Search Results (3,734)

Lead (Pb) is a persistent and highly toxic heavy metal that poses significant ecological and human health risks due to its high bioaccumulation potential. In this study, nitrogen-doped biochar (NBC) was synthesized from straw-derived biochar via ball-milling and ammonium nitrate modification to remediate Pb-contaminated soil. Batch adsorption experiments demonstrated that the adsorption process was best described by the Langmuir isotherm model, indicating monolayer adsorption. X-ray photoelectron spectroscopy (XPS) revealed that Pb(II) immobilization by NBC occurred through multiple mechanisms, primarily precipitation and complexation with hydroxyl and pyrrolic-N functional groups. Subsequent pot experiments confirmed that NBC outperformed pristine biochar (BC) in reducing Pb bioavailability. This superior performance was attributed to the ability of NBC to increase soil pore water pH and significantly decrease soil redox potential (Eh). Moreover, compared to the control, a 5% NBC treatment (NBC2) significantly increased soil organic matter (SOM) by 136.24% while concurrently increasing soil available nitrogen (SAN), phosphorus (SAP), and potassium (SAK) by 46.91%, 75.72%, and 42.79%, respectively. Microbiological analyses indicated that NBC application enhanced soil alpha diversity (Chao1, ACE, and Shannon indices) and enriched beneficial bacterial phyla, such as Proteobacteria and Firmicutes. Random forest analysis identified the acid-soluble Pb fraction and SOM as the main drivers of bacterial operational taxonomic unit (OTU) composition. Specifically, NBC increased the relative abundance of the family Hungateiclostridiaceae, which may promote soil sulfide production and facilitate the precipitation of Pb into highly insoluble forms, further reducing its mobility and toxicity. Collectively, these findings demonstrate that NBC is a promising soil amendment that leverages both physicochemical and microbial pathways to immobilize Pb, mitigate environmental toxicity, and restore soil ecological health. Full article

Accurate cultivar identification of commercial dried goji berries is essential for raw material sorting, batch consistency assessment, and quality control during processing and distribution. Conventional approaches based on manual judgment or physicochemical analysis are often subjective, labor-intensive, time-consuming, and costly, making them unsuitable for rapid commercial sorting and quality inspection. To develop a rapid, low-cost, and nondestructive method for dried goji berry cultivar identification, this study proposes a visual recognition framework that integrates RGB imaging with lightweight deep learning. A dataset comprising 25,899 RGB images from five cultivars of commercial dried goji berry samples, namely Ningqi No. 7, Linqi No. 5, Ningqi No. 1, Keqi 6082, and Jingqi No. 1, was constructed. Given the pronounced surface shrinkage, complex texture, and subtle inter-cultivar appearance differences of dried goji berries, an image quality enhancement method was designed to strengthen the representation of color gradation, textural details, and edge information. For model development, CoAtNet was selected as the baseline network and redesigned for lightweight deployment. By integrating an improved feature extraction module and an information-preserving downsampling module, the proposed LSH-CoAtNet model enhances fine-grained feature representation while reducing computational cost. On the quality-enhanced image dataset, the proposed method achieved an accuracy of 98.80%, a precision of 98.81%, a recall of 98.80%, and an F1-score of 98.80%. The model contained only 6.41 M parameters and required 1.60 GFLOPs, outperforming the baseline model in both classification performance and computational efficiency. Ablation experiments and five-fold cross-validation further confirmed the effectiveness of the image quality enhancement strategy, the contribution of each improved module, and the stability of the model. Overall, the proposed method, which combines RGB image quality enhancement with LSH-CoAtNet, provides a low-cost, nondestructive, and efficient technical solution for rapid cultivar identification, raw material sorting, batch consistency assessment, and quality control of commercial dried goji berries during processing and distribution. It may also serve as a reference for intelligent classification and quality inspection of other specialty dried horticultural products. Full article

The use of Kluyveromyces marxianus in mixed cultures for fermentation processes has become increasingly relevant. This yeast is characterized by rapid growth, thermotolerance, broad sugar utilization, and the ability to produce aroma-active compounds. In this study, we evaluated changes in the growth and volatilome of a K. marxianus strain isolated from agave fermentation under microbial competition induced by co-cultivation interactions and nutritional limitation induced by a nutrient-deficient medium. The results indicate that these stress factors are significant drivers of metabolic changes, leading to substantial increases in the concentrations of key aromatic compounds. Stress-free conditions favor cell growth and the production of stable, reproducible volatile profiles, which is advantageous for batch-to-batch consistency (as in wine or mezcal production). While microbial competition and nutritional limitation induce reduced cell growth and loss of viability, they also lead to increased aromatic diversity, particularly the synthesis of β-phenethyl acetate, ethyl octanoate, and ethyl hexanoate. These findings demonstrate a relationship between environmental stress and the development of volatile profile complexity, offering new insights into harnessing stress-induced changes in the volatilome to optimize the sensory profile of traditional fermentations. Full article

Excessive concentrations of carbon dioxide (CO₂) in the atmosphere lead to adverse environmental effects. Biologically assisted processes that rely on organisms such as microalgae (i.e., Chlorella vulgaris) are common in capturing CO₂ from the atmosphere. Microalgae are rich in proteins, vitamins, minerals, and omega-3 fatty acids. Thus, microalgae production serves both health and environmental sectors. Varying light intensity and temperature are shown to influence algae growth. To quantify algae production under different light intensity and temperature conditions, and monitoring or scaling-up of biological reactors, reliable mathematical models are required. In this work, mathematical models that incorporate light intensity and temperature effects on algae growth in batch and continuous bioreactors are developed. Based on the modeling, the growth rate is maximum at T_opt = 25 °C, reaching the value of μ_max = 0.14 day⁻¹. The growth rate exponentially increases until light intensity (I) reaches around 150 ${\displaystyle \frac{\mathsf{\mu }\mathrm{m}\mathrm{o}\mathrm{l}}{{\mathrm{m}}^2\mathrm{s}}}$, which is approximately the optimal light intensity for Chlorella vulgaris. The effect of T on growth rate is found to be more sensitive than light intensity (I) in both batch and continuous reactor systems. When there are too many parameters in models, uncertainties exist and parameter estimation and model predictions become cumbersome. For these reasons analytical solutions to the models are presented in simplified forms and these models are more practical and easier to implement. The novelty of the work is also the presentation of the models in analytical forms. Analytical solutions to the two reactor models (batch and continuous) will help quantify biomass production as a function of time under the varying light intensity and temperature conditions encountered. Full article

This study examines whether China’s Ecological Civilization Demonstration Zones (ECDZs) promote urban green total factor productivity (GTFP). Using panel data for 282 prefecture-level cities from 2011 to 2022, when six batches of policy pilots were implemented, the paper employs a super-efficiency SBM model to estimate GTFP and a difference-in-differences (DID) model to identify the policy effects. The results indicate that ECDZs significantly improve urban GTFP. Specifically, the baseline estimates show that the implementation of ECDZs increases GTFP by approximately 6.52% relative to the sample means. Potential transmission channels further show that technological innovation and industrial structure upgrading are important channels through which ECDZs promote green productivity growth. In addition, significant regional and city-type heterogeneity is observed. The positive policy effects are more pronounced in central regions and in non-resource-based cities, whereas the effects are relatively weak in eastern regions, western regions, and resource-based cities. These findings suggest that differences in economic foundations, industrial structures, and innovation capacities may influence the effectiveness of ECDZs. Overall, this study provides empirical evidence on the green development effects of ECDZs and offers policy implications for improving differentiated environmental governance and promoting high-quality sustainable development in China. Full article

In the treatment of high-salinity wastewater, the removal of nitrogen and organic pollutants remains a challenge, while the production of value-added compounds, such as ectoine from halophilic bacteria, offers a promising resource recovery pathway. In this study, halophilic activated sludge enriched with Thauera as the dominant strain was cultivated in a sequencing batch reactor (SBR) to treat synthetic high-salinity wastewater (30 g/L NaCl) under different sludge retention times (SRTs). The optimal nitrogen and organic carbon removal performances were achieved at an SRT of 10 days, with an ammonia nitrogen removal rate of 77.67% and a total organic carbon (TOC) removal rate of 72.51%. Ectoine production was strongly SRT dependent, as volumetric ectoine concentration was ~2 mg/L at 5 d SRT, almost undetectable at 10 d SRT, ~10 mg/L at 16 d SRT, and peaked at 21.5 mg/L at 22 d SRT. Short SRTs favored dynamic ectoine utilization for osmoprotection and metabolic stability, whereas long SRTs led to passive ectoine accumulation and deteriorated treatment performance. The system realized stable short-cut heterotrophic nitrification with negligible nitrite and nitrate accumulation, indicating direct conversion of ammonia to gaseous nitrogen. These results demonstrate that SRT regulation effectively balances ectoine synthesis and pollutant removal, providing a feasible strategy for resource-oriented treatment of high salinity wastewater. Full article

Light irradiance and spectral quality are key environmental factors that influence the growth, photosynthetic performance, and metabolic responses of cyanobacteria. In this study, the effects of increasing white and PAR-red light irradiances on Anabaena variabilis were evaluated in repeated-batch cultures, focusing on photosynthetic efficiency, biomass productivity, and the modulation of antioxidant systems, while cultures maintained under constant irradiance were used as control. Results showed that A. variabilis can maintain photosynthetic efficiency, as indicated by F_V/F_M values, within the optimal range for healthy cultures despite variations in light conditions. PAR-red light, in particular, enhanced biomass productivity and induced stronger photoacclimation responses compared to white light. Moreover, analysis of chlorophyll fluorescence (JIP parameters) revealed that photosynthetic machinery adapts to increased irradiance by modulating energy fluxes. Dissipated energy (DI₀/RC) increases by 4.5-fold under increasing PAR-red light with respect to control cultures, which suggests that PAR-red light promotes thermal dissipation of excess absorbed energy at the phycobilisome level, independently of and complementarily to, the increase in light-harvesting antenna pigments (chlorophylls and phycobiliproteins), thereby reducing the net oxidative pressure in the electron transport chain. The increase in photosynthetic pigments reflects an adaptive adjustment to optimize light harvesting under red light, with a phycocyanin content of 123 mg·g⁻¹ biomass, 30% higher than that obtained in control culture. Overall, A. variabilis demonstrated a robust capacity to acclimate increasing light irradiance and varying light quality through coordinated photoacclimation and antioxidant responses, in repeated-batch cultures. These findings highlight its physiological flexibility, which can be properly driven to maximize the production of valuable bioactive compounds, particularly phycobiliproteins such as phycocyanin, with applications in biotechnology. Full article

Anaerobic digestion (AD) of lignocellulosic biomass is often constrained by biomass recalcitrance, limiting methane recovery. This study investigated whether low-temperature dilute-acid hydrothermal pretreatment could enhance methane production from pine nut shells (PNSs), a lignin-rich and underutilized agro-industrial residue, and whether derivative-based kinetic landmarks could provide a more systematic characterization of batch AD performance. Methane production was significantly improved by dilute sulfuric acid and hydrothermal pretreatments. The highest methane yield (201.8 mL CH₄ g⁻¹ VS) was achieved under the combined 100 °C hydrothermal and 2.5% H₂SO₄ condition, representing approximately 1.8-fold and 3.3-fold increases compared with hydrothermal-only and untreated PNSs, respectively. Enhanced performance was attributed to hemicellulose solubilization, lignin disruption, and improved substrate accessibility. In contrast, excessive acid severity resulted in process instability, associated with total volatile fatty acid accumulation and pH reduction. The Modified Logistic Model (MLM) was further used to derive five kinetic landmarks (PAA, PAM, PI, PDM, and PDA) describing phase-specific features of cumulative methane production curves. While these landmarks provide a model-based framework for comparing batch AD kinetics, their nearly constant normalized yields primarily reflect the geometry of the fitted logistic function rather than independent biological invariants. Overall, the results identify 100 °C hydrothermal pretreatment with 2.5% H₂SO₄ as an effective moderate-severity strategy for enhancing methane recovery from PNSs and demonstrate the utility of MLM-derived landmarks as comparative descriptors of phase-resolved methane production. Full article

Black tea quality is governed by aroma chemistry: terpene alcohols (linalool, geraniol, nerolidol), methyl salicylate, and short-chain aldehydes whose abundance and release kinetics from the polyphenol-rich leaf matrix shape perceived grade. Grade information lies not only in the average headspace concentration but in the temporal shape of volatile organic compound (VOC) release under controlled heating. Conventional electronic noses obscure this signal: they rely on multi-sensor arrays, compress each response into summary statistics, and report accuracy only at the level of individual measurements. Whether a single low-cost metal–oxide–semiconductor (MOS) gas sensor can recover grade-defining aroma chemistry, and whether waveform-level modeling can exploit it, was therefore investigated. A portable electronic nose built around a Bosch BME688 sensor recorded 90 time series, each comprising four directly measured channels (temperature, humidity, pressure, gas sensor resistance) and a derived indoor-air-quality (IAQ) proxy computed from them by the on-chip BSEC library, from 16 commercial Turkish black teas across three quality grades. Two representations were compared on the same data: a feature-based pipeline reducing 25 statistical descriptors to seven principal components for six classifiers (best F1-macro = 0.624, MLP), and a raw-waveform Multi-Scale 1D-CNN with Squeeze–Excitation and temporal self-attention (MS-CNN-Attention). Under product-grouped cross-validation, the deep model reached F1-macro = 0.811 (+30%) and graded 14 of 16 products correctly by majority vote, against 11 of 16 for the MLP, with the largest gain in the medium grade (F1: 0.52 → 0.79), where summary-statistic compression destroys the release-kinetic signal. The contributions are threefold: one programmable MOS sensor operated as a thermal-desorption profiler rather than a sensor array; a direct comparison of feature-based classical learning against raw-waveform deep learning on the same small, non-normally distributed dataset; and a product-level decision-consistency metric suited to batch screening. Pairing a low-cost MOS sensor with waveform-level modeling offers a rapid, non-destructive route to aroma-chemistry-based tea quality screening. Full article

Anaerobic digestion of municipal wastewater sludge is often limited by slow hydrolysis rates. This study evaluated the effects of ozone pretreatment on methane production during mesophilic batch digestion. Ozone was applied at 0–10% for 30–90 s, with inoculum-to-substrate ratios of 1.0–2.0. Methane production was monitored using the AMPTS II system. The maximum methane yield (736 NmL CH₄ g⁻¹ VS; 1381 NmL total) was obtained at 10% ozone for 30 s and I/S = 1.5. Kinetic modelling showed enhanced methane production rates and reduced lag phases, with the Gompertz and Logistic models providing the best fit. Full article

Background: Egypt is one of the top steel producers in the Middle East and Africa, yet it faces acute water scarcity and rising energy costs, making it a critical context for studying trade-offs among carbon emissions, water ecological effects, and operational cost in steel supply chain. Methods: Using a multi-objective optimization model based on real data from a major Egyptian steel manufacturer, this study evaluates trade-offs among cost, tardiness, and environmental impact measured by carbon emissions and water ecological effects. Unlike prior studies, this study demonstrates that dedicated warehousing enables batch-level traceability of returned scrap while reducing material handling travel time and carbon emissions. The AUGMECON method generates Pareto-optimal solutions, and sensitivity analysis is conducted on six parameters: scrap take-back rate, demand variability, raw material price, energy cost, production capacity, and carbon tax. Results: Demand and raw material prices dominate performance: a 5% demand increase raises cost by 8.6%, and a 15% raw material price increase raises cost by 32.7%. The knee-point solution achieves 58.18 billion EGP, 0.99 months tardiness, and 2096 million kg CO₂ over nine months. Conclusions: This study quantifies the impact of the circular economy and operational parameters on steel supply chain performance under a dedicated warehousing policy. Full article

Seasonal fluctuations in open solid-state fermentation drive batch-to-batch variability in Chinese Baijiu Daqu; however, how environmental shifts reshape microbial functional expression and non-volatile flavour precursors in medium-high-temperature Daqu remains poorly resolved. In this study, data-independent acquisition (DIA)-based quantitative metaproteomics and untargeted liquid chromatography–mass spectrometry (LC-MS) metabolomics were integrated to characterise winter and summer Daqu from Luzhou, Sichuan. Among 2904 annotated non-volatile metabolites, orthogonal partial least squares discriminant analysis (OPLS-DA) revealed clear seasonal separation; 1472 differential metabolites (560 up- and 912 downregulated in winter vs. summer; variable importance in projection [VIP] > 1, p < 0.05) were enriched in glycolysis/gluconeogenesis, the tricarboxylic acid (TCA) cycle, amino acid biosynthesis, and starch/sucrose metabolism. DIA-based quantitative metaproteomics further resolved season-specific enzyme expression: summer Daqu exhibited elevated saccharolytic, glycolytic and amino-acid-converting enzymes (β-glucosidase, 6-phosphofructokinase, pyruvate dehydrogenase), whereas winter Daqu was enriched in glucose oxidase, phosphoenolpyruvate carboxykinase and aldehyde dehydrogenase, consistent with a pattern suggestive of carbon-storage prioritisation. Proteome–metabolome integration established a coherent “enzyme protein abundance–inferred metabolic tendency–metabolite accumulation” correlative framework axis: higher hydrolytic and central-carbon enzyme abundance in summer corresponded to increased maltose, lactate, acetate, L-glutamate and L-aspartate. Therefore, production season reshapes Daqu quality chiefly by corresponding to distinct patterns of in situ enzyme protein abundance, providing a DIA quantitative metaproteome-anchored mechanistic framework for screening high-expression starters and stabilising seasonal Daqu quality. Full article

Background/Objectives: The precise characterization of the key microstructural and physicochemical attributes in sustained-release microspheres remains a technical bottleneck, hindering the understanding of drug release mechanisms, and limiting insights into the “process–structure–performance” relationship. To address this, we developed novel methods to conduct in-depth research on the microscopic properties of microspheres. Methods: Scanning electron microscopy (SEM) combined with a deep learning-based image segmentation (DLIS) algorithm was established for quantitative analysis of the pore structure. Laser confocal Raman spectroscopy (LCRS) was employed for in situ, non-destructive, three-dimensional (3D) visualization and quantitative mapping of the active pharmaceutical ingredient (API) distribution within microspheres. Results: This study successfully developed and applied SEM-DLIS and LCRS as reliable tools for microstructural and physicochemical characterization. SEM-DLIS analysis revealed significant differences in surface and internal pore structure among microspheres from different manufacturers and between particles of different sizes from the same batch. LCRS imaging further identified distinct API distribution patterns: uniform dispersion, outer-layer enrichment, and heterogeneous distribution. The combined data elucidate that the initial burst release is governed by the synergistic effect of surface porosity and API surface enrichment, whereas the sustained release kinetics are jointly regulated by the internal pore structure, particle size, and API spatial distribution. Conclusions: The findings establish that microstructure dictates release behavior and that all observed structural variations are linked to critical process parameters (CPPs), validating the “process determines structure” hypothesis. The established methodology provides a critical technical framework for the reverse engineering and quality equivalence assessment of generic microspheres, as well as for the quality-by-design-based optimization of innovative drug products, thereby advancing both pharmaceutical development and regulatory science. Full article

Acid-generating mining waste and polymer waste are two of the most persistent environmental problems facing the mining and manufacturing sectors, respectively. We have investigated the co-recovery of these disparate waste streams for the production of unfired cementitious paving blocks. We established a statistically optimized formulation using response surface methodology (RSM) and a central composite design (CCD). We systematically evaluated three process variables: air-curing time (4–37 days), dosage of the waste mixture (5–68% by weight of dry solids: acid-generating mining waste, hydrated lime, and recycled polymer in a waste-to-polymer mass ratio of 1:1), and type of polymeric aggregate (recycled PET flakes versus granulated rubber). Compressive strength ranged from 4.5 to 42.1 MPa across the 40 experimental conditions. The resulting quadratic model was clearly significant (F = 186.31, p < 0.0001) with solid predictive parameters (R² = 0.9796; R²pred = 0.9627; adequate precision = 42.47). Desirability-based optimization, which limited air curing to industrially feasible timeframes (7–28 days) and maximized waste utilization within a 10–50% by weight, identified PET with 12.4 days of curing and a 50% by weight waste mixture as the optimal configuration, predicting a compressive strength of 37.3 MPa. This value exceeds the 32 MPa threshold for Type I heavy-traffic paving blocks; however, confirmatory tests yielded 34.09 ± 1.08 MPa, indicating that production-scale use should include control of moisture content, compaction, and batch homogeneity. Scanning electron microscopy with energy-dispersive spectroscopy (SEM/EDS) and X-ray diffraction (XRD) demonstrated that PET inclusions promoted a denser and more continuous interfacial transition zone than shredded rubber, driven by physical entanglement and the pronounced microfilling effect of the fine waste particles. Full article

The increasing generation of agro-industrial residues like nejayote (maize lime-cooking wastewater from the maize nixtamalization process) poses significant environmental challenges in Mexico due to its elevated chemical oxygen demand (COD) and organic load. This study evaluates the physical separation of nejayote via membranes and its use as a low-cost substrate for producing lipids and carotenoids using Rhodotorula glutinis. A batch culture followed by pulse-feeding achieved a COD removal efficiency of 53.6% (0.22 g COD/(L h)) and a biomass concentration of 3.72 ± 0.45 g COD/L within 48 h. The yeast demonstrated a high specific metabolic efficiency, yielding 0.457 g of lipids and 0.0049 g of carotenoids per gram of biomass, with an oleaginous fraction of 46.21% in dry weight. Experimental data calibrated a process model in SuperPro Designer, simulating full-scale processes treating 100, 1000, and 10,000 m³ of nejayote per batch, producing up to 2137.11 MT of lipids and 22.90 MT of carotenoids annually. A techno-economic analysis estimated the investment, operating costs, and financial indicators for all scenarios. Strategies like evaporation and reverse osmosis to concentrate nejayote significantly improved profitability by reducing equipment size. Additionally, a circular economy approach was modeled, recovering process water and nutrient-rich side streams. These findings confirm that integrated physical and biological treatment, coupled with resource recovery, transforms this particularly agro-industrial residue into a technically robust and economically viable biorefinery feedstock, aligning industrial production with sustainable waste management. Full article