Search Results (131,394)

Bioactive peptides (BAPs) from dairy products have garnered increasing attention as natural agents with health-promoting properties, including antihypertensive, antioxidant, antimicrobial, immunomodulatory, opioid, and antidiabetic activities. This systematic review synthesizes research published between 2014 and 2024, retrieved from Scopus and PubMed, and selected according to PRISMA guidelines. A total of 192 studies met the inclusion criteria, collectively reporting over 3200 distinct peptides, with antihypertensive sequences, predominantly angiotensin-converting enzyme (ACE) inhibitors, constituting the largest category (n = 1237). β-casein was the principal precursor across bioactivities, followed by αs1-casein, β-lactoglobulin, and α-lactalbumin. Peptides were primarily produced via enzymatic hydrolysis, microbial fermentation, and gastrointestinal digestion, with peptide profiles influenced by the type of milk, microbial strains, and processing conditions. While cow’s milk remained the dominant source, investigations into goat, sheep, camel, buffalo, and donkey milk revealed species-specific biopeptides. Recent advances in proteomics have enhanced peptide identification and bioactivity prediction, enabling the discovery of novel sequences. These findings underscore the significant potential of dairy-derived BAPs as functional food components and nutraceutical ingredients, while highlighting the need for further in vivo validation, bioavailability studies, and broader exploration of underrepresented milk sources. Full article

This study systematically investigates settlement sites that record living patterns of ancient humans, aiming to reveal the interactive mechanisms of human–environment relationships. The core issues of landscape archeology research are the surface spatial structure, human spatial cognition, and social practice activities. This article takes the Han Dynasty settlement site in Sanyangzhuang, Neihuang County, Anyang City, Henan Province, as a typical case. It comprehensively uses ArcGIS 10.8 spatial analysis and remote sensing image interpretation techniques to construct spatial distribution models of elevation, slope, and aspect in the study area, and analyzes the process of the Yellow River’s ancient course changes. A regional historical geographic information system was constructed by integrating multiple data sources, including archeological excavation reports, excavated artifacts, and historical documents. At the same time, the sequences of temperature and dry–wet index changes in the study area during the Qin and Han dynasties were quantitatively reconstructed, and a climate evolution map for this period was created based on ancient climate proxy indicators. Drawing on three dimensions of settlement morphology, architectural spatial organization, and agricultural technology systems, this paper provides a deep analysis of the site’s spatial cognitive logic and the ecological wisdom it embodies. The results show the following: (1) The Sanyangzhuang Han Dynasty settlement site reflects the efficient utilization strategy and environmental adaptation mechanism of ancient settlements for land resources, presenting typical scattered characteristics. Its formation mechanism is closely related to the evolution of social systems in the Western Han Dynasty. (2) In terms of site selection, settlements consider practicality and ceremony, which can not only meet basic living needs, but also divide internal functional zones based on the meaning implied by the orientation of the constellations. (3) The widespread use of iron farming tools has promoted the innovation of cultivation techniques, and the implementation of the substitution method has formed an ecological regulation system to cope with seasonal climate change while ensuring agricultural yield. The above results comprehensively reflect three types of ecological wisdom: “ecological adaptation wisdom of integrating homestead and farmland”, “spatial cognitive wisdom of analogy, heaven, law, and earth”, and “agricultural technology wisdom adapted to the times”. This study not only deepens our understanding of the cultural value of the Han Dynasty settlement site in Sanyangzhuang, but also provides a new theoretical perspective, an important paradigm reference, and a methodological reference for the study of ancient settlement ecological wisdom. Full article

This paper presents Multi_mil, a multilingual annotated corpus designed for the analysis of information operations in military discourse. The corpus consists of 1000 texts collected from social media and news platforms in Russian, Kazakh, and English, covering military and geopolitical narratives. A multi-level annotation scheme was developed, combining entity categories (e.g., military terms, geographical references, sources) with pragmatic features such as information operation type, emotional tone, author intent, and fake claim indicators. Annotation was performed manually in Label Studio with high inter-annotator agreement (κ = 0.82). To demonstrate practical applicability, baseline models and the proposed Onto-IO-BERT architecture were tested, achieving superior performance (macro-F1 = 0.81). The corpus enables the identification of manipulation strategies, rhetorical patterns, and cognitive influence in multilingual contexts. Multi_mil contributes to advancing NLP methods for detecting disinformation, propaganda, and psychological operations. Full article

Unsupervised person re-identification (Re-ID) has been proven very effective and it boosts the performance in learning representations from unlabeled data in the dataset. Most current methods have good accuracy, but there are two main problems. First, clustering often generates noisy labels. Second, features can change because of different camera styles. Noisy labels causes incorrect optimization, which reduces the accuracy of the model. The latter results in inaccurate prediction for samples within the same category that have been captured by different cameras. Despite the significant variations inherent in the vast source data, the principles of invariance and symmetry remain crucial for effective feature recognition. In this paper, we propose a method called Invariance Constraint Contrast Learning (ICCL) to address these two problems. Specifically, we introduce center invariance and instance invariance to reduce the effect of noisy samples. We also use camera invariance to handle feature changes caused by different cameras. Center invariance and instance invariance help decrease the impact of noise. Camera invariance improves the classification accuracy by using a camera-aware classification strategy. We test our method on three common large-scale Re-ID datasets. It clearly improves the accuracy of unsupervised person Re-ID. Specifically, our approach demonstrates its effectiveness by improving mAP by 3.5% on Market-1501, 1.3% on MSMT17 and 3.5% on CUHK03 over state-of-the-art methods. Full article

In recent years, research in the field of the sustainable production of refractory ceramics has become topical. Significant attention has been paid to the use of secondary raw materials for obtaining high-quality materials. The purpose of the current study was to develop new high-temperature porous materials based on the magnesium sulfate-refractory clay–chamotte–aluminum system using environmentally friendly raw components. To synthesize porous refractories, rice husk and the by-products of its thermal processing were used as substitutes for ingredients usually introduced into the composition of high-temperature materials. Ground rice husk was used as both a burnout additive and a silica source. It was added to the mixture instead of chamotte. An organic condensate from rice husk pyrolysis was used as a binder. A sodium silicate solution, after activating pyrolyzed rice husk with alkali, was also tested as a binder. These liquid ingredients served as replacements for lignosulfonate and liquid glass. The new raw material components and the porous refractories obtained with their use were studied using methods of chemical analysis, XRD, GC-MS, TA, SEM, and EDS. Standard methods for studying the properties of refractories were used to evaluate the physicomechanical and thermal characteristics of the experimental materials. The sample with the maximum content of rice husk (14.4 wt.%) and organic condensate from its pyrolysis (10.5 wt.%) demonstrated promising properties as a light porous refractory: an apparent porosity of 44%, a volumetric weight of 1.1 g·cm⁻³, compressive strength of 2.1 MPa, tensile strength in bending of 4.5 MPa, bond strength of 0.01 MPa, thermal shock resistance of 155 thermal cycles, and thermal conductivity of 0.05 W (m·K)⁻¹. It can be used as a prospective thermal insulating material. Full article

Soybeans are of strategic importance to China, yet the country’s heavy reliance on imports leaves it highly exposed to policy and market disruptions. Existing studies have largely focused on the initial 2018 tariff episode, while the evolving impacts of subsequent and intensified tariff measures remain insufficiently explored. This study investigates how tariff shocks transmit through import reduction, structural reallocation, and price pass-through by employing a multi-phase difference-in-differences (DID) framework in combination with a continuous-intensity DID model. Using monthly data from January 2015 to June 2025, the analysis evaluates the effects of tariff escalation on import volumes, source-country shares, and landed import prices, thereby capturing both stage-specific dynamics and intensity-dependent responses. Robustness is verified through event-study parallel trend tests and placebo validations. The results show that (1) import volumes from the United States declined sharply and did not fully revert, indicating that tariffs disrupted long-standing trade path dependence; (2) source-country shares reallocated away from the U.S. toward South American suppliers, reinforcing diversification in China’s supply structure; and (3) tariff costs were asymmetrically passed through to prices, with U.S. soybean prices rising by approximately 43 percent, while non-U.S. prices remained relatively stable. Overall, the findings demonstrate that tariff shocks functioned as structural catalysts rather than temporary disturbances, accelerating China’s transition toward a more diversified and resilient soybean import architecture under heightened geopolitical uncertainty. Full article

Cereal-based complementary foods are widely consumed by children, yet limited data exist on their elemental composition and potential health risks. This study quantified As, Cd, Co, Cr, Cu, Fe, K, Mn, Mg, Mo, Ni, P, Pb, Se, Si, V, and Zn in eight commercial cereal-based products collected in Campo Grande, Brazil, using inductively coupled plasma optical emission spectrometry (ICP OES). Arsenic, cadmium, cobalt, and chromium were consistently below the detection limit. Phosphorus and potassium were the predominant elements across brands, followed by Fe, Mg, and Zn, with significant inter-brand variability (Kruskal–Wallis, p < 0.05). Lead was detected in Brands 1–5 (0.11–0.41 mg/kg), but it was below the limit of detection (LOD = 0.003 mg/L) in the other samples. Estimated daily intake (ID) values at 30 g/day and 90 g/day showed that Fe, Zn, Mn, and Se frequently met or exceeded dietary reference intakes for children aged 1–3 years, while Cu, Ni, and P remained below tolerable levels. Comparison with tolerable upper intake levels and ATSDR minimal risk levels indicated that higher consumption (90 g/day) could result in excess intake of Mn, Zn, and Se, with Pb contributing to cumulative hazard indices above the safety threshold (HI > 1). These findings emphasize the dual role of cereal-based foods as important nutrient sources and potential contributors to excessive trace element exposure in young children. Full article

In recent years, public discourse on pesticide impacts has increasingly recognized institutional and structural racism as key drivers of health disparities in Black, Indigenous, and People of Color (BIPOC) communities. While pesticides are vital for crop protection from causing yield losses, extensive research highlights their adverse effects on environmental quality and human health. These impacts disproportionately burden BIPOC populations, making pesticides a major environmental justice (EJ) concern like many other environmental pollutants. Despite progress in understanding these effects and advancing EJ, significant technical, social, and policy gaps remain. The objective of this review is to systematically examine critical gaps in technical, social, and policy dimensions, as well as the environmental and human health impacts of pesticide exposure on BIPOC communities in the United States, through the lens of environmental justice. This review synthesizes 128 sources peer-reviewed articles, books, reports on pesticides, EJ, and BIPOC communities in the U.S. Key findings reveal uneven distribution of pesticide-related health and environmental burdens along racial, ethnic, and socioeconomic lines. Non-Hispanic Blacks and Mexican Americans exhibit higher pesticide biomarkers and greater exposure risks than non-Hispanic Whites. Structural racism and classism, rooted in historical systems, perpetuate these inequities, compounded by regulatory failures and power imbalances. In addition, the EPA has flagged 31 pesticide manufacturing facilities for “Significant Violations” of key environmental laws, including the Clean Air Act, Clean Water Act, and Resource Conservation and Recovery Act. These systemic issues underscore urgent needs for transparency, accountability, and equitable policy reform. An EJ framework exposes critical knowledge gaps and calls for structural changes to ensure equal protection and responsive policies for the most affected communities. Full article

Lycopene, a natural carotenoid with antioxidant and health-promoting properties, has attracted attention as a valuable compound for the food, pharmaceutical, and cosmetic industries. Conventional production methods based on plant extraction or chemical synthesis are limited by low yields, high costs, and environmental concerns. In this study, the oleaginous yeast Yarrowia lipolytica was engineered as an alternative microbial cell factory for sustainable lycopene biosynthesis using short-chain fatty acids (SCFAs)—such as acetate, butyrate, and propionate—as inexpensive, renewable carbon sources. Four heterologous genes from Pantoea agglomerans (crtI, crtB, crtE, and idi) were codon-optimized and integrated into the Y. lipolytica genome using different expression systems, including the Golden Gate Assembly strategy. Among the tested strains, PS05/4lyc/GGA, characterized by enhanced phospholipid biosynthesis, demonstrated the highest lycopene yield of 462.9 mg/g dry cell weight and a titer of 3.41 g/L on butyrate medium—values comparable to or exceeding those reported for bioreactor-scale fermentations. The results indicate that co-activation of phospholipid and carotenoid biosynthesis pathways creates favorable intracellular conditions for hydrophobic pigment accumulation. Moreover, the use of SCFAs improved acetyl-CoA availability and redirected carbon flux through the mevalonate pathway, enhancing productivity. Strains with elevated membrane lipid biosynthesis also exhibited higher metabolic stability and stress tolerance. Full article

Background: Creams are one of the most used cosmetic formulations due to their hydrating and restoring properties, pleasant texture, and the possibility to deliver hydrophobic and hydrophilic active ingredients. The study aims to develop and characterize cosmetic creams based on natural-sourced ingredients—different vegetable oils from the Rosacea family: (1) Chaenomelis japonica seed oil, (2) Rosa canina seed oil, (3) Prunus armeniaca kernel oil, alone and in combination (4), along with silk protein (sericin) and astaxanthin. Methods: The creams were prepared by the hot homogenization method and were characterized in terms of rheological properties, spreadability, and antioxidant activity. Results: Two suitable formulations were selected as feasible for cosmetic application—the model containing Chaenomelis japonica seed oil exhibiting the highest antioxidant activity (47% higher vs. the model based on rosehip oil by FRAP method) and the highest spreadability values among the tested formulations (ranging between 61.57 and 69.34 mm). The second selected optimal formulation is the model based on a combination of oils characterized by the most suitable consistency and high antioxidant activity. Conclusions: The differences in their rheological behavior suggest as feasible application of Japanese quince oil cream its use as a daycare antioxidant cream, whereas the mixed oils-based cream model may potentially serve as a night cream for restorative and antioxidant care. Full article

Aiming to solve the challenges of the weak spatial and temporal correlation of medium- and long-term photovoltaic (PV) power data, as well as data redundancy and low forecasting efficiency brought about by long-time forecasting, this paper proposes a medium- and long-term PV power forecasting method based on the Transformer, SP-Transformer (spatiotemporal probsparse transformer), which aims to effectively capture the spatiotemporal correlation between meteorological and geographical elements and PV power. The method embeds the geographic location information of PV sites into the model through spatiotemporal positional encoding and designs a spatiotemporal probsparse self-attention mechanism, which reduces model complexity while allowing the model to better capture the spatiotemporal correlation between input data. To further enhance the model’s ability to capture and generalize potential patterns in complex PV power data, this paper proposes a feature pyramid self-attention distillation module to ensure the accuracy and robustness of the model in long-term forecasting tasks. The SP-Transformer model performs well in the PV power forecasting task, with a medium-term (48 h) forecasting accuracy of 93.8% and a long-term (336 h) forecasting accuracy of 90.4%, both of which are better than all the comparative algorithms involved in the experiment. Full article

This study aimed to validate a bias estimation framework for low-cost maritime IMUs by applying it to real-world shipborne data. Six estimation methods—including statistical (mean, median), model-based (least squares, cross-correlation), and signal-processing approaches (FFT, Butterworth filter)—were compared. The results demonstrated that the low-frequency Butterworth filter achieved the smallest residuals, with RMS residuals below 0.038 m/s² for accelerometers and 0.0035 deg/s for gyroscopes. In particular, AccX and AccZ residuals converged to 3.04 × 10⁻² m/s² and 2.30 × 10⁻² m/s², respectively, while GyroZ achieved 5.58 × 10⁻⁴ deg/s. Estimated accelerometer biases were 0.0405 m/s² (X-axis) and 0.1615 m/s² (Y-axis), and the optimization successfully converged with an objective function value of 9.314. The findings confirm that the previously proposed bias estimation method, originally validated in simulation, is effective under real-world maritime conditions. However, as ground truth bias values cannot be obtained in shipborne experiments, verification relied on residual statistics and cross-correlation analysis. This limitation has been explicitly stated in the conclusion, and future studies should incorporate sensitivity analyses and controlled experiments to further quantify error sources. Full article

To handle the uncertainties brought by the increasing penetration of renewable energy sources and random loads, we design a stochastic multi-timescale distribution network reconfiguration (SMTDNR) framework to coordinate diverse scheduling resources across different timescales and develop an efficient heuristic algorithm to solve this complex NP-hard combinatorial optimization problem with high efficiency for medium- and high-voltage distribution networks. First, the SMTDNR problem, incorporating distributed renewable generators, fuel generators, energy storage systems, and controllable loads, is simplified through circular constraint linearization, Jabr relaxation, and second-order cone (SOC) relaxation techniques. Then, a one-stage multi-timescale successive branch reduction (MTSBR) algorithm is developed for distribution networks with one redundant branch, which transforms the SMTDNR problem into a stochastic multi-timescale optimal power flow (SMTOPF) problem. This is extended to a two-stage MTSBR algorithm for general networks with multiple redundant branches, which iteratively runs the proposed one-stage MTSBR algorithm. Numerical results on modified IEEE 33-bus and 123-bus distribution networks validate the superior optimality, feasibility, and computational efficiency of the proposed algorithms, particularly in scenarios of high renewable penetration and increased uncertainty, offering robust and feasible solutions where traditional methods may fail. Full article

Reproductive barriers to gene flow play a key role in speciation. However, as it is not always feasible to study them directly, most studies rely on genetic divergence to infer species delimitation. In order to correlate genetic distances to reproductive incompatibilities, compact groups of closely related species are needed. In this work, we explored a species complex of Baikal amphipods (Crustacea: Amphipoda: Gammaroidea), Eulimnogammarus verrucosus. Three biological species (W, S, and E), geographically isolated in Baikal, had been found to have interspecific differences exceeding the patristic distance threshold of 0.16, and a postzygotic incompatibility had been confirmed for the closest pair, W and S. Here, we expanded our knowledge on geographical distribution of the species, discovering that secondary contact between the W and S species already occurs in natural conditions near the source of the Angara River. Our experiments have shown that the three species within the E. verrucosus species complex are separated by both prezygotic and postzygotic barriers. While neither of these barriers is absolute, their combination can ensure reproductive isolation upon secondary contact of the species. The experimental system we have developed in this and previous works can provide support for testing species delimitation hypotheses based on sequencing data and further extend these results to related species for which such experiments are unfeasible. Full article

Non-proteinogenic amino acids, such as L-citrulline and L-theanine, have garnered attention for their potential health benefits, including enhanced immunity, antioxidant activity, and cardiovascular support. The application of natural amino acids in disease treatment and health supplementation is and will remain a research hotspot in pharmaceutics. Plant-derived L-citrulline and L-theanine have demonstrated multifaceted benefits, primarily through mechanisms involving nitric oxide (NO) bioavailability (for L-citrulline) and mitochondrial regulation or immune modulation (for both). Critical gaps are identified: (1) the role of D-amino acids (e.g., D-citrulline and D-theanine) in health and metabolism remains underexplored, particularly regarding chiral-specific bioactivity; (2) derivatives and co-administration strategies of L-forms warrant systematic evaluation for drug. However, while these compounds show promise, evidence is predominantly from animal and cell studies, with limited long-term human data on efficacy and safety. Potential side effects, dosing limitations, and sourcing challenges are discussed. This review emphasizes the need for cautious interpretation of their benefits, acknowledging that while promising, some effects, such as those on muscle protein synthesis, require further validation compared to established nutrients like branched-chain amino acids. By bridging mechanistic insights with translational challenges, this work aims to guide future research toward sustainable nutraceutical production. Full article