Recent Research Trends Research Articles

인공지능을 적용한 국내 간호교육 연구 동향 분석

Purpose : The purpose of this study was to analyze the trends in domestic nursing education research applying artificial intelligence (AI) in South Korea by examining recent research trends and suggesting future research directions. Method : This study conducted a literature review to analyze the trends in research on AI-applied domestic nursing education published in domestic academic journals. Results : A total of 55 keywords were identified based on the titles and major keywords from 12 literature sources, including multiple entries. The major keywords included AI (12, 21.9%), nursing students (10, 18.3%), nurses (4, 7.4%), AI remote medicine (2, 3.6%), general public (2, 3.6%), AI (2, 3.6%), nursing education (2, 3.6%), nursing process (2, 3.6%), AI application(2, 3.6%), program development (2, 3.6%), bioethics (2, 3.6%), eHealth (1, 1.8%), simulation training (1, 1.8%), AI generation (1, 1.8%), remote medicine (1, 1.8%), phenomenological study (1, 1.8%), systematic review(1, 1.8%), validation study (1, 1.8%), social network analysis (1, 1.8%), and newspaper articles (1, 1.8%). Conclusion : Through this study, it is evident that diverse research on AI-related nursing education is necessary for future nursing education research.

A critical review on optimization and implementation of green-grey infrastructures for sustainable urban stormwater management

ABSTRACT Green-grey infrastructures' implementation has progressed significantly in cities around the globe for sustainable stormwater management. This review study conducted on green-grey infrastructures' optimization represented recent research trends, existing research status, possible study gaps, and future research directions and recommendations needed for further improvements. The findings show that the research on green-grey infrastructures has got significant attention recently (after 2012) because of accessibility to computational resources and the development of hydrological-hydraulic models and optimization algorithms. Furthermore, research on green-grey infrastructures is mostly conducted in ten countries including China, USA and Iran ranked in the first three places, respectively, delivering their advantages to other countries with the essential awareness and knowledge. Most previous studies considered particular quantitative and qualitative optimization objectives and these studies were conducted at smaller retrofitting scales, therefore, future studies need to expand their scope towards socio-ecological objectives with consideration of larger study areas or multi-stage planning, designing, and implementation. Moreover, future research is recommended to consider stakeholders’ participation in preliminary planning and designing stages for the successful implementation of sustainable stormwater management approaches. Lastly, the surrogate-based optimization approaches instead of traditional optimization methods can overcome the burden of computational time and resources in future.

Oropharyngeal cancer and human papillomavirus: a visualization based on bibliometric analysis and topic modeling.

The incidence of oropharyngeal cancer (OPC) is increasing. This study used bibliometric analysis and topic modeling to explore the research trends and advancements in this disease over the past 10 years, providing valuable insights to guide future investigations. 7,355 English articles from 2013 to 2022 were retrieved from the Web of Science Core Collection for bibliometric analysis. Topic modeling was applied to 1,681 articles from high-impact journals, followed by an assessment of topic significance ranking (TSR). Medical Subject Headings (MeSH) terms were extracted using R and Python, followed by an analysis of the terms associated with each topic and on an annual basis. Additionally, genes were extracted and the number of genes appearing each year and the newly emerged genes were counted. The bibliometric analysis suggested that the United States and several European countries hold pivotal positions in research. Current research is focused on refining treatments, staging and stratification. Topic modeling revealed 12 topics, emphasizing human papillomavirus (HPV) and side effect reduction. MeSH analysis revealed a growing emphasis on prognosis and quality of life. No new MeSH terms emerged after 2018, suggesting that the existing terms have covered most of the core concepts within the field of oropharyngeal cancers. Gene analysis identified TP53 and EGFR as the most extensively studied genes, with no novel genes discovered after 2019. However, CD69 and CXCL9 emerged as new genes of interest in 2019, reflecting recent research trends and directions. HPV-positive oropharyngeal cancer research, particularly treatment de-escalation, has gained significant attention. However, there are still challenges in diagnosis and treatment that need to be addressed. In the future, more research will focus on this issue, indicating that this field still holds potential as a research hotspot.

Association between inflammatory bowel disease and primary sclerosing cholangitis: Insights from bibliometric analysis.

Crohn's disease and ulcerative colitis are forms of inflammatory bowel disease affecting approximately 1% of the population. Their typical features include chronic diarrhea, abdominal pain, and weight loss. Extraintestinal manifestations may coincide with or precede the diagnosis of these diseases. Primary sclerosing cholangitis is one such extraintestinal manifestation. Although many papers on this field have been published, bibliometric analysis still needs to be conducted. This article summarizes the current research progress through a bibliometric study, provides an overview of the research status in this field, and analyzes recent research trends. Publications on inflammatory bowel disease and primary sclerosing cholangitis from January 1, 2008, to August 31, 2023, were extracted from the Web of Science Core Collection. VOSviewer and CiteSpace were used to perform a bibliometric and visual study. There are 1499 relevant articles, and the number of articles in this field has been relatively stable in recent years. The results indicate that Karlson TH from the University of Oslo has the highest cumulative number of publications. The institution with the highest publication output is the Mayo Clinic, and the United States leads in article production, occupying a dominant position. Keyword analysis reveals 4079 keywords, with primary sclerosing cholangitis, inflammatory bowel disease, and ulcerative colitis being the most frequently occurring keywords. Research on the association between inflammatory bowel disease and primary sclerosing cholangitis is steadily advancing, with the United States leading in publication output globally. China needs to invest more in research in this area, and collaboration among institutions should be strengthened. The research hotspots revolve around the association between inflammatory bowel disease and primary sclerosing cholangitis, gut microbiota, and other fields.

Electrochemically Enhanced Forward Osmosis Processes Unlocking Efficiency and Versatility

AbstractThe growing interest in forward osmosis (FO) for water reclamation and desalination over the past two decades stems from its potential for lower energy consumption. Despite its promise, FO faces significant challenges, such as the lack of an appropriate draw solute, concentration polarization, membrane fouling, and reverse solute flux (RSF). Recent trends in research have focused on combining various technologies with FO to address these challenges. Notably, the integration of electrochemical technologies with FO offers new possibilities. This review covers FO combined with electrochemical cells (FO‐ECs), categorizing them based on their working principles and applications in improving FO. The review discusses different FO‐EC configurations, including (1) electrodialysis‐combined FO for RSF, (2) electro‐FO for water flux enhancement, and (3) electrochemical oxidation‐combined FO and FO with electro‐conductive membranes for self‐cleaning and fouling mitigation. Additionally, it covers (4) reusable electro‐responsive draw solutes, (5) electrochemical osmosis systems for metal removal and energy production, and (6) osmotic microbial fuel cells for energy recovery and other benefits. The review also assesses the practical applicability and potential for achieving carbon neutrality of the FO‐ECs. It concludes with a forward‐looking perspective, outlining future research directions to optimize and expand the use of electrochemical‐enhanced FO technologies.

Strong Bases and beyond: The Prominent Contribution of Neutral Push-Pull Organic Molecules towards Superbases in the Gas Phase.

In this review, the principles of gas-phase proton basicity measurements and theoretical calculations are recalled as a reminder of how the basicity PA/GB scale, based on Brønsted-Lowry theory, was constructed in the gas-phase (PA-proton affinity and/or GB-gas-phase basicity in the enthalpy and Gibbs energy scale, respectively). The origins of exceptionally strong gas-phase basicity of some organic nitrogen bases containing N-sp3 (amines), N-sp2 (imines, amidines, guanidines, polyguanides, phosphazenes), and N-sp (nitriles) are rationalized. In particular, the role of push-pull nitrogen bases in the development of the gas-phase basicity in the superbasicity region is emphasized. Some reasons for the difficulties in measurements for poly-functional nitrogen bases are highlighted. Various structural phenomena being in relation with gas-phase acid-base equilibria that should be considered in quantum-chemical calculations of PA/GB parameters are discussed. The preparation methods for strong organic push-pull bases containing a N-sp2 site of protonation are briefly reviewed. Finally, recent trends in research on neutral organic superbases, leaning toward catalytic and other remarkable applications, are underlined.

Multi-functionality in de-doped poly 3-methylthiophene memristor device

Multi-functional devices are the recent trends in research, as they are cost-effective and reduce e-waste. In this study, detailed current-voltage measurement is performed on electro-polymerized Poly 3-methylthiophene (P3MT) thin film sandwiched between stainless steel (SS) and silver (Ag) electrodes, and the fabricated two-terminal device consisting of geometry SS/P3MT/Ag. Systematic and comparative measurements on partially doped P3MT devices with three dopants (TBAPF6, LiClO4 & TBABF4) helped in realizing multi-functionality. In all the devices the following multifunctional features are demonstrated: negative differential resistance (NDR), sweep voltage-controlled resistive switching, analog memory, and synaptic plasticity. Charge transport in all the devices is modeled based on charge accumulation, trapping, and de-trapping of injected carriers.

Neoliberal Feminism and Political Leadership: The Representation of Giorgia Meloni and Elly Schlein in Popular Culture

Building on a long tradition of studies on the intertwining of politics and popular culture, the article examines the representation of the two Italian political leaders of the moment, Giorgia Meloni and Elly Schlein, offered by women’s magazines. The study focuses in particular on two interrelated aspects: on the one hand, the extent to which the discursive strategies to talk about the leaders, their personal lives, careers and ideas contribute to strengthen the contemporary hegemony on feminism; on the other hand, the discursive strategies used to represent the leaders through a frame of competition typical of the neoliberalism. Indeed, we refer to the most recent trends in feminism research, contested among post-feminism, neoliberal feminism and celebrity feminism. Within this framework, we examined whether and how female political leaders can become icons of life, style and power in a way that is functional to the neoliberal narrative. The critical discourse analysis conducted on eight Italian women’s magazines over the course of a year makes it possible to highlight some results that contribute to the reflection on neoliberal feminism and female leadership. In particular, leaders are presented through argumentative strategies of genealogism, exceptionalism and compensation: the ways in which magazines justify their position of power refer to family relationships and character qualities, emphasizing the characteristics closest to the neoliberal model and overshadowing all others, including political ideas. Rather, leaders are deradicalized and depoliticized to favour instead a reassuring narrative in which women have broken the glass ceiling. In that way, women’s magazines renounce representing women leaders for their ideas and ideologies, and instead focus on their unique mark of difference: their gender.

Diamond-Like Carbon (DLC) Coatings : Classification, Properties, and Applications

This paper presents the most recent and important research trends on the friction and wear properties of diamond like carbon (DLC) coatings deposited on different types of materials. For this the invention, methods, techniques, and design related to this area are discussed. The different trends of tribological properties of materials under different operating conditions are observed. In this article, an attempt is made to provide an opportunity for the future researchers to identify the recent trend of these areas. It is expected that the applications of these results will contribute to the improvement of different concerned mechanical processes. This review article also includes some patents relevant to the method of producing a DLC film.

A Survey on Conversational AI Question answering System for Low Resource Language

Question-and-answer (QA) systems allow users to pose questions about the information accessible in a variety of formats, such as structured and unstructured information in natural languages. It contributes significantly to conversational artificial intelligence (AI), which has led to the creation of a novel research field on conversational question answering (CQA), in which a system is required to understand the provided context before engaging in multi-turn QA to satisfy a user's informational needs. While the majority of currently done research focuses on single-turn QA, pre-trained language models and the availability of large multi-turn QA datasets have recently made multi-turn QA more significant. This study aims to give a thorough analysis of the most recent CQA research trends, mostly based on publications that have been reviewed in recent years. Our data indicates a shift in the industry's preference for multi-turn QA over single-turn QA, which has numerous advantages for conversational AI. In order to create a solid basis for the field of CQA, this survey aims to serve as the pinnacle for the research community.

Gratitude research: Review and future agenda using bibliometric analysis of the studies published in the last 20 years

AbstractAlthough there is an exponential rise in the literature on gratitude research, there is no attempt to systematically identify the historical development and recent trends in gratitude research. Gratitude has been defined diversely as an emotion, an attitude, a moral virtue, a habit, a personality trait or a coping response. As an emotion, people experience gratitude when they receive something valuable from someone else. As a trait, it is defined as a tendency to recognise and respond to goodness in others. The present study uses bibliometric analysis to review gratitude publications from the last 20 years, that is from 2001 to September 2023. WoS (Web of Science) identified 2982 publications referring to gratitude in title, abstract or keywords. It comprised 2860 articles and 122 review papers. The extracted data were analysed and visualised with the help of two analytical tools, that is the WoS analysis and VOSviewer (version 1.6.16). This study elicits the number of publications and citations from 2001 to September 2023, and most cited publications, and the most influential authors, articles, publishers, universities and countries as performance analysis. Furthermore, collaboration among countries, keyword co‐occurrence and recent trend analysis are employed through science mapping. The results reveal that the major research areas of gratitude research are psychology, social sciences, business economics, psychiatry and public environmental and occupational health. The keywords co‐occurrence suggest five major research clusters: evolutionary studies of gratitude, gratitude and health, gratitude and positive psychology, gratitude among children and adolescent and mediating and moderating studies of gratitude. Also, the analysis of recent 5‐year studies highlights a clear trend of scientific explorations of gratitude against earlier trends of articles on philosophical and religious connotations of gratitude.

Problem solving in mathematics education: tracing its foundations and current research-practice trends

In tracing recent research trends and directions in mathematical problem-solving, it is argued that advances in mathematics practices occur and take place around two intertwined activities, mathematics problem formulation and ways to approach and solve those problems. In this context, a problematizing principle emerges as central activity to organize mathematics curriculum proposals and ways to structure problem-solving learning environments. Subjects’ use of concrete, abstract, symbolic, or digital tools not only influences the ways to pose and pursue mathematical problems; but also shapes the type of representation, exploration, and reasoning they engage to work and solve problems. Problem-solving foundations that privilege learners’ development of habits of mathematical practices that involve an inquiry method to formulate conjectures, to look for different ways to represent and approach problems, and to support and communicate results shed light on directions of current research trends and the relevance of rethinking curriculum proposals and extending problem-solving environments in terms of teachers/students’ consistent use of digital tools and online developments.

Global research trends in Total Body Irradiation: a bibliometric analysis.

This manuscript presents a bibliometric and visualization analysis of Total Body Irradiation (TBI) research, aiming to elucidate trends, gaps, and future directions in the field. This study aims to provide a comprehensive overview of the global research landscape of TBI, highlighting its key contributions, evolving trends, and potential areas for future exploration. The data for this study were extracted from the Web of Science Core Collection (WoSCC), encompassing articles published up to May 2023. The analysis included original studies, abstracts, and review articles focusing on TBI-related research. Bibliometric indicators such as total publications (TP), total citations (TC), and citations per publication (C/P) were utilized to assess the research output and impact. Visualization tools such as VOS Viewer were employed for thematic mapping and to illustrate international collaboration networks. The analysis revealed a substantial body of literature, with 7,315 articles published by 2,650 institutions involving, 13,979 authors. Full-length articles were predominant, highlighting their central role in the dissemination of TBI research. The authorship pattern indicated a diverse range of scholarly influences, with both established and emerging researchers contributing significantly. The USA led in global contributions, with significant international collaborations observed. Recent research trends have focused on refining TBI treatment techniques, investigating long-term patient effects, and advancing dosimetry and biomarker studies for radiation exposure assessments. TBI research exhibits a dynamic and multifaceted landscape, driven by global collaboration and innovation. It highlights the clinical challenges of TBI, such as its adverse effects and the need for tailored treatments in pediatric cases. Crucially, the study also acknowledges the fundamental science underpinning TBI, including its effects on inflammatory and apoptotic pathways, DNA damage, and the varied sensitivity of cells and tissues. This dual focus enhances our understanding of TBI, guiding future research toward innovative solutions and comprehensive care.

From MNIST to ImageNet and back: benchmarking continual curriculum learning

Continual learning (CL) is one of the most promising trends in recent machine learning research. Its goal is to go beyond classical assumptions in machine learning and develop models and learning strategies that present high robustness in dynamic environments. This goal is realized by designing strategies that simultaneously foster the incorporation of new knowledge while avoiding forgetting past knowledge. The landscape of CL research is fragmented into several learning evaluation protocols, comprising different learning tasks, datasets, and evaluation metrics. Additionally, the benchmarks adopted so far are still distant from the complexity of real-world scenarios, and are usually tailored to highlight capabilities specific to certain strategies. In such a landscape, it is hard to clearly and objectively assess models and strategies. In this work, we fill this gap for CL on image data by introducing two novel CL benchmarks that involve multiple heterogeneous tasks from six image datasets, with varying levels of complexity and quality. Our aim is to fairly evaluate current state-of-the-art CL strategies on a common ground that is closer to complex real-world scenarios. We additionally structure our benchmarks so that tasks are presented in increasing and decreasing order of complexity—according to a curriculum—in order to evaluate if current CL models are able to exploit structure across tasks. We devote particular emphasis to providing the CL community with a rigorous and reproducible evaluation protocol for measuring the ability of a model to generalize and not to forget while learning. Furthermore, we provide an extensive experimental evaluation showing that popular CL strategies, when challenged with our proposed benchmarks, yield sub-par performance, high levels of forgetting, and present a limited ability to effectively leverage curriculum task ordering. We believe that these results highlight the need for rigorous comparisons in future CL works as well as pave the way to design new CL strategies that are able to deal with more complex scenarios.

Sex estimation research trends in forensic anthropology between 2000 and 2022 in five prominent journals.

In forensic anthropology, osteological sex estimation methods are continuously reevaluated and updated to improve classification accuracies. Therefore, to gain a comprehensive understanding of recent trends in sex estimation research in forensic anthropology, a content analysis of articles published between 2000 and 2022 in Forensic Science International, the Journal of Forensic Sciences, the International Journal of Legal Medicine, the American Journal of Biological Anthropology, and Forensic Anthropology, was performed. The main goals of this content analysis were to (1) examine trends in metric versus morphological research, (2) examine which areas of the skeleton have been explored, (3) examine which skeletal collections and population affinities have been most frequently utilized, and (4) determine which statistical methods were commonly implemented. A total of 440 articles were coded utilizing MAXQDA and the resulting codes were exported for analysis. Statistical analyses were conducted utilizing the Cochran-Armitage and Jonckheere-Terpstra tests for trends, as well as Fisher-Freeman-Halton tests. The results demonstrate that sex estimation research published in these journals has prioritized metric over morphological methods. Further, the most utilized skeletal regions continue to be the skull and pelvis, while the most popular classification statistics continue to be discriminant function analysis and logistic regression. This study also demonstrates that a substantial portion of research has been conducted utilizing U.S. and Europe-based collections and limited populations. Based on these results, future sex estimation research must continue exploring the use of long bones and other postcranial elements, testing newer methods of analysis, as well as developing population-inclusive methods.

Current Landscape of the Robotic Tactile Array Sensors and Algorithm‐Based Performance Enhancement

The automated robots utilizing the traditional rigid tactile sensors have achieved significant success in effective task execution. Advancing into the era of service robots and humanoids that should perform sophisticated works in daily life, recent research trends in robotic tactile sensors have been shifting from the conventional rigid sensors to flexible/stretchable sensors. Over the past decade, the flexible/stretchable tactile sensors with human skin‐like mechanical compliance and stimulation perceptions have seen considerable advances. However, there are many substantial remaining challenges to produce practically useful flexible/stretchable tactile sensors such as the signal hysteresis originating from sensor material and the limited spatial resolution resulting from excessive addressing lines and signal interferences. Incorporation of learning‐based algorithms and data analysis techniques have been introduced recently and made remarkable successes in improving the challenges. Because most robotic tactile sensors are fabricated using the electronic sensing mechanisms or platforms, this article presents a concise overview on recent flexible/stretchable tactile sensors. This article introduces a brief discussion on the sensor performance parameters and sensing mechanisms, and the algorithmic approaches. In addition, it addresses existing challenges associated with current tactile array sensors and algorithms, then discusses prospects, and proposes a research direction for immediate practical uses in robots.

Ceramic Material Properties in High-Temperature Environments: Recent Trends in Finite Element Analysis Research

The finite element method is commonly utilized for high-temperature ceramics, such as cutting tools, thermal/environmental barrier coatings, and aerospace applications. Cutting performance is influenced by both internal and external factors, including heat transfer, and cutting speed. Friction coefficients and heat transfer issues reveal limitations on cutting tool efficiency, requiring accurate modeling and validation. Although oxide formation and crack failure for barrier coatings are discussed, ceramic materials and geometry must be studied. Extensive research on the nucleation and propagation of micro-crack is needed for next-generation spacecraft component applications by validating the established model based on experimental observation. Modeling and verification research improves ceramic reliability under more stress conditions.

Congestion Control Algorithms for the Internet – A Secondary Publication

In the last five years, there has been a V-shaped recovery in the number of papers on congestion controlalgorithms on the Internet. In this paper, congestion problems on the Internet are discussed, such as congestion collapse and bufferbloat from the perspective of the necessity of congestion control algorithms. The typical congestion control algorithms are introduced, and the research areas and methods of congestion control algorithms are described. Recent research trends and future prospects of congestion control algorithms are also presented.

Employee Attrition Prediction using Machine Learning Models: A Review Paper

Employee attrition refers to the decrease in staff numbers within an organization due to various reasons. As it has a negative impact on long-term growth objectives and workplace productivity, firms have recognized it as a significant concern. To address this issue, organizations are increasingly turning to machine-learning approaches to forecast employee attrition rates. This topic has gained significant attention from researchers, especially in recent times. Several studies have applied various machinelearning methods to predict employee attrition, producing different resultsdepending on the employed methods, factors, and datasets. However, there has been no comprehensive comparative review of multiple studies applying machine-learning models to predict employee attrition to date. Therefore, this study aims to fill this gap by providing an overview of research conducted on applying machine learning to predict employee attrition from 2019 to February 2024. A literature review of relevant studies was conducted, summarized, and classified. Most studies agree on conducting comparative experiments with multiple predictive models to determine the most effective one.From this literature survey, the RF algorithm and XGB ensemble method are repeatedly the best-performing, outperforming many other algorithms. Additionally, the application of deep learning to employee attrition prediction issues also shows promise. While there are discrepancies in the datasets used in previous studies, it is notable that the dataset provided by IBM is the most widely utilized. This study serves as a concise review for new researchers, facilitating their understanding of the primary techniques employed in predicting employee attrition and highlighting recent research trends in this field. Furthermore, it provides organizations with insight into the prominent factors affecting employee attrition, as identified by studies, enabling them to implement solutions aimed at reducing attrition rates.

Recent trends in ginseng research.

Ginseng, the dried root of Panax ginseng, contains ginsenosides and has long been used in Korea, China, and Japan to treat various symptoms. Many studies on the utility of ginseng have been conducted and in this paper we investigate recent trends in ginseng research. P. ginseng studies were collected from scientific databases (PubMed, Web of Science, and SciFindern) using the keywords "Panax ginseng C.A. Meyer", "ginsenosides", "genetic diversity", "biosynthesis", "cultivation", and "pharmacology". We identified 1208 studies up to and including September 2023: 549 studies on pharmacology, 262 studies on chemical components, 131 studies on molecular biology, 58 studies on cultivation, 71 studies on tissue culture, 28 studies on clinical trials, 123 reviews, and 49 studies in other fields. Many researchers focused on the characteristic ginseng component ginsenoside to elucidate the mechanism of ginseng's pharmacological action, the relationship between component patterns and cultivation areas and conditions, and gene expression.