Search Results (114)

The increasing volume, temporal density, and diversity of satellite Earth observation (EO) data have fundamentally transformed quantitative vegetation remote sensing. Dense multi-sensor time series and computationally intensive modelling have rendered traditional download-and-process workflows increasingly impractical. Cloud-native computing—where data access, storage, and computation are co-located and analyses are executed in data-proximate environments—has therefore emerged as a key paradigm for scalable and reproducible vegetation EO analysis. This review provides a science-oriented synthesis of cloud-native EO for quantitative vegetation research. We examine architectural principles, data models, and compute patterns that shape how vegetation analyses are implemented, scaled, and scientifically interpreted. Particular attention is given to machine learning as a system component, including model lifecycle management, domain shift, and evaluation integrity in distributed environments. We analyse how cloud-native data abstractions influence algorithmic assumptions, validation design, and long-term product consistency, highlighting trade-offs between analytical complexity, computational cost, latency, and scientific robustness. We provide a forward-looking perspective on emerging imaging spectroscopy missions and the growing system-level requirements for reproducible, scalable, and uncertainty-aware vegetation analytics at continental-to-global scales. We also outline how cloud-native EO infrastructures are driving new scientific paradigms based on continuous monitoring, systematic reprocessing, and AI-driven modelling. Full article

The renewable energy transition is a central component of global strategies to mitigate climate change and achieve sustainable development. However, the large-scale integration of renewable energy sources introduces significant challenges related to variability, system complexity, and operational efficiency. In recent years, artificial intelligence (AI) has emerged as a promising enabler for addressing these challenges through advanced data-driven forecasting, optimization, and decision-support capabilities. This study presents a systematic bibliometric and thematic review of peer-reviewed research on AI applications in the renewable energy transition published between 2015 and 2025, and was conducted following the PRISMA framework. Using the Scopus database, a total of 595 journal articles were analyzed through bibliometric performance indicators, network analysis, and thematic synthesis. The results reveal a rapidly growing and highly collaborative research field, characterized by strong international co-authorship and increasing methodological diversity. Early research predominantly focused on prediction and forecasting tasks, while more recent studies emphasize system-level optimization, energy management, and integrative AI applications across renewable technologies. The review further highlights key research trends, conceptual framing, and methodological orientations shaping the field. By consolidating dispersed literature and mapping its evolution, this study provides a structured overview that supports future research, policy development, and practical implementation of AI-enabled solutions for a sustainable energy transition. Full article

Nitrogen (N) loss poses a significant threat to global climate stability and ecosystem sustainability. Afforestation, as a key ecological restoration strategy, regulates soil N cycling processes by modulating soil microbial community structure. However, a systematic synthesis of how afforestation influences microbial-mediated N loss remains limited. To address this gap, this study conducted a bibliometric analysis using CiteSpace software, based on 104 relevant publications indexed in the Web of Science Core Collection from 1997 to 2025, to comprehensively map the knowledge structure, research hotspots, and evolutionary trajectories in the field of afforestation-driven microbial regulation of soil N loss. The results reveal three developmental phases: initiation (1997–2005), growth (2006–2020), and stabilization (2021–2025). China contributed the highest number of publications (40), while the United States exhibited the greatest academic influence; the Chinese Academy of Sciences and the Russian Academy of Sciences clusters have emerged as core research institutions. Notably, keyword and citation analyses revealed that research hotspots have shifted from process-oriented measurements, including N mineralization and N₂O emissions, toward a deeper exploration of microbial community structure, biodiversity, and functional mechanisms. This study presents the bibliometric synthesis of microbial N loss mechanisms under afforestation, revealing a paradigm shift from environmental driers to microbial diversity. These insights inform microbial forest management strategies that balance N retention with carbon sequestration. Full article

Stevia rebaudiana Bertoni is a strategically important perennial crop because it is the main botanical source of steviol glycosides, a group of high-intensity, non-caloric sweeteners increasingly demanded by the global food and beverage industry. Despite the rapid expansion of stevia cultivation, commercial production remains strongly dependent on a narrow genetic base, particularly on clonally propagated cultivars such as ‘Morita II’, which has long served as the industrial benchmark because of its favourable rebaudioside A profile and processing consistency. This dependence has raised concerns about limited adaptive capacity, genetic erosion and restricted long-term breeding progress. In this review, we provide an integrated and critical synthesis of current knowledge on the genetic diversity of S. rebaudiana, the biosynthetic and regulatory architecture of steviol glycosides, and the conventional and emerging strategies available for crop improvement. Unlike previous reviews, this article explicitly connects domestication-driven genetic bottlenecks, wild germplasm mobilisation, metabolic pathway regulation, advanced analytical phenotyping and precision breeding into a single systems-oriented framework. We examine the roles of wild germplasm, somaclonal variation, polyploidy, molecular markers, omics-assisted approaches and transgene-free genome editing as complementary tools to broaden the stevia breeding base while preserving industrial quality standards. We finally propose an integrative roadmap for the sustainable genetic improvement of stevia, positioning ‘Morita II’ not as an endpoint, but as a benchmark within a broader diversification strategy. Full article

Urban transformations outpace established urban design paradigm shifts. This acceleration widens the gap between inherited theory and contemporary urban realities This article addresses this condition by introducing epistemic urban design as a conceptual orientation and generative inheritance as its procedural extension within urban conditions described as unprecedented urbanism. Drawing on a critical interpretive synthesis of the literature spanning historical, theoretical, and technological developments, the study examines how urban design knowledge is produced, stabilized, and reinterpreted as urban complexity intensifies. The analysis unfolds in three phases. First, it traces how established paradigms historically structured design practices and how current conditions expose their operational limits. Second, it articulates how epistemic urban design treats design knowledge as an evolving resource, specifying analytical dimensions for interpreting diverse urban conditions. Third, it proposes how generative inheritance operationalizes epistemic urban design by linking inherited design knowledge to context-specific empirical situations. The article contributes to urban design research by supporting epistemic urban design with the procedural logic of generative inheritance. This shift enables theoretical insights to systematically inform design operations under conditions of unprecedented urbanism. Full article

Satellite remote sensing has rapidly evolved from an experimental support tool into a structural component of preventive archaeology and cultural heritage governance. Drawing on scientific publications and policy-oriented grey literature from 2010–2025, this study provides an integrated review of how optical, SAR, and multi-sensor satellite data are used to detect archaeological sites, monitor landscape and structural change, and support risk-informed planning across diverse legal and institutional contexts. A multi-platform workflow combines AI-assisted semantic querying (Consensus), bibliometric searches (Scopus), and the collaborative management and geospatial visualisation of references through Zotero, VOSviewer (1.6.19), and QGIS (3.44)-based literature mapping, thereby linking thematic trends, co-authorship networks, and geographical patterns of research and regulation. The results show non-linear but marked publication growth, a strongly interdisciplinary profile, and the consolidation of international hubs that drive advances in Sentinel-2-based prospection, Landsat and night-time lights urbanisation metrics, and SAR time series for deformation, looting, and conflict-damage mapping. Parallel analysis of grey literature and institutional initiatives (Copernicus Cultural Heritage Task Force, national “extraordinary plans”, regional declarations, and UNESCO guidelines) reveals the codification of satellite Earth observation within rescue archaeology protocols, emergency archaeology, and long-term conservation strategies. Overall, the evidence indicates a transition towards data-driven, multi-sensor, and multi-scalar research, underpinned by open satellite data, reproducible workflows, and AI-supported evidence synthesis. Full article

Emerging contaminants (ECs) are a diversely mounting group of chemicals and biological compounds found in air, water, and soil, which include pharmaceuticals, personal care products, per- and poly-fluoroalkyl substances (PFASs), microplastics, endocrine-disrupting chemicals, and various other industrial compounds. Unlike conventional pollutants, ECs are usually unregulated, found in very small amounts, and can persist and build up in living organisms, resulting in toxic risks for both ecosystems and human health. These contaminants originate from various anthropogenic activities and enter the environment through wastewater, stormwater, landfill leaching, and atmospheric deposition. This article documents a holistic literature review of ECs available from the last five years, covering classification, sources and pathways of contamination, and environmental behavior, while assessing their ecological, human health, and socioeconomic impacts. Advances in detection, including high-resolution mass spectrometry, non-target screening, real-time sensors, and AI-assisted monitoring, are addressed. Management strategies including advanced oxidation, membrane filtration, electrochemical treatments, and nature-based solutions are explored. It also analyses global and regional policy frameworks, highlighting regulatory gaps and the need for standardized monitoring. The study emphasizes integrated, multidisciplinary approaches combining scientific innovation, sustainable chemical design, predictive modeling, and public engagement. Synergizing technology, governance, and prevention could reduce the risks related to ECs and protect the environment. The novel contribution is an end-to-end, decision-oriented synthesis that links what monitoring can reliably infer to be feasible, integrated control strategies and sustainability outcomes, supporting risk-based prioritization, targeted pollution treatment, and prevention-focused management. Full article

Urban mobility is a central challenge for sustainable and inclusive cities, as climate change, congestion, and spatial inequality increasingly reveal mobility patterns as expressions of deeper social and spatial structures. Inclusive urban mobility examines whether transport systems equitably support the everyday movements and accessibility needs of historically marginalized and underserved populations. The integration of artificial intelligence with geographic information science, combined with multimodal geospatial data fusion, provides powerful tools to diagnose and address these disparities by integrating heterogeneous data sources such as satellite imagery, GPS trajectories, transit records, volunteered geographic information, and social sensing data into scalable, high-resolution urban mobility analytics. This paper presents a systematic survey of recent GeoAI studies that fuse multiple geospatial data modalities for key urban mobility tasks, including accessibility mapping, demand forecasting, and origin–destination flow prediction, with particular emphasis on inclusive and equity-oriented applications. The review examines 18 multimodal GeoAI studies identified through a PRISMA-ScR screening process from 57 candidate publications between 2019 and 2025. The survey synthesizes methodological trends across data-, feature-, and decision-level fusion strategies, highlights the growing use of deep learning architectures, and examines emerging techniques such as knowledge graphs, federated learning, and explainable AI that support equity-relevant insights across diverse urban contexts. Building on this synthesis, the review identifies persistent gaps in population coverage, multimodal integration, equity optimization, explainability, validation, and governance, which currently constrain the inclusiveness and robustness of GeoAI applications in urban mobility research. To address these challenges, the paper proposes a structured research roadmap linking these gaps to concrete methodological and governance directions including equity-aware loss functions, adaptive multimodal fusion pipelines, participatory and human-in-the-loop workflows, and urban data trusts to better align multimodal GeoAI with the goals of inclusive, just, and sustainable urban mobility systems. Full article

Implementing sustainability-oriented strategies within the nonprofit sector is often framed through corporate ESG (environmental, social, and governance) frameworks, yet the unique institutional logic of nonprofit organizations (NPOs) demands a more nuanced conceptualization. This study investigates the processes and determinants of sustainable value creation in NPOs, adopting an integrated theoretical framework that dynamically combines Stakeholder Theory, the Resource-Based View, and Institutional Theory. Using a mixed-methods approach, the research combines a thematic synthesis of 60 high-impact papers with confirmatory guided interviews with representatives from eight diverse NPOs. Five core categories of sustainable value creation processes were identified: strategic management, operational management, financial resources management, human capital development, and systemic integration of sustainability. Furthermore, the study identifies 25 determinants formally classified into micro (individual agency), meso (organizational structure), and macro (institutional environment) levels. The findings demonstrate tensions between internal leadership agency and external structural constraints, highlighting the challenges associated with the lack of tailored sustainability tools. It is argued that sustainability in NPOs is a fluid, emergent process defined by mission-driven legitimacy rather than financial materiality. This research provides a diagnostic foundation for assessing ESG readiness and emphasizes the need for reflexive, context-sensitive management tools that align sustainability with the unique nonprofit ethos. Full article

This article develops a rigorous and reproducible systematic review of the integration of artificial intelligence (AI) in financial education during the period 2020–2025, structured in accordance with -5.3-PRISMA and explicitly oriented toward detecting narrative and perception. The search was conducted in three complementary databases (Scopus, ScienceDirect, and Taylor & Francis), using search strings equivalent to those of the platform and a selection workflow that begins with 388 records and culminates in 50 included studies, prompting a narrative synthesis given the methodological heterogeneity. From a methodological contribution perspective, the study combines bibliometric mapping with text mining and an NLP process that triangulates sentiment using lexicon-based approaches (VADER, TextBlob) and a multilingual transformer model (XLM-RoBERTa), producing continuous indicators (sentiment index) and reproducible research artifacts. The results position AI as an integrative nexus linking financial literacy, decision-making, sustainability, and language technologies (including ChatGPT-5.3.), highlighting its potential for personalization, virtual tutoring, and immediate gains in comprehension and motivation; however, evidence of sustained behavioral change remains nascent. Critical gaps remain, such as a shortage of longitudinal/controlled studies, a lack of standardized metrics, limited transparency and validation of models, and constraints in terms of geographic and cultural diversity, while privacy, fairness, and algorithmic bias emerge as structural conditions for responsible adoption. Full article

This systematic review focuses on the effect of concurrent high-intensity interval training (HIIT) and resistance training on musculoskeletal function in adult individuals. Four electronic databases (PubMed, Web of Science Core Collection, Scopus, and PsycINFO) were searched for controlled trials in older or middle-aged adults, in recreationally exercising adults, and in athletic or tactical populations, which completed parallel HIIT and resistance training and described musculoskeletal responses to the intervention up to 30 November 2025. A total of 18 trials fulfilled the eligibility criterion and were synthesized narratively across the domains of maximal strength, explosive performance, neuromuscular activity, muscle morphology and architecture, tendon-related outcomes, and adherence and safety. Most 8- to 12-week interventions maintained two to three weekly resistance sessions and were designed in time-effective HIIT formats, increasing or preserving maximal strength in older subjects as well as younger ones that were trained. Explosive performance metrics, including both jump and sprint tasks, were usually preserved or even improved by the maintenance of the power-oriented component in resistance-based exercise sessions. The limited electromyography data indicated improved neuromuscular activation during submaximal tasks, particularly in older subjects, whereas some studies reported subtle increases or maintenance of muscle size and selective architectural patterns during application of progressive loading. Tendon-specific adaptations are difficult to measure, as imaging was seldom available, but functional tasks influenced by the muscle–tendon unit have been studied in multiple studies. Adherence was good, and adverse events were rare in all studies. Overall, the evidence suggests that well-designed concurrent HIIT and resistance training programs can improve or maintain musculoskeletal performance, although the magnitude and expression of these adaptations vary according to population characteristics and intervention design. Importantly, by integrating neuromuscular, morphological, and performance-related outcomes across diverse adult populations, this review provides a musculoskeletal-centered synthesis that extends prior concurrent training reviews beyond cardiorespiratory or interference-focused perspectives. Full article

Drawing on a systematic review of both international and Chinese-language scholarship on counter-urbanization in China, this article proposes a comprehensive typology of counter-urbanization migrations—consisting of eight types of new migrants—based on the diverse motivations driving such migration. We build a bilingual corpus of 273 research papers published between the 1970s and 2025. Integrating bibliometric mapping and qualitative synthesis, we conduct a systematic review to trace the temporal evolution and thematic diversification of counter-urbanization research. The review reveals persistent conceptual ambiguity surrounding counter-urbanization in the Chinese context, which this study addresses by conceptually distinguishing counter-urbanization from suburban expansion, population decentralization, and return migration. Empirically, counter-urbanization in China is shown to involve heterogeneous demographic groups and multiple drivers. Our synthesis identifies a fundamental analytical divide between consumption-oriented and production-oriented engagements with rural space. Counter-urbanization in China therefore cannot be understood as a singular demographic reversal. Finally, contrary to the common view, it reveals that state intervention in China functions primarily as an enabling infrastructure rather than a direct driver of migration. Overall, this review advances a more nuanced theoretical framework for understanding urban-to-rural mobility in China and contributes to broader comparative debates on counter-urbanization beyond Western contexts. Full article

Cholesterol acts as a metabolic cue that reshapes diverse signaling networks, including hedgehog and several sterol-regulated pathways orchestrated by key proteins, including sterol regulatory element-binding protein 2 (SREBP2), sterol O-acyltransferase 1 (SOAT1), Niemann–Pick type C1 (NPC1), and proprotein convertase subtilisin/kexin type 9 (PCSK9). Research over the past decade has highlighted cholesterol metabolism as a key modulator of cancer development and a promising therapeutic target. By integrating mechanistic and translational evidence, this review seeks to clarify how cholesterol metabolism interfaces with oncogenic signaling and set directions for future investigation. Accumulating preclinical and clinical data suggest that dysregulated cholesterol levels, often associated with high-fat diets, may contribute to tumorigenesis and malignant transformation. Implicated pathways, such as SREBP, NPC1, PCSK9, and SOAT1, orchestrate various processes of lipid metabolism, including cholesterol synthesis, esterification, receptor degradation, and transport, that harbor a tumorigenic environment and promote oncogenic processes. Additionally, these enzymes and corresponding pathways provide a promising direction for developing metabolism-oriented anticancer strategies. Cholesterol metabolism dysregulation serves as a major avenue for cancer signaling and growth, but studies also highlight key molecular mechanisms and targets for future treatments. Future studies should focus on expanding studies into further cancer types, investigating combination therapies, and developing novel inhibitors of key molecular targets. Full article

Background/Objectives: Acute generalized exanthematous pustulosis (AGEP) is a severe drug-induced cutaneous reaction characterized by the abrupt onset of sterile pustules, fever, neutrophilia, and a T cell-mediated type IVd hypersensitivity response. This narrative review synthesizes current evidence on pharmacological triggers, immunopathogenic mechanisms, diagnostic criteria, and differential diagnosis to provide a clinically oriented framework. Methods: A comprehensive literature search was conducted in PubMed/MEDLINE, Scopus, ScienceDirect, and SpringerLink for studies published between 2000 and 2025, complemented by selected clinical reference sources. Studies addressing clinical features, immunological pathways, pharmacovigilance signals, and diagnostic tools for AGEP were included. Synthesis of Evidence: β-lactam antibiotics remain the most frequent triggers, while increasing associations have been reported with hydroxychloroquine, targeted therapies, immune checkpoint inhibitors, psychotropic agents, and vaccines. Immunopathogenesis is driven by IL-36 activation, CXCL8/IL-8–mediated neutrophil recruitment, and IL36RN mutations, explaining overlap with pustular psoriasis. Diagnostic accuracy improves through integration of drug latency, clinical morphology, histopathology, biomarkers, and standardized tools such as the EuroSCAR score. Conclusions: AGEP is a complex pustular reaction induced by diverse drugs and amplified by IL-36-mediated inflammation. Accurate diagnosis requires a multidimensional approach supported by structured algorithms and robust pharmacovigilance to identify evolving drug-associated patterns. Full article

Mesenchymal stem/stromal cells (MSCs) exhibit broad differentiation capability and strong immunoregulatory potential mediated through intercellular communication and the release of diverse paracrine mediators. They represent a promising but still investigational therapeutic approach for managing complications associated with allogeneic hematopoietic stem cell transplantation (allo-HSCT). This review provides an updated synthesis of MSC biology, their bidirectional interaction with immune cells, and their functional contribution to the hematopoietic niche. It also evaluates current clinical evidence regarding the therapeutic roles of MSCs and MSC-derived extracellular vesicles (EVs) in acute and chronic graft-versus-host disease (aGVHD/cGVHD), as well as in poor graft function. Mechanistic insights encompass macrophage polarization toward an anti-inflammatory phenotype, inhibition of dendritic cell maturation, enhancement of regulatory T-cell expansion, and modulation of cytokine signaling pathways. Within the bone marrow milieu, MSCs contribute to stromal restoration and angiogenic repair. Recent phase II/III trials in steroid-refractory (SR)-aGVHD have demonstrated overall response rates ranging from 48 to 71%. Efficacy appears particularly enhanced in pediatric patients and with early MSC administration. Across studies, MSC therapy shows a favorable safety profile; however, heterogeneity in response and inconsistent survival outcomes remain notable limitations. For poor graft function, limited prospective studies indicate hematopoietic recovery following third-party MSC infusions, and combination approaches such as co-administration with thrombopoietin receptor agonists are under investigation. MSC-derived EVs emulate many immunomodulatory effects of their parental cells with a potentially safer profile, though clinical validation remains in its infancy. MSC-oriented interventions hold substantial biological and therapeutic promise, offering a favorable safety margin; however, clinical translation is hindered by product variability, suboptimal engraftment and persistence, and inconsistent efficacy across studies. Future directions should emphasize standardized manufacturing and potency assays, biomarker-driven patient and timing selection, optimized conditioning and dosing strategies, and the systematic appraisal of EV-based or genetically modified MSC products through controlled trials. Full article