Pressure-driven flavor formation in rapeseed oil: an integrated multi-omics approach.

China’s coastal zone shifts from land-dependent to green and sustainable development

Urban expansion and population pressure have accelerated and Land Use and Land Cover (LULC) changes, leading to degradation of vegetation and aquatic ecosystems. This research aims to analyze the spatiotemporal dynamics of Normalized Difference Vegetation Index (NDVI) and LULC pattern changes and how they affect urban area transformation and offensive land use for various endeavors in the contexts of Habiganj Sadar and Madhabpur in Sylhet, Bangladesh, from 1989 to 2024. Using multitemporal Landsat satellite imagery, LULC was classified into groups such as vegetation, urbanized regions, aquatic environments, and barren terrain. NDVI values, which ranged from −0.23 to 0.81, were used as indices to assess vegetative health. Overall classification accuracy varied between 86% and 92.5%, with Kappa coefficients ranging from 0.80 to 0.93. Destruction of the environment is the result of a substantial reduction in vegetation in the Madhabpur area (31.91% to 7.43%), as well as Habigonj Sadar (18.99% to 8.71%). The fast urbanisation is prompted by the overcrowding in the Habigonj Sadar (1.82% to 21.08%) and Madhabpur (1.80% to 16.33%) settlement regions. Madhabpur's water body experienced terrible environmental circumstances between 1989 and 2024, falling from 30.41 sq. km to 5.60 sq. km. The data show a significant loss in vegetation health, as demonstrated by a drop in NDVI values from 0.78 in 1989 to 0.43 in 2024, coinciding with an increase in settlement areas from 1.82% to 21.08% in Habiganj Sadar and 1.80% to 16.33% in Madhabpur. This paper demonstrated the pattern of urban expansion coincides with a dramatic decline in both vegetation and aquatic bodies.

In CO2-enhanced coalbed methane recovery (i.e., CO2-ECBM), the selection of CO2 injection timing is pivotal for maximizing methane (i.e., CH4) recovery while preventing premature CO2 breakthrough. This study constructs fully coupled thermal–hydrological–mechanical–chemical (i.e., THMC) models to assess the impacts of different CO2 injection timings on the CO2-ECBM process, using the Panyi Coal Mine (Huainan, China) as a case study. Primary recovery and CO2-ECBM recovery are compared, and the evolution of reservoir permeability under different CH4 extraction strategies is emphasized. Results show that CO2 injection markedly increases CH4 recovery, elevating the peak daily CH4 production from 167.73 m3/d to 921.35 m3/d. The optimal CO2 injection initiation occurs after the drainage and depressurization phases, which circumvents inefficient early injection and yields higher injection rates compared to immediate injection. Both cumulative CH4 production and CO2 storage volume display a linear correlation with the injection timing. Initial reservoir water saturation restricts CH4/CO2 migration, while CH4 desorption and elevated injection pressure improve permeability contrasting with the permeability reduction induced by CO2 adsorption and associated thermal release. Permeability evolution is driven by strains from gas adsorption and desorption, thermal expansion, volumetric changes, and gas pressure. CO2 injection shortens the pore pressure-dominated phase and intensifies the role of adsorption/desorption strains in porosity variation. For delayed injection, the swelling strain from CO2 adsorption must first offset the shrinkage strain from CH4 desorption before the porosity declines. These insights contribute to optimizing CO2-ECBM operations and enhancing CO2 sequestration efficiency.

Against the backdrop of global warming, changes in the frequency and intensity of freeze–thaw cycles in cold regions profoundly impact soil physical structure. This review examines the mechanisms by which freeze–thaw cycles influence soil aggregate stability and pore structure evolution, focusing on revealing their synergistic evolution patterns. Results indicate that ice crystal growth during freeze–thaw processes directly disrupts soil cementation systems through expansion pressure and wedging effects, leading to aggregate disintegration and pore restructuring. This process is not unidirectional but forms a coupled feedback cycle of “ice crystal action–aggregate disintegration–pore restructuring.” Aggregate stability governs the initial pore restructuring, while the pore structure, in turn, influences aggregate stability by regulating water migration and colloidal dynamics. Responses of soil aggregates and pore structures to freeze–thaw cycles are comprehensively regulated by multiple factors, including soil physicochemical properties, freeze–thaw parameters, and anthropogenic disturbances. This synergistic evolution mechanism profoundly impacts soil water and heat transport, nutrient cycling, and erosion resistance. The paper also identifies current research gaps in regional coverage, cross-scale coupling, and in situ monitoring techniques. It envisions future efforts integrating multi-scale observations with intelligent technologies to deepen understanding of freeze–thaw-driven soil structure evolution mechanisms, thereby providing theoretical support for sustainable agriculture and ecological conservation in cold regions.

This study explores a variety of mountain settlements and stress-strain problems caused by tunnels passing through mountain fault zones. Based on the research background of the Lianfeng Mountain tunnel project, the expansion pressure of the rock mass was introduced through the Kastner formula using ABAQUS finite element simulation software. A mountain structure model was established, and the structural stress state of the mountain after tunnel excavation and the stability law of the secondary lining were studied. The results showed that for the double-layer steel frame, the inner steel frame of the tunnel bore more stress. In the normal section, the settlement of the tunnel vault was similar to the amount of bottom uplift. However, in the broken section, the settlement of the vault was significantly greater than the amount of bottom uplift. The excavation of the second tunnel during the construction of the double tunnel caused the strain in the first tunnel to increase. This study provides a theoretical reference for the safety analysis of similar mountain tunnels.

Under the dual pressures of climate change and intensive urban expansion, which jointly exacerbate urban heat risks, optimizing the urban thermal environment through vegetation has become a core pathway for climate adaptation. However, accurately quantifying the nonlinear cooling responses of vegetation under complex urban morphologies and diverse geomorphic conditions remains a major scientific challenge in achieving efficient heat-resilient urban planning. This study takes three representative megacities in China—Beijing, Shanghai, and Shenzhen—as case studies. By integrating multi-source datasets, an urban spatial morphology indicator system was constructed that encompasses key dimensions of the natural environment, urban morphology, and socioeconomic factors. Eleven machine learning models were applied to model and compare urban land surface temperature (LST). The results demonstrate that the CatBoost model exhibited superior performance in simulating complex urban thermal environments (R2 = 0.683–0.873), effectively capturing the interactive effects among multidimensional factors. The findings reveal a dual differentiation pattern of “topographic constraint–morphological dominance” in urban thermal environments: in mountainous cities, elevation and mountain forests act as rigid cooling barriers that restrict the spread of heat islands; whereas in plain cities, thermal conditions are primarily governed by the synergistic warming effects of impervious surface expansion and intensive human–economic activities. More importantly, the study identifies a significant nonlinear threshold effect of vegetation cover (NDVI) on LST reduction—only when vegetation coverage exceeds a critical threshold can large-scale cooling benefits be activated to effectively offset the thermal accumulation associated with high GDP intensity. Based on these insights, the study proposes differentiated climate-adaptive spatial planning strategies: mountainous cities should strictly maintain ecological redlines at mountain fronts to safeguard macro-scale cooling sources, while high-density plain cities should focus on integrating green space patches to surpass the “cooling threshold” and enhance vertical greening systems. These findings provide a quantitative scientific basis for improving urban thermal resilience.

This contribution presents the current distribution of snow leopards across Mongolia and summarises the proposed national IUCN Red List range map. It reviews findings from the nationwide occupancy and density assessment to describe current understanding of population status. The chapter outlines key threats, including habitat fragmentation, livestock-related conflict, prey decline, infrastructure expansion, and climate pressures. It concludes with an overview of current conservation efforts in Mongolia.

Purpose This study aims to investigate the macroeconomic determinants that influence housing prices in Malaysia and Singapore, two Southeast Asian economies with distinct policy frameworks and housing market characteristics. The research seeks to identify both short-run and long-run dynamics that shape housing market behaviour and to provide comparative insights for policymakers and investors. Design/methodology/approach Quarterly time-series data from 2000 to 2024 are analysed using the Autoregressive Distributed Lag (ARDL) bounds testing approach to cointegration and the error correction model (ECM). The Granger causality test is used to determine the direction of relationships among variables. Housing price index (HPI) serves as the dependent variable, while gross domestic product (GDP), inflation (CPI), interest rate, unemployment rate and money supply (M3) act as the explanatory variables. Findings The empirical results indicate that both economies exhibit long-run cointegration among housing prices and the selected macroeconomic variables. Money supply and GDP growth emerge as dominant long-run drivers in both countries, while inflation and interest rates show mixed short-run effects. Singapore demonstrates a stronger feedback mechanism between housing prices and macroeconomic indicators, whereas Malaysia’s housing market appears more sensitive to monetary expansion and inflationary pressures. Research limitations/implications The findings highlight the need for coherent macroeconomic and housing policies. For Malaysia, stabilising money supply growth and enhancing income dynamics are vital to moderating housing price escalation. In Singapore, maintaining policy coordination between monetary and housing supply instruments remains key to ensuring market stability. Originality/value This study offers one of the few comparative empirical analyses of housing price determinants in Malaysia and Singapore using ARDL and Granger causality. The study contributes to the limited Southeast Asian literature by integrating macroeconomic theory with real estate market evidence to guide housing policy and investment strategies.

Foreign expansion pressure in the digital era: online media-based institutional pressure and internationalization

This paper examines the urgent need for integrated resource mapping to protect the livelihoods of Hunter-Gatherer (H&G) communities in northern Tanzania amid the escalating impacts of climate change. Focusing on the Akie and Hadzabe peoples residing in Manyara Region, the study employs ethnographic observation, focus group discussions, and participatory geographical information systems to analyze land use patterns and climate dynamics. Findings reveal that climate change, coupled with increased agricultural expansion and population pressures, has significantly disrupted traditional H&G mobility, resource access, and cultural practices. Once mobile communities reliant on hunting, honey, fruits, and roots are now increasingly confined to smaller areas, with women and children especially burdened by the search for diminishing resources. The shift from bushland and grassland to agriculture has degraded wildlife habitats, reduced beehive trees, and fueled land use conflicts with neighbouring pastoral and farming groups. These changes threaten not only the food security and cultural identity of H&G communities but also their very survival. The paper argues that current village-based land use plans are insufficient and sometimes exacerbate conflicts. It recommends that integrated resource mapping, which considers traditional livelihood routes and resource zones beyond administrative boundaries, is essential for safeguarding the rights and livelihoods of H&G communities and ensuring sustainable co-existence with other land users in the region.

The growing pressures of population expansion, resource depletion, and climate change are intensifying global challenges in health, food security, and environmental sustainability. Amyloid-based materials offer valuable and sustainable solutions for addressing these issues to achieve a healthier planet due to their controllable structure, exceptional adhesion stability, high mechanical robustness, and excellent environmental compatibility. This review summarizes recent advances in amyloid-based biomaterials with relevance to global health, food, agriculture, and environmental systems. We first discuss the structural characteristics and fabrication strategies of conventional amyloid fibrils and their derived materials. We then introduce a superfast amyloid-like protein aggregation strategy that enables rapid formation of robust protein films and higher-order architectures. Applications of these materials include wound healing and tissue regeneration, stabilization and protection of food systems, enhanced utilization of fertilizers and pesticides, and removal of pollutants from water. Together, these developments highlight the growing potential of amyloid-inspired assemblies as sustainable and scalable platforms for promoting human well-being and environmental resilience.

Monitoring temperature and pressure in harsh environments is vital for industrial applications. This study presents a comprehensive multiphysics analysis and simulation of wireless passive temperature and pressure sensors, providing a feasible research framework for accurate simulation model development tailored to these devices and applications. The analysis focuses on evaluating the electromagnetic-thermal-mechanical coupling effects and improving the accuracy of sensor modeling under extreme environments. In particular, multiphysics simulations are performed on a pressure sensor that incorporates structural deformations induced by thermal expansion and external pressure. Comparison with available experimental data demonstrates significantly enhanced accuracy compared with conventional simple models, yielding a resonance frequency deviation of 0.32% (vs. 2.65%) and an error in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$S\_{11}$</tex-math></inline-formula> parameter estimation of 13.15% (vs. 101.92%) relative to measurements. These findings underscore the importance of accounting for multiphysics coupling in sensor design and provide insights for performance optimization in harsh environments.

This study examines urban–water synergy as the spatial coordination between urban expansion and water systems. Using land-use data from 2000 to 2020, the central urban areas of Jingzhou and Anqing are analyzed as representative small and medium-sized cities. Urban–water synergy is assessed across three dimensions: land-use synergy, pathway synergy, and directional synergy. These dimensions are quantified using four indicators: Urban–Water Interaction Intensity (UWII), Urban–Water Interaction Displacement (UWID), Spatial Path Alignment Distance (SPAD), and Directional Alignment Angle (DAA). The results show that Jingzhou and Anqing exhibit two distinct urban–water synergy modes: a convergent interaction mode characterized by increasing alignment in land-use interactions, spatial pathways, and directional tendencies, and a divergent synergy mode characterized by persistent separation across these dimensions. Differences between these synergy modes are associated with expansion pressure, physical template, and institutional mechanisms. Spearman rank correlation and principal component analysis suggest that institutional mechanisms constitute an independent analytical dimension and may be relevant for interpreting potential non-linear changes in urban–water interaction patterns. Based on these findings, this study discusses governance implications centered on institutional effectiveness, supported by spatial restoration and expansion regulation, for informing urban–water synergy governance in small and medium-sized cities.

Using a blend of aeolian and basalt sands as fine aggregate in concrete not only mitigates the reliance on river sand in Inner Mongolia but also aligns with China’s dual-carbon strategy. This study investigates the effects of mixed sand on concrete performance and elucidates the underlying mechanisms through laboratory-based physical experiments conducted under varying environmental conditions, with concurrent analysis of its carbon emissions. The findings demonstrate that incorporating mixed sand fine aggregates reduces the interaction effects among individual aggregate particles, facilitates the formation of a more compact internal packing structure within the concrete matrix, and consequently enhances its structural density. Furthermore, the combined particle morphology and surface roughness characteristics of basalt sand optimize its bonding performance with cement paste and the interlocking effects between aggregates, resulting in a remarkable improvement in the overall strength and stability of concrete. These enhancements enable concrete to better withstand freeze–thaw expansion and crystallization pressures, thereby increasing durability under sulfate freeze–thaw, wet–dry cycles, and their combinations. The model analysis shows that the mixed sand can significantly improve the durability of concrete, especially in the sulfate-freeze–thaw and dry–wet coupling environment. Mechanism analysis reveals that the dry–wet cycle is the dominant factor in the degradation process, while an increased aeolian sand replacement rate facilitates a continuous reduction in carbon emissions. Studies have confirmed that the 1:1 compounding ratio can synergistically optimize cost effectiveness and environmental sustainability, and provide high-quality green composite fine aggregates for low-carbon concrete.

The accelerating diffusion of artificial intelligence is reshaping production systems, energy efficiency, and environmental outcomes in advanced economies. However, the environmental consequences of AI-driven technological progress remain theoretically ambiguous, particularly within high-income, energy-intensive contexts. This study re-examines the dynamic relationship between artificial intelligence innovation and carbon dioxide emissions in the United States within an extended STIRPAT framework incorporating economic growth, energy consumption, foreign direct investment, and urbanization over the period 1990 to 2022. Employing the autoregressive distributed lag approach to capture both long-run equilibrium relationships and short-run adjustments, the results confirm the existence of cointegration among the variables. The long-run estimates reveal that artificial intelligence innovation significantly reduces carbon emissions, suggesting that efficiency gains and technological optimization effects outweigh scale expansion pressures. In contrast, economic growth, energy consumption, foreign direct investment, and urbanization exert upward pressure on emissions, highlighting persistent structural carbon intensity in the U.S. economy. Robustness checks using fully modified ordinary least squares, dynamic ordinary least squares, and canonical cointegrating regression validate the stability of the findings. The evidence supports the view that innovation-driven digital transformation can function as a decarbonization instrument when embedded within supportive energy and industrial policies. These findings offer important implications for climate strategy, technological governance, and sustainable growth pathways in advanced economies.

Non-performing loans (NPLs) represent a critical challenge to financial stability across nine emerging economies in Asia and Africa, where rapid credit growth, macroeconomic, and institutional volatility reinforce systemic risks. This study investigates the determinants of NPLs by employing a novel hybrid methodology integrating Panel ARDL estimation to identify long-run equilibrium, short-run relationships along with checking robustness through Fixed Effect and Random effect, and SHAP (SHapley Additive exPlanations) machine learning analysis for predictive feature importance and non-linear insights, moving beyond traditional approaches. Our findings reveal a complex interplay of factors, with distinct regional patterns. In Asia, NPLs are primarily driven by trend-following credit expansion and inflationary pressures, consistent with the Financial Accelerator mechanism. In Africa, macroeconomic instability, particularly high interest rates, and weak institutional frameworks are the dominant predictors, aligning with Institutional and Credit Rationing theories. The SHAP analysis corroborates these results, identifying bank credit and domestic credit as top global predictors, while highlighting regional asymmetries: inflation and regulatory quality are paramount in Asia, whereas interest rates and macroeconomic shocks generate higher predictive variance in Africa. Based on these insights, we propose distinct policy frameworks:Asia requires countercyclical credit regulations and sector-sensitive capital distribution, while Africa needs institutional reforms focused on collateral registries and interest rate stabilization, with simulations indicating potential NPL reductions. Our research emphasizes that NPLs are a macro-institutional challenge, necessitating integrated, region-specific strategies for financial stability.

In order to prevent the natural gas hydrate form in residual pressure utilization system, an analysis model for hydrate inhibitor injection in the system is proposed in this article. The novel model is fitted by 84 sets of experimental data on natural gas water content, and obtained by the least squares (Levenberg-Marquardt algorithm). The model includes two segments: higher than 0 °C and lower than 0 °C. Percentage deviation and average absolute deviation are used as evaluation criteria for the calculation of water content of eight different natural gas mixtures. The novel model is compared with other water content models and demonstrates high accuracy. Finally, this article calculates the injection rate of inhibitor (ethylene glycol) by varying expansion ratio, pressure, temperature and flow using the proposed model, and compared the results with the Zhulin model and simulation software. The results show that the injection rate calculated by proposed model are closer to the simulation software at expansion ratios between 1.4 and 1.9. With increasing injection inlet temperature, the results are within the error band, while the Zhulin model’s fall outside. Ethylene glycol injection rate is linear with natural gas flow. Overall, the novel model has higher accuracy.

The paper presents an integrated study of controlled directional splitting of monolithic materials driven by soundless chemical demolition agents, in which controlled lateral compression is introduced as an additional governing parameter. We treat the process as a superposition of two fields: the slowly rising expansive pressure inside the borehole, generated by hydration of the mixture, and a quasi-static compressive field uniformly applied to the specimen faces. In this setting, the crack path is dictated not only by local stress concentration near the borehole wall but also by the consistency of boundary conditions with the design splitting plane. The aim is to qualitatively identify ranges in which inter-borehole spacing can be increased without losing crack controllability thanks to moderate lateral compression. The programme is arranged as a parametric study on alabaster prisms; borehole geometry and layout as well as the level of distributed face loading were varied. Baseline drilling parameters were pre-aligned with energy-based criteria for brittle fracture to ensure reproducible initiation. Crack behaviour was assessed by mapping the deviation of the actual split line from the design line along gauge segments. Findings show that even moderate compression planarises the fracture front, suppresses unwanted branching, and reduces edge effects and material heterogeneities. Increasing confinement further stabilises the process, shaping an energetically favourable path within the design plane and broadening the range of rational spacings. A synergy between borehole layout and lateral compression is observed: a suitable choice of diameter, depth, orientation and spacing, combined with uniform pressing, preserves block integrity and improves split surface quality. Practical implications include optimising drilling costs while retaining predictability in vibration- and noise-sensitive environments. Guidance is provided on fixture stiffness, mixture temperature control and loading synchronisation; limitations and a pathway to industrial scaling are outlined.

Abstract Thermal expansion rubber is often used as the mold material in the thermal expansion molding process of composite materials, and has been widely used in thermal expansion molding, soft mold-assisted RTM, airbag-assisted RTM, and other molding processes. At present, the process parameters, such as the pressure value, thickness and clearance of thermal expansion rubber during molding, are determined by theoretical estimation and process test. In order to systematically study the pressure loading law of thermal expansion rubber, this paper uses a push-pull meter to calibrate the high-temperature film pressure sensor at room temperature and high temperature. The calibrated high-temperature film pressure sensor is used to accurately test the thermal expansion pressure of silicone rubber with different thicknesses, and the linear pressure loading law of thermal expansion rubber is obtained. Under the same process gap, the thermal expansion pressure is linearly related to the rubber thickness. The thermal expansion pressure of 6.0 mm, 4.5 mm, and 3.0 mm thermal expansion silicone rubber at 180 °C is about 0.27 MPa, 0.17 MPa, and 0.05 MPa, respectively, which provides data support for the application of thermal expansion rubber in composite molding.