Search Results (11,868)

Air pollution not only affects urban production and residents’ lives but also threatens human health, and the construction of the subway is considered an important measure to improve urban traffic congestion and air quality. To test whether the construction and opening of subways with high operating costs can effectively improve urban air quality, this paper takes the opening of subways as a quasi-natural experiment. Based on panel data from 282 cities in China from 2014 to 2021, the difference-in-differences method is used to estimate the impact of subway openings on urban air pollution. It is found that (1) the subway opening significantly reduces urban air pollution, and this conclusion remains valid after a series of robustness tests. (2) Mechanism analysis indicates that subway openings mostly mitigate urban air pollution through the traffic substitution effect, which is generated through the substitution of private car travel. (3) Heterogeneity analyses show that the abatement effect of subway openings on air pollution is more significant when the city is a non-Yangtze River Economic Belt city, or when the city’s economic level is lower, or when the city is a non-resource-based city. Therefore, this paper puts forward targeted policy recommendations, such as optimising the subway layout, promoting the transit-oriented development mode based on the subway system, and implementing differentiated development strategies, with a view to providing certain references for promoting sustainable urban development. Full article

The growing volume of plastic waste from end-of-life vehicles presents environmental concerns, driving efforts to integrate recycled plastics. This study investigates the possibility of using recycled plastic from automotive parts (painted and unpainted bumpers, fuel tanks) as a 10% filler in the core layer of three-layer particleboards (P) and evaluates its impact on physical properties (water absorption—WA and thickness swelling—TS), mechanical properties (internal bonding strength—IB, modulus of rupture—MOR, modulus of elasticity—MOE and screw driving torque—SDT) and volatile organic compounds—VOC emissions. The boards were produced using conventional hot-pressing technology and analyzed according to applicable standards. Based on the results, the density of the reference (P) was 0.72 g·cm⁻³, while wood–plastic composites ranged from 0.70 g·cm⁻³ to 0.72 g·cm⁻³. After 24 h, WA reached 40% for reference (P) and from 36.9% (for (P) containing unpainted bumpers) to 41.9% (for (P) containing fuel tanks). TS reached 18% for (P) and from 16.8% (for (P) containing unpainted bumpers and fuel tanks) to 18.1% (for (P) containing painted bumpers). Plastic is a hydrophobic material and it is assumed that by increasing the proportion of plastic filler in the particleboards, the WA and TS of prepared boards will decrease. From the point of view of mechanical properties, values for (P) containing plastic filler were slightly lower compared to reference (P). The lowest value of IB (0.39 MPa) were reached for (P) containing painted bumpers. Plastic surface treatment could interfere with adhesion between the plastic and adhesive, weakening the bond in the core layer. For this reason, is preferable to use unpainted fillers, which provide better adhesive properties and higher structural integrity. VOC emissions from wood components consisted primarily of monoterpenes such as α-pinene, 3-carene and limonene. Adding 10% plastic to the particleboard did not increase overall VOC emissions. On the other hand, combining wood and plastic particles resulted in a reduction in overall VOC emissions. The findings confirm that recycled automotive plastics can be effectively incorporated into particleboards, maintaining standard performance while reducing reliance on virgin wood materials, making them a viable and sustainable alternative for furniture and interior applications. Full article

I dispute the conventional claim that the second law of thermodynamics is saved from a “Maxwell’s demon” by the entropy cost of information erasure and show that instead it is measurement that incurs the entropy cost. Thus, Brillouin, who identified measurement as savior of the second law, was essentially correct, and putative refutations of his view, such as Bennett’s claim to measure without entropy cost, are seen to fail when the applicable physics is taken into account. I argue that the tradition of attributing the defeat of Maxwell’s demon to erasure rather than to measurement arose from unphysical classical idealizations that do not hold for real gas molecules, as well as a physically ungrounded recasting of physical thermodynamical processes into computational and information-theoretic conceptualizations. I argue that the fundamental principle that saves the second law is the quantum uncertainty principle applying to the need to localize physical states to precise values of observables in order to effect the desired disequilibria aimed at violating the second law. I obtain the specific entropy cost for localizing a molecule in the Szilard engine and show that it coincides with the quantity attributed to Landauer’s principle. I also note that an experiment characterized as upholding an entropy cost of erasure in a “quantum Maxwell’s demon” actually demonstrates an entropy cost of measurement. Full article

Pressure from competitors and regulatory interventions are external factors influencing hotels’ commitment to Environmental, Social and Governance (ESG) initiatives. This study aimed to explore the relationships between perceived entrepreneurial orientation, perceived commitment to ESG practices, and corporate financial performance through the lens of the resource-based view of the firm. Additionally, the moderating effect of hotel size was analyzed. Data were collected via a survey of hotel managers in Hong Kong in 2025. The results indicate a significant relationship between perceived entrepreneurial orientation and commitment to ESG practices. This study provides a solid understanding of the relationships among perceived entrepreneurial orientation, corporate autonomy, commitment to ESG practices, and corporate financial performance. The moderating effect of corporate size reveals that size itself does not directly influence how commitment to ESG affects corporate financial performance in the hotel industry. In contrast, hotel size does influence how entrepreneurial orientation relates to ESG commitment; specifically, smaller hotels are more entrepreneurial and committed to ESG practices when they have greater decision-making autonomy. However, entrepreneurial orientation and ESG commitment do not significantly influence financial performance, regardless of hotel size. This study offers practical implications for policymakers regarding the relevance of entrepreneurial orientation and corporate autonomy in enhancing commitment to ESG practices. Full article

Dietitian-led grocery store tours (GSTs) educate consumers about nutrition. Virtual GSTs could increase access to nutrition education. A feasibility study was conducted to determine participant acceptability and their physiological responses to a virtual GST using immersive virtual reality (IVR), a desktop monitor (PC), or a tablet. Participants were asked to report to the laboratory on three occasions to view a virtual GST. Physiological measurements were collected, and participants completed questionnaires about their feelings of presence, nausea, mood, and enjoyment during the virtual GST. Participants experienced a greater sense of presence (IVR = 5.8, PC = 2.6, tablet = 2.6; p < 0.05) with a greater feeling of nausea (IVR = 1.7, PC = 0.4, tablet = 0.4; p < 0.05) in the IVR treatment. Participants enjoyed the IVR GST more than the tablet GST (IVR = 5.3, PC = 4.6, tablet = 4.1; p < 0.05). There were marginal effects of treatment on heart rate (p < 0.05) but not on other physiological measures. There were no differences in the participants’ willingness to recommend a virtual GST given the use of different technologies to a friend or in the participants’ reported mood. Virtual GSTs, using different technologies, may be a feasible approach to provide nutrition education Full article

Large-scale deformation fields are crucial for monitoring seismic activity, landslides, and other geological hazards. Traditionally, the acquisition of large-area, three-dimensional deformation fields has relied on GNSS data; however, the inherent sparsity of these data poses significant limitations. The emergence of Interferometric Synthetic Aperture Radar (InSAR) data offers an alternative, enabling the retrieval of large-area, high-resolution deformation velocity fields. Nonetheless, the processing of InSAR data is often complex, time-consuming, and requires substantial storage capacity. To address these challenges, various research institutions have developed online InSAR processing platforms. For instance, the LiCSAR processing platform provides interferometric images covering approximately 250 km × 250 km, facilitating scientific applications of InSAR data. However, the transition from individual interferograms to large-scale, three-dimensional deformation fields often requires additional processing steps, including ramp correction within the images, mosaicking between adjacent images, and the joint inversion of InSAR observations from different viewing angles. In this paper, we propose a novel method for splicing several individual InSAR velocity fields into continent-scale InSAR velocity maps, which takes along-track and cross-track mosaicking into consideration. This method integrates GNSS data with InSAR data and also considers the additional constraint of data overlap region. The efficacy of this methodology is substantiated through its implementation in InSAR observations of the eastern Tibetan Plateau. In some tracks, there are overlapping areas on the east and west sides, and the line-of-sight (LOS) value can be effectively corrected by using these overlapping areas with similar size for two cross-track mosaics. The root mean square error (RMSE) of these tracks was reduced by about 4% to 8% on average when verified using true values of GNSS data compared to no cross-track mosaic. In addition, a significant improvement of 30% in RMSE reduction was achieved for some tracks. Full article

In view of the diversity and varying complexity of ship equipment, and the difficulty of existing state assessment methods in effectively handling the differences in the influence of different characteristic parameters on the equipment’s health state, leading to poor evaluation results, this paper proposes a ship equipment health state assessment method based on BP-RF and combined weighting. This method utilizes the BP-RF model to mine the implicit relationship between ship equipment feature parameters and state patterns, converting monitoring data into state pattern probability information. A trapezoidal membership function is used to determine the membership degree of each state pattern probability to different health state levels. The combined weighting method, which reflects a symmetric concept, balances expert experience and data information by integrating the subjective and objective weights of each state pattern probability, thus determining the equipment’s health state level. Through a case study of a specific type of ship’s gas turbine, the BP-RF model achieves a diagnostic accuracy of 98.3%, with $F_1$ scores improved by 5.1%, 5.0%, 8.6%, 9.9%, 6.7%, 3.4%, and 5.3% compared to the BP neural network, RF, Support Vector Machine (SVM), Convolutional Neural Network (CNN), BP-SVM, SVM-RF, and CNN-SVM models, respectively. Additionally, the evaluation results of this method exhibit clear boundaries for each state membership degree, effectively addressing the problem of unbalanced contributions from characteristic parameters and comprehensively reflecting the relative importance and correlation of each parameter. Overall, this method provides a more accurate and comprehensive assessment of ship equipment health compared to other methods, offering reliable support for ship equipment maintenance and assurance. Full article

Embedded and real-time monitoring of pavement mechanical state changes based on the strain detected by self-sensing sensors of polymer/conductive composites is a new way for pavement health monitoring. Strain monitoring, using polymer-based composite mechanosensitive materials, requires the formation of effective conductive networks and conductive channels within the composite material so that the mechanosensitive material is electrically conductive at the macroscopic level. However, the deformation of the pavement structure is much smaller in magnitude, which is about hundreds or even tens of microstrains (10⁻⁶). Therefore, it is especially important to study the strain self-sensing mechanism of conductive composites at the με level. Micro- and nanostructured polymer composites have a complex structure with multiple layers, scales, and interactions, and thus present many difficulties when studying their microscopic conductive mechanisms. In this paper, the all-atom system of the micro-nanostructured composite mechanosensitive materials model was proposed with the help of molecular dynamics simulations. This achieved a breakthrough and realized the systematic study of the microscopic level of the relevant parameters of the composite’s conductivity from the molecular point of view to construct a relationship between the microscopic parameters, conductive network, and conductivity. The kinetic models of the micro-nanostructure and resin interface based on the molecular dynamics simulation technology were constructed to explore the dispersion state of the conductive filler, the interfacial interactions between the conductive filler and epoxy resin matrix, and the structural changes in the conductive network within the system under the tension state. Full article

Background: Endophthalmitis is a rare, sight-threatening condition resulting from infection inside the eye. This study more accurately characterises the cytokines upregulated in human endophthalmitis, and for the first time demonstrates a correlation with cytokine elevation in the serum. Methods: We recruited 39 patients, 17 with endophthalmitis and 22 controls. We compared cytokine expression quantified through cytometric bead assays for both vitreous and serum. Conclusions: The cytokine profile in the vitreous of patients with infectious endophthalmitis was suggestive of a highly inflammatory environment, as 23/26 cytokines examined were significantly elevated. In the patient sera, MMP-9, MPO, Calprotectin, NGAL, SAA (HVIP1), and MCP-1 (HIP1) were all significantly elevated in endophthalmitis samples, which was unexpected as pathology was thought to be localised with minimal systemic effects. Overall, many of the observed cytokines in endophthalmitis are associated with neutrophil responses, and we believe that this deserves further investigation with a view to developing immunomodulatory therapies to prevent endophthalmitis or improve clinical outcomes. Furthermore, our novel demonstration that cytokine elevation associated with endophthalmitis can be demonstrated in serum may allow for novel and rapid interventions. Full article

The existing literature on power grid reliability extensively examines the effects of individual automation technologies, such as Smart Grids, IoT, and AI, on reducing SAIDI (System Average Interruption Duration Index) and SAIFI (System Average Interruption Frequency Index) indices. However, previous studies have largely focused on partial analyses, often limited to specific aspects of grid operation or isolated case studies. As a result, there is a lack of a comprehensive and integrated theoretical approach that considers the interdependencies between different automation technologies, their impact on various levels of grid management and the economic consequences of their deployment. This study presents a novel theoretical framework aimed at providing a holistic perspective on power grid automation and its impact on energy supply reliability. The key elements of this approach include developing a multidimensional mathematical model that integrates the impact of key automation technologies on SAIDI and SAIFI, allowing for a quantitative assessment of different implementation strategies and applying a probabilistic approach to predict the likelihood of power outages based on the level of automation and real-time grid conditions. This proposed framework offers a holistic view of power grid automation, integrating technical, economic and operational dimensions. It serves as a foundation for further empirical research and the implementation of intelligent grid modernisation strategies, aiming to enhance power supply stability and increase the resilience of distribution networks against outages. The introduced concept aligns with the current challenges of the energy transition, providing utilities and policymakers with analytical tools for making optimal decisions regarding the adoption of digitalisation and automation technologies in the power sector. Full article

In planar linkage mechanisms, due to various influencing factors, the existence of joint clearance becomes an inevitable phenomenon, which substantially diminishes the precision of the system’s movement. Currently, the majority of studies are largely confined to simple mechanisms with a single clearance, whereas investigations into more intricate systems with multiple types of clearances are still lacking. In view of this, this paper proposes an innovative dynamic algorithm for complex multilink mechanisms, aiming to deeply explore the specific impacts of multiple factors on dynamic response and nonlinear rigid-body properties, as well as its reliability analysis. Taking an eight-bar mechanism as an example, a dynamic model with mixed clearances is constructed, based on which the dynamic responses of the mechanism to different types of clearances are studied. Simultaneously, the effects of different variation ranges of clearance values and traveling speeds on the dynamic response, nonlinear characteristics, and dynamic accuracy reliability analysis of the mechanism were investigated. This research not only lays a robust theoretical foundation for the dynamics of multilink mechanisms but also demonstrates significant value and significance in both academic research and engineering application fields. Full article

The fusion modeling of intra-session item information representation and inter-session item transition pattern for session recommendation has shown performance advantages. However, existing research still suffers from the following challenges: (1) the time-varying effects of complex relationships between item transitions within sessions need to be deeply explored; and (2) the lack of effective representation for inter-session item transition patterns. To address these challenges, we propose a new session recommendation, named EGDLTP-CCL. Specifically, we first design a patch-enhanced gated neural network representation of session item transition patterns, which accurately captures the time-dynamically varying impacts of the complex relationships within sessions of item transitions through a designed transformer patching strategy. Then, we develop an energy-constraint-based graph diffusion model to capture the inter-session item transition patterns, which mitigates the problem of poor simulation of real inter-session item transition patterns by the introduction of an energy-constraint strategy for the graph diffusion model. In addition, patch-enhanced gated neural networks and energy-constrained graph diffusion models are treated as two different views in the contrastive learning framework. By introducing a curriculum learning strategy that explores how to effectively select and train negative samples in a contrastive learning framework, thereby deeply improving performance in contrastive learning task. Finally, we combine and jointly train the recommendation task and the curriculum learning contrastive learning task for optimization based on a multi-task learning strategy to further improve the recommendation performance. Experiments on real-world datasets show that EGDLTP-CCL significantly outperforms state-of-the-art methods. Full article

Background: To provide effective mental health care across cultural differences, therapists must develop cultural competencies, including an awareness of and sensitivity to diverse backgrounds. In Israel, secular therapists (STs) working with ultra-orthodox (UO), also referred to as Haredi, clients face challenges due to mutual distrust and sociopolitical tensions between the communities. This study aims to assess Israeli STs’ cross-cultural competencies and attitudes toward Haredi clients, examining the association between perceptions and competencies. Methods: The data were collected from an anonymous, self-administered online survey conducted between April and November 2024 among 70 STs in Israel. The study utilized the Cross-Cultural Competence of Healthcare Professionals (CCCHP-27) scale and a self-developed questionnaire assessing STs’ attitudes toward UO clients. The statistical analysis was performed using JASP 0.18.3. Results: While STs exhibited high general cross-cultural competence, their competence in working with Haredi clients was lower and more complex. Therapists with more experience treating UO clients had more positive attitudes toward them, whereas those working in public settings demonstrated lower cultural awareness. Although STs faced cultural and ideological challenges, many expressed openness and professional growth. Notably, while 57.2% felt that working with UO clients improved their skills, only 37.2% recommended it to others. Similarly, while 52.8% enjoyed working with diverse clients, only 27.2% reported enjoying working with UO clients. A negative correlation was found between the emotions about minorities scale and two UO-related subscales, views (ρ = −0.307, p = 0.01) and awareness (ρ = −0.534, p < 0.001), suggesting that local sociopolitical factors influence attitudes toward the Haredi community. Conclusions: This study highlights a gap between STs’ general cross-cultural competencies and their attitudes toward the Haredi population. The findings underscore the need for continued professional training in culturally competent therapy, as personal interactions play a crucial role in bridging societal divides and improving therapeutic relationships. Full article

Underwater polarization imaging has emerged as a fundamental technique for detecting and imaging underwater targets. However, the effectiveness of this technique is hampered by the low light intensity and optical system deformation induced by water pressure in deep-water environments, particularly for the detection of polarized signals. To address this issue, a wide-field-of-view oil-immersion lens tailored for deep-sea operations is designed, offering robust imaging performance and an extensive observation range. A Mueller matrix is deployed to scrutinize the polarization properties of the entire optical system across diverse fields of view, and the measurement errors in the polarization degree under incident polarization states are discussed. Simulation results demonstrate that the measurement error for linearly polarized light is greater than that for circularly polarized light. Therefore, the system adopts circularly polarized light as the active illumination source, characterized by minimal polarization effects and high detection accuracy. Finally, a deep-sea camera lens is produced and manufactured. The resulting lens is shown to pass a test in a hydrodynamic simulator machine, demonstrating that it can operate properly and capture images. Full article

People are less likely to help others when they view time as a scarce resource. Does changing people’s perception of time influence their willingness to help? We hypothesized that people would be more willing to help and would allocate more time to helping others when they view time as a nonzero-sum resource (i.e., as a resource that merely exists or that can be created moment-by-moment with their interactions with others) versus a zero-sum resource (i.e., a commodity that can be lost, taken, or given away). Study 1 measured people’s perception of time and their willingness to help in hypothetical vignettes. Studies 2 and 3 manipulated the perception of time to examine its effect on people’s willingness to help others and the amount of time they wanted to spend helping. Study 3 further examined prosocial motivation as a potential mediator. Across the three studies, we demonstrated that when people perceive time as a nonzero-sum resource versus a zero-sum resource, people are more willing to help others. People’s prosocial motivation to reduce others’ distress mediated this relationship. We speculate that when people perceive time to be nonzero-sum, time spent helping others is not viewed as costly, but as a resource to invest in to benefit both themselves and others. Full article