Search Results (5,449)

Glycosylation of many proteins has been revealed to be closely related to food allergy, and screening and structural analysis of related glycoproteins are essential for studies in this important area. Gly m Bd 30K is one of the major allergens that exist in soybeans. N-Glycans of the Gly m Bd 30K influenced the immunoreactivity and antigen-presenting efficiency. In this paper, soybean allergen glycoprotein Gly m Bd 30K was used as the research object. It was separated and purified by the combination of isoelectric point and Sepharose CL-6B gel. The glycoprotein was analyzed and identified by SDS-PAGE and MALDI-TOF MS. The N-glycans of Gly m Bd 30K glycoprotein were released and labeled by a newly developed one-pot method, and qualitatively and quantitatively analyzed by ESI-MSⁿ and HILIC-UV-MS/MS. The results showed that the purity of Gly m Bd 30K glycoprotein was 95%, and the relative molecular mass was 33,923 Da. The Gly m Bd 30K glycoprotein contained a total of six kinds of glycans, including two types: oligo-mannose type (4.3%) and paucimannose type (95.7%). The paucimannose modified with core α-1,3-fucose and β-1,2-xylose accounted for 92.87%. This study provides quality-reliable materials for the follow-up study of glycan sensitization and also provides a theoretical basis for the in-depth study of the specificity and biological function of the antigenic determinant of Gly m Bd 30K glycoprotein. Full article

Empirical research on the impact of the digital economy on sustainable development is hampered by severe methodological challenges. Discrepancies in the theoretical foundations and construction logic of measurement frameworks have led to diverse and often conflicting conclusions, hindering the systematic accumulation of knowledge. This study aims to address this critical gap by proposing a new, logically consistent measurement framework. To overcome the existing limitations, we construct a functional deconstruction framework grounded in General-Purpose Technology (GPT) theory and a “stock–flow” perspective. This framework deconstructs the digital economy into a neutral “digital infrastructure” (stock platform) and two forces reflecting its inherent duality: a “consumption force” (digital industrialization) and an “empowerment force” (industrial digitalization). Based on this, we develop a measurement system adhering to the principle of “logical purity” and apply a “two-step entropy weighting method with annual standardization” to assess 30 provinces in China from 2012 to 2023. Our analysis reveals a multi-scalar evolution. At the micro level, we identified four distinct provincial development models and three evolutionary paths. At the macro level, we found that the overall inter-provincial disparity followed an inverted U-shaped trajectory, with the core contradiction shifting from an “access gap” to a more profound “application gap.” Furthermore, the primary driver of this disparity has transitioned from being “empowerment-led” to a new phase of a “dual-force rebalancing.” The main contribution of this study is the provision of a new analytical tool that enables a paradigm shift from “aggregate assessment” to “structural diagnosis.” By deconstructing the digital economy, our framework allows for the identification of internal structural imbalances and provides a more robust and nuanced foundation for future causal inference studies and evidence-based policymaking in the field of digital sustainability Full article

This study conducts a detailed and systematic Life Cycle Assessment (LCA) of demineralized (DEMI) water production at the Al-Hilla Second Gas Power Plant in Iraq, employing the Open LCA-ReCiPe 8 Midpoint (H) method to evaluate potential environmental impacts across 18 midpoint categories. The analysis focuses on the production of 1 cubic meter of high-purity water, offering a comprehensive evaluation of the environmental burdens associated with chemical usage, energy consumption, and resource depletion. The results indicate that terrestrial ecotoxicity is the most dominant impact category (20.383 kg 1,4-DCB-eq), largely driven by the extensive use of treatment chemicals such as coagulants, disinfectants, and antiscalants. Climate change follows as the second highest impact category (3.496 kg CO₂-eq), primarily due to significant electricity consumption during energy-intensive stages, particularly reverse osmosis (RO) and electro-deionization (EDI). These stages also contribute notably to fossil resource depletion (1.097 kg oil-eq) and particulate matter formation, reflecting the heavy reliance on fossil fuel-based energy in the region. Additional environmental concerns identified include human toxicity (both carcinogenic and non-carcinogenic), freshwater and marine ecotoxicity, and metal/mineral resource depletion, all of which underscore the need for improved chemical and material management throughout the treatment process. While impacts from categories such as ozone layer depletion, ionizing radiation, and eutrophication are relatively low, their cumulative effect over time remains a concern for long-term sustainability. The energy assessment reveals that the RO and EDI units alone account for over 70% of the total energy consumption, estimated at 3.143 kWh/m³. This research provides insights into minimizing environmental burdens in water treatment systems, especially in regions facing energy and water stress. Full article

Water plays a fundamental role in sustaining biological processes, ecological functions, and economic systems. However, the progressive pollution of water sources compromises these functions, posing significant threats to water purity, human well-being, and environmental sustainability. Human activities, such as industrial waste, agriculture, and urbanization, alongside natural processes, are major contributors to the deterioration of surface water quality, which in turn leads to environmental and economic risks. The decline in water quality results in issues such as waterborne diseases, loss of biodiversity, and a shortage of clean water for consumption and industrial use. This paper emphasizes the critical need for maintaining good water quality and the importance of implementing effective strategies for the removal of physical, chemical, and biological contaminants. In response, this work presents an intelligent embedded system (electronic control unit, ECU) developed as part of a modular filtration system designed to improve surface water quality, provide more precise water analyses, and perform tests within a controlled environment. Full article

The depletion of fossil fuel reserves and their environmental impact have driven the search for sustainable energy alternatives. Biodiesel has emerged as a promising substitute. Being a major byproduct of the coffee industry, spent coffee grounds (SCGs) offer a viable feedstock due to their abundance, high fatty acid content, and calorific value. This study explores biodiesel production from SCGs. First, oil was experimentally extracted from SCGs using Soxhlet extraction with hexane as the solvent. The oil yield varied between 12 and 13.4% with a density of 0.9 g/mL. Reactor modeling and kinetic analysis were performed, showing that CSTRs in series are favorable for the esterification and transesterification reactions. Furthermore, Aspen Plus was used to simulate the extracted oil conversion into biodiesel through a two-step esterification and purification process. The simulation results are verified against previous experimental research. Sensitivity analyses were performed to evaluate the influence of key process parameters, including methanol-to-oil ratio, reactor residence time, and transesterification temperature. The simulation results indicate an optimal biodiesel mass yield of 90.31%, with a purity of 99.63 wt%, at a methanol-to-oil ratio of 12:1 and a transesterification temperature of 60 °C. Full article

A novel skin test for an in vivo assessment of SARS-CoV-2-specific T-cell immunity was developed using CoronaDermPS, a multiepitope recombinant polypeptide encompassing MHC II–binding CD4+ T-cell epitopes of the SARS-CoV-2 structural proteins (S, E, M) and full length nucleocapsid (N). In silico epitope prediction and modeling guided antigen design, which was expressed in Escherichia coli, was purified (>95% purity) and formulated for intradermal administration. Preclinical evaluation in guinea pigs, mice, and rhesus macaques demonstrated a robust delayed type hypersensitivity (DTH) response at optimal doses (10–75 µg), with no acute or chronic toxicity, mutagenicity, or adverse effects on reproductive organs. An integrated clinical analysis included 374 volunteers stratified by vaccination status (EpiVacCorona, Gam-COVID-Vac, CoviVac) prior to COVID-19 infection (Wuhan/Alpha, Delta, Omicron variants), and SARS-CoV-2–naïve controls. Safety assessments across phase I–II trials recorded 477 adverse events, of which >88% were mild and self-limiting; no severe or anaphylactic reactions occurred. DTH responses were measured at 24 h, 72 h, and 144 h post-injection by papule and hyperemia measurements. Overall, 282/374 participants (75.4%) exhibited a positive skin test. Receiver operating characteristic analysis yielded an overall AUC of 0.825 (95% CI: 0.726–0.924), sensitivity 79.5% (95% CI: 75.1–83.3%), and specificity 85.5% (95% CI: 81.8–88.7%), with comparable diagnostic accuracy across vaccine, and variant subgroups (AUC range 0.782–0.870). CoronaDerm-PS–based skin testing offers a simple, reproducible, and low-cost method for qualitative evaluation of T-cell–mediated immunity to SARS-CoV-2, independent of specialized laboratory equipment (Eurasian Patent No. 047119). Its high safety profile and consistent performance across diverse cohorts support its utility for mass screening and monitoring of cellular immune protection following infection or vaccination. Full article

Moringa oleifera seeds are rich in protein, yet their potential as plant-based protein in food remains underutilized. This study evaluated the extraction efficiency, composition, and techno-functional properties of moringa seed protein isolate (MSPI) using enzyme-assisted (EAE), ultrasonic-assisted (UAE), and microwave-assisted extraction (MAE) methods, compared to conventional alkaline extraction (CE). EAE was performed with viscozyme (2%, pH 8, 50 °C, 2 h) and papain (1%, pH 7, 50 °C, 1 h), UAE at 40% amplitude (20 kHz, 20 min), and MAE at 800 W (50 °C, 90 s). All methods significantly improved extraction yield (14.60–30.08%), protein content (80.47–86.61%), solubility (40.78–60.09% at pH 10), and techno-functional properties over CE. However, MAE slightly reduced solubility. Phytates (0.83–0.49 g/100 g) and trypsin inhibitor activity significantly decreased (4.48–1.92 U/mg). In vitro protein digestibility improved (p < 0.05) across all samples (88.11–93.81%), with hydrolysis patterns supporting the enhanced digestibility. Structural modifications were indicated by altered surface hydrophobicity and thermal properties. SDS-PAGE showed consistent major protein bands at 17, 25, and 48–63 kDa, with EAE showing reduced intensity at ~63 kDa. While UAE and MAE achieved high protein yield and purity, EAE offered the best balance of functionality and digestibility, making it the most promising method for producing high-quality MSPI. These findings are relevant for guiding the selection of extraction methods for MSPI recovery for food applications. Full article

In the race toward next-generation electronics and energy systems, ceramic nanocomposites have taken center stage due to their remarkable dielectric and ferroelectric functionalities. By pushing the boundaries of nanoscale engineering, recent studies have shown how microstructural control and interfacial design can unlock unprecedented levels of polarization, permittivity, and frequency stability. This review presents a critical and up-to-date synthesis of the last decade’s progress in ceramic-based nanocomposites, with a special focus on the structure property processing nexus. Diverse processing techniques ranging from conventional sintering to advanced spark plasma sintering and scalable wet-chemical methods are analyzed for their influence on phase purity, grain boundary behavior, and interfacial polarization. The review also explores breakthroughs in lead-free and eco-friendly systems, flexible ferroelectric nanocomposites, and high-k dielectrics suitable for miniaturized devices. By identifying both the scientific opportunities and persistent challenges in this rapidly evolving field, this work aims to guide future innovations in material design, device integration, and sustainable performance. Full article

Rebar is a critical material in concrete constructions like high-rise buildings and seismic-resistant structures. To enhance its properties, microalloying with nitrogen is employed, but traditional methods using micro alloy additives such as vanadium (FeV), niobium (FeNb), titanium (FeTi), and vanadium nitride (VN) face issues of high costs, reduced purity, and difficulty in controlling molten steel composition. This article presents a novel approach of injecting top-blown O₂–N₂ mixed gas to increase nitrogen content efficiently. Experiments simulated HRB400 steel samples, varying N₂ ratios (10%, 20%, 30%, 40%), temperatures (1500 °C, 1550 °C, 1600 °C), and blowing times (1, 2, 3 min). Results show that optimized parameters enable nitrogen content adjustment from 50 to 104 ppm, with nitrogen utilization improved to 5.4%. This method utilizes inexpensive N₂ gas, reduces impurities, and provides precise control, offering a cost-effective and sustainable solution for high-performance steel production by replacing costly alloys and meeting nitrogen requirements. Full article

The separation of butadiene 1,3 from pyrolysis products is a critical step in the petrochemical industry, as butadiene is a key raw material for producing synthetic rubber and other polymers. This study presents a detailed model-based analysis of the separation process, focusing on optimizing operational parameters to maximize butadiene recovery, enhance product purity, and reduce energy consumption. The simulation was conducted using Aspen Plus, evaluating critical variables such as the solvent-to-feed ratio, reflux ratio, number of column stages, and energy integration between distillation units. The simulation results indicated that an optimal solvent-to-feed ratio of 1.5:1 and a reflux ratio of 4.2:1 in the extractive distillation column provided the highest separation efficiency. Under these conditions, the recovery rate of butadiene 1,3 reached 98%, with a final product purity of 99.5%. Furthermore, this study revealed that increasing the number of theoretical stages in the distillation column improved the separation process without significantly increasing energy demand. Energy integration, specifically through heat recovery between the primary distillation and extractive distillation columns, led to a 12% reduction in total energy consumption. These findings demonstrate the importance of fine-tuning operational parameters to achieve high separation efficiency and product quality while minimizing energy use. This model-based analysis provides valuable insights into the design and optimization of industrial-scale butadiene separation processes, offering strategies to reduce operational costs and improve sustainability in production. The methodology and results can serve as a basis for further improvements in similar separation processes across the petrochemical industry. Full article

Global food security is increasingly challenged by climate change and the availability of arable land. This situation calls for improved crop monitoring and management strategies. Rice is a staple food for nearly half of the world’s population and a significant source of calories. Accurately identifying rice varieties is crucial for maintaining varietal purity, planning agricultural activities, and enhancing genetic improvement strategies. This study evaluates the effectiveness of machine learning algorithms to identify the most effective approach to predicting rice varieties, using multitemporal Sentinel-2 images in the Marismas del Guadalquivir of Sevilla, Spain. Spectral reflectance data were collected from ten Sentinel-2 bands, which include visible, red-edge, near-infrared, and shortwave infrared regions, at two key phenological stages: tillering and reproduction. The models were trained on pixel-level data from the growing seasons of 2021 and 2024, and they were evaluated using a test set from 2022. Four classifiers were compared: random forest, XGBoost, K-nearest neighbors, and logistic regression. Performance was assessed based on accuracy, precision, recall, specificity and F1 score. Non-linear models outperformed linear ones. The highest performance was achieved with the Random Forest classifier during the reproduction phase, reaching an exceptional accuracy of 0.94 using all bands or only the most informative subset (red edge, NIR, and SWIR). This classifier also maintained excellent accuracy (0.93 and 0.92) during the initial tillering phase. This fact demonstrates that it is possible to perform reliable varietal mapping in the early stages of the growing season. Full article

Flexible polyurethane foams (PUFs) are widely used materials whose crosslinked chemical structure hinders conventional recycling, leading to significant environmental challenges. This study presents a selective and scalable depolymerization strategy for polyurethane foam waste (PUFW), utilizing a combination of 1-butyl-3-methylimidazolium chloride ([Bmim][Cl]) as water-miscible ionic liquid (IL) and a strong organic base to enable hydrolytic cleavage of urethane bonds under mild reaction conditions (98 °C, atmospheric pressure). The approach was evaluated across different PUFW formulations and successfully scaled up to a 1 kg reaction mass, maintaining high efficiency in both the depolymerization and separation steps. The recovered polyols exhibited high purity and structural fidelity, comparable to those of virgin polyols. The recycled products were integrated into a new foam formulation, resulting in a PUF with mechanical and morphological properties, as revelated by scanning electron microscopy (SEM), which closely resemble those of virgin polyol-based references and surpass those of foams produced using commercially recycled polyols. These findings support the feasibility of closed-loop polyurethane recycling and represent the transition towards circular polymer economy strategies. Full article

The precise identification, classification, sorting, and rapid and accurate quality assessment of soybean seeds are extremely important in terms of the continuity of agricultural production, varietal purity, seed processing, protein extraction, and food safety. Currently, commonly used methods for the identification and quality assessment of soybean seeds include morphological analysis, chemical analysis, protein electrophoresis, liquid chromatography, spectral analysis, and image analysis. The use of image analysis and artificial intelligence is the aim of the presented research, in which a method for the automatic classification of soybean varieties, the assessment of the degree of damage, and the identification of geometric features of soybean seeds based on numerical models obtained using a 3D scanner has been proposed. Unlike traditional two-dimensional images, which only represent height and width, 3D imaging adds a third dimension, allowing for a more realistic representation of the shape of the seeds. The research was conducted on soybean seeds with a moisture content of 13%, and the seeds were stored in a room with a temperature of 20–23 °C and air humidity of 60%. Individual soybean seeds were scanned to create 3D models, allowing for the measurement of their geometric parameters, assessment of texture, evaluation of damage, and identification of characteristic varietal features. The developed 3D-CNN network model comprised an architecture consisting of an input layer, three hidden layers, and one output layer with a single neuron. The aim of the conducted research is to design a new, three-dimensional 3D-CNN architecture, the main task of which is the classification of soybean seeds. For the purposes of network analysis and testing, 22 input criteria were defined, with a hierarchy of their importance. The training, testing, and validation database of the SB3D-NET network consisted of 3D models obtained as a result of scanning individual soybean seeds, 100 for each variety. The accuracy of the training process of the proposed SB3D-NET model for the qualitative classification of 3D models of soybean seeds, based on the adopted criteria, was 95.54%, and the accuracy of its validation was 90.74%. The relative loss value during the training process of the SB3D-NET model was 18.53%, and during its validation process, it was 37.76%. The proposed SB3D-NET neural network model for all twenty-two criteria achieves values of global error (GE) of prediction and classification of seeds at the level of 0.0992. Full article

Naringin and pectin were innovatively and sequentially extracted from naturally dropped fruit of pomelo (NDFP), optimizing yields via response surface methodology (RSM). Under optimized conditions, naringin was extracted first with 70% ethanol (70 °C, 110 min, SSR 15:1 v/w), followed by pectin extraction from the residue using pH 1.50 acetic acid (80 °C, 160 min, ratio 40:1 v/w) naringin yield reached 42.77% with 97.6% ± 0.31% HPLC purity, while pectin yield was 14.32%. Critically, the recovered pectin was identified as low-ester and exhibited significantly superior antioxidant activity compared to commercial pectin. This work establishes an efficient sequential extraction process valorizing waste pomelo drop, yielding high-purity naringin and antioxidant-rich, low-ester pectin. Full article

In this work, a set of methods for the study of the physical–chemical properties of flotation processing products was applied to establish parameters for the technological mode of anthropogenic raw material flotation processing using waste paper as an example. The proposed methods include the criterion E_f estimation, which characterizes the interfacial characteristics during flotation, and the criterion J determination, which characterizes the degree of purification of the obtained paper mass. The estimation of criterion E_f is based on the measurement of electric potential difference during flotation. The estimation of criterion J is based on spectrophotometric studies of the flotation product’s optical properties. Based on dispersion analysis, it was established that the proposed criteria are statistically dependent on the variation of the flotation purification mode parameters. The results of the study of flotation processing products show that the criterion E_f is sensitive to the recovery selectivity of dye particles in the froth product. In conjunction with the criterion of optical purity, J, it can be used to assess the effectiveness of proposed solutions of hardware design and the technological mode of flotation separation. Full article