Search Results (8,938)

Against the backdrop of global agricultural sustainability transition, this study examines the mechanism through which peer effects influence the intention–behaviour paradox in farmers’ adoption of organic fertilisers as a substitute for chemical fertilisers, from the perspective of ecological rationality. Using survey data from 505 rice farmers in Hunan Province, this research integrates peer effects and ecological rationality into a unified analytical framework and employs a Probit model to test the mediating role of ecological rationality in the relationship between peer effects and the intention–behaviour gap in chemical fertiliser reduction for sustainable farmland management. The results show that support from family members and people in one’s immediate social environment can effectively alleviate the intention–behaviour paradox among farmers in the process of substituting chemical fertilisers with organic fertilisers, whereas support from friends is positively correlated with this degree of discrepancy. Ecological rationality serves as a mediating variable that strengthens the positive effect of peer influence on the consistency between farmers’ behavioural intentions and actual practices in sustainable agricultural production. These findings provide a new theoretical perspective for understanding farmers’ pro-environmental behaviour, and offer actionable policy implications for advancing agricultural sustainability by enhancing family and community support and improving farmers’ ecological rationality. Full article

The rapid growth of organisational textual data has increased the value of Natural Language Processing (NLP) and semantic analytics for strategic decision support. However, many employees still lack the knowledge and skills needed to evaluate AI-generated information critically. This study develops an explainable Management Information Systems (MIS) framework that integrates NLP-based semantic analytics with PLS-SEM to examine the relationship between AI illiteracy and strategic decision quality. A convergent mixed-methods design with sequential analytical integration was used with a valid sample of 200 knowledge workers from public organisations in Saudi Arabia across six industries. The sample included employees from Saudi Arabia, Egypt, Jordan, Sudan, Syria, India, and the Philippines. Quantitative data were analysed using PLS-SEM, while textual data were analysed using Sentence-BERT, BERTopic, semantic network analysis, and Aspect-Based Sentiment Analysis. The results showed that higher AI illiteracy was negatively associated with strategic decision quality and positively associated with automation bias, uncritical trust in AI, and cognitive offloading. Digital proficiency and AI governance awareness weakened the negative association between AI illiteracy and decision quality, while functional-background differences were examined through multigroup analysis. The semantic analysis identified six themes: AI competency, decision trust, AI governance, decision support, organisational learning, and risk awareness. Sentiment analysis showed positive views of productivity and decision support, together with concerns about algorithmic bias, explainability, transparency, and AI governance. The study contributes an integrated human–AI decision vulnerability framework in which semantic evidence complements structural modelling and provides a clearer understanding of AI-related competency, reliance, governance, and decision-support issues. Full article

Fruit and vegetable supply chains generate heterogeneous data across production, storage, logistics, and sales, creating challenges for trusted data sharing, privacy protection, and real-time traceability across distributed supply-chain information systems. Conventional single-chain blockchains suffer from limited scalability, data redundancy, and low retrieval efficiency, making them inadequate for high-frequency full-process information management. This study proposes a multi-chain blockchain framework for trusted full-process information management of fruit and vegetable supply chains. The framework integrates traceability, enterprise, notary, and regulatory chains to support hierarchical data management and privacy isolation. A reputation-based notary node election mechanism and a threshold-signature scheme based on Shamir secret sharing are designed to enhance cross-chain security and distributed regulatory consensus. To improve retrieval efficiency, a Cuckoo-Augmented Merkle Tree (CMerkle) and a skip-list-based block index are developed. Simulation results show that all malicious nodes were restricted by the 19th round, signature aggregation required 70.16 ms in a 500-node setting, and CMerkle achieved retrieval speedups of 14.7 and 153 times at data scales of 500 and 10,000 records, respectively. The framework supports trusted data governance, real-time traceability, privacy-preserving sharing, and regulatory decision support in blockchain-enabled supply-chain information systems. Full article

Carbon capture is more and more often seen as a component of an integrated carbon-management system than as a stand-alone separation phase. The practical utility of capture technology depends on the chemical state in which the carbon dioxide is held, the energy and material needs for regeneration, the compatibility of the caught species with downstream catalysis and the lifetime of the resulting carbon-containing product. This paper offers an in-depth framework for integrated CO₂ capture and circular carbon use, including catalytic conversion, bio-integrated processes, biomass-derived materials and fuels, hydrogen-enabled routes, mineralization, and artificial intelligence-assisted process design. Reactive capture techniques that convert carbonate, bicarbonate, carbamate, dissolved CO₂ or surface-bound intermediates without first generating a purified gas stream are contrasted with sequential capture, purification, compression, transport and conversion. The thermocatalytic, electrochemical, photoelectrochemical and biological conversion pathways are compared against common parameters such as working capacity, conversion rate, selectivity, carbon efficiency, regeneration energy, stability and life-cycle greenhouse gas performance. Special emphasis is given on dual-functional materials, interfacial reactors, bio-integrated methanation, carbon mineralization in construction materials and coupling with renewable hydrogen. The review also discusses how machine learning, molecular screening, process simulation, graph-based data architecture, and digital monitoring could speed up material selection and system optimization. Across all pathways, the central design requirement is not maximum capture capacity alone, but a balanced match among binding strength, transport, catalytic reactivity, product separation, durability, and carbon permanence. A reporting framework and research agenda are proposed to guide credible scale-up and comparison of integrated carbon-management technologies. Full article

This research investigated the relationship between agility and educational service quality in higher education. The prior literature has mainly studied such relations in production organizations, while service organizations, especially higher education organizations, have been examined less often. We extend prior knowledge by developing and analyzing a comprehensive model that explains how key internal and external organizational factors affect overall agility and, in turn, how overall agility influences perceived educational service quality in higher education institutions. The study draws on management, education, and quality theories and analyzes responses from final-year students in business and management studies. The results show that the main agility factors—namely, market forces, internal practices and processes, and human resource management—significantly affect the agility of higher education institutions. The study’s findings also confirm that the agility of higher education institutions significantly affects the dimensions of Higher Education PERFormance (HEdPERF), the chosen model for assessing the quality of educational services. Considering the importance of agility in achieving objectives in an era of uncertainty and crises, we propose a model that may help improve the current higher education system by enhancing service provision to students and other stakeholders. Full article

Soil erosion is a critical global challenge and presents particularly alarming characteristics in the Amazon–Cerrado transition in Mato Grosso, a leading agricultural state in Brazil. Therefore, soil and water losses were evaluated under three soil cover conditions for corn and pasture cultivation (with vegetation cover, without vegetation cover, and without vegetation cover with soil scarified to a depth of 0.10 m) and four precipitation patterns (Advanced, Intermediate, Delayed, and Constant). The results showed that both soil cover and rainfall patterns directly influence the erosion processes. Soil loss increased up to sixfold under the Intermediate compared to the Constant rainfall, highlighting the strong influence of rainfall temporal distribution on erosion dynamics. The highest maximum runoff rates (MRR) and soil losses (SL) were recorded in tilled plots under maize cultivation, reaching 98.57 mm h⁻¹ and 5.90 g m⁻², respectively, under the intermediate pattern. In pasture areas, SL followed a similar pattern to the maize area, with maximum values of 6.96 g m⁻², but the MRR was recorded under the advanced pattern and in plots with cover (89.71 mm h⁻¹). This may be attributed to soil management conditions in pasture areas. Advanced and Intermediate patterns resulted in greater soil losses (3.78 and 2.04 g m², respectively), highlighting the impact of peak intensity timing on soil erosion. Greater soil losses were observed at the pasture experimental site than at the maize experimental site. Because the experiments were conducted at different locations with contrasting soil and management conditions, these differences should not be interpreted as being caused exclusively by crop type. The current study reinforces the need for erosion control and management strategies that account for natural variations in rainfall and soil cover to mitigate the negative impacts of land degradation on agricultural production and environmental sustainability. Full article

This research proposes an approach based on a circular economy principle for the integral valorization of Sargassum from the Mexican Caribbean. The biomass was characterized through proximal and elemental analyses, and then an oxidative pretreatment was carried out to enhance a sequential processing scheme to extract sodium alginate and use the solid waste as a substrate for biogas production via anaerobic digestion. The oxidative pretreatment successfully reduces the recalcitrant content and the concentration of heavy metals. The sodium alginate extracted from treated biomass achieves a yield higher than 20%; the characterization of the polymer via nuclear magnetic resonance showed that the mannuronic-to-guluronic ratio was between 0.34 and 0.62, indicating the potential for its use for environmental and biomedical applications. The highest yield in methane production was 328 mL CH₄/g of volatile solids, with a purity of 90%, and was achieved using the waste from alginate extraction with an inoculum-to-substrate ratio of 1:1. The experimental data presented an excellent fit to a Gompertz model (R² > 0.99). The proposed valorization pathway improves the sustainability of Sargassum management, prioritizing the recovery of high-value compounds before energy production. This circular approach provides a framework for converting environmental challenges into opportunities in the Caribbean. Full article

Hypertension is the most common comorbidity in chronic kidney disease (CKD), affecting roughly 80–85% of patients overall and an even higher proportion in nondialysis CKD G3–G5. This narrative review examines whether, and under what clinical conditions, fruits, vegetables, and legumes can be used safely in adults with hypertensive CKD, especially nondialysis CKD G3–G5, as well as moderate to severe loss of kidney function, paying close attention to the gut microbiota, short-chain fatty acids, gut-derived uremic toxins, potassium bioavailability, and modifiable clinical risk factors. The clinical effect of plant foods on serum potassium cannot be predicted from total potassium content alone. The Kidney Disease: Improving Global Outcomes (KDIGO) 2024 guidelines explicitly advise individualized potassium management and emphasize limiting foods rich in bioavailable potassium, especially processed foods, rather than reflexively restricting fruits and vegetables. Across CKD studies, the association between dietary potassium and serum potassium is weak or inconsistent, and the risk of hyperkalemia is modified by kidney function, bowel function, metabolic acidosis, diabetes and hyperglycemia, medications, food processing, and the food matrix itself. Potassium bioavailability varies substantially according to the food matrix, preparation method, portion size, and processing method; some minimally processed plant foods may provide less readily absorbable potassium than potassium-rich processed foods, juices, or potassium additives. Fruits, vegetables, and legumes also provide fiber, resistant starch, and polyphenols that can support saccharolytic fermentation, short-chain fatty acid production, bowel transit, and lower concentrations of some gut-derived uremic toxins. However, blood-pressure and kidney-outcome benefits in CKD are supported more strongly by observational and selected alkali-diet trials than by large microbiome-focused randomized studies. In hypertensive CKD, fruits, vegetables, and legumes should not be universally restricted simply because they contain potassium. A safer and more evidence-aligned strategy is individualized, food-source-aware prescribing that prioritizes minimally processed plant foods, accounts for preparation method and portion size, corrects constipation and acidosis, reviews potassium-raising medications and additives, and monitors serum potassium according to baseline risk. Full article

The growing demand for gluten-free products has increased the need for a better understanding of the rheological behavior of alternative flours and their suitability for bakery applications. This study aimed to evaluate the effect of different hydration levels on the rheological properties of gluten-free flours and compare their behavior with that of wheat flour. Rice flour, corn flour, chickpea flour, buckwheat flour, and wheat flour were analyzed using Mixolab 2 at hydration levels of 55%, 58%, and 60%. The resulting torque curves were examined to assess dough development, stability, and behavior during mixing and heating. Differences among flour types were observed throughout dough development and protein weakening. One-way ANOVA identified significant flour-type effects for all 19 Mixolab variables at 55% and 60% hydration and for 17 of 19 variables at 58%, where T(C4) and γ-slope were not significant. Across the three common hydration levels, two-way ANOVA showed significant main effects of flour type and hydration for every variable and significant flour × hydration interactions for all variables (p ≤ 0.035), confirming flour-specific hydration responses. Among the gluten-free flours, buckwheat maintained the most stable and comparatively robust torque profile, rice was particularly sensitive at 60% hydration, and corn and chickpea showed pronounced structural weakening during heating, most notably chickpea. A focused principal component analysis (PCA) of the five directly measured torque points (C1–C5), using the hydration levels common to all flour types, identified a dominant first component that explained 76.9% of the total variance. The first two axes together accounted for 94.3% and provided a concise two-dimensional representation of flour-specific and hydration-dependent differences. These findings highlight the importance of hydration management in gluten-free formulations and provide useful information for optimizing bakery processes involving alternative flours. Full article

Lithium, as a Li-ion battery constituent, is pivotal for the transition to clean energy. Western Australia (WA) has become a global leader in hard-rock lithium mining, realising 10-fold growth from 2010 to 2024 and with royalty receipts to the WA government surpassing $1 billion AUD. Given the sector’s economic significance, we analyse key performance metrics including resource/reserve build, production growth, cumulative capital deployed, capital intensity, and development timelines for the new-generation lithium mines. Several enabling factors supported the rapid build-out of capacity. These include an efficient mine permitting process to manage environmental impacts and competing land use issues, a stable royalty regime, energy and logistics infrastructure, availability of a skilled workforce, and mining services capability. Contrary to the standard industry narrative that new mineral projects are constrained by legislative delay, the new lithium projects achieved development timelines of 7 years or less from first resource to production. This has broader implications for critical mineral projects where success is likely to depend less on strategic classification and more on project quality, financing, and regional capability. Full article

Digital transformation in agricultural production requires automated approaches for monitoring, risk assessment, and decision support under uncertainty. This study proposes an automated risk assessment and control framework for feed production in digital agroengineering systems. The framework is designed for the quantitative evaluation of producer and consumer risks arising during the control of key feed-quality parameters, using the case of feed production for cattle in the OHMK agricultural holding. The proposed approach integrates probabilistic modeling, simulation-based risk estimation, fuzzy logic, expert evaluation, and a multi-agent representation of agroengineering processes. A three-dimensional risk model is developed to represent producer risk, consumer risk, and actuarial risk as interconnected components of a digital control environment. In addition, a fuzzy model is introduced to assess the robustness and digital maturity of management functions, including organization, planning, motivation, and control. Computer experiments based on statistical data for crude protein content in silage demonstrate that control risks depend nonlinearly on measurement uncertainty, parameter variability, and normative thresholds. In the analyzed single-indicator case study, the arithmetic mean of crude protein content in silage was 7.5% of dry matter, the standard deviation was 0.5, and the Weibull approximation parameters were α = 1.0, β = 2.5, and γ = 6.0. Under the most sensitive normative threshold scenario, producer risk increased to approximately 25%, while consumer risk showed a lower but nonlinear increase with measurement uncertainty. The results show that producer risk may reach significant levels when measurement uncertainty becomes comparable with the variability of the controlled parameter. The proposed framework can serve as a computational basis for future automated monitoring, risk-aware control, and decision-support systems in Industry 4.0-oriented agricultural production. Full article

This research investigates the potential for valorizing submerged arc welding (SAW) slag as a partial substitute for Portland cement in eco-efficient mortars. The research focuses on microstructural characterization, mechanical performance, and, innovatively, resistance to microbial adhesion by Escherichia coli. The residue was processed by grinding and incorporated at substitution levels of 5%, 10%, and 15% by weight. The mechanical results demonstrate that the 5% substitution (AM5%) showed the best performance, reaching 47.55 MPa at 28 days, an increase of approximately 20% compared to the reference sample. This improvement is attributed to the pozzolanic effect with the filling and refinement of the pore structure, in the production of the secondary C-A-S-H phase. In the bioreactor biological assay, the AM5% sample demonstrated a significant reduction in bacterial colonization adhering to the material’s surface, with values of 9.4 × 10¹ CFU/cm². Scanning electron microscopy (SEM) analyses revealed that the denser surface, with lower porosity, hindered the anchoring of E. coli and the formation of biofilm. The study concludes that the use of 5% SAW slag not only improves the structural properties of mortars but also increases their durability in environments prone to biological contamination, such as sanitation systems, promoting a sustainable alternative for the management of industrial waste in civil construction. Full article

Digital technologies have become an essential part of modern workplaces, improving communication, efficiency, and organisational processes. However, excessive and uncontrolled use of digital technologies may negatively affect employees’ well-being and workplace productivity. This narrative literature review examines the relationship between digital addiction and workplace productivity by focusing on the individual, social, and organisational consequences of problematic digital technology use. The study first defines the concepts of digital addiction and workplace productivity to establish a conceptual framework. It then discusses how problematic digital technology use, including excessive internet use, social media use, smartphone use, screen use, gaming disorder, and online gambling, may influence productivity through distraction, reduced concentration, poor time management, stress, health problems, and impaired work–life balance. The review highlights that digital technologies are not inherently harmful; rather, productivity problems arise from uncontrolled and problematic patterns of use. The study concludes by suggesting organisational and individual-level interventions, including digital awareness training, responsible technology use policies, improved time management practices, and supportive workplace environments to reduce the negative effects of digital addiction. Full article

Monitoring forest degradation using medium-resolution optical sensors often results in an underestimation of the actual ecological impacts, limiting conservation strategies in threatened regions. We evaluated the forest disturbance dynamics (2004–2025) in the Permanent Production Forests of Tahuamanu, Madre de Dios, Peru. We processed multitemporal Landsat images in Google Earth Engine to map change trajectories by applying Spectral Mixture Analysis to derive the Normalized Difference Fraction Index (NDFI) integrated with a stratified area estimator. This approach yielded overall accuracies of ≥93%. Our findings show that structural degradation is replacing deforestation as the main driver of forest alteration. By 2025, the footprint of this disturbance, which silently affects the understory, had quadrupled the extent of deforestation, a trend evidenced by the stratified adjustment that revealed over 10,000 hectares of structural damage previously hidden under the label of intact forest, demonstrating the typical omission bias of passive sensors. Relying on raw maps means underestimating biomass lost to understory degradation. To address this systematic bias, it is necessary to operationalize the NDFI model along with a rigorous stratified estimation. With this combined approach, a scalable, cost-effective, and statistically robust framework is offered to monitor the subtle degradation that traditional mapping systems overlook. To our knowledge, this is the first long-term, area-corrected assessment of forest disturbance within Peru’s oldest formal timber concessions, and it shows that degradation persists and accelerates even under a regulated management model. Full article

Conservation governance frameworks assess equity through recognition, procedure, and distribution. These dimensions give limited attention to Indigenous authority over land and conservation decisions in settler-colonial contexts, including the relationships, responsibilities, and governance conditions that shape equitable conservation. This study develops and pilots the Conservation with Equity framework across three UNESCO-designated Biosphere Reserves in Canada: Clayoquot Sound, Mount Arrowsmith, and Redberry Lake. Using document analysis of UNESCO governance documents, complemented by semi-structured interviews with Biosphere Reserve managers, we examined how equity is reflected in conservation governance practices. The pilot application identified ecological reconciliation as a fourth and foundational dimension of equitable conservation governance, extending existing equity frameworks. Results show that the Biosphere Reserves incorporate Indigenous knowledge into conservation activities, involve communities in decision-making through governance processes, and support local livelihoods and restoration initiatives. However, these practices improve participation and benefit sharing without consistently shifting decision-making authority over land and conservation. Indigenous-led initiatives, including Tribal Parks, land-based education, healing initiatives, and food production systems, demonstrate pathways where Indigenous communities direct land use and conservation decisions. The Conservation with Equity framework provides a basis for assessing conservation governance with greater attention to Indigenous authority, governance, and relationships with land. Full article