Similar Topics Research Articles

Turkey's gender gap in higher education: An analysis of IR doctoral students

This article assesses gender research patterns among Ph.D. students in International Relations (IR) discipline in Turkey with a particular focus on women. We examined 622 IR doctoral dissertations accepted by institutions of higher education in Turkey between 2009 and 2019. We found a statistically significant gender-based pairing among students and advisors, in addition to a higher number of male students and advisors, which suggests greater male visibility in graduate school and academia. Dissertation keyword analysis shows that similar topics are studied by both men and women, and reveals a noticeable absence of gender-sensitive issues, even among the work of female researchers. The striking omission of feminist IR reveals the importance of ‘minding the gap’ in contexts outside of the Western domain.

Otak Sosial dalam Pendidikan Islam

Social Intelligence, Daniel Goleman in his work, social intelligence, reveals that social knowledge is separated into two classes, namely special social concerns and social positions. Current Islamic education is rarely linked to the brain framework or neuroscience. Meanwhile, from one side, according to Pasiak, the school itself follows neuroscience related to efforts to improve students' brains. Call it the accelerated learning hypothesis, quantum learning, the brain being put together advances thus. Despite these problems, Islamic teaching today is considered more as an exchange of information, underscoring the achievement of mental domination. The aim of this research is to examine in more depth the role and function of the brain in humans. More specifically, how the brain is used as the basis for character education carried out by educators so that the education carried out is successful as expected. This research attempts to examine this problem from an Islamic perspective. This exploration is a subjective examination in the context of writing a survey. This research uses literature research that discusses the importance of the topic and compares the results with findings in other research on similar topics and ultimately produces an idea. To obtain data the author used sources found in libraries such as books, journals and the internet. Based on this study, the social brain can be optimized by training students' attitudes and manners and developing social sensitivity with an Islamic material approach.

Analysis of Hot Topics and Evolution of Research in World-class Agricultural Universities Based on BERTopic

Abstract In this paper, the cited papers and cited patents of world-class agriculture-related universities are taken as the research objects, and the preprocessing process of the research hotspot text of agriculture-related universities is accomplished by combining the participle processing method and the TF-IDF method. To make up for the shortcomings of the semantic level of the LDA model, BERTopic is utilized to obtain the document-topic distribution probability and the topic-topic word distribution probability, and the topic hotness of different topics is calculated. Then the Glove method is used to extract the word vector features of the topic words, normalize them, calculate the word vectors by taking the distribution probability values as the weighted weights, solve the topic vectors, and then calculate the similarity of the hot topics in different time windows by the cosine similarity to explore the hot topics and the evolution of the world’s first-class agriculture-related colleges and universities research.

Socio-demographic factors’ influence on the energy-saving behaviour of residential consumers: Evidence from Romania

In the context of various attempts to regulate energy consumption and educate consumers in the spirit of sustainable behavior, this paper aims to identify the role of the main socio-demographic factors on the decision to adopt measures to reduce consumption and save energy. Many studies have approached similar topics, but correlating their conclusions, it can be deduced that psycho-socio-demographic factors interact differently from one country to another, depending on the economic and political context of the moment. From the fact that in the former communist countries, the severe political regime subjected the population to very restrictive living conditions, based on deprivations that led to the formation of a traditional saving behavior and, on the other hand, considering the new Sustainable Development Goals (SDGs) that shape the young generation in the spirit of sustainable society, the authors aimed to study the correlation between socio-demographic factors (age, gender, education, professional status, income) and consumption and energy saving behavior at residential level, in an ex-communist state, Romania. For this purpose, quantitative research was carried out based on the answers of 865 subjects to the questionnaire distributed at the Academy of Economic Studies in Bucharest and in the immediate environment to the members of the university community, using convenience sampling. Using descriptive statistical indicators and linear regression techniques, the intensity of correlation between selected variables was determined and the degree of differentiation of the purchasing and use behavior of green-label household appliances was analysed, as well as the population’s availability to adopt some energy-saving methods. Although the sample is not representative, the conclusions are that measures to reduce energy consumption must be voluntary and stratified, depending on the nature of social and demographic factors.

Perception of Staff Nurses on Quality Patient Care

Introduction: Quality of care reflects how health-care services improve health outcomes. Nurses, as the largest health-care workforce, play a critical role. This study analyzed nurses’ perceptions of quality patient care and identified factors influencing it at MGM Hospital, Kamothe, India.Materials and Methods: Aquantitative, descriptive survey was conducted with 106 nurses using convenient sampling. The study included nurses aged 20 or above working directly with patients and willing to participate administrative permission was obtained from the MS of MGM hospital. Data were collected through Google Forms from June 09, 2021 to June 19, 2021, with links distributed through WhatsApp to the nursing superintendent and ward incharge.Results: The majority (65%) of nurses held a neutral perception of quality patient care, followed by negative (25%) and positive (16%) perceptions. The highest mean perception score (61.9%) with the lowest standard deviation (SD 2) was observed for communication between nurses, patients, and relatives among factors promoting quality care. Conversely, equipment and consumables had the highest mean perception score (55.4%) with the highest SD (3) as factors hindering quality care.Conclusion: While communication is perceived positively by nurses, a significant portion holds neutral or negative views on quality patient care. Equipment and resources are areas needing improvement. Further research with a larger, representative sample and qualitative methods is recommended to inform targeted interventions for enhancing care quality at the hospital. This study encourages beginning researchers to explore similar topics with different variables on a larger scale.

Unveiling How Examples Shape Visualization Design Outcomes.

Visualization designers (e.g., journalists or data analysts) often rely on examples to explore the space of possible designs, yet we have little insight into how examples shape data visualization design outcomes. While the effects of examples have been studied in other disciplines, such as web design or engineering, the results are not readily applicable to visualization due to inconsistencies in findings and challenges unique to visualization design. Towards bridging this gap, we conduct an exploratory experiment involving 32 data visualization designers focusing on the influence of five factors (timing, quantity, diversity, data topic similarity, and data schema similarity) on objectively measurable design outcomes (e.g., numbers of designs and idea transfers). Our quantitative analysis shows that when examples are introduced after initial brainstorming, designers curate examples with topics less similar to the dataset they are working on and produce more designs with a high variation in visualization components. Also, designers copy more ideas from examples with higher data schema similarities. Our qualitative analysis of participants' thought processes provides insights into why designers incorporate examples into their designs, revealing potential factors that have not been previously investigated. Finally, we discuss how our results inform how designers may use examples during design ideation as well as future research on quantifying designs and supporting example-based visualization design. All supplemental materials are available in our OSF repo.

Labor regulation of medical professionals in the universal health care system through the lens of health economics

Current events in the healthcare sector are aimed at amending the Labour Code, specifically section 93. Employees face more difficult working conditions as a result of this issue, despite the fact that this amendment is intended to protect them. The purpose of this thesis was to determine what information exists in academic, official, governmental, and discursive environments, as well as what relevant data can be extracted from the available sources to draw constructive conclusions. The entire subject is treated as a theoretical concept that analyses the situation from the standpoint of the Austrian school of economics and health economics and provides a useful perspective on the issue of health system regulation and reform.The findings reflect an opinionated reality that elicited a media response from the general public and medical personnel. There was an interim agreement on salary increases for doctors and non-medical staff in the health sector in this case. Although the Chamber of Deputies' action appears to be relatively settled, it is still practically unresolved whether doctors will be allowed to work up to twice as many hours of overtime, and although each 12-hour shift should be followed by eight hours of uninterrupted rest, we should probably brace ourselves for further possible Labor Code circumvention. Furthermore, it was noted that this and similar topics are rarely discussed in academic and scientific settings, and that there is a lack of a systemic perspective and evidence.

Topic prevalence and trends of metaverse in healthcare: a bibliometric analysis

Metaverse technology is an advanced form of virtual reality and augmented technologies. It merges the digital world with the real world, thus benefitting healthcare services. Medical informatics is promising in the metaverse. Despite the increasing adoption of the metaverse in commercial applications, a considerable research gap remains in the academic domain, which hinders the comprehensive delineation of research prospects for the metaverse in healthcare. This study employs text-mining methods to investigate the prevalence and trends of the metaverse in healthcare; in particular, more than 34,000 academic articles and news reports are analyzed. Subsequently, the topic prevalence, similarity, and correlation are measured using topic-modeling methods. Based on bibliometric analysis, this study proposes a theoretical framework from the perspectives of knowledge, socialization, digitization, and intelligence. This study provides insights into its application in healthcare via an extensive literature review. The key to promoting the metaverse in healthcare is to perform technological upgrades in computer science, telecommunications, healthcare services, and computational biology. Digitization, virtualization, and hyperconnectivity technologies are crucial in advancing healthcare systems. Realizing their full potential necessitates collective support and concerted effort toward the transformation of relevant service providers, the establishment of a digital economy value system, and the reshaping of social governance and health concepts. The results elucidate the current state of research and offer guidance for the advancement of the metaverse in healthcare.

Personality adjectives in Serbian Tweets: An opening

There has been a great interest in investigating relations between personality and language use on the web or social media. Most of the recent studies are based on mining the users’ information available online and then using machine learning algorithms to predict their personality characteristics. On the other hand, a few studies have relied on the traditional lexical hypothesis when exploring personality under the assumption that personality-related attributes could be obtained from dictionaries. However, little is known about personality structure from Twitter - do data strictly reflect personality structure as represented by personality models, or as unique personality semantic patterns. The aim of the study was to assess and interpret the personality adjective-based structure contained in tweets. The data were collected from an open-access „Tweet-sr“ Serbian Twitter linguistic corpus (Ljubešić & Klubička, 2014). Latent Dirichlet Allocation, a topic modeling technique, was conducted to extract topics and cosine similarity was used as a measure to determine topic similarities, as well as topic-personality dimensions’s similarities. The results showed that the optimal solution comprised four non-overlapping topics reflecting specific semantic structures. Topics did not replicate trait constructs but were modestly related to them. The largest similarities were found with Extraversion and Agreeableness, pointing out the conceptual importance of these traits when describing interpersonal behavior. Also, no inter-topic differences in category distributions were found, with the evaluation terms being the second most frequent in three topics. Although tweets are short-form text messages, they have the potential to communicate socially relevant information through personality descriptors.

SALES PROMOTION, LIVE STREAMING, SUBJECTIVE NORM TERHADAP IMPULSIVE BUYING DENGAN PAYLATER SEBAGAI VARIABEL MODERASI

E-commerce has profoundly altered the shopping behaviors of consumers in Indonesia. Additionally, fintech companies have introduced "paylater" services, revolutionizing the payment process for online purchases. Paylater operates on a Buy Now Pay Later (BNPL) system, allowing consumers to make purchases and defer payment. This innovation enhances the ease and security of online shopping, enticing users with enticing sales promotions. A survey targeting e-commerce users in Indonesia was conducted and subsequently analyzed using structural equation modeling (SEM - PLS). Employing a quantitative descriptive approach with a cross-sectional design, data was collected offline over 14 days in DKI Jakarta, Indonesia, yielding a final dataset from 122 respondents out of 210 obtained. Research outcomes revealed that sales promotion, subjective norms, and e-commerce live streaming features significantly influence impulsive buying behavior among consumers. The use of paylater services moderates this relationship, indicating that frequent paylater users tend to exhibit more impulsivity in their purchasing patterns. Despite the convenience offered by paylater services, there are associated risks such as debt accumulation and financial mismanagement. The findings of this research can serve as an educational tool for potential paylater users, encouraging responsible use and financial management. This research substantially contributes to the growth of fintech companies and micro, small, and medium-sized enterprises (MSMEs), ultimately fostering economic development and providing a reference for future researchers exploring similar topics.

A horizon scan for novel and impactful areas of physical geography research in 2023 and beyond

This editorial reports on a horizon scan exercise that was undertaken to identify new frontier topics, new or emerging themes/concepts, or new philosophical questions of relevance to physical geography. Researchers with broad geographical and disciplinary scope, all of whom were members of the journal's editorial board or editorial advisory board, were invited to join a horizon scan panel. The horizon scan Chair canvassed panel members for ideas, resulting in an initial 32 independently proposed topics. Similar topics were merged by the Chair, and panel members were then invited to vote on and score anonymously the remaining 28 topics, bearing in mind the perceived importance/relevance and novelty for the discipline. The final ranking and sifting phase produced a list of 12 topics, which were categorised as being either new study areas or new epistemological frameworks for physical geography. In this editorial, we outline these 12 topics, some of which have been inspired by developments outside of the discipline, but we identify how potentially fertile contributions could be added by physical geographers. We discuss how new studies of extreme event geographies, the impacts of compound stressors, cross-system pollution and toxicity, the geomorphological basis of zoonoses, ancient environmental DNA, the projection and visualisation of landscape futures, and planetary sciences can all benefit from additional physical geography perspectives. We then consider the ways in which physical geographers may engage further with new approaches in personalised and internet-of-things monitoring, artificial intelligence, innovative technologies for teaching physical geography, the study of human-climate impacts, and the raising of the profile of physical geography thinking alongside other knowledge forms. We encourage more physical geographers to apply their unique skillsets and ways of thinking to these topics. The journal will welcome new submissions, or proposals for special issues, that address these topics from physical geographers and their colleagues.

Systematic Literature Review: Implementation of a Problem-Based Learning Model with Ethnomathematics Nuances in Improving Students' Mathematical Problem Solving Ability

The industrial revolution in the 21st century brought changes to the education system, especially in terms of learning media, where the media used must implement the results of innovation. For example, ethnomathematics is used to increase students' competence in finding solutions to mathematical problems. The aim of carrying out this research is to analyze the extent of students' abilities in solving mathematical problems after receiving based learning Problem Based Learning with ethnomathematics methods. Meanwhile, the research implementation method implements SLR (Systematic Literature Review) by reviewing several articles that have similar topics in the form of developing student competence in solving mathematical problems based on ethnomathematics in the Problem Based Learning learning modeland published between 2019 and 2023. The number of national and international articles used as literature studies was 13 articles. This article was obtained by researchers from the Google Scholar publish or perish database. Based on the analysis carried out, the results showed that the effectiveness of the ethnomathematics-based Problem Based Learning learning model was found in optimizing student competence in terms of solving mathematical problems.

Creating a Visual Topic Map for Battery Researchers Using a Large Global Open Dataset

Battery related research has gained increasing attention in recent years. A large number of research papers about battery are being published as open access. In order to explore the research content in these papers efficiently, it is necessary to develop information management tools to capture the knowledge embedded in them.We are working on a project to create a visual topic map for battery researchers. This map connects battery researchers according to their research topics. This allows potential connection between researches with similar research topics, which increase collaboration opportunities to advance battery research. Additionally, visualization of research content supports intuitive capturing of research trend by maximizing information absorbance.We extract all published works related to battery research from OpenAlex1, which is a fully open catalog of the global research that offers significant advantages in terms of data coverage and affordability and openness. Anther important feature of OpenAlex is that, every article is tagged with multiple concepts using automatic classifier. In addition to concepts extracted from OpenAlex dataset, we used a pre-trained large language model, named KeyBERT2, to further extract representative terms from the work abstract. KeyBERT is a minimal and easy-to-use keyword extraction technique based on the transformers model.For each researcher, we have extracted all concepts and terms from all the articles that authored by that author. Using those terms and concepts, we formulate a vector for each researcher that represents the total research output. To find researchers with similar research interests, we measure similarity between the vectors in the authors space. Top matching authors are connected visually to create a map expands over representative topics in battery related research. Figure 1 shows a snapshot of this map. Researchers names were hidden for privacy purposes. 1Priem, J., Piwowar, H., & Orr, R. (2022). OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and concepts. ArXiv. https://arxiv.org/abs/2205.01833 2Grootendorst, M. (2020). KeyBERT: Minimal keyword extraction with BERT. https://doi.org/10.5281/zenodo.4461265 Figure 1

Differentiated formation of lexical competence in speech among future philologists-orientalists

Relevance. The research is relevant because in the modern pedagogical discourse there is a need to introduce new methods and principles of work for the development of lexical skills and the formation of communicative competence.Purpose. The purpose of this work is to determine the key characteristics of the educational process using the example of the training of orientalist students, to study the specifics of the work on the development of lexical skills at different levels of training: low, medium and high in the speaking process.Methodology. Analytical-synthetic, comparative-comparative, the method of studying and summarizing pedagogical experience and questionnaires, which were used for complex and detailed analysis, were the main methods for writing this work.Results. In this study, an analysis of educational bachelor�s programs in Japanese, Korean, and Indonesian philology of Taras Shevchenko National University of Kyiv was carried out, the main forms of work oriented to different levels of students� knowledge were shown: low, medium, high. Attention is focused on the main methods of work, in particular, discussions, debates, problem tasks, modelling of dialogues, and lexical exercises are mentioned. The results obtained in the course of my own research were compared with the results of other researchers dealing with similar pedagogical topics. The results of a survey of students of 1-5 courses regarding the assessment of their level of lexical training and the effectiveness of the applied teaching methods are presented. The theoretical aspects of the concept of �lexical competence� and �differentiated learning� were also considered.Conclusions. This work can be used for the further development of the problem of differentiated education, in particular, the introduction of new methods, the integration of modern educational practices in order to develop lexical competence in the process of speaking.

Servant Leadership and Career Development: Supporting Employee Growth

In this article, the authors present a literature review encompassing an analysis of Career Development and Servant Leadership in the context of human resource management and organizational growth. The research unveils how leaders who implement servant leadership principles can positively impact the career growth and development of their employees. Applying a Literature Review method, the authors analyzed other articles with similar topics. The research suggests that these characteristics can create an environment in which employees feel valued and supported, thus advancing their career development. The study finds that when leaders exhibit servant leadership characteristics, employees are more likely to experience increased job satisfaction and engagement. This positive experience, in turn, contributes to higher levels of commitment to their organizations. Servant leadership fosters open communication, trust, and a strong sense of community in the workplace, all of which support career development. Furthermore, the research highlights how servant leaders often strive harder to provide growth opportunities to employees. This may include mentorship, training, and guidance in setting and achieving career goals. Employees under servant leadership are more likely to feel empowered and motivated to take control of their career paths. In conclusion, this article emphasizes the strong impact of servant leadership on employee career development. It highlights that leaders prioritizing the well-being and growth of their employees can create a work environment that fosters career advancement, enhances job satisfaction, and strengthens organizational commitment. The research underscores the importance of developing servant leadership within organizations to support employee development and overall success.

Business aspects in focus, investor underreaction and return predictability

Overlap in business aspects serves as a proxy for firm relatedness. Employing an unsupervised topic modelling methodology from machine learning, we characterize the attention allocations of earnings conference call participants (corporate executives, financial analysts, and investors) over the topics discussed. We construct a novel topic similarity measure that captures incremental, difficult-to-observe, and time-varying firm relatedness. However, valuable information from topic peers is not incorporated into stock price in a timely fashion. A long-short strategy based on the returns of topic peers yields a monthly alpha of approximately 69 basis points. Furthermore, return predictability stems primarily from similar business models, customer management, and influential macroeconomic situations. Return predictability is more pronounced among focal firms with higher information complexities and arbitrage costs. Overall, this study provides a novel approach to automatically summarise firms' business aspects in focus and highlights the asset pricing implications of investors' underreactions to non-obvious and dynamic firm relatedness hidden in earnings conference calls.

Publication of materials about the Russian­Ukrainian war in the professional scientifical journals on cultural studies in 2023

The purpose of the article is to establish the main directions in the coverage of the Russian-Ukrainian war in the articles in the scientific journals on cultural studies and their heuristic perspectives.
 The methodology combined bibliometric, classical bibliographic and cultural approaches. The elements of comparativism made it possible to compare the analyzed cultural works with coverage of the topic of full-scale Russian aggression in the publications in the Ukrainian scientific journals on historical sciences.
 The results. The specific weight of scientific journals which placed such publications and the specific weight of articles on similar topics among 199 specifically cultural articles in 16 journals were determined. The experience of combining them into separate rubrics had been evaluated. 7 main thematic groups had been distinguished according to the keywords of the considered works: 1) Art; 2) Cultural identity; 3) Cultural policy; 4) Preservation and restoration of cultural heritage; 5) Transformations of the cultural landscape; 6) Burial and commemoration; 7) Forced migrants. It had been indicated that these articles only recorded certain socio-cultural phenomena or trends, which, however, refer either to the actualization or to the reconceptualization of more general problems — the multidimensionality of the Ukrainian identity and the cultural and artistic landscape, the peculiarities of the national memorial tradition, and ultimately, the post-colonial status of Ukraine.
 The scientific novelty. This article is the first historiographical review of culturological articles, that highlighted the topic of the Russian-Ukrainian war.
 The practical significance. The materials of this ar-ticle can be used in the scientific and public discussions, and for preparation of educational programs as well.

ПЕРІОДО-ОРІЄНТОВАНА РЕТРАНСЛЯЦІЯ: ЗМІНИ В МАКРОСТРАТЕГІЇ ПЕРЕКЛАДУ УКРАЇНОМОВНОЇ ПРОЗИ, НАПИСАНОЇ МІЖ 1918 І 1939 РОКАМИ

Tendencies in the macrostrategies (domestication and foreignization) concerning translation receive signifi cant attention from the translation studies scholars. A common assumption is that domestication typically precedes all forms of foreignization during the translation of the same literary texts. The main goal of this article is to analyze theoretical material regarding this topic and off er an analysis of the outlined assumption from the standpoint of English translations of Ukrainian prose aimed at the 1918–1939 period. The analysis of the theoretical and practical materials allows proclaiming that the assumptions regarding the transition from domestication to foreignization with the development of national literature are incorrect. Instead, translation macrostrategies change on the basis of objective factors such as ideology. More importantly, they are visible in the case of diverging prose texts with similar ideological topics. Key words: macrostrategy, censorship, retranslation, culture, domestication, foreignization.

The Influence of Financial Slack on Firm Innovativeness: The Moderating Role of Board Size

This study aims to investigate the influence of financial slack on firm innovativeness, with board of commissioners and the board of directors as moderating variables. The population of this study consists of 61 companies listed in the Indonesian Stock Exchange, but during the course of the research, some companies were eliminated due to incomplete relevant data from year 2016 to 2021. After the statistical analysis and modelling, this study found that financial slack does not influence firm innovativeness. Similarly, the moderating variables, board of commissioners and the board of directors, also do not moderate the influence of financial slack on firm innovativeness. Hence, the results contradict the hypothesized relationships. This study argues that these findings might be influenced by the economic conditions in Indonesia at that time of the COVID-19 pandemic. As a result, companies shifted their focus and priorities, placing a higher emphasis on the financial health and risk management of the company rather than using excess resources to enhance corporate innovation. While this study is limited to the available sample size, as not all companies allocate their funds for innovation activities, its novelty lies in the inclusion of the board of commissioners and the board of directors as moderating variables in examining the influence of financial slack on firm innovativeness. As such, the research model and findings contribute to the diversity of existing research outcomes on similar topics.

Comparing Artificial Intelligence Classification Models to Improve an Image Comparison System with User Inputs

Data science techniques have increased in popularity over the last decades due to its numerous applications when handling complex data, but also due to its high precision. In particular, Machine (ML) and Deep Learning (DL) systems have been explored in many unique applications, owing to their high precision, flexible customization, and strong adaptability. Our research focuses on a previously described image detection system and analyses the application of a user feedback system to improve the accuracy of the comparison formula. Due to the non-traditional requirements of our system, we intended to assess the performance of multiple AI techniques and find the most suitable model to analyze our data and implement possible improvements. The study focuses on a set of test data, using the test results collected for one particular image cluster. We researched some of the previous solutions on similar topics and compared multiple ML methods to find the most suitable model for our results. Artificial Neural networks and binary decision trees were among the better performing models tested. Reinforcement and Deep Learning methods could be the focus of future studies, once more varied data are collected, with bigger comparison weight diversity.