Search Results (2,062)

Active magnetic levitation bearings incorporate backup bearings that support the rotor during a breakdown, allowing it to maintain its circular movement despite the loss of magnetic force. This safeguards both the stator of the magnetic levitation bearing and the motor stator from harm. Research reveals that ball bearings are susceptible to failure mechanisms, including raceway wear and scoring. The principal cause is the unregulated motion of the rolling parts, which are divided by the cage, once wear manifests, resulting in raceway lag. This leads to significant contact deformation between the rolling elements and the raceway, along with prolonged cumulative impacts between the rolling elements and the cage. Cage-free bearings prevent collisions between the cage and rolling elements; yet, the orbital motion of the rolling elements in these bearings demonstrates a level of independence and randomness relative to traditional caged ball bearings. This presents considerable obstacles to attaining standard orbital motion in cage-free ball bearings. Despite advancements in technology that have largely elucidated the non-linear motion dynamics of ball bearings, several critical hurdles in behavioral characterization persist. This work presents a thorough review of the non-linear motion behavior of ball bearings and the methodologies for their multi-body dynamic characterization. This report proposes future research topics to improve the design of high-performance bearings and augment their reliability. Full article

Background/Objectives: Pediatric malnutrition is associated with loss of muscle mass and impaired physical function. While anthropometric measurements are widely used for diagnosis, functional indicators that reflect early changes in nutritional status are limited in children. Handgrip strength has been proposed as a simple and objective marker of muscle function; however, pediatric data remain scarce. Methods: In this prospective controlled study, 55 children aged 3–17 years diagnosed with malnutrition and 50 age- and sex-matched healthy controls were evaluated. Anthropometric measurements and muscle strength assessments, including handgrip and pinch grip strength, were performed in both groups. Muscle strength values were additionally converted to age- and sex-adjusted standard deviation scores (SDS). In the malnutrition group, measurements were repeated at 2 and 8 weeks following individualized nutritional therapy to assess treatment response. Results: Children with malnutrition had significantly lower body weight, body mass index, mid-upper arm circumference, triceps skinfold thickness, and lean body mass compared with controls (p < 0.05 for all). Both dominant and non-dominant handgrip strength values were also significantly reduced in the malnutrition group. When adjusted for age and sex, handgrip strength SDS values remained significantly lower in children with malnutrition, whereas pinch grip strength SDS values did not differ significantly between groups. During follow-up, nutritional therapy was associated with significant improvements in anthropometric parameters and absolute muscle strength measurements. However, SDS-based analyses demonstrated that these changes were not uniform across all parameters, suggesting that observed improvements may only partly exceed expected physiological growth. Conclusions: Handgrip strength appears to reflect nutritional status in children, and its association with malnutrition persists after adjustment for growth-related factors. These findings support its potential role as a complementary functional marker. However, longitudinal changes in standardized scores indicate that recovery is variable, and interpretation should consider the influence of normal growth and development. Further large-scale, age-standardized studies are needed to better define their role in clinical practice. Full article

Globally, Central Asian wild fruit forests are critical repositories of wild fruit germplasm resources and provide essential ecosystem services. However, their habitats are facing escalating degradation risks driven by climate warming, shifting precipitation regimes, and intensifying anthropogenic disturbances. Accurately quantifying climate-driven spatiotemporal variations in habitat suitability for keystone wild fruit tree species is therefore an essential prerequisite for formulating targeted conservation and management strategies in arid and semi-arid landscapes. In this study, we applied the maximum entropy (MaxEnt) model to simulate the current (2000–2020 baseline) and future (2030s, 2050s, 2070s) potential suitable habitats of two dominant wild fruit tree species, Malus sieversii (Ledeb.) M.Roem. and Prunus cerasifera Ehrh., in the Ili Valley, a core distribution area of Central Asian wild fruit forests in northwestern China. We integrated rigorously screened species occurrence records with key environmental predictors and characterized future climate conditions using three Shared Socioeconomic Pathways (SSPs; SSP126, SSP245, and SSP585) spanning low to high radiative forcing levels. The model exhibited excellent predictive performance (AUC > 0.85), confirming the robustness and reliability of our habitat suitability simulations. Elevation and annual precipitation were identified as the dominant environmental variables governing habitat suitability for both species, highlighting the critical role of terrain–hydroclimate interactions in maintaining viable dryland refugia for wild fruit forests. Under the baseline climate scenario, the total area of suitable habitats reached 24.014 × 10³ km² for Malus sieversii and 18.990 × 10³ km² for Prunus cerasifera. Future climate projections revealed a consistent and significant contraction trend in suitable habitats for both species, with the magnitude of habitat loss escalating with increasing radiative forcing and longer projection time horizons. Specifically, under the high-emission SSP585 scenario by the 2070s, the suitable habitat area is projected to decline by 7.579 × 10³ km² for Malus sieversii and 9.883 × 10³ km² for Prunus cerasifera relative to the baseline. Our findings delineate climate-vulnerable hotspots of wild fruit forests and provide a robust spatial scientific basis for prioritizing in situ conservation, targeted habitat restoration, and anthropogenic disturbance regulation to support the long-term persistence of these irreplaceable wild fruit germplasm resources under accelerating global climate change. Full article

With the explosive growth of the Internet of Things (IoT) and cloud-computing traffic, Intrusion Detection Systems (IDSs) have become a cornerstone of network security. However, modern traffic data often exhibits extreme class imbalance and long-tailed distributions, leading to persistently high miss rates for minority attack categories in Machine Learning (ML)-based IDSs. Conventional oversampling may introduce decision noise, whereas standard Generative Adversarial Networks (GANs) can suffer from training instability and mode collapse when modeling high-dimensional tabular traffic features. To address these challenges, we propose a high-fidelity traffic augmentation framework based on an Adaptive Hybrid-loss Conditional GAN (AH-CGAN). Specifically, AH-CGAN introduces an iteration-dependent adaptive gradient penalty (AGP) schedule to enforce the Lipschitz continuity constraint more effectively during training and incorporates a feature-matching objective to align intermediate critic representations between real and synthetic traffic. Experiments on the CIC-IDS2017 benchmark show that AH-CGAN generates distribution-consistent synthetic samples and that augmentation improves downstream detection across multiple classifiers. In particular, the weighted F1-score of Logistic Regression increases from 0.8237 to 0.8697 (Δ = +0.0460, i.e., +4.6%). Overall, the proposed approach enhances minority coverage in the feature space and can improve class separability, providing a practical solution for long-tailed IDS. Full article

Background/Objectives: Staphylococcus aureus (S. aureus) intramammary infection remains a major global dairy problem due to its contagious nature, its ability to persist and colonize teat/skin and mucosal niches, and the often-limited bacteriological cure achieved with antimicrobial therapy. Beyond udder health, it is relevant to public health because it can enter raw milk chains and serve as a reservoir for antimicrobial resistance determinants that may circulate between dairy animals and humans. Methods: We assessed S. aureus’ ecology in raw ewe milk from 75 sheep farms in Epirus (Greece) by sampling clinically healthy controls (group A) and clinical mastitis cases pre-treatment (group B), followed by resampling at the first post-withdrawal milking after penicillin/streptomycin treatment (group C1—therapeutic protocol 1), oxytetracycline treatment (group C2—therapeutic protocol 2), or enrofloxacin treatment (group C3—therapeutic protocol 3). Results: S. aureus detection was high and comparable across groups (A 23.0%, B 22.0–30.0%, C 20.0–22.0%), and paired analyses showed no significant pre–post shifts in detection/burden within therapeutic protocols (all p > 0.05). Nevertheless, persistence remained evident. The chromosomal gene mecA was detected in S. aureus strains in all groups, ranging from 13.6% in controls to 54.5% post-withdrawal in group C1, and was also present in the pre-treatment group. In paired sampling animals, mecA was mostly stable, with rare emergence or loss. Across antibiotic classes, within-animal resistance transitions were generally uncommon and non-significant (p > 0.05); β-lactam resistance was fully stable (p = 1.00). Descriptively, resistance to protein synthesis inhibitors tended to decline after therapy in protocol 1 and protocol 3, while protocol 3 showed post-treatment gains in fluoroquinolone resistance. By contrast, virulence-associated phenotype traits shifted after therapy: enterotoxigenicity increased post-withdrawal (especially in the C3 group), Staphylococcal Enterotoxin A (SEA) and Staphylococcal Enterotoxin B (SEB) appeared only post-therapy, Staphylococcal Enterotoxin D (SED) increased significantly in paired isolates (p = 0.002), and strong biofilm adherence increased (in C3, p = 1.5 × 10⁻⁵). Conclusions: The detection of S. aureus after therapy suggests that one possibility is that antimicrobial exposure may select for, or otherwise reshape, the residual intramammary population, rather than reliably eliminating it—an outcome that remains clinically relevant for udder health. Moreover, the persistence of mecA/methicillin-resistant Staphylococcus aureus (MRSA)-compatible profiles indicates that milk released to the food chain after withdrawal compliance may still harbor S. aureus with enhanced preservation capacity and significant food safety relevance. Full article

Accurate tail risk forecasting in emerging markets is frequently compromised by the nonlinear dynamics and time-varying long memory of high-frequency volatility. In this study, we employ multifractal detrended fluctuation analysis (MF-DFA) to decode the complex market behavior, revealing pronounced multifractality and strong persistence that defy the static assumptions of classical linear models. The multifractal analysis is only used for research motivation and model design, not as input features for the model. To bridge the gap between fractal diagnostics and predictive modeling, we propose an attention-based dynamically reweighted SA-HAR-J-Net framework. This architecture uniquely integrates HAR-style multi-horizon inputs with a bidirectional LSTM (BiLSTM) encoder and a temporal self-attention mechanism. Crucially, the attention module functions as a dynamic reweighting system, allowing the model to adaptively emphasize historical patterns that receive higher attention weights under changing market conditions, thereby mimicking the time-varying correlations inherent in multifractal processes. Furthermore, we incorporate jump proxies and realized higher moments to enhance the capture of extreme tail dynamics. Utilizing a strict expanding-window out-of-sample protocol, the proposed method achieves significantly lower quantile loss and superior calibration relative to established econometric and machine learning benchmarks for Value-at-Risk (VaR) forecasting. This work provides a robust framework for tail risk monitoring by effectively aligning deep learning architectures with the stylized facts of multifractal markets. Full article

The emergence of classicality through quantum decoherence is commonly described from complementary perspectives emphasizing stability (environment-induced superselection), objectivity (Quantum Darwinism), or physical feasibility (information thermodynamics). In realistic open quantum systems, however, these aspects coexist and compete under finite physical resources. In this work we argue that classical structure selection is most naturally understood as a resource-constrained, multi-objective process. We introduce the Informational Economy Functional (IEF), an effective accounting framework that places loss of distinguishability, energetic dissipation, and the generation of redundantly accessible records on equal footing. The associated Principle of Informational Economy characterizes emergent classical structures as those achieving an optimal compromise among stability, objectivity, and energetic feasibility. Classicality is thus neither maximally stable, nor maximally redundant, nor maximally energy-efficient, but instead reflects a Pareto-optimal balance shaped by environmental constraints. The IEF yields falsifiable predictions concerning pointer-structure variability, redundancy deformation, and resource-sensitive trade-offs, and suggests concrete experimental tests in continuously monitored quantum platforms. Classical reality is thereby reinterpreted as the most economical configuration in which information can stably form, propagate, and persist. Full article

Digital stylization of Dunhuang murals can support cultural heritage revitalization by transferring their distinctive aesthetics to modern images, but existing methods face practical limitations. Transformer-based models can yield high visual quality, but often at a prohibitive computational cost. In contrast, standard state space models (SSMs) are more efficient but tend to incur issues such as semantic loss, inconsistent stylization, and an undesired coupling between color and structure when processing the complex textures of historical murals. To address these issues, we propose Dh-Mamba, a hierarchical visual Mamba framework tailored for high-fidelity Dunhuang mural style transfer. Dh-Mamba introduces a CrossMamba in-context style injection mechanism. This mechanism prefixes the style token sequence to the content sequence, which enables globally consistent style propagation as a persistent memory and retains linear-time efficiency. We also designed two additional components: a Modulated Style Perception Module (Δt) and an Orthogonal Decoupled HSV Modulator. The former adaptively regulates texture injection based on style complexity. The latter models mineral pigment palettes and mitigates oxidation-related artifacts by disentangling hue, saturation, and value. Experiments on a custom Dunhuang dataset show that Dh-Mamba improves content preservation and produces more natural mural textures than recent state-of-the-art methods; multiple quantitative metrics corroborate these gains. With 20.04 million parameters, Dh-Mamba provides a resource-efficient solution suitable for deployment in resource-constrained terminal applications for cultural heritage preservation Full article

Wildfire occurrence in temperate Europe is increasingly shaped by the interaction of human activities and short-term climatic anomalies rather than by natural ignition processes alone. This study analyses national wildfire statistics from Slovakia covering the period 2010–2025 to investigate temporal trends in wildfire occurrence, ignition causes, and fire-related impacts, including economic damages and human casualties. Official fire records provided by the Fire Research Institute of the Ministry of the Interior of the Slovak Republic were analyzed using descriptive and exploratory statistical methods. The dataset includes annual information on wildfire frequency, detailed ignition cause classifications, direct economic losses, fatalities, and injuries. European-scale wildfire patterns were considered for contextual comparison using data from the European Forest Fire Information System (EFFIS). Results show that wildfire occurrence in Slovakia is overwhelmingly dominated by human-caused ignitions, with negligence-related activities forming a persistent baseline of ignition pressure throughout the study period. The extreme wildfire year 2012, during which more than 11,000 wildfire events were recorded, illustrates how routine human behaviors can be strongly amplified under climatically favorable conditions without altering the underlying cause structure. Importantly, wildfire impacts were found to be weakly correlated with fire frequency, as years with moderate numbers of fires occasionally generated disproportionately high economic damages and casualties. These findings demonstrate that wildfire risk in Slovakia is primarily driven by behavioral ignition patterns modulated by short-term climatic variability. The results support a shift towards prevention-oriented and impact-focused wildfire risk management strategies, consistent with current European policies emphasizing integrated risk assessment, early warning, and targeted prevention in temperate regions. Full article

The environmental persistence of β-lactam antibiotics represents a growing ecological concern, requiring materials capable of combined adsorption and catalytic degradation. Herein, pure ZnS and 1% Fe-doped ZnS nanoparticles were synthesized via microwave-assisted treatment and evaluated for the removal of ceftaroline fosamil from aqueous media. Transmission electron microscopy revealed quasi-spherical nanoparticles below 10 nm, while selected area electron diffraction confirmed a face-centered cubic structure retained after Fe incorporation. UV-Vis spectroscopy showed similar absorption edges (~316 nm), indicating negligible band-gap variation, whereas photoluminescence analysis demonstrated strong emission quenching in Fe-ZnS, indicating suppressed electron–hole recombination. Point-of-zero charge measurements (pH_PZC ≈ 4.6 for ZnS; 4.5 for Fe-ZnS) indicated negatively charged surfaces under circumneutral conditions, influencing interfacial interactions with the antibiotic. Adsorption experiments followed the Langmuir isotherm model, with Fe-ZnS exhibiting a higher maximum adsorption capacity (156 mg g⁻¹) compared to ZnS (115 mg g⁻¹). Under UV irradiation (302 nm), Fe-ZnS achieved near-complete degradation at a catalyst loading of 500 ppm. Liquid chromatography–mass spectrometry analysis revealed the transformation of ceftaroline fosamil (m/z 685.01) into ceftaroline (m/z 605.05) via phosphate group loss, followed by the formation of intermediate fragments at m/z 492.08 and 308.03, associated with cleavage of the thiadiazol-amine moiety and subsequent opening of the cephalosporin ring. After extended irradiation, these intermediates diminished, and a fragment at m/z 356.01 was detected, suggesting further breakdown through thioether bond cleavage. These results support a degradation pathway involving sequential dephosphorylation and fragmentation of the cephalosporin core. Overall, the enhanced performance of Fe-ZnS arises from the synergistic interplay between surface charge characteristics and dopant-modulated charge carrier dynamics, highlighting its potential for antibiotic remediation in aquatic environments. Full article

Against the backdrop of accelerating climate change, extreme weather events have increasingly caused yield losses in agricultural crops. Meanwhile, they undermine the stability of production systems, posing an increasingly severe threat to agriculture. This study draws on the “diversity–stability” hypothesis to construct a country-level measure of agricultural production resilience in China (ARES). Using output time series for multiple agricultural products, we capture the co-movements of shocks and system resilience through output stability and volatility. By combining ARES with climate exposure measures, we assemble a panel dataset covering 1343 counties over the period 2000–2023 and employ a dynamic panel threshold model to jointly account for persistence in ARES and state-dependent nonlinearities in climate impacts. The results reveal significant path dependence in ARES and pronounced threshold effects across climate dimensions. In the full sample, extreme high-temperature days become significantly detrimental after crossing the threshold, whereas extreme low-temperature days become significantly beneficial in the high-exposure regime. Extreme rainfall days and extreme drought days generally exhibit positive effects that weaken markedly beyond their respective thresholds, indicating diminishing marginal gains in ARES under severe exposure. The comprehensive climate physical risk index significantly suppresses ARES when it is below the threshold value; however, after surpassing the threshold, its marginal effect becomes significantly weaker. Heterogeneity analyses across hilly, plain, and mountainous areas, as well as nationally designated key counties for poverty alleviation and development, further show that threshold locations and regime-specific effects differ substantially by terrain and development conditions. These findings highlight the need for “threshold-based” climate adaptation governance, emphasizing targeted investments and risk-financing instruments to prevent ARES collapse under tail-risk regimes. Full article

Background: The genus Brucella has expanded considerably in the 21st century. With the advent of advanced phylogenetic analyses, a close genetic relationship between Brucella and Ochrobactrum has been identified, leading to reclassification of Ochrobactrum species within the genus Brucella. Among these, Brucella anthropi (formerly Ochrobactrum anthropi) is increasingly recognized as a rare cause of invasive human infection. We report a clinically significant case of B. anthropi infective endocarditis and review the available literature. Methods: We report a case of B. anthropi infective endocarditis and conducted a narrative review of the English-language medical literature through 2025. Cases were analyzed for demographics, clinical presentation, antimicrobial susceptibility, and outcomes. Results: A 75-year-old man with a prosthetic aortic valve and prior endocarditis presented with fever of unknown origin, weight loss, and prior transient ischemic attacks. Blood cultures grew B. anthropi after prolonged incubation. Transesophageal echocardiography demonstrated vegetations involving both the aortic and tricuspid valves, and the patient required targeted combination antimicrobial therapy due to persistent bacteremia. Seven additional cases of B. anthropi infective endocarditis were identified on review of the literature. Most patients had underlying valvular disease or prosthetic material. Reported lethality approached 25%. Antimicrobial susceptibility patterns were variable, underscoring the importance of targeted individualized therapy. Conclusion: Consistent with other Gram-negative bacilli, B. anthropi is a rare but established cause of acute bacterial endocarditis. Despite its rarity, it may represent an under-recognized cause of invasive disease. This case highlights the importance of prolonged culture incubation, careful microbiologic interpretation, and susceptibility-guided therapy. Full article

Background/Objectives: Wolfram syndrome type 1 (WS1) is a rare, progressive, multisystem neurodegenerative disorder characterized by diabetes mellitus, optic atrophy, diabetes insipidus, and sensorineural hearing loss. As survival has improved, an increasing number of affected women are reaching reproductive age. However, evidence on pregnancy and peripartum management in WS1 remains scarce, and practical guidance is limited. This case report describes the multidisciplinary management of pregnancy and delivery in a woman with genetically confirmed WS1 and highlights key considerations for peripartum care. Case Presentation: A woman with genetically confirmed WS1 and long-standing multisystem involvement, including diabetes mellitus, diabetes insipidus, neurogenic bladder requiring frequent self-catheterization, progressive neurologic manifestations, and severe sensory impairment, achieved pregnancy through assisted reproduction with oocyte donation and was closely monitored by a multidisciplinary team. Due to persistent breech presentation, a planned external cephalic version was performed at 37 + 5 weeks’ gestation with immediate availability for cesarean delivery. After unsuccessful attempts, cesarean delivery was performed under combined spinal–epidural anesthesia. Peripartum management focused on strict glycemic control, careful monitoring of fluid balance and urine output, neuraxial anesthesia with proactive hemodynamic management, precautions related to the cochlear implant, and tailored communication strategies. Postpartum recovery was favorable, although anemia on postoperative day 1 required transfusion of one unit of packed red blood cells and intravenous iron therapy. Discussion and Conclusions: Pregnancy in WS1 represents a high-risk clinical scenario because of the coexistence of endocrine, urologic, and neurologic comorbidities, while published evidence on peripartum management remains limited. This case supports an individualized, multidisciplinary approach to obstetric and anesthetic planning and the use of a practical framework to optimize peripartum management and enhance maternal–fetal safety in this rare condition. Full article

Road traffic accidents at intersections pose a persistent challenge in Riyadh, Saudi Arabia, contributing significantly to public health burdens and economic losses. Traditional statistical approaches often fail to capture the complex, non-linear interactions among geometric design, traffic parameters, and accident severity. This study develops a multi-methodological machine learning framework to predict intersection accident severity using the Equivalent Property Damage Only (EPDO) metric. Historical data (2017–2023) from Riyadh Municipality for 150 high-risk intersections were analyzed, incorporating predictors such as service road distance (SRD), U-turn distance (UTD), median width (MW), peak hour volume (PHV), heavy vehicle percentage (HV%), and injury/frequency counts. Six algorithms, i.e., Decision Tree, Random Forest, Gradient Boosting, Support Vector Machine, Linear Regression, and Artificial Neural Network, were compared using a 70/30 train–test split and k-fold cross-validation in this study. The Gradient Boosting model achieved superior performance (R² = 0.89 with MSE = 63.43 and RMSE = 7.96) and was selected for final deployment. SHAP feature importance analysis revealed minor injuries (MIs), serious injuries (SRIs), and fatalities (FAs) as the most important dominant predictors, with geometric factors (UTD, MW) and traffic composition (HV%) providing actionable infrastructure insights. The model ranked intersections and identified the “Jeddah Road with Taif Road” (predicted EPDO = 137.22) as the highest-risk location. Evidence-based recommendations include enforcing the minimum 300 m U-turn buffers with staggering service road exits ≥150 m and restricting heavy vehicles during peak hours. The scalable framework developed in this study supports the data-driven prioritization of safety interventions and aligns with sustainable urban mobility goals and offers transferability to other metropolitan contexts worldwide. Full article

Background and Clinical Significance: Neurosarcoidosis (NS) is a rare manifestation of systemic sarcoidosis involving the central nervous system, with highly variable neurological and endocrine presentations. Among these, anterior pituitary dysfunction is particularly uncommon and diagnostically challenging. Case Presentation: We report the case of a 37-year-old woman with a 4-year history of secondary amenorrhoea and an initially suspected pituitary microadenoma, who was ultimately diagnosed with probable NS presenting with multiaxial anterior pituitary insufficiency. Early magnetic resonance imaging (MRI) revealed a small pituitary lesion and isolated pituitary stalk thickening, without other central nervous system abnormalities. Subsequent imaging demonstrated contrast-enhancing lesions involving the meninges and cranial nerves, along with progression of pituitary stalk involvement and loss of the posterior pituitary bright spot. Further evaluation confirmed systemic sarcoidosis. High-dose corticosteroid therapy led to partial clinical and radiological improvement; however, relapse necessitated methotrexate, and persistent pituitary hormone deficiencies required long-term hormonal replacement. Conclusions: This case highlights the diagnostic complexity of NS presenting with isolated endocrine dysfunction and subtle imaging findings. It underscores the need to consider systemic sarcoidosis in patients with unexplained hypopituitarism. Full article