Search Results (12,759)

6082 aluminum alloy is widely applied in marine engineering, rail transportation and other industries owing to its excellent comprehensive performance. Welding heat source characteristics exert a decisive influence on the microstructure and mechanical properties of welded joints and become a major constraint for the application of medium-thick aluminum alloy welded structures. In this work, comparative tests of TIG and MIG welding were carried out on 16 mm thick 6082 aluminum alloy plates. Combining thermal simulation, metallographic observation and mechanical property tests, the temperature field distribution, microstructure, microhardness, tensile properties and bending properties of the two kinds of joints were systematically studied. The results show that TIG welding possesses high heat input, forming a broad temperature field with steep thermal gradients. Its weld microstructure is coarse and accompanied by severe coarsening of Mg₂Si precipitates, and the joint presents a highly fluctuating M-shaped microhardness distribution. The average tensile strength of TIG welded joints is 194 MPa, and all specimens fracture in the heat-affected zone. By contrast, MIG welding with low heat input produces a uniform temperature field, as well as a fine and homogeneous weld microstructure with dispersed precipitates. Its microhardness distribution is stable, and the average tensile strength reaches 256 MPa, 32% higher than that of TIG joints. Both welding methods deliver favorable bending performance. The difference in heat input and cooling behavior changes the grain evolution and precipitate characteristics and further dominates the final mechanical performance of joints. MIG welding is more suitable for multi-layer, multi-pass welding of 16 mm thick 6082 aluminum alloy. This work clarifies the correlation between heat input, microstructure and mechanical properties, and the optimized process can effectively improve the microstructural uniformity of the weld joint and enhance its mechanical properties. Full article

Transposable elements (TEs) are inserted into the genome and may change its properties; those occurring in or near regulatory regions may also alter gene expression. Given the challenges of detecting insertions in short-read sequencing, we analyzed structural variants in polar and brown bear genomes by a reciprocal alignment of one species’ sample genomes to a reference sequence of the other species, thus inferring TE insertion as the other genome’s “deletions”. With this approach, we detected short interspersed elements (SINEs) belonging to the CAN SINE family as dominant fixed TEs. We observed a non-random distribution of CAN SINE insertion positions near both protein- and RNA-coding genes, where TEs often overlap UTRs or occur in their vicinity. In contrast, SINEs avoid coding sequences, suggesting TE insertions that would disrupt such sequences are under purifying selection. We used black bear as an outgroup and determined that most of the CAN SINE insertions in the polar bear genome were derived, since they are not present in black or brown bear, while there is no dominant trend for CAN SINE insertions in brown bear relative to the outgroup. Many of the genes with UTRs affected by CAN SINEs are potentially relevant to the differences between the species (body shape, size, etc.) or to Arctic-adaptation phenotypes such as fur color, metabolism, and the immune system. This supports a model that CAN SINEs have contributed to regulatory evolution in bears and provides further evidence of such events across carnivore genomes in the animal kingdom. Full article

Background/Objectives: Weight loss achieved through lifestyle interventions has been demonstrated to improve the clinical prognosis of female hyperandrogenism. However, the interplay between such interventions, androgens, and glucose–lipid metabolism remains heterogeneous. This study evaluated the effects of lifestyle-induced weight loss on glucose and lipid metabolism and androgen levels in Chinese women of reproductive age with hyperandrogenism and examined the association between the degree of weight loss and changes in androgen levels, glucose and lipid metabolism, exercise capacity, and dietary patterns. Methods: This observational study, based on real-world clinical settings, collected medical records of women of reproductive age with hyperandrogenism who underwent weight-loss interventions between July 2023 and September 2025. Correlation analysis employed Spearman’s rank correlation coefficient, whilst pre- and post-weight-loss comparisons utilised paired t-tests or Wilcoxon signed-rank tests. Results: After a follow-up of 6 to 7 months, a total of 66 participants achieved a mean weight loss of 5.67 ± 4.27 kg. Statistically significant reductions were observed in testosterone (0.40 ± 0.10 vs. 0.30 ± 0.10 ng/mL, p < 0.001), androstenedione (p < 0.001), and the free androgen index (p < 0.001). Glucose metabolism showed statistically significant improvement, with decreases in HOMA-IR (p = 0.040), fasting glucose (p = 0.001), and fasting/2 h postprandial insulin (p < 0.001). However, lipid profiles showed no statistically significant changes. Multiple linear regression revealed that change in testosterone was independently and inversely associated with change in apolipoprotein A1 (β = −0.496, p = 0.008), while change in dehydroepiandrosterone sulfate was inversely associated with change in fasting insulin (β = −0.357, p = 0.032). A non-linear, inverted U-shaped relationship was found between weight loss magnitude and change in sex hormone-binding globulin, with moderate weight loss (5–10%) yielding the greatest increase (p = 0.044). Marked weight loss (≥10%) was associated with the lowest follow-up fasting insulin levels (p = 0.039). Conclusions: Weight loss achieved through lifestyle interventions is associated with improvements in androgen levels and glucose metabolism, though its impact on lipid metabolism remains limited. The degree of improvement in insulin sensitivity correlates more strongly with the magnitude of weight reduction. Full article

IoT devices operate as integrated systems spanning hardware, firmware/software layers, and communication layers. In operational settings, many faults and performance degradations are emergent: they arise from cross-layer interactions, workload changes, and telemetry artifacts, rather than a single physics-of-failure mechanism. These realities make traditional supervised fault classification difficult because labeled fault data are rarely available during deployment, and the fault surface is unknown and a priori. This paper presents a practitioner-oriented, label-free fault detection and diagnosis (FDD) pattern based on Dynamic Time Warping (DTW) for rapid implementation in production IoT telemetry. The method represents a device as a sequence of overlapping episodes and organizes telemetry into interpretable layers (hardware sensors, communication health proxies, and software/firmware-derived KPIs). A reference library of regular episodes is built from an assumed-healthy training window; new episodes are scored using constrained DTW distances against this library, while retaining per-layer and per-channel contributions for attribution. We show that production performance depends strongly on operational parameterization, including episode length, DTW constraints, robust threshold learning, and temporal validation. Within a verified-healthy evaluation window, the tuned configuration achieves an AUROC of 0.97 for the temporally structured faults DTW is suited to (bias, drift, and interaction faults, with spikes detected at an AUROC of 0.93), detecting 100% of injected faults, with a mean delay under 25 min. We further show that constant-value (stuck-at) and missing-data (dropout) faults fall outside DTW’s shape-matching scope (AUROC about 0.66) and are better served by complementary variance- and missingness-based detectors, a consequence of DTW’s shape-matching scope rather than a parameter choice. This work contributes a system-level methodological framework for deploying DTW as an IoT fault-detection-and-diagnosis capability: an episode-and-layer architecture aligned with hardware, communication, and software/firmware ownership; a label-free reference library requiring only assumed-healthy data; per-layer and per-channel attribution for cross-domain triage; and a reproducible operational tuning procedure. Together, these deliver a fast-to-deploy, scalable, and accurate first-line detector for label-scarce IoT systems. Full article

Urban flood vulnerability is increasingly shaped by the interaction between climate change, urbanization, and spatial planning practices, particularly in Mediterranean metropolitan areas. This study develops an integrated GIS–AHP framework to assess the susceptibility component of flood vulnerability in the urban area of Thessaloniki, Greece. Using open-access geospatial data, ten indicators representing soil, hydrological, and environmental conditions are derived and spatially analyzed. The Analytic Hierarchy Process (AHP), based on expert judgment, is applied to estimate the relative importance of these indicators and to support their integration into a composite flood susceptibility index. The results reveal strong spatial heterogeneity, with high susceptibility concentrated in low-lying, densely urbanized areas and zones near drainage pathways. Among the examined factors, the Topographic Wetness Index emerges as the most influential, highlighting the persistent role of terrain-driven hydrological processes even in highly built environments. The proposed framework provides a transparent and transferable methodology for identifying flood-prone areas and supports evidence-based urban planning and climate resilience strategies. The findings contribute to the broader discussion on vulnerability and resilience in urban systems by linking spatial analysis with decision-support tools in a policy-relevant context. Full article

Emotional well-being has become a central concern in contemporary educational research, particularly in contexts shaped by social and cultural diversity. However, dominant approaches to educational assessment continue to prioritize cognitive outcomes, often overlooking the affective dimensions of children’s everyday experiences. In this context, play emerges as a key yet underexplored process through which emotional well-being is constructed in childhood. This study aimed to analyze the role of play in the configuration of emotional well-being in sociocultural educational contexts from a sociocultural and relational perspective. A qualitative multiple-case study was conducted in two rural schools located in Mapuche territories in southern Chile, involving students, teachers, caregivers, and Mapuche knowledge holders (kimches). Data were generated through semi-structured interviews and focus groups and analyzed using inductive coding procedures supported by qualitative data analysis software. The findings indicate that play operates as a socioemotional ecology through which children participate in collective forms of life, construct relationships, and experience emotional well-being in interaction with others, territory, and culturally meaningful practices. Three interconnected dimensions emerged. First, play was experienced as a relational, territorialized, and culturally situated practice sustained through participation, collective interaction, and intergenerational transmission. Second, emotional well-being emerged through enjoyment, companionship, belonging, and opportunities for social participation. Third, well-being appeared as a situated experience dependent on access to meaningful spaces, material conditions, cultural repertoires, and opportunities for play. Participants also identified tensions associated with technological change, the reduction in free play opportunities, and transformations in community life, while highlighting the potential role of schools in revitalizing culturally significant play practices such as palín and linao. These findings suggest that emotional well-being is not simply an individual psychological state but a relational and sociocultural accomplishment emerging through participation in meaningful play practices. The study contributes to interdisciplinary debates on childhood, emotional well-being, intercultural education, and sociocultural approaches to development by proposing the concept of play as a socioemotional ecology. Full article

Snake-like robots require body adaptation during locomotion when creeping through environments with obstacles. Central Pattern Generator (CPG) provides an effective way to generate rhythmic signals through parameter modulation. During body-shape adaptation, the body wave generated by the CPG can be modified by adjusting its parameters. In this paper, a CPG network based on Hopf oscillators is adopted, and the amplitude parameter is used for body-shape adaptation. However, the influence of amplitude variation during the transition process has not been fully understood. More specifically, when the amplitude parameter changes abruptly, the attractor shifts immediately, while the oscillator state cannot follow the new attractor instantaneously. This mismatch produces transient responses and waveform distortion during the transition process. To address this issue, a linear parameter transition method is introduced. The proposed method is subsequently extended to a coupled CPG network for controlling the multi-joint snake-like robots. Simulations are conducted under different parameter transition conditions. The results demonstrate that the parameter transition method strongly affects the transient torque response. Compared with abrupt parameter variation, the proposed linear transition method significantly reduces transient torque peaks. Additionally, the results further show that even a short transition interval is sufficient to achieve most of the torque reduction. Experiment results show that the proposed method can be applied to body-shape modulation and obstacle avoidance during snake-like robot locomotion. Full article

Background/Objectives: Emotion processing has increasingly been conceptualized as a transdiagnostic mechanism underlying psychological adaptation and psychopathology. From an attachment perspective, individual differences in emotion perception may be rooted in internal working models shaped by early relationships. This systematic review synthesized the literature on the relationship between adult attachment representations and intrapersonal emotion perception (Impathy) and interpersonal emotion perception (Empathy). Methods: The review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A systematic search was conducted on 9 February 2026, in PsycINFO, PsycArticles, and PubMed. Studies were included if they investigated adolescents or adults, assessed attachment representations using narrative-based measures (Adult Attachment Interview (AAI) or Adult Attachment Projective Picture System (AAP)), and examined intrapersonal and/or interpersonal emotion perception. Findings were synthesized narratively, and a random-effects meta-analysis examined the association between attachment security and reflective functioning. Results: Thirty-eight studies, including 2736 participants, met the inclusion criteria. Across studies, attachment representations were systematically associated with intrapersonal and interpersonal emotion perception. The strongest evidence emerged for reflective functioning, the Impathy dimensions Perceiving and Understanding, and cognitive-empathic processes. Secure attachment representations were consistently associated with higher reflective functioning and more adaptive emotion perception, whereas insecure and especially unresolved attachment representations were linked to impairments in emotional self-awareness, alexithymia-related processes, differentiated emotional understanding, and cognitive-empathic processing. The meta-analysis showed a large positive association between secure attachment representations and reflective functioning (k = 8; r = 0.64, 95% CI [0.50, 0.74]). Conclusions: Attachment representations appear systematically associated with the perceptual foundations of emotion processing. Intrapersonal and interpersonal emotion perception may therefore represent attachment-sensitive processes relevant to psychological adaptation, psychopathology, caregiving, and therapeutic change. Full article

Anomaly detection models trained exclusively on healthy data are widely used in wind turbine condition monitoring because failure data are scarce, heterogeneous, and often unavailable. However, these models produce anomaly indicators that are sensitive not only to fault-related degradation but also to normal operational variability, transient disturbances, and changes in loading conditions. As a result, the practical behavior of an alarm system depends not only on the anomaly detection model but also on the decision rule used to activate and maintain alarm states. This study presents a decision-oriented evaluation of persistence-based alarm confirmation in wind turbine anomaly detection. Four representative techniques are analyzed within a unified framework: Isolation Forest, One-Class Support Vector Machine, Referenced Moving Window Principal Component Analysis using Q-statistic and percentage component weight indicators, and Autoencoder-based reconstruction error. The evaluation combines controlled OpenFAST simulations of rotor unbalance under different severity and noise conditions with an industrial SCADA case study involving a documented main bearing fault. Results show that temporal persistence strongly shapes alarm outcomes across methods and datasets. Low persistence values favor early detection but promote alarms from isolated threshold exceedances, whereas moderate persistence substantially reduces false positives while preserving detection capability in severe and well-observable faults. Excessive persistence increases detection latency and missed detections, particularly for weak, intermittent, or slowly evolving fault signatures. These findings indicate that persistence-based alarm confirmation should be treated as an explicit decision-level configuration variable, rather than as a fixed post-processing or alarm-state heuristic, when designing anomaly detection systems for wind turbine condition monitoring. Full article

Modern power grids with high renewable energy penetration are vulnerable to fast voltage disturbances caused by grid faults. Among these, voltage sags are critical because they develop within milliseconds and require rapid reactive current support to maintain grid stability and power reliability. Reinforcement learning has previously shown potential for reactive current injection control during voltage sag events due to its fast response and adaptability to changing system conditions. However, existing approaches rely on separate policies for specific subsets of the operating space, which limits their ability to provide optimal actions when the system operates across broader or combined state regions. To address this limitation, this paper proposes a unified Soft Actor–Critic (SAC) target policy trained over the full state and action space by integrating multi-source transfer learning with potential-based reward shaping approach. Results show that the proposed multi-source transfer approach enables the target agent to converge faster and reach a higher reward solution than the baseline SAC and single-source transfer approach. The trained policy also improved prediction accuracy, achieving reactive-current errors below 0.2 A with respect to the ground-truth reference generated through extensive simulations over the full observation and action space. The reference follows the grid-code requirement for minimum reactive current injection during faults and provides a benchmark for evaluating prediction accuracy. This can help distributed generation sources respond more effectively during severe perturbations such as voltage sags, support voltage recovery, and reduce the risk of cascaded disconnections that could lead to unwanted blackouts. Additionally, the inference execution time is also sufficiently fast to satisfy the response-time requirement of voltage sag events, confirming the real-time feasibility of the proposed controller. Full article

Rising demand for high-performance battery thermal management systems (BTMSs) has rendered single-mode cooling insufficient for advanced lithium-ion batteries (LIBs) in new energy vehicles (NEVs), particularly under high discharge rates. This study proposes a synergistic hybrid BTMS integrating composite phase-change material (CPCM)–aluminum foam with liquid cooling to enhance thermal regulation of cylindrical battery modules under 5 C discharge conditions. Multiple liquid-cooled plate (LCP) configurations, including serpentine, straight, and leaf-shaped designs, together with different flow channel topologies (FCTs), were systematically investigated and optimized. The effects of coolant flow speed (CFS) and ambient temperature were also analyzed. Results indicate that the optimized leaf-shaped LCP with FCT #2 delivers superior performance, limiting the maximum temperature to 309.98 K, reducing temperature difference by 7.6%, and decreasing pressure drop by 88.79% compared to the serpentine configuration. Increasing CFS improves heat dissipation and delays PCM melting, although it raises pressure losses. Furthermore, the proposed system maintains a cell-to-cell temperature difference below 0.51 K, indicating excellent thermal uniformity. Compared to a CPCM-only system, the hybrid BTMS reduces peak temperature by 8.81 K under elevated ambient conditions (309.15 K), demonstrating strong potential for reliable and efficient thermal management in demanding operating environments. Full article

Research on the effect of channel bending on control rod drop is crucial; this paper employs FLUENT dynamic mesh technology to study the drop behavior of a control rod in a simplified control rod channel after bending deformation. It compares the differences in rod drop under different fluid media and various bent channel geometries (straight channel, C-shaped bent channel, S-shaped bent channel), and analyzes the variation patterns of rod drop time, velocity, static pressure, dynamic pressure, and flow field. The results show that under C-shaped and S-shaped bends, the changes in the flow field when the control rod descends without contacting the channel have no effect on the rod drop time. Full article

The transition toward sustainable manufacturing requires an understanding of how industrial policies shape firms’ long-term green innovation capabilities. This study investigates the impact of China’s intelligent manufacturing pilot policy on enterprises’ sustainable green innovation, conceptualizing the policy as an exogenous driver of systemic transformation at the firm level. Using multi-period difference-in-differences (DID) regression on an unbalanced panel dataset of Chinese listed companies from 2010 to 2023, we find that the intelligent manufacturing pilot policy exerts a significantly positive effect on enterprises’ sustainable green innovation. Mechanism analyses reveal that the policy promotes sustainable green innovation through three pathways: facilitating digital transformation, alleviating financing constraints, and enhancing ESG performance. Heterogeneity analysis further indicates that the policy effects are more pronounced in eastern regions, among non-state-owned enterprises, in non-heavily polluting industries, and in technology-intensive industries. These findings provide insights into how systemic policy interventions can drive sustainable innovation at the firm level, with implications for policymakers and enterprises seeking to align industrial upgrading with long-term green development. These findings are interpreted through a system transformation lens, where intelligent manufacturing policies trigger co-evolutionary changes across digital, financial, and governance subsystems. Full article

Sewage sludge management is increasingly shifting from a liability-focused “treat-and-dispose” approach toward resource recovery, where digestion residues and their liquid fractions are treated as secondary feedstocks for nutrient, water, and energy recovery. In Europe, the recast Urban Wastewater Treatment Directive strengthens performance and monitoring requirements and reinforces the need for efficient sludge treatment and downstream valorization routes. This review synthesizes evidence on how pretreatment-induced changes in digestate properties translate into membrane performance outcomes and maps practical design implications for selecting pretreatment-membrane trains for nutrient recovery and reclaimed water production. Pressure-driven membrane methods (MF/UF/NF/RO), together with membrane distillation and electrodialysis, are central candidates for producing clarified water streams and concentrating nutrients; however, their performance is governed by digestate rheology, colloidal stability, and the composition of soluble microbial products and inorganic ions, which collectively shape fouling and scaling risks. Pretreatments such as thermal hydrolysis and microwave conditioning can modify floc structure and solubilize organics, with potential benefits for dewaterability and mass transfer, but can also shift particle size distributions toward fines and increase fouling propensity if not coupled with appropriate solid–liquid separation and conservative flux control. Emphasis is placed on mechanisms and operational trade-offs rather than single-point performance claims, highlighting where evidence is robust and where further comparability and full-scale validation remain necessary. Full article

This study investigates the psychological and contextual mechanisms through which consumers’ awareness of agriculture’s contribution to climate change translates into a willingness to pay (WTP) for low-carbon agricultural products. Drawing on data from Eurobarometer 93.2 (ZA7739; N = 24,193), the research applies a moderated mediation model (Hayes’ PROCESS Model 14) to examine the mediating role of support for mandatory environmental labelling and the moderating effect of residential context. The results indicate that climate change awareness is significantly and positively associated with WTP. Moreover, support for mandatory labelling partially mediates this relationship, suggesting that institutionalized transparency may serve as a key mechanism through which environmental concern becomes economically actionable. The findings further reveal that this indirect effect is moderated by the level of urbanization, being stronger in urban areas than in rural settings. This highlights the importance of socio-spatial context in shaping consumer responses to sustainability information. Overall, the study contributes to the literature on sustainable consumption by demonstrating that willingness to financially support low-carbon agriculture depends not only on environmental awareness but also on trust-enhancing policy instruments and contextual factors. The findings offer important implications for policymakers aiming to promote sustainable food systems through information-based regulation. Full article