Search Results (36,893)

Edible insects have emerged as a sustainable source of high-quality proteins, lipids, and carbohydrates (including chitin), as well as micronutrients such as minerals and vitamins, and diverse bioactive compounds, thereby making them promising ingredients for functional food applications. Their favourable nutritional profile and low environmental footprint make them attractive ingredients for next-generation food systems. However, processing and preservation remain critical challenges, particularly with respect to the stability of bioactive compounds, lipid oxidation, and protein functional properties such as solubility, emulsifying capacity, and water-holding capacity. This review critically examines recent advances in food processing technologies applied to edible insects, including drying, extraction, fermentation, and microencapsulation, with emphasis on their effects on bioactive compound retention and functional performance. The role of processing strategies in enhancing oxidative stability, protein solubility, emulsifying properties, and overall technological applicability is discussed, alongside safety, regulatory, and consumer acceptance considerations. Overall, this review highlights key technological pathways for the effective valorisation of insect-derived ingredients and outlines future directions for their integration into sustainable and functional food products. In contrast to previous reviews, this work provides a comparative and mechanism-oriented analysis of processing methods, highlighting inconsistencies across studies and identifying key technological trade-offs. Particular attention is given to the relationship between processing parameters and the stability of bioactive compounds. Full article

In the context of occupational environments and sustainable employment, this review explores the effects of declining workers’ health, environmental degradation, and the depletion of marine resources on workers’ psychological well-being. As seas and oceans are increasingly exploited and used as dumping sites for both solid and liquid waste, marine ecosystems are severely degraded, with negative impacts on biodiversity, water quality, and ecosystem processes. Marine biodiversity is crucial to maintaining global food security and supporting the livelihoods of millions of people worldwide. Moreover, this study examines the role of digital technology in the marine industry in safeguarding workers’ sustainable well-being. It emphasizes the complementary roles of law and technology in promoting it. The risks to the health and well-being of marine workers are greatly increased by the occupational consequences of climate change on the sustainable environment and the effects of working in marine environments. Working conditions, incomes, and even unemployment among marine workers have been directly affected by the degradation of marine environments and the depletion of marine resources. Anxiety, panic, depression, rage, and other unpleasant emotions that affect workers’ health and pose mental health risks are detrimental to the psychological well-being of marine workers. The challenges of employment in the marine industry adversely affect the physical and mental well-being of marine employees and hinder economic growth. However, digital technology in marine environments has fundamentally altered the regulations governing marine operations. Full article

The environmental challenges posed by heavy metal contamination in sludge leachate are becoming increasingly severe, necessitating the development of highly efficient remediation technologies. Among various treatment approaches, magnetic adsorbents have garnered significant attention as a promising solution due to their outstanding adsorption performance, convenient magnetic separation characteristics, and potential for regeneration. This paper systematically reviews the latest research progress on magnetic adsorbents designed for the complex system of sludge leachate, covering synthesis methods, surface functionalization, adsorption mechanisms, and performance evaluation. Key synthesis strategies are analyzed, including magnetic core preparation, inorganic coating, carbon composites, organic polymer grafting, functional molecule impregnation, and metal–organic framework (MOF) composites. The mechanisms by which these strategies influence material adsorption capacity, selectivity, and stability are elucidated. Despite significant achievements in laboratory studies, practical applications still face challenges such as large-scale synthesis, regeneration efficiency, cyclic stability, and adaptability to complex water bodies. Future research should focus on green synthetic pathways to advance the industrial application of structurally functional magnetic composite materials, providing systematic solutions from material design to process optimization for the sustainable remediation of heavy metal contamination in sludge leachate. Full article

This study addresses the increasing need to structure knowledge in the field of circular resource management, with a focus on energy efficiency and sustainable resilience. Previous studies have examined various taxonomies for the circular economy, yet a clear gap remains in understanding how energy efficiency and resilience serve as the main pillars for operational stability. This study is designed as a bibliometric analysis based on a selection of relevant scientific articles. The identified factors were extracted based on their frequency of occurrence in the literature and processed using statistical clustering techniques to group them into coherent categories. The results show that the field is defined by a set of interconnected factors that can be structured into distinct clusters, reflecting key dimensions such as operational performance, environmental impact, and system resilience. Specifically, the analysis demonstrates how energy-related attributes and resilience attributes act as stabilizing factors within closed-loop systems. Based on these findings, this study proposes a structured framework that organizes the identified factors into a clear configuration. This framework provides a reference point for researchers who aim to develop models in this area and for practitioners involved in the design and optimization of circular systems. This study contributes by offering a structured view of the field and by supporting the development of consistent analytical and decision-making approaches grounded in the necessity of balancing resource recovery with system stability. Full article

In light of the accelerating process of global urbanization, the quality of cultural ecosystem services (CES) in urban parks has become a core metric for efforts to promote urban livability and sustainable cities. However, previous research has failed to consider the differential impacts of the external environment across various travel scenes. In this study, 32 parks in Chengdu serve as the empirical data, and public CES perception data are extracted from social media comments via text mining. Based on a unified 15 min time threshold, we delineate the service scope for four travel scenes and employ geographically weighted regression and piecewise regression models to analyze the spatial heterogeneity, driving mechanisms and threshold effects associated with the relationship between external environmental factors and park CES. The findings indicate that the external environment’s influence on CES exhibits a “scene-factor-scale” adaptation pattern. Walking scenes are influenced primarily by land-use and population factors; in contrast, cycling scenes rely on the availability of shared bicycle facilities, and public transport and driving scenes are driven by economic vitality and traffic-support factors, respectively. Five critical thresholds are identified, including a 40% impervious surface area. This research proposes scene-based optimization strategies and helps enhance the “external environment–travel behavior–spatial characteristics” coupling framework, thereby serving as a scientific reference for efforts to improve 15 min living circles. Full article

Socio-environmental conflicts in mining regions are often examined through political, economic, or social lenses, while the role of land-system transformation remains less integrated into quantitative analysis. This study examines the co-evolution of socio-environmental conflict and territorial change in Las Bambas (Apurímac, Peru) as a socio-territorial process. Annual conflict records from the Peruvian Ombudsman’s Office (2007–2024) were combined with annual land-cover data from MapBiomas. Yearly conflict influence zones were reconstructed from reported affected communities and geographic features using buffered spatial entities and concave hull polygons. Clustering methods (K-medoids, DBSCAN, and agglomerative hierarchical clustering) and FP-Growth association rule mining were applied to 23 unique conflicts consolidated from the original records and encoded with 10 root causes. The most intense conflict phases were accompanied by measurable landscape transformations, including the emergence of mining-related land cover from 2012 onward, sustained loss of high-Andean natural vegetation, expansion of agricultural mosaics, urban growth along the Apurímac–Cusco corridor, and hydrological alterations in wetlands and headwaters. Three conflict typologies were identified, with unfulfilled company commitments emerging as the most recurrent co-occurring grievance. The dynamic polygon approach offers a replicable framework for linking conflict records with land-system change in extractive regions. Full article

The high accuracy achieved by deep learning techniques has made them indispensable in computer vision applications. However, their substantial memory demands and high computational complexity limit their deployment in resource-constrained environments. To address this challenge, this study introduces a Feature Enhancement Module (FEM) as part of a unified hybrid compression framework that combines mixed-precision quantization and structured pruning to improve model efficiency. Experimental results on the Tiny ImageNet dataset using ResNet50 and MobileNetV3 architectures demonstrate the strong adaptability and scalability of the proposed approach. Compared with state-of-the-art compression methods, the proposed FEM-based framework achieves up to 6% improvement in Top-1 accuracy, while reducing memory usage by 32.26% and improving inference speed by 66%. Furthermore, the ablation study demonstrates that incorporating the FEM module leads to up to 24% improvement over the baseline model, highlighting its effectiveness. The results further show that FEM effectively preserves inter-channel feature representation stability even under aggressive compression, making it well suited for real-time processing and practical Artificial Intelligence (AI) applications. By maintaining semantic richness while significantly reducing computational cost, the proposed method bridges the gap between high-performance deep models and lightweight, deployable solutions. Overall, the FEM-based hybrid compression framework establishes a scalable and architecture-independent foundation for sustainable deep learning in resource-limited environments. Full article

Sustainable sourcing of bioactive ingredients is an important direction in the development of topical formulations. Fruit by-products generated during food processing such as apple pomace, represent a promising resource for skincare applications. The aim of this study was to evaluate the safety, effectiveness, and consumer perception of a three-step facial skincare regimen consisting of a cleansing gel, serum, and face cream containing upcycled apple pomace extract. Unlike most cosmetic studies focusing on single products, this research assessed a complete skincare routine to better reflect real-life usage conditions. All formulations underwent dermatological safety evaluation prior to the in vivo study. The clinical assessment was conducted on 30 healthy female volunteers aged 25–55 years. Skin hydration, pH, transepidermal water loss, sebum level, and skin gloss were measured on untreated skin, after the first use, and after four weeks. User perception was assessed using a questionnaire completed by 58 participants. Short-term changes in skin parameters were observed after application, while four weeks of use maintained them within physiological ranges. Skin gloss increased significantly by 4.2%, and no adverse reactions were reported. These results indicate that the tested skincare regimen containing apple pomace extract was well-tolerated and cosmetically acceptable under the study conditions. Full article

Agrivoltaics (AV) has emerged as an integrated land-use innovation capable of simultaneously addressing food, energy, and water challenges, yet its systemic implications for farming system sustainability remain insufficiently synthesized. This review adopts a farming system dynamics perspective to examine how AV systems reorganize biophysical, ecological, and socio-economic interactions across agroecosystems. Drawing upon agroecological principles, pathways of sustainable intensification and ecological intensification, and resource-loop strategies in circular economy, we identify the key elements and cause-and-effect relationships that shape AV system performance. Evidence indicates that the co-location of photovoltaics (PV) structures and crop cultivation generates new system properties, altered light distribution, moderated microclimates, redistributed soil moisture, and diversified production functions that influence productivity, resource-use efficiency, ecological services, and farm resilience. Using causal loop analysis, we conceptualize four central feedback dynamics: (i) PV–crop trade-offs and spatial-sharing relationships; (ii) microclimate modifications and crop physiological responses; (iii) ecological performance and landscape-level interactions; and (iv) circularity loops connecting resource conservation, renewable-energy substitution, soil processes, and material flows. This feedback collectively determines eco-efficiency outcomes, including enhanced land-equivalent productivity, improved water-use efficiency, strengthened regulating services, and reductions in external energy dependence. At the farming-system scale, AV diversifies income streams and stabilizes yields under climatic variability, whereas at the landscape scale, it fosters multifunctionality by supporting regenerative resource flows and ecological resilience. Building on these insights, we propose an integrated framework that links agroecological elements with dynamic feedback structures to guide context-specific AV design, management, and governance. This system-oriented synthesis provides a foundation for future research and policy efforts aimed at optimizing AV as a circular, resilient, and sustainable farming system innovation. Full article

Conductive core–shell superabsorbent polymers (SAPs) are emerging as multifunctional additives for cementitious materials, combining moisture management with electrical functionality. In cement-based systems, a swellable polymeric core enables internal curing and crack-sealing through controlled water uptake and release, while a conductive shell introduces ionic and/or electronic charge transport, addressing key limitations of conventional non-conductive SAPs. This dual functionality provides a pathway toward smart cementitious composites with enhanced durability, self-sensing capability, and moisture-responsive behavior. This review focuses on the physical chemistry mechanisms governing conductive core–shell SAPs in cementitious environments, with emphasis on swelling thermodynamics, water transport kinetics, interfacial phenomena, and charge transport mechanisms. The roles of osmotic pressure, elastic network constraints, ionic effects, and pore solution chemistry are critically discussed, together with their impact on conductivity, hydration processes, microstructure development, and long-term performance. The relative contributions of ionic and electronic conduction are examined in relation to hydration state, shell morphology, and percolation of conductive networks. In addition, the relevance of core–shell SAP architectures to sustainable packaging is briefly discussed as a secondary application, illustrating how similar physicochemical principles—such as moisture buffering and functional coatings—apply beyond construction materials. Finally, key knowledge gaps are identified, including long-term stability in highly alkaline environments, trade-offs between swelling capacity and conductivity, environmental impacts of conductive phases, and the need for integrated experimental and modeling approaches. Addressing these challenges is essential for the rational design and practical implementation of conductive core–shell SAPs in next-generation cementitious materials. Full article

Background/Objectives: Endophytic fungi represent an alternative source for resveratrol (RES) production. The present study aims to utilize mycoendophytic-derived resveratrol as a reducing agent for the synthesis of silver nanoparticles (AgNPs), in addition to further assay the cytotoxic activity of a RES-conjugated nanocarrier system toward human epidermoid carcinoma A-431 cells. Methods: Alternaria alternata AUMC 16209 was isolated from the stem of grapevine Vitis vinifera L. cultivar prime. Strain identification was achieved through morphological and molecular characterization using ITS sequencing. A. alternata AUMC 16209 exhibited RES production capability upon cultivation on PDB medium for seven days with a total of 8.25 mg/L as determined by HPLC. The crude RES was purified using flash chromatography followed by structure elucidation through ¹H and ¹³C NMR analyses. The purified RES was used for green synthesis of nanoparticles, acting as a reducing agent for silver ions. Results: Stable RES-AgNPs were fabricated at particle sizes ranging from 25 to 47 nm. RES-AgNPs observed a plasmon resonance absorption band at 415 nm with a negative zeta potential value of −38.5 mV. The crystalline structure of RES-AgNPs was addressed through X-ray diffraction analysis. FT-IR spectroscopy confirms the involvement of the functional –OH group and the aromatic C=C bond in the reduction and stabilization process. RES-AgNPs was more efficient to inhibit the cellular proliferation of human epidermoid carcinoma A-431 cells compared to RES alone. Conclusions: This report introduces for the first time an endophytic A. alternata as a sustainable source for RES production and emphasizes its potential for green synthesis of stable AgNPs with promising cytotoxic activity. Full article

The use of renewable energy sources instead of conventional ones, together with the development of efficient electricity storage solutions, represents a central objective of the transition to sustainable and resilient energy systems. In this context, two main development directions are the integration of hydrogen in the energy chain (Power-to-Gas) and the use of batteries, each with specific advantages and disadvantages, compared to internal combustion engines. The purpose of this work was to evaluate the dynamic response time of a hydrogen fuel cell model powered by green hydrogen, under conditions of sudden and instantaneous power demand, for its integration into wind-based renewable energy systems. Experimental research was carried out on an autonomous installation designed to operate continuously for an unlimited duration, simulating the integration of hydrogen produced from wind sources. The novelty consists of the application of an instrumental method for automatic measurement of the response time of a proton exchange membrane hydrogen fuel cell, based on the automatic acquisition and processing of measured electrical signals. The response time of the fuel cell was compared with that of an internal combustion engine based on the classic Carnot cycle, using a dedicated oscilloscope. The load connection time, the current and voltage variation as a function of time were recorded simultaneously. The results show that the response time of the fuel cell is relatively short (approximately 0.3 ms), much lower than that of the internal combustion engine (0.7 s), being of the order of about 2333 times smaller. In conclusion, the hydrogen fuel cell can be effectively integrated into renewable energy systems for the role of an uninterruptible power supply, with an exceptionally fast dynamic response, suitable for applications in regulating and supporting wind-powered networks. Full article

Ceramics are widely evaluated for their extreme hardness, high-temperature stability, and corrosion resistance, which enable applications in harsh service environments. However, these same properties, high melting points, brittleness, and low thermal shock resistance, make conventional manufacturing of complex ceramic components difficult and expensive. Traditional processes often require costly diamond tooling or energy-intensive sintering and tend to produce only simple geometries, with significant waste material and risk of defects. Additive manufacturing (AM) has recently emerged as a promising route to fabricate intricate, near-net-shape ceramic parts without these drawbacks. By building components layer by layer, AM reduces the need for extensive machining and enables the fabrication of geometrically complex, near-net-shape ceramic structures with reduced material waste, although challenges such as porosity, interlayer defects, and cracking during post-processing remain. Nonetheless, ceramic AM technologies lag behind their metal and polymer counterparts, and significant challenges remain in achieving fully dense parts with reliable mechanical properties. This review provides an in-depth overview of the state of the art in ceramics and ceramic composite additive manufacturing. We detail the most widely used AM processes (stereolithography, binder jetting, material extrusion, powder bed fusion, inkjet printing, and direct energy deposition) and typical feedstock formulations for each technique. We examine the resulting mechanical properties (strength, toughness, hardness, wear resistance) and functional properties (thermal stability, dielectric behavior, biocompatibility) of additively manufactured ceramics, and discuss their current and potential engineering applications in the aerospace, defense, automotive, biomedical, and energy sectors. Persistent challenges, including porosity, shrinkage and cracking during sintering, achieving uniform microstructures, high process costs, and scalability issues, are analyzed, and we highlight promising future directions such as multi-material grading, integration of machine learning for process optimization, and sustainable manufacturing approaches. Despite significant progress, challenges remain in achieving fully dense structures, improving process reliability, and scaling ceramic AM for industrial applications, highlighting the need for further research in process optimization, material design, and multi-material integration. Full article

This is a narrative conceptual paper, not a systematic review. Ultrasound-guided fascial hydrorelease (FHR) has been reported to provide sustained pain relief in patients with chronic musculoskeletal pain; however, its underlying biological mechanisms remain incompletely understood. In this paper, we propose the “Fascial Memory Reset Hypothesis” as an integrative framework linking mechanobiology, extracellular matrix (ECM) remodeling, peripheral nociception, microcirculatory dynamics, and ultrasound imaging findings. Mechanobiological research has demonstrated that increased tissue stiffness activates YAP/TAZ signaling, promoting fibroblast activation, ECM deposition, and mechano-epigenetic regulation. These mechanically driven processes can stabilize pathological tissue phenotypes without DNA sequence alterations. The “Fascial Memory Reset Hypothesis” proposes that targeted mechanical interventions such as FHR may partially reverse these mechanically maintained states by restoring tissue mobility and modifying stiffness-dependent mechanotransduction. We propose that “stacking fascia” (observed as layered hyperechoic bands on ultrasound) represents the macroscopic structural phenotype of mechano-epigenetic memory formed through sustained mechanical stress. Integrating molecular mechanotransduction pathways, mechano-epigenetic mechanisms, neural sensitization, and vascular factors, we propose that FHR may hypothetically partially normalize pathological fascial states by mechanically restoring tissue mobility and modifying stiffness-dependent signaling. Although direct molecular evidence of the effect of FHR in human fascia remains limited, this hypothesis provides a biologically plausible link between mechanical stress, ultrasound-visible structural alterations, and sustained clinical improvement. Full article

Accurate prediction of effluent water quality is essential for the intelligent and sustainable operation of wastewater treatment plants (WWTPs). However, this task remains challenging due to the strong nonlinearity, long-term temporal dependencies, and severe fluctuations inherent in influent characteristics. In this study, a novel data-driven framework termed the Multi-Scale Temporal Representation-Enhanced Informer (MTRE-Informer), is proposed to predict key effluent quality indicators, including total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD). To ensure data quality and computational efficiency, a generative recurrent learning framework is first employed for anomaly detection and correction, followed by variance inflation factor (VIF)-based feature selection to mitigate multicollinearity. Furthermore, feature contribution analysis is conducted to improve model interpretability. Subsequently, the core MTRE-Informer architecture utilizes hierarchical multi-scale temporal representation learning to simultaneously capture local patterns and long-term dependencies within the complex dynamics of the wastewater treatment process. Experimental results demonstrate that the MTRE-Informer achieves robust and stable predictive performance across diverse operational datasets. For TN prediction, the proposed framework attains a coefficient of determination () of 0.9637 and a mean absolute percentage error (MAPE) of 3.39%. Compared with baseline approaches, the improvement ranges from 3.8% to 14.2%, validating its superior capability. To further enhance model robustness, an anomaly detection and correction strategy based on a generative recurrent learning framework is employed. In addition, feature contribution analysis and VIF-based feature selection are conducted to improve interpretability, mitigate multicollinearity, and enhance computational efficiency. Overall, this framework provides a reliable and practical solution for real-time effluent quality prediction, facilitating the intelligent management of WWTPs. Full article