Search Results (15,433)

Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology, with its advantages in large-scale and high-precision deformation monitoring, has become an essential tool for monitoring surface subsidence in coal mining areas. To address the issue of missing deformation values resulting from interferometric decoherence when using InSAR technology for surface subsidence monitoring in mining areas, this study proposes a combined approach integrating SBAS-InSAR with KTree Adaptive Inverse Distance Weighting (KTree-AIDW). The method constructs a dynamic neighborhood search mechanism through the KTree algorithm, considering the spatial heterogeneity between the interpolation points and adjacent sample points, and optimizes the weight distribution of heterogeneous sample points. The study is based on Sentinel-1 data with a 12-day revisit cycle, focusing on the 2021 grouting working face of the Liangbei Mine in Yuzhou, Henan Province, China. The results show the following: (1) Along both the strike and dip lines, the correlation coefficient between the SBAS-InSAR + KTree-AIDW results and leveling result is 0.95, with an overall root mean square error (RMSE) of 22.08 mm and a relative root mean square error (RRMSE) of 9.48%. The Mean Absolute Error (MAE) of characteristic points in the decoherence region is 19.05 mm, indicating a significantly improved accuracy in the decoherence region compared to traditional methods. (2) The cumulative maximum subsidence in the study area reached 233 mm, with an average maximum subsidence rate of 171 mm/yr. The maximum positive/negative inclines were 2.4 mm/m and −2.9 mm/m; the maximum positive/negative curvatures were ±0.18 mm/m². The surface structures are within the threshold values specified for Class I damage. The proposed method effectively addresses the decoherence issue that leads to missing deformation data in mining areas, providing a novel technical approach to accurate surface subsidence monitoring under grouting and backfilling conditions. Full article

Background/Objectives: Voice disorders caused by laryngeal hypertension can impact volume, quality, pitch, resonance, flexibility, and stamina. The laryngeal palpation is a tactile-perceptual assessment, which is one of a few examination methods to evaluate laryngeal hypertension. Laryngeal palpation is a manual examination of the extrinsic and paralaryngeal tissues of the larynx (e.g., lateral laryngeal mobility, thyrohyoid and cricothyroid spaces, vertical laryngeal position/mobility, and pain) through the examiner’s fingers. It can be performed during rest (static assessment) or during phonation (dynamic assessment) of the individual being evaluated. This study aimed to validate a novel laryngeal palpation tool with quantitative ordinal scores by assessing its reliability and diagnostic accuracy establishing preliminary clinical cut-off values, and examining its correlations with self-reported voice disorder symptoms. Methods: In a prospective, controlled validation study, 33 participants were selected to assess the validity and reliability of the novel diagnostic tool in a clinical sample and healthy controls. The clinical sample (n = 19) comprised individuals diagnosed with voice disorders, whereas the healthy control group (n = 14) included participants with no history or symptoms of voice pathology. The novel laryngeal palpation tool was employed by two independent examiners to assess both static and dynamic laryngeal function in all participants. In addition, each participant completed the following questionnaires: Voice Handicap Index (VHI-30) with the 30-item, Vocal Fatigue Index (VFI), and the Vocal Tract Discomfort Scale (VTD). Results: Static palpatory assessment of laryngeal tension demonstrated excellent discriminatory power between groups and tension levels (AROC = 0.979), along with high intra-rater (ICC = 0.966) and inter-rater reliability (ICC = 0.866). Significant correlations were revealed between the static palpation results and the VHI scores (r = 0.496; p < 0.01) and VFI (r = 0.514; p < 0.01). For the dynamic evaluation of the palpation tool, comparable results for the validity (AROC = 0.840) and reliability (inter-rater: ICC = 0.800, and intra-rater: ICC = 0.840) were revealed. However, no significant correlations were found between dynamic palpation and self-perceived questionnaires, although some were likely found with static palpation. The validity of the total score was found to be AROC = 0.992. Conclusions: The static and dynamic assessments using the novel laryngeal palpation tool demonstrated promising reliability and diagnostic accuracy, providing initial evidence to support its clinical utility. Further studies are needed to establish broader validation. Full article

Robotic milling offers significant advantages for machining large aerospace components due to its low cost and high flexibility. However, compared to computerized numerical control (CNC) machine tools, robot systems exhibit lower stiffness, leading to force-induced deformation during milling process that significantly compromises path accuracy. This study proposed a dynamic robot posture programming method to enhance the stiffness for aluminum alloy milling task. Firstly, a milling force prediction model is established and validated under multiple postures and various milling parameters, confirming its stability and reliability. Secondly, a robot stiffness model is developed by combining system stiffness and milling forces within the milling coordinate system to formulate an optimization index representing stiffness performance in the actual load direction. Finally, considering the constraints of joint limit, singular position and joint motion smoothness and so on, the robot posture in the milling trajectory is dynamically programmed, and the joint angle sequence with the optimal average stiffness from any cutter location (CL) point to the end of the trajectory is obtained. Under the assumption that positioning errors were effectively compensated, the experimental results demonstrated that the proposed method can control both axial and radial machining errors within 0.1 mm at discrete points. For the specific milling trajectory, compared to the single-step optimization algorithm starting from the initial optimal posture, the proposed method reduced the axial error by 12.23% and the radial error by 8.61%. Full article

The rapid rise of social media has accelerated the evolution of public opinion, leading to frequent group polarization. Meanwhile, advancements in information science have enabled large-scale experiments, positioning dynamics as a crucial perspective for studying group polarization. This paper systematically reviews group polarization from a dynamics perspective. First, we outline its definitions and its explanatory theories. Then, we examine the role of dynamics in polarization research, summarize the current measurement methods of group polarization, and analyze intervention strategies based on elements of dynamics. Finally, we propose a logical framework for dynamics-based interventions. Our findings indicate that while research on group polarization from a dynamics perspective is relatively comprehensive, most intervention studies remain at the simulation level, requiring further validation for real-world applicability. This review provides a systematic overview of group polarization through a dynamics lens, offering insights for addressing challenges in network governance within the social media era. Full article

This study investigates long-term changes in thermal comfort across the Italian and Iberian Peninsulas from 1940 to 2024, using the Universal Thermal Climate Index (UTCI) derived from ERA5-HEAT reanalysis. We apply a dual analytical framework combining structural break detection to identify regime shifts and Sen’s slope estimation with confidence intervals to quantify monotonic trends. Results reveal pronounced seasonal asymmetries. Summer exhibits abrupt regime shifts in both regions: in 1980 for Italy (slope shifting from −0.039 °C/year before 1980 to +0.06 °C/year after) and 1978 for Iberia (from −0.054 °C/year to +0.050 °C/year). Winter, by contrast, shows no structural breaks but a persistent, spatially uniform warming trend of ~0.030–0.033 °C/year across the 1940–2024 period, consistent with a gradual erosion of cold stress. Transitional seasons display more nuanced responses. Spring reveals detectable breakpoints in 1987 for Italy (shifting from −0.028 °C/year to +0.027 °C/year) and 1986 for Iberia (from −0.047 °C/year to +0.024 °C/year), indicating the early acceleration of warming. Autumn shows a breakpoint in 1970 for Italy, with trends intensifying from +0.011 °C/year before to +0.052 °C/year after, while Iberia exhibits no clear breakpoint but a consistent positive slope. These findings highlight spring as an early-warning season, where warming acceleration first emerges, and autumn as a consolidating phase that extends summer-like heat into later months. Overall, the results demonstrate that Mediterranean thermal regimes evolve through both abrupt and gradual processes, with summer defined by non-linear regime shifts, winter by steady accumulation of warming, and spring and autumn by transitional dynamics that bridge these extremes. The methodological integration of breakpoint detection with Sen’s slope estimation provides a transferable framework for detecting climate regime transitions in other vulnerable regions under accelerated global warming. Full article

Purpose: This study investigates the relationship between flexible working arrangements (FWAs), employee experiences (EEs), and perceived productivity (PP) in the context of New Zealand employees. The study aims to understand how opportunities and challenges within FWAs impact employee productivity, utilising the Job Demands–Resources (JD-R) model as a theoretical framework. Design/methodology/approach: A survey was conducted with 176 employees who transitioned from traditional office settings to FWAs. Data were collected using a structured questionnaire measuring work demand, autonomy, employee experiences, and perceived productivity. The analysis involved correlational and moderated regression techniques to assess the relationships between the variables. Findings: The study found that positive employee experiences (expressed as opportunities) are significantly associated with higher perceived productivity (r = 0.610, p < 0.001), while negative experiences (expressed as challenges) are associated with lower perceived productivity (r = 0.515, p < 0.001). Moreover, management strategies were found to moderate these relationships, further influencing perceived productivity. Originality: This research contributes to the understanding of how FWAs, when effectively managed, can enhance employee productivity by fostering positive experiences. It also highlights the importance of addressing challenges to mitigate negative impacts on productivity. The use of the JD-R model offers a novel approach to exploring these dynamics in the context of FWAs. Practical and social implications: Organisations can enhance productivity by focusing on management strategies that amplify positive employee experiences and reduce challenges within FWAs. Effective FWAs can improve work–life balance, employee wellbeing, and organisational commitment, contributing to a more satisfied and productive workforce. Full article

This article presents a comprehensive investigation of the dynamic coupling between a piezoelectric actuator (PZT) and its driving nonlinear stiffness mechanism (NSM) stage for precise positioning control. Particular emphasis is placed on the preload-induced effects on the force transmission and structural separation between the PZT and NSM. To ensure continuous mechanical contact between them, we propose a no-separation criterion based on acceleration matching, from which the minimum preload requirement is analytically derived. Additionally, static and dynamic simulations reveal that increasing the preload force from 0 N to 10 N can push the first natural frequency of the holistic system from $214.21$ Hz to $258.17$ Hz, respectively. This beneficially enhances the displacement consistency across different geometric configurations. Moreover, an appropriate preload force can prevent separation and increase system stiffness while reducing nonlinear deformation. Experimental results verifies that a preload of 10 N can prevent the separation between the PZT and NSM stage and maintain achievable output displacement of the stage within the range from $54.35\mathsf{\mu }$m to $129.42\mathsf{\mu }$m. This article offers the analytical results of preload setting to guarantee reliable actuation for nonlinear precision positioning stages. Full article

Although epsilon-near-zero (ENZ) media have emerged as a promising platform for power dividers, the majority of existing designs are confined to fixed power splitting. In this work, two dynamically tunable power dividers using waveguide ENZ media are proposed by precisely modulating the internal magnetic field and the widths of the output waveguides. The first approach features a mechanically reconfigurable ring-shaped ENZ waveguide. By continuously re-distributing the magnetic field within the ENZ tunneling channels utilizing rotatable copper plates, arbitrary power division among multiple output ports is constructed. The second design integrates a rectangular-loop ENZ cavity into a substrate-integrated waveguide, with four positive–intrinsic–negative diodes embedded to dynamically activate specific output ports. This configuration steers electromagnetic energy toward output ports with varying cross-sectional areas, enabling on-demand control over both the power division and the number of output ports. Both analytical and full-wave simulation results confirm dynamic power division, with transmission efficiencies exceeding 93%. Despite differences in structure and actuation mechanisms, both designs exhibit flexible field control, high reconfigurability, and excellent transmission performance, highlighting their potential in advanced applications such as real-time wireless communications, multi-input–multi-output systems, and reconfigurable antennas. Full article

This study examines the effects of sustainability-related data requests—spurred by the EU Corporate Sustainability Reporting Directive (CSRD)—on small and medium-sized enterprises (SMEs) in the Netherlands. Using a representative survey of 431 SMEs and 48 qualitative interviews with SME representatives and business stakeholders, the research provides a comprehensive overview of their experiences in late 2024. A key finding is that most Dutch SMEs (72%) have not yet received sustainability data requests. However, SMEs embedded in international value chains report more frequent and complex data demands, particularly concerning environmental indicators like CO₂ emissions and material use. Ratings of perceived relevance reveal a disconnect between external data requests and SMEs’ internal priorities, with many SMEs prioritizing health and safety over climate metrics. While some SMEs see data requests as opportunities for improved sustainability performance and market positioning, many also experience challenges, including limited resources, fragmented IT systems, and regulatory uncertainty. The implementation of CSRD highlights the urgency of supporting SMEs in building data management capacities and standardized processes. The study recommends clearer communication of data relevance, targeted support measures, and further research into cross-national and longitudinal dynamics to foster an effective sustainability transition across value chains. Full article

Small object detection in UAV imagery remains challenging due to complex aerial perspectives and the presence of dense, small targets with blurred boundaries. To address these challenges, we propose ACD-DETR, an adaptive end-to-end Transformer detector tailored for UAV-based small object detection. The framework introduces three core modules: the Multi-Scale Edge-Enhanced Feature Fusion Module (MSEFM) to preserve fine-grained details; the Omni-Grained Boundary Calibrator (OG-BC) for boundary-aware semantic fusion; and the Dynamic Position Bias Attention-based Intra-scale Feature Interaction (DPB-AIFI) to enhance spatial reasoning. Furthermore, we introduce ACD-DETR-SBA+, a fusion-enhanced variant that removes OG-BC and DPB-AIFI while deploying densely connected Semantic–Boundary Aggregation (SBA) modules to intensify boundary–semantic fusion. This design sacrifices computational efficiency in exchange for higher detection precision, making it suitable for resource-rich deployment scenarios. On the VisDrone2019 dataset, ACD-DETR achieves 50.9% mAP@0.5, outperforming the RT-DETR-R18 baseline by 3.6 percentage points, while reducing parameters by 18.5%. ACD-DETR-SBA+ further improves accuracy to 52.0% mAP@0.5, demonstrating the benefit of SBA-based fusion. Extensive experiments on the VisDrone2019 and DOTA datasets demonstrate that ACD-DETR achieves a state-of-the-art trade-off between accuracy and efficiency, while ACD-DETR-SBA+ achieves further performance improvements at higher computational cost. Ablation studies and visual analyses validate the effectiveness of the proposed modules and design strategies. Full article

To meet the vibration isolation requirements of engines under diverse operating conditions, this paper proposes a novel magnetorheological fluid-elastomer isolator with high load and tunable parameters. The mechanical and magnetic circuit structures of the isolator were designed and optimized through theoretical calculations and finite element simulations, achieving effective vibration isolation within confined spaces. The dynamic performance of the isolator was experimentally evaluated using a hydraulic testing system under varying excitation amplitudes, frequencies, initial positions, and magnetic fields. Experimental results indicate that the isolator achieves a static stiffness of 3 × 10⁶ N/m and a maximum adjustable compression load range of 105.4%. In light of the asymmetric nonlinear dynamic behavior of the isolator, an improved nine-parameter Bouc–Wen model is proposed. Parameter identification performed via a genetic algorithm demonstrates a model accuracy of 95.0%, with a minimum error reduction of 28.8% compared to the conventional Bouc–Wen model. Full article

Drowning constitutes the leading cause of injury-related fatalities among adolescents. In swimming pool environments, traditional manual surveillance exhibits limitations, while existing technologies suffer from poor adaptability of wearable devices. Vision models based on YOLO still face challenges in edge deployment efficiency, robustness in complex water conditions, and multi-scale object detection. To address these issues, we propose YOLO11-LiB, a drowning object detection model based on YOLO11n, featuring three key enhancements. First, we design the Lightweight Feature Extraction Module (LGCBlock), which integrates the Lightweight Attention Encoding Block (LAE) and effectively combines Ghost Convolution (GhostConv) with dynamic convolution (DynamicConv). This optimizes the downsampling structure and the C3k2 module in the YOLO11n backbone network, significantly reducing model parameters and computational complexity. Second, we introduce the Cross-Channel Position-aware Spatial Attention Inverted Residual with Spatial–Channel Separate Attention module (C2PSAiSCSA) into the backbone. This module embeds the Spatial–Channel Separate Attention (SCSA) mechanism within the Inverted Residual Mobile Block (iRMB) framework, enabling more comprehensive and efficient feature extraction. Finally, we redesign the neck structure as the Bidirectional Feature Fusion Network (BiFF-Net), which integrates the Bidirectional Feature Pyramid Network (BiFPN) and Frequency-Aware Feature Fusion (FreqFusion). The enhanced YOLO11-LiB model was validated against mainstream algorithms through comparative experiments, and ablation studies were conducted. Experimental results demonstrate that YOLO11-LiB achieves a drowning class mean average precision (DmAP50) of 94.1%, with merely 2.02 M parameters and a model size of 4.25 MB. This represents an effective balance between accuracy and efficiency, providing a high-performance solution for real-time drowning detection in swimming pool scenarios. Full article

The satellite-derived climatic variables offer extensive spatial and temporal coverage for research; however, their inherent biases can subsequently reduce their accuracy for water balance estimate. This study evaluates the effectiveness of bias correction in improving the Tropical Rainfall Measuring Mission (TRMM) rainfall and the Global Land Data Assimilation System (GLDAS) land surface temperature (LST) data and illustrates their long-term (2000–2019) hydrological assessment. The novelty lies in coupling the bias-corrected climate variables with the Thornthwaite–Mather water balance model as well as land use land cover (LULC) for improved predictive hydrological modeling. Bias correction significantly improved the agreement with ground observations, enhancing the R² value from 0.89 to 0.96 for temperature and from 0.73 to 0.80 for rainfall, making targeted inputs ready to predict hydrological dynamics. LULC mapping showed a predominance of agricultural land (64.5%) in the area followed by settlements (20.0%), forest (7.3%), barren land (6.5%), and water bodies (1.7%), with soils being silt loam, clay loam, and clay. With these improved datasets, the model found seasonal rise in potential evapotranspiration (PET), peaking at 120.7 mm in June, with actual evapotranspiration (AET) following a similar trend. The annual water balance showed a surplus of 523.8 mm and deficit of 121.2 mm, which proves that bias correction not only enhances the reliability of satellite data but also reinforces the credibility of hydrological indicators, with a direct, positive impact on evidence-based irrigation planning and flood mitigation and drought management, especially in data-scarce regions. Full article

Against the backdrop of urban–rural integrated development, special ecological function zones, as spatial carriers with significant regional ecological value and rural development functions, are confronted with a striking conflict between ecological conservation and regional advancement. This contradiction is comprehensively reflected in the interactions among land use functions (LUFs) that differ in nature and intensity. Therefore, exploring the trade-off and synergy (TOS) among regional LUFs is not only of great significance for optimizing territorial spatial patterns and advancing rural revitalization but also provides scientific evidence for the differentiated administration of regional land use. Taking 185 townships in the Funiu Mountain area of China as research units, this study constructs a land use assessment system based on the ‘Production–Living–Ecological’ (PLE) framework, utilizing multi-source datasets from 2000 to 2020. Spearman correlation analysis, geographically weighted regression (GWR), and bivariate local spatial autocorrelation methods are employed to examine the spatio-temporal dynamics of LUFs and the spatial non-stationarity of their TOSs. The findings indicate that, throughout the research period, the production function (PF) displayed a fluctuating declining trend, whereas the living function (LF) and ecological function (EF) demonstrated a fluctuating increasing trend. Notably, EF held an absolute dominant position in the overall structure of LUFs. This is highly consistent with the region’s positioning as a special ecological function zone and also a direct reflection of the effectiveness of continuous ecological construction over the past two decades. Spatially, PF is stronger in southern, eastern, and northern low-altitude townships, correlating with higher levels of economic development; LF is concentrated around townships near county centers; and high EF values are clustered in the central and western areas, showing an opposite spatial pattern to PF and LF. A synergistic relationship is observed between PF and LF, while both PF and LF exhibit trade-offs with EF. The TOSs between different function changes demonstrate significant spatial non-stationarity: linear synergy was the primary type for PF-LF, PF-EF, and LF-EF combinations, but each combination exhibited unique spatial characteristics in terms of non-stationarity. Notably, towns identified as having different types of trade-off relationships in the study of spatial non-stationarity are key areas for township spatial governance and optimization. Through the allocation of regional resources and targeted policy tools, the functional relationships can be adjusted and optimized to attain sustainable land use. Full article

Background/Objectives: A series of 1-(3,5-dimethoxyphenyl)azetidine-2-ones were synthesised to evaluate their antiproliferative activity in MCF-7 breast cancer cells and HT-29 chemoresistant colon cancer cells. The 1,4-diarylazetidin-2-ones were designed by replacing the characteristic 3,4,5-trimethoxyphenyl Ring A of the antimitotic stilbene combretastatin CA-4 with a 3,5-dimethoxyphenyl substituent at N-1, together with phenyl, hydroxyl, and phenoxy substituents at C-3 of the four-membered ring. Methods: A panel of 12 novel compounds was synthesized and evaluated in estrogen receptor (ER)- and progesterone receptor (PR)-positive MCF-7 breast cancer cells followed with the more potent compounds further evaluated in HT-29 chemoresistant colon cancer cells. Cytotoxicity was determined by LDH assay. The structures of the 1-(3,5-dimethoxyphenyl)azetidine-2-ones 12i, 12k, 12o, 12p together with the 1-(3,5-dimethoxyphenyl)azetidine-2-one 12s were determined by X-ray crystallography. The trans configuration of the C-3 and C-4 substituents of the β-lactam ring was confirmed for compounds 12k and 12u. Molecular modelling and molecular dynamics studies examined the molecular interactions of the compounds with the colchicine binding site of tubulin. Results: The 1-(3,5-Dimethoxyphenyl)-4-(4-ethoxyphenyl)-3-hydroxyazetidin-2-one 12l was identified as the most potent antiproliferative compound in the series (with an IC₅₀ value of 10 nM in MCF-7 breast cancer cells and 3 nM in HT-29 colon cancer cells) and with greater potency than CA-4 in the chemoresistant HT-29 cells. Computational docking studies predicted binding conformations for 12l and the related series of compounds in the colchicine binding site of tubulin and rationalised the impact of the 3,5-dimethoxyphenyl substituent at N-1 of the azetidine-2-one on activity. Conclusions: These findings indicate that the novel 1-(3,5-dimethoxyphenyl)-2-azetidinone 12l is a suitable candidate for further investigation as a potential antiproliferative microtubule-targeting agent for breast and chemoresistant colon cancers. Full article