Search Results (2,181)

Pork is a major global source of animal protein, and improving both its production efficiency and meat quality is a central goal in modern animal agriculture and food systems. This study investigated post-inflection-point growth patterns in two genetically distinct pig breeds—the lean-type Yorkshire pig (YP) and the fatty-type Qingyu pig (QYP)—with the aim of elucidating breed-specific characteristics that influence pork quality and yield. Comprehensive evaluations of carcass traits, meat quality attributes, nutritional composition, and gene expression profiles were conducted. After the growth inflection point, carcass traits exhibited greater variability than meat quality traits in both breeds, though with distinct patterns. YPs displayed superior muscle development, with the longissimus muscle area (LMA) increasing rapidly before plateauing at ~130 kg, whereas QYPs maintained more gradual but sustained muscle growth. In contrast, intramuscular fat (IMF)—a key determinant of meat flavor and texture—accumulated faster in YPs post inflection but plateaued earlier in QYPs. Correlation and clustering analyses revealed more synchronized regulation of meat quality traits in QYPs, while YPs showed greater trait variability. Gene expression patterns aligned with these phenotypic trends, highlighting distinct regulatory mechanisms for muscle and fat development in each breed. In addition, based on the growth curves, we calculated the peak age at which the growth rate declined in lean-type and fat-type pigs, which was approximately 200 days for YPs and around 270 days for QYPs. This suggests that these ages may represent the optimal slaughter times for the respective breeds, balancing both economic efficiency and meat quality. These findings provide valuable insights for enhancing pork quality through precision management and offer theoretical guidance for developing breed-specific feeding strategies, slaughter timing, and value-added pork production tailored to consumer preferences in the modern food market. Full article

Vegetation dynamics are complexly influenced by multiple factors such as climate, human activities, and topography. In recent years, the frequency, intensity, and diversity of human activities have increased, placing substantial pressure on the growth of vegetation. Arid and semi-arid regions are particularly sensitive to climate change, and climate change and large-scale ecological restoration have led to significant changes in the dynamic of dryland vegetation. However, few studies have explored the nonlinear relationships between these factors and vegetation dynamic. In this study, we integrated trend analysis (using the Mann–Kendall test and Theil–Sen estimation) and machine learning algorithms (XGBoost-SHAP model) based on long time-series remote sensing data from 2001 to 2020 to quantify the nonlinear response patterns and threshold effects of bioclimatic variables, topographic features, soil attributes, and anthropogenic factors on vegetation dynamic. The results revealed the following key findings: (1) The kNDVI in the study area showed an overall significant increasing trend (p < 0.01) during the observation period, of which 26.7% of the area showed a significant increase. (2) The water content index (Bio 23, 19.6%), the change in land use (15.2%), multi-year average precipitation (pre, 15.0%), population density (13.2%), and rainfall seasonality (Bio 15, 10.9%) were the key factors driving the dynamic change of vegetation, with the combined contribution of natural factors amounting to 64.3%. (3) Among the topographic factors, altitude had a more significant effect on vegetation dynamics, with higher altitude regions less likely to experience vegetation greening. Both natural and anthropogenic factors exhibited nonlinear responses and interactive effects, contributing to the observed dynamic trends. This study provides valuable insights into the driving mechanisms behind the condition of vegetation in arid and semi-arid regions of China and, by extension, in other arid regions globally. Full article

The Qinghai-Tibetan Plateau is one of the world’s most prominent biodiversity hotspots. Understanding the spatial patterns of ecological uniqueness in its plant communities is essential for uncovering the mechanisms of community assembly and informing effective conservation strategies. In this study, we analyzed data from 758 plots across 338 sites on the Qinghai-Tibetan Plateau. For each plot, the vegetation type was classified, and all plant species present, along with their respective abundance or coverage, were recorded in the database. To assess overall compositional variation, community β-diversity was quantified, while a plot-level approach was applied to determine the influence of local environmental conditions and community characteristics on ecological uniqueness. We used stepwise multiple regressions, variation partitioning, and structural equation modeling to identify the key drivers of spatial variation in ecological uniqueness. Our results show that (1) local contributions to β-diversity (LCBD) exhibit significant geographic variation—increasing with longitude, decreasing with latitude, and showing a unimodal trend along the elevational gradient; (2) shrubs and trees contribute more to β-diversity than herbaceous species, and LCBD is strongly linked to the proportion of rare species; and (3) community characteristics, including species richness and vegetation coverage, are the main direct drivers of ecological uniqueness, explaining 36.9% of the variance, whereas climate and soil properties exert indirect effects through their interactions. Structural equation modeling further reveals a coordinated influence of soil, climate, and community attributes on LCBD, primarily mediated through soil nutrient availability. These findings provide a theoretical basis for adaptive biodiversity management on the Qinghai-Tibetan Plateau and underscore the conservation value of regions with high ecological uniqueness. Full article

Promoting sustainable development requires a clear understanding of how short-term fluctuations in anthropogenic emissions affect urban environmental quality. This is especially relevant for cities experiencing rapid industrial changes or emergency policy interventions. Among key environmental concerns, variations in ambient pollutants like ozone (O₃) are closely tied to both public health and long-term sustainability goals. However, traditional chemical transport models often face challenges in accurately estimating emission changes and providing timely assessments. In contrast, statistical approaches such as the difference-in-differences (DID) model utilize observational data to improve evaluation accuracy and efficiency. This study leverages the synthetic difference-in-differences (SDID) approach, which integrates the strengths of both DID and the synthetic control method (SCM), to provide a more reliable and accurate analysis of the impacts of interventions on city-level air quality. Using Shanghai’s 2022 lockdown as a case study, we compare the deweathered ozone (O₃) concentration in Shanghai to a counterfactual constructed from a weighted average of cities in the Yangtze River Delta (YRD) that did not undergo lockdown. The quasi-natural experiment reveals an average increase of 4.4 μg/m³ (95% CI: 0.24–8.56) in Shanghai’s maximum daily 8 h O₃ concentration attributable to the lockdown. The SDID method reduces reliance on the parallel trends assumption and improves the estimate stability through unit- and time-specific weights. Multiple robustness checks confirm the reliability of these findings, underscoring the efficacy of the SDID approach in quantitatively evaluating the causal impact of emission perturbations on air quality. This study provides credible causal evidence of the environmental impact of short-term policy interventions, highlighting the utility of SDID in informing adaptive air quality management. The findings support the development of timely, evidence-based strategies for sustainable urban governance and environmental policy design. Full article

The Matra As–Sb deposit (Alpine Corsica, France) is hosted in the normal N–S trending Matra Fault. Sulfide minerals in ore consist of realgar, stibnite, and pyrite with minor orpiment and hörnesite. The gangue includes quartz, dolomite, and calcite. In this study, the microstructural analysis of selected ore samples has been combined with the geochemical characterization of the sulfides. The results depict a succession of events that record the evolution of the ore deposit related to fault movement. In the pre–ore stage, plumose, crustiform, jigsaw, and feathery textures of quartz testify to a short–lived boiling event. The mineral assemblage of the main–ore stage includes an Fe(–Zn) substage dominated by the formation of different textures of pyrite. In general, pyrite samples contain significant concentrations of As (≤32,231 ppm) and Sb (≤10,684 ppm), with lesser amounts of by Tl (≤1257 ppm) and Ni (≤174 ppm). This is followed by an Sb–As–Fe substage of pyrite–stibnite–realgar ±orpiment. The precipitation of the sulfides was mainly driven by changes in ƒS₂. The increasing level of oxidation is attributed to a progressive influx of meteoric water resulting from reactivation of the Matra Fault. Full article

Whilst there has been an increasing trend of women holding academic positions in European Higher Tertiary Institutions (HTIs), leadership positions are held predominantly by men. The study draws on radical feminism theory with which its methodology is aligned by investigating the perceptions of both genders. To that end, the study categorizes the impediments holding women back from breaking the glass ceiling into endogenous and exogenous factors. By doing so, the authors are in a better position to recommend the implementation of policies and procedures to address this inequality and navigate towards achieving sustainable gender equality. The research was conducted using an online survey questionnaire administered among all academic and administrative staff of universities in the Republic of Cyprus, the country with the highest glass ceiling in the EU. The authors found that the binary genders differ in their perceptions of what keeps women from breaking the glass ceiling and that this is attributable to exogenous factors, namely, (a) the walls created by male leaders, reinforcing a feeling of marginalization and mansplaining; and (b) family obligations enhancing women’s experiencing a lack of time and burnout. Furthermore, the exogenous factors and the extremely gendered higher echelons of HTIs underpin the endogenous factor of self-sabotage, making women feel they would rather avoid the toxic leadership environment with its lack of professional credit, a view supported by radical feminism theory. The authors suggest practical policy implications to rectify the gender imbalance in leadership in HTIs and suggest directions for future research. Full article

This study evaluates the influence of fiber type, geometry, and interfacial behavior on the physical and mechanical performance of cementitious composites reinforced with recycled pulp from beverage cartons (RPBC), bamboo fiber (BF), and eucalyptus fiber (EF) as the sole reinforcing agents. The BF was rounded in shape and had the highest aspect ratio, while the ribbon-shaped EF exhibited the highest tensile strength index. The RPBC fibers were fibrillated and the shortest, with a ribbon shape. Flexural strength results showed that RPBCC achieved a maximum strength that was 47.6% higher than the control specimen (0% fiber), outperforming both BF- and EF-reinforced counterparts. This superior performance is attributed to the higher fibrillation level of the ribbon-shaped RPBC fibers, which promoted better fiber–matrix bonding. As the fiber content increased, the bulk density of EFC and BFC decreased linearly, while RPBC composites showed only a modest decrease in density. Porosity steadily increased in EFC and BFC, whereas a non-linear trend was observed in RPBCC, likely due to its unique morphology and fibrillation. Conversely, EFC exhibited significantly higher maximum fracture toughness (3600 J/m² at 10 wt.%) compared to PBFCC (1600 J/m² at 14 wt.%) and BFC (1400 J/m² at 14 wt.%). This enhancement is attributed to extensive fiber pullout mechanisms and increased energy absorption during crack propagation. Overall, all composite types demonstrated flexural strength values above 4 MPa, placing them in the Grade I category. Those reinforced with 10–14% RPBC exhibited strengths of 11–12 MPa, categorizing them as Grade II according to ASTM C1186-02. Full article

To address critical technical challenges in coalbed methane fracturing, including the uncontrollable release rate of conventional breaker agents and incomplete gel breaking, this study designs and fabricates an intelligent controlled-release breaker system based on paraffin-coated mesoporous silica nanoparticle carriers. Three types of mesoporous silica (MSN) carriers with distinct pore sizes are synthesized via the sol-gel method using CTAB, P123, and F127 as structure-directing agents, respectively. Following hydrophobic modification with octyltriethoxysilane, n-butanol breaker agents are loaded into the carriers, and a temperature-responsive controlled-release system is constructed via paraffin coating technology. The pore size distribution was analyzed by the BJH model, confirming that the average pore diameters of CTAB-MSNs, P123-MSNs, and F127-MSNs were 5.18 nm, 6.36 nm, and 6.40 nm, respectively. The BET specific surface areas were 686.08, 853.17, and 946.89 m²/g, exhibiting an increasing trend with the increase in pore size. Drug-loading performance studies reveal that at the optimal loading concentration of 30 mg/mL, the loading efficiencies of n-butanol on the three carriers reach 28.6%, 35.2%, and 38.9%, respectively. The release behavior study under simulated reservoir temperature conditions (85 °C) reveals that the paraffin-coated system exhibits a distinct three-stage release pattern: a lag phase (0–1 h) caused by paraffin encapsulation, a rapid release phase (1–8 h) induced by high-temperature concentration diffusion, and a sustained release phase (8–30 h) attributed to nano-mesoporous characteristics. This intelligent controlled-release breaker demonstrates excellent temporal compatibility with coalbed methane fracturing processes, providing a novel technical solution for the efficient and clean development of coalbed methane. Full article

Wildlife–vehicle collisions (WVCs) remain a significant cause of animal mortality worldwide, particularly in regions experiencing rapid road network expansion. During the COVID-19 pandemic, a number of studies reported decreased WVC rates, attributing this trend to reduced traffic volumes. However, the validity of the simplified assumption that “fewer vehicles means fewer collisions” remains underexplored from a mechanistic perspective. This study aims to reevaluate that assumption using two simulation-based models that incorporate both the physics of vehicle movement and behavioral parameters of road-crossing animals. Employing an inverse modeling approach with quasi-realistic traffic scenarios, we quantify how vehicle speed, spacing, and animal hesitation affect collision likelihood. The results indicate that approximately 10% of modeled cases contradict the prevailing assumption, with collision risk peaking at intermediate traffic densities. These findings challenge common interpretations of WVC dynamics and underscore the need for more refined, behaviorally informed mitigation strategies. We suggest that integrating such approaches into road planning and conservation policy—particularly under the European Union’s ‘Vision Zero’ framework—could help reduce wildlife mortality more effectively in future scenarios, including potential pandemics or mobility disruptions. Full article

This study systematically evaluated the effects of pH (4–10) on the gelation properties, structural characteristics, and in vitro digestion–fermentation behavior of fish gelatin (FG, 6% (w/v)) hydrogels combined with either xanthan gum (XG, 0.07% (w/v)) or κ-carrageenan (κC, 0.07% (w/v)). The results revealed that the gel strength, hardness, and chewiness of the composite gels initially increased (pH 4–6) and subsequently decreased with rising pH levels. This trend correlated with the formation of a dense gel network structure. Furthermore, as pH increased, in vitro digestibility showed a similar pH-dependent trend, with FG–XG demonstrating superior enhancement compared to FG–κC. The addition of XG and κC resulted in increased gas production and a decreased pH during fermentation. Intestinal microbiota analysis revealed that both FG–XG and FG–κC improved the abundances of Proteobacteria and Bacteroidete while reducing Firmicutes. Compared to FG–XG and FG, FG–κC promoted higher levels of the genera Lachnospiraceae and Bacteroides, suggesting a more favorable impact on intestinal health. These findings provide valuable insights into the pH-responsive functional properties of FG-based hydrogels and their potential applications in designing novel food matrices with enhanced nutritional and probiotic attributes. Full article

In recent years, China has experienced growing impacts from extreme weather events, emphasizing the importance of understanding regional atmospheric moisture dynamics, particularly Precipitable Water Vapor (PWV), to support sustainable environmental and urban planning. This study utilizes ten years (2013–2022) of Global Navigation Satellite System (GNSS) observations in typical cities in eastern China and proposes a comprehensive multiscale frequency-domain analysis framework that integrates the Fourier transform, Bayesian spectral estimation, and wavelet decomposition to extract the dominant PWV periodicities. Time-series analysis reveals an overall increasing trend in PWV across most regions, with notably declining trends in Beijing, Wuhan, and southern Taiwan, primarily attributed to groundwater depletion, rapid urban expansion, and ENSO-related anomalies, respectively. Frequency-domain results indicate distinct latitudinal and coastal–inland differences in the PWV periodicities. Inland stations (Beijing, Changchun, and Wuhan) display annual signals alongside weaker semi-annual components, while coastal stations (Shanghai, Kinmen County, Hong Kong, and Taiwan) mainly exhibit annual cycles. High-latitude stations show stronger seasonal and monthly fluctuations, mid-latitude stations present moderate-scale changes, and low-latitude regions display more diverse medium- and short-term fluctuations. In the short-term frequency domain, GNSS stations in most regions demonstrate significant PWV periodic variations over 0.5 days, 1 day, or both timescales, except for Changchun, where weak diurnal patterns are attributed to local topography and reduced solar radiation. Furthermore, ERA5-derived vertical temperature profiles are incorporated to reveal the thermodynamic mechanisms driving these variations, underscoring region-specific controls on surface evaporation and atmospheric moisture capacity. These findings offer novel insights into how human-induced environmental changes modulate the behavior of atmospheric water vapor. Full article

Under the continuous disturbance of ecosystems driven by urbanization, landscape fragmentation and the disruption of ecological processes and functions are key challenges in optimizing ecological networks (EN). This study aims to examine the spatiotemporal evolution of topological patterns, ecological processes, and ecosystem services (ES) in Wuhan from the “pattern–process–function” perspective. To overcome the lag in research concerning the coupling of ecological processes, functions, and spatial patterns, we explore the long-term dynamic evolution of ecosystem structure, process, and function by integrating multi-source data, including remote sensing, enabling comprehensive spatiotemporal analysis from 2000 to 2020. Addressing limitations in current EN optimization approaches, we integrate morphological spatial pattern analysis (MSPA), use circuit theory to identify EN components, and conduct spatial optimization accurately. We further assess the effectiveness of two scenario types: “pattern–function” and “pattern–process”. The results reveal a distinct “increase-then-decrease” trend in EN structural attributes: from 2000 to 2020, source areas declined from 39 (900 km²) to 37 (725 km²), while corridor numbers fluctuated before stabilizing at 89. Ecological processes and functions exhibited phased fluctuations. Among water-related indicators, water conservation (as a core function), and modified normalized difference water index (MNDWI, as a key process) predominantly drive positive correlations under the “pattern–function” and “pattern–process” scenarios, respectively. The “pattern–function” scenario strengthens core area connectivity (24% and 4% slower degradation under targeted/random attacks, respectively), enhancing resistance to general disturbances, whereas the “pattern–process” scenario increases redundancy in edge transition zones (21% slower degradation under targeted attacks), improving resilience to targeted disruptions. This complementary design results in a gradient EN structure characterized by core stability and peripheral resilience. This study pioneers an EN optimization framework that systematically integrates identification, assessment, optimization, and validation into a closed-loop workflow. Notably, it establishes a quantifiable, multi-objective decision basis for EN optimization, offering transferable guidance for green infrastructure planning and ecological restoration from a pattern–process–function perspective. Full article

In the modern world, there is a need to provide a better understanding of the importance or relevance of the available descriptive features for predicting target attributes to solve the feature ranking problem. Among the published works, the vast majority are devoted to the problems of feature selection and extraction, and not the problems of their ranking. In this paper, we propose a novel method based on the Bayesian approach that allows us to not only to build a methodically justified way of ranking features on small datasets, but also to methodically solve the problem of benchmarking the results obtained by various ranking algorithms. The proposed method is also model-free, since no restrictions are imposed on the model. We carry out an experimental comparison of our proposed method with the classical frequency method. For this, we use two synthetic datasets and two public medical datasets. As a result, we show that the proposed ranking method has a high level of self-consistency (stability) already at the level of 50 samples, which is greatly improved compared to classical logistic regression and SHAP ranking. All the experiments performed confirm our theoretical conclusions: with the growth of the sample, an increasing trend of mutual consistency is observed, and our method demonstrates at least comparable results, and often results superior to other methods in the values of self-consistency and monotonicity. The proposed method can be applied to a wide class of rankings of influence factors on small samples, including industrial tasks, forensics, psychology, etc. Full article

Urban and regional ecosystems are increasingly challenged by the compounded effects of climate change and intensive land use. In this study, a predictive assessment framework for ecosystem resilience in the Beijing–Tianjin–Hebei region was developed by integrating multi-source remote sensing data, with the aim of quantitatively evaluating the coupled effects of climate change and land use change on future ecosystem resilience. In the first stage of the study, the SD-PLUS coupled modeling framework was employed to simulate land use patterns for the years 2030 and 2060 under three representative combinations of Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Building upon these simulations, ecosystem resilience was comprehensively evaluated and predicted on the basis of three key attributes: resistance, adaptability, and recovery. This enabled a quantitative investigation of the spatio-temporal dynamics of ecosystem resilience under each scenario. The results reveal the following: (1) Temporally, ecosystem resilience exhibited a staged pattern of change. From 2020 to 2030, an increasing trend was observed only under the SSP1-2.6 scenario, whereas, from 2030 to 2060, resilience generally increased in all scenarios. (2) In terms of scenario comparison, ecosystem resilience typically followed a gradient pattern of SSP1-2.6 > SSP2-4.5 > SSP5-8.5. However, in 2060, a notable reversal occurred, with the highest resilience recorded under the SSP5-8.5 scenario. (3) Spatially, areas with high ecosystem resilience were primarily distributed in mountainous regions, while the southeastern plains and coastal zones consistently exhibited lower resilience levels. The results indicate that climate and land use changes jointly influence ecosystem resilience. Rainfall and temperature, as key climate drivers, not only affect land use dynamics but also play a crucial role in regulating ecosystem services and ecological processes. Under extreme scenarios such as SSP5-8.5, these factors may trigger nonlinear responses in ecosystem resilience. Meanwhile, land use restructuring further shapes resilience patterns by altering landscape configurations and recovery mechanisms. Our findings highlight the role of climate and land use in reshaping ecological structure, function, and services. This study offers scientific support for assessing and managing regional ecosystem resilience and informs adaptive urban governance in the face of future climate and land use uncertainty, promotes the sustainable development of ecosystems, and expands the applicability of remote sensing in dynamic ecological monitoring and predictive analysis. Full article

A high intake of saturated fats and cholesterol from processed meats is associated with increased cardiovascular disease risk. This study aimed to develop a nutritionally enhanced Bologna-type sausage by partially replacing the beef content with a structured emulsion gel (EG) formulated from pine nut oil, inulin, carrageenan, and whey protein concentrate. The objective was to improve its lipid quality and functional performance while maintaining product integrity and consumer acceptability. Three sausage formulations were prepared: a control and two variants with 7% and 10% EG, which substituted for the beef content. The emulsion gel was characterized regarding its physical and thermal stability. Sausages were evaluated for their proximate composition, fatty acid profile, cholesterol content, pH, cooking yield, water-holding capacity, emulsion stability, instrumental texture, microstructure (via SEM), oxidative stability (TBARSs), and sensory attributes. Data were analyzed using a one-way and two-way ANOVA with Duncan’s test (p < 0.05). The EG’s inclusion significantly reduced the total and saturated fat and cholesterol, while increasing protein and unsaturated fatty acids. The 10% EG sample achieved a PUFA/SFA ratio of 1.00 and an over 80% reduction in atherogenic and thrombogenic indices. Functional improvements were observed in emulsion stability, cooking yield, and water retention. Textural and visual characteristics remained within acceptable sensory thresholds. SEM images showed more homogenous matrix structures in the EG samples. TBARS values increased slightly over 18 days of refrigeration but remained below rancidity thresholds. This period was considered a pilot-scale evaluation of oxidative trends. Sensory testing confirmed that product acceptability was not negatively affected. The partial substitution of beef content with pine nut oil-based emulsion gel offers a clean-label strategy to enhance the nutritional quality of Bologna-type sausages while preserving functional and sensory performance. This approach may support the development of health-conscious processed meat products aligned with consumer and regulatory demands. Full article