Search Results (42,076)

The Apple TV+ series Severance (2022–present) offers a dystopian portrayal of workplace life that intensifies real-world dynamics of control, boundary management, and identity regulation. This paper analyzes Severance as a speculative case study in organizational theory, treating the show’s fictional world as a site for conceptual reflection. Drawing on critical management studies and labor process theory, we examine how mechanisms of control, the regulation of work–life boundaries, and the fragmentation of autonomy and subjectivity are depicted in extreme form. We argue that fiction—particularly speculative satire—can serve as a tool of theoretical production, not merely illustration. Rather than restating familiar critiques, Severance allows us to see workplace norms with renewed clarity, surfacing the moral and psychological consequences of surveillance, coercion, and instrumentalized consent. A methodological note outlines our interpretive approach to narrative fiction, and a discussion of implications situates the analysis within broader debates about organizational ethics, resilience, and critique. Full article

Resolved spectroscopic binaries (RSBs) are an extremely valuable class of objects, being the only (apart from trigonometric) supplier of dynamical stellar parallaxes. This circumstance, as well as the comparative paucity of studied RSBs, makes the problem of identifying binary systems potentially capable of being added to the list of known RSBs extremely urgent. In this paper, we propose a methodology for estimating the probability of a spectroscopic binary system to be resolved into components, perform the first step of its application to the SB9 catalogue, and present preliminary results, in particular, a list of the most promising RSB candidates. Full article

Automated surface defect detection in steel manufacturing is pivotal for ensuring product quality, yet it remains an open challenge owing to the extreme heterogeneity of defect morphologies—ranging from hairline cracks and microscopic pores to elongated scratches and shallow dents. Existing approaches, whether classical vision pipelines or recent deep-learning paradigms, struggle to simultaneously satisfy the stringent demands of industrial scenarios: high accuracy on sub-millimeter flaws, insensitivity to texture-rich backgrounds, and real-time throughput on resource-constrained hardware. Although contemporary detectors have narrowed the gap, they still exhibit pronounced sensitivity–robustness trade-offs, particularly in the presence of scale-varying defects and cluttered surfaces. To address these limitations, we introduce MBY (MBDNet-Attention-YOLO), a lightweight yet powerful framework that synergistically couples the MBDNet backbone with the YOLO detection head. Specifically, the backbone embeds three novel components: (1) HGStem, a hierarchical stem block that enriches low-level representations while suppressing redundant activations; (2) Dynamic Align Fusion (DAF), an adaptive cross-scale fusion mechanism that dynamically re-weights feature contributions according to defect saliency; and (3) C2f-DWR, a depth-wise residual variant that progressively expands receptive fields without incurring prohibitive computational costs. Building upon this enriched feature hierarchy, the neck employs our proposed MultiSEAM module—a cascaded squeeze-and-excitation attention mechanism operating at multiple granularities—to harmonize fine-grained and semantic cues, thereby amplifying weak defect signals against complex textures. Finally, we integrate the Inner-SIoU loss, which refines the geometric alignment between predicted and ground-truth boxes by jointly optimizing center distance, aspect ratio consistency, and IoU overlap, leading to faster convergence and tighter localization. Extensive experiments on two publicly available steel-defect benchmarks—NEU-DET and PVEL-AD—demonstrate the superiority of MBY. Without bells and whistles, our model achieves 85.8% mAP@0.5 on NEU-DET and 75.9% mAP@0.5 on PVEL-AD, surpassing the best-reported results by significant margins while maintaining real-time inference on an NVIDIA Jetson Xavier. Ablation studies corroborate the complementary roles of each component, underscoring MBY’s robustness across defect scales and surface conditions. These results suggest that MBY strikes an appealing balance between accuracy, efficiency, and deployability, offering a pragmatic solution for next-generation industrial quality-control systems. Full article

Degradable fluorescent sensors present a promising portable approach for heavy metal ion detection, aiming to prevent secondary environmental pollution. Additionally, the excessive intake of ferric ions (Fe³⁺), an essential trace element for human health, poses critical health risks that urgently require effective monitoring. In this study, we developed a thermally degradable fluorescent hydrogel sensor (Eu-CDs@DPPG) based on europium-doped carbon dots (Eu-CDs). The Eu-CDs, synthesized via a hydrothermal method, exhibited selective fluorescence quenching by Fe³⁺ through the inner filter effect (IFE). Embedding Eu-CDs into the hydrogel significantly enhanced their stability and dispersibility in aqueous environments, effectively resolving issues related to aggregation and matrix interference in traditional sensing methods. The developed sensor demonstrated a broad linear detection range (0–2.5 µM), an extremely low detection limit (1.25 nM), and rapid response (<40 s). Furthermore, a smartphone-assisted LAB color analysis allowed portable, visual quantification of Fe³⁺ with a practical LOD of 6.588 nM. Importantly, the hydrogel was thermally degradable at 80 °C, thus minimizing environmental impact. The sensor’s practical applicability was validated by accurately detecting Fe³⁺ in spinach and human urine samples, achieving recoveries of 98.7–108.0% with low relative standard deviations. This work provides an efficient, portable, and sustainable sensing platform that overcomes the limitations inherent in conventional analytical methods. Full article

The recent surge in the popularity of brachycephalic dog breeds has raised concerns about their predisposition to serious health issues linked to breed-specific morphological traits. This study examined the demographic characteristics, motivations, and awareness of owners regarding welfare issues in four brachycephalic breeds (French Bulldogs, Bulldogs, Pugs, Boston Terriers). Methods: A total of 497 owners of brachycephalic dogs examined over six years at an Italian university veterinary hospital were considered; a subset of 75 owners completed a structured questionnaire. Based on responses to a key multiple-choice question about the main reason for breed choice, owners were classified into three groups: trend-driven (aesthetics/fashion), value-oriented (intelligence/behavior), and indeterminate. Results: Gender distribution did not differ significantly compared to the overall population, but brachycephalic owners were significantly younger (p < 0.001). Value-oriented owners were significantly more likely (p < 0.01) to consult a veterinarian before acquisition and showed better understanding of typical respiratory issues, which did not affect their purchasing decision. Trend-driven owners were more influenced by public figures (p < 0.05) and less engaged in preventive care. Conclusion: Our findings highlight the need for pre-acquisition veterinary counseling. Veterinarians can also assist breeders by promoting awareness of the ethical risks of selecting extreme traits in dogs. Full article

Machine learning and artificial intelligence have transformed fault detection and maintenance strategies for industrial machinery. This study applies well-established data-driven techniques to a rarely explored industrial application—the condition monitoring of high-precision paper cutting machines—enhancing condition-based maintenance to improve operational efficiency, safety, and cost-effectiveness. A key element of the proposed approach is the integration of an infrared pyrometer into vibration monitoring, utilizing accelerometer data to evaluate the state of health of machinery. Unlike traditional fault detection studies that focus on extreme degradation states, this work successfully identifies subtle deviations from optimal, which even expert technicians struggle to detect. Building on a feasibility study conducted with Tecnau SRL, a comprehensive diagnostic system suitable for industrial deployment is developed. Endurance tests pave the way for continuous monitoring under various operating conditions, enabling real-time industrial diagnostic applications. Multi-scale signal analysis highlights the significance of transient and steady-state phase detection, improving the effectiveness of real-time monitoring strategies. Despite the physical similarity of the classified states, simple time-series statistics combined with machine learning algorithms demonstrate high sensitivity to early-stage deviations, confirming the reliability of the approach. Additionally, a systematic analysis to downgrade acquisition system specifications identifies cost-effective sensor configurations, ensuring the feasibility of industrial implementation. Full article

The Mapleton Falls National Park transmission line corridor in Queensland, Australia, has received a number of vegetation management treatments over the last decade to maintain and protect the infrastructure and to ensure continuous electricity supply. Recent treatments have included ‘mega-mulching’ (mechanical mastication of vegetation to a mulch layer) in 2020 and targeted herbicide treatment of woody vegetation, with the aim of reducing vegetation height by encouraging a native herbaceous groundcover beneath the transmission lines. We measured vegetation structure (cover and height) and composition (species presence in 15 × 2 m plots), at 12 transects, 90 m in length on the transmission line corridor, to determine if management goals were being achieved and to determine how the vegetation and fire hazard (based on the overall fuel hazard assessment method) varied among the treated corridor, the forest edge environment, and the natural forest. The results showed that vegetation structure and composition in the treated zones had been modified to a state where herbaceous plant species were dominant; there was a significantly (p < 0.05) higher native grass cover and cover of herbs, sedges, and ferns in the treated zones, and a lower cover of trees and tall woody plants (>1 m in height) in these areas. For example, mean native grass cover and the cover of herbs and sedges in the treated areas was 10.2 and 2.8 times higher, respectively, than in the natural forest. The changes in the vegetation structure (particularly removal of tall woody vegetation) resulted in a lower overall fuel hazard in the treated zones, relative to the edge zones and natural forest. The overall fuel hazard was classified as ‘high’ in 83% of the transects in the treated areas, but it was classified as ‘extreme’ in 75% of the transects in the adjacent forest zone. Importantly, there were few introduced species recorded. The results suggest that fuel management has been successful in reducing wildfire risk in the transmission corridor. Temporal monitoring is recommended to determine the frequency of ongoing fuel management. Full article

Earthquakes, as one of the most destructive natural disasters, often cause significant casualties and severe economic losses. Accurate prediction of earthquake fatalities is of great importance for pre-disaster prevention and mitigation planning, as well as post-disaster emergency response deployment. To address the challenges of small sample sizes, high dimensionality, and strong nonlinearity in earthquake fatality prediction, this paper proposes an integrated modeling approach (PCA-IWOA-XGBoost) combining Principal Component Analysis (PCA), the Improved Whale Optimization Algorithm (IWOA), and Extreme Gradient Boosting (XGBoost). The method first employs PCA to reduce the dimensionality of the influencing factor data, eliminating redundant information and improving modeling efficiency. Subsequently, the IWOA is used to intelligently optimize key hyperparameters of the XGBoost model, enhancing the prediction accuracy and stability. Using 42 major earthquake events in China from 1970 to 2025 as a case study, covering regions including the west (e.g., Tonghai in Yunnan, Wenchuan, Jiuzhaigou), central (e.g., Lushan in Sichuan, Ya’an), east (e.g., Tangshan, Yingkou), north (e.g., Baotou in Inner Mongolia, Helinger), northwest (e.g., Jiashi in Xinjiang, Wushi, Yongdeng in Gansu), and southwest (e.g., Lancang in Yunnan, Lijiang, Ludian), the empirical results showed that the PCA-IWOA-XGBoost model achieved an average test set accuracy of 97.0%, a coefficient of determination (R²) of 0.996, a root mean square error (RMSE) and mean absolute error (MAE) reduced to 4.410 and 3.430, respectively, and a residual prediction deviation (RPD) of 21.090. These results significantly outperformed the baseline XGBoost, PCA-XGBoost, and IWOA-XGBoost models, providing improved technical support for earthquake disaster risk assessment and emergency response. Full article

This study analyzes spatiotemporal aridity dynamics in Central Kazakhstan (1960–2022) using a monthly Aridity Index (AI = P/PET), where P is precipitation and PET is potential evapotranspiration, Mann–Kendall trend analysis, and climate zone classification. Results reveal a northeast–southwest aridity gradient, with Aridity Index ranging from 0.11 to 0.14 in southern deserts to 0.43 in the Kazakh Uplands. Between 1960–1990 and 1991–2022, southern regions experienced intensified aridity, with Aridity Index declining from 0.12–0.15 to 0.10–0.14, while northern mountainous areas became more humid, where Aridity Index increased from 0.40–0.44 to 0.41–0.46. Seasonal analysis reveals divergent patterns, with winter showing improved moisture conditions (52.4% reduction in arid lands), contrasting sharply with aridification in spring and summer. Summer emerges as the most extreme season, with hyper-arid zones (8%) along with expanding arid territories (69%), while autumn shows intermediate conditions with notable dry sub-humid areas (5%) in northwestern regions. Statistical analysis confirms these observations, with northern areas showing positive Aridity Index trends (+0.007/10 years) against southwestern declines (−0.003/10 years). Key drivers include rising temperatures (with recent degradation) and variable precipitation (long-term drying followed by winter and spring), and PET fluctuations linked to temperature. Since 1991, arid zones have expanded from 40% to 47% of the region, with semi-arid lands transitioning to arid, with a northward shift of the boundary. These changes are strongly seasonal, highlighting the vulnerability of Central Kazakhstan to climate-driven aridification. Full article

Terahertz (THz) has attracted substantial attention owing to its unique advantages in high-speed communications. However, conventional THz waveguide systems are inherently constrained by high transmission losses, stringent fabrication precision requirements, and extreme sensitivity to structural defects. Topological edge states with topological protection have driven significant advancements in THz wave manipulation. Nevertheless, the width of the topological waveguide based on edge states remains restricted. In this work, we put forward a type of spin photonic crystal with three-layer heterostructures, where large-area topological waveguide states are demonstrated. The results show that these topological waveguide states are localized within the region of Dirac photonic crystals. They also display spin-momentum-locking characteristics and maintain strong robustness against defects and sharp bends. Furthermore, a THz beam splitter and a topological beam modulator are implemented. The designed heterostructures expand the applications of multi-functional topological devices and provide a prospective pathway for overcoming the waveguide bottleneck in THz applications. Full article

This study investigates the production and characterization of basalt continuous fibers (BCFs) with varying oxide contents (including Na₂O, SiO₂, CaO, TiO₂, and Al₂O₃), derived from modified basalt bulk glasses. The fibers were created through a two-stage process that included the preparation of basalt glasses followed by fiber drawing. A key focus of the research was on evaluating the mechanical properties of BCF after low-temperature treatments. Tensile testing revealed that the maximum tensile strength of the fibers was 1915 MPa at room temperature, which decreased to 1714 MPa at −196 °C, representing a shift of −10.5%. The addition of sodium oxide not only broadened the fiber-forming temperature range but also increased the strength to 2351 MPa. However, significant reductions in strength were observed at cryogenic temperatures, particularly for the Na-rich sample, which experienced a decrease of 32.8%. These findings highlight the importance of optimizing oxide content and minimizing hydroxyl (OH) groups to enhance the performance of basalt fibers in low-temperature applications, positioning them as viable materials for use in extreme environments. Full article

In this study, a combined approach joining the machine learning model Extreme Gradient Boosting (XGBoost) with Shapley Additive Explanation (SHAP) is adopted to simulate the temporal pattern of the air quality index (AQI) and subsequently explore the key factors affecting AQI variability. Based on the analysis of air pollutants and meteorological data acquired from two air quality monitoring stations in Rome (Italy), over the 2018–2022 period, the results demonstrate the effectiveness of the proposed methodological approach in elucidating the role of the main factors driving AQI evolution, and their interaction effects. Full article

Due to increased precipitation intensity and sea-level rise, low-lying coastal roads are increasingly vulnerable to subbase saturation. Widely applied lumped hydrological approaches cannot accurately represent time and space-varying groundwater levels in some highly conductive coastal soils, calling for more sophisticated tools. This study assesses the suitability of the Gridded Surface Subsurface Hydrologic Analysis model (GSSHA) for representing hydrological processes and groundwater dynamics in a unique coastal roadway setting in Alabama. A high-resolution model was developed to assess a 2 km road segment and was calibrated for hydraulic conductivity and aquifer bottom levels using observed groundwater level (GWL) data. The model configuration included a fixed groundwater tidal boundary representing Mobile Bay, a refined land cover classification, and an extreme precipitation event simulation representing Hurricane Sally. Results indicated good agreement between modeled and observed groundwater levels, particularly during short-duration high-intensity events, with NSE values reaching up to 0.83. However, the absence of dynamic tidal forcing limited its ability to replicate certain fine-scale groundwater fluctuations. During the Hurricane Sally simulation, over two-thirds of the segment remained saturated for over 6 h, and some locations exceeded 48 h of pavement saturation. The findings underscore the importance of incorporating shallow groundwater processes in hydrologic modeling for coastal roads. This replicable modeling framework may assist DOTs in identifying critical roadway segments to improve drainage infrastructure in order to increase resiliency. Full article

Purpose: This study investigates the test–retest reliability of maximal voluntary contraction (MVC) and integrated object positioning during bimanual box lifting tasks in children with unilateral spastic cerebral palsy (USCP), using the Activities of Daily Living Test and Training Device (ADL-TTD). Materials and Methods: Utilizing an explorative cross-sectional design, the study recruited 47 children with USCP. The ADL-TTD, equipped with an Inertial Measurement Unit (IMU) for precise object positioning, measured MVC, and object position in 3D space in a cross-sectional measurement containing two measurements in a fixed time period. Results: The findings demonstrated good test–retest reliability for MVC, with an ICC_agreement of 0.95 for the mean MVC value. Additionally, good reliability was observed for object positioning in different directions measured with an IMU, with ICC_agreement ranging from 0.82 to 0.86 degrees. Regarding the standard error of measurement (SEM), the SEM_agreement for the mean MVC value was 5.94 kg, while the SEM_agreement for object positioning was 1.48, 5.39, and 3.43 degrees, respectively. Conclusions: These results indicate that the ADL-TTD demonstrates good test–retest reliability for both MVC and object positioning, making it a valuable tool for analyzing this population in cross-sectional research by providing reliable measures of task-oriented strength and object manipulation. However, the relatively high SEM_agreement, particularly in MVC, suggests that caution is needed when using this tool for repeated testing over time. This pioneering approach could significantly contribute to tailored assessment and training for children with USCP, highlighting the importance of integrating task-specific strength and positional accuracy into therapeutic interventions. Full article

Vortex-induced vibrations (VIVs) pose significant risks to the structural integrity of subsea cables and pipelines under free-span conditions. It is extremely helpful to be able to screen for VIV and understand for a particular cable or pipeline what the minimum free-span threshold lengths are beyond which in-line and/or cross-flow VIV can be excited, causing fatigue problems. To date screening is a more complex and detailed task. This paper introduces a universal dimensionless velocity, V*, and one graph that can be used across all types of VIV free spans to quickly assess minimum free-span threshold lengths. Natural frequencies are not required to be calculated for screening each time, as they are implicit in the curve. The universal criteria are developed via non-dimensional analysis to establish the significant physical mechanisms, after which the relationships are populated, forming a single curve for in-line and for cross-flow VIV with a typical mass ratio and a conservative zero as-laid tension case. Full article