Search Results (1,447)

The combined effects of organic pollutants and vertical soil gradients on microbial community assembly in long-term contaminated sites remain insufficiently understood. In this study, high-throughput sequencing was employed to characterize prokaryotic communities across depth-resolved soil profiles at a contaminated site in Tianjin, China. Microbial diversity, taxonomic composition, and predicted functional traits varied significantly with soil depth and pollutant distribution. Surface soils exhibited higher richness and diversity, with Shannon, Sobs, and PD indices decreasing with depth (p = 0.020, p = 0.002, and p < 0.001, respectively). Redundancy analysis showed that the first two axes explained 89.91% of the total variance, indicating strong associations between microbial community structure and environmental variables. Community differentiation was related to pollutant type, with aromatic hydrocarbons more strongly linked to surface assemblages and chlorinated compounds associated with deeper horizons. Although the overall abundance of predicted metabolic genes decreased with depth, the distribution of major functional categories, including pathways related to organic matter degradation, remained comparatively stable. Co-occurrence network analysis revealed a progressive decline in network connectivity and complexity along the vertical gradient, with the number of edges decreasing from 853 (L1) to 447 (L3) and average degree decreasing from 16.404 to 9.122. These findings highlight depth-related environmental filtering as a key mechanism structuring microbial communities under long-term organic contamination and provide a scientific basis for optimizing depth-specific in situ bioremediation strategies, such as targeting aromatic hydrocarbon degradation in surface soils and chlorinated compound remediation in deeper layers. Full article

With the acceleration of digital transformation in education, this paper examines how blockchain is being framed as a governance solution for trust, transparency, and decentralization. Using a hybrid bibliometric and thematic analysis of 93 Web of Science and Scopus publications, the study maps publication trends, leading outlets, author networks, and conceptual clusters. We analyze co-authorship networks, keyword co-occurrence patterns, and conceptual structures using VOSviewer version 1.6.19 and the R-based Bibliometrix package. Then, we apply qualitative coding to offer a more profound interpretation of governance stories. Findings show that blockchain in educational governance is predominantly positioned through techno-managerial lenses—focusing on secure credentials, tamper-proof records, and efficiency—while critical perspectives on power, equity, and participation remain limited. Global North institutions and computer science–oriented venues dominate the field, with little engagement from Global South contexts or educational leadership scholarship. The paper concludes by proposing a research agenda that reimagines blockchain not as a neutral tool, but as a socio-technical assemblage that must be interrogated through equity-, ethics-, and community-centered frameworks. Full article

The increasing global demand for sustainable water purification technologies has accelerated research on catalytic degradation and advanced oxidation processes for the removal of refractory pollutants. This study provides a comprehensive bibliometric analysis of global research trends in catalytic water and wastewater treatment from 2010 to 2025, combining quantitative mapping with a qualitative synthesis of emerging technological directions. Bibliographic data were retrieved from the Scopus database and screened using the PRISMA framework, followed by analysis using VOSviewer (v1.6.20) and OriginPro (version 2023, OriginLab Corporation, Northampton, MA, USA) to examine publication growth, citation patterns, international collaboration networks, and thematic evolution. A total of 1550 publications, including 1265 research articles and 285 review papers, were analyzed. The results show a significant increase in research output after 2015, reflecting growing global attention to water sustainability and environmental remediation. China, the United States, and India were identified as the leading contributors, with strong international collaboration networks. Keyword co-occurrence analysis revealed three dominant research themes: photocatalytic degradation and semiconductor engineering, Fenton and Fenton-like advanced oxidation processes, and emerging hybrid catalytic systems involving carbon-based materials and metal–organic frameworks. The analysis also indicates a recent shift toward multifunctional hybrid catalysts designed to improve efficiency, stability, and performance in complex wastewater systems. These findings highlight key scientific developments and suggest future research priorities, including green catalyst synthesis, reactor and process scale-up, AI-assisted catalyst design, and life-cycle sustainability assessment to support the transition from laboratory research to practical water treatment applications. Full article

Baihua Reservoir, a typical large waterbody in the karst region of southwestern China and an essential drinking water source, is characterized by a high carbonate buffering capacity that profoundly shapes the structure and function of its phytoplankton community. This study systematically elucidates the multi-dimensional driving mechanisms underlying seasonal phytoplankton community assembly in karst reservoirs by integrating multiple analytical models—including the Neutral Community Model, β-diversity decomposition, co-occurrence network analysis, XGBoost-SHAP machine learning, and Partial Least Squares Path Modeling—based on monthly sampling at five sites from 2020 to 2024. The results revealed that: (1) Stochastic processes dominated community assembly across all four seasons, while deterministic processes played a crucial role in local species turnover. (2) The co-occurrence network structure showed significant seasonal dynamics, with the composition of keystone species adaptively shifting in response to changing environmental conditions. (3) The key environmental factors influencing the phytoplankton community exhibited clear seasonal patterns, primarily pH, NH₃-N, and COD_Mn in spring; water temperature, COD_Mn, and NH₃-N in summer; TN, TP, and pH in autumn; and pH, water temperature, and DO in winter. To support the sustainable management of karst reservoirs, we propose seasonally differentiated strategies derived from our phytoplankton community analysis: target COD_Mn reduction in spring and summer, focus on TN and TP load control in autumn, prioritize water column stability in winter, and maintain hydrological connectivity and pH monitoring year-round. This approach enhances phytoplankton community stability, safeguards drinking water safety, and provides a targeted management model for similar reservoir ecosystems globally. Full article

Industrial-scale Anaerobic Digestion (AD) is a key technology for the energy recovery of agro-industrial and municipal waste and for the mitigation of greenhouse gas emissions; however, the actual operational performance of industrial biodigesters continues to show significant discrepancies with respect to the theoretical values reported in the scientific literature. In this context, there is still a lack of systematic analysis to identify which operating parameters are consistently monitored in industrial settings and which remain insufficiently explored, particularly those that describe the overall state of the digestion environment. To address this gap, a systematic literature review was conducted in the Scopus database for the period 2000–2026, complemented by a bibliometric analysis using VOSviewer software v1.6.18. 3. After applying inclusion criteria focused exclusively on industrial-scale and pilot systems, 1327 documents corresponding to the category of operating parameters were selected and analyzed using keyword co-occurrence networks and evaluation of occurrence frequencies and total link intensities. The analysis shows a marked concentration of the literature on a small set of classic parameters, highlighting pH (154 occurrences, 3667 link intensities), temperature (147 occurrences, 3255 link intensities), and ammonia (131 occurrences, 2824 link intensities) as the most recurrent variables in the industrial operation of anaerobic digesters. Complementarily, parameters such as chemical oxygen demand, total and volatile solids, and hydrogen sulfide have progressively increased their presence since 2015, mainly associated with effluent quality assessment, nutrient recovery, and overall process sustainability. In contrast, variables that integrate the state of the environment, such as electrical conductivity, oxidation-reduction potential, and the rheological properties of digestate, appear in less than $5\%$ of the studies analyzed, despite their ability to integrate information on stability, buffer capacity, and overall operating conditions. Taken together, these findings highlight an imbalance between the intensive use of traditional parameters and the limited incorporation of integrative indicators in industrial monitoring, suggesting that their systematic inclusion, together with the development of soft sensors and predictive models, could contribute to improving operational control and reducing the gap between the theoretical performance and actual behavior of industrial biodigesters. Full article

Understanding how migratory waterbird species co-vary through time can reveal guild structure and guide monitoring in dynamic coastal wetlands, yet seasonal phenology can inflate simple co-occurrence signals. Here, we used standardized monthly bird counts from Yongan Wetland, Taiwan (36 survey months across two survey blocks: November 2014 and January–August 2015, and October 2016–December 2018) to infer de-seasonalized interspecific associations. We analyzed 50 regularly recorded species and a focal subset of 13 shorebirds and ducks. For each species, we transformed raw counts to monthly anomalies that remove recurrent seasonal patterns, then quantified pairwise Spearman correlations and controlled multiple testing using Benjamini–Hochberg FDR (q ≤ 0.05) to construct association networks. The anomaly-based network revealed strong guild structure: positive links were concentrated within dabbling ducks and within shorebirds, consistent with shared habitat use and foraging regimes, whereas negative links were fewer and suggested potential niche partitioning or spatiotemporal segregation. Robustness analyses (moving-block bootstrap stability, a circular-shift null comparison, and log-transformed anomaly sensitivity) supported that the main network patterns were unlikely to arise from chance alignment. Our framework provides a transparent, time-series–based approach for disentangling phenology from association inference, offering a practical framework for wetland monitoring and hypothesis generation about waterbird community dynamics. Full article

Eukaryotic microorganisms, including microalgae, protists, fungi, and micro-metazoans, act as drivers of energy flow and nutrient cycling, collectively forming the microbial food loop, and also serve as important indicators of environmental health. To investigate the seasonal variation in eukaryotic microorganisms in a mussel farming area, a total of 96 seawater samples were collected from surface and bottom layers of water across different seasons. High-throughput sequencing of the 18S rRNA gene was employed to characterize shifts in microbial community structure and identify key influencing factors. Our results indicated significant seasonal differences in eukaryotic microbial communities between surface and bottom waters. Redundancy Analysis (RDA) revealed that seasonal variations in community structure were primarily driven by environmental factors such as temperature, dissolved oxygen (DO), and salinity. Co-occurrence network analysis indicated that surface water networks exhibited higher numbers of nodes and edges, as well as greater modularity, suggesting more distinct niche differentiation and higher natural connectivity within the community. These findings provide fundamental data for understanding the response mechanisms of eukaryotic microbial communities to seasonal changes in the mussel cultivation area of Gouqi Island. Full article

The comprehension of the complex dynamics of degassing is critical for volcano monitoring and assessing volcanic hazards. In this study, we apply visibility graph analysis (VGA) to a decadal, high-resolution time series of daily soil CO₂ flux recorded by a standardized monitoring network at Mt. Etna volcano (Italy). By mapping these time series into complex networks, we demonstrate that the connectivity degree distributions follow a power law described by the exponent $\gamma$, which reveals a self-similar behavior of gas emissions. We introduce the $\gamma$-deviation, namely the variation of the scaling exponent from its long-term site-specific baseline, as a novel proxy for degassing efficiency. The long-term baseline is interpreted as a site-specific measure of flux efficiency, while its variations are attributed to other factors, such as fluctuations in the sources or changes in the efficiency of fluids transport pathways. Our results identify a transition from a period of discordance across the monitoring sites (pre-2016) to a phase of network-wide concordance (after 2016). The striking correlation between topological $\gamma$-deviations and the established normalized network signal (${\Phi }_{norm}$) validates the methodology, suggesting that VGA is able to capture the same underlying magmatic drivers. This study establishes VGA as a robust and reliable tool for medium- and long-term monitoring, potentially capable of identifying the occurrence of large-scale magmatic processes and refining the characterization of fluid transport dynamics in active volcanic systems. Full article

The stability of solar-dependent energy systems is vital for urban sustainability, but it is increasingly threatened by compound energy risks (CERs), events where low photovoltaic generation coincides with high electricity demand. This study addresses a critical knowledge gap by disentangling the co-evolving structural and magnitude drivers of these events to identify their propagation pathways and the most vulnerable districts. To achieve this, a novel hybrid framework was developed to provide a high-resolution, spatiotemporal assessment of both risk dimensions across Singapore’s 41 districts. Structural risk was mapped by integrating an undirected co-occurrence network, quantified using Mutual Information (MI), with a directed influence network derived from Bayesian Network Theory (BNT). Concurrently, magnitude risk was assessed through a copula-based analysis of joint probabilities for historical and future climate conditions, using Singapore’s new V3 dataset under multiple Shared Socioeconomic Pathways (SSPs). The results reveal a significant shift in the compound energy risk landscape. Structurally, the network of risk propagation evolves from a historically diffuse configuration to a consolidated system dominated by clusters of 8 to 9 highly interconnected districts under the SSP245 scenario. Under the high-diffusion SSP585 scenario, this evolution is expanded by the addition of 4 more districts. At the same time, the magnitude of risk intensifies across identified hotspot districts. This synthesis uncovers a critical feedback dynamic: districts such as 29, 36, and 40 not only serve as key structural hubs but also experience sharp increases in event probability, with their return periods for extreme compound events collapsing from over 50 years historically to the 10–20-year range. This forms a self-reinforcing loop of systemic vulnerability. These findings indicate that Singapore’s energy security will become increasingly exposed to climate-driven risks that propagate through this consolidated network, requiring targeted spatial adaptation to ensure long-term grid sustainability. Full article

Lycium ruthenicum is a typical desert halophyte with strong stress resistance and high medicinal value in the Tarim Basin. Root endophytic microbes play critical roles in host adaptation, nutrient cycling, and secondary metabolite accumulation. To clarify the diversity patterns of root endophytic bacteria and fungi and their relationships with environmental factors and fruit quality, high-throughput sequencing was used to analyze microbial community characteristics of Lycium ruthenicum collected from different habitats in the Tarim Basin. The results showed that rarefaction curves of alpha diversity indices (Chao1, Shannon, Pielou_e) tended to be saturated, indicating sufficient sequencing depth. Principal coordinate analysis (PCoA) revealed significant habitat-driven differentiation in both bacterial and fungal community structures. Community composition analysis showed that the relative abundance of dominant taxa at the phylum and genus levels differed significantly among sampling sites. Co-occurrence network analysis indicated that bacterial and fungal networks exhibited high modularity and were dominated by positive synergistic interactions, with Pseudomonas, Bacillus, Sphingomonas, Alternaria, and Fusarium as key hub genera. Moreover, root endophytic communities were significantly correlated with climatic variables, soil physicochemical properties, and fruit quality traits, including anthocyanin (AC), proanthocyanidin (PA), total flavonoids (TF), and total polyphenols (TP). Several keystone microbial genera were closely associated with the accumulation of functional metabolites in fruits. This study reveals the biogeographic distribution and co-occurrence characteristics of root endophytes in Lycium ruthenicum and provides a theoretical basis for understanding microbe–host–environment interactions and the quality improvement of desert medicinal plants. Full article

Fish host complex intestinal bacterial communities that contribute to a wide range of functions, from nutrient assimilation to modulation of the immune system. Understanding how environmental and host-related factors shape the fish gut microbiota is essential for advancing sustainable aquaculture practices. This study compared the intestinal microbiota of gilthead sea bream (Sparus aurata) between wild and aquaculture populations in western Greece using 16S rRNA gene amplicon sequencing targeting the V3–V4 region, combined with culture-based methods. The analysis was based on a 97% similarity threshold and included 141 gastrointestinal samples of fish collected at two aquaculture facilities and two wild fisheries, representing two different growth phases (150 g and 300 g body weight). High-throughput sequencing data revealed a clear separation of gut microbial communities according to origin (wild vs. aquaculture), geographic location, and body growth phase, with most wild fish groups exhibiting higher microbial diversity than their farmed counterparts, except for group MES_150 which showed similar or lower values. The gut microbiota was dominated by Pseudomonadota (53%), Bacillota (29%), Actinomycetota (7%), Deinococcota (5%), and Bacteroidota (4%). A shared core microbiome, comprising Psychrobacter, Staphylococcus, Geobacillus, Aeromonas, Enterobacter, Pantoea, Bacillus, and Acinetobacter, was detected across all populations. Wild fish were enriched in Psychrobacter, Aeromonas, and Photobacterium, while aquaculture fish displayed higher abundances of Vibrio, Allomeiothermus, and Staphylococcus. Network analysis revealed mostly mutually exclusive interactions in both groups but distinct patterns of co-occurrence, driven mainly by Paenibacillus, Enterobacter, and Staphylococcus in wild samples, and by Vibrio, Aeromonas, and Pseudomonas in farmed fish. Culture-based assays demonstrated greater diversity in wild fish, dominated by Pseudomonas, Staphylococcus, and Vibrio strains, in contrast to the frequent occurrence of Staphylococcus and Psychrobacter in aquaculture samples. The findings suggest that aquaculture practices significantly alter gut microbial community structure and reduce diversity, with potential implications for fish health and disease resistance. The identified core and differentially abundant taxa provide candidates for probiotic development to improve aquaculture sustainability. Full article

Background: Diabetic foot ulcers (DFUs) represent a major chronic complication of diabetes mellitus, often leading to severe infection, amputation, and reduced quality of life. Among various factors affecting DFUs, plantar pressure plays a pivotal role in ulcer formation and recurrence. Despite growing interest in this domain, few studies have comprehensively evaluated the research landscape concerning plantar pressure in the context of DFUs from a bibliometric perspective. Aim: To conduct a comprehensive bibliometric analysis and visualization of global research trends, hotspots, and collaborative networks in the field of plantar pressure-related diabetic foot studies from 2000 to 2024. Methods: A systematic search was conducted in the Web of Science Core Collection (WoSCC) on 16 February 2025, for articles published between 2000 and 2024 using terms related to “diabetic foot” and “plantar pressure”. A total of 2518 records were retrieved, from which 2110 English-language articles and reviews were included. Bibliometric and visual analyses were performed using Microsoft Excel 2021, VOSviewer (v1.6.20), CiteSpace (v6.4.R1), Charticulator, and Scimago Graphica. Analyses included publication trends, country/institution/author collaborations, journal distributions, keyword co-occurrence and clustering, citation bursts, and reference co-citation networks. Results: A total of 2110 publications were identified, showing an overall increase in annual publication output from 2000 to 2024, with some year-to-year fluctuations. The United States led in publication volume (678 articles), citation frequency, and H-index, followed by the United Kingdom and China. Armstrong, David was the most prolific and also had the highest H-index among the listed authors, while the University of Amsterdam was the leading institution. “Journal of Wound Care” had the highest publication count, whereas “Diabetes Care” ranked first in citation frequency. Keyword analysis revealed major research clusters including “diabetic foot”, “plantar pressure”, “wound healing”, “offloading”, and “negative pressure wound therapy”. Recent trends show an increased focus on microcirculation, regenerative medicine, customized footwear, and wound care technologies. Conclusions: The bibliometric analysis reveals research trends and current hotspots in plantar pressure management for diabetic foot ulcers, with a particular focus on managing plantar pressure through personalized offloading strategies and custom footwear. These findings highlight the practical value of tailoring interventions to individual patient needs, emphasizing the importance of biomechanical factors in ulcer prevention and healing. Full article

Background: Polyploid and chromosomal copy number gains (CNGs) cells may serve as key mediators of tumor plasticity, therapeutic resistance, and clonal evolution. Despite growing interest, their biological and clinical relevance in colorectal cancer, particularly in the metastatic setting, remains poorly defined. Methods: We performed an integrated morphological, cytogenetic, and genomic analysis of metastatic colon cancer. A tissue microarray comprising 100 tumors was evaluated, of which 47 cases were fully assessable for morphology and fluorescence in situ hybridization (FISH). Polyploid nuclei and chromosomal CNGs were assessed morphologically and cytogenetically. High-resolution targeted sequencing (TruSight Oncology 500) was conducted to characterize genomic alterations. Bioinformatic analyses included Gene Ontology enrichment and Phenolyzer network modeling. Associations with clinicopathological variables and survival outcomes were explored. Results: Polyploid nuclei and/or chromosomal CNGs were identified in approximately 25% of evaluable cases. These alterations were enriched in right-sided CRCs and in older patients, suggesting a link with age-related genomic instability. Polyploid/CNG tumors did not show significant enrichment for canonical CRC driver mutations (RAS, TP53, SMAD4), although trends toward co-occurrence with BRAF mutation and mutual exclusivity with HER2 amplification were observed. Integrative bioinformatic analyses highlighted dysregulation of pathways involved in mitotic control, centrosome organization, and DNA replication stress. Conclusions: In metastatic colon cancer, the presence of genome-wide copy number gain may delineate a tumor subset with distinctive clinicopathological and molecular characteristics. Further studies are warranted to elucidate the biological significance of these features and to explore their potential implications for tumor evolution, treatment response, and clinical stratification. Full article

The rapid adoption of artificial intelligence (AI) across public services and critical infrastructure is reshaping digital governance. While AI promises efficiency and innovation, its reliance on large, high-dimensional datasets introduces privacy, bias, transparency and accountability risks that existing frameworks struggle to address. This study evaluates the maturity of current AI governance frameworks and develops an integrated risk-tiering model that connects ethical principles to auditable technical controls, aligning with Sustainable Development Goal 9 on industry, innovation and infrastructure. A systematic literature review of 450 records from major databases was conducted using PRISMA 2020 guidelines; 95 high-quality studies were analyzed using principal component analysis and k-means clustering. The analysis produced a heat map of governance frameworks, a co-occurrence network of themes, a cluster analysis of framework coverage and an integrated governance risk framework supported by a risk-tiering matrix. Findings reveal a fragmented landscape dominated by ethics/privacy-centric and compliance/risk-focused approaches, with few integrated frameworks and evident tension between privacy and security. This synthesis bridges the gap between values and practice, offering a policy-ready model for secure and sustainable AI governance. Full article

As Villanova University students navigate campus life, ghost stories tied to specific buildings, paths, and rituals circulate as grassroots spatial narratives. This article argues that these stories involving haunted halls, underground tunnels, and ritualized practices surrounding seals, arches, and fountains, function as forms of Radical Placemaking, through which students collectively reinterpret, appropriate, and sometimes resist the university’s officially sanctioned spatial order. Drawing on 162 student testimonies collected in 2019, translated into Spanish, and analyzed using topic modeling, co-occurrence mapping, and GIS visualization, the study demonstrates how vernacular stories encode lived experiences, informal knowledge, and alternative claims to campus space. Nine thematic clusters emerge, organized into three narrative domains: supernatural encounters anchored to institutional buildings (including Alumni Hall’s Civil War history, the St. Mary’s nun legend, and Tolentine Hall hauntings), ritual and tradition practices that reinscribe or subvert formal authority (the Corr Chapel arch, the Driscoll Hall seal ritual, and student ceremonies), and hidden-space narratives that imagine infrastructures beyond official visibility (such as underground tunnels linking campus buildings). Analysis of narrative transmission reveals uneven power relations: institutional channels circulate curated traditions aligned with university identity. Peer networks and personal experiences generate counter-mappings that privilege exploration, embodiment, and affect. Villanova’s ghost stories constitute spatial perceptions that enable students to assert belonging, contest institutional narratives, and produce place through collective storytelling within an evolving and hierarchically governed campus landscape. Full article