Search results for: learning strategy

Authors: Prabhashini Wijewantha

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This study looks at the impact of protean career attitude of employees on their career success and next it looks at the mediation effect of career insights on the above relationship. Career success is defined as the accomplishment of desirable work related outcomes at any point in person’s work experiences over time and it comprises of two sub variables, namely, career satisfaction and perceived employability. Protean career attitude was measured using the eight items from the Self Directedness subscale of the Protean Career Attitude scale developed by Briscoe and Hall, where as career satisfaction was measured by the three item scale developed by Martine, Eddleston, and Veiga. Perceived employability was also evaluated using three items and career insight was measured using fourteen items that were adapted and used by De Vos and Soens. Data were collected from a sample of 300 mid career executives in Sri Lanka deploying the survey strategy and data were analyzed using the SPSS and AMOS software version 20.0. A preliminary analysis of data was initially performed where data were screened and reliability and validity were ensured. Next a simple regression analysis was performed to test the direct impact of protean career attitude on career success and the hypothesis was supported. The Baron and Kenney’s four steps, three regressions approach for mediator testing was used to calculate the mediation effect of career insight on the above relationship and a partial mediation was supported by the data. Finally theoretical and practical implications are discussed.

Keywords: career success, career insight, mid career MBAs, protean career attitude

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Authors: Sirajoddeen Al-Ameen

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Researchers seek to introduce development leading to technologies that address environmental problems and learn how to interact with stakeholders, managers, and policymakers for appropriate actions. One of the greatest strategies that African countries need to consider in realizing sustainable development is effective, efficient, credible, and lasting environmental sustainability and ensuring that future generations have access to natural resources to live in a better way. Therefore the coordinated set of participatory and continuously improving processes of analysis, capacity, planning, and investment seeks to integrate the social and environmental objectives of society, and this is not given priority in Nigeria. Environmental sustainability is a field where people can understand the natural environment and public works for sustainable development. Sustainable development requires shifts from ordinary ways of doing things to modern ways of executing activities ranging from low to high productivity, the creation and adoption of new strategies, new skills, and knowledge. It ensures a developed world with a secure and healthy environment for all; human beings, animals, and plants alike. This paper is to carry out a review of various literature sources to ascertain the potential strategy of environment and sustainable development reform using the content analysis method to discuss the environmental strategies towards sustainable development in Nigeria. The objective of this paper is to enable Nigerians to understand and have an orientation on how to manage environmental resources and avoid environmental impact on the ecosystem, and also to find sustainable solutions for environmental issues without compromising economic development.

Keywords: development, environment, strategies, sustainable

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Authors: Argaw Amare, Abbuna Fuffa, Stringer Andy

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Improving public knowledge and changing their attitudes towards antibiotic use will be a crucial early strategy to contain Antibiotic resistance. The current study was undertaken from November 2015 to June 2016. A cross-sectional survey using a pretested questionnaire was conducted on 392 residents (330 male and 62 female) aged 18 and above. Participants were selected randomly. Data was analyzed using simple descriptive statistics; the Chi-square test was used to determine any significant difference. The majority of participants (81%) were farmers in their occupation. Most of the respondents (76%) were not able to define the difference between antimicrobials and antibiotics. Furthermore, (61%) of participants were not able to define what antibiotics and for what purpose they are used. Thirty-four percent of participants do not know the names of antibiotics they have used for their animals and for themselves. Nearly 68% have no knowledge about the disease they have been treated for. The majority of participants (73.5%) agree to complete their course of treatment even if they feel better. About 72.5% of participants disagree that antibiotics are safe and can be used to treat different diseases, without prescription. Most of the participants (95%) treat their animals after diagnosis; more than 80% of them agree to not purchase veterinary drugs from local traders. This study showed that the participants have poor knowledge and good attitude, with an average score of 41.3±16.1% and 79.6±16, respectively. Knowledge and attitude are significantly correlated (p<0.01). The participants in this study had a good attitude toward the rational use of antibiotics. Whereas they lack knowledge with regard to the kinds of antibiotics and the diseases they are prescribed for. Therefore, further educational interventions are necessary to improve their understanding of the antibiotics currently available and the major bacterial diseases they are prescribed.

Keywords: AMR, knoweledge, attitude, perception

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Authors: Sumbul Farhat, Pratyay Vaibhav, Sarah Jain, Kapinder Kumar, Archna Kumar

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The Diamondback Moth, Plutella xylostella (Linnaeus), is a major pest of cole crops that causes approximately 50% loss in global production. The utilization of inorganic pesticides is reflected in the development of resistance to this pest. Thus, there is a great need for an eco-friendly, sustainable strategy for the control of this pest. Although this pest, several natural enemies are reported worldwide, none of them can control it efficiently. Therefore, a proposed study is planned to understand the Volatile Organic Compounds (VOCs) mediated signaling interaction mechanism of the plant, pest, and natural enemy. For VOCs collection during different deployment stages of Cabbage POI, Green Ball, Pusa Cabbage, Cabbage Local, Snowball 16, Kanchan Plus, Pusa Meghna, Farm Sona Hybrid F1, and Samridhi F1 Hybrid, the Solid-phase microextraction (SPME) method was employed. Characterization of VOCs was conducted by Gas Chromatography-Mass Spectrometry (GC-MS). The impact of collected VOCs was assessed through Y-Tube Bioassays. The results indicate that the Cabbage variety Green Ball shows maximum repellency for P. xylostella (-100%). The cues present in this variety may be exploited for efficient management of P. xylostella in the cole crop ecosystem.

Keywords: Plutella xylostella, cole crops, volatile organic compounds, GC-MS, Green Ball

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Authors: Sanaa Bardaweel

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Inorganic polyphosphate (poly P) is present in all living forms tested to date, from each of the three kingdoms of life. Studied mainly in prokaryotes, poly P and its associated enzymes are vital in diverse basic metabolism, in at least some structural functions and, notably, in stress responses. These plentiful and unrelated roles for poly P are probably the consequence of its presence in life-forms early in evolution. The genomes of many bacterial species, including pathogens, encode a homologue of a major poly P synthetic enzyme, poly P kinase 1 (PPK1). Genetic deletion of ppk1 results in reduced poly P levels and loss of pathogens virulence towards protozoa and animals. Thus far, no PPK1 homologue has been identified in higher-order eukaryotes and, therefore, PPK1 represents a novel target for chemotherapy. The idea of the current study is to purify the PPK1 from Escherichia coli to homogeneity in order to study the effect of active site point mutations on PPK1 catalysis via the application of site-directed mutagenesis strategy. The knowledge obtained about the active site of PPK1 will be utilized to characterize the catalytic and kinetic mechanism of PPK1 with model substrates. Comprehensive understanding of the enzyme kinetic mechanism and catalysis will be used to design and screen a library of synthetic compounds for potential discovery of selective PPK1-inhibitors.

Keywords: antimicobial, Escherichia coli, inorganic polyphosphate, PPK1-inhibitors

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Authors: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

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Authors: Suarez-Puello Alejandro, Baquero-Ruiz Andrés F, Suarez-Puello Rodrigo

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This paper discusses the results of a foresight exercise which analyzes Bogota’s fruit, vegetable and tuber supply chain strategy- described at the Food Supply and Security Master Plan (FSSMP)-to provide the inhabitants of Bogotá, Colombia, with basic food products at a fair price. The methodology consisted of using quantitative and qualitative foresight tools such as system dynamics and variable selection methods to better represent interactions among stakeholders and obtain more integral results that could shed light on this complex situation. At first, the Master Plan is an input to establish the objectives and scope of the exercise. Then, stakeholders and their relationships are identified. Later, system dynamics is used to model product, information and money flow along the fruit, vegetable and tuber supply chain. Two scenarios are presented, discussing actions by the public sector and the reactions that could be expected from the whole food supply system. Finally, these impacts are compared to the Food Supply and Security Master Plan’s objectives suggesting recommendations that could improve its execution. This foresight exercise performed at a governmental level is intended to promote the widen the use of foresight as an anticipatory, decision-making tool that offers solutions to complex problems.

Keywords: decision making, foresight, public policies, supply chain, system dynamics

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Authors: Tabiti S. Tabiti, A. M. Jinadu, Daramola Japheth

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Urban insecurity is among the challenges militating against sustainable urban governance; in the first place it distorts the peace of urban areas making them unsafe. On the other hand it hinders the effective performance of urban functions. Urban security challenges manifest in different forms such as, street violence, theft and robbery, accidents of different types kidnapping, killings etc.. Efforts to address urban security challenges in Nigeria have been concentrated in legislative, law enforcement and the use of community vigilante groups. However in this study, the place of physical planning strategy through effective neighbourhood renewal as practiced in Mokola is presented as an effective complementary approach for addressing urban insecurity. On this backdrop, the paper recommends the need for gradual rehabilitation of urban slum neighborhoods by the state government in collaboration with World Bank and other development financiers. The local governments should be made autonomy in Nigeria so as to make them more responsible to the people. Other recommendations suggested in the paper include creating enabling environment that will promote economic empowerment and public enlightment on personal and community sanitation. It is certain that if these recommendations are adopted the challenge of urban insecurity will reduce significantly in Nigerian cities.

Keywords: neighbourhood renewal, pilot project, slum upgrading, urban security

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Authors: Asma Dill

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The aim of this study is to explore the role of HRM practices in SMEs success. The role of HRM practices in large enterprises is relatively known, on the other hand, small and medium enterprises (SMEs) companies have not been greatly studied in relation to the HRM practices in the past. Although, there is a lack of literature and empirical research in this area, several studies in the recent years emphasized on the importance of the HRM practices for the success of the SMEs. This study finds out relationship of HRM practices and SMESs performances. The objective is to analyze significant impacts of HRM practices (training, performance appraisal, compensation and employee development) on SMEs success, to determine whether SMEs recognize the importance of HRM practices in their businesses. To carry out this research a survey research strategy was followed. The sample frame for this study consisted of firms that belong to the services and commerce sector, employing at least 50 employees. The final research sample consisted of questionnaires. Descriptive statistical methods have been used during quantitative analysis to explore the relations. The findings of the study revealed that HRM practices have a significant influence on the performance of SMEs, and the better the HRM practice, the higher the performance of the SMEs. HRM practices, including, training, compensation, performance appraisal and employee development, have been found to be significantly and positively related to business success. Outcome of the study will provide useful guidelines to the business organizations. This study contributes to knowledge by providing insights on the impact of HRM practices on SMEs performance.

Keywords: compensation, employee performance, HRM practices, training

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Authors: Arun Prasad Jaganathan

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In today's rapidly evolving technological landscape, the need for efficient and proactive maintenance management solutions has become increasingly evident across various industries. Traditional approaches often suffer from drawbacks such as reactive strategies, leading to potential downtime, increased costs, and decreased operational efficiency. In response to these challenges, this paper proposes an AI-enabled approach to object-based maintenance management aimed at enhancing reliability and efficiency. The paper contributes to the growing body of research on AI-driven maintenance management systems, highlighting the transformative impact of intelligent technologies on enhancing object reliability and operational efficiency.

Keywords: AI, machine learning, predictive maintenance, object-based maintenance, expert team scheduling

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Authors: Mahshid Arabi

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With the rapid expansion of digital technologies and the internet, information security has become a critical priority for organizations and individuals. The widespread use of digital tools such as smartphones and internet networks facilitates the storage of vast amounts of data, but simultaneously, vulnerabilities and security threats have significantly increased. The aim of this study is to examine and analyze modern methods of information security management and to develop a comprehensive model to counteract threats and information misuse. This study employs a mixed-methods approach, including both qualitative and quantitative analyses. Initially, a systematic review of previous articles and research in the field of information security was conducted. Then, using the Delphi method, interviews with 30 information security experts were conducted to gather their insights on security challenges and solutions. Based on the results of these interviews, a comprehensive model for information security management was developed. The proposed model includes advanced encryption techniques, machine learning-based intrusion detection systems, and network security protocols. AES and RSA encryption algorithms were used for data protection, and machine learning models such as Random Forest and Neural Networks were utilized for intrusion detection. Statistical analyses were performed using SPSS software. To evaluate the effectiveness of the proposed model, T-Test and ANOVA statistical tests were employed, and results were measured using accuracy, sensitivity, and specificity indicators of the models. Additionally, multiple regression analysis was conducted to examine the impact of various variables on information security. The findings of this study indicate that the comprehensive proposed model reduced cyber-attacks by an average of 85%. Statistical analysis showed that the combined use of encryption techniques and intrusion detection systems significantly improves information security. Based on the obtained results, it is recommended that organizations continuously update their information security systems and use a combination of multiple security methods to protect their data. Additionally, educating employees and raising public awareness about information security can serve as an effective tool in reducing security risks. This research demonstrates that effective and up-to-date information security management requires a comprehensive and coordinated approach, including the development and implementation of advanced techniques and continuous training of human resources.

Keywords: data protection, digital technologies, information security, modern management

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Authors: Wing Mui Winnie So, Tian Luo, Zeyu Han

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To fully explore and develop the potentials of gifted students systematically and strategically by providing them with opportunities to receive education at appropriate levels, schools in Hong Kong are encouraged to adopt the "Three-Tier Implementation Model" to plan and implement the school-based gifted education, with Level Three refers to the provision of learning opportunities for the exceptionally gifted students in the form of specialist training outside the school setting by post-secondary institutions, non-government organisations, professional bodies and technology enterprises. Due to the growing concern worldwide about low interest among students in pursuing STEM (Science, Technology, Engineering, and Mathematics) careers, cultivating and boosting STEM career interest has been an emerging research focus worldwide. Although numerous studies have explored its critical contributors, little research has examined the effectiveness of comprehensive interventions such as “Studying with STEM professional”. This study aims to examine the effect on gifted students’ career interest during their participation in an off-school support programme designed and supervised by a team of STEM educators and STEM professionals from a university. Gifted students were provided opportunities and tasks to experience STEM career topics that are not included in the school syllabus, and to experience how to think and work like a STEM professional in their learning. Participants involved 40 primary school students joining the intervention programme outside the normal school setting. Research methods included adopting the STEM career interest survey and drawing tasks supplemented with writing before and after the programme, as well as interviews before the end of the programme. The semi-structured interviews focused on students’ views regarding STEM professionals; what’s it like to learn with a STEM professional; what’s it like to work and think like a STEM professional; and students’ STEM identity and career interest. The changes in gifted students’ STEM career interest and its well-recognised significant contributors, for example, STEM stereotypes, self-efficacy for STEM activities, and STEM outcome expectation, were collectively examined from the pre- and post-survey using T-test. Thematic analysis was conducted for the interview records to explore how studying with STEM professional intervention can help students understand STEM careers; build STEM identity; as well as how to think and work like a STEM professional. Results indicated a significant difference in STEM career interest before and after the intervention. The influencing mechanism was also identified from the measurement of the related contributors and the analysis of drawings and interviews. The potential of off-school support programme supervised by STEM educators and professionals to develop gifted students’ STEM career interest is argued to be further unleashed in future research and practice.

Keywords: gifted students, STEM career, STEM education, STEM professionals

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Authors: Abdul Basit Kiani

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Web development, the art of creating and maintaining websites, has witnessed remarkable advancements. The aim is to provide an overview of some of the cutting-edge developments in the field. Firstly, the rise of responsive web design has revolutionized user experiences across devices. With the increasing prevalence of smartphones and tablets, web developers have adapted to ensure seamless browsing experiences, regardless of screen size. This progress has greatly enhanced accessibility and usability, catering to the diverse needs of users worldwide. Additionally, the evolution of web frameworks and libraries has significantly streamlined the development process. Tools such as React, Angular, and Vue.js have empowered developers to build dynamic and interactive web applications with ease. These frameworks not only enhance efficiency but also bolster scalability, allowing for the creation of complex and feature-rich web solutions. Furthermore, the emergence of progressive web applications (PWAs) has bridged the gap between native mobile apps and web development. PWAs leverage modern web technologies to deliver app-like experiences, including offline functionality, push notifications, and seamless installation. This innovation has transformed the way users interact with websites, blurring the boundaries between traditional web and mobile applications. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) has opened new horizons in web development. Chatbots, intelligent recommendation systems, and personalization algorithms have become integral components of modern websites. These AI-powered features enhance user engagement, provide personalized experiences, and streamline customer support processes, revolutionizing the way businesses interact with their audiences. Lastly, the emphasis on web security and privacy has been a pivotal area of progress. With the increasing incidents of cyber threats, web developers have implemented robust security measures to safeguard user data and ensure secure transactions. Innovations such as HTTPS protocol, two-factor authentication, and advanced encryption techniques have bolstered the overall security of web applications, fostering trust and confidence among users. Hence, recent progress in web development has propelled the industry forward, enabling developers to craft innovative and immersive digital experiences. From responsive design to AI integration and enhanced security, the landscape of web development continues to evolve, promising a future filled with endless possibilities.

Keywords: progressive web applications (PWAs), web security, machine learning (ML), web frameworks, advancement responsive web design

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Authors: Ruchi Agarwal, Jake Ansell

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Austerity impacts on all aspects of society. Companies into the future will have to be more capable of dealing with the risks they face. Enterprise Risk Management (ERM) has widely been accepted in recent years as an approach to manage risks within businesses. ERM attempts to tackle risk holistically with gains from opportunities in a managing risk and reduction in the risk of failure. The paper reviews merits and demerits of approaches to risk management in regard to antifragility. A qualitative study has investigated current practices and the problems with ERM implementation by interviewing over 25 chief risk officers and senior management. The findings indicate the gap in ERM description, understanding, and implementation. The paper suggests risk learning and expertise knowledge supports development of effective enterprise risk management by designing systems with inherent resilience.

Keywords: risk management, interviews, antifragility, failure

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Authors: Isaac Makundi, Kazuo Nishigaki

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The Tsushima leopard cat (TLC) Prionailurus bengalensis euptilurus, designated a National Natural Monument of Japan, inhabits Tsushima Island, Nagasaki Prefecture, Japan. TLC is considered a subspecies of P. bengalensis, and lives only on Tsushima Island. TLCs are threatened by various infectious diseases. Feline leukemia virus (FeLV) causes a serious infectious disease with a poor prognosis in cats. Therefore, the transmission of FeLV from Tsushima domestic cats (TDCs) to TLCs may threaten the TLC population. We investigated the FeLV infection status of both TDCs and TLCs on Tsushima Island by screening blood samples for FeLV p27 antigen and using PCR to amplify the full-length FeLV env gene. The prevalence of FeLV was 6.4% in TDCs and 0% in TLCs. We also demonstrated that the virus can replicate in the cells of TLCs, suggesting its potential cross-species transmission. The viruses in TDCs were classified as genotype I/clade 3, which is prevalent on a nearby island, based on previous studies of FeLV genotypes and FeLV epidemiology. The FeLV viruses identified on Tsushima Island can be further divided into two lineages within genotype I/clade 3, which are geographically separated in Kamijima and Shimojima, indicating that FeLV may have been transmitted to Tsushima Island at least twice. Monitoring FeLV infection in the TDC and TLC populations is highly recommended as part of the TLC surveillance and management strategy.

Keywords: epidemiology, Feline leukemia virus, Tsushima Island, wildlife management

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Authors: Yayun Hsu, Henry Horng-Shing Lu

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This paper proposes a data-driven, biology-inspired neural segmentation method of 3D drosophila Brainbow images. We use Bayesian Sequential Partitioning algorithm for probabilistic modeling, which can be used to detect somas and to eliminate cross talk effects. This work attempts to develop an automatic methodology for neuron image segmentation, which nowadays still lacks a complete solution due to the complexity of the image. The proposed method does not need any predetermined, risk-prone thresholds since biological information is inherently included in the image processing procedure. Therefore, it is less sensitive to variations in neuron morphology; meanwhile, its flexibility would be beneficial for tracing the intertwining structure of neurons.

Keywords: brainbow, 3D imaging, image segmentation, neuron morphology, biological data mining, non-parametric learning

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Authors: Nan Deng, Zhenqiu Liu

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Thousands of patients with metastatic tumors were diagnosed with cancers of unknown primary sites each year. The inability to identify the primary cancer site may lead to inappropriate treatment and unexpected prognosis. Nowadays, a large amount of genomics and transcriptomics cancer data has been generated by next-generation sequencing (NGS) technologies, and The Cancer Genome Atlas (TCGA) database has accrued thousands of human cancer tumors and healthy controls, which provides an abundance of resource to differentiate cancer types. Meanwhile, deep convolutional neural networks (CNNs) have shown high accuracy on classification among a large number of image object categories. Here, we utilize 25 cancer primary tumors and 3 normal tissues from TCGA and convert their RNA-Seq gene expression profiling to color images; train, validate and test a CNN classifier directly from these images. The performance result shows that our CNN classifier can archive >80% test accuracy on most of the tumors and normal tissues. Since the gene expression pattern of distant metastases is similar to their primary tumors, the CNN classifier may provide a potential computational strategy on identifying the unknown primary origin of metastatic cancer in order to plan appropriate treatment for patients.

Keywords: bioinformatics, cancer, convolutional neural network, deep leaning, gene expression pattern

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Authors: Basma Khelfa, Antoine Tordeux, Ibrahima Ba

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We present a descriptive analysis data of lane-changing events in multi-lane roads. The data are provided from The Highway Drone Dataset (HighD), which are microscopic trajectories in highway. This paper describes and analyses the role of the different parameters and their significance. Thanks to HighD data, we aim to find the most frequent reasons that motivate drivers to change lanes. We used the programming language R for the processing of these data. We analyze the involvement and relationship of different variables of each parameter of the ego vehicle and the four vehicles surrounding it, i.e., distance, speed difference, time gap, and acceleration. This was studied according to the class of the vehicle (car or truck), and according to the maneuver it undertook (overtaking or falling back).

Keywords: autonomous driving, physical traffic model, prediction model, statistical learning process

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Authors: Renz Paolo B. Ramos, Jake S. Espina

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The Local Government Academy of the Philippines explains that Local legislation is both a power and a process by which it enacts ordinances and resolutions that have the force and effect of law while engaging with a range of stakeholders for their implementation. Legislative effectiveness is crucial for the development of any given area. This study's objective is to evaluate the legislative performance of the 10th Sangguniang of Kawayan, a legislative body in a fifth-class municipality in the Province of Biliran, during the height of the COVID-19 pandemic (2019-2021) with a focus on legislation, accountability, and participation, institution-building, and intergovernmental relations. The aim of the study was that a mixed-methods strategy was used to gather data. The Local Legislative Performance Appraisal Form (LLPAF) was completed, while Focus Interviews for Local Government Unit (LGU) personnel, a survey questionnaire for constituents, and ethnographic diary-writing were conducted. Convenience Sampling was utilized for LGU workers, whereas Simple Random Sampling was used to identify the number of constituents participating. Interviews were analyzed using thematic analysis, while frequency data analysis was employed to describe and evaluate the nature and connection of the data to the underlying population. From this data, the researchers draw opportunities and challenges met by the local legislature during the height of the pandemic.

Keywords: local legislation, local governance, legislative effectiveness, legislative analysis

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Authors: Lisseth Rojas Barreto, Carlos Muñoz Hernández

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The COVID-19 pandemic led to many abrupt changes, including a prolonged lockdown, which brought about work and personal challenges to the population worldwide. Among the most affected populations are women who are workers and housewives at the same time, and especially those who are also parenting. These women were faced with the challenge to perform their usual varied roles during the lockdown from the same physical space, which inevitably had strong repercussions for each of them. This paper will present some results of a research study whose main objective was to examine the possible effects that the COVID-19 pandemic lockdown may have caused in the work, social, family, and personal environments of female English teachers who are also housewives and, by extension in the teaching and learning processes that they lead. Participants included five female English language teachers of a public foreign language school, they are all married, and two of them have children. Similarly, we examined some of the coping strategies these teachers used to tackle the pandemic-related challenges in their different roles, especially those used for their language teaching role; coping strategies are understood as a repertoire of behaviors in response to incidents that can be stressful for the subject, possible challenging events or situations that involve emotions with behaviors and decision-making of people which are used in order to find a meaning or positive result (Lazarus &Folkman, 1986) Following a qualitative-case study design, we gathered the data through a survey and a focus group interview with the participant teachers who work at a public language school in southern Colombia. Preliminary findings indicate that the circumstances that emerged as a result of the pandemic lockdown affected the participants in different ways, including financial, personal, family, health, and work-related issues. Among the strategies that participants found valuable to deal with the novel circumstances, we can highlight the reorganization of the household and work tasks and the increased awareness of time management for the household, work, and leisure. Additionally, we were able to evidence that the participants faced the circumstances with a positive view. Finally, in order to cope with their teaching duties, some participants acknowledged their lack of computer or technology literacy in order to deliver their classes online, which made them find support from their students or more knowledgeable peers to cope with it. Others indicated that they used strategies such as self-learning in order to get acquainted and be able to use the different technological tools and web-based platforms available.

Keywords: coping strategies, language teaching, female teachers, pandemic lockdown

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Authors: Sarah Mohammed, Huda Allagany, Ayah Barakat, Muna Elyas

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This paper delves into the history and development of ChatGPT, tracing its evolution from its inception by OpenAI to its current state, and emphasizing its design improvements and strategic partnerships. It also explores the performance and applicability of ChatGPT versions 3.5 and 4 in various contexts, examining its capabilities and limitations in producing accurate and relevant responses. Utilizing a quantitative approach, user satisfaction, speed of response, learning capabilities, and overall utility in academic performance were assessed through surveys and analysis tools. Findings indicate that while ChatGPT generally delivers high accuracy and speed in responses, the need for clarification and more specific user instructions persists. The study highlights the tool's increasing integration across different sectors, showcasing its potential in educational and professional settings.

Keywords: artificial intelligence, chat GPT, analysis, education

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Authors: Aminah Muchdar, Nuraeni, Eddy

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The aims of the research are: (1) to verify the cropsyst plant model of experimental data in the field of soybean plants and (2) to predict planting time and potential yield soybean plant with the use of cropsyst model. This research is divided into several stages: (1) first calibration stage which conducted in the field from June until September 2015.(2) application models stage, where the data obtained from calibration in the field will be included in cropsyst models. The required data models are climate data, ground data/soil data,also crop genetic data. The relationship between the obtained result in field with simulation cropsyst model indicated by Efficiency Index (EF) which the value is 0,939.That is showing that cropsyst model is well used. From the calculation result RRMSE which the value is 1,922%.That is showing that comparative fault prediction results from simulation with result obtained in the field is 1,92%. The conclusion has obtained that the prediction of soybean planting time cropsyst based models that have been made valid for use. and the appropriate planting time for planting soybeans mainly on rain-fed land is at the end of the rainy season, in which the above study first planting time (June 2, 2015) which gives the highest production, because at that time there was still some rain. Tanggamus varieties more resistant to slow planting time cause the percentage decrease in the yield of each decade is lower than the average of all varieties.

Keywords: soybean, Cropsyst, calibration, efficiency Index, RRMSE

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Authors: Mariana Volpini, Volker Bartenbach, Marcos Pinotti, Robert Riener

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Restoration of gait ability is an important task in the rehabilitation of people with neurological disorders presenting a great impact in the quality of life of an individual. Based on the motor learning concept, robotic assisted treadmill training has been introduced and found to be a feasible and promising therapeutic option in neurological rehabilitation but unfortunately it is not available for most patients in developing countries due to the high cost. This paper presents the concept of a low cost rehabilitation robot to help consolidate the robotic-assisted gait training as a reality in clinical practice in most countries. This work indicates that it is possible to build a simpler rehabilitation device respecting the physiological trajectory of the ankle.

Keywords: bioengineering, gait therapy, low cost rehabilitation robot, rehabilitation robotics

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Authors: Qi Wang

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Accurate pronunciation is the first condition of communication. Compared with the alphabetic languages, Chinese is more difficult for the foreigners to study as a second language, due to the tonal language with the meaningful characters as the written system, especially speaking. This research first presents the statistics of the typical errors of the pronunciations, based on the data of our two- year program of graduate students, which shown 90% of their speaking with strong foreign accents and no obvious change of the pitches, even if they could speak Chinese fluently. Second part, analyzed the caused reasons in the learning and teaching processes. Third part, this result of this research, based the theory of Chinese prosodic words, shown that the earlier the students get trained on prosodics at the beginning and suprasegmentals at intermediate and advanced levels, the better effects for them to communicate in Chinese as a second language.

Keywords: second language, prosodic word, foot, suprasegmental

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Authors: Ishani Das, Avinash Padhi, Sitabja Mukherjee, Santosh Kar, Avinash Sonawane

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Activation of cell mediated and humoral immune responses to Mycobacterium tuberculosis (Mtb) are critical for protection. Herein, we show that mice immunized with Mtb lipid bound chitosan nanoparticles(NPs) induce secretion of prominent Th1 and Th2 cytokines in lymph node and spleen cells, and also induced significantly higher levels of IgG, IgG1, IgG2 and IgM in comparison to control mice measured by ELISA. Furthermore, significantly enhanced γδ-T cell activation was observed in lymph node cells isolated from mice immunized with Mtb lipid coated chitosan-NPs as compared to mice immunized with chitosan-NPs alone or Mtb lipid liposomes through flow cytometric analysis. Also, it was observed that in comparison to CD8+ cells, significantly higher CD4+ cells were present in both the lymph node and spleen cells isolated from mice immunized with Mtb lipid coated chitosan NP. In conclusion, this study represents a promising new strategy for efficient delivery of Mtb lipids using chitosan NPs to trigger enhanced cell mediated and antibody response against Mtb lipids.

Keywords: antibody response, chitosan nanoparticles, cytokines, mycobacterium tuberculosis lipids

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Authors: Hendrik Bernard Van Der Walt, Frik Van Niekerk

Abstract:

Fuel models render a reduction in BOL when thorium is added to a reactor core. Thorium emulates the role of a fertile poison, and is beneficial for reducing beginning of cycle (BOC) excess reactivity. In spite of the build-up of 233U over the duration of a fuel cycle, the effects of fuel reloading have a significant impact on fuel viability, especially in the case of heterogeneous thorium-based fuels. The most common practice of compensating for the reduction of BOC reactivity is the addition of fissile isotopes (uranium fuel with increased enrichment or plutonium). This study introduces a heterogeneous thorium-based fuel with minimal fissile isotope additions. A pseudo reloading scheme was developed for numerical simulations of an infinite reactor based on the North-Anna 1 reactor operating in Virginia, USA. Use of this reloading pattern allows new thorium-based fuel to be loaded into the reactor model as part of a phasing in strategy at the end of any conventional reactor cycle. Results demonstrate the effects of thorium-based fuel on fuel cycle characteristics such as fuel cycle length, neutron economy and material matrix. Application of the above mentioned approach delivered promising results and presents a heterogeneous thorium-based fuel which could replace conventional fuel of typical, currently operating (or future) reactors without the need for expensive reactor redesign or fuel recycling strategies.

Keywords: nuclear fuel, nuclear characteristics, nuclear fuel cycle, thorium-based fuel, heterogeneous design, fuel reloading

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Authors: Chananporn Areekul

Abstract:

The purpose of this study was to study the experimental result of using board games for enhancing the active citizen of the undergraduate students. The research methodology of this study was the quasi experimental research. The sample was 30 undergraduate students that were chosen by the purposive sampling. The instruments were board games for enhancing the active citizen and the questionnaire for measuring the active citizen levels. The result of the mean difference test was found that there were statistically significant differences at the .05 level (t = 2.028, p = 0.047) between before and after using board game for enhancing the active citizen of undergraduate students.

Keywords: active citizen, board game, learning innovation, undergraduate students

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Authors: Yi-ju Ariel Wu

Abstract:

Exploring The Effects of Immersive Virtual Reality on Increasing Willingness to Communicate, Oral Performance, and Reducing Speaking Anxiety for EFL Elementary Students from Taiwan

Keywords: Immersive Virtual Reality, EFL speaking, situated learning, pragmatics

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Authors: Pin-Hua Chou

Abstract:

MACAN (Museum of Modern and Contemporary Art in Nusantara) is a new private art museum in Jakarta, Indonesia. Facing challenges of rapidly changing social, cultural environments, MACAN is responding by devoting themselves to not only presenting famous international artists but also constructing the context of artists from Indonesia by interdisciplinary education and cultural exchange. This paper discusses the exhibitions, collections and the activities of MACAN. The purpose of this museum is to make people aware of the dialogue between local and international artist, and also Indonesia’s own art history. Yet how they build up the cultural consciousness for their audience inside and outside Indonesia? What strategy or method do they adapt to enhance general understanding of their own history and the relation between Indonesia and the world through their exhibition? MACAN has tried to convey their mission by every action they took since its opening (2017). The discussion begins with the premise that the initiative of MACAN offers us a new vision to better understand how a modern and contemporary art museum can make an effort to connect art with cultural identity and stimulate the awareness of recognition in Indonesia. This paper will adopt a case study, curator interview, and document analysis. Last but not least, the paper seeks to contribute towards the narrative of its first exhibition Art Turns, World Turns, Exploring the collection of the MACAN, as well as the possibility of raising audience’s cultural consciousness by a variety of public programs.

Keywords: contemporary art museum, challenges for art museum curators today, culture heritage, museum collections and exhibitions

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Authors: Dai Yizheng, Chen-Yang Zhang

Abstract:

As station-city integration has been widely accepted as a strategy for mixed-use development, a quantitative analysis of the functional characteristics of urban complexes based on station-city integration is urgently needed. Taking 15 railway stations in European, North American, and East Asian cities as the research objects, this study analyzes their functional proportion, functional positioning, and functional correlation with respect to four categories of functional facilities for both railway passenger flow and subway passenger flow. We found that (1) the functional proportion of urban complexes was mainly concentrated in three models: complementary, dominant, and equilibrium. (2) The mathematical model affected by the functional proportion was created to evaluate the functional positioning of an urban complex at three scales: station area, city, and region. (3) The strength of the correlation between the functional area and passenger flow was revealed via data analysis using Pearson’s correlation coefficient. Finally, the findings of this study provide a valuable reference for research on similar topics in other countries that are developing station-city integration.

Keywords: urban complex, station-city integration, mixed-use, function, quantitative analysis

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