Research In Field Research Articles

가상현실 저작도구의 상호작용 요소 비교분석 및 고찰

Objectives This study compares and analyzes the interaction elements of non-programming IVR authoring tools and suggests tools that are appropriate for developing immersive virtual reality (IVR) content to help instructors who want to develop their own IVR content choose authoring tools. Methods In this study, we selected Cospaces Edu, Roblox, CenarioVR, and Mozilla Hubs, which are being used in IVR-contents development research in education field, and analyzed the interaction elements that can be utilized without programming, and connected them to the five IVR content types (Activity-based, Discovery, Presentation, Experiential, and Collaborative) Results The four non-programming authoring tools were analyzed according to a total of nine interaction elements, and representative interaction elements for each tool were identified. Cospaces Edu was suitable for Activity-based and Experiential contents, Roblox and Mozilla Hubs for Experiential, Discovery, Collaborative contents, and CenarioVR for Discovery and Presentation content development. Conclusions The results of the study provided criteria for instructors who are not experts in programming but want to develop IVR-enabled educational content in the future so that they can choose the appropriate non-programming authoring tool based on the type of IVR content they want to apply.

Towards equitable multilingualism: promoting transdisciplinary, collaborative dialogue between English as a lingua franca and translingualism

Abstract Inspired by Hult’s (2010. Theme-based research in the transdisciplinary field of educational linguistics. In Francis M. Hult (ed.), Directions and prospects for educational linguistics, 19–32. Springer) discussion of theme-based research within educational linguistics that focuses, first and foremost, on solving problems rather than adhering to disciplinary boundaries and conventions, this article calls for transdisciplinary collaboration to resolve educational problems related to monolingualism, native-speakerism, and the hegemony of colonial ideologies. More specifically, we make a case for transdisciplinary dialogue between English as a lingua franca (ELF) and translingualism. We argue that these two research fields, with their increasingly converging interests and goals as well as distinct strengths, can make a greater impact in addressing persistent educational problems through targeted collaboration, research, and (language) pedagogy based on equitable multilingualism (e.g., Ortega, Lourdes. 2019. SLA and the study of equitable multilingualism. The Modern Language Journal 103. 23–38). In this conceptual paper, we first introduce translingualism and ELF as equally legitimate multilingual theories. Next, we identify shared key tenets and orientations as well as distinctive vantage points of each approach that researchers and educators can take advantage of for collaboratively addressing problems within classrooms and beyond. Finally, we lay out a vision for how this transdisciplinary, collaborative dialogue can help realize more equitable multilingualism.

Performance assessment of novel catalytic spouted-bed vapor jet flow heat exchanger in amine-based carbon capture process

This study introduced a spouted bed and jet flow catalytic heat exchanger (SBJ-EX). This novel non-agitated technology can potentially integrate with a conventional desorption column to enhance heat transfer and CO2 desorption performance in amine-based post-combustion carbon capture systems. As its first research in the carbon capture field, this work experimentally evaluated key factors including overall heat transfer coefficient, logarithmic mean temperature difference, temperature distribution along the reactor, and cyclic loading under varied parameters such as inlet temperature of the heating oil, inlet solvent temperature, rich CO2 loadings, and mass of catalysts to simulate real-world operating conditions using benchmark MEA solvent and solid acid catalyst HZSM-5. Compared to conventional plate heat exchangers, the SBJ-EX demonstrated over a 70 % enhancement in heat transfer performance due to its effective overall heat transfer coefficient. It also exhibited impressive CO2 desorption performance even at lower temperatures with sufficient catalysts. Unlike agitated-type heat exchangers, the SBJ-EX could minimize catalyst attrition and offer more excellent stability. In contrast to fixed-bed catalyst desorbed columns, this equipment offered a more compact design for quicker and simpler catalyst replacement to reduce downtime for operators significantly. The SBJ-EX can also function as an optional backup or add-on unit to provide operators with flexibility. This work further discussed advantages and challenges of the SBJ-EX operation. This work enriched the future research outlook for this technology, and contributed a commercially viable approach to catalysts in carbon capture processes.

Role of Si and SiO2 in Optoelectronic Device Fabrication

Silicon and its oxide deliver a dextrous way for engineering the successors of optoelectronic/photonic devices, by integrating fabrication techniques with heterostructured material possessing tuneable properties. Besides comprehensive knowledge, a collection of functional materials with device fabrication should be amplified. In general, silicon-based allied compounds can co-form with other materials like polymers, nanometal oxides, and organic/inorganic hybrid materials to deliver multiple electronic characteristics. A noteworthy and excellent performance of Si and its oxide secures a prominent position in the realm of the optoelectronics field. This study deliberates an exhaustive overview of advances in fabrication strategies, characteristics, Si/SiO2-based optoelectronic devices, and new materials used in this field. Additionally, this investigation spotlights the potential of Si/SiO2 in accentuating diverse applications like light-emitting diodes, solar cells, photodiodes, and phototransistors. In brief, this article will expose novel pathways of research and peregrination in this mushrooming field.

Research on stock trend prediction based on grey wolf optimized RF and SVM models

The volatility of the stock market has a profound impact on the stability of the financial market, and then has a significant effect on the overall economic situation, so the accurate prediction of stock trend has always been the focus of research in the financial field. In this paper, the raw minute-level stock data of SSE 50 and CSI 300 in 2021 are normalized, and the historical training and test sets of daily stocks for model training and testing are established based on the datasets. The RF-SVM model based on the gray wolf optimization algorithm is constructed to compare the traditional support vector machine and random forest model, and the relevant performance indexes are calculated. In this study, the RF-SVM model based on gray wolf optimization is highly correlated with the characteristics of stock data, and the prediction accuracy of stock index data is more than 85%. The cross-validation score is over 0.77 and the overall weighted score is as high as 0.98. Compared with the SVM and random forest models under the default parameters, the RF-SVM model based on gray wolf optimization has an average advantage of 25% in performance indicators. The generalization ability is increased by about 26%; The fitting error was reduced by about 51.15%; The overall average score advantage is about 34%. These results prove that the RF-SVM model of gray wolf optimization has superior performance and significant optimization effect in stock prediction, and compared with the traditional grid search optimization algorithm, gray wolf optimization has excellent adaptability and can gradually obtain the global optimal parameter configuration.

Unemployed Biotechnology Graduates: Need of Modernization of Education and Training in Tunisia

Biotechnology is a priority higher education and economical sector for Tunisia. However, there is an ever-increasing unemployment rate of the biotechnology graduates in the country. Indeed, this huge problem warrants immediate attention and necessary actions from various stakeholders. This study presents the results of a benchmarking visit, which was arranged by Tampere University of Applied Sciences (TAMK) in Finland, as part of 'BiotechTunisia' Erasmus+ project entitled ‘Modernization of Biotechnology training for better employability of graduates in Tunisia’. There are four Tunisian and three European partners in this project that leads to modernization of skills of teachers, researchers, and students to improve employment and opportunities for entrepreneurship of young graduates in Tunisia. The project aims to modernize the education and the scientific research in the biotechnology field. During this benchmarking visit, Tunisian partners attended seminars, workshops, visited advanced learning facilities, participated to many group discussions, learned about teacher tutoring concept, and student counselling method. Delegation learned about new learning methodologies, pedagogy, and soft skills of students, which could be replicated in their home country education system. The benchmarking visit is seen as an opportunity for Tunisian partners to transfer the good practices from Finland to their home country. Tunisian delegates agree that the learnings could have a positive impact in their education system in coming years towards modernization of education and training of biotechnology students.

Non-uniform magnetic particle capture based on single-fiber optical tweezers

In this study, single-fiber optical tweezers are used to capture polystyrene magnetic particles with non-uniform surfaces. By preparing the tip of the optical fiber probe in the shape of a protruding cone, the laser beam is highly converged at the tip of the fiber to form a strong focused light field, and the laser beam can pass through the gap between the inorganic magnetic particles on the surface of the magnetic particles and enter into the internal polystyrene to generate a gradient force and realize the stable capture of the magnetic particles. This method provides a feasible and effective solution for the capture of non-uniform polystyrene magnetic particles using optical fiber and opens up new possibilities for research in related fields.

Rotation invariance and equivariance in 3D deep learning: a survey

Deep neural networks (DNNs) in 3D scenes show a strong capability of extracting high-level semantic features and significantly promote research in the 3D field. 3D shapes and scenes often exhibit complicated transformation symmetries, where rotation is a challenging and necessary subject. To this end, many rotation invariant and equivariant methods have been proposed. In this survey, we systematically organize and comprehensively overview all methods. First, we rewrite the previous definition of rotation invariance and equivariance by classifying them into weak and strong categories. Second, we provide a unified theoretical framework to analyze these methods, especially weak rotation invariant and equivariant ones that are seldom analyzed theoretically. We then divide existing methods into two main categories, i.e., rotation invariant ones and rotation equivariant ones, which are further subclassified in terms of manipulating input ways and basic equivariant block structures, respectively. In each subcategory, their common essence is highlighted, a couple of representative methods are analyzed, and insightful comments on their pros and cons are given. Furthermore, we deliver a general overview of relevant applications and datasets for two popular tasks of 3D semantic understanding and molecule-related. Finally, we provide several open problems and future research directions based on challenges and difficulties in ongoing research.

GEOGRAPHIC INFORMATION MODEL OF PRECIPITATION INTENSITY

The paper analyses the technological features of building a geoinformation model to study the precipitation intensity in Ukraine. Analysis of natural phenomena requires promptness in obtaining and updating initial data. For this reason, today, geoinformation technologies most often use remote sensing data, mainly in raster format. We collected the raw data on precipitation intensity from the Global Precipitation Climatology Centre website of the German Meteorological Service (DWD). It is monthly data for 2022 in raster format with a raster size of 1 degree. For the organisation and analysis of geographical information, we chose the most suitable new software product, SAGA GIS, designed for geoscientific analysis automation. The advantages of this system are the availability of a complete set of geophysical analysis methods, the spatial algorithms implementation, and open-source code. After data loading, we geoprocessed the data, in particular, using the SAGA software module ‘Set Coordinate Reference System’ and selected the WGS84 coordinate system for the required layers. To prepare the data for analytical studies, we limited them to the administrative boundaries of Ukraine and transformed the WGS84 coordinate system into a UTM 36N projection. Using SAGA analytical tools, we grouped the data by season. Then, we determined the distribution of precipitation intensity over the territory for each season, identifying areas with the highest and lowest precipitation intensity and a part of the territory with the highest annual precipitation. The results of this work may have practical significance for various sectors of the economy and decision-making on adaptation to climate change. They can be relevant both for scientific research and practical application in fields related to environmental assessment. By supplementing the model with data for other subsequent or previous periods, it will be possible to determine trends in precipitation intensity by regions of Ukraine or physiographic zones of its territory. Keywords: modelling, precipitation intensity, geodatabase, geoprocessing, seasonality, software modules, SAGA GIS.

ATP-Citrate Lyase (ACLY): An Extensive Investigation from Molecular Insight to Therapeutic implications

ATP Citrate Lyase (ACLY) is a central enzyme bridging carbohydrate metabolism and lipid biosynthesis, crucial for various physiological processes and implicated in numerous pathologies. This review comprehensively describes ACLY, a pivotal enzyme at lipid biosynthesis and cellular metabolism interface. It serves as crucial role for several physiological functions, making it a highly valued topic for research. Starting with a description of the biochemistry and molecular biology of ACLY, elucidating its structural features, functions, and regulatory mechanisms, particularly in lipid synthesis and histone acetylation. Considering the pathophysiological aspect, the review also examines the relationship between ACLY dysregulation and associated diseases, explaining its contribution to pathological conditions mechanistically. An explanation of ACLY inhibitors is as follows: an overview of these inhibitors, an understanding of their mechanisms of action, and an analysis of their effectiveness and specificity. The following sections transition from preclinical studies, summarising key findings and knowledge into therapeutic potential, to clinical trials. The review offers updated information about ACLY research, integrating data from multiple sources to give an in-depth understanding. It concludes with the challenges and outlook facing the developing ACLY inhibitors, considering the strategies to overcome these challenges and the upcoming path in research and development in this promising field. This comprehensive examination not only encapsulates the knowledge at present but also aims to inspire and guide future inquiries into the complex realm of ACLY and its potential as a therapeutic target, ultimately improving patient outcomes and quality of life.

On English Reading Teaching in Junior High School Based on ARCS Learning Motivation Model

In the cultivation of the four basic skills of listening, speaking, reading, and writing in language learning, reading is a more comprehensive reflection of the language application process. However, there are still many problems in the current stage of English reading teaching, which affects the effectiveness of English reading teaching and the improvement of students’ reading ability. Strong reading motivation is a key factor in promoting students to actively learn reading. Professor Keller, a renowned American psychologist, proposed the “ARCS Learning Motivation Model” in 1983, which starts with four elements: Attention, Relevance, Confidence, and Satisfaction, and designs corresponding motivational strategies based on the characteristics of students’ learning motivation and teaching content. This study aims to stimulate students’ reading motivation as a breakthrough point, apply the ARCS learning motivation model to English reading teaching in junior high school, and explore whether English reading teaching based on this model can improve students’ reading motivation and thus improve their reading ability and grades. This research selected two classes in the first grade of a middle school as experimental subjects. The experimental class adopted a reading teaching method based on the ARCS learning motivation model, while the control class adopted traditional reading teaching methods. Through a one-month teaching experiment, the researchers collected and analyzed data from students, including questionnaires, tests, and interviews. Based on the analysis of the research results, this research confirms the effectiveness of middle school English reading teaching based on the ARCS learning motivation model in enhancing students’ reading motivation, improving reading ability, and improving reading performance. This provides useful insights for English reading teaching in junior high school and also serves as a reference for future research in related fields.

Diverse Flowering Response to Blue Light Manipulation: Application of Electric Lighting in Controlled-Environment Plant Production

Blue light is an important light wavelength in regulating plant flowering. In a controlled environment (CE) plant production systems, blue light can be manipulated easily and even precisely through electric lighting, especially with the advancement of light-emitted diode (LED) technologies. However, the results of previous studies in the literature about blue-light-mediated flowering are inconsistent, which would limit its practical application in CE plant production while implying that an in-depth study of the relevant physiological mechanism is necessary in the future. This review consolidates and analyzes the diverse findings from previous studies on blue light-mediated plant flowering in varying high-value crops from ornamental plants to fruits, vegetables, and specialty crops. By synthesizing the contrasting results, we proposed the possible explanations and even the underlying mechanisms related to blue light intensity and exposure duration, its co-action with other light wavelengths, background environment conditions, and the involved photoreceptors. We have also identified the knowledge gaps based on these studies and outlined future directions for research and potential application in this promising field. This review provides valuable insights into the important and diverse role of blue light in plant flowering and offers a foundation for further investigations to optimize plant flowering through lighting technologies.

Spreading model of single droplet impacting the banana leaf surface and computational fluid dynamics simulation analysis

The droplet deposition behavior is an important indicator of precision agriculture and sustainable agriculture 4.0. Comprehensive analysis of the behavior and modeling of pesticide droplets impacting target leaves is an important basis for achieving efficient spray deposition. In this study, banana leaves were taken as the research object, the spreading model and computational fluid dynamics (CFD) model of single droplet impacting on the target leaf surface were studied from the micro and macro perspectives. The aim is to clarify and obtain the quantitative mapping relationship between droplet deposition performance and related operating parameters. The results showed that the pesticide droplets were asymmetrically spread and slipped on the surface of the inclined banana leaves. The maximum lateral spreading diameter Dnmax was only affected by the normal component of Weber number Wen, while the maximum tangential spreading diameter Dtmax and slip distance L were affected by the normal component of Weber number Wen and the inclination angle α. As the impact velocity increases, the pesticide droplets interact with the non-smooth morphology of the banana leaf surface to form a large number of pinning sites on the edge contact line. Combining the microscopic characteristics of banana leaves with the physicochemical characteristics of the droplets, a CFD model was established to carry out single-drop impact simulation verification. The impact velocity and inclination angle were set as variables to carry out CFD simulation of the dynamic process. The numerical simulation results are consistent with the spreading model obtained from the experimental study, which can quantitatively reflect the impact process of pesticide droplets. The spreading model and CFD model of pesticide droplets impacting on the banana leaf surface established in this study, can provide guidance for the selection of pesticide application for the spray droplet deposition behavior. At the same time, it can also provide methodological reference for other crop spray research and spray technology research in other fields.

Heat Treatment Influence on the Cavitational Erosion Zn-Mg Behavior Used for Biomedical Applications

Recent research in the medical field of temporary implants refers to the development of new biodegradable alloys, which are simultaneously subject to aggressive conditions of pressure fluctuations exerted in blood vessels. Both zinc and magnesium are biocompatible metallic materials, but also biodegradable. The present work approaches a new alloy from the Zn-Mg system, elaborated within the Polytechnic University of Bucharest, on which cavitational erosion tests were performed. It was followed the effect of applying the homogenization heat treatments of cast alloy, at different temperatures and maintenance durations (300°C and 400°C, each with a maintenance of 5h and 10 h) on the behavior at the vibratory cavitation. Finally, the correlation between the parameters of the heat treatment – the structure – behavior at cavitational erosion compared to those of the untreated thermal alloy was determined.

The social media sentiment analysis framework: deep learning for sentiment analysis on social media

Researching public opinion can help us learn important facts. People may quickly and easily express their thoughts and feelings on any subject using social media, which creates a deluge of unorganized data. Sentiment analysis on social media platforms like Twitter and Facebook has developed into a potent tool for gathering insights into users' perspectives. However, difficulties in interpreting natural language limit the effectiveness and precision of sentiment analysis. This research focuses on developing a social media sentiment analysis (SMSA) framework, incorporating a custom-built emotion thesaurus to enhance the precision of sentiment analysis. It delves into the efficacy of various deep learning algorithms, under different parameter calibrations, for sentiment extraction from social media. The study distinguishes itself by its unique approach towards sentiment dictionary creation and its application to deep learning models. It contributes new insights into sentiment analysis, particularly in social media contexts, showcasing notable advancements over previous methodologies. The results demonstrate improved accuracy and deeper understanding of social media sentiment, opening avenues for future research and applications in diverse fields.

A Study on the Community Wisdom Elderly Care Model in the Context of Digital Economy

As the proportion of the elderly population in China continues to rise, the living pressure of the middle-aged group increases and the financial burden of the country gradually increases, it has become a priority to seek the empowerment of digital economy to the pension industry. In addition, the number of high-quality talents is gradually increasing, so it is particularly important to study how digital economy can promote and improve elderly care services in this context. From the perspective of community smart pension, this paper analyzes the three aspects of material resources (R), technology (T) and human resources (H), and deeply discusses the problems faced by the digital economy enabling community smart pension industry, such as insufficient digital application degree, lack of community smart application platform, lack of digital talents and application talents. The corresponding solution is proposed. It is hoped that this can provide reference significance for promoting the exploration of community smart pension mode, and provide enlightenment for future academic research and practical work in related fields.

Decision-Making in Healthcare. A Bibliometric Exploration

Abstract The dynamic environment in which healthcare systems operate highlights the importance of the decision-making process, especially considering the fact that it influences the quality of services and the well-being of patients. The aim of this research is to examine the conceptual link between the concepts “decision”, “decision making process”, “healthcare”, and “management” and how they interact in the literature. Thus, the research aims to identify common trends and patterns in these areas. The research carries out scientific mapping using a three-stage methodological approach: bibliographic data collection through refined searches in the Web of Science database, data analysis using Biblioshiny, and subsequent bibliometric analysis of the 259 scientific documents collected. The main results of the analyses carried out illustrated an increase in scientific publications over time, especially in 2023, when most academic materials were published. International collaboration is in its infancy, with the US and China leading such collaborations. The theoretical implications are centered around the methodological approach to research in the healthcare field. Regarding the practical implications, the research provides information to decision-makers in the medical sector by identifying current contexts in the lives of organizations, but also to academics, with the research having the role of revealing publication sources and other information of interest to them.

Preface

Abstract The 10th of International Conference on Sustainable Agriculture and Environment (ICSAE-X) 17-18 October, 2023 Surakarta, Indonesia (an online conference) This conference was held by Research and Development Centre for Biotechnology and Biodiversity Universitas Sebelas Maret The International Conference on Sustainable Agriculture and Environment (ICSAE) is a circuit meeting that has been held since 2013, and recognized for its focus on sustainable agriculture and the environment. As we all know, agriculture and the environment are critical to human, particularly in terms of food and other necessities. It is also more than just food; agriculture and the environment are involved in economics, politics, and a variety of other fields. This year’s conference, known as ICSAE-X, will be held online in Surakarta, Indonesia, from October 17 to 18, 2023. We intend to provide a platform for researchers, academics, and practicing professionals from around the world to present their research and professional development activities in agriculture, the environment, food, and other relevant fields. The experience of the Covid-19 pandemic has taught us that delivering the conference online effectively broadens the conference participant base and disseminates the results. ICSAE-X welcomes speakers to share their valuable information and knowledge. All presentation mechanisms were carried out using the Zoom meeting online platform. There were four plenary sessions with invited speakers, four rooms where participants could present their specific topics, and a poster session. This year, ICSAE-X received 88 papers, which were presented virtually in both oral and poster formats. According to the presenter, the oral format was set for 10 minutes with 5 minutes for Q&A, while the posters were presented digitally via the ICSAE website. To increase flexibility, the presenter’s presentations were all recorded and uploaded to YouTube. As a result, participants (usually non-registered) who are unable to attend in person can view the presentation at their leisure. Finally, we’d like to thank the entire committee and all of the participants for their contributions to the ICSAE-X. We hope to meet again at a future meeting. ICSAE-X Chair List of Committee of ICSAE-X is available in this pdf.

Flavonoids as Potential Natural Compounds for the Prevention and Treatment of Eczema.

Eczema is a systemic autoimmune disease characterized by inflammation and skin manifestation with a range of comorbidities that include physical and psychological disorders. Despite recent advancements in understanding the mechanisms involved in atopic dermatitis, current marketed products have shown varying results with more side effects. The present objective of the research studies is to develop new agents for eczema that cut down the cost of the novel drugs available and also improve the efficacy with the least adverse effects. Natural compounds and medicinal plants have been traditionally used since ancient civilizations. Nowadays, research in the herbal field is at its peak. One such natural compound, flavonoid, was found to be beneficial for the treatment of eczema. This review describes the use of certain flavonoid products to prepare preparations suitable for the treatment of prophylaxis or eczema. This is especially true for prophylaxis or atopic eczema treatment. These compounds exhibit anti-inflammatory, anti-inflammatory, anti-inflammatory, and anti-inflammatory properties and are, therefore, used in treatments to prevent allergies, inflammation, and irritation to the skin. We also dock the flavonoid derivatives used with the protein associated with the inhibition of eczema for better lead optimization. These preparations appear to be used for cosmetic, dermatological, or herbal remedies as a local application.

Current Challenges and Opportunities for Circular Economy in the Beauty Industry. A Bibliometric Analysis

Abstract The beauty industry contributes not only to the pollution of the environment, because of the improper disposal of packaging, but to the users’ health as well, due to the harmful ingredients, which are used to mass-produce beauty and personal care products. Although sustainability has become an imperative worldwide, this industry still fails to adhere to such norms if we pay attention to the large volumes of plastic and the exaggerated impulse to buy without actually needing, which is a behavior driven by actual consumerism. This paper aims to disclose the current state of research in the academic field of circular economy in the beauty industry, by investigating the contributing authors, organizations and countries and the networks created until now, as a stepping stone for future research. By performing a bibliometric analysis using the VOSviewer software, it was found out that the current literature is not very rich in publications on the integration of circular economy in the beauty sector, mainly because the topic started to be of interest in the recent years with the most productive publication year being 2022. Our research shows that authors from countries like India, China, Indonesia, Italy and the United States have contributed to the literature by touching topics revolving around sustainability in cosmetics and beauty products and innovations regarding a clean development of such products. However, the theme of circular economy in the creation of a clean and safe beauty industry still needs attention from academics in order to fully attain sustainable development goals.