Contribution Of Research Research Articles

The Difference of Cognitive Ability under Different Levels of Emotion Regulation under Stress

What will people react and respond when they are facing a stressful environment and a uncomfortable place. Will they react differently when they are facing interference than others who work at a normal environment? Research purpose refers to the starting point and direct intention of scientific research. The purpose of the study not only explains the reason of the study, but also points out the direction and focus of the study. The correct research purpose can help researchers better grasp the research direction, avoid blind exploration, and improve the efficiency and accuracy of research. Research significance refers to the contribution of research results to practice, theory, method and so on. Research significance can be divided into practical significance and theoretical significance. Practical significance refers to the guiding effect of research results on practice, which can provide reference and guidance for practice. Theoretical significance refers to the contribution of research results to the theory, which can provide support for the development and improvement of the theory. So, this research is important for author.

Analyzing the Merits and Drawbacks of Multilingual Text Detection Datasets for Videos

In recent years, video contents have observed a massive growth with online lecture, news channels, and media contents and with short clips. These contents have objects, texts in them. The majority of the time, multilingual datasets are not available as per the need and have to utilize YouTube videos with multiple languages as a source . This study proposes a systematic structure for the generation of multilingual datasets and explains the purpose for their creation. Additionally, the study demonstrated the difficulties in creating the data set, like segregating data that is multilingual, etc. Lastly, discusses the effects of creating multilingual datasets because of various difficulties. As a result, the research's contribution is the multilingual dataset that was created using the suggested systematic structure, which also practically shows its limitations and benefits. Key Words:, Data Set, Multilingual, Text detection, challenge, consequences

Effectiveness of Occupational Safety and Health interventions: a long way to go

BackgroundOccupational Safety and Health (OSH) has become an area of increasing concern for organizations and institutions. As it evolves, it has gradually posed ongoing challenges, becoming more complex, for organizations. Consequently, more comprehensive studies are required to advance academic and institutional research. From this perspective, this study aims to gather research contributions on the effectiveness of existing interventions for OSH improvement and identify areas for further exploration.MethodsAccording to the nature of scientific literature, the overall process of a literature review was investigated following an integrative approach, which involved searching for, selecting, and analyzing various literature in a creative and integrated manner, without a predefined structure.ResultsThe analysis suggests that there is room for improvement in understanding the effectiveness of OSH interventions and more concrete guidance is still desirable. Based on the literature, some research areas for future developments in OSH interventions are identified. One potential area to explore further is fostering human-centered technological development and a more conscious network of stakeholders, with higher coordination, shared knowledge, and open communication.ImplicationsFocusing on the proposed directions will support scholars and practitioners in pursuing continuous OSH improvement through more effective and well-grounded workplace interventions and encourage organizations to be proactive in daily OSH management.

Revolutionizing Maritime Trade: Unveiling The Innovative Sea Toll Framework Through Advanced Livestock Folding Container Ship Science Mapping

Objective: This study aims to trace the evolution of literature concerning sea tolls and livestock folding containers from 2014 to 2023, focusing on understanding research trends, sources, influential countries, author contributions, and major research areas. Method: Utilizing the Crossref database, the study collected 1000 relevant publications related to sea tolls and livestock folding containers. A science mapping approach, assisted by VOSviewers, was employed for analysis. Research Findings and Discussions: The analysis revealed several key findings. Firstly, it identified the emergence of sea tolls and livestock folding containers as significant research areas, indicating their growing importance. Secondly, the study identified dominant research topics and areas of interest, categorized into frequent, moderate, and rare levels. Additionally, it highlighted influential countries and sources contributing to the literature in this field. Furthermore, the study provided insights into author contributions and collaboration patterns, shedding light on the collaborative nature of research in this domain. Research Implications: This study provides a comprehensive roadmap of current research directions in the fields of sea tolls and livestock folding containers. The findings of this study can guide future research endeavors, facilitate interdisciplinary collaboration, and inform policy decisions aimed at enhancing maritime transportation and economic development. Originality/Value: The significance of this study lies in its comprehensive analysis of literature related to sea tolls and livestock folding containers, spanning a decade from 2014 to 2023. By employing a science mapping approach, the study offers a systematic overview of research trends and contributions in this field.

Emigration and fiscal gap in population-exporting region.

This paper analyzes how emigration impacts fiscal gap of population-exporting region in the long term. We construct a general equilibrium model of emigration and fiscal gap and make empirical verification using two-step system GMM model. Among the major lessons from this work, five general and striking results are worth highlighting: (1) the economic losses of emigration are the immediate cause of widening the fiscal gap. (2) in the short and long term, emigration can expand the fiscal revenue gap through the superimposed effect of tax rate and tax base. (3) the gap in fiscal expenditure is widened by the outflow of people in the short term. However, local governments would change the strategy to keep the spending gap from widening in the long run. (4) a positive impact of emigration on the fiscal gap. the more severe population emigration, the larger the fiscal gap. (5) when the trend of emigration becomes irreversible, the subsequent efforts of local governments to expand fiscal expenditure for attraction population would not only fail to revive the regional economy, but aggravate the expansion of fiscal gap. The contribution of research is twofold. On the one hand, it fills the theoretical gap between emigration and fiscal gap because previous studies have paid little attention to the fiscal problems of local government of population outflow. On the other hand, the selection of Northeast China that has been subject to long-term out-of-population migration is good evidence to verify this theory, which is tested very well using the 2S-GMM model. The comprehensive discussion on the relationship between emigration and fiscal gap is helpful to guide those continuous population-exporting regions that are facing a huge fiscal gap how to solve the fiscal gap and unsustainability from the perspective of fiscal revenue and expenditure.

Dissemination innovation: Using found poetry to return study results to patients and partners facing cancer

ObjectiveInvestigators should return study results to patients and families facing cancer to honor their research contributions. We created a found poem from transcripts of sexual and gender minority (SGM) couples facing cancer and returned it to study participants. MethodsParticipants were randomized to receive the found poem in text, text and audio, audio, or video format, completed dissemination preferences and emotion questionnaires, and open-ended questions about their experience receiving the poem. ResultsParticipants preferred the format they received (n = 15, 75.0%), with text-only and combined text and audio formats evoking the greatest number of emotions (n = 13 each). The following categories and subcategories were identified: dyadic experiences (support, strength, depth, durability); dissemination preferences (timing, method); emotion (positive, negative); utility of the found poem (affirming; fostering reflection; not useful or inaccurate, and sense of community). SGM participants utilized positive emotion, affirming, and a sense of community with greater frequency than non-SGM participants. ConclusionInnovative approaches to dissemination are acceptable; providing choices in how and when participants receive results may increase engagement; and SGM versus non-SGM groups may describe dyadic experiences differently. InnovationReturning study results via found poetry is an innovative way to honor research participants facing cancer.

Examining the Influence of AI Chatbots on Semantic Web-Based Global Information Management in Various Industries

This article presents a comprehensive analysis of the application and effect of ChatGPT, an advanced AI chatbot model, on global information management across various industries such as healthcare, industry, education, and more. Leveraging a dataset obtained from the Scopus database encompassing research papers from 2022 to 2023, this study investigates the influence of ChatGPT by examining publisher impact, authorship patterns based on Lotka's Law, country-specific scientific production, and keyword distribution. The analysis sheds light on prominent publishers, prolific authors, geographic distribution of research contributions, and prevailing research themes. By understanding the impact of ChatGPT in these sectors, this research contributes to the advancement of knowledge and facilitates informed decision-making regarding the responsible and effective utilization of artificial intelligence (AI) chatbot technologies in global information management.

Computer vision digitization of smartphone images of anesthesia paper health records from low-middle income countries

BackgroundIn low-middle income countries, healthcare providers primarily use paper health records for capturing data. Paper health records are utilized predominately due to the prohibitive cost of acquisition and maintenance of automated data capture devices and electronic medical records. Data recorded on paper health records is not easily accessible in a digital format to healthcare providers. The lack of real time accessible digital data limits healthcare providers, researchers, and quality improvement champions to leverage data to improve patient outcomes. In this project, we demonstrate the novel use of computer vision software to digitize handwritten intraoperative data elements from smartphone photographs of paper anesthesia charts from the University Teaching Hospital of Kigali. We specifically report our approach to digitize checkbox data, symbol-denoted systolic and diastolic blood pressure, and physiological data.MethodsWe implemented approaches for removing perspective distortions from smartphone photographs, removing shadows, and improving image readability through morphological operations. YOLOv8 models were used to deconstruct the anesthesia paper chart into specific data sections. Handwritten blood pressure symbols and physiological data were identified, and values were assigned using deep neural networks. Our work builds upon the contributions of previous research by improving upon their methods, updating the deep learning models to newer architectures, as well as consolidating them into a single piece of software.ResultsThe model for extracting the sections of the anesthesia paper chart achieved an average box precision of 0.99, an average box recall of 0.99, and an mAP0.5-95 of 0.97. Our software digitizes checkbox data with greater than 99% accuracy and digitizes blood pressure data with a mean average error of 1.0 and 1.36 mmHg for systolic and diastolic blood pressure respectively. Overall accuracy for physiological data which includes oxygen saturation, inspired oxygen concentration and end tidal carbon dioxide concentration was 85.2%.ConclusionsWe demonstrate that under normal photography conditions we can digitize checkbox, blood pressure and physiological data to within human accuracy when provided legible handwriting. Our contributions provide improved access to digital data to healthcare practitioners in low-middle income countries.

Special Collection: Holistic Development of Electrochemical Processes for Industrial Systems

AbstractThis special collection is dedicated to the field of application‐oriented electrochemical processes and contains a diverse selection of original research contributions in this field. It reaches from a fundamental electrochemical understanding, over catalyst material development, to engineering technology. With this Special Collection key factors in energy transition processes are highlighted and emerging research topics to enable scale‐up from lab‐based fundamental research to industrial‐level system integration are showcased.

Editorial: COVID-19 pandemic and the social determinants of health

As we learn to co-exist with COVID-19, this Research Topic highlights significant research contributions that examine the interaction of COVID-19 and the social determinants of health. To emphasize the impactful research in this area, this Research Topic features scholarly contributions in the fields of Epidemiology, specifically Aging and Life-course Epidemiology, and Public Health, specifically Public Health Policy. This theme is intentionally broad in scope, and our editorial provides an overview of the key findings of the papers published in the Research Topic on COVID-19 pandemic and the social determinants of health. The types of articles received in response to this Research Topic are summarized below.

Systematic challenges and opportunities in insect monitoring: a Global South perspective.

Insect monitoring is pivotal for assessing biodiversity and informing conservation strategies. This study delves into the complex realm of insect monitoring in the Global South-world developing and least-developed countries as identified by the United Nations Conference on Trade and Development-highlighting challenges and proposing strategic solutions. An analysis of publications from 1990 to 2024 reveals an imbalance in research contributions between the Global North and South, highlighting disparities in entomological research and the scarcity of taxonomic expertise in the Global South. We discuss the socio-economic factors that exacerbate the issues, including funding disparities, challenges in collaboration, infrastructure deficits, information technology obstacles and the impact of local currency devaluation. In addition, we emphasize the crucial role of environmental factors in shaping insect diversity, particularly in tropical regions facing multiple challenges including climate change, urbanization, pollution and various anthropogenic activities. We also stress the need for entomologists to advocate for ecosystem services provided by insects in addressing environmental issues. To enhance monitoring capacity, we propose strategies such as community engagement, outreach programmes and cultural activities to instill biodiversity appreciation. Further, language inclusivity and social media use are emphasized for effective communication. More collaborations with Global North counterparts, particularly in areas of molecular biology and remote sensing, are suggested for technological advancements. In conclusion, advocating for these strategies-global collaborations, a diverse entomological community and the integration of transverse disciplines-aims to address challenges and foster inclusive, sustainable insect monitoring in the Global South, contributing significantly to biodiversity conservation and overall ecosystem health. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Preface

Greetings and a warm welcome to the expansive compilation of research and scholarly contributions presented in the Proceedings of the ICEMINE 2023. In the spirit of intellectual exploration and collaboration, this voluminous collection encapsulates the diverse and profound discussions that unfolded during the conference. As we delve into the following pages, readers will encounter a comprehensive exploration of knowledge, innovation, and interdisciplinary collaboration within the overarching theme of ICEMINE 2023.ICEMINE 2023 is the 6th International Conference hosted by the Faculty of Mineral Technology, Universitas Pembangunan Nasional “Veteran” Yogyakarta, Indonesia. The conference was held at Grand Keisha Hotel, Yogyakarta, Indonesia, on the 9th of November 2023. The theme of this year’s program is “Accelerating the advancements in lower carbon energy for a sustainable environment”. We extend our appreciation to our esteemed partner university, whose unwavering dedication and scholarly contributions have significantly enriched the contents of this conference proceedings. In collaboration with our partner universities, Trisakti University and PEM Akamigas, UPN Veteran Yogyakarta creates an academic platform that fosters diverse perspectives, innovative ideas, and interdisciplinary exchange. Their insightful research and collaborative spirit have undeniably elevated the quality of discourse within our academic community, fostering an environment conducive to intellectual growth and innovation.Furthermore, we would like to express our profound gratitude to our sponsors, whose generous support has been pivotal in bringing this event to success. Their unwavering commitment to advancing research and cultivating intellectual exchange underscores the importance of their role in shaping the trajectory of our academic disciplines.List of Reflecting on Sustainability in Indonesia, Navigating the future: a vision for what lies ahead, Steering Committee, Organizing Committee, Scientific Committee, Keynote Speakers and Best Presenters are available in this Pdf.

Leveraging sentiment analysis of Arabic Tweets for the 2022 FIFA World Cup insights, incorporating the gulf region

ABSTRACT Purpose The study analyzes Arabic Tweets, with a focus on those originating from the Gulf Cooperation Council (GCC) region, to examine public perceptions of the 2022 FIFA World Cup. Methodology Twitter’s search API was utilized to gather a substantial dataset of 157,756 tweets collected from 1 October 2022, to 1 January 2022. After data cleaning, a refined dataset of 43,658 tweets, was categorized into positive, neutral, and negative sentiments based on sentiment scores. Findings Arabic tweets, initially held a positive sentiment towards the World Cup, which increased during the tournament, accompanied by a decrease in negative sentiment. Research contribution This study offers valuable insights into public sentiment regarding the 2022 FIFA World Cup among Arabic-speaking Twitter users, with a particular emphasis on those from the GCC region. Additionally, it lends support to FIFA's decision to host the event in the Arab World by highlighting the favorable public reception. Originality This research's originality lies in its examination of the transformation in public sentiment within the Arabic-speaking community throughout the 2022 FIFA World Cup. These insights hold the potential to inform future decisions related to the hosting of major sporting events, providing a unique perspective on the evolving dynamics of sentiment within this demographic.

Insights into leadership practices in South African Higher Education

Insights into leadership practices in South African Higher Education

Managing safety of the human on the factory floor: a computer vision fusion approach

PurposeMaintaining the safety of the human is a major concern in factories where humans co-exist with robots and other physical tools. Typically, the area around the robots is monitored using lasers. However, lasers cannot distinguish between human and non-human objects in the robot’s path. Stopping or slowing down the robot when non-human objects approach is unproductive. This research contribution addresses that inefficiency by showing how computer-vision techniques can be used instead of lasers which improve up-time of the robot.Design/methodology/approachA computer-vision safety system is presented. Image segmentation, 3D point clouds, face recognition, hand gesture recognition, speed and trajectory tracking and a digital twin are used. Using speed and separation, the robot’s speed is controlled based on the nearest location of humans accurate to their body shape. The computer-vision safety system is compared to a traditional laser measure. The system is evaluated in a controlled test, and in the field.FindingsComputer-vision and lasers are shown to be equivalent by a measure of relationship and measure of agreement. R2 is given as 0.999983. The two methods are systematically producing similar results, as the bias is close to zero, at 0.060 mm. Using Bland–Altman analysis, 95% of the differences lie within the limits of maximum acceptable differences.Originality/valueIn this paper an original model for future computer-vision safety systems is described which is equivalent to existing laser systems, identifies and adapts to particular humans and reduces the need to slow and stop systems thereby improving efficiency. The implication is that computer-vision can be used to substitute lasers and permit adaptive robotic control in human–robot collaboration systems.

Remembering Jan Amesz (1934-2001): a great gentleman, a major discoverer, and an internationally renowned biophysicist of both oxygenic and anoxygenic photosynthesisa.

We present here the research contributions of Jan Amesz (1934-2001) on deciphering the details of the early physico-chemical steps in oxygenic photosynthesis in plants, algae and cyanobacteria, as well as in anoxygenic photosynthesis in purple, green, and heliobacteria. His research included light absorption and the mechanism of excitation energy transfer, primary photochemistry, and electron transfer steps until the reduction of pyridine nucleotides. Among his many discoveries, we emphasize his 1961 proof, with L. N. M. Duysens, of the "series scheme" of oxygenic photosynthesis, through antagonistic effects of Light I and II on the redox state of cytochrome f. Further, we highlight the following research on oxygenic photosynthesis: the experimental direct proof that plastoquinone and plastocyanin function at their respective places in the Z-scheme. In addition, Amesz's major contributions were in unraveling the mechanism of excitation energy transfer and electron transport steps in anoxygenic photosynthetic bacteria (purple, green and heliobacteria). Before we present his research, focusing on his key discoveries, we provide a glimpse of his personal life. We end this Tribute with reminiscences from three of his former doctoral students (Sigi Neerken; Hjalmar Pernentier, and Frank Kleinherenbrink) and from several scientists (Suleyman Allakhverdiev; Robert Blankenship; Richard Cogdell) including two of the authors (G. Garab and A. Stirbet) of this Tribute.

Intellectual capital information via Twitter: the effect on firm value

PurposeSocial media are emerging as the ideal channel for building one-to-many communication and disseminating intellectual capital (IC) information. Their rise is bringing out new research challenges to investigate the implications of their use. However, there needs to be more research contributions relating to the financial benefits of using social media for IC disclosure (ICD). This study aims to bridge this gap by analyzing, under the lens of signaling theory, the effect of ICD through Twitter on firm value.Design/methodology/approachThis study is based on a content analysis of tweets disseminated by 262 companies aimed at examining the amount of IC information disclosed and on a regression analysis aimed at analyzing the impact of this type of information on firm value.FindingsEmpirical results show that a large ICD via Twitter favors an increase in firm value. They also demonstrate that disclosing information relating to the three IC dimensions positively affects the firm value. These findings suggest that actively and comprehensively communicating IC information via Twitter can help improve the perception and evaluation of the company by investors and other stakeholders.Research limitations/implicationsThis study offers empirical evidence about the financial benefits associated with using social media as disclosure tools by companies. It also enriches the literature on the relationship between ICD and firm value and consolidates the goodness of the signaling theory as an ideal theoretical perspective to frame the relationship between IC information and firm value.Practical implicationsThis study offers important managerial implications for firms and investors. In light of the significant financial benefits, firms should use social media to disclose IC information and should seek to increase their visibility on such platforms to convey the information to a greater number of users. Investors should also heed social media when gathering IC information, combining the analysis of these platforms with that of traditional corporate documents.Originality/valueThis study enriches the limited literature on ICD via social media and extends knowledge about the relationship between IC information and firm value. In this regard, the originality also lies in the individual analysis of the impact of the three IC dimensions on firm value.

Economic Fraud and Associated Risks: An Integrated Bibliometric Analysis Approach

This study offers a comprehensive insight into the realms of economic fraud and risk management, underscoring the necessity of adaptability to evolving technologies and shifts in financial market dynamics. Through the application of bibliometric methodologies, this study meticulously maps the relevant literature, delineating influential works, notable authors, collaborative networks, and emerging trends. It reviews key research contributions within the field, alongside reputable journals and institutions engaged in academic research. The examination highlights the logical, conceptual, and social interconnections that define the landscape of economic fraud and associated risks, elucidating how these findings inform the understanding, mitigating, and combating of the risk of fraud. Our bibliometric analysis methodology is grounded in the utilization of the Scopus database, employing rigorous filtering and extraction processes to obtain a substantial corpus of pertinent articles. Through a fusion of performance analysis and science mapping, our investigation elucidates central themes and visually represents the interrelationships between studies. Our research outcomes underscore the frequency of paper publications across diverse regions, with particular emphasis on the predominant scientific output from the US and China. Additionally, trends in academic citations are identified, indicative of the significant impact of papers on academic research and the formulation of public policies. By means of bibliometric analysis, this study not only consolidates existing knowledge but also catalyzes the exploration of future research trajectories, emphasizing the imperative of addressing these issues with heightened scientific rigor.

The influence of ChatGPT on digital learning: experience among university students

Purpose This study aims to investigate the influence of ChatGPT, an AI-based chatbot, on the digital learning experience of students at Mzumbe University. Design/methodology/approach This study adopted a qualitative research design to gather in-depth insights from participants. Semi-structured interviews and an analysis of previous chat content were used as primary sources of data. Thematic analysis was used to analyze the qualitative data, allowing for the exploration of participants’ perspectives, experiences and opinions regarding the integration of ChatGPT into the learning process. Findings The results of the study demonstrated that ChatGPT is widely used in educational contexts and has a positive influence on students’ study habits, academic performance, and understanding of course material. Students appreciated the system’s simplicity, tailored instructions, and the promptness and accuracy of the responses. Despite the possibility of isolated mistakes. Research limitations/implications It is important to recognize the limitations of this study. First, the sample size was small, limiting the broad application of the results. Second, this study’s narrow emphasis on students at Mzumbe University limits its applicability in other situations. Furthermore, depending on self-reported experiences, biases, such as individual interpretation or recollection bias, can occur. Practical implications Educators can maximize ChatGPT in the classroom by using study insights. Its advantages, such as effectiveness and enhanced performance, highlight the possibility for student-centered learning. Practitioners are guided by their awareness of problems, such as probable errors. Constant updates guarantee ChatGPT’s applicability and provide educators with useful advice. Social implications Peer impact is highlighted in this study concerning social factors on the adoption of AI in education. Resolving issues preserves public confidence. Views influence public opinion and direct policymakers in discussions about safe AI use. It influences public attitudes while navigating the ethical integration of AI. Originality/value This study offers insightful information about the impact of ChatGPT on digital learning in Tanzania’s higher education. It makes innovative research contributions that enhance educational practices and emphasizes the advantages, difficulties and demands of responsible usage in the context of AI-based chatbots.

LITERATURE REVIEW: THE INFLUENCE OF SELF-MANAGEMENT AND STRESS MANAGEMENT IN IMPROVING EMPLOYEE PERFORMANCE IN COMPANIES

This research aims to explore and reveal the importance of the influence of self-management and stress management in improving employee performance in companies or agencies. The research method uses a literature review approach, by collecting 15 journal articles from 2017-2023 from Google Scholar. The results of this research reveal the positive impact of self-management in achieving work goals, conflict management, and improving employee quality of life. Apart from that, the concept of stress management is an important key in living a balanced and healthy life in a world full of challenges. Stress is a natural response to pressure and demands routine life, but if not managed carefully, it can have detrimental impacts on a person's physical and mental well-being as well as an important basis for improving the work environment and employee welfare, which can increase productivity and performance. The research contribution can explain that the more stress management increases, the impact it will have on increasing employee performance. For this reason, there needs to be a balance between soft skills and hard skills. This research has limitations, namely the small number of journals reviewed due to the limited number of relevant topics.