Search Results (631)

We present a comprehensive information-theoretic evaluation of three widely used rigid water models (TIP3P, SPC, and SPC/$\epsilon$) through systematic analysis of water clusters ranging from single molecules to 11-molecule aggregates. Five fundamental descriptors—Shannon entropy, Fisher information, disequilibrium, LMC complexity, and Fisher–Shannon complexity—were calculated in both position and momentum spaces to quantify electronic delocalizability, localization, uniformity, and structural sophistication. Clusters containing 1, 3, 5, 7, 9, and 11 molecules (denoted 1 M, 3 M, 5 M, 7 M, 9 M, and 11 M) were selected to balance computational tractability with representative scaling behavior. Molecular dynamics simulations validated the force fields against experimental bulk properties (density, dielectric constant, self-diffusion coefficient), while statistical analysis using Shapiro–Wilk normality tests and Student’s t-tests ensured robust discrimination between models. Our results reveal distinct scaling behaviors that correlate with experimental accuracy: SPC/$\epsilon$ demonstrates superior electronic structure representation with optimal entropy–information balance and enhanced complexity measures, while TIP3P shows excessive localization and reduced complexity that worsen with increasing cluster size. The transferability from clusters to bulk properties is established through systematic convergence of information-theoretic measures toward bulk-like behavior. The methodology establishes information-theoretic analysis as a useful tool for comprehensive force field evaluation. Full article

This letter aims to investigate thermodynamic processes in small systems in the Onsager region by showing that fundamental quantities such as total entropy production can be discretized on the mesoscopic scale. Even thermodynamic variables can conjugate to thermodynamic forces, and thus, Glansdorff–Prigogine’s dissipative variable may be discretized. The canonical commutation rules (CCRs) valid at the mesoscopic scale are postulated, and the measurement process consists of determining the eigenvalues of the operators associated with the thermodynamic quantities. The nature of the quantized quantity β , entering the CCRs, is investigated by a heuristic model for nano-gas and analyzed through the tools of classical statistical physics. We conclude that according to our model, the constant β does not appear to be a new fundamental constant but corresponds to the minimum value. Full article

To address the flood risks driven by climate change and urbanization, this study proposes the DRIRA model (Driving Force, Resistance, Influence, Recoverability, Adaptability). Distinct from BRIC (Baseline Resilience Indicators for Communities) and PEOPLES (Population, Environmental/Ecosystem, Organized Governmental Services, Physical Infrastructure, Lifestyle, Economic Development, Social–Cultural Capital), the model emphasizes dynamic interactions across the entire disaster lifecycle, introduces the “Influence” dimension, and integrates SNA (Social Network Analysis) with a modified gravity model to reveal cascading effects and resilience linkages among cities. Based on an empirical study of 30 cities in the Central Plains Urban Agglomeration, and using a combination of entropy weighting, a modified spatial gravity model, and social network analysis, the study finds that: (1) Urban flood resilience increased by 35.5% from 2012 to 2021, but spatial polarization intensified, with Zhengzhou emerging as the dominant core and peripheral cities falling behind; (2) Economic development, infrastructure investment, and intersectoral governance coordination are the primary factors driving resilience differentiation; (3) Intercity resilience connectivity has strengthened, yet administrative fragmentation continues to undermine collaborative effectiveness. In response, three strategic pathways are proposed: coordinated development of sponge and resilient infrastructure, activation of flood insurance market mechanisms, and intelligent cross-regional dispatch of emergency resources. These strategies offer a scientifically grounded framework for balancing physical flood defenses with institutional resilience in high-risk urban regions. Full article

The Yangtze River Delta (YRD) region has experienced rapid development in its tourism industry, establishing itself as a leading force within China’s tourism sector. However, significant regional disparities continue to hinder its sustainable development. This study adopts a mixed-methods approach to analyze the spatiotemporal evolution of domestic tourist flows and tourism industry agglomeration patterns in the region. Using city-level data from 2016 to 2022, the analysis employs a comprehensive methodology including standard deviation, coefficient of variation, standard deviation ellipse, and locational entropy. The main findings are as follows: (1) In the pre-pandemic period (2016–2019), absolute disparities in tourist flows widened, whereas relative disparities narrowed. During the pandemic (2020–2022), absolute disparities decreased, while relative disparities initially increased before contracting. (2) Tourist flows displayed a southeast–northwest gradient, with high-value areas clustered along the southeastern coast. Standard deviation ellipse analysis reveals that tourist flows were primarily distributed along the eastern coastal corridor, parallel to the coastline. Prior to the pandemic, tourism growth showed a tendency toward spatial equilibrium; however, this trend was disrupted during the pandemic, resulting in a more decentralized spatial pattern. (3) Throughout the pandemic, tourism industry concentration increased significantly in most cities. Cities with renowned scenic attractions and diversified economic structures demonstrated stronger resilience, while those heavily reliant on tourism were more vulnerable to the pandemic’s effects. Full article

One of the greatest quests in physics in current times is the search for a grand unified theory—to bring all the forces of nature into one coherent explanatory framework. Despite two centuries of progress, both in comprehending the individual forces and formulating mathematical constructs to explain the existence and operation of such forces, the final step to unify the localised atomic and subatomic forces with gravity has proven to be elusive. Whilst recognising that there are arguments for and against the unification of all the forces of nature, the pursuit for unity has been driving many physicists and mathematicians to explore increasingly extraordinary ideas, from string theory to various other options requiring multiple dimensions. Can process philosophy ride to the rescue? By changing our perspective, it might be possible to derive a provocative and compelling alternative way to understand basic (and advanced) physics. This process approach would see all matter objects, at whatever scale, as energetic systems (inherently dynamic). Through the use of game theory, there is a way to appreciate the combination of entropy together with all the apparent forces of nature, being gravity and the more localised forces, within a singular, metaphysically consistent, construct. The outcome, however, challenges our whole understanding of the universe and fundamentally changes our relationship with matter. Full article

Background: This study investigated sex differences in foot arch structure and function, and their impact on postural control and energy flow during dynamic tasks. Findings aim to inform sex-specific training, movement assessment, and injury prevention strategies. Methods: A total of 108 participants (53 males and 55 females) underwent foot arch morphological assessments and performed a sit-to-stand (STS). Motion data were collected using an infrared motion capture system, three-dimensional force plates, and wireless surface electromyography. A rigid body model was constructed in Visual3D, and joint forces, segmental angular and linear velocities, center of pressure (COP), and center of mass (COM) were calculated using MATLAB. Segmental net energy was integrated to determine energy flow across different phases of the STS. Results: Arch stiffness was significantly higher in males. In terms of postural control, males exhibited significantly lower mediolateral COP frequency and anteroposterior COM peak velocity during the pre-seat-off phase, and lower COM displacement, peak velocity, and sample entropy during the post-seat-off phase compared to females. Conversely, males showed higher anteroposterior COM velocity before seat-off, and greater anteroposterior and vertical momentum after seat-off (p < 0.05). Regarding energy flow, males exhibited higher thigh muscle power, segmental net power during both phases, and greater shank joint power before seat-off. In contrast, females showed higher thigh joint power before seat-off and greater shank joint power after seat-off (p < 0.05). Conclusions: Significant sex differences in foot arch function influence postural control and energy transfer during STS. Compared to males, females rely on more frequent postural adjustments to compensate for lower arch stiffness, which may increase mechanical loading on the knee and ankle and elevate injury risk. Full article

This research investigates the potential of Seed Press Cake of Nigella sativa (SPCN) as a low-cost, eco-friendly biosorbent for the removal of the cationic dye Toluidine Blue (TB) from aqueous solutions. The physicochemical properties of the material were characterized using Fourier-transform infrared (FTIR) spectroscopy, nitrogen adsorption–desorption isotherms, and scanning electron microscopy (SEM). Adsorption performance was evaluated under varying conditions, with the process best described by the pseudo-second-order kinetic model and the Langmuir isotherm, indicating monolayer adsorption. The maximum adsorption capacity was determined to be 305 mg·g⁻¹ at 20 °C. Thermodynamic analysis revealed that the adsorption is spontaneous, exothermic, and entropy-driven. FTIR analysis indicated that TB interacts with SPCN primarily via physical interactions, including electrostatic attraction, van der Waals forces, and hydrogen bonding, without strong chemical bonding. These findings demonstrate the high potential of black cumin seed waste as a sustainable and efficient biosorbent for dye removal in wastewater treatment. Full article

Industrial control systems (ICS) are increasingly vulnerable to evolving cyber threats due to the convergence of operational and information technologies. This research presents a robust cybersecurity framework that integrates machine learning-based anomaly detection with advanced cryptographic techniques to protect ICS communication networks. Using the ICS-Flow dataset, we evaluate several ensemble models, with XGBoost achieving 99.92% accuracy in binary classification and Decision Tree attaining 99.81% accuracy in multi-class classification. Additionally, we implement an LSTM autoencoder for temporal anomaly detection and employ the ADWIN technique for real-time drift detection. To ensure data security, we apply AES-CBC with HMAC and AES-GCM with RSA encryption, which demonstrates resilience against brute-force, tampering, and cryptanalytic attacks. Security assessments, including entropy analysis and adversarial evaluations (IND-CPA and IND-CCA), confirm the robustness of the encryption schemes against passive and active threats. A hardware implementation on a PYNQ Zynq board shows the feasibility of real-time deployment, with a runtime of 0.11 s. The results demonstrate that the proposed framework enhances ICS security by combining AI-driven anomaly detection with RSA-based cryptography, offering a viable solution for protecting ICS networks from emerging cyber threats. Full article

Research on prestressed concrete cylinder pipes (PCCPs) has focused primarily on their failure mechanisms, monitoring methods, and the effectiveness of repairs. However, gaps in the study of damage risks associated with PCCPs remain. Based on existing relevant research, this study focused on analysing the uncertainties in the material production and manufacturing processes of PCCPs to assess their damage risk. The research employs onsite test data about the compressive strength of C55 concrete and the real prestressing force exerted on prestressed steel wires, utilising the measured compressive strength of the concrete core in PCCPs alongside the actual prestressing force applied to the steel wires. An inverse cloud generator was employed to obtain the expected value Ex, entropy En, and hyperentropy He of the characteristic numbers. These values are then combined with the forward cloud model in cloud theory to train random parameters. By combining cloud theory with the Monte Carlo method, a risk analysis model for PCCP pipelines was established. Using internal water pressure monitoring data from the Qiliqiao Reservoir to the Xiayi Water Supply Line in the South-to-North Water Diversion Project, along with relevant PCCP pipeline data, the failure probability of the PCCP pipeline was calculated. The reliability index of this pipeline section under 0.6 MPa loading was found to be 4.49, demonstrating the reliability of the PCCP pipeline in this section of the water supply line. Full article

In this study, aluminium matrix hybrid composites reinforced with boron carbide (B₄C) and silicon carbide (SiC) were fabricated using the direct hot-pressing technique under 35 MPa pressure at 600 °C for 5 min. Particle size distribution and scanning electron microscope analysis were conducted for the input powders. The microstructure, mechanical properties, and drillability of the fabricated composites were examined. As the SiC content increased, the density decreased, hardness improved, and transverse rupture strength declined. Drilling experiments were performed based on the Taguchi L₁₈ orthogonal array. The control factors included cutting speed (25 and 50 m/min), feed rate (0.08, 0.16, and 0.24 mm/rev), point angle (100°, 118°, and 136°), and SiC content (0%, 5%, and 10%). Quality characteristics such as thrust force, torque, surface quality indicators, diameter deviation, and circularity deviation were evaluated. The Taguchi method was applied for single-response optimization, while the Entropy-weighted, Taguchi-based CoCoSo method was used for multi-response optimization. Analysis of Variance was conducted to assess factor significance, and regression analysis was used to model relationships between inputs and responses, yielding high R² values. The optimal drilling performance was achieved at 50 m/min, 0.08 mm/rev, 136°, and 10% SiC, and the confirmation tests verified these results within the 95% confidence interval. Full article

To assist resource-based regions in overcoming the bottlenecks of industrial transformation and advancing high-quality development, this paper conducts an in-depth analysis of the internal mechanisms through which new quality productive forces contribute to high-quality development. Based on the construction of a measurement index system, a comprehensive measurement model is established, which includes three components: a coupling coordination degree model integrating the entropy method and grey relational analysis, an impact factor analysis model based on random effects Tobit regression, and a trend prediction model using the GM(1,1) approach. Taking Hebei Province as an example, an empirical analysis was conducted and relevant policy suggestions were proposed. The research findings are summarized as follows: (1) New quality productive forces promote high-quality development through driving, guiding, and synergistic mechanisms; (2) From 2013 to 2022, the coupling coordination degree across various cities in Hebei Province evolved from moderate imbalance to primary coordination, with the spatial pattern transitioning from “higher in the south and lower in the north” to a “central rise” phase, and finally to a stage of “all-round coordination”; (3) Forecast results indicate that inter-city coordination will continue to improve over the next five years; (4) Urbanization, scientific and technological innovation, and government intervention are identified as the core driving factors for promoting coordinated development. This study provides both theoretical methodological support and regional empirical evidence for the role of new quality productive forces in enabling high-quality development in resource-based regions. Full article

As Shared Autonomous Vehicles (SAVs) emerge as a transformative force in urban mobility, integrating them into dense, historic urban environments presents distinct spatial and planning challenges—such as narrow street patterns, irregular road networks, and the need to protect cultural heritage. This study investigates the spatial adaptability of SAVs in Suzhou old town, a representative example of East Asian heritage cities. To assess spatial readiness, a hybrid weighting approach combining the Analytic Hierarchy Process (AHP) and the Entropy Weight Method (EWM) is used to evaluate 22 spatial indicators across livability, mobility, and spatial quality. These weighted indicators are mapped using a spatial density analysis based on Point of Interest (POI) data, revealing urban service distribution patterns and spatial mismatches. Results show that “Accessibility to Transportation Hubs” receives the highest composite weight, emphasizing the priority of linking SAVs with existing subway and bus networks. Environmental comfort factors—such as air quality, noise reduction, and access to green and recreational spaces—also rank highly, reflecting a growing emphasis on urban livability. Drawing on these findings, this study proposes four strategic directions for SAV integration that focus on network flexibility, public service redistribution, ecological enhancement, and cultural preservation. The proposed framework provides a transferable planning reference for historic urban areas transitioning toward intelligent, human-centered mobility systems. Full article

The increasing frequency of extreme weather events and rapid urbanization has exacerbated pluvial flood risks, underscoring the urgent need to strengthen the assessment of pluvial flood resilience in China’s southwestern mountainous regions. Kunming—a plateau basin city—was selected as a case study, and an urban pluvial flood resilience assessment system was developed based on the DPSIR model. The analytic hierarchy process (AHP), entropy method, and game theory-informed combination weighting were applied to determine indicator weights, while the extension cloud model was utilized to quantitatively assess resilience evolution from 2013 to 2022. The results reveal that: (1) Kunming’s pluvial flood resilience experienced a clear three-stage evolution—initial construction (Level II), resilience enhancement (Level III), and resilience reinforcement (Level IV)—reflecting a transition from rudimentary resilience to advanced adaptive capacity; (2) the ranking of primary indicator weights is as follows: Driving Forces > Pressure > State > Response > Impact, with Flood Disaster Risk (P6), Flood Disaster Early Warning Capability (R1), and Topographic and Geomorphological Characteristics (P7) identified as key influencing factors; (3) marked disparities exist across the five dimensions: the Driving Forces dimension demonstrates increasing economic support; the Pressure dimension reflects structural vulnerabilities and climate variability; the State and Impact dimensions advance incrementally through policy implementation; and the Response dimension has substantially improved due to smart city technologies, although persistent gaps in inter-agency emergency coordination remain. This research offers a scientific basis for enhancing pluvial flood resilience in southwestern mountainous cities. Full article

Empirical research on the impact of the digital economy on sustainable development is hampered by severe methodological challenges. Discrepancies in the theoretical foundations and construction logic of measurement frameworks have led to diverse and often conflicting conclusions, hindering the systematic accumulation of knowledge. This study aims to address this critical gap by proposing a new, logically consistent measurement framework. To overcome the existing limitations, we construct a functional deconstruction framework grounded in General-Purpose Technology (GPT) theory and a “stock–flow” perspective. This framework deconstructs the digital economy into a neutral “digital infrastructure” (stock platform) and two forces reflecting its inherent duality: a “consumption force” (digital industrialization) and an “empowerment force” (industrial digitalization). Based on this, we develop a measurement system adhering to the principle of “logical purity” and apply a “two-step entropy weighting method with annual standardization” to assess 30 provinces in China from 2012 to 2023. Our analysis reveals a multi-scalar evolution. At the micro level, we identified four distinct provincial development models and three evolutionary paths. At the macro level, we found that the overall inter-provincial disparity followed an inverted U-shaped trajectory, with the core contradiction shifting from an “access gap” to a more profound “application gap.” Furthermore, the primary driver of this disparity has transitioned from being “empowerment-led” to a new phase of a “dual-force rebalancing.” The main contribution of this study is the provision of a new analytical tool that enables a paradigm shift from “aggregate assessment” to “structural diagnosis.” By deconstructing the digital economy, our framework allows for the identification of internal structural imbalances and provides a more robust and nuanced foundation for future causal inference studies and evidence-based policymaking in the field of digital sustainability Full article

Agriculture is fundamental to food security and environmental sustainability. Advancing its holistic ecological transformation can stimulate socioeconomic progress while fostering human–nature harmony. Utilizing provincial data from mainland China (2013–2022), this research establishes a multidimensional evaluation framework across four pillars: agricultural ecology, low-carbon practices, modernization, and productivity enhancement. Through comprehensive assessment, we quantify China’s low-carbon green agriculture (LGA) development trajectory and conduct comparative regional analysis across eastern, central, and western zones. As for methods, this study employs multiple econometric approaches: LGA was quantified using the TOPSIS entropy weight method at the first step. Moreover, multidimensional spatial–temporal patterns were characterized through ArcGIS spatial analysis, Dagum Gini coefficient decomposition, Kernel density estimation, and Markov chain techniques, revealing regional disparities, evolutionary trajectories, and state transition dynamics. Last but not least, Tobit regression modeling identified driving mechanisms, informing improvement strategies derived from empirical evidence. The key findings reveal the following: 1. From 2013 to 2022, LGA in China fluctuated significantly. However, the current growth rate is basically maintained between 0% and 10%. Meanwhile, LGA in the vast majority of provinces exceeds 0.3705, indicating that LGA in China is currently in a stable growth period. 2. After 2016, the growth momentum in the central and western regions continued. The growth rate peaked in 2020, with some provinces having a growth rate exceeding 20%. Then the growth rate slowed down, and the intra-regional differences in all regions remained stable at around 0.11. 3. Inter-regional differences are the main factor causing the differences in national LGA, with contribution rates ranging from 67.14% to 74.86%. 4. LGA has the characteristic of polarization. Some regions have developed rapidly, while others have lagged behind. At the end of our ten-year study period, LGA in Yunnan, Guizhou and Shanxi was still below 0.2430, remaining in the low-level range. 5. In the long term, the possibility of improvement in LGA in various regions of China is relatively high, but there is a possibility of maintaining the status quo or “deteriorating”. Even provinces with a high level of LGA may be downgraded, with possibilities ranging from 1.69% to 4.55%. 6. The analysis of driving factors indicates that the level of economic development has a significant positive impact on the level of urban development, while the influences of urbanization, agricultural scale operation, technological input, and industrialization level on the level of urban development show significant regional heterogeneity. In summary, during the period from 2013 to 2022, although China’s LGA showed polarization and experienced ups and downs, it generally entered a period of stable growth. Among them, the inter-regional differences were the main cause of the unbalanced development across the country, but there was also a risk of stagnation and decline. Economic development was the general driving force, while other driving factors showed significant regional heterogeneity. Finally, suggestions such as differentiated development strategies, regional cooperation and resource sharing, and coordinated policy allocation were put forward for the development of LGA. This research is conducive to providing references for future LGA, offering policy inspirations for LGA in other countries and regions, and also providing new empirical results for the academic community. Full article