Graphene has obtained an adorable response from researchers and scientists owing to its meticulous structure and astonishing properties. The rapid evolution of research on the electronic properties of graphene has generated a vast and complex body of literature, necessitating systematic quantitative mapping to understand its intellectual structure and developmental trajectory. In this study, a comprehensive citation analysis of global research on the electronic properties of graphene has been performed. Bibliographic records were retrieved from the Web of Science (WoS) Core Collection covering the period from January 2004 to March 2025. Two specialized bibliometric software tools were employed to construct citation networks, visualize relational structures, and evaluate influential publications, authors, and countries. Sankey plot was generated to visualize the relationships among key authors, cited references, and keywords, thereby providing an initial structural overview of the dataset. Direct citation analysis is employed to trace the chronological knowledge flow and identify seminal contributions shaping the field. Network centrality indicators and clustering metrics are applied to identify influential authors, countries, and core publications. Various bibliometric indicators like number of documents, total linking strength, number of citations and normalized citations have been used in the analysis, as they reflect different aspects of contribution. Normalised citations have been evaluated from the Vosviewer map file by writing a Python script. Bibliographic coupling is used to detect contemporary research clusters and emerging thematic frontiers, while co-citation analysis reveals the foundational intellectual base and conceptual interconnections within the domain. By integrating three complementary citation methods, this study provides a structured overview of the knowledge architecture governing research on the electronic properties of graphene. The findings serve as a reference framework for researchers seeking to understand both the maturity and emerging opportunities within this rapidly advancing field.

Atom-centered electric multipole moments can be extremely useful in chemistry, as they enable the systematic mapping of a complex electrostatic problem to a simpler model. However, since they do not correspond to physical observables, there is no unique way to define them. In this study, we present an extension of the dynamically generated RESP charges (D-RESP) method, referred to as xDRESP, where atom-centered multipoles are computed from mixed quantum mechanics/molecular mechanics molecular dynamics simulations. We compare the ability of xDRESP charges to reproduce the electrostatic potential, as well as molecular multipoles, against the performance of fixed point-charge models commonly used in force fields. Moreover, we highlight cases where xDRESP atomic multipoles can provide valuable information about chemical systems, such as indicating when polarization plays a significant role, and chemical reactions in which xDRESP atomic multipoles can be used as an on-the-fly analysis tool to track changes in electron density.

This study systematically analyzed research trends in aquaculture wastewater treatment from 2000 to 2024 using bibliometric methods. Through knowledge mapping and keyword co-occurrence analysis conducted with Citespace6.1 software on the Web of Science Core Collection and the CNKI (China National Knowledge Infrastructure) Core Journal Database, we aimed to elucidate the distribution characteristics, evolution of research hotspots, and differences in technological pathways within the existing research landscape, while identifying gaps in integrated knowledge synthesis and cross-regional comparative analysis. The results indicate: (1) China’s publication output in this field over the past five years has significantly surpassed international levels, reflecting an imbalance in regional research activity; (2) antibiotics, nitrogen and phosphorus, organic pollutants, and heavy metals constitute the primary pollutant categories, with increasing attention focused on antibiotic and heavy metal pollution in recent years; (3) domestic research demonstrates a preference for natural ecological treatment technologies, whereas international research is predominantly oriented toward biological treatment technologies. By integrating Chinese- and English-language literature data with visual analytics, this study addresses the existing gap in systematic knowledge mapping and comparative analysis of regional technological pathways, and highlights the ongoing paradigm shift from pollution elimination toward resource recovery. The findings provide an empirical basis for formulating differentiated regional governance policies and guiding investments in low-carbon and environmentally friendly technology research and development, thereby promoting the transition of the aquaculture industry toward green and sustainable development.

A roadmap for federated learning projects using health data to guide sustainable artificial intelligence development in the European Union.

P0436 Diagnostic value of combined transperineal MRI-targeted and systematic mapping biopsies: Diagnostic contribution of secondary and tertiary lesions

Artificial intelligence in web accessibility: A systematic mapping study

Symptom-specific neural circuits and corresponding transcriptomic profiles in depression.

Systematic mapping study to assess security landscape for IoT-based smart farming systems

Advanced technologies and complementary or adjunctive interventions are increasingly used for chronic or recurrent orofacial pain (OP), but comparative evidence remains fragmented across diagnoses, modalities, and outcomes. We conducted a systematic evidence map with selective meta-analyses (PROSPERO CRD420251270501) following PRISMA 2020. Six databases were searched from inception to 31 December 2025 for randomized and non-randomized intervention studies in adults with temporomandibular disorders (TMD), burning mouth syndrome (BMS), trigeminal neuralgia (TN), and other chronic or recurrent orofacial pain phenotypes. Two reviewers independently screened records, extracted data, assessed risk of bias using validated tools, and rated certainty with GRADE. Random-effects meta-analyses of randomized comparisons used standardized mean differences within prespecified follow-up windows and reported prediction intervals. Pain intensity was prioritized, and disability, jaw function, quality of life, global improvement, medication outcomes, and adverse events were extracted when available. We included 130 studies (n = 6879 participants). Non-randomized intervention studies were retained to widen the evidence map and to capture feasibility, durability, and safety signals that are often underrepresented in early randomized trials. These studies were synthesized narratively and did not contribute to pooled comparative estimates or to certainty upgrading. Low risk of bias was uncommon, and reporting of function, quality of life, and harms was inconsistent, which limited pooling. Safety outcomes were not reported in 37 of 130 included studies, and denominators were often unclear, which limits risk-benefit interpretation. In BMS, photobiomodulation or low-level laser therapy (PBM/LLLT) versus inactive control reduced short-term pain (k = 6, N = 200, standardized mean difference - 0.81, 95% CI - 1.35 to - 0.27). The 95% prediction interval crossed the null (- 1.80 to 0.17), while certainty was moderate. Most pharmacologic and supplement interventions for BMS showed uncertain or inconsistent effects. For TMD, effects varied by modality and comparator and were generally low or very low certainty. Evidence for TN and digital therapeutics was sparse, and adverse-event reporting was inconsistent. PBM/LLLT shows the clearest short-term analgesic signal for BMS versus inactive control, but transportability remains uncertain given null-crossing prediction intervals and limited long-term data. Future trials should standardize outcomes, extend follow-up, and report harms transparently to support diagnosis-stratified care.

This research is motivated by the rapid development of scientific publications in Indonesia, which requires systematic mapping to understand the direction of global scientific development. The main objective of this study is to map the bibliometric landscape of research in Indonesia through the Web of Science (WOS) database to identify annual trends, dominant themes, and future research directions. The method used is descriptive bibliometric analysis and network visualization using VOSviewer software on publication data for the period 2004-2026. The research findings indicate a highly exponential growth of publications, reaching a peak in 2025 with a contribution of 35.6% of the total literature. Dominant themes are concentrated in the management, economics, and education clusters, with sustainability and digital innovation emerging as the latest research trends. The National Research and Innovation Agency (BRIN) emerged as the most productive institution, while the field of financial management recorded the highest citation impact. The study's conclusions confirm that research in Indonesia has transformed towards an internationally competitive multidisciplinary approach. Going forward, it is recommended to explore thematic areas with low density to fill the remaining research gaps.

CVD Environmental Health Disparities Tool: systematic evidence mapping of psychosocial stressors, environmental exposures, and cardiovascular diseases to inform disparities research and action.

The accelerating pace of digital innovation presents new governance challenges, necessitating the establishment of robust policy, legislative, and institutional frameworks to mitigate risks and maximize sustainability benefits. This study examines the intersection between digital transformation (DT), governance, and sustainability within the context of the United Nations Sustainable Development Goals (SDGs). The purpose of this study is to synthesize and critically evaluate the evidence on how DT governance influences progress toward the SDGs. Using a systematic mapping and structured qualitative evidence synthesis, aligned with PRISMA 2020 guidelines, the study reviews peer-reviewed literature published between 2015 and 2024 on the governance of DT in relation to the SDGs. Sixty-five studies were analyzed across governance scales, digital technologies, and sustainability dimensions. The findings reveal strong optimism regarding DT contributions to the SDGs, alongside persistent governance gaps, contextual inequalities, and underexamined trade-offs. To address these gaps, the study proposes an evidence-informed framework for sustainable DT governance that integrates inclusivity, adaptability, transparency, and multi-stakeholder collaboration. The framework is positioned relative to existing digital and sustainability governance models and highlights implementation challenges, particularly in low- and middle-income country contexts. The results advance policy-relevant insights for aligning digital innovation with long-term sustainability objectives.

Single-molecule force spectroscopy (SMFS) is a powerful tool to measure how biomolecules respond to mechanical force, but limited sequence throughput constrains its potential. Here, we present a single-molecule, multiplexed, microfluidic force spectroscopy (SM 3 FS) assay that uses parallelized microfluidics to measure up to 80 sequence variants per experiment. Using SM 3 FS, we stretched, overstretched, or unzipped 241 different DNA structures and generated 131,847 single-molecule traces from a quarter-million observations. High sequence throughput allowed us to identify DNA structures that are kinetically stable yet mechanically fragile (F rupture < 3 pN at 0.5 pN s -1 ), revealing how mechanosensitivity can arise as an intrinsic property of multivalent systems. By enabling systematic sequence-function mapping under force, SM 3 FS opens a path to high-throughput nonequilibrium studies of biomolecules.

The psychosocial consequences of conflict and trauma exposure place a significant burden on individuals, communities, and on the social fabric essential for rebuilding peace. There is growing recognition of the need to integrate trauma-informed approaches into peacebuilding efforts. However, little is known about how practitioners are being equipped for this work, what training programs exist, and what core components they include. This systematic mapping review aims to systematically map and characterize existing training programs on trauma-informed peacebuilding, specifically examining their core components and implementation modalities. An initial systematic search of bibliographic databases (Web of Science, Scopus, PubMed) yielded no relevant results. Therefore, a systematic web search of non-bibliographic material was conducted in line with Cochrane's guidelines. A total of 2,400 results were screened, and 21 relevant training initiatives were included. The review identified 15 facilitated and six non-facilitated programs. Training providers were primarily non-governmental organizations based in high-income Western countries, with half of all programs originating in the United States. Thematic analysis of training contents revealed seven core components: (1) defining and conceptualizing trauma, (2) realizing the impact of trauma on peace and peacebuilding efforts, (3) self-care and resilience strategies for peace practitioners, (4) psychosocial support skills to address trauma and foster resilience in communities, (5) integrating trauma-informed practices into programs and organizations, (6) ethical considerations, and (7) cultural competence and contextual awareness. Despite increasing demand, training efforts in trauma-informed peacebuilding remain fragmented, unevenly distributed, and unevaluated. This review highlights the need for more accessible, contextually relevant, and evidence-informed training initiatives. Recommendations are provided to guide future training development and inform policy and practice aimed at strengthening trauma-informed capacities in peacebuilding.

The modern Indian classical and folk fusion music has become an important musical trend shaped by the increased globalization, the digital spreading, and the transnational artistic interaction. Although these fusion practices are commonly loosely grouped into the term of a world music, the available literature rarely constructs systemic frameworks to examine the manner in which particular global musical influences interact with the Indian musical systems both structurally and aesthetically. This gap is filled in this paper when the author presents the concept of global resonances as an analytical tool to evaluate mutual relations of Indian classical and folk traditions and global musical idioms. Based on interdisciplinary interpretations of ethnomusicology, cultural studies, and globalization theory, the paper offers a Global Resonance Mapping theory in order to classify and evaluate the musical influences in the world in various dimensions, such as rhythm, harmony, instrumentation, vocal aesthetics, form, and production practices. The research design is a qualitative and mixed-methods study that examines a purposely chosen collection of modern fusion work that covers in the styles of classical-rooted, folk-rooted and global-genre-led. Comparative case study is built up and applied to develop a structured taxonomy of global influences, showing the unique patterns of integration and accommodation between fusion orientations. The results prove that worldly impact in Indian fusion music is not one-dimensional or one-way but instead follows selective and context-dependent mechanisms that keep the balances between the traditions of the culture and innovations. The paper also suggests that fusion practices help to create a dynamic redefinition of authenticity as a negotiated and changing object. This paper builds analytical insights into Indian fusion music by providing a systematic mapping of global resonances and the transferable framework of the analysis of cross-cultural musical interactions in the globalized environment.

Student dropout in higher education is a global challenge that affects educational quality, institutional performance indicators, and students' academic development. With the increasing availability of educational data and advances in data mining techniques, unsupervised learning methods such as clustering have emerged as promising approaches for identifying dropout risk patterns without the need for labeled data. This study aimed to systematically map and analyze clustering techniques applied to segment students at risk of dropout in higher education between January 2010 and July 2025. To this end, a Systematic Literature Mapping was conducted following the PRISMA protocol, which included the stages of search, screening, data extraction, and thematic analysis of the studies. The results indicate that algorithms such as K-Means, DBSCAN, HDBSCAN, BIRCH, SOM and hierarchical methods have been used with varying levels of effectiveness, with internal validation metrics predominating. Academic and behavioral variables were the most frequently used in cluster formation, while psychosocial variables, although still limited, demonstrated significant potential. The findings show that clustering is a promising approach to support student retention strategies, although further progress depends on expanding datasets, strengthening validation methods, and integrating results into institutional policies designed to promote student persistence and academic success.

The constant growth in data generation, driven by technological advancement, highlights the need to organize information to extract relevant knowledge. In this context, visual representations emerge as effective tools to simplify this complex task. The automation of this process can be achieved through visualization recommendation systems. This work aims to improve the understanding of data visualization recommendations by synthesizing current literature to identify research gaps and outline initial requirements for developing prototypes and tools in this area. To achieve this, we conducted a systematic literature mapping followed by forward snowballing, covering the period from 2017 to 2025, through which we carefully selected and analyzed 89 papers on data visualization recommendations. We provide an overview of visualization recommendation systems, identifying employed techniques and categorizing studies based on different recommendation approaches. We also guide the selection of algorithms and methods for developing automatic and semiautomatic recommendation systems and present lessons learned and future research possibilities.

Wine quality is a multidimensional and contested concept that generates persistent information asymmetries among producers, consumers, experts, and regulators. This review synthesizes multidisciplinary evidence from economics, marketing, sensory science, and digital innovation to examine how wine quality’s intrinsic, extrinsic, institutional, and cultural dimensions interact with mechanisms of signalling and screening. Using a structured conceptual review and systematic evidence mapping of 76 peer-reviewed studies, the paper identifies where traditional mechanisms - such as price, reputation, expert ratings, geographical indications, and certification schemes - mitigate uncertainty and where they merely relocate it along the value chain. The analysis introduces the notion of layered systems of trust, showing that each corrective instrument reduces one type of asymmetry while generating dependencies elsewhere. Emerging digital tools, particularly blockchain and related traceability technologies, offer complementary ways to enhance transparency and governance but also create new informational challenges around data input and interoperability. The paper concludes that wine markets will continue to rely on hybrid constellations of traditional and technological signals, underscoring the need for governance frameworks that integrate digital innovation with the preservation of wine’s sensory, cultural, and institutional complexity.

Mapping the molecular landscape of glioblastoma: Pathogenesis, therapeutic targets and bioactive interventions.

The Bactrian camel (Camelus bactrianus), with its unique physiological adaptations and immune characteristics, represents a highly valuable model for innate immunity research. However, a systematic dissection of its innate immune gene repertoire and the key functional drivers within its immune response remains limited. This study integrated CRISPR-Cas9 knockout screening with time-resolved transcriptomic profiling to systematically unveil the immune regulatory mechanisms in camel dermal fibroblasts challenged with the viral mimic poly(I:C) and the bacterial mimic LPS. The CRISPR screen successfully identified 59 key genes conferring a survival advantage under lethal pathogenic challenge. The gene sets required for resisting viral versus bacterial mimics were entirely distinct, revealing divergent genetic underpinnings. Transcriptomic analysis further delineated a dynamic reprogramming of gene expression, uncovering a shared core immune response program alongside significant stimulus-specific regulation. Integrative analysis pinpointed pivotal genes, such as HSP90AA1 in the antiviral process and CSF1 in the antibacterial process, which played critical roles at both the functional screening and transcriptional regulatory levels. These key genes exhibited dynamic and evolving co-expression networks across different time points, indicating their temporally specific regulatory roles throughout the immune response. By combining functional genomics and transcriptomics, this study provides the first systematic mapping of the innate immune landscape and its dynamic regulation in the Bactrian camel, not only deepening the understanding of camelid immunobiology but also offering a new framework and insights for evolutionary studies of immune adaptation mechanisms in mammals.