Search Results (2,049)

The rational utilization of cultivated land resources is central to ensuring both ecological and food security in the Yangtze River Economic Belt (YREB), holding strategic significance for regional sustainable development. Using panel data from 2010 to 2023 for 130 cities in the YREB, this study examines a spatial correlation network (SCN) for non-grain land use (NGLU) and its driving forces via a modified gravity model, social network analysis (SNA), and quadratic assignment procedure regression. The results show the following: (1) The risk of NGLU continues to increase, with the spatial pattern evolving from a “single-peak right deviation” pattern to a “multi-peak coexistence” pattern featuring three-level polarization and gradient transmission, primarily driven by economic potential disparities. (2) The SCN has increased in density, but its pathways are relatively singular. Node functions exhibit significant differentiation, with high-degree nodes forming “control poles”, high-intermediate nodes dominating cross-regional risk transmission, and low-proximity nodes experiencing “protective marginalization”. Node centrality distribution is highly connected with the regional development gradient. (3) The formation of the spatial network is jointly driven by multiple factors. Geographical proximity, economic potential differences, comparative benefit differences, non-agricultural employment differences, and factor mobility all positively contribute to the spillover effect. Conversely, implementing cultivated land protection policies and the regional imbalance in local industrial development path dependence significantly inhibit the non-grain trend. This study further reveals that a synergistic governance system characterized by “axial management, node classification, and edge support” should be recommended to prevent the gradient risk transmission induced by economic disparities, providing a scientific basis for achieving sustainable use of regional cultivated land resources and coordinated governance of food security. Full article

The six-degree-of-freedom (6-DoF) interaction forces/torque of the tool-end play an important role in the robotic tool manipulation using a gripper, which are usually indirectly measured by a robot wrist force/torque sensor. However, the real-time decoupling of the tool’s inertial force remains a challenge when different tools and grasping postures are involved. This paper presents a universal tool-end interaction forces estimation approach, which is capable of handling diverse grippers and tools. Firstly, to address uncertainties from varying tools and grasping postures, an online-identifiable tool dynamics model was built based on the Newton–Euler approach for the integrated gripper–tool system. Sensor zero-drift caused by factors such as the tool weight and prolonged operation is incorporated into the dynamic model and identified online in real time, enabling a coarse estimation of the interaction forces. Secondly, a spiking neural network (SNN) is specially employed to compensate for uncertainties caused by the wrist sensor creep effect, since its temporal processing and event-driven characteristics match the time-varying creep effects introduced by tool changes. The proposed method is experimentally validated on a robotic arm with a gripper, and the results show that the root mean square errors of the estimated tool-end interaction forces are below 0.5 N with $x$, $y$, and $z$ axes and 0.03 Nm with ${\tau }_x$, ${\tau }_y$, and ${\tau }_z$ axes, which has a comparable precision with the in situ measurement of the interaction forces at the tool-end. The proposed method is further applied to robotic scraper manipulation with impedance control, achieving the interaction forces feedback during compliant operation precisely and rapidly. Full article

Atmospheric aerosols are known to alter the Earth’s radiative balance and influence climate. However, accurately quantifying the magnitude of aerosol-induced radiative forcing remains challenging. We characterize optical properties of biomass-burning (BB) and non-biomass-burning (NB) aerosols and quantify BB aerosol radiative forcing at two AERONET (AErosol RObotic NETwork) sites in Huancayo (Peru) and La Paz (Bolivia) during 2015–2021. From AERONET data, we derive aerosol optical depth (AOD), Ångström exponent (AE), single-scattering albedo (SSA), and asymmetry parameter (ASY). We then employ the SBDART model to calculate aerosol radiative forcing (ARF) on monthly and multiannual timescales. BB aerosols peak in September (AOD: 0.230 at Huancayo; 0.235 at La Paz), while NB aerosols reach maxima in September at Huancayo (0.109) and November at La Paz (0.104). AE values exceeding unity for BB aerosols indicate fine-mode dominance. Huancayo exhibited the highest BB ARF in November: +16.4 W m⁻² at the top of the atmosphere (TOA), –18.6 W m⁻² at the surface (BOA), and +35.1 W m⁻² within the atmospheric column (ATM). This was driven by elevated AOD and high scattering efficiency. At La Paz, where SSA data was only available for September, BBARF values were also significant (+15.16 at TOA, –17.52 at BOA, and +32.73 W m⁻² within the ATM). This result underscores the importance of quantifying the ARF, particularly over South America where data is scarce. Full article

The geometric content of chaos in nonlinear systems with multiple stabilities of high order is a challenge to computation. We introduce a single algorithmic framework to overcome this difficulty in the present study, where a parametrically forced oscillator with cubic–quintic nonlinearities is considered as an example. The framework starts with the Sparse Identification of Nonlinear Dynamics (SINDy) algorithm, which is a self-learned algorithm that extracts an interpretable and correct model by simply analyzing time-series data. The resulting parsimonious model is well-validated, and besides being highly predictive, it also offers a solid base on which one can conduct further investigations. Based on this tested paradigm, we propose a unified diagnostic pathway that includes bifurcation analysis, computation of the Lyapunov exponent, power spectral analysis, and recurrence mapping to formally describe the dynamical features of the system. The main characteristic of the framework is an effective algorithm of computational basin analysis, which is able to display attractor basins and expose the fine scale riddled structures and fractal structures that are the indicators of extreme sensitivity to initial conditions. The primary contribution of this work is a comprehensive dynamical analysis of the DM-CQDO, revealing the intricate structure of its stability landscape and multi-stability. This integrated workflow identifies the period-doubling cascade as the primary route to chaos and quantifies the stabilizing effects of key system parameters. This study demonstrates a systematic methodology for applying a combination of data-driven discovery and classical analysis to investigate the complex dynamics of parametrically forced, high-order nonlinear systems. Full article

Driven by the dual-carbon goals, photovoltaic (PV) battery systems at renewable energy stations are increasingly clustered on the distribution side. The rapid expansion of these clusters, together with the pronounced uncertainty and spatio-temporal heterogeneity of PV generation, degrades battery utilization and forces conservative dispatch. To address this, we propose a “spatio-temporal clustering–deep estimation” framework for short-term interval forecasting of PV clusters. First, a graph is built from meteorological–geographical similarity and partitioned into sub-clusters by a self-supervised DAEGC. Second, an attention-based spatio-temporal graph convolutional network (ASTGCN) is trained independently for each sub-cluster to capture local dynamics; the individual forecasts are then aggregated to yield the cluster-wide point prediction. Finally, kernel density estimation (KDE) non-parametrically models the residuals, producing probabilistic power intervals for the entire cluster. At the 90% confidence level, the proposed framework improves PICP by 4.01% and reduces PINAW by 7.20% compared with the ASTGCN-KDE baseline without spatio-temporal clustering, demonstrating enhanced interval forecasting performance. Full article

This study investigates the influence of magnetic fields on the electrochemical corrosion behavior of aerospace-grade H62 brass alloy in 3.5 wt% NaCl solution and its underlying 10 mechanisms. Employing electrochemical testing techniques combined with surface characterization methods, we explored the effects of magnetic field intensity (25–100 mT) and orientation (parallel and perpendicular to electrode surface) on the corrosion kinetics and corrosion product evolution of H62 brass alloy. Results demonstrate that magnetic fields significantly accelerate the corrosion process of H62 brass alloy. Under parallel magnetic field (100 mT), the corrosion current density increased from 0.49 μA/cm² to 3.66 μA/cm², approximately 7.5 times that of the non-magnetic condition, while perpendicular magnetic field increased it to 1.73 μA/cm², approximately 3.5 times the baseline value. The charge transfer resistance decreased from 3382 Ω·cm² to 1335 Ω·cm². Magnetic field orientation determines the fundamental differences in corrosion acceleration mechanisms. Parallel magnetic fields primarily enhance mass transfer processes through Lorentz force-driven magnetohydrodynamic (MHD) effects, resulting in intensified uniform corrosion; perpendicular magnetic fields alter interfacial ion distribution through magnetic gradient forces, inducing localized corrosion tendencies. Magnetic fields promote the transformation of protective Cu₂O films into porous Cu₂(OH)₃Cl, reducing the protective capability of corrosion product layers. Full article

Recent frequent food safety incidents have heightened consumer concern about agricultural product traceability, driving companies to build more robust supply chain traceability systems. However, enhancing traceability level is not only driven by consumer preferences but is also profoundly shaped by supply chain power structures and coordination mechanisms. In this study, we investigate how consumer preferences, power structures, and contractual mechanisms jointly shape traceability investment and coordination in agricultural supply chains. Using a two-tier supplier–retailer game-theoretic model, we compare traceability levels, pricing, and profit allocation under three governance structures: vertical Nash, supplier-led, and retailer-led. We also evaluate the effectiveness of cost-sharing and revenue-sharing contracts. The results reveal several key insights. First, consumer preference for traceable products serves as a critical market-driven force that enhances traceability investment across supply chain tiers. Second, power structures fundamentally determine traceability outcomes through threshold-dependent mechanisms: when consumer preference is weak, vertical Nash structures yield superior traceability via balanced cost-sharing; however, once preference intensity surpasses critical thresholds, retailer-led structures dominate in responsiveness, profit distribution, and capability building. In contrast, supplier-led structures deliver the weakest outcomes, as concentrated cost burdens suppress investment incentives, particularly in supply chains composed of small and medium-sized suppliers. Third, coordination contracts exhibit structure-specific efficacy. Cost-sharing contracts achieve full optimization in vertical Nash contexts and yield Pareto improvements in supplier-led chains, whereas traditional contracts exert minimal influence in retailer-led settings. These findings enrich our theoretical understanding of traceability governance and provide practical guidance for differentiated traceability design and contract formulation. Full article

Hepatocellular carcinoma (HCC) is characterized by a complex disruption of hemostatic balance, increasing the risk of both thrombotic and hemorrhagic events. Thrombotic complications, most notably portal vein thrombosis (PVT) and venous thromboembolism (VTE), have a significant impact on clinical outcomes and therapeutic strategies. Cirrhosis contributes to the precarious equilibrium between pro- and anticoagulant forces through impaired synthesis of coagulation factors, endothelial dysfunction, and systemic inflammation. In the presence of HCC tumor-driven mechanisms, such as tissue factor expression, extracellular vesicle release, platelet activation, and suppression of fibrinolysis exacerbate this prothrombotic state. In this scenario, advanced diagnostic tools such as thrombin generation assay (TGA) and rotational thromboelastometry (ROTEM) offer a more accurate assessment of coagulation dynamics than conventional tests, enabling better risk stratification especially for therapeutic purposes. Anticoagulant therapy has demonstrated clinical benefit in selected cases of non-malignant PVT and VTE, particularly when liver function is preserved. While prophylactic strategies are still under investigation, data suggest they may be safely implemented in selected surgical patients. In the setting of immunotherapy, especially regimens involving anti-VEGF agents, anticoagulation may be considered with careful management of bleeding risk due to portal hypertension. An individualized approach to anticoagulation, supported by functional coagulation testing, is gaining acceptance as a means to safely reduce thrombotic burden and potentially improve outcomes in patients with HCC. Full article

To address challenges such as temperature rise, operational instability, and premature failure in rolling bearings caused by retainer friction, this study designed and developed a high-performance polyimide (PI)-based composite self-lubricating retainer to enable “ultra-stable” bearing operation. Both solid and oil-porous self-lubricating retainers were fabricated through material composition and structural design. Systematic tests under controlled load and speed conditions were conducted to compare their temperature rise behavior and wear morphology. The results demonstrated that the temperature rise in the YSU-PI1 bearing with a solid retainer decreased by approximately 57% compared to a conventional bearing. The YSU-PA2 bearing with an oil-porous retainer exhibited a further improvement in thermal performance. Notably, under high-speed conditions, the equilibrium temperature of the YSU-PA2 bearing was lower than that under low-speed conditions, confirming a centrifugal-force-driven self-regulating oil-supply mechanism. Wear surface analysis revealed that the porous structure promoted the formation of a continuous and uniform transfer film, effectively mitigating wear and pitting. This study successfully integrates “material–structure–function” innovation. The oil-porous PI-based composite retainer transforms centrifugal force—typically considered detrimental—into a beneficial lubrication mechanism, effectively suppressing temperature rise and enabling “ultra-stable operation”. These findings provide crucial theoretical and technical support for developing bearings for high-end equipment. Full article

The growing demand for safe and reliable weaponry has heightened performance requirements for explosives. Cocrystal systems, offering a balance between high energy density and safety, have become key targets in advanced energetic material research. However, the influence of molar ratios and crystal facets on thermal sensitivity, mechanical strength, and detonation properties remains underexplored. This study investigates cocrystals of hexanitrohexaazaisowurtzitane (CL-20) and 1,1-diamino-2,2-dinitroethylene (FOX-7) with molar ratios of 3:1, 5:1, and 8:1 on the (1 0 1) crystal facet, using the Forcite module in Materials Studio. Comparative analysis with (0 1 1) facet and pure explosives revealed that the 5:1 cocrystal achieved the highest cohesive energy density (0.773 kJ/cm³) and theoretical crystal density (1.953 g/cm³), driven by strong electrostatic and non-bonded interactions—indicating superior detonation performance. In contrast, the 3:1 cocrystal displayed optimal mechanical strength, with an elastic modulus of 8.562 GPa and shear modulus of 3.365 GPa, suitable for practical applications. The results suggest increasing CL-20 content enhances energy performance up to a point, beyond which structural loosening occurs (8:1 ratio) due to steric hindrance weakening van der Waals forces. This work clarifies how molar ratio regulates the influence between sensitivity, strength, and energy, providing guidance for designing application-specific high-energy cocrystals. Full article

Self-oscillations convert ambient energy into continuous periodic motion through feedback mechanisms, but their response to external periodic disturbances is not yet fully understood. Through the combination of a photothermally-responsive liquid crystal elastomer fiber and a mass block within a linear light field, we consider a liquid crystal elastomer self-oscillator. Following theoretical modeling of the light-driven self-oscillator under external periodic forcing and numerical simulations, three distinct phase-locking regimes are identified: in-phase, anti-phase, and quadrature synchronizations. Mechanisms are elucidated through time-domain, frequency-domain, and phase-space analyses. Moreover, approximate analytical expressions for the steady-state amplitude–frequency and phase–frequency responses of the self-oscillator under periodic forcing are derived using the multi-scale method. The impact of periodic forcing on the self-oscillator and its response regulation via system parameters is examined. A close correspondence exists between numerical and analytical results. This work investigates the response characteristics of a liquid crystal elastomer self-oscillator under periodic forcing, advances fundamental insights into disturbance rejection in self-oscillators, and delivers practical guidance for their robust operation in complex oscillatory settings. Full article

The study is referenced by interdisciplinary theories, i.e., routine activity, and social cohesion, to investigate the impacts of sport clubs and events on London’s expressive crimes at varied geographical scales, by utilizing Geographical-temporally weighted regression model. It has identified the spatial patterns of effects from sport clubs’ onto local expressive crimes among London wards, with several boroughs standing out for their being significantly affected. The case study in the home borough of the Hotspur Football Club has further been conducted, by proving the seasonal influences of sports clubs on reducing youth violence within school terms. It was also found disproportional increases in expressive crimes on Premier League match days, especially when receiving the results of draw. The data-driven evidence has generated insights on localized policies and strategies on developing tailored sports to support local young people’s development; pinpointing the optimisation of police forces resources on stop and search practices during sports events in hot spot stadiums. The methodology and workflow had also been proved with high replicability into other UK cities. Full article

With billions of users worldwide, social media has become a powerful force in shaping lifestyle behaviors, including physical activity (PA), particularly among young adults. This narrative review examined the growing role of social media–driven interventions in promoting PA among young adults at risk of obesity. We analyzed the application of behavior change theories, including Social Cognitive Theory, the Theory of Planned Behavior, the COM-B, and specific behavior change techniques, alongside the role of intersectionality in shaping intervention effectiveness. Platform-specific strategies across Instagram, TikTok, YouTube, and Facebook were summarized, highlighting engagement mechanisms, personalized content delivery, and behavior change approaches that influence behavioral, physiological, and motivational outcomes. Despite these opportunities, challenges such as ethical concerns, misinformation, accessibility barriers, and quality control issues remained significant. Finally, future directions were outlined, including integration with wearables, AI-driven multi-platform strategies, co-designed interventions, and policy frameworks to optimize digital health promotion. In conclusion, social media offers considerable potential as a cost-effective, accessible tool for promoting PA and preventing obesity in young adults, though effectiveness is limited by misinformation, unregulated content, and poor quality control. Full article

Contemporary religiosity is undergoing profound transformation, shaped by postsecular and postmodern dynamics. Amid global declines in institutional affiliation, religious and spiritual tourism has emerged as a salient expression of evolving faith. Poland exemplifies this paradox: witnessing one of the world’s steepest declines in youth religiosity, even as Catholicism retains symbolic centrality. Drawing on survey data from 510 Polish young adults (Generation Z), this study examines how religiosity, faith-based travel, and social attitudes intersect within a postsecular framework. Findings reveal a dual trajectory: while religious tourism reinforces institutional belonging and traditional values, spiritual tourism aligns with individualized, fluid religiosity and looser ties to religious institutions. The study introduces a novel conceptual model mapping the interdependencies between religiosity, mobility, and identity among youth in postsecular societies. This framework demonstrates how faith-based travel actively mediates social attitudes and reconfigures religious engagement, positioning mobility as a generative force in shaping contemporary belief. Rather than following a linear path of secularization, Generation Z selectively blends inherited Catholic traditions with personalized, experience-driven spirituality. These findings advance sociological debates on secularization, postsecularism, and the transformation of religious identity through mobility. Full article

The Science and Technology Finance ecosystem plays an increasingly important role in shaping the sustainable development of new quality productive forces (NQPF). This study, based on the perspective of complex systems and using a multi-period fsQCA approach, takes 31 provinces, municipalities, and autonomous regions in mainland China as cases to analyze the relationship between the Science and Technology Finance ecosystem and NQPF from 2017 to 2022. The findings are as follows: first, the antecedent configurations of NQPF are multiple, with the variables of the Science and Technology Finance ecosystem jointly matching and working together to drive its development. Second, in 2017–2018, there were three configurations: the “Bank–Enterprise” collaborative-driven type, the Bank-led type, and the Enterprise-led type; in 2019–2020, there were three configurations: the “Bank–Enterprise” collaborative-driven type, the “Bank–Enterprise–Market” collaborative-driven type, and the “Enterprise–Market” collaborative-driven type; in 2021–2022, there was one configuration, namely the Multi-Actor collaborative-driven type. Third, the development of NQPF across the three stages underwent an evolution from being dominated by core financial resources, to coordinated driving by core finance and the market, and finally to multi-stakeholder collaborative promotion. Fourth, in the configurations where high-level NQPF was not achieved, insufficiency of Enterprise Self-owned Funds (ESOF) was identified as a common problem. These findings provide theoretical references and policy implications for optimizing the Science and Technology Finance ecosystem in line with local conditions. Full article