Emerging Research Directions Research Articles

Report on the Second International Workshop on DataSystems Education (DataEd '23)

This report summarizes the outcomes of the second international workshop on Data Systems Education: Bridging Education Practice with Education Research (DataEd '23). The workshop was held in conjunction with the SIGMOD '23 conference in Seattle, USA on June 23, 2023. The aim of the workshop was to provide a dedicated venue for presenting and and discussing data management systems education experiences and research by bringing together the database and the computing education research communities to share findings, to crosspollinate perspectives and methods, and to shed light on opportunities for mutual progress in data systems education. The program featured two keynote talks, eight research paper presentations, and a discussion session. In this report, we present the workshop's main results, observations, and emerging research directions.

The frontier of precision medicine: application of single-cell multi-omics in preimplantation genetic diagnosis.

The advent of single-cell multi-omics technologies has revolutionized the landscape of preimplantation genetic diagnosis (PGD), offering unprecedented insights into the genetic, transcriptomic, and proteomic profiles of individual cells in early-stage embryos. This breakthrough holds the promise of enhancing the accuracy, efficiency, and scope of PGD, thereby significantly improving outcomes in assisted reproductive technologies (ARTs) and genetic disease prevention. This review provides a comprehensive overview of the importance of PGD in the context of precision medicine and elucidates how single-cell multi-omics technologies have transformed this field. We begin with a brief history of PGD, highlighting its evolution and application in detecting genetic disorders and facilitating ART. Subsequently, we delve into the principles, methodologies, and applications of single-cell genomics, transcriptomics, and proteomics in PGD, emphasizing their role in improving diagnostic precision and efficiency. Furthermore, we review significant recent advances within this domain, including key experimental designs, findings, and their implications for PGD practices. The advantages and limitations of these studies are analyzed to assess their potential impact on the future development of PGD technologies. Looking forward, we discuss the emerging research directions and challenges, focusing on technological advancements, new application areas, and strategies to overcome existing limitations. In conclusion, this review underscores the pivotal role of single-cell multi-omics in PGD, highlighting its potential to drive the progress of precision medicine and personalized treatment strategies, thereby marking a new era in reproductive genetics and healthcare.

Subscriber retention management: SRM framework and future research agenda

Purpose This article aims to systematically review the fragmented but increasingly relevant research field of customer retention management in subscription scenarios, proposing the subscriber retention management framework for retention management in subscription settings and directing future research. Design/methodology/approach The authors systematically reviewed 1,295 articles to offer a comprehensive, unbiased overview on customer retention management in subscription-based services. From 122 selected articles, the authors conducted a descriptive analysis, conceptualized key insights into a novel framework and recognized research gaps. Findings Among 122 articles, 111 focus on private customers across various service sectors, while lacking reflection on new digital industries, reactive retention and the corporate context. The conceptualization of results merges existing insights into seven dimensions, encompassing strategic and tactical aspects and the interplay of controllable and uncontrollable factors. The authors also outline 12 emerging research directions. Research limitations/implications Given the extensive body of literature, the authors were unable to delve into detailed explanations. The findings are limited to management science research sourced from Scopus, adhering to a rigorous filtering process. Sub-domains, such as reactive or business-to-business retention management, remain somewhat provisional due to little results. Practical implications A sustainable subscriber retention strategy hinges on: (1) integrating retention into business strategy, (2) adjusting acquisition and retention tactics to specific markets and (3) using a consistent retention marketing mix considering affective, calculative and habitual commitment factors. Originality/value The authors contribute with a first systematic review of subscription-specific retention management in a rapidly growing area. This results in a novel framework that broadens the understanding of subscriber retention and identifies research gaps.

FGTL: Federated Graph Transfer Learning for Node Classification

Unsupervised multi-source domain transfer in federated scenario has become an emerging research direction, which can help unlabeled target domain to obtain the adapted model through source domains under privacy-preserving. However, when local data is graph, the difference of domains (or data heterogeneity) mainly originate from the difference in node attributes and subgraph structures, leading to serious model drift, which is not considered by the existing related algorithms. Currently, there are two challenges in this scenario: (1) The node representations extracted directly through conventional GNNs lack inter-domain generalized and consistent information, making it difficult to apply existing federated learning algorithms. (2) The knowledge of source domains has quality differences, which may lead to negative transfer. To address these issues, we propose a novel two-phase Federated Graph Transfer Learning (FGTL) framework. In the generalization phase, FGTL utilizes local contrastive learning and global context embedding to force node representations to capture the inter-domain generalized and consistent information, lightly alleviating model drift. In the transfer phase, FGTL utilizes consensus knowledge to force the decision bound of classifier to adapt to the target client. In addition, FGTL+ exploits model grouping to make consensus knowledge generation more efficient, further enhancing the scalability of FGTL. Extensive experiments show that FGTL significantly outperforms state-of-the-art related methods, while FGTL+ further enhances privacy protection and reduces both communication and computation overhead.

Trends and Future Directions in Analysing Attractiveness of Geoparks Using an Automated Merging Method of Multiple Databases—R-Based Bibliometric Analysis

Since their creation, geoparks have been among the fastest growing natural environments. Their attractiveness is one of the most important factors for the success of this natural destination. Despite their importance, a bibliometric analysis on geopark attractiveness is missing from the studied databases. The aim of this paper is to synthesise a heterogeneous body of knowledge of geoparks in terms of attractiveness, highlighting the evolution and breadth of the research field. To achieve this, the following objectives were set: (a) to adopt a method based on functions provided by the bibliometrix package to automatically combine databases, namely WoS, Scopus, PubMed and Dimensions, detailing the method used and (b) to analyse the bibliometric indicators in order to identify the trends in the literature and the possible directions for future research. The applied methodology was based on bibliometric analysis using R for non-coders. From the 707 documents retrieved, the validation process resulted in 349 eligible documents published between 2002 and 2024, on which the analysis was carried out. The current study elaborated a method and examined the key information on the topic trends, which were given by production performance, productivity trends, spatial analysis and abstract approach analysis. Additionally, strategic mapping of the conceptual context was performed. Thus, the result provides a description of the automatic method with practical applications. As discerned from the three-dimensional analysis (spatial, temporal and size), the emerging research directions within scientific creativity encompassed (1) forms of tourism practiced in geoparks, especially focused on ecotourism and volcanic tourism; (2) geomorphological features, mineral springs and mud volcanoes; (3) aesthetic aspects, scenic sites and mining heritage; and (4) methodology, data analysis and modelling methods across different regions and countries.

Global trends and emerging topics related to triglyceride-glucose index: A bibliometric analysis and visualization from 2000 to 2024.

The triglyceride-glucose (TyG) index is a crucial marker of insulin resistance, as evidenced by numerous studies related to metabolic diseases. This bibliometric analysis investigates research trends associated with the TyG index over the past 24 years. We collected data on TyG index publications from January 1, 2000, to January 7, 2024, using the Web of Science database. Analysis was conducted utilizing VOSviewer, Scimago Graphica, and CiteSpace to evaluate publication metrics, citations, countries, institutions, authors, journals, and keywords. A total of 1163 publications from 354 journals authored by 6149 researchers across 60 countries were analyzed. China emerged as the leading contributor, with 654 publications (56.23%). Capital Medical University was the most productive institution, and Wu Shouling was the top author. Cardiovascular Diabetology was identified as the most influential journal. Key emerging research directions include the role of the TyG index as a representative marker for insulin resistance, particularly concerning insulin sensitivity; its association with body mass index and hyperuricemia; and its diagnostic and prognostic value in nonalcoholic fatty liver disease and cardiovascular conditions such as acute coronary syndrome, carotid plaque, and hypertension. Current trends favor cohort studies predominantly involving adult populations. Overall, China leads TyG index research, focusing on its connections to insulin sensitivity, body mass index, and hyperuricemia, while the index's diagnostic and prognostic significance for nonalcoholic fatty liver disease and cardiovascular diseases represents an expanding research frontier.

Inflammation, tertiary lymphoid structures, and lung cancer: a bibliometric analysis.

The intricate interplay between inflammation and lung cancer has long been recognized by large number of studies, yet a comprehensive understanding of this relationship remains elusive. There is a clinical need to elucidate the role of tertiary lymphoid structures (TLSs) in lung cancer, particularly their impact on prognosis and therapy. This study aims to address these gaps by conducting a bibliometric analysis to explore the correlations between lung cancer, inflammation, and TLS, highlighting collaborative networks, publication trends, and emerging research directions. This study conducted a comprehensive bibliometric analysis of academic literature on lung cancer and inflammation from 2013 to 2023 using the Web of Science Core Collection database. The search strategy "topic (TS) = ('lung cancer') AND TS = (inflammation)" yielded 5,470 records, which were refined through exclusion criteria to 1,284 relevant studies. The inclusion process involved excluding non-English studies and non-original articles or reviews, followed by a relevance check based on titles and abstracts. The bibliometric indicators were calculated based on a transparent and repeatable methodology to ensure the integrity of the findings. The investigation encompassed 1,284 selected studies, revealing an escalating publication trend since 2013. The interdisciplinary scope of research is apparent, with contributions from 54 countries, with China at the forefront. In-depth author and journal analyses exposed key contributors like Zhang L and influential journals like "Lung Cancer". Co-citation networks illuminated crucial references, clusters, and evolving themes over time, underscoring the intricate relationship between inflammation, cancer, and TLS. TLS as a key component of immune response and inflammation, studying its mechanism of impact on cancer will be a potential research direction in the future. This study underscores the pivotal role of inflammation in lung cancer progression, mediated by a delicate balance of immune responses. The emerging prominence of TLS as indicator of adaptive immune responses within the tumor microenvironment (TME) offers intriguing avenues for future research and therapeutic interventions. However, limitations in the current research, such as the need for more longitudinal studies and clinical trials, must be addressed. The insights gained from this bibliometric analysis can inform clinical practices and guide future investigations into novel strategies to improve patient outcomes.

Nano Photocatalysis: Pioneering Progress and Industrial Applications for Sustainable Environmental Solutions

Nano photocatalysis has become a cornerstone technology in environmental sustainability. This paper delves into the significance of nano photocatalysis, highlighting its mechanisms, industrial applications, and benefits for sustainable development. By reducing industrial pollution and enabling eco-friendly practices, nano photocatalysis offers an innovative approach to environmental challenges. Key sections address its role in water and air treatment, energy efficiency, and emerging research directions, making it a pivotal solution aligned with sustainable development goals

A Review of Renewable Energy Investment in Belt and Road Initiative Countries: A Bibliometric Analysis Perspective

Since the proposal of the “Belt and Road” initiative (BRI) in 2013, China’s renewable energy investments in the countries along the route have shown rapid growth and diversification. These investments have shifted from initial product exports and engineering contracts to deeper equity investments and financing cooperation. They not only promote a global energy structure transformation towards green and low-carbon development but also bring significant economic growth and social progress to the participating countries. This study aims to systematically review the research status and trends of renewable energy investments in “Belt and Road” countries through comprehensive bibliometric analysis. Utilizing the Web of Science database and VOS viewer 1.6.17 software for visualization, this research reveals the publication trends, high-impact articles, institutional collaborations, and author networks in this field. Additionally, through keyword co-occurrence network analysis, three core research themes are identified: investment motivations, synergy effects, renewable energy consumption, and international cooperation. This systematic bibliometric analysis not only outlines the current research landscape but also provides important insights for identifying emerging research directions, thereby supporting more in-depth investigations into renewable energy investments within the “Belt and Road” initiative.

Hydrogen-Induced Topotactic Phase Transformations of Cobaltite Thin Films.

Manipulating physical properties through ion migration in complex oxide thin films is an emerging research direction to achieve tunable materials for advanced applications. While the reduction of complex oxides has been widely reported, few reports exist on the modulation of physical properties through a direct hydrogenation process. Here, we report an unusual mechanism for hydrogen-induced topotactic phase transitions in perovskite La0.7Sr0.3CoO3 thin films. Hydrogenation is performed upon annealing in a pure hydrogen gas environment, offering a direct understanding of the role that hydrogen plays at the atomic scale in these transitions. Topotactic phase transformations from the perovskite (P) to hydrogenated-brownmillerite (H-BM) phase can be induced at temperatures as low as 220 °C, while at higher hydrogenation temperatures (320-400 °C), the progression toward more reduced phases is hindered. Density functional theory calculations suggest that hydroxyl bonds are formed with the introduction of hydrogen ions, which lower the formation energy of oxygen vacancies of the neighboring oxygen, enabling the transition from the P to H-BM phase at low temperatures. Furthermore, the impact on the magnetic and electronic properties of the hydrogenation temperature is investigated. Our research provides a potential pathway for utilizing hydrogen as a basis for low-temperature modulation of complex oxide thin films, with potential applications in neuromorphic computing.

A Bibliometric Analysis of Teacher’s Turnover Intention

Aim. The purpose of this article is to review past research trends and explore emerging research directions on teachers’ turnover intentions. Methods. The authors used the co-citation method and bibliometric analysis using VOS Viewer software to review 137 publications mentioning teachers’ intention to leave. Results. The results of the co-citation analysis show that there are 4 main topics, while the results of the bibliographic coupling analysis show that there are 6 main topics in the study of teachers’ intention to quit. From there, it shows that future research trends can focus on specific teacher populations more likely to consider quitting and explore how various factors influence their intentions. Improving teachers’ professional environment to reduce professional burnout and increase job satisfaction is also an interesting future research aspect. Conclusions. In conclusion, this study contributes to the understanding of the literature by classifying studies on teachers’ turnover intention and identifying significant patterns through bibliometric method. However, the study’s limitations, as analyses rely solely on citations, potentially introduce biases; the interpretation of researchers in determining topics may lead to exclusions of emerging trends due to insufficiently gathered publications.

Data-Driven Materials Research and Development for Functional Coatings.

Functional coatings, including organic and inorganic coatings, play a vital role in various industries by providing a protective layer and introducing unique functionalities. However, its design often involves time-consuming experimentation with multiple materials and processing parameters. To overcome these limitations, data-driven approaches are gaining traction in materials science. In this paper, recent advances in data-driven materials research and development (R&D) for functional coatings, highlighting the importance, data sources, working processes, and applications of this paradigm are summarized. It is begun by discussing the challenges of traditional methods, then introduce typical data-driven processes. It is demonstrated how data-driven approaches enable the identification of correlations between input parameters and coating performance, thus allowing for efficient prediction and design. Furthermore, carefully selected case studies are presented across diverse industries that exemplify the effectiveness of data-driven methods in accelerating the discovery of new functional coatings with tailored properties. Finally, the emerging research directions, involving integrating advanced techniques and data from different sources, are addressed. Overall, this review provides an overview of data-driven materials R&D for functional coatings, shedding light on its potential and future developments.

A low redox potential and long life organic anode material for sodium-ion batteries

Sodium-ion batteries (SIBs) with organic electrodes are an emerging research direction due to the sustainability of organic materials based on elements like C, H, O, and sodium ions. Currently, organic electrode materials for SIBs are mainly used as cathodes because of their relatively high redox potentials (>1 V). Organic electrodes with low redox potential that can be used as anode are rare. Herein, a novel organic anode material (tetrasodium 1,4,5,8-naphthalenetetracarboxylate, Na4TDC) has been developed with low redox potential (<0.7 V) and excellent cyclic stability. Its three-sodium storage mechanism was demonstrated with various in-situ/ex-situ spectroscopy and theoretical calculations, showing a high capacity of 208 mAh/g and an average decay rate of merely 0.022% per cycle. Moreover, the Na4TDC-hard carbon composite can further acquire improved capacity and cycling stability for 1200 cycles even with a high mass loading of up to 20 mg cm−2. By pairing with a thick Na3V2(PO4)3 cathode (20.6 mg cm−2), the as-fabricated full cell exhibited high operating voltage (2.8 V), excellent rate performance and cycling stability with a high capacity retention of 88.7% after 200 cycles, well highlighting the Na4TDC anode material for SIBs.

New light-illuminated silk road: emerging silk fibroin-based optical biomedical sensors.

Biomedical silk protein optics has become the subject of intensive research aimed at solving the challenges associated with traditional medical devices in terms of biocompatibility and performance balance. With its significant potential for biomedical applications in the field of drug storage and wound monitoring, it is dedicated to reducing the perturbation of neighbouring tissues. The transparency and biocompatibility of silk proteins make them ideal materials in the field of optical device fabrication, effectively overcoming the challenges posed by conventional materials. In this paper, we explore in detail the complex aspects of the design, synthesis and application related to biomedical silk protein optical devices and comprehensively analyse the potential use of silk protein-centric microstructures (e.g., micropillars, microneedles, and photonic crystals) in the development of optical devices. This review also offers insights into the challenges of applying silk protein optical devices in healthcare and their future trends, aiming to provide a comprehensive overview of the advances, potential impacts and emerging research directions in the field of biomedical silk protein optical devices.

A Comprehensive Review of Metabolic Syndrome and Its Role in Cardiovascular Disease and Type 2 Diabetes Mellitus: Mechanisms, Risk Factors, and Management.

Metabolic syndrome is a multifaceted metabolic disorder characterized by a constellation of interconnected risk factors, including insulin resistance, abdominal obesity, dyslipidemia, and hypertension. These components collectively predispose individuals to an elevated risk of cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM). The prevalence of metabolic syndrome has escalated globally, paralleling the rise in obesity rates and sedentary lifestyles. This review explores the pathophysiology underlying metabolic syndrome, emphasizing its role in the development and progression of CVD and T2DM. Epidemiological data underscore the substantial public health burden metabolic syndrome poses, necessitating effective preventive strategies and management approaches. The current diagnostic criteria and screening tools are discussed, highlighting their utility in clinical practice. Management strategies encompass lifestyle modifications, pharmacotherapy, and surgical interventions, each targeting specific components of metabolic syndrome to mitigate cardiovascular and metabolic risks. The challengesin diagnosing and managing metabolic syndrome are addressed alongside emerging research directions to enhance prevention and treatment outcomes. By elucidating the intricate relationship between metabolic syndrome, CVD, and T2DM, this review aims to guide healthcare practitioners in optimizing patient care and advancing public health initiatives to combat this pervasive syndrome.

EVs as biomarkers of cardiovascular disease

Exosomes are an emerging research direction in biology, and their current definition is: Exosomes are small vesicles (30-150nm) containing complex RNA and proteins, and nowadays, they are specifically dish-like vesicles with diameters of 40-100nm. Many cells can produce exosome under physiological or physiological conditions. The mechanism is formed by the deposition of polyvesicles after binding to the extracellular membrane. Therefore, it can be seen from this definition that exosomes are a general term for a large class of vesicle-wrapped biological contents, which are physiological substances used by organisms to maintain normal physiological activities. Therefore, exosomes have a very rich classification, subclasses, and subsets.

Investigating underlying molecular mechanisms, signaling pathways, emerging therapeutic approaches in pancreatic cancer.

Pancreatic adenocarcinoma, a clinically challenging malignancy constitutes a significant contributor to cancer-related mortality, characterized by an inherently poor prognosis. This review aims to provide a comprehensive understanding of pancreatic adenocarcinoma by examining its multifaceted etiologies, including genetic mutations and environmental factors. The review explains the complex molecular mechanisms underlying its pathogenesis and summarizes current therapeutic strategies, including surgery, chemotherapy, and emerging modalities such as immunotherapy. Critical molecular pathways driving pancreatic cancer development, including KRAS, Notch, and Hedgehog, are discussed. Current therapeutic strategies, including surgery, chemotherapy, and radiation, are discussed, with an emphasis on their limitations, particularly in terms of postoperative relapse. Promising research areas, including liquid biopsies, personalized medicine, and gene editing, are explored, demonstrating the significant potential for enhancing diagnosis and treatment. While immunotherapy presents promising prospects, it faces challenges related to immune evasion mechanisms. Emerging research directions, encompassing liquid biopsies, personalized medicine, CRISPR/Cas9 genome editing, and computational intelligence applications, hold promise for refining diagnostic approaches and therapeutic interventions. By integrating insights from genetic, molecular, and clinical research, innovative strategies that improve patient outcomes can be developed. Ongoing research in these emerging fields holds significant promise for advancing the diagnosis and treatment of this formidable malignancy.

Resilience in supply chain risk management in disruptive world: rerouting research directions during and after pandemic

AbstractThe pandemic and a series of subsequent disruptive events fully exposed the vulnerability of supply chains. Research in the field of resilience in supply chain risk management has recorded significant interest across a wide range of academic disciplines. Therefore, there is a need to synthesize, categorize and explain existing and newly emerging research directions, which may represent relevant platforms for developing supply chain concepts in the future. This study addresses this need by providing a bibliometric review of published papers on resilience in supply chain risk management. By analyzing more than 2500 published papers through bibliometric and machine-learning-based methods, we identified ten topics related to risk and resilience of supply chains: Pandemic impacts of food supply chain; Practices for capability and performance; Supplier-related modeling and optimization; System security and critical infrastructure; Production changes; IT in manufacturing process; Sustainability in global economy; Management and business approach; Modeling and design of complex networks; Operational strategies for risk mitigation. By analyzing articles published since 2020, we also identified a change in the direction of research dedicated to supply chain risk and resilience; we identified three other topics that were not recognized as distinct topics prior to 2020—Operational management; strategy; Sustainable production. The results of this study help in understanding the change in the direction of research in the area of risk and resilience of supply chains and thus provide up-to-date information for further research in this dynamically developing area.

Recent Advances in Understanding and Management of Arteriovenous Malformations of the Temporal Skin Area

Context: Arteriovenous malformations (AVMs) of the temporal skin area, though less common than cerebral AVMs, pose significant challenges in terms of cosmetic and functional outcomes. Over the past decade, substantial advancements have been made in the understanding and management of these lesions. This paper aims to review the latest developments in the pathophysiology, diagnosis, and treatment of temporal skin AVMs, and to explore ongoing challenges and emerging research directions. Evidence Acquisition: A comprehensive literature search was conducted using databases such as PubMed, Scopus, and Google Scholar. The focus was on research published in the past ten years related to temporal skin AVMs, including reviews, clinical studies, and advancements in treatment techniques. Results: The review discusses the evolution in understanding the pathophysiology of temporal skin AVMs, improvements in diagnostic imaging techniques, and the refinement of surgical and non-surgical treatment approaches. The outcomes, including cosmetic and functional results, and complications associated with various treatments, are also presented. Conclusions: The management of temporal skin AVMs has benefited from multidisciplinary approaches, combining surgery, interventional radiology, and dermatology. However, challenges remain in achieving optimal cosmetic and functional outcomes, necessitating ongoing research and innovation.

Neuroplasticity and Rehabilitation: Harnessing Brain Plasticity for Stroke Recovery and Functional Improvement

This paper provides a comprehensive review of the current understanding of neuroplasticity and its application in stroke rehabilitation. Stroke remains a leading cause of disability worldwide, often resulting in motor, sensory, and cognitive impairments. Neuroplasticity, the brain's ability to reorganize and adapt in response to experience and injury, offers promising avenues for recovery. This review discusses key principles of neuroplasticity and explores various rehabilitation strategies aimed at harnessing its potential for stroke recovery. Topics covered include early intervention, task-specific training, intensity and repetition, constraint-induced movement therapy, multimodal approaches, environmental enrichment, and neurostimulation techniques. Additionally, the paper discusses emerging research directions and challenges in optimizing neuroplasticity-based rehabilitation approaches. Understanding the role of neuroplasticity in stroke recovery can inform the development of more effective rehabilitation interventions and improve outcomes for individuals affected by stroke.