Search Results (8,998)

In this work, three sulfur-iron materials (sulfide-modified nanoscale zerovalent iron (S-nZVI), ferrous sulfide (FeS), and pyrite (FeS₂)) were employed to enhance the Fenton process for naphthalene (NAP) degradation. The enhancement performance and mechanisms of S-nZVI, FeS, and FeS₂ were investigated and compared. The results showed that NAP removal was enhanced from 56.4% in the H₂O₂/Fe(II) system to 88.6%, 83.0%, and 89.1% with the addition of S-nZVI, FeS, and FeS₂, respectively. Three sulfur-iron materials could all reduce Fe(III) produced in aqueous solution, regenerate Fe(II), and slow down the precipitation of dissolved iron. In addition, the addition of sulfur-iron materials could promote the generation of hydroxyl radical (HO•), thus intensifying the degradation of NAP. The results of scavenging tests indicated that HO• was the dominant reactive oxygen species (ROS) for NAP removal, while superoxide radical (O₂⁻•) also participated. The effect of complex water matrices on NAP degradation was evaluated, showing that sulfur-iron material-enhanced techniques had a wide pH application range and had great tolerance to inorganic ions and humic acid. Moreover, NAP degradation intermediates and their toxicity were elucidated. Finally, the obvious removal of various pollutants in sulfur-iron material-enhanced systems demonstrated that these technologies could be used to remediate organic-polluted groundwater. Full article

Ayu (Plecoglossus altivelis) is an East Asian amphidromous river fish, yet seasonal microbiota dynamics remain unclear. We investigated ayu in the Dajing Stream (Zhejiang Province, China) by synchronously sampling water microbiota (H), gut content microbiota (N), and gut tissue-associated microbiota (C) across four seasons. Each season, four fish were collected, and an overlapping pooling strategy (abc/abd/bcd) generated three composite replicates for C and N (n = 3 composites/season); water was collected as three field replicates (n = 3/season), yielding 36 samples (12 per niche). Using 16S rRNA amplicon sequencing and COI barcoding of stomach contents, we observed the clearest seasonal differentiation in H and seasonal variation in N consistent with diet shifts, whereas C was comparatively stable. COI signals indicated a diet dominated by aquatic insects in spring/summer, which shifted toward smaller prey (e.g., rotifers) in winter. Together, these results highlight strong niche partitioning and season-linked shifts in water and gut content communities relative to the more stable tissue-associated microbiota. These findings should be interpreted as exploratory and require validation in larger individual-level studies. Full article

Moderate thermal exposure can significantly influence the mechanical behavior of volcanic rocks by inducing microcrack development and altering crack network characteristics. However, quantifying such damage processes remains challenging when relying solely on conventional mechanical parameters. In this study, the evolution of crack network complexity in andesite and andesitic–basaltic rocks subjected to moderate thermal exposure (200 °C) is investigated using fractal analysis integrated with mechanical and mineralogical observations. Six core specimens were tested under uniaxial compression, including three natural specimens and three specimens thermally treated at 200 °C prior to loading. After failure, crack surfaces were digitized and fractal dimensions (D) were calculated using the box-counting method. Petrographic observations and X-ray powder diffraction (XRPD) analyses were conducted to characterize the mineralogical composition and microstructural features controlling crack development. The results indicate that thermal exposure primarily reduces rock stiffness rather than peak strength. While the uniaxial compressive strength (UCS) of two specimens remains nearly unchanged after heating, the elastic modulus (E) decreases in all thermally treated specimens. Mineralogical observations reveal a heterogeneous volcanic fabric dominated by plagioclase and pyroxene within a fine-grained groundmass, with secondary calcite phases occurring in veins and pocket fillings. Fractal analysis shows generally lower D values in thermally treated specimens, suggesting crack redistribution and coalescence rather than increased network complexity, consistent with the observed reduction in stiffness and a tendency toward more ductile deformation behavior. Full article

Conventional fault analysis and calculation methods developed for synchronous-generator-dominated power systems exhibit limited applicability to distribution networks with high penetration of distributed generation (DG). These methods cannot provide a reliable theoretical basis for fault characteristic analysis or protection coordination. Existing studies on this scenario have primarily focused on the integration of grid-following (GFL) inverter-based resources (IBRs). By contrast, research on the integration of grid-forming (GFM) IBRs—particularly the virtual synchronous generator (VSG), which enables stable and sustainable utilization of renewable energy resources as synchronous generators—remains significantly inadequate. Therefore, this paper introduces a concise fault analysis and calculation method tailored to distribution networks with VSG-type DGs. First, the control strategy of the VSG-type DGs is examined, and the active-power response characteristics of VSG-type DGs are analyzed for faults in distribution networks. Equivalent models of a typical distribution network with VSG-type DGs are then established for symmetrical and asymmetrical faults. Subsequently, leveraging the active power–frequency and reactive power–voltage dependencies, a fault calculation method for distribution networks is proposed and its generality is examined. The method is convenient to implement and computationally efficient. It requires no detailed information on internal PI controller parameters or time constants of the control loops. PSCAD/EMTDC simulations are performed to verify the high accuracy and suitability of the proposed method for multi-DG scenarios, which facilitates the integration of VSG-type DGs in distribution networks. Full article

This study characterizes the multifractal structure of monthly precipitation in the semi-arid state of Guanajuato, Mexico, using Multifractal Detrended Fluctuation Analysis with quadratic detrending (MFDFA-2). We analyze 65 quality-controlled meteorological stations covering the period 1981–2016. All series exhibit multifractality, with generalized Hurst exponents $h\left(2\right)=0.568\pm 0.065$ indicating predominantly persistent dynamics and long-term positive autocorrelation (64.6% of stations). The multifractal spectrum width ($\Delta \alpha$) ranges from 0.15 to 0.72 (mean = 0.2423), revealing substantial spatial variability in scaling complexity. K-means clustering based on multifractal features identifies the following four hydroclimatic groups: one random cluster (29.2% of stations) and three persistence-dominated clusters (70.8%), with coherent spatial organization. These findings provide new insights into the temporal scaling properties of precipitation in semi-arid regions and have important implications for water resource management and regionalized drought-risk assessment. Full article

Deep learning is increasingly integrated into oral rehabilitation workflows, particularly in implant planning, prosthodontic design automation, and peri-implant diagnosis. However, reported performance is heterogeneous and difficult to compare across tasks, modalities, and validation designs. The goal of this study was to critically analyze deep learning architecture families applied to oral rehabilitation and to provide task-driven selection guidance supported by an evidence table reporting dataset characteristics, validation strategy, and performance metrics. A focused narrative review was conducted using transparent, database-specific search criteria (final n = 10 included studies), emphasizing implant planning (cone–beam computed tomography [CBCT]-based segmentation), prosthodontic design (intraoral scan [IOS]/mesh inputs), and peri-implant diagnosis (periapical/panoramic radiographs). Evidence certainty for each clinical task was assessed using GRADE-informed ratings (High/Moderate/Low/Very Low). Extracted variables included clinical task, imaging modality, dataset size, architecture, validation strategy (internal vs. internal + external), split level, ground truth protocol, and performance metrics. A structured computational and hardware feasibility analysis was conducted for each architecture family to support real-world deployment planning. Encoder–decoder networks (U-Net/nnU-Net) dominate CBCT segmentation for implant planning, while detection architectures (Faster R-CNN, YOLO) support implant localization and peri-implant assessment on radiographs. Generative models (3D GANs, transformer-based point-to-mesh networks) enable crown design from three-dimensional scans. Hybrid CNN–Transformer architectures show promise for multimodal CBCT–IOS fusion, though direct evidence from the included studies remains limited to a single study. External validation remains uncommon yet essential given the risk of domain shift. In conclusion, architecture selection should be anchored to task geometry (2D vs. 3D), artifact burden, and required clinical output type. Reporting standards should prioritize dataset transparency, validation rigor, multi-center external testing, and uncertainty-aware outputs. Full article

We investigate a generalization of complement reducible graphs, called co-graphs, for r-uniform hypergraphs. The operations of r-co-hypergraphs are the disjoint union of two given r-co-hypergraphs and the join operation, which inserts all hyperedges of cardinality r between the non-empty vertex subsets of two given r-co-hypergraphs. We show that the primal graphs of r-co-hypergraphs are special co-graphs and that r-co-hypergraphs are closed under complementation of r-uniform hypergraphs. This leads to a method that can determine whether an input hypergraph H is an r-co-hypergraph. If the answer is positive, we find a decomposition tree for H in polynomial time. We give specific formulas for how to compute several hypergraph parameters for r-uniform hypergraphs defined by the disjoint union of two r-uniform hypergraphs and the join of two r-uniform hypergraphs. The considered parameters are the size of a largest stable set, the size of a largest co-stable set, the size of a largest independent set, the size of a largest co-independent set, the size of a smallest vertex cover, the size of a smallest 2-transversal, the size of a smallest dominating set, the strong chromatic number, and the upper chromatic number. This leads to $\mathcal{O}\left(n\right)$ time algorithms to compute these values on r-co-hypergraphs on n vertices given by a decomposition tree. Further, we conclude relations for the considered parameters restricted to r-co-hypergraphs. Our methods generalize and re-prove several results known for co-graphs. Full article

Mycotoxin contamination remains a persistent threat to food safety in the Democratic Republic of the Congo (DRC) and neighboring countries, driven by conducive tropical agroecological conditions, inadequate post-harvest practices, and limited regulatory governance. This critical narrative review (2009–2024) synthesizes the occurrence data for major staple foods (maize, peanuts, cassava, sorghum, millet, and beans) and dairy products compiled from Google Scholar, ScienceDirect, MDPI and institutional sources. It examines the co-occurrence patterns, exposure pathways, and analytical and regulatory gaps. Warm, humid lowland environments favor Aspergillus and aflatoxins, whereas cooler, humid highland zones promote Fusarium, fumonisins, and deoxynivalenol. Across commodities, contamination intensifies along food value chains through inadequate drying, non-hermetic storage, insect damage, and prolonged handling, with processed products generally exhibiting the highest levels of mycotoxins. Regulated mycotoxins, including aflatoxins, fumonisins, trichothecenes, ochratoxins, and zearalenone, frequently exceed European Union (EU), East African Community (EAC), and Codex Alimentarius Commission (CAC) limits in staple foods. Their co-occurrence is widespread, including emerging mycotoxins such as beauvericin and enniatins, particularly in maize- and peanut-based products, raising concerns about potential additive or synergistic effects. Aflatoxin M1 in milk highlights plant–feed–animal–human transfer within a One Health framework. Despite increasing evidence, the available data remain fragmented and heterogeneous; rapid tests dominate, while few studies employ multi-mycotoxin LC-MS/MS methods. Cross-border trade between countries, such as Uganda, Tanzania, Zambia and Angola, facilitates the circulation of contaminated commodities in the absence of harmonized standards and risk-based controls. Priorities include harmonized regional surveillance, biomarker-based co-exposure assessment, cost-effectiveness evaluation of mitigation strategies, and regulatory alignment at borders. Coordinated, multisectoral action is essential to reduce chronic dietary exposure and improve food safety across the region. Full article

This study evaluated how a partial substitution of pea protein isolate (PPI) with brewer’s spent grain (BSG) or barley rootlets (BRs) affects high-moisture meat analogues (HMMAs). PPI was substituted with 10% and 20% with BSG or BRs, respectively. Extrudates were produced on a co-rotating twin-screw extruder at maximum temperatures of 140 °C and 160 °C. Extrudates were assessed for colour, moisture, firmness and fibre morphology. Furthermore, the technofunctional and nutritional properties of the raw materials were determined. Extrudates with BSG produced the darkest colour, whereas PPI and BR formulations exhibited the lightest. A stronger reddish tint was observed at 160 °C, while the colour within the yellow–blue spectrum was largely temperature-independent. Firmness was generally higher at 160 °C, consistent with lower end-product moisture. Side stream addition lowered protein content and weakened fibre formation, with the effect most pronounced for BRs. Overall, formulation was the dominant factor influencing lightness, while temperature modestly increased redness and firmness. Preliminary sensory evaluation supported these trends. Extrudates produced at 140 °C were perceived as having a more fibrous structure. Higher substitution levels resulted in a weaker, more crumbly texture. With respect to the environmental assessment, a 20% replacement of PPI with BRs or BSG reduced overall environmental impacts by up to 19% and climate impacts by up to 16%. With regard to the novel food status, the EU Novel Food Status Catalogue classifies BSG as not novel, whereas BRs are not novel only when used in food supplements. Any other food uses, other than as, or in, food supplements, might considered to be novel and consequently might need to be authorised under the novel food regulation framework prior to market placement. Full article

Quantitatively characterizing the dynamic evolution of fracture swarms under offset well low-frequency distributed acoustic sensing (LF-DAS) monitoring remains a significant challenge. This study proposes a physics-data dual-driven closed-loop inversion framework to address this problem. The framework consists of three core modules: (1) a fluid–solid coupled semi-analytical forward model applicable to variable-rate injection and shut-in conditions; (2) an automatic key feature identification method based on multi-scale scanning and physical polarity constraints; and (3) a dynamic inversion model for fracture swarms based on adaptive particle swarm optimization (APSO). Validation against the classical PKN model confirms that the proposed forward model accurately reproduces the fundamental fracture propagation behavior, with good agreement in fracture half-length and net pressure evolution. In synthetic inversion cases, the method successfully recovers the number of fractures, the dynamic flow rate allocation history, fracture length evolution, and the spatiotemporal strain rate response. A field application further demonstrates that three dominant fractures were generated during stimulation, reaching the vicinity of the monitoring well at 18, 27, and 46 min with corresponding spacings of approximately 21 m and 16 m. The proposed framework provides a new route for advancing LF-DAS monitoring from qualitative interpretation to quantitative dynamic inversion. Full article

High-fidelity haptic interfaces are widely assumed to enhance virtual reality (VR) training; however, they can trigger a “fidelity paradox” where hardware complexity paradoxically degrades usability. Grounded in Task-Technology Fit (TTF) theory and Hassenzahl’s pragmatic-hedonic quality framework, this study investigates the mechanisms underlying this paradox through a within-subject experiment ($N=70$) in a VR cooking simulation comparing three interface paradigms: VR controllers (VRC), hand tracking (HT), and haptic gloves (HG). Results confirmed that HG’s low task-technology fit—manifested as tracking errors, physical resistance, and increased operational overhead—generated significantly higher extraneous cognitive load (H1) and degraded interaction satisfaction (H2) despite its superior intended sensory resolution. Critically, in the HG condition, pragmatic quality (technical reliability) was identified as the dominant driver of satisfaction, while hedonic quality additions (thermal feedback) did not show a significant independent contribution to satisfaction in the HG condition. Perceived training effectiveness remained above the neutral threshold across all conditions (H3), indicating that content-level TTF is preserved independently of interface-level TTF mismatch. These findings suggest that VR interface design should prioritize “functional sufficiency”—ensuring tools serve as transparent, seamless extensions of the user—over the blind pursuit of sensory maximization. Full article

As a core area for soil and water conservation on the Loess Plateau and a national primary shale oil production zone, Qingyang City faces an increasingly acute contradiction between its inherently fragile ecological base and energy development activities. From the dual perspectives of ecological regulating services and production-supporting services, this study selected six key ecosystem services—habitat quality (HQ), soil retention (SR), carbon storage (CS), water yield (WY), food supply (FS), and grassland forage supply (GS)—to comprehensively assess their spatiotemporal evolution, trade-off/synergy relationships, and driving mechanisms from 2000 to 2020. The results indicate: (1) Significant changes occurred in the total amounts and spatial patterns of all ecosystem services during 2000–2020. HQ showed a fluctuating upward trend, while SR, FS, and GS increased overall; by contrast, CS and WY generally declined. (2) Ecosystem services exhibited a differentiated pattern characterized by “intra-category synergy and inter-category trade-off.” Regulating and supporting services were generally dominated by synergistic relationships, although clear differences remained among specific service pairs; provisioning services generally showed trade-offs with regulating services, among which the trade-offs between FS–HQ and between FS–GS were the most pronounced, whereas FS–CS showed a certain degree of synergy. (3) Driving force analysis revealed a continuous decline in the influence of natural factors and a sharp intensification of human activity factors. Groundwater level and land-use intensity became core drivers of pattern shifts, with their explanatory power increasing significantly. The study reveals that ecosystem services in Qingyang have rapidly transitioned from being dominated by natural hydrothermal conditions to being profoundly reshaped by energy development activities, exposing the region to the ecological risk of a “resource curse.” These findings provide a scientific basis and management insights for achieving coordinated development between resource exploitation and ecological conservation in ecologically fragile areas of the Loess Plateau. Full article

Energy use remains central to Colombia’s economic growth, yet its composition shapes the scale and direction of environmental outcomes. This study investigates how coal, oil, and hydroelectricity influence ecological degradation within the context of economic growth. The study applies cross-quantilogram and bootstrap Fourier Granger causality techniques to capture directional dependence and predictive causality across different quantiles, respectively. The findings show that the relationships are heterogeneous rather than uniform across the distribution. Economic growth exhibits a predominantly negative dependence on ecological footprint, suggesting that higher output is associated with lower ecological pressure under several environmental states. Hydroelectricity also shows a largely negative dependence, indicating its general contribution to environmental sustainability, although this effect weakens under extreme conditions. By contrast, the effects of coal and oil are more conditional and vary across quantiles, reflecting the complex role of fossil fuels in Colombia’s environmental dynamics. The bootstrap Fourier Granger causality results further reveal that causality is not constant across the distribution, but emerges only at specific quantiles. The central policy implication from this result lies in adopting an adaptive environmental strategy in which preventive measures dominate under low degradation, green-supportive policies are emphasized under moderate degradation, and stronger corrective interventions are implemented under high ecological stress. Full article

The large-scale generation of industrial waste salts (IWSs) across sectors such as coal chemical, pesticide, pharmaceutical, and dye manufacturing has raised increasing environmental and regulatory concerns. These IWSs often exhibit complex physicochemical profiles—featuring high concentrations of inorganic salts, persistent organic pollutants, and trace heavy metals—that pose significant challenges for both safe disposal and resource recovery. This review provides a comprehensive and pollutant-oriented overview of industrial waste salts, focusing on their sector-specific characteristics, dominant contaminant types, and tailored treatment strategies. Removal pathways for organic matter (e.g., thermal decomposition, advanced oxidation) and inorganic impurities (e.g., precipitation, ion exchange) are systematically analyzed, followed by technical pathways for salt separation based on crystallization and membrane processes. Resource utilization routes for major salt components, particularly NaCl and Na₂SO₄, are critically assessed in terms of technical feasibility, impurity tolerance, and end-use compatibility. The emergence of reclaimed salt quality standards and sector-specific impurity thresholds reflects a paradigm shift from purity-based to performance-based reuse evaluation. Finally, the review highlights future priorities including adaptive impurity control, downstream-specific salt grading, and enforceable regulatory frameworks to ensure the safe, scalable, and circular deployment of reclaimed salts in industrial systems. This study supports the coordinated advancement of control technologies and reuse standards, enabling the transformation of waste salts from environmental liabilities to secondary resources. Full article

This article presents a systematic bibliometric analysis on academic research into Artificial Intelligence (AI) applications in Architectural Conceptual Design (ACD). Based on a curated selection of publications indexed in the Web of Science (WoS) and Scopus databases between 2010 and 2025, this article shows a study that maps the intellectual evolution, thematic composition, and methodological trends of the field. By using the software tool VOSviewer, this study generates a series of knowledge graphs, including Keyword Co-Occurrence and International Collaboration Networks. The findings from this study reveal a rapid acceleration in AI-related research focused on the conceptual design stage, highlighting its transformative potential for architectural practice. Through a critical analysis of bibliometric results, this study identifies dominant research emphases, emerging directions, and persistent frictions between academic approaches and industry adoption. This review article contributes to the theoretical consolidation of AI applications in ACD and provides a structured foundation for future ACD-related research and practice. Full article