Search Results (2,373)

Health-related product positioning has become an important strategy for influencing consumer evaluations and consumption behaviour. Previous studies have shown that favourable health-related perceptions positively affect consumer responses, yet the cognitive mechanism linking these perceptions to consumption decisions remains insufficiently understood. This study examines the mediating role of perceived product quality in the relationship between perceived health image and consumption decision toward Bear Brand sterilized milk in Indonesia. A survey of 200 consumers was analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings indicate that perceived health image influences consumption decisions both directly and indirectly through perceived product quality. More importantly, consumers ultimately rely on quality evaluations rather than favourable health-related impressions alone when making consumption decisions. This study contributes to consumer behaviour literature by demonstrating how the Health Halo Effect, Cue Utilization Theory, and Signalling Theory jointly explain the sequential cognitive process underlying health-related consumption decisions. In practice, the findings suggest that firms should complement health-oriented brand positioning with consistently superior product quality to strengthen consumer confidence and improve the effectiveness of health-related marketing communications. Full article

The world’s food industry faces significant obstacles today as it strives to meet the nutritional needs of its rapidly expanding global population while also managing an immense amount of food processing waste (FPW) generated throughout the entire food supply chain. The widespread use of traditional disposal techniques for food waste (landfilling and incineration) regularly faces challenges related to environmental sustainability and economic efficiency. This manuscript reviews the necessary transition from a linear “take-make-dispose” approach to food production to a more circular model that recycles food waste into high-value intermediate chemicals and renewable energy through the development of biorefineries. The manuscript explores the biochemical composition of food waste, with carbohydrates, lipids, proteins, and bioactive materials, making it a suitable feedstock for different multi-stage biorefinery operations. In addition, this review will evaluate a variety of existing conversion technologies for food processing waste, such as biological methods (e.g., anaerobic digestion and fermentation) and thermochemical methods (e.g., pyrolysis, gasification, and hydrothermal liquefaction), to create various platform chemicals, including organic acids, bio-alcohols and volatile fatty acids (VFAs), as well as the production of sustainable biofuels and biopolymers. The review also elucidates the three most determinative constraints on large-scale industrial implementation of food waste valorisation: feedstock variability, techno-economic feasibility, and the need for comprehensive life cycle assessments (LCAs). The alignment of food waste management strategies with the UN SDGs (in particular, SDG 12 ‘Responsible Consumption and Production’ and SDG 13 ‘Climate Action’) reflects the opportunity for food waste to serve as a foundation for a carbon-neutral, sustainable future. This review provides a strategic roadmap for academics, practitioners, and policymakers to tap into the full potential of food waste through a sustainable circular economy model. Full article

Brands increasingly rely on digital peer communication to promote environmentally friendly products. Whether electronic word-of-mouth (EWOM) actually shifts green purchase intention (GPI), though, is far from settled. Some studies have found no reliable word-of-mouth effect; others have examined green trust and anticipated guilt separately, leaving the joint operation of these parallel mediators poorly specified. This is especially true in Bali, Indonesia, where environmental pressures, heavy social media use, and Tri Hita Karana values coexist. Working under the stimulus–organism–response (SOR) framework, this study tests a dual-mediation model that routes EWOM to GPI through anticipated guilt and green trust among eco-conscious social media users. Survey responses from 393 participants were analysed with partial least squares structural equation modelling (PLS-SEM). EWOM related positively to GPI, directly and through both mediators. Anticipated guilt and green trust each partially mediated the effect, so the mediation was partial rather than full. The EWOM-to-guilt path was the stronger of the two. The EWOM-to-trust path was weaker, yet both mediators connected to GPI at similar strength. This study contributes a dual-pathway SOR specification by incorporating anticipated guilt into digital peer communication within a tourism-heavy cultural setting. Interpreted with caution, the pattern indicates that credible EWOM aimed at greener, more responsible consumption may operate through two mechanisms simultaneously, validating trust and prompting moral anticipation among digitally exposed, eco-conscious consumers. However, this interpretation still needs experimental and longitudinal testing before these relationships can be treated as causal. Full article

Efficient particle combustion is crucial for improving the overall performance of solid rocket ramjets. However, particle combustion is jointly constrained by multiple environmental factors, such as oxidizer supply, gas–solid transport, and residence characteristics, which are difficult to characterize using conventional mixing-ratio-based evaluations fully. To provide a diagnostic evaluation of particle combustion potential under complex flow-field organization during design and optimization, a thermal-environment-informed particle combustion index $I_{TPCI}$ is proposed in this study. The index incorporates oxidizer availability, particle–oxidizer transport, residence-related effects, gas thermal environment, and particle thermal reactivity, and is intended to indicate regions where particle oxidizer-consumption capability can be retained under favorable thermochemical conditions. The reacting duct case shows that $I_{TPCI}$ provides a combustion-potential-oriented description of particle consumption. In the canonical jet-interaction flow, the conventional mixing degree mainly identifies shear-layer-dominated transport boundaries, while $I_{TPCI}$ emphasizes the regions with particle-consumption potential. Application to the afterburner further shows that particle combustion potential is governed by the match among oxidizer supply, particle transport, residence condition, and thermal environment. The head region has favorable thermal and residence conditions but remains oxygen-lean, whereas the downstream regions receive additional oxidizer but are constrained by nonuniform oxygen–particle distributions, thermal environment, and residence time. In the pulsed-jet cases, the variation of $I_{TPCI}$ provides a diagnostic interpretation of changes in particle source-term distribution. For the present configuration, upstream pulsed actuation mainly enhances the head-region response, and the selected case increases the full-domain gaseous-product source term associated with boron combustion by 2.96%. These results indicate that the proposed index can support combustion-potential diagnosis and flow-control assessment in solid rocket ramjet afterburners. Full article

Counting electricity connections is easy. Understanding what those connections actually do for people is harder—and more important. This study examines how a 450 kWp Smart Grid Hybrid Microgrid on Semau Island, East Nusa Tenggara, Indonesia, shaped the daily lives and economic futures of a community in one of the country’s most geographically isolated 3T territories (Frontier, Outermost, Underdeveloped), using a sequential explanatory mixed-methods design (SEM-AMOS, n = 123; key informant interviews, n = 4)—and we find that forty percent of households have shifted from passive consumption to productive agricultural use within five years of grid connection, a rate that challenges common assumptions about rural electrification in eastern Indonesia. The data also reveal a troubling pattern at the heart of Indonesia’s subsidy architecture: the 450 VA tier, which absorbs the highest per-kWh State Budget subsidy (IDR 10,518/kWh; 96.2% of Cost of Supply), is associated with the weakest welfare returns. Meanwhile, an estimated IDR 1.87 billion per year in lost capacity—a figure we term the Governance Maintenance Loss (GML)—is linked to governance shortfalls rather than hardware failure. SEM-AMOS results (χ²/df = 1.613; RMSEA = 0.049; CFI = 0.973; TLI = 0.983; SRMR = 0.043) indicate that, among the constructs examined, Energy Diversification Policy shows the strongest association with community welfare (β = 0.718, p < 0.001)—more so than the physical infrastructure itself. In response, this study proposes three governance instruments: the MIDEK framework, a Knowledge Transfer Mandate (KTM), and a Productive Energy Tariff (PET). Together, these tools offer a replicable, low-cost pathway for Indonesia’s 1200 planned island installations under Presidential Regulation No. 112/2022—one that is simultaneously revenue-positive for PLN, budget-positive for the State, and welfare-positive for the communities these systems are meant to serve. Full article

Asymmetric diurnal warming is a salient feature of global climate change, and its reshaping of hydrological and carbon processes in terrestrial ecosystems has attracted increasing attention. Water use efficiency (WUE), defined as the ratio of gross primary productivity to evapotranspiration, serves as a key indicator coupling vegetation water consumption with carbon sequestration; however, how daytime and nighttime warming directly and indirectly drive divergent WUE responses through soil moisture and evapotranspiration pathways—and whether these responses are governed by soil-moisture thresholds—remains insufficiently explored in arid grasslands. In this study, the arid and semi-arid grasslands of northern Xinjiang were selected as the study area, and the spatiotemporal heterogeneity of diurnal land surface temperature, evapotranspiration components, soil moisture, and WUE during the growing season was systematically analyzed to identify the key hydrological factors and driving pathways through which diurnal warming regulates WUE. The results showed that: (1) nighttime warming in the grasslands of northern Xinjiang was significantly stronger than daytime warming during the study period, with significant nighttime warming (p < 0.05) detected over 86.31% of the area, far exceeding the 16.62% observed for daytime warming, and the diurnal temperature range narrowing continuously at a rate of 0.02 °C per year; (2) over the same period, WUE exhibited an overall non-significant declining trend with pronounced spatial heterogeneity, with areas of significant increase concentrated in the Junggar Basin, whereas areas of significant decrease were clustered on the northern slope of the Tianshan Mountains, reflecting divergent evapotranspiration and productivity responses under contrasting moisture regimes; (3) LAI emerged as the most critical independent factor regulating WUE variation, with daytime warming exerting a significant negative effect on WUE primarily by depleting soil moisture, suppressing LAI, and intensifying vapor pressure deficit-driven evapotranspiration stress, whereas nighttime warming across the broader region exerted a positive compensatory effect by promoting LAI growth and sustaining soil moisture availability; (4) these pathway reversals are governed by a soil-moisture threshold: in the arid basin where WUE increased significantly, the effects of nighttime warming on soil moisture and LAI shifted from promotive to inhibitory, and the direct effect of daytime warming likewise reversed from positive to negative, revealing that the apparent WUE increase reflects a passive hydrological response in which transpiration is preferentially suppressed under severe water deficit rather than an improvement in ecosystem function. These findings demonstrate that diurnal warming effects on grassland water use exhibit pronounced soil-moisture threshold dependence and spatial heterogeneity. Our study highlights that substituting daily mean temperature for separate daytime and nighttime temperatures masks the opposing effects of asymmetric warming on coupled water consumption and carbon processes, and underestimates the sensitivity of arid grassland hydrological cycles to climate warming. This study provides a new mechanistic basis for optimizing parameters in carbon–water cycle models and for differentiated water resource management in arid grassland regions. Full article

The cement industry, responsible for 26% of industrial CO₂ emissions and 8% of global emissions, is under growing pressure to reduce its environmental footprint while maintaining profitability. In this context, optimizing grinding processes is essential to enhance both the efficiency and sustainability of cement production. This study presents the development of a self-adaptive expert system for closed-loop control, integrating symbolic Artificial Intelligence (AI) and Advanced Process Control (APC) techniques. The system dynamically adjusts operational parameters in real time to minimize the specific energy consumption of cement grinding while meeting quality targets. Notably, it enables autonomous plant operation without direct human supervision, thereby reallocating personnel to higher-value tasks and maintaining optimal performance continuously. The benefits observed following industrial implementation are discussed, alongside an analysis of the key factors influencing grinding performance and productivity. Furthermore, the integration of Artificial Neural Networks (ANNs) and genetic algorithms is proposed as a future enhancement, complementing the expert system through neuro-symbolic approaches. This fusion represents a significant step toward the digital transformation of industrial operations. Full article

This article presents an Artificial Intelligence and Internet of Things (AI–IoT/AIoT) decision-making framework for smart water management and sustainable aquaponic systems. The framework connects sensors, IoT telemetry, machine learning algorithms, and real-time monitoring of key water quality parameters, with the aim of early detection of deviations, operational decision support, and risk reduction in system management. A special contribution of the paper is that water is viewed simultaneously as a limiting resource, a biological factor and an operational cost. The proposed framework defines the structure of a decision support system, including monitoring of temperature, pH value, dissolved oxygen, ammonia/ammonium, EC/TDS value, water flow, feeding regime, and basic biological indicators. In the methodological sense, the paper presents a conceptual-methodological framework based on publicly available data, scenario estimates, and a clearly defined protocol for future pilot validation of high-frequency operational data. In addition to the technical architecture, the framework includes elements of responsible application of AIoT systems: data quality control, sensor deviation and drift detection, model explainability through XAI/SHAP, data transfer security, and the possibility of human confirmation before risky interventions. The economic part of the paper shows ROI/NPV as a scenario estimate, based on explicit assumptions about costs, resource consumption and possible operational savings, and not as a confirmed financial result. The framework is aligned with the principles of the circular bioeconomy, as it links the monitoring of water quality, the reduction in nutrient losses, the reuse of resources, and better planning of interventions in aquaculture and aquaponics. The results indicate the potential of AIoT approaches to improve monitoring, transparency and operational decision-making, while the actual effects on productivity, water consumption, food consumption, energy, and economic sustainability must be confirmed in a pilot phase. Full article

Branch retinal vein occlusion (BRVO) is a retinal vascular disorder characterized by ischemia and hypoxia. These pathological conditions contribute to retinal pigment epithelial (RPE) cell injury through oxidative stress and ferroptosis. However, whether baicalin (BC) protects against hypoxia-induced RPE injury remains unclear. CoCl₂-induced hypoxic ARPE-19 cells were used to evaluate the protective effects and potential mechanisms of BC. BC improved cell viability and reduced LDH release under hypoxic conditions. BC markedly suppressed hypoxia-induced inflammatory responses, as evidenced by reduced p65 and ICAM-1 expression and decreased release of pro-inflammatory cytokines. Moreover, BC alleviated oxidative stress by reducing ROS and MDA accumulation and restoring SOD and GSH activity. BC attenuated mitochondrial dysfunction, accompanied by restoration of mitochondrial membrane potential, oxygen consumption rate (OCR), and ATP production. Transmission electron microscopy (TEM) results further confirmed the protective effect of BC on mitochondrial integrity. Mechanistically, BC suppressed ferroptosis by reducing intracellular Fe²⁺ accumulation and lipid peroxidation, accompanied by downregulation of TFR1, ACSL4, and p53, as well as upregulation of SLC7A11 and GPX4. These findings suggest that BC protects ARPE-19 cells against hypoxia-induced injury through preservation of mitochondrial function and inhibition of ferroptosis. Full article

Seaweeds are valuable marine resources rich in polysaccharides and polyphenols. Carbon dots (CDs) from Gracilaria salicornia (GS-CDs), Halymenia dilatata (HD-CDs), Sargasum polycystum (SP-CDs), Spatoglossum asperum (SA-CDs), Ulva lactuca (UL-CDs), and Caulerpa peltata (CP-CDs) were synthesized by a hydrothermal process and characterized by FTIR, XPS, and SEM-EDX. All the CDs had sizes less than 10 nm with spherical morphology and various functional groups. UL-CDs showed the strongest UV-A blocking efficacy via the measurement of light transmission (p < 0.05). HD-CDs exhibited the highest DPPH-RS-A (148.32 ± 1.51 μmol TE/L) and FRA-P (717.24 ± 7.87 μmol TE/L), whereas SA-CDs had the highest ABTS-RS-A (1043.40 ± 3.00 μmol TE/L). HD-CDs had antifungal activity against both Aspergillus flavus and Aspergillus parasiticus. All CDs suppressed the proliferation of both pathogenic and spoilage bacteria; however, high MIC values indicated the limited antibacterial effectiveness. CDs up to 500 mg/L maintained cell viability greater than 80% towards normal BJ cells. When SA-CDs (500 ppm) were incorporated into peeled and deveined Pacific white shrimp (Litopenaeus vannamei), lipid peroxidation during 10 days of refrigerated storage was retarded, as evidenced by lower PV, TBARS, and greater PUFA retention than the control and ascorbic acid-treated samples. Heat map and PCA analyses revealed that lipid oxidation was governed by CD type and storage time. Full article

Baobab fruit (Adansonia digitata L.) has attracted increasing attention due to its nutritional value and potential as a functional food ingredient; however, its acceptance among European consumers remains poorly understood. This study investigated sensory drivers of liking, consumer segmentation, and behavioural responses towards baobab fruit pulp in a Portuguese convenience sample of adults. Sensory attributes were evaluated using a 9-point hedonic scale, alongside measures of intended consumption frequency and willingness to pay. Overall liking indicated moderate acceptance (median = 6; IQR: 3–7). Multiple linear regression identified taste as the main driver of liking (β = 0.362, p < 0.001), followed by texture (β = 0.182, p = 0.042) and acidity (β = 0.105, p = 0.045), explaining 82.3% of the variance in overall liking. Cluster analysis revealed two consumer segments: low-liking consumers (n = 70; median = 4) and high-liking consumers (n = 47; median = 8). High-liking consumers reported significantly greater intended consumption frequency and willingness to pay (p < 0.01). These findings highlight the importance of sensory optimisation and consumer heterogeneity in supporting consumer acceptance of baobab fruit pulp and informing future product development in European markets. Full article

Exhaust gas temperature is a critical indicator of combustion efficiency and waste heat recovery in regenerative aluminum smelting furnaces, directly governing the energy intensity and carbon footprint of secondary aluminum production—a cornerstone of the circular economy. However, accurate prediction is challenged by pronounced long-range thermal lag and dynamically evolving spatial dependencies among process variables during operational transitions, which hinder real-time process optimization for energy savings. To address these challenges and advance sustainable manufacturing, a novel prediction model termed ChronoClassGAT (Chronological Class-aware Graph Attention Network) is proposed in this paper. The model integrates three key components: (1) a Temporal Convolutional Autoencoder (TCN-AE) with a Gaussian Mixture Model (GMM) for unsupervised identification of distinct operating regimes, providing categorical priors for dynamic graph construction; (2) a multi-graph fusion mechanism that builds operating-condition-specific spatial structures, enabling a Graph Attention Network (GAT) to adaptively model evolving inter-variable dependencies; and (3) a ChronoSwish activation function that modulates LSTM-based temporal encoding with time-aware periodic and switching signals, enhancing responsiveness to transient dynamics. Validated on real-world industrial datasets, ChronoClassGAT achieves superior prediction accuracy (RMSE of 2.2712, MAE of 1.8023, and $R^2$ of 0.9985) over state-of-the-art baselines. By enabling precise and robust exhaust gas temperature forecasting, our framework provides the decision-support intelligence needed for optimizing regenerator switching, minimizing thermal losses, and reducing fuel consumption, thereby contributing significantly to the operational energy efficiency and environmental sustainability of the energy-intensive non-ferrous metal industry. Full article

As online luxury fashion resale platforms continue to emerge and expand, persistent challenges related to trust and product authenticity have become increasingly pronounced. digital product passports (DPPs) offer a potential solution to these trust-related challenges by providing detailed information about a product, thereby enhancing product transparency and traceability throughout the product lifecycle. Drawing on signaling theory, this study investigates how DPP-enabled platforms influence consumers’ purchase intentions toward luxury fashion resale consumption. An online survey generated 307 valid responses. Structural equation modeling (SEM) was employed to test the proposed hypotheses. A multi-group chi-square difference test was also conducted to test the moderating role of DPP usage experience. The results demonstrate that trust and attitude are decisive predictors of consumers’ intention to purchase second-hand luxury fashion products from DPP-enabled platforms. Risk reduction alone does not directly drive intention, highlighting the distinction between eliminating uncertainty and fostering positive motivation. This study focuses on consumer perception and intention regarding DPPs within the luxury fashion resale market, an area that has received limited empirical attention. By integrating signaling theory with fashion resale and digital innovation, this study offers novel insights into the role of technological transparency in driving consumer engagement in circular fashion. Full article

Proper substrate moisture management is essential for producing high-quality seedlings in nurseries. This study aimed to evaluate the morphological and physiological quality of lettuce (Lactuca sativa L.) and tomato (Solanum lycopersicum L.) seedlings subjected to different substrate moisture levels, monitored by weighing lysimetry under protected environment conditions. Four experiments were conducted over two growing seasons (2019 and 2020) using six irrigation treatments corresponding to 80, 70, 60, 50, and 40% of the substrate water-holding capacity, in addition to the conventional irrigation management adopted by the grower (Control). Water consumption, morphological traits, root architecture, gas exchange, chlorophyll fluorescence, and photosynthetic pigments were assessed. Cumulative irrigation water applied ranged from 77 to 92 mm in lettuce and from 91 to 132 mm in tomato. Reducing substrate moisture to 40% negatively affected seedling growth, root development, and physiological performance in both species. In tomato, stomatal conductance decreased by up to 90%, accompanied by a decline in Fv/Fm from 0.78 to 0.70. Both lettuce and tomato tolerated moderate reductions in substrate moisture (60–70% holding capacity) without significant losses in growth or gas exchange performance. However, the highest seedling quality was achieved under the grower-managed Control and the 80% substrate moisture treatment, although the traits contributing to this response differed between species. In lettuce, favorable performance was associated with growth, pigment-related traits, and photochemical efficiency, whereas in tomato superior seedling quality was linked to shoot growth, root development, and gas exchange characteristics. These findings support the use of species-specific irrigation strategies to improve seedling quality in nursery production. Full article

Background: Endothelial dysfunction is a key feature of diabetic vascular disease and is associated with high-glucose-induced changes in endothelial energy metabolism and redox balance. Transglutaminase-2 has been implicated in vascular stress responses, but its contribution to endothelial adaptation to high glucose remains incompletely defined. Methods: EA.hy926 endothelial cells were cultured under normoglycaemic (NG) or high-glucose conditions and treated with LDN-27219 at 20 µg/mL (48.9 µM). Cellular reducing capacity, total protein content, mitochondrial respiration, MitoSOX Red fluorescence, and selected cytokine and adhesion-marker secretion were assessed. Results: High glucose shifted cells toward a more glycolytic basal phenotype, increased MitoSOX Red fluorescence, and reduced glycolytic stress responsiveness compared with NG conditions. LDN-27219 had limited effects under NG conditions but, under high-glucose conditions, reduced basal respiration, maximal respiration, ATP-linked oxygen consumption, and spare respiratory capacity, while partially restoring stressed extracellular acidification. LDN-27219 also reduced high-glucose-induced MitoSOX Red fluorescence, although this cannot be interpreted as definitive evidence of reduced mitochondrial superoxide production because mitochondrial membrane potential was not measured. No statistically significant changes were detected in the selected inflammatory or adhesion markers. Conclusions: LDN-27219 modifies endothelial bioenergetic and oxidant-associated fluorescence responses under high-glucose conditions. Full article