Search Results (12,052)

Aflatoxin M1 (AFM1), a hepatocarcinogenic metabolite of aflatoxin B1, poses significant risks to human health through its presence in milk and dairy products. This study investigates AFM1 contamination in raw milk produced in Serbia from 2021 to 2025, assessing annual and seasonal variations and associated health risks. A total of 907 milk samples were analyzed using enzyme-linked immunosorbent assay (ELISA), revealing contamination in 70.1% of samples, with mean concentrations exceeding the EU regulatory limit of 50 ng/kg. Seasonal analysis identified the highest contamination levels during winter, attributed to increased use of contaminated feed during colder months. Health risk assessments estimated the daily intake of AFM1 and associated health risks, with high-exposure individuals showing notably reduced margins of safety. The research demonstrates the essential requirement for better feed quality management alongside enhanced regulatory oversight along with health programs that reduce AFM1 exposure in Serbian populations. Full article

To quantitatively assess the carbon emission characteristics of expressway construction and to identify its key influencing factors, this study establishes a comprehensive carbon emission accounting framework that covers the material production, transportation, and construction stages based on the life cycle assessment (LCA) approach. Typical expressway projects are selected as case studies to perform stage-based emission quantification and multivariable response analysis. The results indicate that the total carbon emissions per kilometer during the construction phase are approximately 1.80 × 10³ kg CO₂-eq/km, with material production being the dominant contributor, accounting for about 60–70%, followed by transportation and construction activities. The analysis of structural layers shows that variations in the thickness of the asphalt surface and cement-stabilized base layers, which are the main sources of emissions, are strongly and positively correlated with total emissions, making them the principal control factors. Transportation distance and equipment efficiency are identified as moderately sensitive parameters, each contributing approximately 3–5% to emission variation. Further multivariable response analysis demonstrates nonlinear coupling effects between structural parameters and transportation factors. The combined increase in layer thickness and transport distance significantly amplifies total emissions, while the marginal impact of long-distance transport gradually decreases. Based on these findings, this study proposes a low-carbon construction strategy that focuses on structural optimization, local material sourcing, energy-efficient construction practices, and the use of clean energy. The outcomes of this research provide a theoretical foundation and quantitative reference for carbon emission prediction, structural design optimization, and green construction decision making during the expressway construction phase. Full article

Complex associations among production cost factors, multi-source cost information silos, and opaque transmission mechanisms of hidden costs in open-pit coal mining were addressed. The production process—including drilling, blasting, excavation, transportation, and dumping—was taken as the application context. A corpus of 103 open-pit coal mining standards and related research documents was constructed. Eleven entity types and twelve relationship types were defined. Dynamic word vectors were obtained through transformer (BERT) pre-training. The optimal entity tag sequence was labeled using a bidirectional long short-term memory–conditional random field (BiLSTM–CRF) 9 model. A total of 3995 entities and 6035 relationships were identified, forming a symmetry-aware knowledge graph for open-pit coal mining costs based on the BERT–BiLSTM–CRF model. The results showed that, among nine entity types, including Parameters, the F1-scores all exceeded 60%, indicating more accurate entity recognition compared to conventional methods. Knowledge embedding was performed using the TransH inference algorithm, which outperformed traditional models in all reasoning metrics, with a Hits@10 of 0.636. This verifies its strong capability in capturing complex causal paths among cost factors, making it suitable for practical cost optimization. On this basis, a symmetry-aware BERT–BiLSTM–CRF knowledge graph of open-pit coal mining costs was constructed. Knowledge embedding was then performed with the TransH inference algorithm, and latent relationships among cost factors were mined. Finally, a knowledge-graph-based cost factor identification system was developed. The system lists, for each cost item, the influencing factors and their importance ranking, analyzes variations in relevant factors, and provides decision support. Full article

High-Andean lakes are strategic freshwater ecosystems whose monitoring is essential for effective water resource management. However, their optical complexity limits the applicability of conventional methods. In this study, the water quality conditions of the Ozogoche lakes, located in Sangay National Park (PNS), were assessed using Sentinel-2 (S2), Landsat-8 OLI (L8), and Landsat-9 (L9) imagery processed with automated water products from the Case 2 Regional Coast Colour (C2RCC) processor, including the C2RCC, C2X-COMPLEX, and C2X versions. Comparisons between in situ chlorophyll-a (Chl-a) measurements and satellite-derived products confirmed that C2RCC achieved the lowest error (RMSE = 0.68 mg/m³). The multitemporal analysis (2016–2024) of Chl-a, total suspended solids (TSSs), and the diffuse attenuation coefficient (kd_z90max) revealed interannual variations. The results consistently classified the lakes as ultra-oligotrophic, providing an integrated perspective of their environmental quality. This study demonstrates the reliability of C2RCC products for monitoring high-Andean aquatic ecosystems and underscores the potential of remote sensing to overcome accessibility and cloud cover constraints, delivering valuable insights for the sustainable management of water resources in protected areas. Full article

Foxtail millet is a vital grain whose amino acid content affects nutritional quality. Traditional detection methods are destructive, time-consuming, and inefficient. This work established a rapid and non-destructive method for detecting essential amino acids in the foxtail millet. To address these limitations, this study developed a rapid, non-destructive approach for quantifying eight essential amino acids—lysine, phenylalanine, methionine, threonine, isoleucine, leucine, valine, and histidine—in foxtail millet (variety: Changnong No. 47) using near-infrared hyperspectral imaging. A total of 217 samples were collected and used for model development. The spectral data were preprocessed using Savitzky–Golay, adaptive iteratively reweighted penalized least squares, and standard normal variate. The key wavelengths were extracted using the competitive adaptive reweighted sampling algorithm, and four regression models—Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), Convolutional Neural Network (CNN), and Bidirectional Long Short-Term Memory (BiLSTM)—were constructed. The results showed that the key wavelengths selected by CARS account for only 2.03–4.73% of the full spectrum. BiLSTM was most suitable for modeling lysine (R² = 0.5862, RMSE = 0.0081, RPD = 1.6417). CNN demonstrated the best performance for phenylalanine, methionine, isoleucine, and leucine. SVR was most effective for predicting threonine (R² = 0.8037, RMSE = 0.0090, RPD = 2.2570), valine, and histidine. This study offers an effective novel approach for intelligent quality assessment of grains. Full article

Urban transportation is a major source of air pollution. On urban highways, driver behavior significantly influences vehicle emissions, as tailpipe pollutants depend on driving patterns. Therefore, estimating the emission factors of key pollutants namely carbon monoxide (CO), carbon dioxide (CO₂), nitrogen oxides (NO_X), and hydrocarbons (HC) is essential. This study investigates the impact of driver behavior on environmental pollutants and derives field-based emission factors on urban highways in Mashhad, Iran, during June 2022. A total of 150 drivers were classified using the K-means algorithm based on their aggressiveness scores from the Driver Behavior Questionnaire (DBQ), maximum acceleration, frequency of maximum acceleration events, and the number of traffic accidents recorded over the past five years. The clustering quality was evaluated using the Silhouette score, leading to two categories: aggressive and non-aggressive drivers. Cochran’s formula was applied to select 10 drivers from each group, and emissions were measured using an onboard monitoring device. Results indicate that aggressive drivers exhibit higher speeds, more pronounced acceleration and deceleration (A/D) patterns, and elevated engine RPM compared with non-aggressive drivers. Spearman’s rank correlation analysis revealed a strong and significant relationship between engine RPM and tailpipe emissions in both driver groups, indicating increased emissions at higher RPMs. In contrast, A/D behavior showed no significant association with emissions, suggesting a minimal direct effect. Overall, emission factors for NO_X, CO₂, CO, and HC were 37.50%, 23.60%, 41.90%, and 53.13% higher, respectively, in aggressive drivers compared with non-aggressive drivers. Furthermore, the Mann–Whitney U test confirmed statistically significant differences in tailpipe emissions between the two groups. These findings demonstrate that distinct driving behaviors are closely linked to variations in vehicular emissions. Full article

This study employs an integrated framework that combines field-based measurements, remote sensing, and Geographic Information Systems (GISs) to monitor vegetation dynamics and assess the suitability of a steppe range reserve for livestock grazing. Forty-three surface and subsurface soil samples were collected in April and November 2021 to capture seasonal variations. Above-ground biomass (AGB) measurements were recorded at five sampling locations across the reserve. Six Sentinel-2 satellite imageries, acquired around mid-March 2016–2021, were processed to derive time-series Normalized Difference Vegetation Index (NDVI) data, capturing temporal shifts in vegetation cover and density. The GIS-based Multi-Criteria Decision Analysis (MCDA) was employed to model the suitability of the reserve for livestock grazing. The results showed higher salinity, total dissolved solids (TDSs), and nitrate (NO₃) values in April. However, the percentage of organic matter increased from approximately 7% in April to over 15% in November. The dry forage productivity ranged from 111 to 964 kg/ha/year. On average, the reserve’s dry yield was 395 kg/ha/year, suggesting moderate productivity typical of steppe rangelands in this region. The time-series NDVI analyses showed significant fluctuations in vegetation cover, with lower NDVI values prevailing in 2016 and 2018, and higher values estimated in 2019 and 2020. The grazing suitability analysis showed that 13.8% of the range reserve was highly suitable, while 24.4% was moderately suitable. These findings underscore the importance of tailoring grazing practices to enhance forage availability and ecological resilience in steppe rangelands. By integrating satellite-derived metrics with in situ vegetation and soil measurements, this study provides a replicable methodological framework for assessing and monitoring rangelands in semi-arid regions. Full article

Leptospirosis is a globally distributed zoonosis of major public health and veterinary relevance, caused by pathogenic species of the genus Leptospira. Brazil is a hotspot for transmission due to its ecological diversity and complex host–environment interfaces. This study explored the genetic diversity and structure of circulating pathogenic Leptospira spp. in Brazil through a single-locus sequence typing (SLST) analysis based on the secY gene. A total of 531 sequences were retrieved from GenBank and subjected to phylogenetic and haplotype diversity analyses. Maximum likelihood reconstruction revealed strongly supported clades for seven species, with L. interrogans being the most prevalent and broadly distributed across hosts and regions. This species showed evidence of clonal expansion, with a dominant haplotype (n = 242) shared by humans, domestic animals, and wildlife. In contrast, L. santarosai and L. noguchii exhibited high haplotypic diversity and reticulated network structures, reflecting greater evolutionary variability. The species L. kirschneri and L. borgpetersenii displayed reduced haplotypic variation, the latter mainly associated with cattle, consistent with its host-adapted profile. Host- and biome-based haplotype networks revealed both the broad ecological adaptability of certain lineages and the exclusive presence of haplotypes restricted to specific environments, such as those found in marine mammals from the Atlantic Ocean. Genetic distance analyses confirmed the strong taxonomic resolution of the gene secY, which effectively distinguished closely related species while capturing intraspecific diversity. These findings provide a comprehensive molecular overview of pathogenic Leptospira in Brazil, highlighting ecological connectivity across hosts and biomes, as well as the contrasting evolutionary dynamics among species. Beyond describing genetic patterns, our analyses emphasize evolutionary processes, host–environment connectivity, and the implications for One Health. This integrative framework strengthens the basis for surveillance and control strategies in other endemic regions in the world. Full article

Mercury (Hg) is a pervasive environmental contaminant with high bioavailability and toxicity, accumulating in aquatic food chains and posing significant risks to human health through seafood consumption. This systematic review aims to collect evidence on Hg bioaccumulation in seafood across Europe, assessing species that exceed legal limits. A total of 74 studies were identified on bioaccumulation among marine fish and seafood from European and adjacent seas, published between 2000 and 2024. Findings highlight that methylmercury (MeHg) constitutes the majority of total Hg in fish species, with concentrations often exceeding EU regulatory limits, especially in the Adriatic and Iberian areas. In general, teleosts exhibit higher tissue concentrations of both MeHg and total Hg compared to either selachians or mollusks. Species likely to exceed their legal limits are larger, apex predators, e.g., tuna, swordfish, and sharks, as well as benthic species, e.g., monkfish and mullet. In recent years, there has been a decrease in mercury contamination, probably due to agreed international regulations. However, significant regional variations still persist in Europe. To mitigate Hg contamination in seafood and ensure food safety, this study highlights the need for ongoing monitoring and management strategies, the interplay of environmental factors, food web dynamics, and species-specific biological characteristics. Full article

Mixed cell heights pose significant challenges to placement in large-scale integrated circuits. In particular, the heterogeneity of cells remarkably complicates the legalization of mixed-cell-height cells. To preserve the global placement results as much as possible, we propose to directly optimize the total displacement through $l_1$-norm minimization. For illegal cells that extend beyond the chip boundaries, the netlist information of cells is taken into account and a mixed-integer programming model is employed to determine the optimal placement that minimizes the half-perimeter wirelength (HPWL) variation. This joint optimization strikes a balance between minimizing geometric displacement and HPWL, ensuring that the legalization process remains compact to achieve better placement performance. Experimental evaluations on mixed-cell-height benchmarks demonstrate that the proposed approach achieves smaller total displacement and notably lower HPWL variation within practical time limits compared with state-of-the-art legalization methods. Moreover, this work provides a scalable foundation for future extensions to three-dimensional (3D) IC placement legalization. Full article

Mannitol dehydration is routinely used to prevent and treat cerebral damage after total aortic arch replacement (TAAR), but existing neuroimaging technologies cannot achieve bedside real-time quantitative assessment of its impact on cerebral perfusion in different patients. This study applied dynamic cerebral perfusion electrical impedance tomography (DCP-EIT), a non-invasive neuroimaging technique, for bedside cerebral perfusion monitoring in TAAR patients during dehydration. Seventeen patients with normal neurological function and nineteen with neurological dysfunction (ND) were enrolled. The variation patterns and differences in perfusion impedance, images, and the relative ratios (RY) of mean perfusion velocity (MV), height of systolic wave (Hs), inflow volume velocity (IV), and angle between the ascending branch and baseline (A_ab) were analyzed. Results showed DCP-EIT could visualize cerebral perfusion changes, with detected poorly perfused regions showing good consistency with ischemic areas identified by computed tomography (CT). RY of normal patients fluctuated around 0.97–1.04, with no significant difference from baseline. RY of ND patients peaked at 14–20 min after dehydration and remained higher than baseline even at 100 min (p < 0.001). DCP-EIT holds potential to optimize individualized cerebral protection strategies for other cerebral damage scenarios and neurocritical care. Full article

The genetic diversity of cultivated crops is limited, largely as a result of domestication bottlenecks and the selective pressures imposed during modern breeding. An introgression cross was initiated by mating bitter apple (Citrullus colocynthis), as a wild founder parent, with ‘Charleston Grey’ watermelon (Citrullus lanatus) commercial cultivar, focused on identifying and utilizing trait-enhancing alleles from crop wild relative (CWR). Successful crosses resulted in diverse families, including F₁ hybrids, F₂ population, and backcross (BC) progenies. The study revealed substantial variation among the founder parents and their derived progeny in plant growth and major agronomic fruit traits, highlighting the value of this genetic diversity for breeding programs and demonstrating the potential of Citrullus introgression lines to enhance desired traits in cultivated watermelon. Morphological analysis demonstrated that F₁ progeny resembled the maternal parent for the majority of investigated fruit traits. A considerable proportion of the introgression progeny in the F₂ generation outperformed both parents in total soluble solids and lycopene content, suggesting that crop wild relatives hold strong breeding value through beneficial allelic recombination. BC₁ siblings were closer to the wild watermelon, which is presumably maternally controlled through plastome and mitogenome in crosses between cultivated watermelon and wild bitter apple, which is expected to be retained in successive backcrosses. The study uncovers novel alleles of CWR that preserve extensive genetic variation that is essential for enhancing resilience traits in current breeding lines. These introgression-derived resources provide a critical platform for advancing genetic studies and enhancing crop resilience. Full article

Pediatric obesity is rising globally, and emerging evidence suggests that sleep timing may influence metabolic health through epigenetic mechanisms. This study investigated epigenome-wide DNA methylation patterns associated with bedtime in children and explored their biological relevance. Children aged 6–10 years were classified as early (≤8:30 PM) or late (>8:30 PM) bedtime groups. Saliva-derived DNA was analyzed using the Illumina Infinium MethylationEPIC BeadChip Array, and the Sparse Wrapper Algorithm (SWAG) was applied to identify differentially methylated loci. A total of 1006 CpG sites, representing 571 unique genes, were significantly associated with bedtime (p < 0.001). Significant methylation differences were observed between early and late bedtime groups, with ABCG2, ABHD4, MOBKL1A, AK3, SDE2, PRAMEF4, CREM, CDH4, BRAT1, and SDK1 showing the most consistent variation. Functional enrichment analyses (Gene Ontology, KEGG, and DisGeNET) conducted on the SWAG-identified gene set revealed enrichment in biological processes including peptidyl-lysin demethylation, regulation of sodium ion transport, DNA repair, and lipo-protein particle assembly. Key KEGG pathways included circadian entrainment, neurotransmission (GABAergic, dopaminergic, and glutamatergic), growth hormone synthesis, and insulin secretion. DisGeNET analysis identified associations with neurodevelopmental disorders and cognitive impairment. Cross-comparison with established sleep and obesity gene sets identified ten overlapping genes(CDH4, NR3C2, ACTG1, COG5, CAT, HDAC4, FTO, DOK7, OCLN, and ATXN1). These findings suggest that variations in bedtime during childhood may epigenetically modify genes regulating circadian rhythm, metabolism, neuronal connectivity, and stress response, potentially predisposing to later-life developmental, and metabolic challenges. Full article

This study aims to identify the most effective irrigation rates for Manfalouty pomegranate trees to enhance their growth, yield, bioactive compound content, and fruit quality. Additionally, the research evaluates the effects of foliar spray applications of glycine, ascorbic acid, and riboflavin on the physiological responses of the trees. Morphological, physiological impacts, and fruit quality treatments were analyzed using Pearson correlation and cluster analysis. As irrigation levels were reduced up to 60%, all vegetative characters demonstrated a significant drop. Glycine treatment enhanced yielding shoot lengths, leaf area, and leaf number. Among the key findings was that there were no appreciable variations between 100% ETc and 80% ETc with riboflavin or glycine spraying for leaves total chlorophyll. Leaves treated with glycine, ascorbic acid, and riboflavin spraying had higher levels of total antioxidants, total phenols, and total flavonoids, while glycine gives the highest results and enhanced the antioxidant system of pomegranate leaves. Reducing irrigation from 100% to 60% ETc in both seasons, respectively, resulted in a progressive decrease in yield (ton/fed.), and fruit creaking (%); this effect was overcome using the glycine foliar spraying. The results also demonstrated that all spray treatments reduced the cracking rate, with the glycine spray treatment being the most effective in this respect that enhanced also fruit length, fruit diameter, fruit weight, and arils weight %, total soluble solids, total sugar, anthocyanin, vitamin C, and the antioxidant contents. The findings provide valuable insights for sustainable pomegranate cultivation practices that maximize productivity and quality while maintaining plant health using low irrigation and glycine as foliar sprayer. Full article

Larrea cuneifolia Cav. (common name: jarilla macho) is an endemic Argentinian medicinal shrub that has traditionally been used by the Diaguita-Calchaquí communities in the Monte Desert region in northwestern Argentina. The aim of the present study was to analyze the phytochemical profile and biological activity of the aerial parts of jarilla collected in different places throughout the year, in different seasons and times of day, to determine the optimal harvesting conditions for promoting its medicinal use. The aerial parts were collected three times a day over the course of four seasons in eight L. cuneifolia populations. The total phenolic compounds (TPCs), total flavonoid (TF) content, total lignans (TL), sugars (S) and soluble protein (SP) content were quantified by using spectrophotometric methods and HPLC-DAD. Antioxidant activity was determined by using ABTS scavenging. Significant seasonal, diurnal and spatial variations in the accumulation of TPC (52.61 to 113.52 mg GAE/g), TF (3.71 to 17.92 mg QE/g), TL (283 to 582 μg NDHGAE/g); S (5.73 to 15.17 mg GE/g) and SP (36.75 to 103.10 mg BSAE/g) in aerial parts of L. cuneifolia were revealed. The highest concentrations of TPC and TF were recorded in spring mornings. Maximum accumulation of nordihydroguaiaretic acid (291.8 ± 2.8 μg NDHGAE/mg dry weight) and other lignans were also observed in spring. Heat map analyses pinpoint Ampimpa (Site 1) as a site for jarilla sustainable harvesting, balancing high metabolite content with population abundance, especially in spring, when the highest antioxidant activity (SC₅₀ = 1.560 ± 0.021 μg GAE/mL) coincides with increased phenol levels. These studies highlight the importance of integrating ecological and phytochemical data to define harvesting strategies; collecting during spring mornings optimizes the yield of bioactive compounds, simultaneously minimizing ecological pressure. This study demonstrates how seasonal bioprospecting can inform pharmacological research and local development while safeguarding the endemic plant population. Full article