Current State Of Research Research Articles

Ratiometric Fluorescent Probes for Copper Ion Detection and Cuproptosis Studies

Abstract: This study reviews the latest progress of ratiometric fluorescent probes of copper ions from 2022 till now. As a key trace element in biological systems, copper ions play an important role in a variety of biological processes. However, the abnormal change in copper ion concentration is closely related to a variety of diseases, so the development of highly sensitive and highly selective copper ion detection methods is of great significance for scientific research and clinical diagnosis. In this paper, we first introduced the classification of copper ion fluorescence probes, including molecular sensors based on five-membered azocycles, six-membered azocycles, imide groups (R2C=NR'), oxygen and nitrogen functional groups (such as ethers, aldehydes, ketones, esters, carboxylic acids and hydroxyl groups) and group ⅥA elements. Subsequently, the application of nanosensors in the detection of copper ions is further discussed, especially the nanosensors in which copper is used as a reactant, catalyst or alternative reaction. Finally, the current research status of copper ion fluorescence probes is summarized, and the future development direction is prospected in order to provide reference and inspiration for the design of new high-efficiency copper ion detection tools.

Advances in Highly Ductile Concrete Research.

In recent years, high-ductility concrete (HDC) has gradually become popular in the construction industry because of its excellent ductility and crack resistance. Concrete itself is a kind of building material with poor tensile properties, and it is necessary to add a large number of steel bars to improve its tensile properties, which increases the construction cost of buildings. However, most of the research studies on high-ductility concrete are scattered. In this paper, the basic mechanical properties of high-ductility concrete and the effects of dry and wet cycles, freeze-thaw cycles, and salt erosion on the durability of high-ductility concrete are obtained by comprehensive analysis. The results show that the tensile properties of HDC can be significantly improved by adding appropriate fiber. When the volume fraction of steel fiber is 2.0%, the splitting tensile strength of concrete is increased by 98.3%. The crack width threshold of concrete chloride erosion is 55-80 μm, and when the crack width threshold is exceeded, the diffusion of CL-1 will be accelerated, and the HDC can control the crack within the threshold, thereby improving the durability of the concrete. Finally, the current research status of high-ductility concrete is analyzed, and the future development of high-ductility concrete is proposed.

Decoding machine learning in nursing research: A scoping review of effective algorithms.

The rapid evolution of artificial intelligence (AI) technology has revolutionized healthcare, particularly through the integration of AI into health information systems. This transformation has significantly impacted the roles of nurses and nurse practitioners, prompting extensive research to assess the effectiveness of AI-integrated systems. This scoping review focuses on machine learning (ML) used in nursing, specifically investigating ML algorithms, model evaluation methods, areas of focus related to nursing, and the most effective ML algorithms. The scoping review followed the Preferred Reporting Items for Systematic Review and Meta-Analysis Extension for Scoping Reviews (PRISMA-ScR) guidelines. A structured search was performed across seven databases according to PRISMA-ScR: PubMed, EMBASE, CINAHL, Web of Science, OVID, PsycINFO, and ProQuest. The quality of the final reviewed studies was assessed using the Medical Education Research Study Quality Instrument (MERSQI). Twenty-six articles published between 2019 and 2023 met the inclusion and exclusion criteria, and 46% of studies were conducted in the US. The average MERSQI score was 12.2, indicative of moderate- to high-quality studies. The most used ML algorithm was Random Forest. The four second-most used were logistic regression, least absolute shrinkage and selection operator, decision tree, and support vector machine. Most ML models were evaluated by calculating sensitivity (recall)/specificity, accuracy, receiver operating characteristic (ROC), area under the ROC (AUROC), and positive/negative prediction value (precision). Half of the studies focused on nursing staff or students and hospital readmission or emergency department visits. Only 11 articles reported the most effective ML algorithm(s). The scoping review provides insights into the current status of ML research in nursing and recognition of its significance in nursing research, confirming the benefits of ML in healthcare. Recommendations include incorporating experimental designs in research studies to optimize the use of ML models across various nursing domains. The scoping review demonstrates substantial clinical relevance of ML applications for nurses, nurse practitioners, administrators, and researchers. The integration of ML into healthcare systems and its impact on nursing practices have important implications for patient care, resource management, and the evolution of nursing research.

Parametric optimization and comparative study of machine learning and deep learning algorithms for breast cancer diagnosis.

Breast Cancer is the leading form of cancer found in women and a major cause of increased mortality rates among them. However, manual diagnosis of the disease is time-consuming and often limited by the availability of screening systems. Thus, there is a pressing need for an automatic diagnosis system that can quickly detect cancer in its early stages. Data mining and machine learning techniques have emerged as valuable tools in developing such a system. In this study we investigated the performance of several machine learning models on the Wisconsin Breast Cancer (original) dataset with a particular emphasis on finding which models perform the best for breast cancer diagnosis. The study also explores the contrast between the proposed ANN methodology and conventional machine learning techniques. The comparison between the methods employed in the current study and those utilized in earlier research on the Wisconsin Breast Cancer dataset is also compared. The findings of this study are in line with those of previous studies which also highlighted the efficacy of SVM, Decision Tree, CART, ANN, and ELM ANN for breast cancer detection. Several classifiers achieved high accuracy, precision and F1 scores for benign and malignant tumours, respectively. It is also found that models with hyperparameter adjustment performed better than those without and boosting methods like as XGBoost, Adaboost, and Gradient Boost consistently performed well across benign and malignant tumours. The study emphasizes the significance of hyperparameter tuning and the efficacy of boosting algorithms in addressing the complexity and nonlinearity of data. Using the Wisconsin Breast Cancer (original) dataset, a detailed summary of the current status of research on breast cancer diagnosis is provided.

Bibliometric Insights into Research Hotspots and Trends in Obesity and Asthma from 2013 to 2023

Introduction: Obesity and asthma are closely linked, but the current state of research on this topic and future research directions have yet to be comprehensively explored. This study aims to provide an up-to-date overview of the research landscape in the field of obesity and asthma. Methods: A bibliometric analysis was conducted using the Web of Science Core Collection database to identify papers published on obesity and asthma between 2013 and 2023. VOSviewer software was utilized for statistical analysis and visualization of collaborative networks, research trends, literature sources, citation analysis, co-citation analysis, and keyword analysis. Results: A total of 3,406 records from 1,010 journals authored by 17,347 researchers affiliated with 4,573 institutes across 117 countries and regions were retrieved. The number of publications and citations increased annually. The USA and China contributed the majority of records. Major nodes in the collaboration network map included Harvard Medical School, Johns Hopkins University, University of Newcastle, Karolinska Institution, University of Toronto, and Seoul National University. Prolific authors included Anne E. Dixon, Erick Forno, Lisa G. Wood, Deepa Rastogi, and Fernando Holguin. Research trends and hotspots focused on metabolism studies, Mendelian randomization, gut microbiome, inflammation response, gene, biomarker research, and comorbidities were identified as potential future research frontiers. Conclusion: This study provides a comprehensive overview of the current research status and trends in the field of obesity and asthma. Our findings highlight the importance of understanding collaboration patterns, research hotspots, and emerging frontiers to guide future research in this area.

Unraveling social undermining at the workplace: A systematic review of past achievements and future promises

AbstractIn the contemporary landscape of organizational dynamics, it is imperative to understand the nuance of social undermining behaviors in the workplace for effective strategy and decision‐making. In this regard, this study reviews, identifies, and critically evaluates the social undermining literature and offers new avenues for future research. The systematic literature review methodology has been used to select and critically review 65 studies on this topic. The analysis and findings of this review are presented in three sections, as follows, (i) research profiling—to highlight the current status of research on social undermining in management literature, (ii) literature synthesis—to highlight key theories and conceptions of social undermining as well as discuss the antecedents and outcomes of social undermining, and (iii) critical analysis—to highlight knowledge gaps in existing research and set future agenda. This review is the first comprehensive review on social undermining at the workplace and serves as a knowledge base by presenting a comprehensive literature review as well as extending further development of knowledge on this topic. A key contribution of our review is the proposal of a comprehensive framework of literature synthesis to provide a bird's eye view on this scholarly domain. Our study contributes to organizational behavior and strategic management discourse by offering crucial insights on human dynamics that shape organizational strategy, and change.

A review on recent progress of refractory high entropy alloys: From fundamental research to engineering applications

Refractory high-entropy alloys (RHEAs) have emerged as frontier materials for high-temperature structural applications due to their exceptional mechanical properties and thermal stability. This review aims to provide a comprehensive and in-depth summary of the latest research progress in the field of RHEAs. By systematically analyzing 253 publications since 2022, this review presents a panoramic overview of the current research status in the field of RHEAs, covering aspects from alloy design, microstructure, processing techniques, mechanical behavior, to physicochemical properties. Key strengthening and toughening mechanisms, such as solid solution strengthening, precipitation strengthening, and grain boundary strengthening, are extensively analyzed. The high-temperature mechanical performance, oxidation resistance, and adaptability of RHEAs in extreme environments including corrosion and irradiation, are critically reviewed, and the potential application value of these research findings in aerospace, nuclear energy, biomedical, and other fields is discussed. Simultaneously, the multidisciplinary characteristics of RHEAs research has revealed the trend of the field evolving from fundamental research to practical applications. Furthermore, with the aid of advanced characterization techniques and computational methods, the review elucidates the controlling effects of chemical short-range order, defect structures, and other factors on the performance evolution of RHEAs, highlighting the importance of multi-principal element synergistic effects. Based on summarizing the key scientific issues and technological bottlenecks faced by RHEAs, the article provides a forward-looking perspective on future research directions, emphasizing development strategies that integrate computation and experiments, and accelerate the transformation of fundamental research into engineering applications, thus providing insights and guidance for developing a new generation of high-performance RHEAs.

Research Progress on Ecological Carrying Capacity and Ecological Security, and Its Inspiration on the Forest Ecosystem in the Karst Desertification Control

Social progress and the improvement of living standards are often accompanied by the intensification of ecological crises. The long-term abuse of natural resources has led to the accumulation of ecological liabilities, which in turn seriously hinders economic development. This has prompted all sectors of society to recognize the importance of ecological carrying capacity (ECC) and ecological security (ES). Remarkable progress has been made in karst desertification control (KDC), which has helped reshape the ECC and ES pattern of forests. Currently, the research field of ECC and ES is experiencing rapid development. Further studies in these areas have immeasurable value in promoting regional sustainable development strategies and strengthening ecological civilization construction. The objective of this paper is to provide an overview of the current research status and potential challenges in the field of ECC and ES, with a view to optimizing the program of forest restoration and protection in KDC. This study systematically analyzed 350 relevant studies and found that (1) research on forest ECC and ES has shown a strong growth trend overall, especially after 2017, with a growth rate exceeding 75%; (2) the literature predominantly focuses on the assessment of forest ECC (40.58%) and the enhancement of forest ES (23.42%); and (3) geographically, research findings are heavily concentrated in Asia, representing 95.40% of the total. Notably, China emerges as the primary contributor to research in this field, accounting for a substantial 94.12%. Based on the above analysis, this review summarizes the significant advancements in forest ecosystems, ECC, and ES, while also delving into the key scientific issues that need to be addressed. Furthermore, it offers valuable insights from forest ecosystems in tackling KDC, with the goal of offering guidance and strategic recommendations for future research and practices in managing delicate ecological environments.

Immunothrombosis: A bibliometric analysis from 2003 to 2023.

Immunothrombosis is a physiological process that constitutes an intravascular innate immune response. Abnormal immunothrombosis can lead to thrombotic disorders. With the outbreak of COVID-19, there is increasing attention to the mechanisms of immunothrombosis and its critical role in thrombotic events, and a growing number of relevant research papers are emerging. This article employs bibliometrics to discuss the current status, hotspots, and trends in research of this field. Research papers relevant to immunothrombosis published from January 1, 2003, to May 29, 2023, were collected from the Web of Science Core Collection database. VOSviewer and the R package "Bibliometrix" were employed to analyze publication metrics, including the number of publications, authors, countries, institutions, journals, and keywords. The analysis generated visual results, and trends in research topics and hotspots were examined. A total of 495 target papers were identified, originating from 58 countries and involving 3287 authors from 1011 research institutions. Eighty high-frequency keywords were classified into 5 clusters. The current key research topics in the field of immunothrombosis include platelets, inflammation, neutrophil extracellular traps, Von Willebrand factor, and the complement system. Research hotspots focus on the mechanisms and manifestations of immunothrombosis in COVID-19, as well as the discovery of novel treatment strategies targeting immunothrombosis in cardiovascular and cerebrovascular diseases. Bibliometric analysis summarizes the main achievements and development trends in research on immunothrombosis, offering readers a comprehensive understanding of the field and guiding future research directions.

Targeting Fibrinolytic Inhibition for Venous Thromboembolism Treatment: Overview of an Emerging Therapeutic Approach.

Venous thrombosis and pulmonary embolism (venous thromboembolism) are important causes of morbidity and mortality worldwide. In patients with venous thromboembolism, thrombi obstruct blood vessels and resist physiological dissolution (fibrinolysis), which can be life threatening and cause chronic complications. Plasminogen activator therapy, which was developed >50 years ago, is effective in dissolving thrombi but has unacceptable bleeding risks. Safe dissolution of thrombi in patients with venous thromboembolism has been elusive despite multiple innovations in plasminogen activator design and catheter-based therapy. Evidence now suggests that fibrinolysis is rigidly controlled by endogenous fibrinolysis inhibitors, including α2-antiplasmin, plasminogen activator inhibitor-1, and thrombin-activable fibrinolysis inhibitor. Elevated levels of these fibrinolysis inhibitors are associated with an increased risk of venous thromboembolism in humans. New therapeutic paradigms suggest that accelerated and effective fibrinolysis may be achieved safely by therapeutically targeting these fibrinolytic inhibitors in venous thromboembolism. In this article, we discuss the role of fibrinolytic components in venous thromboembolism and the current status of research and development targeting fibrinolysis inhibitors.

Literature Review of English Reading Strategies in Junior High School

Reading strategy, as one of the important branches of learning strategies, is a means adopted by learners for solving reading difficulties. In order to understand the basic situation of English reading strategy research, the author adopts a descriptive review method. By summarizing the research on English reading strategies by scholars at home and abroad, this paper elaborates on the current status of domestic research and foreign research separately. It is found that in the domestic research on English reading strategies, although both theoretical and empirical research are given equal importance, the research method is limited, the research content is too concentrated, and the theoretical research basis is insufficient. These areas require further improvement.

Analysis of the current status and hot topics in spinal schwannoma imaging research based on bibliometrics.

This study aims to explore the current hot topics and future research trends in spinal schwannoma imaging research, providing a reference for related studies and promoting the development of spinal schwannoma imaging. We conducted a literature search in the Web of Science database using the search terms (((TS = (Spinal schwannoma)) AND TS = (Imaging)) OR TS = (Spinal schwannoma)) AND TS = (image) to retrieve relevant articles. The collected data, including authors, keywords, journals, countries, institutions, and references, were subjected to visual analysis using the visualization software CiteSpace 6.4.2R and VOSviewer 1.6.19. A total of 310 relevant articles were identified. After further screening based on time limits, inclusion, and exclusion criteria, 179 articles were included in the study, consisting of 132 original articles and 42 reviews. These articles were authored by 1,034 authors from 35 countries and 324 institutions and were published in 82 different journals. The included articles cited a total of 6,583 references from 1,314 journals. Although the field of spinal schwannoma imaging research is not a popular research area in the medical community, there has been an increasing international interest in this field in recent years. While China ranks high in terms of the number of published articles, there is still a gap in terms of the quality and research level compared to developed countries in Europe and America. MRI, as the gold standard for diagnosing spinal schwannomas, is expected to be a research hotspot in terms of feature analysis, enhancement characteristics, and quantitative analysis. It is also hoped that China can increase its investment in research and contribute to the field by publishing high-quality articles in the future.

Current Status, Hotspots, and Trends of "Artificial Intelligence + Education" Research in China

The rapid development of artificial intelligence technology is profoundly leading education towards an intelligent direction. This article takes the literature related to "Artificial Intelligence + Education" published in the core journals of CSSCI from 2013 to 2024 as the research object, and uses the CiteSpace tool for visualization analysis. It combs and discusses the current status of domestic research in this field from aspects such as publication status, authors, institutions, and keyword co-occurrence and burst words, analyzes research hotspots, and predicts research trends. The results show that: in the past decade, the number of publications in this field in China can be divided into three stages: preliminary exploration, rapid development, and steady growth; some high-productivity authors have gradually formed a core group of authors, showing an overall development trend of multi-author cooperation and multi-unit collaboration; the types of publishing institutions are mainly normal colleges and departments of colleges and universities, with relatively low participation of enterprises and government institutions; research hotspots focus on three aspects: educational reform, categories of education, and educational technology, revealing the active exploration of the education field for intelligent technology; with the transformation of education and the development of technology, the combination of artificial intelligence and digital economy, new requirements for citizens' core literacy, and new challenges for teachers' professional literacy and educational models have become hot topics in current artificial intelligence research.

Current Utilization and Research Status of Herbal Medicine Sipjeondaebotang for Anemia: A Scoping Review.

Anemia is a global health issue affecting diverse populations, particularly older adults, and conventional treatments often show limited efficacy. This study aimed to evaluate the utilization and effectiveness of Sipjeondaebotang (SDT), a prescription drug used in traditional East Asian medicine, in treating various types of anemia. A scoping review was conducted following Arksey and O'Malley's framework and PRISMA-ScR guidelines. Six electronic databases were searched for clinical studies on SDT, while focusing on human participants and excluding animal and cellular studies. Sixteen studies, including nine randomized controlled trials, two controlled clinical trials, two case series, and three case reports, involving 863 participants, were analyzed. These studies were primarily conducted in China, Korea, and Japan. According to the analysis, SDT improved hemoglobin levels across all types of anemia studied, with all controlled studies showing significant improvements compared with the control groups. Additionally, SDT reduced blood loss, improved recovery times, and decreased transfusion requirements in patients with post-operative anemia, with lower adverse event rates than those in the control groups. These findings suggest that SDT may enhance hematological parameters and improve overall patient outcomes. In conclusion, SDT may be an effective treatment for anemia that improves hemoglobin levels and patient outcomes. However, further high-quality, large-scale studies are necessary to standardize SDT prescriptions, confirm the optimal treatment duration, and validate its efficacy and safety across different anemia types.

Factors influencing high-tech startup business model innovation in China: A systematic literature review

Business model innovation (BMI) has garnered substantial academic and corporate attention in recent decades. Researchers have not yet agreed on the most complicated BMI practices in the high-tech startups (HTS). Despite being the second-biggest economy in the world today, China has done little research on the practice of business model innovation in China’s high-tech startups. This study addresses the factors that impact the business model innovation of high-tech startups in China. Our study aims to fill the research gap by visualising and analysing, using systematic literature review (SLR) analyses and reviewing 36 in-depth articles, from 688 academic literature sources. Relevant publications from Scopus, Springer, ScienceDirect, Web of Science, IEEE Xplore, and the JDM e-library expose the current research status from 2013 to December 2023 without bias. We conducted a literature-based investigation to identify essential insights on the BMI factors in the literature and derived a high-tech startup’s BMI critical factor. Our study shows that three main factors affect the innovation of business models in high-tech startups in China. The findings raise managers’, entrepreneurs’, and executives’ knowledge of corporate resource bricolage and cognitive style constraints in business model innovation and their pros and cons. The findings will help Chinese academics understand enterprises’ institutional environment and resource bricolage as final suggestions and proposals for corporates, regulators, and policymakers are presented.

Review of the Practice and Research on the Integration of International Curriculum in Chinese Schools

With the acceleration of globalization, the integration of international curricula has become increasingly important in the field of Chinese education, aiming to cultivate talents with a global perspective and local wisdom. This review, through an in-depth examination of existing literature, reveals the current research status and trends in the field of international curriculum integration. The study finds that, despite significant progress in the introduction of curriculum systems, innovation in teaching models, and professional development of teachers, there are still issues such as insufficient exploration of the correlation between teaching models and student learning outcomes, a lack of systematic research on curriculum localization and cross-cultural competence development, and a need for more in-depth strategies to support the professional growth of teachers. Therefore, future research needs to further explore the empirical effects of teaching model innovations, systematic strategies for curriculum localization, and multi-dimensional approaches to promote the professional development of teachers, in order to advance the integration of international curricula and improve the quality of education.

A review of RIS-assisted wireless communication research

This paper presents a review of the research progress in Reconfigurable Intelligent Surface (RIS) assisted wireless communications. It begins by providing an overview of recent developments and trends in the field of wireless communications. The following sections introduce the fundamental principles of both RIS technology and wireless communication technology, providing a foundation for the subsequent comprehensive examination of the current research status of RIS-assisted wireless communication. This study then turns to an in-depth analysis of the advancements in RIS-assisted wireless communication research, encompassing hardware regulation, baseband algorithms, multi-access enhancement, and network design. Subsequently, this paper offers a concise examination of the opportunities and challenges associated with RIS in wireless communication. This paper closes with a summary of the field of RIS-assisted wireless communication, followed by an outlook on future directions.

Fabric-based intelligent fire-warning and flame-retardant coating: A review of advances, challenges and prospects

Fabric-based fire-warning and flame-retardant coatings could achieve dual functions of active warning response and passive fire retardancy. In contrast to conventional fire detection systems that necessitate installation at designated locations, the contact surface between the coating sensing material and the flame is substantially augmented. Therefore, it possesses crucial application value in enhancing the warning efficiency and fire safety performance of flammable substrates. This review primarily delved into the flame retardancy and fire warning of fabric coating materials. It thoroughly examined the current research status of fabric-based flame-retardant coatings and analyzed the fire-warning mechanisms of voltage-based and resistance-based coatings. Furthermore, this comprehensive review elucidated the research and current applications of various coatings based on sensing materials such as graphene oxide, carbon nanotubes, and MXene in the fire warning and flame resistance. Additionally, it is worth noting that the current functionality of fabric-based coatings is relatively limited, necessitating the incorporation of multi-functionality to adapt to various usage scenarios. In addition, it is necessary to develop large-scale coating preparation technique to achieve commercial production and combine artificial intelligence technology to achieve higher-level fire warning and flame-resistant application. Finally, the future development trend of the fabric-based coating was prospected.

Advances in Research for Mechanical Characteristics of Vertically Loaded Anchors for Offshore Platforms under Cyclic Loads

Vertically loaded anchors (VLAs) are widely used as mooring foundations in marine environments. Their working conditions typically involve deep-sea seabed, frequently subjected to cyclic loads induced by wind, waves, and currents. Therefore, understanding the mechanical properties of VLAs under cyclic loading is essential for ensuring the safety of mooring systems. This paper summarizes the current research status on the mechanical properties of VLAs under cyclic loading, analyzing the mechanisms by which cyclic loads affect these properties. Additionally, it reviews and summarizes the research methods applied to studying VLAs under cyclic loading, discussing the issues inherent in various methodologies. Finally, it provides an outlook on future research into VLAs under cyclic loading, laying the groundwork for subsequent studies on the bearing mechanisms of novel VLAs, such as the double-plate vertically loaded anchor (DVLA), under cyclic loading.

Current research status of virus-like particle vaccine

Virus-like particles (VLPs) are self-assembled protein nanoparticles with repetitive antigen epitopes, which can stimulate immune response and do not contain viral genetic materials. VLPs has important research value and application potential in vaccine development, targeted drug delivery and bioengineering materials. In this review, the mechanism of VLPs vaccine induced immune responses is discussed. The existing VLPs expression systems are summarized. The research progress of VLPs vaccine in prevention and treatment of virus infection are summarized. This review provides general reference and guidance for the design and development of antiviral VLPs vaccine.