two fragments and/or clusters Ai which assimilates the neck formation effects.

Keywords: entrance channel effects, fusion reactions, skyrme force, superheavy nucleus

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Authors: Naveen Porika, Snigdho Majumdar, Niraj Sethi

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Water, food and energy securities are emerging as increasingly important and vital issues for India and the world. Hyderabad urban agglomeration (HUA), the capital city of Andhra Pradesh State in India, is the sixth largest city has a population of about 8.2 million. The Musi River, which is a tributary of Krishna river flows from west to east right through the heart of Hyderabad, about 80% of the water used by people is released back as sewage, which flows back into Musi every day with detrimental effects on the environment and people downstream of the city. The average daily sewage generated in Hyderabad city is 950 MLD, however, treatment capacity exists only for 541 Million Liters per Day (MLD) but only 407 MLD of sewage is treated. As a result, 543 MLD of sewage daily flows into Musi river. Hyderabad’s current estimated water demand stands at 320 Million Gallons per Day (MGD). However, its installed capacity is merely 270 MGD; by 2020 estimated demand will grow to 400 MGD. There is huge gap between current supply and demand, and this is likely to widen by 2021. Developing new fresh water sources is a challenge for Hyderabad, as the fresh water sources are few and far from the City (about 150-200 km) and requires excessive pumping. The constraints presented above make the conventional alternatives for supply augmentation unsustainable and unattractive .One such dependable and captive source of easily available water is the treated sewage. With proper treatment, water of desired quality can be recovered from the waste water (sewage) for recycle and reuse. Hyderabad Amberpet sewage treatment of capacity 339 MLD is Asia’s largest sewage treatment plant. Tertiary sewage treatment Standard basic engineering modules of 30 MLD,60 MLD, 120MLD & 180 MLD for sewage treatment plants has been developed which are utilized for developing Sewage Reclamation & Reuse model in Asia’s largest sewage treatment plant. This paper will focus on Hyderabad Water Supply & Demand, Sewage Generation & Treatment, Technical aspects of Tertiary Sewage Treatment and Utilization of developed standard modules for reclamation & reuse of treated sewage to overcome the deficit of 130 MGD as projected by 2021.

Keywords: water reclamation, reuse, Andhra Pradesh, hyderabad, musi river, sewage, demand and supply, recycle, Amberpet, 339 MLD, engineering modules, tertiary treatment

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Authors: Atlal El-Assaad

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Viruses change with time through mutations and result in new variants that may persist or disappear. A Mutation refers to an actual change in the virus genetic sequence, and a variant is a viral genome that may contain one or more mutations. Critical mutations may cause the virus to be more transmissible, with high disease severity, and more vulnerable to diagnostics, therapeutics, and vaccines. Thus, variants carrying such mutations may increase the risk to human health and are considered variants of concern (VOC). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) - the contagious in humans, positive-sense single-stranded RNA virus that caused coronavirus disease 2019 (COVID-19) - has been studied thoroughly, and several variants were revealed across the world with their corresponding mutations. SARS-CoV-2 has four structural proteins, known as the S (spike), E (envelope), M (membrane), and N (nucleocapsid) proteins, but prior study and vaccines development focused on genetic mutations in the S protein due to its vital role in allowing the virus to attach and fuse with the membrane of a host cell. Specifically, subunit S1 catalyzes attachment, whereas subunit S2 mediates fusion. In this perspective, we studied all charged amino acid mutations of the SARS-CoV-2 viral spike protein S1 when bound to Antibody CC12.1 in a crystal structure and assessed the effect of different mutations. We generated all missense mutants of SARS-CoV-2 protein amino acids (AAs) within the SARS-CoV-2:CC12.1 complex model. To generate the family of mutants in each complex, we mutated every charged amino acid with all other charged amino acids (Lysine (K), Arginine (R), Glutamic Acid (E), and Aspartic Acid (D)) and studied the new binding of the complex after each mutation. We applied Poisson-Boltzmann electrostatic calculations feeding into free energy calculations to determine the effect of each mutation on binding. After analyzing our data, we identified charged amino acids keys for binding. Furthermore, we validated those findings against published experimental genetic data. Our results are the first to propose in silico potential life-threatening mutations of SARS-CoV-2 beyond the present mutations found in the five common variants found worldwide.

Keywords: SARS-CoV-2, variant, ionic amino acid, protein-protein interactions, missense mutation, AESOP

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Authors: Ali Nabavi, Farimah Safari, Mohammad Kashkooli, Sara Sadat Nabavizadeh, Hossein Molavi Vardanjani

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Cognitive impairment presents a significant and increasing health concern as populations age. Environmental risk factors such as heavy metal exposure are suspected contributors, but their specific roles remain incompletely understood. Machine learning offers a promising approach to integrate multi-factorial data and improve the prediction of cognitive outcomes. This study aimed to develop and validate machine learning models to predict early risk of cognitive impairment by incorporating demographic, clinical, and biomarker data, including measures of heavy metal exposure. A retrospective analysis was conducted using 2011-2014 National Health and Nutrition Examination Survey (NHANES) data. The dataset included participants aged 20 years and older who underwent cognitive testing. Variables encompassed demographic information, medical history, lifestyle factors, and biomarkers such as blood and urine levels of lead, cadmium, manganese, and other metals. Machine learning algorithms were trained on 90% of the data and evaluated on the remaining 10%, with performance assessed through metrics such as accuracy, area under curve (AUC), and sensitivity. Analysis included 2,933 participants. The stacking ensemble model demonstrated the highest predictive performance, achieving an AUC of 0.778 and a sensitivity of 0.879 on the test dataset. Key predictors included age, gender, hypertension, education level, urinary cadmium, and blood manganese levels. The findings indicate that machine learning can effectively predict the risk of cognitive impairment using a comprehensive set of clinical and environmental exposure data. Incorporating biomarkers of heavy metal exposure improved prediction accuracy and highlighted the role of environmental factors in cognitive decline. Further prospective studies are recommended to validate the models and assess their utility over time.

Keywords: cognitive impairment, heavy metal exposure, predictive models, aging

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Authors: Geun-Yeon Kim, S. P. Praveen Kumar, Kwon-Hee Lee

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A steering knuckle arm is the component that connects the steering system and suspension system. The structural performances such as stiffness, strength, and durability are considered in its design process. The former study suggested the lightweight design of a knuckle arm considering the structural performances and using the metamodel-based optimization. The six shape design variables were defined, and the optimum design was calculated by applying the kriging interpolation method. The finite element method was utilized to predict the structural responses. The suggested knuckle was made of the aluminum Al6082, and its weight was reduced about 60% in comparison with the base steel knuckle, satisfying the design requirements. Then, we investigated its manufacturability by performing foraging analysis. The forging was done as hot process, and the product was made through two-step forging. As a final step of its developing process, the durability is investigated by using the flexible dynamic analysis software, LS-DYNA and the pre and post processor, eta/VPG. Generally, a car make does not provide all the information with the part manufacturer. Thus, the part manufacturer has a limit in predicting the durability performance with the unit of full car. The eta/VPG has the libraries of suspension, tire, and road, which are commonly used parts. That makes a full car modeling. First, the full car is modeled by referencing the following information; Overall Length: 3,595mm, Overall Width: 1,595mm, CVW (Curve Vehicle Weight): 910kg, Front Suspension: MacPherson Strut, Rear Suspension: Torsion Beam Axle, Tire: 235/65R17. Second, the road is selected as the cobblestone. The road condition of the cobblestone is almost 10 times more severe than that of usual paved road. Third, the dynamic finite element analysis using the LS-DYNA is performed to predict the durability performance of the suggested knuckle arm. The life of the suggested knuckle arm is calculated as 350,000km, which satisfies the design requirement set up by the part manufacturer. In this study, the overall design process of a knuckle arm is suggested, and it can be seen that the developed knuckle arm satisfies the design requirement of the durability with the unit of full car. The VPG analysis is successfully performed even though it does not an exact prediction since the full car model is very rough one. Thus, this approach can be used effectively when the detail to full car is not given.

Keywords: knuckle arm, structural optimization, Metamodel, forging, durability, VPG (Virtual Proving Ground)

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Authors: Christine A. Odinga, G. Sanjay, M. Mathew, S. Gupta, F. M. Swalaha, F. A. O. Otieno, F. Bux

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Wastewater discharged from municipal treatment plants contain an amalgamation of trace metals. The presence of metal pollutants in wastewater poses a huge challenge to the choice and applications of the preferred treatment method. Conventional treatment methods are inefficient in the removal of trace metals due to their design approach. This study evaluated the treatment performance of a constructed rhizofiltration system in the removal of heavy metals from municipal wastewater. The study was conducted at an eThekwni municipal wastewater treatment plant in Kingsburgh - Durban in the province of KwaZulu-Natal. The construction details of the pilot-scale rhizofiltration unit included three different layers of substrate consisting of medium stones, coarse gravel and fine sand. The system had one section planted with Phragmites australis L. and Kyllinga nemoralis L. while the other section was unplanted and acted as the control. Influent, effluent and sediment from the system were sampled and assessed for the presence of and removal of selected trace heavy metals using standard methods. Efficiency of metals removal was established by gauging the transfer of metals into leaves, roots and stem of the plants by calculations based on standard statistical packages. The Langmuir model was used to assess the heavy metal adsorption mechanisms of the plants. Heavy metals were accumulated in the entire rhizofiltration system at varying percentages of 96.69% on planted and 48.98% on control side for cadmium. Chromium was 81% and 24%, Copper was 23.4% and 1.1%, Nickel was 72% and 46.5, Lead was 63% and 31%, while Zinc was 76% and 84% on the on the water and sediment of the planted and control sides of the rhizofilter respectively. The decrease in metal adsorption efficiencies on the planted side followed the pattern of Cd>Cr>Zn>Ni>Pb>Cu and Ni>Cd>Pb>Cr>Cu>Zn on the control side. Confirmatory analysis using Electron Scanning Microscopy revealed that higher amounts of metals was deposited in the root system with values ranging from 0.015mg/kg (Cr), 0.250 (Cu), 0.030 (Pb) for P. australis, and 0.055mg/kg (Cr), 0.470mg/kg (Cu) and 0.210mg/kg,(Pb) for K. nemoralis respectively. The system was found to be efficient in removing and reducing metals from wastewater and further research is necessary to establish the immediate mechanisms that the plants display in order to achieve these reductions.

Keywords: wastewater treatment, Phragmites australis L., Kyllinga nemoralis L., heavy metals, pathogens, rhizofiltration

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Authors: Masoud Sheidaei, Mohammad-Reza Kordasti, Fahimeh Koohdar

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Calotropis procera (Aiton) W.T.Aiton, (Apocynaceae), is an economically and medicinally important plant species which is an evergreen, perennial shrub growing in arid and semi-arid climates, and can tolerate very low annual rainfall (150 mm) and a dry season. The plant can also tolerate temperature ran off 20 to30°C and is not frost tolerant. This plant species prefers free-draining sandy soils but can grow also in alkaline and saline soils.It is found at a range of altitudes from exposed coastal sites to medium elevations up to 1300 m. Due to morpho-physiological adaptations of C. procera and its ability to tolerate various abiotic stresses. This taxa can compete with desirable pasture species and forms dense thickets that interfere with stock management, particularly mustering activities. Caloteropis procera grows only in southern part of Iran where in comprises a limited number of geographical populations. We used different population genetics and r landscape analysis to produce data on geographical populations of C. procera based on molecular genetic study using SCoT molecular markers. First, we used spatial principal components (sPCA), as it can analyze data in a reduced space and can be used for co-dominant markers as well as presence / absence data as is the case in SCoT molecular markers. This method also carries out Moran I and Mantel tests to reveal spatial autocorrelation and test for the occurrence of Isolation by distance (IBD). We also performed Random Forest analysis to identify the importance of spatial and geographical variables on genetic diversity. Moreover, we used both RDA (Redundency analysis), and LFMM (Latent factor mixed model), to identify the genetic loci significantly associated with geographical variables. A niche modellng analysis was carried our to predict present potential area for distribution of these plants and also the area present by the year 2050. The results obtained will be discussed in this paper.

Keywords: population genetics, landscape genetic, Calotreropis procera, niche modeling, SCoT markers

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