Search Results (19,584)

Bridge settlement prediction is essential for understanding structural deformation evolution and supporting bridge condition assessment. However, settlement monitoring sequences usually exhibit nonlinear characteristics, non-stationarity, and multi-scale fluctuations, which increase the difficulty of accurately capturing deformation evolution trends. This study develops an integrated settlement prediction and dynamic early warning framework for concrete bridges by combining Variational Mode Decomposition (VMD), Temporal Convolutional Network (TCN), and Bidirectional Long Short-Term Memory Network (BiLSTM). In the proposed framework, VMD is employed to decompose settlement monitoring sequences into multiple components with different frequency characteristics, TCN is used to extract local temporal variation features, and BiLSTM is applied to capture long-term temporal dependencies for settlement prediction. Based on the predicted settlement responses, settlement increment, settlement rate, and differential settlement indicators are further incorporated to establish a dynamic early warning method for deformation risk identification. Continuous monitoring data from an in-service reinforced concrete bridge were used for validation. The results show that the proposed framework achieves better prediction performance than benchmark models, with an R² of 0.956, MAE of 0.38 mm, RMSE of 0.51 mm, and MAPE of 1.52%. Furthermore, simulated abnormal settlement scenarios were constructed to evaluate the response capability of the warning framework under different deformation conditions. The results demonstrate that the proposed framework can effectively integrate settlement prediction and deformation risk assessment, providing a potential approach for bridge settlement monitoring and early warning analysis. Full article

Lewis acid-catalyzed epoxide openings efficiently promote intramolecular cyclizations forming complex oxygenated frameworks. Herein, we investigated the reactivity of epoxyolefins under catalytic conditions using various metal triflates. The study focuses on the competition between epoxide isomerization and intramolecular cyclization involving a pendant olefin. Screening of several metal triflates revealed that Lewis superacids, particularly Bi(OTf)₃, promote efficient transformations at room temperature with low catalyst loadings (1 mol%). Structural variation in the substrates significantly influenced product distribution likely through coordination effects, impacting cyclization efficiency with higher yields observed for non-chelating epoxyolefins. Substrates derived from geraniol underwent selective cyclization to cis-cyclic alcohols and bicyclic ethers in good yields, with stereochemical outcomes consistent with the Eschenmoser model. Reaction conditions such as temperature and catalyst loading further modulated selectivity, allowing control over product distribution. These results highlight the potential of metal triflates as versatile and efficient catalysts for the stereoselective intramolecular cyclization of epoxyolefins, offering access to cyclic frameworks under mild conditions. Full article

Arbuscular mycorrhizal (AM) fungi are often considered host generalists. Although the host-mediated assembly of AM fungal communities is well documented, its functional significance remains poorly understood, particularly in organic and low-input agroecosystems, where crop–weed interactions may influence the soil AM fungal reservoir. We investigated plant and AM fungal functional traits, mycorrhizal dependency (MD), and root AM communities in three legume crops and five weed species grown in pots with the same indigenous AM fungal inoculum. AM fungal communities were characterized using SSU rRNA gene clone libraries, sequencing, and terminal restriction fragment length polymorphism (T-RFLP) analysis. Of 825 examined clones, 792 were assigned to AM fungi, representing 23 RFLP types. Plant species significantly affected the plant traits, root colonization, spore density, extraradical mycelium density, and MD. PERMANOVA revealed that plant species explained 97.3% of the variation in the AM fungal community structure, although this result should be interpreted cautiously because within-species dispersion may have contributed to the explained variance. RELATE analysis showed a significant association between the AM fungal community structure and plant–AM fungal functional traits. The specific root length, shoot and root N concentrations, AM fungal colonization, and spore abundance best explained community patterns. Legume crops supported greater AM fungal development and positive growth responses, whereas several weeds hosted diverse AM communities without showing biomass benefits. These findings highlight that weed management could indirectly influence AM fungal persistence through host-mediated community assembly, although field validation is required. Full article

Aiming at the challenges of potato storage scenarios, severe target stacking and occlusion, and large variations in defect characteristics in potato storage environments, a potato defect detection method named MDS-DETR was proposed, and its deployment on a robotic sorting platform was validated. First, potato images under different illumination conditions and stacking states were collected in potato storage warehouses to construct a potato defect dataset containing defects such as black spot, sprouting, dry rot, decay, green skin, and cracking. Subsequently, according to the characteristics of object detection tasks in storage scenarios, an MCF module was designed to strengthen the extraction and integration of contextual features across different spatial scales. An AIFI-DyMona structure, namely Anchor-free Instance Feature Interaction with Dynamic Mona, was constructed to improve the stability of feature representation under different illumination conditions. In addition, the Shape-IoU regression strategy was incorporated to improve the network sensitivity to irregular defect contours and geometric characteristics. Validation experiments demonstrated that the proposed MDS-DETR framework achieved 96.3% mAP@0.5, with only 14.2 M parameters and 42.9 G FLOPs. Compared with several representative object detection algorithms, the proposed method exhibited superior recognition capability and stronger robustness under complicated storage conditions, while also showing better suppression of missed and incorrect detections. To further evaluate its practical applicability, the trained network was integrated into an intelligent potato sorting robot and tested in real warehouse scenarios. Experimental observations indicated that the robotic system consistently maintained a sorting accuracy exceeding 95%, demonstrating the effectiveness and practical deployment potential of the proposed approach for potato storage applications. This study can provide a reference for intelligent detection and automated sorting in potato storage processes. Full article

Variable-speed operation of scroll compressors is a prevailing trend for energy saving in refrigeration systems; however, complex electromagnetic excitation induces prominent vibration and noise, yet its dominant timing, spatial distribution, and action mechanism remain unclear. An electromagnetic–structural–acoustic sequential coupling model of a scroll compressor is established and validated at three speeds (3600–6600 rpm), and a dominance identification method integrating harmonic–modal matching, variational mode decomposition, and electromagnetic correlation identification is proposed. Predicted frequencies agree well with experiments; even-order harmonics migrate linearly with speed, with harmonic–modal matching exceeding 80% at low and medium speeds. At 5400 rpm, the 24th-order harmonic (2160 Hz) coincides with mode 2 (2162 Hz), causing resonance and a threefold amplitude increase. At low and medium speeds, vibration dominance indices range between 0.68 and 0.75, while noise dominance indices decrease from 0.55 to 0.48, dropping to 0.35 and 0.28 at 6600 rpm, indicating noise source transition. Vibration at S1 through S4 shows spatial variation, and far-field noise at F1 through F4 is non-uniform. These findings clarify how electromagnetic excitation dominates the vibration and noise of scroll compressors, providing a theoretical basis for speed-segmented and zone-specific noise source identification and control. Full article

The honeybee (Apis mellifera) gut microbiota serves as a model for host–microbe studies, as newly emerged workers provide a low-complexity, nearly germ-free system. Although multiple inoculation strategies are commonly applied under laboratory conditions, their comparative effects on microbial colonization remain incompletely understood. Here, we systematically compared four commonly used inoculation strategies, including pollen mixture feeding, oral feeding, dunk inoculation, and comb-exposed inoculation, under controlled laboratory conditions using an identical microbial source. We assessed gut microbiota establishment using spike-in 16S rRNA gene sequencing, enabling the quantification of both relative and absolute bacterial abundances, together with analyses of community composition, alpha diversity, and beta diversity. Our results showed that method-dependent differences were observed. Pollen mixture feeding and oral feeding produced highly comparable outcomes across the measured parameters, suggesting that dietary incorporation and direct oral delivery are similarly effective for establishing core gut communities (p > 0.05). Dunk inoculation also supported core bacterial colonization, although differences in beta diversity indicated some variation in community structure (p < 0.05). Comb-exposed inoculation showed the most pronounced differences, with significantly reduced bacterial abundance, lower alpha diversity, and decreased colonization of specific core taxa including Bifidobacterium and Snodgrassella alvi (p < 0.05). Importantly, despite these differences, none of the inoculation methods resulted in atypical communities dominated by noncore taxa, indicating that the core gut microbiota remained broadly conserved across treatments. Collectively, our findings indicate that although inoculation delivery methods differed fundamentally in inoculum volume, microbial concentration, and the mechanisms by which microbes were introduced into the bee gut, these distinct strategies can introduce measurable differences, while the established gut communities remain consistently dominated by core bacterial taxa. These results provide a basis for selecting appropriate inoculation strategies in experimental studies of honeybee microbiota. Full article

Background/Objectives: Empirical research exploring the linkages between community leisure facility diversity, distinct facility categories, and mental health outcomes among older populations remains scarce, especially regarding gender-specific variations. Methods: Grounded in social capital theory, this study establishes an analytical framework to unpack the underlying mechanisms of these relationships. Based on a sample of 10,270 adults aged 60 and older drawn from the 2023 CLASS, structural equation modeling is applied to investigate the correlational patterns, indirect transmission pathways, and gender heterogeneity embedded in these associations. Results: The results indicate that community leisure facility diversity is positively correlated with better mental health status among older adults, with a total association coefficient of 0.052. Social networks partially mediate this correlational pattern, with an indirect association value of 0.010. Five facility categories exhibit significant positive total associations with mental health, namely senior activity rooms (0.038), fitness centers (0.053), chess and card rooms (0.031), libraries (0.028), and community canteens (0.043), while their indirect association pathways present divergent features. Notably, the linkages between community leisure facilities and mental health are more pronounced for older men. Five facility types show significant positive associations with male mental health, whereas for older women, only senior activity rooms and fitness centers yield significant correlational patterns. Conclusions: These findings suggest that community leisure facility planning can be optimized by shifting from simple quantity expansion to refined, targeted provision with gender-sensitive design. Adopting gender-informed strategies, particularly prioritizing socially supportive facilities and reducing usage barriers for older women, offers a valuable direction for building age-friendly communities and promoting healthy aging. Full article

Introduction: The recognition of Complex Post-Traumatic Stress Disorder (CPTSD) as a distinct diagnosis in ICD-11 has intensified the need to clarify its boundaries with Borderline Personality Disorder (BPD), given their symptom overlap and shared traumatic origins. Therefore, this systematic review aimed to examine whether CPTSD is distinct from BPD, assess their comorbidity and symptom overlap, identify key criteria for differential diagnosis, and explore therapeutic implications. Method: A systematic search was conducted in PubMed, Scopus, and Web of Science following PRISMA 2020 guidelines. Seven empirical studies (2015–2025) were included, comprising 2574 adults (mean age 40.4 years; 73.3% women). Methods included latent class analysis, structural equation modeling, and network analysis. The methodological quality of the included studies was evaluated independently by two reviewers using the JBI Critical Appraisal Checklist for Analytical Cross-Sectional Studies. Results: Findings consistently supported that CPTSD and BPD are empirically distinguishable, though substantially correlated, particularly within the ICD-11 framework. High symptom co-occurrence was observed, with affective dysregulation identified as the symptom most centrally connecting the two symptom networks. Self-concept emerged as the most robust differentiator: stable and persistently negative in CPTSD versus unstable and fragmented in BPD. Shame was a key affective marker of more severe presentations, and trauma severity, rather than diagnostic category, was associated with symptom variation across studies. Conclusions: CPTSD and BPD are distinct yet frequently co-occurring conditions. Differential diagnosis should focus on self-concept stability, patterns of behavioral dysregulation, and shame. Treatment requires individualized, trauma-informed, and shame-sensitive approaches, with transdiagnostic emotion regulation strategies across presentations. These conclusions should be interpreted with caution, given the predominantly cross-sectional design and methodological heterogeneity of the available evidence. Full article

We investigate the structural limits of Variational Quantum Classifiers (VQC) for network anomaly detection in the Noisy Intermediate-Scale Quantum (NISQ) era. Using the official 20% research subset of NSL-KDD, we train a 4-qubit classifier that embeds 16 principal components by amplitude encoding and reaches 88% accuracy on the held-out partition. On the four established attack families, an explicit many-to-one decoding of the sixteen basis outcomes attains 71.8% in-sample accuracy and a macro-averaged recall of 0.787 on held-out attack records, against 0.250 for a majority-class classifier. Aggregate accuracy conceals that separation entirely: 78.4% for the trained model against 78.7% for the trivial one. Measuring class separability in the encoded states before training, amplitude encoding retains an AUC of $0.560\pm 0.018$ at sixteen components over five seeds, against $0.762\pm 0.020$ for angle encoding. Yet a trained comparison at matched parameter count on four components converts none of that advantage into accuracy: the separation is present in the encoded geometry and absent from the classifier, which implicates the readout alongside the encoding, a distinction this design does not separate. A controlled sweep over five ansatz depths and five seeds, spanning 8 to 72 trainable parameters at fixed encoding, data and decoding, finds subsample accuracy saturating at $0.880\pm 0.005$ while the training objective keeps falling, with a parameter-matched circuit trailing a 73-parameter classical network by 7.9 points across the two protocols compared. Depth is therefore not the binding constraint. On KDDTest+, classical recall on novel signatures falls by 19 to 32 points while the variational classifier shows no comparable decline. Full article

Bovine neonatal diarrhea (BND) is a leading cause of morbidity and mortality in pre-weaned calves. Commercial maternal vaccines targeting bovine rotavirus (BRV), bovine coronavirus (BCoV), and enterotoxigenic Escherichia coli (ETEC) have been available for decades, yet field outbreaks continue in vaccinated herds. This review examined peer-reviewed literature published between January 2019 and March 2026, identified through a structured PubMed search supplemented by reference-list screening. For BRV, a field strain sharing its VP7 genotype with a vaccine component was not neutralized by vaccine-induced antiserum, indicating that genotype concordance does not predict serologic coverage. For BCoV, hemagglutinin-esterase variation and regional lineage divergence indicate surface-protein evolution, although data linking these changes to reduced efficacy are not available. For ETEC, adhesin diversity and antimicrobial resistance affect both vaccination strategy and case management. Maternal vaccination retains biological value, but field performance is constrained by colostral variability, incomplete passive transfer, and product-to-product immunogenic differences. For all three pathogens, antigenic divergence from vaccine strains is located at individual epitopes, receptor-binding domains, or adhesins rather than at the level of whole-pathogen identity. Subunit and multi-epitope antigen designs, for which proof-of-concept constructs have been reported, operate at this level, and their selection requires characterization of candidate antigens for efficacy, diversity, polymorphism, and cross-protective breadth. Such antigen improvements address the pathogen-side gap but not the passive-transfer and mucosal constraints. Functional surveillance to guide antigen updating, field trials that measure passive-transfer efficiency, and adjunctive strategies are identified as priorities for BND control. Full article

The lipid and fatty acid composition of the little Baikal oilfish (Comephorus dybowskii Korotneff, 1905) was studied to identify the features of its biochemical adaptation to the environmental conditions of Lake Baikal. Multivariate analysis of lipid classes and FA profiles revealed reproducible clustering patterns in both muscle tissue and whole-body samples, indicating the presence of distinct physiological states differing in membrane organization and lipid metabolism. Lipid-class variability was primarily associated with sphingomyelin, cholesterol esters, phosphatidylinositol, and lysophosphatidylcholine, suggesting the coordinated regulation of membrane structure. The fatty-acid profiles were mainly presented by variations in saturated, monounsaturated, and long-chain polyunsaturated fatty acids, with muscle tissues characterized by a relatively longer carbon chain (ACL = 19 vs. 18 I whole body) and unsaturation (UI = 1.98–2.76 vs. 1.64–2.53 in whole body). At the same time, comparative analysis demonstrated low correspondence between lipid and FA profiles, indicating partially independent adaptive mechanisms. The experimental transfer of fish from their natural habitat to controlled conditions resulted in the significant remodeling of both lipid and FA compositions, including increases in acylglycerols, membrane phospholipids, and monounsaturated fatty acids, together with a decline in long-chain n-3 polyunsaturated fatty acids. The results suggest that lipid classes and fatty acids represent complementary but functionally distinct levels of biochemical adaptation contributing to the maintenance of membrane organization and metabolic homeostasis in C. dybowskii, revealing a previously undescribed multi-level organization of lipid-related adaptive responses in this endemic deep-water fish. Full article

Lethal foodborne illness outbreaks represent a critical intersection of public health surveillance, environmental health, and forensic toxicology. When acute gastrointestinal syndromes lead to sudden death, traditional postmortem investigation techniques are often hindered by tissue autolysis and the overgrowth of putrefactive microflora, which complicate conventional microbiological assays. This review establishes a comprehensive framework for chemical forensics by evaluating the utility of stable isotope analysis (SIA) as a supportive, probabilistic chemical proxy to complement traditional epidemiological investigations of postmortem food contamination sources. Following JBI scoping review guidelines and the PRISMA-ScR reporting framework, data from 42 peer-reviewed articles (2000–2026) were charted and synthesized to map natural isotopic variations (δ¹³C, δ¹⁵N, δ¹⁸O, δ²H and δ³⁴S) across both forensic decedents and environmental reservoirs. The findings outline a structured, multi-tissue diagnostic cascade governed by biological metabolic turnover rates: unabsorbed gastric chyme provides a direct chemical match to contaminated source food items within a hyper-acute 0–6 h window; high-turnover visceral matrices (liver, blood plasma) shift to reflect acute exposure profiles within 1–7 days; and continuously fixed keratinized matrices (hair, nails) archive multi-month dietary and transcontinental transit histories. Furthermore, compound-specific isotope analysis (CSIA) of individual amino acids offers unprecedented structural resolution, utilizing the carbon discrimination metric (Δ¹³C_glu-phe) to differentiate pristine agricultural signatures from endogenous metabolic distortions while biochemically verifying pre-mortem physiological stress and hyper-catabolic muscle wasting. Taphonomic thresholds were explicitly defined, establishing that bulk visceral soft tissues remain isotopically stable (±0.3‰) for up to 48 h at room temperature (~21 °C) before microbially induced nitrogen enrichment (δ¹⁵N > +2.8‰) alters native profiles, whereas hair and nail keratin maintain absolute isotopic stability for over 180 days postmortem. When pristine multi-isotope signatures are coupled with mandatory chloroform–methanol lipid extraction and processed through spatial Bayesian assignment models, geographic provenance tracking via environmental isoscapes achieves a predictive accuracy of 97%. This review introduces a standardized environmental health protocol designed to harmonize field environmental sampling with medical autopsies. This protocol provides a legally robust strategy for investigating unresolved lethal foodborne illness case-outbreaks, particularly those involving pediatric mortalities linked to the consumption of counterfeit or fraudulent food products in low- and middle-income countries. Furthermore, it aims to strengthen national and municipal legal frameworks and international biosecurity enforcement. Full article

Maintaining genetic diversity is essential for the long-term conservation of migratory freshwater fishes facing increasing anthropogenic pressures. Prochilodus magdalenae (bocachico), one of Colombia’s most economically and ecologically important freshwater fish species, supports artisanal fisheries, regional food security, and the livelihoods of local communities but has experienced population declines associated with overfishing, habitat degradation, and hydrological alteration. This study evaluated the genetic diversity and population structure of wild and hatchery-associated P. magdalenae from northern Colombia using sequence-based microsatellite genotyping (SSR-GBS). Sixty individuals (48 wild adults from three localities in the Department of Sucre and 12 hatchery-associated fingerlings from Cereté) were genotyped at seven polymorphic microsatellite loci. Wild populations retained high genetic diversity and exhibited weak but significant genetic differentiation (FST = 0.017, p = 0.003), with only 2% of the molecular variation distributed among populations and high estimated gene flow (Nm = 14.899). Hatchery-associated fingerlings consistently exhibited lower allelic richness while maintaining relatively high heterozygosity. Rarefied allelic richness did not differ significantly among populations (Kruskal–Wallis, p = 0.400); however, hatchery-associated fish consistently showed lower values, highlighting the value of allelic richness as a complementary indicator for evaluating hatchery-produced stocks. These findings provide a genetic baseline for the conservation of P. magdalenae and support incorporating routine genetic monitoring into supportive breeding and restocking programs. Full article

Architectural design problems vary significantly in their degree of definition, and this variation may influence the creative outcomes of student work. This study provides an empirically validated comparison of creativity scores across well-defined and ill-defined architectural design problems, employing a five-criterion framework (elaboration, imagination, flexibility, fluency, and originality) and a double-blind expert jury protocol. By moving beyond theoretical claims, the study offers quantitative evidence on how problem structure shapes creative performance in architectural education. Architecture students were asked to produce solution sketches for both well-defined and ill-defined problems. The creativity of the resulting products was evaluated by an independent jury of domain-expert academics using five criteria established in the literature: elaboration, imagination, flexibility, fluency, and originality. Evaluation scores were subsequently analyzed with statistical methods to determine which problem type elicited higher creativity. In a sample of 20 second-year architecture students, solutions produced for ill-defined problems received statistically significantly higher total creativity scores than those for well-defined problems (p = 0.022, r = 0.51), suggesting that the structural openness of ill-defined problems may be associated with enhanced divergent thinking and original idea generation, though causal mechanisms remain to be established through future process-level research. These results support integrating ill-defined problems and uncertainty-based design scenarios into architectural education studios more frequently to develop creative problem-solving skills. Full article

Construction delays remain a persistent challenge in Australian construction projects, contributing to cost escalation, disrupted work sequences, contractual claims, and reduced confidence in project delivery. Although delay causes have been widely investigated, existing studies often provide broad factor lists and prioritise risks using single-dimension or inconsistent scoring approaches. This limits guidance on which delay risks should receive priority attention when project teams face constrained time, cost, and management resources. This study addresses this limitation by quantifying and prioritising 22 validated delay risk factors in Australian construction projects. Probability of occurrence and schedule impact were evaluated as separate judgement dimensions before being integrated into an overall measure of risk criticality. Data were collected from 48 experienced Australian construction professionals. A dual-dimension Fuzzy Best–Worst Method was applied to derive separate ratio-scale weights for probability of occurrence and schedule impact, with dimension-specific consistency screening used to improve judgement reliability. The resulting weights were integrated using a probability–impact formulation and mapped onto a 5 × 5 Probability–Impact Matrix through quantile-based discretisation. A 10,000-iteration Monte Carlo robustness analysis was subsequently conducted to assess the stability of the resulting rankings under alternative expert-selection and weighting scenarios. The results indicate that the delay risks perceived by the participating professionals as having the highest combined probability and schedule impact are predominantly governance-, approval-, and coordination-related, particularly owner late decisions, change-approval delays, owner requirement changes, cost-estimation deficiencies, design-approval delays, and inadequate planning. The Monte Carlo analysis further indicated that the principal risk rankings remained relatively stable under variations in expert aggregation. Overall, the integrated FBWM–PIM framework provides a structured and practically interpretable approach for eliciting and prioritising expert perceptions of construction delay risk and translating them into an actionable classification tool for allocating limited risk management resources. Full article