Search Results (18,202)

Retrieving aerosol optical depth (AOD) over land remains challenging because the relatively weak aerosol signal in top-of-atmosphere (TOA) observations must be separated from strong and spatially heterogeneous surface reflectance. Here, we develop a physically informed random forest framework for global 1 km land AOD retrieval from MODIS. The framework integrates multispectral TOA reflectance, surface properties, observation geometry, meteorological conditions, topography, and physically informed aerosol–surface features. Long-term Aerosol Robotic Network (AERONET) observations from 2001 to 2017 were collocated with MODIS and ancillary datasets for model development and evaluation. Two physically informed features were introduced to improve retrieval robustness across diverse aerosol and surface conditions, including minimum AOD derived from long-term AERONET observations and time-series clear-sky reflectance (TSCR) in the blue, red, and shortwave-infrared bands derived using the 6S radiative-transfer model. Independent retrieval evaluation for 2013–2014 showed good agreement with AERONET observations, with R = 0.81, MAE = 0.063, RMSE = 0.096, and 74.93% of matched samples falling within the MODIS land expected-error envelope, although increasing underestimation was observed at high aerosol loading (AOD > 1). The proposed retrievals also showed better agreement with AERONET than the MOD04 Dark Target and Deep Blue products. These results demonstrate the value of incorporating physically interpretable aerosol-background and surface-reflectance information into data-driven retrievals for AOD over land surfaces. Full article

This study investigates machine learning techniques for predicting the behavior of proton exchange membrane electrolyzers, which are vital for sustainable hydrogen production. This work addresses these challenges by integrating artificial neural networks to develop predictive models capable of capturing the performance of proton exchange membrane electrolyzers with high accuracy. This research utilizes a multi-layer perceptron network architecture, optimized through rigorous data preprocessing, parameter tuning, and error minimization strategies. The dataset used was based on published PEME numerical simulation datasets and encompasses key performance indicators, including stack voltage, water transport, and electrochemical reactions. The trained artificial neural networks models achieved mean squared error values of 3.66 × 10⁻⁵ and 9.75 × 10⁻⁶, with correlation coefficients of 0.99996 and 0.99958, demonstrating near-perfect predictive accuracy. A comparative benchmarking study against alternative regression algorithms revealed that the proposed MLP models significantly outperformed Gradient Boosting and Random Forest by several orders of magnitude, thereby establishing a higher level of persuasiveness and reliability for the developed framework. Average deviation rates of 0.11% and −0.01% further validated model reliability. The novelty of this work lies in its comprehensive approach, which goes beyond isolated metrics by addressing interactions across system parameters. This integrated framework enables enhanced prediction, control, and optimization of proton exchange membrane electrolyzer’s performance, setting a new benchmark for leveraging machine learning in hydrogen energy systems. These findings pave the way for scalable, cost-effective solutions to improve proton exchange membrane electrolyzers’ efficiency and operational reliability. Full article

In the context of the global green development wave and the rapid iteration of digital technology, digital empowerment has become the core driving force for high-end manufacturing enterprises to achieve green transformation. At present, China’s manufacturing industry is facing the dual pressures of tightening resource and environmental constraints and industrial upgrading. How to break the bottleneck of green development through digital technology innovation has become a key issue to be solved urgently. Based on the techno-economic paradigm, green development theory and value creation theory, this study constructs a theoretical analysis framework for the green development of a digital-enabling manufacturing industry and deeply analyzes the mechanisms of digital technology (such as big data, Internet of Things, artificial intelligence, etc.) in optimizing energy allocation, improving production efficiency and reducing environmental emissions. By selecting 303 manufacturing enterprises of different scales in China as samples, the structural equation model is used for empirical tests. The results show that (1) digital empowerment has a significant positive impact on the green value performance of manufacturing enterprises, and (2) green development plays an intermediary role between digital empowerment and the green value performance of enterprises; that is, digital technology indirectly promotes green development by improving energy conservation and emission reduction, green innovation and green upgrading of enterprises. The research reveals the internal logic of digitally enabling the green development of Chinese manufacturing enterprises and provides a theoretical basis and implementation path for enterprises to formulate the innovation mechanism of digital–green development. Full article

In this study, rapid-hardening sulfoaluminate cement (SAC) was used as cementitious material, and recycled fine aggregates (RFAs) were surface pretreated by immersion in nano-SiO₂ (NS) suspensions. NS-modified SAC recycled fine aggregate mortars were prepared at three cement–sand ratios (1:1, 1:2 and 1:3) to systematically investigate the regulatory effects of NS concentrations (0%, 1%, 2% and 3%) on macroscopic performance, hydration products and interfacial microstructure. Multi-scale characterizations, including XRD, TG-DTG, SEM-EDS and microhardness tests, were carried out. The testing results show that appropriate NS can optimize SAC hydration by heterogeneous nucleation and the pozzolanic reaction. At a cement–sand ratio of 1:1, the compressive and flexural strengths gradually increase as the NS concentration rises from 0% to 2%. Compared with the control group, the 28 d compressive and flexural strength are enhanced by 19.5% and 16.6%, respectively, the drying shrinkage decreases by 8.0%, and carbonation resistance is obviously improved. Meanwhile, the formation of AFt is promoted, amorphous C-S-H gel accumulates continuously, and the content of Ca(OH)₂ is gradually consumed by the pozzolanic reaction of NS. For specimens modified with 2% NS, the maximum microhardness reaches 1326 HV, which greatly benefits the mechanical properties of mortar. However, further increasing the NS concentration to 3% triggers nanoparticle agglomeration and reduces effective reactive silica, leading to a decline in hydration products, deteriorated interfacial compactness and reduced mechanical performance. Therefore, 2% can be determined as the optimal NS concentration which can provide a theoretical basis for high-value resource recycling of recycled fine aggregates in SAC mortar. Full article

Keratin is an abundant, recalcitrant structural protein that constitutes the primary component of several animal wastes, particularly chicken feathers. Because of their potential and availability, various technologies, such as anaerobic biodigestion, have been used to degrade keratin and transform feathers into biogas and other value-added products. However, due to their fibrous architecture and rigid structure, keratinous materials are elastic, water-insoluble, and enzymatically resistant, which makes natural degradation difficult. In this sense, before using chicken feathers as feedstock in biodigesters, the keratin in the residue must be cleaved in pretreatment steps. Whether as a single substrate or in co-digestion processes, the keratin breakdown is critical for enhancing biogas production from feathers. In this context, there is growing emphasis on developing pretreatment methods to facilitate protein hydrolysis and digestion, thereby improving biogas generation. To evaluate progress in recycling waste keratin, a bibliometric analysis of original scientific publications on the pretreatment of chicken feathers for anaerobic digestion was conducted using the Scopus database. The findings indicate that researchers apply chicken feathers in processes, including standard biodigestion, co-digestion with food waste, animal manure, and slaughterhouse waste, for biomethane and biohydrogen production. Across the evaluated studies, the pretreatment methods showed notable improvements in feather solubilization and subsequent biogas yield; however, they still encounter key limitations, including ammonia (NH₃) inhibition, high chemical/reagent costs, and high energy demand. Full article

The piezocatalytic activity of metal–organic frameworks (MOFs) is generally hampered by an insufficient intrinsic piezoelectric response, which largely restricts their application in energy catalytic conversion. Herein, MIL-125-NH₂(Ti) (denoted NM) was chosen as a prototypical model to demonstrate that defect engineering serves as an efficient strategy to simultaneously reinforce the piezoelectric characteristics and piezocatalytic hydrogen evolution performance of MOFs. Multiple comprehensive characterizations verify that thermally treated NM-250 (NM thermally treated at 250 °C under flowing N₂ atmosphere) contains abundant in situ-generated oxygen vacancies. These defects disrupt the high intrinsic structural symmetry of pristine NM and promote the establishment of polarized electric fields upon mechanical excitation. Electrochemical measurements further reveal that the introduced oxygen vacancies effectively suppress charge carrier recombination and accelerate interfacial charge transfer, thereby facilitating the piezocatalytic hydrogen evolution reaction. Benefiting from the optimized piezoelectric polarization and improved charge separation efficiency, NM-250 delivers a piezocatalytic H₂ production rate of 413.5 μmol g⁻¹ h⁻¹, exceeding the value of pristine NM (180.9 μmol g⁻¹ h⁻¹) by 2.28 times. This work elucidates the underlying mechanism by which oxygen vacancy defects modulate piezoelectric polarization and catalytic kinetics and validates defect engineering as a promising route to construct high-performance MOFs-based piezocatalysts. Full article

Oxidative stress is a key mechanism underlying nicotine-induced male reproductive dysfunction, yet evidence-based phytopharmacological interventions remain limited. Uncaria gambir Roxb., a catechin-rich medicinal plant from West Sumatra, Indonesia, exhibits strong antioxidant potential; however, a comprehensive multi-regional evaluation combined with in vivo androgenic assessment is lacking. This study aimed to characterize the antioxidant activity, phytochemical composition (HPLC-DAD), and antimicrobial properties of gambir extracts from three production regions (Halaban, Mungka, and Pesisir Selatan), to evaluate catechin pharmacokinetics in silico (PASS Online; SwissADME), and to assess dose-dependent effects in male Wistar rats exposed to nicotine (n = 36). The Halaban extract showed the highest antioxidant activity (IC₅₀ = 6.99 ± 0.28 µg mL⁻¹) and catechin content (7.91 ± 0.07 mg g⁻¹). All extracts demonstrated broad-spectrum antimicrobial activity. PASS analysis predicted strong membrane integrity agonism (Pa = 0.950) and HMOX1 induction (Pa = 0.778), while SwissADME indicated favorable pharmacokinetic properties, including full Lipinski compliance and high gastrointestinal absorption. In the in vivo study, gambir Halaban extract at 300 mg kg⁻¹ day⁻¹ significantly increased follicle-stimulating hormone, luteinizing hormone, and testosterone levels compared to controls (p < 0.05), exceeding baseline values and indicating HPG axis stimulation. A non-linear (hormetic) response was observed, with reduced efficacy at higher doses. These findings highlight bioactive-rich gambir as a promising multi-target natural antioxidant for mitigating oxidative-stress-related reproductive dysfunction, warranting further mechanistic and translational studies. Full article

Carminic acid (CA) is a high-value natural anthraquinone pigment used in foods, cosmetics, textiles, and pharmaceuticals, but its current industrial supply depends largely on extraction from the scale insect Dactylopius coccus, creating constraints in yield, cost, sustainability, and allergen control. This review summarizes recent progress from pathway elucidation to microbial production. We first outline the structure, occurrence, applications, and biosynthetic logic of CA, emphasizing the convergence of type III polyketide assembly with insect-associated tailoring reactions, especially C-glycosylation. We then compare heterologous production strategies in Escherichia coli, Saccharomyces cerevisiae, Yarrowia lipolytica, and Aspergillus nidulans, focusing on chassis-specific advantages, bottlenecks, precursor supply, malonyl-CoA engineering, dynamic regulation, enzyme compatibility, compartmentalization, and downstream processing. Structurally related anthraquinone pigments are further discussed to extract broader design principles for pathway diversification and synthetic biology. Finally, we highlight key challenges for industrial translation, including low titers, incomplete enzyme characterization, host–pathway incompatibility, and scalable purification, and propose integrated strategies combining precursor-pathway rewiring, AI-assisted enzyme engineering, biosensor-based regulation, and process optimization to develop competitive microbial cell factories. Full article

Low-glutamic-acid monosodium glutamate wastewater (L-MSGW), characterized by high (NH₄)₂SO₄ concentrations, presents significant challenges for conventional treatment. γ-Polyglutamic acid (γ-PGA) production using industrial wastewater is an economical and environmentally friendly strategy. In the current study, we isolated and identified Bacillus subtilis GB, which exhibited exceptional tolerance to (NH₄)₂SO₄, and capability for the high-efficiency biosynthesis of γ-PGA using untreated L-MSGW. Fermentation conditions were optimized using single-factor experiments coupled with response surface methodology, followed by scale-up validation in a 5 L fermenter. Under optimal conditions, the maximum γ-PGA yield reached 16.57 g/L with a minimal glutamate consumption of only 4.9 g/L. The study validated the feasibility of efficient γ-PGA production from L-MSGW by B. subtilis GB, providing a novel technical approach and theoretical basis for low-cost treatment and high-value resource utilization of L-MSGW. This study not only demonstrates the low-cost L-MSGW can be used for the high-value γ-PGA by B. subtilis GB but also provides a sustainable and economically viable solution for industrial wastewater treatment. Full article

Arachidonic acid (AA) is a high-value long-chain polyunsaturated fatty acid commonly produced by submerged fermentation of oleaginous fungi. Solid-state fermentation (SSF) using low-cost agro-industrial by-products represents a promising alternative approach for sustainable microbial lipid production. In this study, spent malt, a by-product of the brewing industry, was evaluated as a solid substrate for AA production by Mortierella alpina under SSF conditions. Four M. alpina strains were screened for growth, lipid accumulation, and AA production, and M. alpina 959 was selected as the most promising strain. The effects of nitrogen supplementation and oil incorporation on biomass formation, lipid accumulation, and AA productivity were subsequently investigated. Sunflower oil incorporation into spent malt-based substrates improved AA productivity under the most favorable conditions, resulting in an AA proportion of 38.6% of total fatty acids and 102.5 mg AA g⁻¹ of final dry mass of the SSF system (FDW-SC). Comparison of selected vegetable oils further demonstrated that the lipid source affected AA production, while having only a limited effect on fungal growth and total lipid accumulation. Overall, this study demonstrates the feasibility of spent malt-based SSF for AA production by M. alpina and highlights the valorization of brewery spent malt as a low-cost agro-industrial by-product for the production of value-added microbial lipids. Full article

Steel production contributes significantly to global resource consumption and accounts for nearly 8% of worldwide CO₂ emissions. As the construction industry moves toward decarbonization, the reuse of structural steel has emerged as a highly impactful strategy for reducing embodied carbon and extending material life cycles. However, most end-of-life structures are still demolished using conventional methods that prioritize recycling for scrap value rather than recovering reusable steel components, resulting in the loss of high-quality material and reduced environmental and economic benefits. Despite growing interest in circular construction, systematic analyses of real-world structural steel reuse projects remain limited. This restricts the understanding of the practical conditions required for scalable implementation. Moreover, there is a lack of structured approaches for identifying the factors influencing deconstruction and large-scale structural steel reuse across reverse supply chains. This study addresses these gaps by developing a framework of factors affecting efficient deconstruction and structural steel reuse, identified through a thematic analysis of the literature and structured around structure attributes, business attributes, value chain activities, project management, and regulations. Fifteen case studies were analyzed: two from North America, twelve from Europe, and one from Asia. A structural steel reuse classification model is introduced to support cross-case comparison of coordination demands, implementation barriers, and scalability potential within reverse supply chains. The results demonstrate that reuse pathways differ substantially in coordination requirements, implementation complexity, and scalability outcomes. They further indicate that the dominant challenges to structural steel reuse are no longer primarily technical, but instead stem from system-level coordination gaps, limited information availability, and insufficient integration across reverse supply chains. Based on these findings, targeted solutions are identified, including improved dismantling strategies, enhanced documentation systems, dedicated storage infrastructure, and stronger regulatory alignment. This study provides a structured analytical approach and practical recommendations to support decision-making, stakeholder coordination, and the scalable implementation of structural steel reuse. Full article

Polyphenol-rich pomegranate juice (PJ) has attracted growing interest in its health-promoting properties. However, most studies have focused on purified extracts rather than the whole beverage. Here, we evaluated the effects of whole PJ on gut microbiota composition and functionality using the Simulator of the Human Intestinal Microbial Ecosystem (SHIME^®). The PJ was characterized by a high polyphenol content (2.3 g/L) and largely dominated by anthocyanins (~98% of identified compounds), with ellagic acid derivatives and flavonols present at lower concentrations. Following 7 days of treatment in the SHIME^® model, PJ polyphenols exhibited a bioaccessibility of 20–30%, in agreement with data from the literature. PJ supplementation induced a time-dependent modulation of the gut microbiota, leading to enhanced microbial fermentation and increased SCFA production, particularly in the descending colon, where total SCFA levels surpassed baseline values and reached 100 mmol/L. Moreover, PJ promoted the enrichment of beneficial taxa, including Akkermansia, supporting the ability of the whole juice matrix to improve gut microbial composition and metabolic activity. Overall, these findings support the potential of whole pomegranate juice as a functional food capable of modulating gut microbiota composition and activity. Full article

Agricultural nonpoint source pollution mainly causes lake eutrophication in China, largely affected by variations in crop distribution. To analyze the multiscale relationships between the long-term evolution of cropping patterns and lake water quality at the macro scale, this study analyzed nationwide datasets for 2000 and 2020 covering 420 relatively large lakes. We systematically examined the spatial restructuring of six major food and cash crops—wheat, rice, maize, soybean, peanut, and rapeseed—and evaluated their multiscale associations with lake total nitrogen (TN) and total phosphorus (TP) concentrations and how these associations changed over time. The results showed the following: (1) From 2000 to 2020, the spatial distributions of the six major crops underwent substantial restructuring. The dominant production areas of rice, wheat, and maize were maintained or further reinforced, whereas soybean, rapeseed, and peanut exhibited varying degrees of regional redistribution and localized concentration. (2) Lake water quality differed between the flood and non-flood seasons. TN exhibited pronounced seasonal differences between the two study periods, whereas temporal changes in TP were generally limited; both nutrients nevertheless showed marked regional heterogeneity among the five major lake regions. (3) The crop–water quality relationship exhibits significant scale dependence and crop-specific variations. The XGBoost model demonstrated a certain degree of out-of-field (OOF) predictive capability for both TN and TP, with OOF R² values of 0.448 and 0.447, respectively. For TN, the highest OOF R² values were observed in the 1000–2000 m buffer zone in both 2000 and 2020; the optimal prediction scale for TP shifted from 1000–2000 m in 2000 to 2000–5000 m in 2020. SHAP results showed that corn maintained a high and relatively stable predictive importance in the TN model, followed by wheat, peanuts, and rice; in the TP model, corn and rapeseed were the crop predictors with the highest relative SHAP importance. PDP results further indicate that there are generally nonlinear or non-monotonic relationships between different crop coverage proportions and TN and TP. (4) Pronounced spatial heterogeneity was observed across the five lake regions. The Eastern Plain Lake Region was characterized by associations involving multiple crops, whereas maize was the most prominent crop in the Northeast Plain and Mountain Lake Region. In the Inner Mongolia–Xinjiang Plateau Lake Region, maize predominated, with wheat and rapeseed also showing notable importance. In the Tibetan Plateau Lake Region, TN was associated with multiple crops, whereas TP was primarily related to maize and rapeseed. The Yunnan–Guizhou Plateau Lake Region exhibited particularly strong scale-dependent differences. This study provides a nationwide analytical framework for comparing the scale differences and regional variations in the statistical associations between the spatial distribution of crops and lake water quality at the specific crop level. The findings can provide a scientific basis for formulating differentiated agricultural nonpoint source pollution control strategies that are adapted to the evolving characteristics of crop planting structures. 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

This research study focused on the use of technologies such as high-pressure processing (400 MPa for 15 min, HPP) and enzymatic hydrolysis (with cellulase) to process eucalyptus pulp, subsequently the pulp submitted to carboxymethylation to produce cellulose films and investigate their properties. The results revealed that the combination of HPP and cellulase resulted in the production of partially transparent and smoother films. As for mechanical properties, this combination resulted in a 2.7-fold increase in the tensile strength (TS) value, a 35.5-fold increase in the elongation at break (EAB) value, and a 1.4-fold increase in the moisture content of the films. The crystallinity index (CrI) was also increased by HPP and enzymes, resulting in a 6.6-fold increase, compared to the control film. On the other hand, the combined use of HPP and enzymatic hydrolysis resulted in similar contact angle (CA) values on both sides of the films, but in the bottom side, when compared to the control film, a 2.1-fold decrease was observed. Furthermore, the water vapor permeability (WVP) of the films increased 1.8-fold. Finally, the thermal resistance of the films was slightly reduced when either HPP, enzymatic or both treatments were used on the cellulose pulp. In general, this work showed a new potential way to produce cellulose films with novel and potentially tailor-made properties. Full article