Search Results (4,147)

Non-grain production of cultivated land has increasingly affected regional food security and the stability of agricultural ecosystems. In traditional rice-producing regions, changes associated with non-rice cultivation, fallow land, rice-fishery integrated farming, and intensive agricultural management are reshaping the spatial structure of paddy landscapes. To identify the long-term spatiotemporal evolution of paddy systems, this study investigated Northern Jiangxi, China, using Landsat surface reflectance imagery from 2000, 2005, 2010, 2015, and 2020 on the Google Earth Engine (GEE) platform. The Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI) were used to construct a phenology-based Flooding Frequency (FF) indicator. Based on the annual frequency with which pixels satisfied the condition LSWI > EVI, cultivated land was classified into three categories: non-flooded cropland, standard rice paddy, and high-frequency flooded cropland. In this study, non-flooded cropland was used as an indicator of potential non-rice cultivation rather than as direct evidence of confirmed non-grain production. Landscape metrics, transition matrices, gravity center migration, standard deviation ellipses, and geographically weighted regression (GWR) were then used to examine paddy landscape dynamics, fragmentation patterns, and county-level spatial associations with socioeconomic factors. The results suggest that the paddy system in Northern Jiangxi experienced marked stage-based fluctuations between 2000 and 2020. Standard rice paddy recovered during 2005–2010, whereas non-flooded cropland expanded considerably during 2010–2015, accompanied by intensified paddy landscape fragmentation. Non-flooded cropland was mainly distributed around urban fringes, transport corridors, and some hilly margins. Standard rice paddy was concentrated in traditional grain-producing areas, including the Poyang Lake Plain and the Gan-Fu Plain. High-frequency flooded cropland was primarily located in low-lying lake areas, where its dynamics were likely associated with rice-fishery integrated farming, continuous irrigation, and hydrological fluctuations. Landscape metrics showed that the largest patch index and mean patch size of standard rice paddy declined after 2010, indicating reduced spatial continuity of core paddy fields. The GWR analysis provided auxiliary evidence that total population, per capita gross domestic product (GDP), and urbanization rate were spatially associated with changes in non-flooded cropland at the county level; however, the results should be interpreted as exploratory associations rather than causal mechanisms. Overall, paddy landscape change in Northern Jiangxi was expressed not only through changes in cultivated land area, but also through the reorganization of paddy function, spatial continuity, and land-use intensity. Future cropland protection should therefore move beyond area-based control toward integrated management of quantity, quality, function, and spatial configuration. Future research should further verify these findings using dynamic cropland boundaries, higher-resolution imagery, and more detailed socioeconomic data. Full article

Cachaça is one of Brazil’s most important distilled spirits, and its chemical and sensory quality is strongly influenced by the technological conditions adopted throughout production. Among the physicochemical parameters used to assess quality, volatile acidity has traditionally been regarded as a regulatory criterion; conversely, increasing evidence indicates that its significance extends beyond legal compliance, reflecting microbial control, fermentation performance, distillation practices, storage conditions, and consumer perception. This narrative review critically examines the current knowledge regarding the formation, technological modulation, regulatory relevance, and sensory implications of volatile acidity in Brazilian cachaça. The literature was selected from major scientific databases and official regulatory documents, emphasizing studies addressing fermentation, distillation, aging, chemical quality, and sensory evaluation. The review discusses the biochemical pathways involved in acetic acid formation, the influence of acetic acid bacteria, oxygen availability, hygienic practices, distillation fraction separation, and oxidative processes during storage. It further compares Brazilian regulatory requirements with those adopted for other distilled beverages and examines the relationship between volatile acidity and sensory perception, highlighting the absence of consensus regarding sensory thresholds specific to cachaça and the influence of beverage matrix and volatile interactions on consumer acceptance. Finally, the review proposes volatile acidity as an integrated quality marker capable of reflecting multiple technological stages rather than an isolated analytical parameter. Current knowledge gaps, particularly regarding the integration of chemical, microbiological, and sensory data, are discussed to support future research and contribute to the continuous improvement, standardization, and international competitiveness of Brazilian cachaça. Full article

Accurate correction of gridded numerical weather prediction precipitation forecasts remains challenging because many end-to-end deep learning correction models treat meteorological variables as undifferentiated data channels and therefore provide limited physical interpretability. Inspired by general principles of biological environmental sensing, selective information processing, and regulatory constraint learning, this study proposes PCPNet, a bio-inspired and physically constrained precipitation correction framework. The framework does not imitate a specific biological organ or species; instead, it abstracts three information-processing principles into a meteorological correction task. First, key weather-system cues, including low-level shear lines, trough-ridge effects, upper-level jet-stream forcing, vorticity-divergence-related vertical motion, and water-vapor flux convergence, are quantified as structured diagnostic fields. This transforms the subjective synoptic diagnosis of forecasters into automated grid-based sensing features. Second, these diagnostic cues are fused with numerical weather prediction variables and terrain descriptors in an encoder–attention–decoder network, allowing the model to emphasize dynamically important precipitation-triggering regions. Third, water-vapor conservation and terrain-forcing relationships are embedded as differentiable constraint losses, providing training-time constraint-based regulation that guides the corrected precipitation field toward physically consistent solutions. The method is evaluated from 2021 to 2023 in Hunan Province, China, using hourly numerical weather prediction model outputs as input features, China Meteorological Administration Land Data Assimilation System gridded analysis data as the training target, and independent meteorological station observations for strict cross-validation. PCPNet reduces the mean absolute error by 22.1% compared with the uncorrected China Meteorological Administration Land Data Assimilation System gridded precipitation products and outperforms Linear Regression, Bagging, Boosting, Multi-Layer Perceptron, TabNet, and Tree-based Progressive Regression Models by 12.9%, 13.5%, 16.9%, 10.8%, 14.9%, and 15.9%, respectively. The single-day event analysis provides an initial demonstration of heavy precipitation recovery capability, while comprehensive validation across long-term continuous weather events is planned for future operational deployment to further verify model stability. These results indicate that bio-inspired sensing and regulatory constraint learning can improve both the accuracy and interpretability of precipitation nowcasting correction. Full article

This study examines the determinants of Generation Z’s purchase intention for environmentally friendly public transportation in Indonesia, a mode of transport that continues to experience suboptimal ridership. We investigate the effect of consumers’ awareness of green product attributes and operational processes, as well as their exposure to green promotions, on green brand sustainability and, subsequently, on green purchase intention. The study involved 400 Generation Z respondents aged 19 years or older residing in Jakarta, Indonesia. Data were analyzed using Structural Equation Modeling (SEM) with LISREL11.0. The results show that green product awareness, green process awareness, and green promotion exposure significantly influence green brand sustainability, explaining 69 percent of its variance, with green product awareness being the most dominant predictor. Furthermore, green purchase intention is significantly shaped by these antecedents and green brand sustainability, collectively explaining 84 percent of its variance. The findings demonstrate that strengthening environmental awareness across product attributes, operational processes, and promotional communication can substantially increase Generation Z’s intention to use sustainable public transportation. This study extends the research on green consumer behavior and provides strategic insights to strengthen sustainability in the public transportation sector. Full article

Enterococcus spp. are increasingly recognized as important opportunistic pathogens in poultry production and represent a potential One Health concern because of their virulence potential and capacity to acquire antimicrobial resistance determinants. This study characterized Enterococcus isolates recovered from clinical poultry cases in Chile, focusing on species distribution, virulence-associated genes, antimicrobial resistance patterns and genes, biofilm formation, and cytolysin activity. A total of 39 isolates were identified using the VITEK^® 2 Compact system and confirmed by PCR targeting the tuf gene. Seven Enterococcus species were detected, with E. faecalis predominating (61.5%) and E. faecium following (15.4%). The virulence-associated genes asa1, gelE, and cylA were detected in 97.4%, 97.4%, and 48.7% of the isolates, respectively. Phenotypic antimicrobial susceptibility testing showed resistance mainly to tetracycline (61.5%) and erythromycin (17.9%), whereas all isolates were susceptible to vancomycin, ampicillin, chloramphenicol, and linezolid. Molecular analysis identified tetM (71.8%), ermB (66.7%), and tetL (30.8%) as the most predominant resistance genes. A significant association was observed between tetM and phenotypic tetracycline resistance (Fisher’s exact test, p = 0.010). However, no association was found between ermB and erythromycin resistance. Biofilm formation was observed in 66.7% of the isolates, although most were weak biofilm producers. Despite the relatively high prevalence of cylA, β-hemolytic activity was detected in only 5.1% of isolates, indicating an incomplete genotype–phenotype concordance. Overall, poultry-associated Enterococcus spp. circulating in Chile harbored multiple virulence and antimicrobial resistance determinants that may contribute to their persistence and adaptation in poultry production systems. These findings provide the first baseline molecular epidemiological data on clinical poultry-associated Enterococcus spp. isolates in Chile and support the need for continued surveillance and prudent antimicrobial use in veterinary medicine. Full article

To control the impact of the invasive crayfish Faxonius limosus on native crayfish and fish biodiversity in the Danube River ecosystem, one possible approach is the valorization of this species through the production of value-added biopolymers, considering the continuously increasing demand for chitosan. However, there are very limited data regarding the utilization of Faxonius limosus shell waste as a source of chitosan. Therefore, this study evaluated chitosan recovery from spiny-cheek crayfish shell, including conventional chemical treatment with different demineralization intensities and numbers of deproteinization steps, as well as ultrasound and autolysis-assisted deproteinization. The obtained chitosans were characterized in terms of yield, moisture content, degree of deacetylation, color, crystallinity and structural properties. Residual heavy metal concentrations (Hg, Cd and Pb) were determined to assess the safety of crayfish shell as a raw material intended for food-related applications. Particular emphasis was placed on gel-related functional properties of obtained chitosans, including rheological behavior, wettability on fruit surfaces, antioxidant and antimicrobial activities, and film-forming ability. These properties govern the formation of structured biopolymeric networks and their performance as active food coating materials. The relationships between the extraction process, physicochemical characteristics and functional performance were investigated to identify the most suitable chitosan for potential food preservation applications. The results demonstrated that extraction conditions significantly affected the physicochemical and functional properties of chitosan. Samples obtained through intensive deproteinization showed enhanced antimicrobial activity, whereas higher antioxidant activity was observed in samples containing residual bioactive compounds. Most formulations exhibited suitable wettability on apple and nectarine surfaces and successfully formed transparent films, indicating their potential application as edible coatings. Full article

Green and resilient agriculture can strike a balance between agricultural production and ecological conservation, ensuring a continuous and stable supply of food and agricultural products. Based on provincial panel data from 31 provinces in China during 2014–2023, this study constructs an evaluation system for agricultural green resilience and employs the fixed-effects model, mediation effect model, and spatial Durbin model to empirically examine the impact mechanism and spatial effects of digital inclusive finance on agricultural green resilience. The main findings are as follows: (1) Digital inclusive finance significantly enhances agricultural green resilience. (2) Agricultural technological innovation plays a mediating role in the relationship between digital inclusive finance and agricultural green resilience. (3) Digital inclusive finance generates significant positive spatial spillover effects on agricultural green resilience, not only improving local agricultural green resilience but also promoting coordinated development in neighboring regions. (4) Regional heterogeneity analysis indicates that the promoting effect is strongest in the central region, followed by the western region, while no significant effect is observed in the eastern region. From the perspective of different dimensions, the effect intensity follows the order of coverage breadth, depth of use, and degree of digitalization. These findings suggest that digital inclusive finance serves as an important driver of agricultural green resilience and sustainable agricultural transformation in China. Therefore, policymakers should further expand digital financial inclusion, strengthen support for agricultural technological innovation, and promote coordinated regional development to enhance agricultural green resilience. Full article

Despite growing interest in artificial intelligence (AI) applications in the construction industry, the literature still lacks a consolidated understanding of how AI functions across the full spectrum of construction supply chain processes. Existing studies are dispersed across different technologies, project stages, and application contexts, making it difficult to identify the intellectual structure of this field, the main areas of AI application, and the barriers that continue to constrain practical implementation. To address this gap, this study conducts a systematic review of AI applications in construction supply chains by combining scientometric analysis with qualitative content synthesis. A total of 212 journal articles retrieved from Scopus were analyzed using VOSviewer-based scientometric analysis and qualitative content synthesis. The scientometric analysis maps annual publication trends, keyword co-occurrence patterns, co-cited sources, influential documents, and collaboration networks. The qualitative synthesis further examines how AI supports construction supply chain management across three broad themes: procurement and production optimization, logistics and material management, and collaborative decision-making for resilience and sustainability. The findings show that AI has been primarily applied to demand forecasting, resource optimization, logistics coordination, contract and document processing, computer vision-based monitoring, and multi-agent decision support. However, its practical diffusion remains constrained by fragmented and low-quality data, limited empirical validation, high implementation costs, algorithmic opacity, cybersecurity risks, and unresolved governance and liability issues. Based on these findings, this study proposes a data-centric and phased research agenda that emphasizes benchmark datasets, human–AI collaboration, lifecycle economic evaluation, explainable AI, and multi-stakeholder governance. The study contributes to the literature by integrating fragmented AI-related research into a structured knowledge map and by clarifying future pathways for developing intelligent, transparent, and resilient construction supply chains. Full article

Background: This study aimed to investigate the association between educational attainment and depressive symptoms among young-old adults aged 60–74 years, and to examine the mediating effect of self-reported memory function between them, so as to provide a reference for the early screening and intervention of depressive symptom severity in this population. Methods: This was a cross-sectional study, and data were derived from the 2022 China Family Panel Studies (CFPS). After data cleaning, 3666 valid samples were included. Depressive symptom severity was assessed using the 8-item Center for Epidemiologic Studies Depression Scale (CES-D 8) (Cronbach’s α = 0.771, Guttman Split-Half Coefficient = 0.742), with a total score ≥ 9 defined as probable depression. Self-reported memory function was measured using a single item (scored 0–4), with higher scores indicating better perceived memory, and was treated as a continuous variable for analysis. Descriptive statistics and Pearson correlation analysis were performed using R software (version 4.2.3). The mediation effect was tested using the product-of-coefficients method combined with the bootstrap method (5000 resamples), supplemented by a quasi-Bayesian model and multiple sensitivity analyses (including outcome variable substitution and model diagnostic corrections) for robustness testing. Results: Among the study participants, the prevalence of probable depression was 25.18%. Correlation analyses showed that educational attainment was significantly negatively correlated with depressive symptom severity (r = −0.177, p < 0.001) and significantly positively correlated with self-reported memory function (r = 0.241, p < 0.001). Self-reported memory function was significantly negatively correlated with depressive symptom severity (r = −0.223, p < 0.001). After adjusting for age, gender, place of residence, subjective income, self-rated health, and chronic disease status, mediation analysis showed that the direct effect of educational attainment on depressive symptom severity was −0.297 (95% CI: −0.424 to −0.174), while the indirect effect via self-reported memory function was −0.109 (95% CI: −0.139 to −0.082). The direct and indirect effects accounted for 73.20% and 26.80% of the total effect, respectively; the results of the quasi-Bayesian analysis and multiple sensitivity analyses were consistent in direction, further validating the stability of this mediation effect. Conclusions: Among young-old adults aged 60–74 years, self-reported memory function plays a partial statistical mediating role in the association between educational attainment and depressive symptom severity. This suggests that strengthening attention to memory status and early screening among individuals with lower educational attainment may offer a potential intervention approach for alleviating depressive symptom severity in this population in the future. Full article

New-quality productive forces provide an important conceptual lens for understanding how innovation-driven development, digital empowerment, and the green transition jointly support sustainable regional development. From a geographical perspective, this study develops a multidimensional evaluation system for new-quality productive forces based on the three elements of productive forces: laborers, means of labor, and objects of labor. Using panel data for 31 provincial-level administrative units in China from 2012 to 2022, we integrate the entropy weight method, standard deviation ellipse, exploratory spatiotemporal data analysis, the obstacle degree model, and the random forest model to examine the spatiotemporal evolution and influencing mechanisms of new-quality productive forces. The results show that: (1) China’s new-quality productive forces increased steadily during the study period, but their overall level remained relatively low and regional disparities continued to widen. Spatially, they exhibited a pronounced “high in the east and low in the west” pattern, with South China and East China maintaining leading positions and Guangdong and Jiangsu forming a dual-core growth structure. (2) The spatial center of gravity remained southeast of the Hu Huanyong Line, and its expansion direction was broadly parallel to this line, indicating a relatively stable spatial configuration. The ESTDA results further reveal significant positive spatial autocorrelation, strong temporal inertia, and marked path dependence in local spatial transitions. (3) High-tech talent supply, innovation and entrepreneurship vitality, and ecological governance capacity constitute the main internal bottlenecks constraining the development of new-quality productive forces. The analysis of external factors indicates that economic scale and population size are the primary predictors of NQPF development, whereas government intervention, openness, urbanization, and industrial structure exhibit varying degrees of nonlinearity and regional heterogeneity. These findings enrich the geographical interpretation of new-quality productive forces and provide empirical evidence for formulating differentiated regional innovation policies and productivity transformation strategies. Full article

Customer complaints are considered one of the key indicators of customer discontentment with a service. In organizations, such as telecommunications companies, not all customers raise their complaints, which raises concerns about their potential churn or retention. As firms usually rely on the complaints raised to customer services, there exists an important portion of customers who claim their complaints through other platforms, such as social media, even though another portion does not complain at all. This places the company’s image in jeopardy and might affect its productivity and profits. To address this challenge, it is important to address possible customer problems before they turn into effective complaints. To do so, the current study aims to predict the complaints of customers in a telecommunication company and their potential churn through the usage of supervised machine learning models to test the correlation between churn and complaints. Through a thorough data analysis, it becomes evident that a good portion of clients who encounter service issues decide not to present any complaints to the company. In addition, among complainers, some do not complain directly to the company, while others who contact the company have their problems postponed. Among those, there is a proportion, considered as having unresolved concerns, turned into churn. Using a dataset of 1000 clients, recruited over a period of six months, the results showed that a considerable portion of customers using the services during the day were non-churners and continued using it over the overall period of 6 months. Whereas, day churn and evening churn both showed much lower frequencies compared to non-churn customers, with fewer calls across all durations. Additionally, the findings showed that there exists a correlation between customer complaints and customer churn, where churn events frequently coincide with complaints, indicating that customers without churn are generally content with their service, while those having complaints are more likely to quit. This study presents important insights into telecommunications companies to improve their service offerings, enhance customer satisfaction, and reduce churn rates, leading to a more stable and profitable customer base. Full article

The bean bug, Riptortus pedestris (Fabricius), and the southern green stink bug, Nezara viridula (L.), are important pod-sucking pests of soybean, Glycine max (L.) Merr. Their feeding on pods and developing seeds induces soybean staygreen symptoms and causes severe yield losses. To assess their future damage risk, we integrated MaxEnt, PCA env and a phenological matching index (PMI) using global occurrence records, bioclimatic variables and soybean phenology data. Under current climatic conditions, R. pedestris exhibited a predominantly temperate East Asian distribution, with suitable areas extending farther north and northeast. By contrast, N. viridula showed a more southerly and spatially continuous distribution across South and Southeast Asia, with suitability declining markedly toward northern and northeastern Asia. By the 2090s under SSP5-8.5, suitable areas decreased by 26.7% for N. viridula but increased by 34.0% for R. pedestris, and the co-suitable area declined from 9.460 to 7.350 million km². PCA env indicated low to moderate niche overlap (Schoener’s D = 0.278) with significant niche differentiation. Under fixed soybean calendars, mean PMI generally increased for both pests, although the increase plateaued for R. pedestris under high emission scenarios by the late 21st century. Collectively, these findings indicate that Asian soybean production regions currently face overlapping damage risk, that the potential damage zone of R. pedestris is likely to expand further, and that the temporal overlap between the soybean sensitive period and adult activity windows of both pests will generally increase—despite the projected contraction in the potential damage distribution of N. viridula. Full article

Energy efficiency interventions are typically evaluated and implemented at the single-firm level, yet energy use and savings are shaped by interdependent decisions distributed across the supply chain, spanning sourcing, production, inventory, logistics, and financing. A foundational observation motivating this paper is that some energy efficiency actions are only possible through inter-firm cooperation: they require changes to partners’ processes or technologies, create benefits that accrue to different actors than those bearing the investment costs, and demand governance mechanisms (e.g., cost-sharing contract, buyer-financed supplier development, supply chain finance instruments) to be financially viable. This paper proposes CHAIN-EE (Collaborative Holistic Approach for Integrated Network Energy Efficiency), an action-oriented framework that operationalizes systems thinking into a practical roadmap for supply chain decision-makers. CHAIN-EE integrates three interconnected phases: (A) supply-chain energy diagnosis, covering boundary definition, baseline construction, and hotspot identification across nodes and flows; (B) action portfolio design, structured around a six-lever intervention taxonomy and multi-criteria evaluation embedding a cost–benefit alignment map that makes governance feasibility an explicit selection criterion; and (C) governance and continuous improvement, including incentive alignment, investment architecture and ISO 50001-compatible performance management. Evidence from four European research projects spanning the food cold chain, dairy, food-and-beverage/transport value chains, and HORECA illustrates how each phase operates in practice across different sectors and governance contexts. The paper contributes an integrative, sector-adaptable structure for supply chain energy efficiency programmes, grounded in both analytical research and applied project experience, and a targeted research agenda on cross-node rebound effects, data-enabled energy flow mapping, and multi-tier coordination mechanisms. Full article

This study investigates the relationship between economic growth, trade openness, energy intensity, and carbon dioxide (CO₂) emissions in South Africa within the Environmental Kuznets Curve (EKC) framework over the period 1970–2022. Using quarterly time series data and the Autoregressive Distributed Lag (ARDL) modelling approach, the study examines both the short-term and long-term dynamics between economic activity and environmental degradation. Descriptive statistics, correlation analysis, unit root tests, ARDL bounds testing, error-correction modelling, Granger causality analysis, and diagnostic tests were employed to ensure robust empirical results. The Augmented Dickey–Fuller (ADF) and Phillips–Perron (PP) tests indicate that all variables are integrated of order one, I(1), thereby satisfying the conditions for ARDL estimation. The ARDL bounds test confirms the existence of a long-term cointegrating relationship among carbon emissions, economic growth, trade openness, and energy intensity. The long-term results reveal a statistically significant negative coefficient for economic growth and a positive coefficient for the squared income term, indicating a U-shaped relationship between income and carbon emissions. Consequently, the conventional Environmental Kuznets Curve hypothesis is not supported for South Africa. The findings suggest that economic growth initially reduces environmental degradation; however, beyond a certain income threshold, further economic expansion increases carbon emissions. Trade openness and energy intensity exert positive and statistically significant effects on carbon emissions in the long run, implying that increased integration into global markets and continued dependence on energy-intensive production contribute to environmental degradation. The Error-Correction Model (ECM) reveals a negative and highly significant adjustment coefficient (−0.928), indicating that approximately 92.8% of short-term disequilibrium is corrected within one period. Granger causality results further show a unidirectional causal relationship running from trade openness to carbon emissions, while no significant causal relationship is found between economic growth and carbon emissions. The study concludes that economic growth alone is insufficient to achieve environmental sustainability in South Africa. Policy efforts should therefore focus on promoting renewable energy adoption, improving energy efficiency, strengthening environmental regulations, encouraging cleaner production technologies, and integrating environmental considerations into trade and industrial policies. These measures are essential for achieving sustainable economic development while meeting national climate-change-mitigation objectives. Full article

Sporadic cases of trichinellosis have occurred almost every year in Serbia. The success of trichinellosis control in the country depends on effective communication among medical professionals who discover a case of trichinellosis, the Public Health Service, and the Veterinary Service, in line with the One Health concept. The collaborative approach, supported by a robust reporting and monitoring system, has been essential for identifying infection sources and preventing further spread. However, in March 2023, the National Reference Laboratory for Trichinellosis (NRLT) received reports of hospitalized patients with suspected trichinellosis, signaling the possibility of two outbreaks based on their socio-epidemiological history. The investigation revealed separate trichinellosis outbreaks occurred in Grocka, Belgrade municipality, and Dolovo, Pancevo municipality, with pork identified as the source of infection. Serological tests confirmed the presence of Trichinella-specific antibodies in the patients, including their family members and friends. A total of four patients required hospitalization. In accordance with regulations, veterinary inspectors took dried meat and meat products samples and Trichinella larvae were detected using the digestion method. The entire amount of dried meat and meat products was subsequently destroyed. Multiplex PCR confirmed the identification of Trichinella britovi at the species level in both outbreaks. These findings represent the first documented cases of T. britovi infection in domestic pigs in Serbia. The outbreak data once again highlight that inadequate animal husbandry practices, certain human behaviors, and a lack of awareness about the risks continue to be major contributors to the persistence of trichinellosis in Serbia. Full article