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How institutional pressure and green transformational leadership shape enterprise green development
Abstract This study extends existing literature by exploring the impact of institutional pressures on green transformational leadership in a way that triggers green thinking and creative process engagement among employees. This research enhances the understanding that leveraging employees to express their concerns over environmental issues would contribute to sustainable solutions that foster enterprise green development. Data was collected from China’s manufacturing industry executives and non-executives and analyzed in SmartPLS. This study responds to environmental concerns through the lens of institutional pressure that motivates leaders to engage their subordinates in green thinking and creative processes, and work together to boost the financial and environmental performance of the organizations. This research study highlighted the nexus between IP, GTL, CPE, GT, and enterprise green development. The study revealed direct and indirect relations of IP and GTL on the cognitive aspects of subordinates and enterprise green development. The findings offer significant insights and mechanisms for managers to translate institutional pressures into GT and CPE to achieve EGD.
Optimizing the dose of flywheel resistance training for jumping and sprinting performance: a systematic review and meta-analysis of frequency, volume, and duration
Abstract To compare the efficacy of lower-limb flywheel resistance training (FRT) versus conventional training (e.g., barbell and dumbbell exercises) on athletes’ sprinting and jumping abilities, and to identify optimal training dosages (frequency, duration, and volume). Four electronic databases were searched from inception to present. Following PICOS criteria, randomized and non-randomized controlled trials involving athletes and FRT interventions (≥ 3 weeks) were included. Data were synthesized using a random-effects model in R software, with Hedges’ g calculated as the effect size, and evidence certainty was assessed via the GRADE approach. Twelve studies (280 subjects) were included. Meta-analysis showed that FRT produced a small but significant improvement in jump height (g = 0.35, p < 0.05) and sprint time (g = − 0.32, p < 0.05) compared to conventional training. Subgroup analysis revealed a significant dose-response relationship: meaningful improvements required a duration of ≥ 8–9 weeks, ≥ 10 total sessions, specific volume threshold (i.e., sets × repetitions × number of sessions performed; ≥210 for jumping; ≥244 for sprinting). Furthermore, lower weekly frequencies (< 2 sessions/week) yielded larger effect sizes than higher frequencies. FRT, when implemented as a standalone modality, appears more effective than traditional training for enhancing sprinting and jumping abilities. To optimize adaptations, practitioners should implement longer interventions (≥ 8 weeks) with low weekly frequency (1–2 sessions) to balance high-intensity eccentric loading with neuromuscular recovery.
Meta-cluster driven ensemble learning with cluster-augmented features for explainable heart disease prediction
Structural characterization and visualization of oligomeric states of the Rhagium mordax antifreeze protein
Secure electronic voting system based on blockchain with dilithium authentication and zero-knowledge proof verification
House price prediction using a hybrid GRU–MLP based on binary whale optimization algorithm and ant colony optimization for hyperparameter tuning
Abstract Accurate house price prediction is essential for real estate valuation, investment planning, and intelligent property decision-support systems. This study proposes an optimized hybrid deep learning framework that integrates a Gated Recurrent Unit and Multilayer Perceptron model with the Binary Whale Optimization Algorithm for feature selection and Ant Colony Optimization for hyperparameter tuning. The proposed framework was evaluated using a publicly available Kaggle house price regression dataset containing 500 housing records with structural, locational, and amenity-related attributes. The dataset was divided into training, validation, and testing subsets using a 70:20:10 ratio, and leakage-free normalization was applied using only the training data. Experimental results show that the proposed BWOA–ACO–GRU–MLP model outperformed standalone GRU, MLP, CNN, LSTM, and BiLSTM models. It achieved an MSE of 0.0146, MAE of 0.1051, RMSE of 0.1208, MAPE of 0.0112, MedAE of 0.0969, and an R 2 of 99.04%. These results demonstrate that combining feature selection, hyperparameter optimization, and hybrid neural regression improves prediction accuracy and model stability for house price estimation. The proposed framework provides a reliable data-driven approach for smart real estate valuation applications.
Resolving FRET signal degeneracy and population heterogeneity via Bayesian nonparametrics
The effects of using a multi-modal rest cabin versus a waitlist control on worker well-being: A pragmatic randomized controlled trial
Abstract Workplace rest cabins are a promising yet understudied approach to supporting worker well-being. This pragmatic randomized controlled trial examined whether a multi-modal rest cabin could improve general and work-related well-being among workers of a Canadian insurance company. Participants were randomly assigned to either a one-month waiting-list control condition or a cabin-use condition. A total of 80 participants were included in the final analytic sample. Surveys were completed at baseline (T0) and again one month later (T1); cabin users also completed follow-up surveys two (T2) and four months (T3) after completing T0. Outcomes included positive and negative affect, depression, anxiety, flourishing, burnout (namely cognitive weariness, emotional exhaustion, and physical fatigue), absenteeism, presenteeism (namely troublesome symptoms at work and impaired productivity), job satisfaction, mindful attention awareness, insomnia, and psychological detachment. Cabin-use frequency was extracted from reservation logs. Linear mixed-effects models evaluated i) differential change between conditions from T0 to T1, ii) maintenance of effects within the experimental group across Times 1 to 3 relative to T0, and iii) whether use frequency was associated with changes in well-being from T0 to T1. Compared with the control group, cabin users experienced protective effects against depression, cognitive weariness, and physical fatigue, and protective effects approaching statistical significance against a deterioration in positive affect and mindful attention awareness. When examining maintenance of effects at follow-ups (versus baseline) in the experimental group, positive affect, cognitive weariness, and mindful attention awareness improved, or trended towards improvement, at T3, whereas physical fatigue improved, or trended towards improvement, at each time point. Workers who used the rest cabin more frequently experienced improved well-being across multiple indicators (positive affect, physical fatigue, insomnia, impaired productivity, mindful attention awareness); however, those who used the cabin four times in the one month showed greater improvement in physical fatigue, insomnia, and mindful attention awareness. Effects for all other outcomes were neither significant nor trending. A multi-modal rest cabin may buffer against declines in well-being and appears to offer accumulating benefits with more sustained use, suggesting usefulness as a personalized micro-break intervention in organizational settings. Trial registration: Retrospectively registered. Registration number: NCT07322354; Date: 2026-01-07.
Fairness and transparency in ML: a methodological framework
Acoustic wave speed in aerogels across material classes: density scaling from theory and experiments
Abstract Understanding the propagation of elastic waves in ultra-light porous solids is essential for linking their microstructure to macroscopic properties and mechanical performance. In this work, we present first an experimental study of longitudinal sound velocity in aerogels spanning a wide range of chemical structures and mesoscopic architectures, including polyurethane, polylactic acid, polyimide, flexible organo-silica, classical silica, and phenolic (resorcinol-formaldehyde) aerogels. Compression wave velocities were measured and correlated with bulk density to establish scaling relations across aerogel material families. While classical elasticity implies direct coupling between sound velocity in isotropic solids and elastic moduli, we then examine the extent to which such continuum relations remain valid in aerogels, whose structure is governed by hierarchical porosity, nanoscale connectivity, and bending-dominated network mechanics. Finally, we suggest measuring the Young modulus of aerogels from the acoustic wave speed as a non-destructive testing alternative.
Adaptive trajectory tracking control for autonomous vehicles based on heading angle deviation
Spatiotemporal dynamics and driving mechanisms of the coupling coordination between transportation carbon emissions and regional economy: a case study of Sichuan Province
Multi timescale predictive energy management for battery life extension in electric vehicles
Abstract Electric-vehicle battery energy management increasingly requires coordinated control of electrical demand, thermal behavior, and long-term degradation to ensure safe and durable operation. Existing predictive and digital-twin-inspired model-based observer battery-management approaches often do not fully integrate fast electro-thermal regulation with slow health-aware supervisory adaptation. To address this gap, this study proposes a multi-timescale health-resilient predictive energy-management framework that combines a fast predictive control layer for real-time traction-demand satisfaction with a slow supervisory layer that updates health-dependent limits, adaptive weights, and operating envelopes using cumulative electro-thermal-aging stress. The framework is evaluated in discrete-time simulation under Urban-Nominal, Highway-Nominal, Aggressive-Hot, and Aged-Battery-Hot scenarios against Rule-Based, Fast-MPC-Only, and Electro-Thermal-MPC strategies. Results show that the proposed controller consistently provides the most favorable battery-preservation tradeoff. Under Urban-Nominal operation, it reduces RMS current to 125.75 A and achieves the lowest cumulative degradation among the predictive controllers. Under Aggressive-Hot operation, it lowers RMS current to 120.44 A and cumulative degradation to $$\:1.4929\times\:{10}^{-5}$$ , while under Aged-Battery-Hot conditions it again yields the lowest degradation and loss-energy trends among the predictive methods. The proposed framework therefore offers a balanced compromise between short-term energy-management performance and long-term battery durability, suggesting its potential usefulness for health-aware EV battery energy-management studies, subject to further experimental and long-horizon validation.
DFT and molecular docking investigation of tamoxifen interactions with metal-encapsulated boron nitride nanocages
Abstract Tamoxifen (TMF), a lipid-soluble selective estrogen receptor modulator (SERM), is extensively used in the treatment of breast cancer. In this work, we systematically investigate the covalent and non-covalent interactions of TMF with the perfect B 12 N 12 compared to as well as with calcium- and potassium-encapsulated derivatives (B 12 CaN 12 and B 12 KN 12 ). These interactions are predominantly mediated by the dimethylamino group (-N(CH₃)₂) of TMF and were examined using density functional theory (DFT) calculations at the M06-2X level, incorporating D3 dispersion corrections (M06-2X-D3) and the 6–31 + G** basis set. The results reveal that TMF undergoes strong chemisorption on B 12 KN 12 (-2.27 eV) and B 12 CaN 12 (-1.91 eV), in contrast to weaker adsorption on the pristine B 12 N 12 surface (-1.75 eV). The strong binding of TMF to B₁₂N₁₂ via its dimethylamino group occurs through a synergistic combination of covalent interactions and hydrogen bonding, accompanied by a larger charge transfer from the drug to the cage, leading to a significant increase in dipole moment and a change in the energy gap. Thermodynamic analyses based on Gibbs free energy and enthalpy changes confirm that complex formation is highly stable, spontaneous, and exothermic. Notably, B 12 N 12 exhibits the shortest recovery time, indicating rapid TMF detachment, whereas B 12 CaN 12 and B 12 KN 12 show longer desorption times, favoring sustained release. ADMET predictions suggest moderate intestinal absorption and good membrane permeability, indicating potential for oral bioavailability. Docking studies reveal that B 12 KN 12 enhances TMF binding to EGFR, HER2, and Caspase-8, despite a minor reduction in ERα affinity, supporting the potential of B 12 KN 12 as a nanocarrier for HER2-driven breast cancer treatment.
Electrostatic headroom coordinated minimum feasible high-frequency injection strategy for low-speed motor drives using a half bridge modular multilevel converter
Abstract This paper proposes a boundary-based minimum-injection high-frequency balancing strategy for low-speed standard half-bridge modular multilevel converter (MMC) motor drives to reduce the injected high-frequency balancing voltage and current and the associated electrical stress while maintaining the prescribed submodule capacitor-voltage ripple limit. The proposed method preserves the conventional Korn-type high-frequency injection (HFI) balancing path, but determines the commanded injection level from a constrained minimum-injection condition governed by the residual arm-energy demand and the available electrostatic buffering capability of the capacitor stack. An analytical operating boundary between HFI-assisted balancing and capacitor-based self-buffering is established by comparing the residual-energy requirement with the usable capacitor-voltage headroom constrained by modulation feasibility and the upper submodule voltage limit. Accordingly, the injection coefficient and the average capacitor-voltage reference are jointly coordinated so that the capacitor stack buffers the admissible residual energy, whereas the HFI channel supplies only the remaining balancing component required for ripple regulation. Comparative simulations against fixed HFI and a recent adaptive HFI benchmark demonstrate reductions of 33.0% in the mean compensation coefficient, 29.1% in the representative peak-to-peak submodule capacitor-voltage ripple, 13.7% in the representative arm-current RMS, 28.5% in the representative arm-current peak, and 25.3% in the current-squared loss proxy. The common-mode-voltage benefit is mainly reflected in the RMS and accumulated-burden indices rather than in the reduction of every instantaneous peak. These results verify that the proposed strategy reduces the injected high-frequency balancing content and the associated current- and voltage-side stresses under explicit ripple, modulation, and capacitor-headroom constraints.
Occupational sleepiness in suburban metro drivers: association with fatigue, occupational balance and work functioning
Abstract The study examined levels of daytime sleepiness, occupational fatigue, perceived work functioning and occupational balance among suburban metro train drivers, and identified independent predictors of daytime sleepiness. A cross-sectional study was conducted with 191 public transport train drivers who completed validated self-report measures assessing sleep-related functional outcomes (FOSQ), daytime sleepiness (ESS), occupational fatigue (SOFI), work role functioning (WRFQ) and occupational balance (OBQ-E). Descriptive analyses and Pearson correlations were performed, and a multiple linear regression model adjusted for work shift identified independent predictors of daytime sleepiness. Clinically relevant levels of daytime sleepiness (ESS median 11, IQR 7–15) and occupational fatigue were observed. Sleepiness showed a moderate positive correlation with occupational fatigue ( r = .544, p < .001) and negative correlations with occupational balance ( r = − .419, p < .001) and work role functioning ( r = − .434, p < .001). The regression model adjusted for work shift was significant (F(6,173) = 17.00, p < .001) and explained 37.1% of the variance. Occupational fatigue (β = 0.298, p = .002), occupational balance (β = −0.210, p = .007) and work role functioning (β = −0.169, p = .045) were significant predictors of daytime sleepiness, whereas work-shift categories were not significant after adjustment. Interventions targeting fatigue management and occupational balance may help reduce sleepiness and enhance operational safety.
Integrated proteomics–driven discovery of synovial fluid biomarkers reflecting structural damage and pain in knee osteoarthritis
Attentional focus modulates neuromechanical organization and motor complexity during walking
Abstract Attentional focus instructions have long been recognized for their impact on motor performance and learning, yet their influence on the neuromechanical aspects of gait—spanning multiple analytical levels—remains underexplored. In this study, the authors investigated how attentional focus (internal, external, or no focus) and sex affect lower-limb coordination during walking, drawing on a blend of biomechanical and neuromuscular methods. The complexity of kinematic and electromyographic (EMG) signals was quantified using sample entropy, the inter-joint coordination was evaluated through the Uncontrolled Manifold (UCM) framework by calculating the synergy index (ΔV = log₁₀(V_UCM / V_ORT)) in the sagittal, frontal, and transverse planes, and muscle synergies were extracted via non-negative matrix factorization, emphasizing the number needed to account for 90% of the total variance (VAF). The findings highlighted a persistent main effect of attentional focus across all levels. External focus led to greater kinematic and EMG sample entropy, suggesting heightened movement complexity. Likewise, the UCM synergy index (ΔV) was markedly higher with external focus in every plane, indicating more variability that stabilized the task. In muscle synergy analysis, attentional focus reshaped neuromuscular modularity, requiring fewer synergies to achieve 90% VAF under external focus. Sex differences were modest, appearing only in sagittal-plane ΔV, with no interactions between attentional focus and sex. These results illustrate how attentional focus reshapes gait organization from signal complexity to inter-joint coordination and neuromuscular patterns. Together, they bolster the notion that external focus encourages more adaptive, task-oriented control during walking. This underscores the benefits of multilevel analyses in unpacking the mechanisms behind attentional influences on locomotion.