Search Results (4,504)

Point-of-interest (POI) data are widely used as urban big data to sense the functional organization of urban land and associated socioeconomic activities. Yet, POI-based studies often treat these records as temporally stable, even though different POI categories vary in turnover and responses to external shocks, affecting the comparability of urban sensing over time. Using POI datasets for Changzhou, China, from 2016, 2019, 2022, and 2025, this study examines category-specific changes before, during, and after the COVID-19 disruption. The results identify three patterns: government-driven POIs (government and residential) show high stability and retention; government–market hybrid POIs (financial and educational) exhibit moderate stability; and market-driven POIs (catering and shopping) have low stability. Across periods, change intensity is inversely related to stability. During the pandemic, turnover increased across all categories, retention declined markedly, and most replacements occurred within the same category, indicating functional continuity despite entity-level change. Although the overall spatial framework of urban functions remained broadly stable, new hotspots emerged during the pandemic and some persisted into the recovery period. These findings demonstrate that POI-based urban sensing is temporally contingent and that category-specific dynamics should be considered when interpreting urban land-use functions and supporting land-use planning under disruptive events. Full article

Post-fire plantations play a crucial role in recovering carbon stocks, yet how carbon is partitioned among vegetation, litter, and soil pools during stand growth dynamics remains insufficiently resolved for Quercus acutissima plantations. Forest ecosystems play a crucial role in the global carbon cycle. This study quantified carbon-storage allocation and identified stand characteristics and soil factors associated with carbon recovery in fire-affected Q. acutissima plantations. Using a chronosequence design, we compared five stand-age classes (4, 10, 25, 45, and 50 years) on Huangfu Mountain, China, and measured carbon stocks in tree organs, understory vegetation, litter, and the 0–30 cm soil layer. Ecosystem carbon stock increased from 31.64 t ha⁻¹ in 4-year-old stands to 230.66 t ha⁻¹ in 50-year-old stands, representing a 629% increase. Soil was the dominant carbon pool, with 0–30 cm soil carbon rising from 25.32 to 126.56 t ha⁻¹ (a 400% increase). The contribution of soil carbon to total ecosystem storage declined from approximately 80% in 4-year-old stands to 55% in 50-year-old stands, indicating a shift in allocation toward vegetation biomass over time. Carbon accumulation was primarily concentrated in the 0–10 cm layer. Tree basal area was significantly associated with ecosystem carbon stocks, identified as a key structural factor linked to carbon accumulation through potential direct and indirect pathways involving light availability and soil carbon. Soil organic matter and nitrogen were also positively correlated with carbon accumulation. These findings suggest that stand development and topsoil carbon formation are closely linked to post-fire carbon recovery processes. Future management measures should optimize stand density, maintain soil fertility, and protect surface carbon to enhance long-term carbon sequestration. Full article

High-dimensional engineering datasets often combine class imbalance, noisy structures, and limited ground truth, making unsupervised analysis difficult to evaluate reliably. This study quantifies how three properties—partition stability, minority class recovery, and topological interpretability—are traded off across clustering methods, using a capacity-matched 25-seed comparison on a TCGA-derived RNA expression dataset (10,095 samples, 19 cancer types, 13,634 genes). We compare K-means across cluster counts $k\in \{19,\dots ,400\}$, self-organizing maps (SOMs) across lattice sizes from 25 to 625 nodes, consensus K-means, a granularity-matched SOM-Super20 control, and four modern baselines (HDBSCAN, spectral clustering, Gaussian mixtures, and Leiden). At matched prototype budgets, K-means is both more reproducible and substantially better at recovering minority classes than SOMs: at 400 prototypes, K-means achieves pairwise NMI $0.819$ versus $0.621$ for the $20\times 20$ SOM and recovers the smallest cancers 6–$14\times$ more effectively (pancreas effective coverage $0.760$ vs. $0.054$).Crucially, the SOM does not close this gap even when given more prototypes ($0.07$ at 625 nodes), so, under matched capacity, minority recovery is better explained by representational capacity and centroid allocation freedom than by topology preservation. The recovery is not free: increasing k overfragments the partition and lowers the pairwise ARI stability ($0.643\to 0.419$ from $k=20$ to $k=400$), while the NMI remains robust ($\approx 0.82$). The hardest minority, pancreas, is recovered only by high-capacity K-means and by no other method evaluated, including SOMs at any size, consensus K-means, SOM-Super20, HDBSCAN, Gaussian mixtures, spectral clustering, and Leiden. The SOM’s distinct value is therefore not stability or recovery but the interpretable two-dimensional topological visualization that it uniquely provides, including a gradient-organized structure that is reproducible across seeds for kidney (weaker for uterus). No single method optimizes all three properties; the appropriate choice depends on whether a task prioritizes reproducibility, minority recovery, or visual interpretability. Because these conclusions follow from the shape of the data and the allocation behavior of the algorithms rather than from biological semantics, we expect them to transfer to high-dimensional imbalanced engineering data, such as those from fault clustering, condition monitoring, and anomaly detection. Full article

Intracranial abscesses are extremely rare in alpacas, and previously reported cases have lacked systematic etiological characterization. The virulence characteristics of Mammaliicoccus sciuri (formerly Staphylococcus sciuri) in alpaca intracranial infections remain unclear. We investigated an alpaca with chronic otitis media and an intracranial abscess. Bacteria were recovered from intracranial purulent material and several other sites. A representative isolate was designated CS234. It was identified as M. sciuri by 16S rDNA sequencing and whole-genome sequencing (WGS). Average nucleotide identity (ANI) analysis showed 95.58% identity with M. sciuri NCTC12103. WGS identified mecA, mecA1, fexA, optrA, and sal(A). The isolate showed phenotypic resistance to aminoglycosides, tetracyclines, and macrolides. PCR screening detected several virulence-associated gene targets, including exhB and tsst-1. To our knowledge, this is the first report of exhB in M. sciuri. In an intraperitoneal mouse challenge, the median lethal dose (LD₅₀) was 4.4 × 10⁷ colony-forming units (CFU)/g body weight. Multiple-organ lesions were also observed. These findings indicate systemic pathogenic potential in mice. Recovery of M. sciuri from several affected sites indicates a strong etiological association with the suppurative disease in this alpaca. These findings expand current knowledge of M. sciuri infection and antimicrobial resistance in alpacas. They may also aid the diagnosis and treatment of similar cases. Full article

Combined drought–heat stress is not adequately described by adding the responses to drought and heat in isolation. Water limitation restricts evaporative cooling, whereas high temperature increases atmospheric demand and threatens photosynthesis, proteostasis, and reproduction. To assess what has been demonstrated rather than merely proposed, we combined a structured narrative review with a study-level evidence map spanning genomics, multi-omics, and emerging artificial intelligence (AI). The PubMed search, updated on 9 August 2026, returned 254 records; targeted and backward searches contributed eight seminal or reviewer-nominated publications. Independent screening retained 90 verified publications: 69 direct combined-stress studies, 11 genomics studies, six original AI or prediction studies, and four reviews or quantitative syntheses used for context. No conserved molecular signature emerged. Response direction varied with soil water status, vapor-pressure deficit, stress order, tissue, and developmental stage. Carbon allocation, redox and proteostasis balance, reproductive failure, and recovery recurred across omics layers, although neither their direction nor their adaptive value was consistent. Genomic loci and predictive performance were also environment dependent. Direct uses of AI remain uncommon and currently support prioritization more convincingly than causal inference. We organize this uneven evidence as a ladder extending from molecular association to functional validation, multi-environment prediction, and cultivar deployment. The main shortage is not another nominal omics layer but harmonized factorial experiments that measure recovery and reproduction, report field-relevant environmental metadata, and include external validation. Full article

Hydraulic perturbations are among the earliest plant-wide consequences of drought, salinity and wounding, yet they are often treated as passive outcomes rather than as biologically interpreted inputs. This review distinguishes hydraulic state, hydraulic perturbation and hydraulic signal, and evaluates how organ-scale pressure and water-potential changes are converted into local membrane tension, wall strain, turgor and water-flux cues. We propose, as a testable model rather than an established mechanism, a distributed architecture comprising OSCA/TMEM63 and other mechanosensitive channels, cell-wall integrity pathways, aquaporin-mediated conductance control and vacuolar buffering. Evidence for the individual components is substantial, but evidence that they act together within a single physiological event is still limited. These layers are reciprocally coupled to Ca²⁺, ROS, electrical, hormonal and peptide networks. Hydraulic cues are fast, and they differ in amplitude, direction, rise time, duration, recovery and anatomical route, so they are not informationally inert. Specificity nevertheless appears to emerge from the integration of the hydraulic waveform with tissue state and coincident ionic, electrical and biochemical inputs rather than from any single variable. We compare drought, salinity and wounding; clarify the roles of roots, vasculature, bundle sheath, mesophyll and guard cells; and outline experiments that combine calibrated physical perturbations with live reporters, tissue-specific genetics and hydromechanical modeling. The key frontier is no longer to document that pressure changes occur. It is to identify the variables directly sensed, to separate instructive from permissive roles, and to test whether dynamic decoding traits improve crop resilience at acceptable carbon and growth cost. Full article

Biodiesel production from waste cooking oils, non-edible oils and other low-grade lipid feedstocks is constrained by free fatty acids, water, salts, oxidation products, and the poor miscibility of triglycerides with short-chain alcohols. Carbon–inorganic hybrid catalysts are attractive because the inorganic phase can provide strong acid or base sites, while the carbon phase can alter dispersion, wettability, pore accessibility, microenvironment polarity, leaching, and recovery. Yet the term hybrid is often applied to materials for which the carbon component has not been shown to affect catalysis. This critical review therefore focuses on one defined reaction scenario: esterification and transesterification for biodiesel production from low-grade lipid feedstocks. The discussion is organized by the catalytic problem rather than by an unrestricted catalogue of materials. Carbon-supported CaO and MgO, carbon-coupled layered-double-hydroxide-derived mixed oxides, sulfonated carbon–inorganic acids, bifunctional acid–base systems, magnetically recoverable ferrite/carbon catalysts, and graphenic supports are compared through structure–activity relationships, reaction conditions, feedstock quality, FAME yield, heterogeneity, reusability, and post-reaction evidence. Particular attention is given to the distinction between a true interfacial effect and activity caused by leached Ca, K, Na or sulfonic species. A minimum evidence hierarchy is proposed, requiring carbon-only, inorganic-only, and physical-mixture controls, hot-filtration tests, elemental analysis of the liquid phase, recovered-mass accounting, and post-reaction structural characterization. The literature shows that high first-cycle yield is common, whereas water tolerance, low leaching, retained active-site density, and continuous operation remain uncommon. The most defensible future direction is therefore not greater compositional complexity, but simpler hybrid architectures designed around a specific failure mode and validated under realistic feedstock and reactor conditions. Full article

Background: Work-related fatigue is a preventable occupational health concern in high-intensity manufacturing environments. However, supervisors and occupational health services often lack transparent criteria to support the preventive review of overtime practices. This study developed and internally validated an explainable human-in-the-loop concurrent screening model to identify employees with currently elevated work-related fatigue using routinely collected working-hour records and occupational health examination data. Materials and Methods: De-identified administrative and occupational health data from 314 full-time manufacturing employees were linked with standardized fatigue assessment data. Currently elevated work-related fatigue was defined using the top quartile of the standardized work-related fatigue subscale. To reduce information leakage, the work-related fatigue score used to define the outcome was excluded from the predictor sets. Multivariable logistic regression and XGBoost were compared using nested stratified five-fold cross-validation, with aggregated out-of-fold predictions from the outer folds used for the performance evaluation. Model performance was assessed using discrimination, probabilistic accuracy, calibration, and classification metrics at provisional, study-specific thresholds. Results: XGBoost demonstrated greater discrimination and better overall probabilistic accuracy than logistic regression, with an AUC of 0.77 versus 0.68 and a Brier score of 0.14 versus 0.17, respectively. At the provisional study-specific threshold of τ1 = 0.28, XGBoost achieved a sensitivity of 0.78 and a specificity of 0.70. Using τ1 = 0.28 and τ2 = 0.55, 58.0%, 27.1%, and 15.0% of employees were classified into provisional low-, moderate-, and high-priority tiers, respectively. The observed prevalence of currently elevated work-related fatigue increased across these tiers from 9.3% to 28.2% and 78.7%, respectively. Calibration assessment indicated systematic miscalibration for both XGBoost (intercept α = 0.78, slope β = 1.64) and logistic regression (α = −0.49, β = 0.56). Because τ1 and τ2 were selected and evaluated using aggregated out-of-fold predictions generated from the same single-organization development dataset, their stability and transportability are unknown. Medium-term cumulative overtime, particularly during months −2 to −6, together with routinely measured indicators of vulnerability and recovery, contributed substantially to the model-estimated probability of currently elevated fatigue. Conclusions: Routinely collected working-hour and occupational health examination data may support explainable concurrent screening for currently elevated work-related fatigue and illustrate a potential framework for differentiated preventive reviews. However, the proposed thresholds and review-priority tiers are provisional and study-specific and should not be interpreted as implementation-ready decision rules for occupational health practices. Prospective temporal validation, external validation in independent organizations, and local recalibration are required before threshold-based implementation. Full article

The effects of transcutaneous electroacupuncture stimulation (TEAS) on large-scale brain function remain insufficiently characterized. This study employed a graph-theoretical approach to analyze electroencephalogram (EEG) data from 48 healthy participants in the Pilot-6 TEAS study. Participants received sham (0 pps), 2.5 pps, 10 pps, and 80 pps stimulation during baseline, stimulation, and recovery phases. Functional connectivity was assessed using coherence and the weighted phase-lag index, followed by calculation of global and nodal graph measures from thresholded weighted undirected sensor-level networks. Descriptive analysis indicated potential frequency-related differences in EEG network organization. The 2.5 pps condition exhibited the highest average degree, whereas the 80 pps condition demonstrated the highest average clustering coefficient. At 10 pps, sensor-level maps revealed a distinct frontal–central betweenness-centrality pattern. Although 48 participants provided usable EEG data for descriptive analysis, only 3 participants had complete matched graph-metric data for all four stimulation conditions, limiting repeated-measures statistical validation. After correction for multiple comparisons, no statistically significant frequency-related effects were observed, and nodal hub differences were not independently confirmed. Consequently, these patterns should be interpreted as descriptive and exploratory rather than established group-level effects. These findings indicate that graph-theoretical EEG analysis may facilitate the identification of candidate network features for future investigations of TEAS-related brain network organization. Full article

Mycotoxin contamination remains a persistent threat to food and feed safety owing to the chemical stability of many mycotoxins, frequent co-occurrence, and matrix-dependent risks. Enzymatic detoxification enables structure-targeted transformation of toxicity-determining motifs, such as epoxide rings, reactive double bonds, amide linkages, and lactone structures. However, free mycotoxin-degrading enzymes are often constrained by poor operational stability, difficult recovery, and limited adaptability to complex matrices. Metal–organic frameworks (MOFs) provide programmable microenvironments for enzyme immobilization through tunable pore structures, interfacial chemistry, and confinement effects. This review links toxic structural motifs with enzymatic transformation targets, discusses MOF–enzyme interface engineering and representative host–enzyme compatibility, and evaluates application modes including single-enzyme systems, multi-enzyme co-immobilization or cascade systems, adsorption–degradation coupling, and detection–degradation integration. Key bottlenecks involving enzyme leakage, mass-transfer limitation, real-matrix stability, scalable preparation, and biosafety are critically discussed. Rather than treating MOFs as passive enzyme carriers, this review proposes an application-oriented framework that integrates toxin structure, enzyme function, MOF interface regulation, matrix compatibility, and safety validation to guide the development of MOF-immobilized degrading enzymes for practical mycotoxin detoxification. Full article

The fabrication of efficient Fenton catalysts from solid waste offers a sustainable strategy for achieving waste valorization and wastewater remediation. In this work, after selective separation of valuable Li from spent lithium iron phosphate (LFP), the generated iron-rich slag (IRS) was employed as a Fenton catalyst for the degradation of organic pollutants. IRS catalysts consist of lumpy particles with abundant active sites, enabling efficient H₂O₂ activation. Under optimal conditions, 99.62% of doxorubicin hydrochloride (DOX) can be degraded within 30 min with a rate constant of 0.30 min⁻¹. In the continuous-flow degradation experiment, the catalyst maintains a DOX removal efficiency of over 90% at an effluent volume of 1400 mL. The IRS catalyst exhibits efficient DOX degradation over a wide pH range (2.0–8.0), and it also potentially removes different pollutants, including amodiaquine, tetracycline, methyl orange, and methylene blue. Quenching tests and characterizations reveal the dominant contribution of ·OH radicals as reactive species, while the Fe²⁺/Fe³⁺ cycle facilitates continuous H₂O₂ activation. This work establishes an integrated strategy coupling lithium recovery from spent LFP with catalyst production for advanced wastewater treatment. Full article

Reclaiming coastal saline–alkali land is important for food security, yet little is known about how irrigation and biochar jointly affect the fate of fertilizer nitrogen in these soils. Using ¹⁵N isotope tracing, this field experiment tracked the distribution and recovery of labeled fertilizer in a soil–sunflower system under three irrigation quotas (8, 16, and 24 mm per event, applied every 10 days) and four biochar rates (0, 3, 5, and 7 t·ha⁻¹). After harvest, approximately 73% of residual ¹⁵N remained in the 0–40 cm topsoil, with organic-bound N as the dominant fraction (72–74%). Mineral ¹⁵N increased with soil depth, indicating downward movement with water flow. Within sunflower plants, labeled N accumulation followed the order flower head > stem > leaf > root, with heads containing 11–12 times more ¹⁵N than roots, confirming active transport to reproductive organs. Overall ¹⁵N use efficiency ranged from 18.8% to 24.9% across treatments. Increasing biochar rate enhanced ¹⁵NUE by up to 28.2% under the same irrigation regime, whereas raising irrigation from 16 mm to 24 mm reduced ¹⁵NUE by 3.2–3.8%. Mass balance analysis showed that moderate irrigation (16 mm) combined with high biochar (7 t·ha⁻¹) achieved the highest plant ¹⁵N recovery (24.9%), maintained 70.0% of labeled N in soil, and limited unaccounted ¹⁵N to only 5.1%. These findings demonstrate that integrated water–biochar management can optimize fertilizer N retention and crop uptake in coastal saline–alkali soils, providing a scientific basis for precision fertilization in these degraded lands. Full article

Background/Objectives: Cardiovascular toxicity and pre-existing cardiovascular disease can affect cancer-treatment tolerance, functional recovery, and survivorship. This narrative review aimed to summarize current evidence and propose an author-derived risk-adaptive clinical framework for adult cardio-oncology rehabilitation (CORE), organized around exercise prescription, multimodal monitoring, and implementation. Methods: PubMed/MEDLINE and the Web of Science Core Collection were searched from database inception through 27 July 2026. Guidelines, systematic reviews, randomized and non-randomized clinical studies, feasibility studies, and selected mechanistic sources were prioritized according to their relevance to the three review domains. Evidence was classified as direct clinical, guidance/synthesis, feasibility/implementation, or mechanistic/conceptual; no PRISMA protocol, formal risk-of-bias assessment, or meta-analysis was undertaken. Results: Clinical trials support improvements in cardiorespiratory fitness, selected cardiovascular risk factors, and functional outcomes in some settings, but effects on cancer therapy-related cardiac dysfunction, cardiovascular events, and mortality remain uncertain. Direct evidence is dominated by breast-cancer cohorts and women, although mixed-cancer, lymphoma, and lung-cancer studies broaden the functional evidence base. An evidence-informed approach is to individualize aerobic and resistance exercise to treatment context, symptoms, functional capacity, and clinical stability, with reassessment linked to actionable findings; the proposed pathway remains conceptual and non-validated. Artificial intelligence, digital twins, omics, and monitoring-guided exercise-dose adjustment remain investigational. Conclusions: CORE is best regarded as exercise-centered care linked to guideline-based risk assessment and clinically indicated reassessment. Prospective studies should test therapy-specific timing, risk-stratified delivery, monitoring-guided dose adjustment, clinical endpoints, equity, and cost-effectiveness. Full article

Food waste digestate is a high-moisture organic residue that requires effective stabilization before resource recovery or land application. This engineering-scale study compared high aeration (HA, 0.30 L·min⁻¹·kg⁻¹ dry matter), low aeration (LA, 0.15 L·min⁻¹·kg⁻¹ dry matter), and turning without forced bottom aeration (TG) during a 30-day food waste digestate–corn straw co-composting experiment. One engineering-scale pile was operated for each treatment. Physicochemical trajectories, bacterial succession, predicted functional potential, and microbial co-occurrence patterns were evaluated. All treatments rapidly entered the thermophilic phase. HA reached the highest temperature (63.70 °C) and remained above 55 °C for 340.8 h, but it also had the lowest final moisture reading (18.62%). LA achieved the greatest organic matter (OM) reduction (17.47%), compared with 13.47% in HA and 7.44% in TG, while retaining more moisture than HA at day 30. Bacillota became dominant in all treatments, although the intensity of thermophilic filtering and the pattern of late-stage succession differed among treatments. Functional predictions indicated the highest late-stage ureolysis potential in LA, whereas TG showed greater predicted representation of several nitrogen-transformation-related groups and the densest co-occurrence network. These findings suggest that engineering-scale composting performance depends on the balance among oxygen supply, heat accumulation, moisture conservation, and microbial organization rather than on thermophilic intensity alone. Under the tested conditions, LA provided the most favorable balance, particularly in terms of OM reduction and moisture retention. Full article

Agricultural lands in Russia are increasingly being converted into fallow areas, making the study of potentially mineralizable carbon (PMC) in fallow soils essential for understanding post-agrogenic ecosystem functioning. This study provides a comparative assessment of the spatial and temporal dynamics of PMC in soils of the Leningrad and Novgorod regions (Bankovo, Belogorka, and Borovichi sites) under different land-use types, including fallows of various ages, arable, garden, pasture, hayfield soils, and secondary forests. Total carbon content was determined by high-temperature dry combustion, while basal respiration was measured using a standard incubation method. PMC parameters were estimated using biokinetic fractionation of soil organic matter (SOM), and cumulative carbon release was calculated as the sum of emissions over the incubation period. The highest basal respiration values among the studied fallow soils were observed in fallow soils at the Bankovo site (1.44–1.66 µg CO₂–C g⁻¹ h⁻¹). Carbon stocks in most fallow soils were lower than those of the corresponding background soils, although the magnitude of differences varied among sites. Both the size of the PMC pool and its mineralization rate varied among fallow soils depending on post-agrogenic succession, vegetation type, and site-specific environmental conditions. The highest cumulative C-CO₂ production was recorded in degraded pasture soils and secondary forests at Borovichi. Restorative ecosystems generally showed higher carbon-mineralizing activity than arable and garden soils, although turnover characteristics varied among sites. Region-specific patterns related to parent material and environmental conditions were identified. Even after long-term fallowing (up to 120 years), several soil properties remained different from background conditions, indicating prolonged and site-dependent recovery of organic matter dynamics. Full article