Search Results (8,928)

This study aims to identify and evaluate the impact of operational and organizational activities on reducing energy consumption in selected stages of agricultural transport equipment component production. The research focused on manufacturing companies from the agricultural machinery sector, characterized by high energy intensity and operational complexity. The empirical study was conducted among 121 experts representing manufacturing enterprises. The results indicate that enterprises achieve the highest level of implementation in organizational and Lean Manufacturing-related activities, particularly in reducing downtime, optimizing production scheduling, limiting empty transport runs, and eliminating overproduction. In contrast, technological and investment-intensive solutions, such as heat recovery systems, advanced energy monitoring, and digital simulation tools, remain implemented to a significantly lower extent. The findings also reveal a moderate level of maturity in energy management practices and limited integration of energy-related data into strategic decision-making processes. The study confirms the multidimensional nature of energy efficiency and highlights the importance of integrating Lean Manufacturing principles with digital technologies and systemic energy management. The proposed research model may serve as a practical diagnostic tool supporting the identification of key improvement areas for sustainable production development in manufacturing enterprises. This study aims to identify and evaluate the impact of operational and organizational activities on reducing energy consumption at selected stages of agricultural transport equipment component manufacturing. The research focused on manufacturing companies operating in the agricultural machinery sector, which is characterized by high energy intensity and operational complexity. The empirical study involved 121 experts representing manufacturing enterprises. The results indicate that organizational and Lean Manufacturing-related practices exhibit the highest levels of implementation, particularly those aimed at reducing downtime, optimizing production scheduling, limiting empty transport runs, and eliminating overproduction. In contrast, technology-intensive and capital-intensive solutions, such as heat recovery systems, advanced energy monitoring, and digital simulation tools, show substantially lower implementation levels. The findings also reveal a moderate level of maturity in energy management practices and limited integration of energy-related data into strategic decision-making processes. The findings confirm the multidimensional nature of industrial energy efficiency and highlight the importance of integrating Lean Manufacturing principles with digital technologies and systematic energy management. The proposed research model may serve as a practical diagnostic tool for identifying key areas for improvement in the development of sustainable manufacturing. Full article

The digitalization of healthcare systems has transformed the production, storage, and sharing of clinical information. While electronic health records (EHRs) enhance care efficiency, accessibility, and continuity, they simultaneously introduce complex ethical, legal, and cybersecurity challenges that directly affect patient interests. This narrative review examines the emerging rights associated with digital health records, particularly the right to privacy and the right to be forgotten, alongside threats to confidentiality, cybersecurity, and patient safety. A comprehensive literature search was conducted across PubMed, Web of Science, MEDLINE, and the Cochrane Library. First, the right to be forgotten appears particularly relevant for oncological patients facing financial discrimination and for individuals asserting gender identity rights, yet it cannot be unconditionally extended to genetic data, given its relevance to relatives and future generations. Second, confidentiality risks are amplified by re-identification vulnerabilities, unauthorized access by personnel, and the broad connectivity of digital systems. Third, the secondary use of data from EHRs, including artificial intelligence (AI) integration, commercial exploitation, and large language model training, raises substantial privacy concerns. Fourth, ransomware, phishing, and data breaches can erode patient trust. In this article, we analyze these issues within the evolving European regulatory framework, highlighting the tension between individual privacy rights and broader public interests. We argue that robust data protection must be balanced with scientific progress and that this requires opt-in consent frameworks, staff training, and transparent AI governance. Full article

Chili products are vulnerable to the addition of unauthorized substances, including Sudan dyes, Rhodamine B, Basic Orange 2, poppy-derived materials and improperly used processing chemicals. Their analysis is complicated by the high contents of lipids, carotenoids, capsaicinoids and other co-extracted matrix components in chili powder, chili oil, chili sauce and composite seasonings. This review critically evaluates conventional and emerging sample-preparation strategies, including solid-phase extraction; the quick, easy, cheap, effective, rugged and safe (QuEChERS) procedure; deep eutectic solvent (DES)-assisted extraction; enhanced matrix removal for lipids (EMR-Lipid); and molecularly imprinted sorbents. Laboratory methods based on high-performance liquid chromatography (HPLC), liquid chromatography–tandem mass spectrometry (LC–MS/MS) and gas chromatography–mass spectrometry (GC–MS) are compared with enzyme-linked immunosorbent assay (ELISA), surface-enhanced Raman spectroscopy (SERS), electrochemical sensors, miniature mass spectrometry and artificial intelligence-assisted hyperspectral imaging (AI–HSI). The comparison considers representative limits of detection and quantification, recovery, precision, sample-preparation burden, cost, portability, validation status and regulatory role. LC–MS/MS remains the preferred confirmatory platform for targeted multi-residue analysis, whereas rapid and portable methods are more appropriate for screening and sample triage. A three-tier workflow linking rapid screening, laboratory confirmation, and emerging-risk identification and traceability is proposed. Future priorities include standardized chili reference materials, open AI training and validation datasets, greener DES-based extraction and interlaboratory validation of field-deployable methods. Full article

The growing volume of plastic waste produced has made the need for efficient identification and quantification strategies to detect and identify harmful contaminants, particularly heavy-metals, in industrial plastic-waste streams more urgent than ever. Traditional chemical digestion methods (acid digestion, ICP-MS, or AAS) provide accurate quantification and are time-consuming, costly, and not high-throughput-sorting. Laser-induced breakdown spectroscopy (LIBS) offers several advantages, including rapid real-time analysis, minimal sample preparation, multi-element detection, and efficient elemental characterization. The current review aims to investigate the possibility of using the LIBS technique to detect and quantify some heavy-metals like lead (Pb), cadmium (Cd), chromium (Cr), and arsenic (As) in heterogeneous industrial plastic wastes. The calibration strategies (reference standards) as well as optimization of the signal response and algorithms for data processing, including chemometric models, are evaluated to reduce the limit of detection and enhance analytical accuracy. The results indicate that LIBS can detect heavy-metal contamination at concentrations relevant to regulatory limits and can be scaled for online quality-control monitoring in plastic recycling facilities. In this review, the results have been summarized to support the use of LIBS for waste management towards environmental compliance, reduced use of hazardous materials in recycling products, and reduced health problems due to heavy-metal pollution. Full article

Bee bread is a fermented product derived from bee pollen, whose fermentation improves preservation, nutrient bioavailability, and functional properties. However, the microbial succession driving this process, particularly the role of yeasts, remains poorly understood. This study investigated microbial dynamics during fourteen-day spontaneous fermentation of five fresh bee pollen samples from different geographical origins, mimicking natural bee bread formation. Cultivable yeasts and lactic acid bacteria were monitored by viable cell counts and molecular identification. Physicochemical parameters, nutritional components, bioactivities, and pollen structure were evaluated. A clear microbial succession was observed, with Starmerella sp. dominating the early stages and the osmotolerant yeast Zygosaccharomyces rouxii prevailing during the final phase. Together with Apilactobacillus kunkeei, these microorganisms may constitute a cultivable fermentative core involved in bee bread formation. Fermentation significantly increased protein availability, with increases of up to 18%, reduced pH, promoted bee pollen degradation up to 16%, and enhanced antimicrobial activity against Staphylococcus aureus and Listeria monocytogenes. Understanding of cultivable microbiota dynamics during spontaneous bee pollen fermentation could provide an effective natural strategy to stabilize bee pollen while improving its nutritional and functional properties, laying the foundation for developing controlled industrial fermentations to produce bee bread-like products with consistent quality and health-promoting characteristics. Full article

Edge chamfering is a critical process in glass manufacturing because it suppresses crack propagation and improves both edge strength and operational safety. As such, it has become an essential step in modern glass production. However, in current automated production lines, chamfer quality inspection still relies heavily on manual visual inspection and contact-based measuring instruments, which are limited by low efficiency, strong subjectivity, and poor compatibility with production-line takt time. To overcome these limitations, this paper proposes a vision-based inspection method for transparent glass chamfers using corner analysis, and a dedicated glass chamfer inspection system is developed for experimental validation. First, machine-vision image processing is applied to enhance chamfer-region features and improve detection robustness. Candidate endpoint generation is then combined with the construction of an endpoint-screening coordinate system to achieve stable localization of chamfer endpoints. In addition, quadrant-based spatial constraints are introduced to further enhance endpoint localization stability, enabling automatic measurement of key geometric parameters, including chamfer length, width, and height. On this basis, multiple defect-discrimination criteria are established by integrating geometric tolerance violations with spatial abnormalities in endpoint distribution, thereby enabling automatic identification of chamfer defects. Experimental results show that the proposed method achieves a mean absolute measurement error of 0.087 mm and an average inspection time of 0.505 s per workpiece. The method can also effectively identify chamfer defects, demonstrating its suitability for online inspection while maintaining both dimensional measurement accuracy and defect detection capability. Full article

High-angle fractures are widely developed in ultra-low permeability reservoirs in the Ordos Basin, and their propagation has a significant influence on waterflooding performance. However, few studies have focused on the identification of high-angle fractures, let alone the impact of their propagation on waterflooding performance. Therefore, a waterflooding model considering dynamic fracture propagation was developed to evaluate the impact of fracture propagation on waterflooding performance in this study. Firstly, based on the logging response characteristics of high-angle fracture intervals, the high-angle fracture identification model was established by the fuzzy comprehensive evaluation method, and a comprehensive index was proposed to identify high-angle fracture intervals. A threshold of approximately 70 effectively distinguishes high-angle fracture intervals from non-high-angle fracture intervals. After that, the waterflooding model considering dynamic fracture propagation was established to investigate the effect of its parameters on waterflooding performance. A smaller initial leak-off coefficient and a faster decline rate reduce fluid loss, promote fracture propagation, and ultimately improve oil recovery. Higher injection rates promote dynamic fracture propagation, accelerate water cut rise, mitigate production decline, and enhance cumulative oil production, while improving the waterflooding response of wells along the fracture direction. Optimal well group performance is achieved at a fracture orientation of 45°, beyond which production declines. Increasing well spacing reduces the water cut rise rate and the production decline rate, thereby improving cumulative oil production. However, it leads to a faster production decline in the early development stage. This work could provide theoretical guidance for waterflooding in ultra-low permeability reservoirs. Full article

Vacuum freeze drying significantly influences the water status and aroma characteristics of mulberry. This study monitored the dynamic changes in water distribution, non-volatile components, and key aroma-active compounds during a 72 h drying process. The results showed that free water decreased from 85.3% to 5.96% at 12 h and then leveled off, marking the entry of the drying process into a slow moisture-change stage. This transition in water status coincided with marked changes in non-volatile and volatile components. After 12 h, the decreases in most free amino acids and reducing sugars, as well as the consumption of linoleic acid, slowed markedly after 12 h; the contents of fruity compounds (ethyl isovalerate, β-ionone) and hexanal decreased by more than 50% within the first 12 h and then stabilized, whereas the lipid oxidation product (E)-2-nonenal began to increase continuously after 12 h. Correlation analysis revealed that free water and bound water were positively correlated with fruity compounds and (E)-2-nonenal, respectively, while linoleic acid was negatively correlated with (E)-2-nonenal. Principal component analysis and hierarchical cluster analysis further supported the identification of 12 h as a potential turning point for both water status and flavor transformation. Collectively, these findings suggest a coupling relationship between water status and flavor evolution during drying, providing a basis for optimizing vacuum freeze-drying processes to better preserve the characteristic aroma of mulberry. Full article

Vitamin D comprises a group of fat-soluble secosteroids traditionally associated with animal physiology, calcium-phosphate homeostasis, and skeletal metabolism. However, vitamin D and related compounds have also been reported in taxonomically distinct non-animal systems, including fungi, microalgae, other algae, phytoplankton, and higher plants, although the strength of evidence differs substantially among these groups. This review synthesizes current knowledge on the occurrence, structural chemistry, UV-B-driven photochemical mechanisms, environmental determinants, analytical challenges, and biofortification potential of vitamin D formation in photosynthetic organisms and fungi. Vitamin D synthesis is initiated by UV-B radiation, primarily within the 290–315 nm range, which converts sterol precursors such as 7-dehydrocholesterol and ergosterol into previtamin D intermediates and is followed by thermal isomerization to the corresponding vitamin D forms. Continued irradiation may additionally generate lumisterol, tachysterol, and other photoproducts, thereby limiting net vitamin D accumulation. This non-enzymatic mechanism supports the interpretation that vitamin D formation can occur outside vertebrates when an appropriate 5,7-diene sterol precursor is accessible to a sufficient UV-B dose. In photosynthetic organisms and fungal matrices, net vitamin D accumulation is constrained by the spectral dose of UV-B, environmental exposure, tissue architecture, sterol localization, oxygen availability, antioxidant capacity, and ROS-mediated degradation. Studies of microalgae and phytoplankton, including reports concerning Emiliania huxleyi, suggest the occurrence or UV-B-dependent formation of both vitamin D₂ and vitamin D₃. However, these findings require evaluation according to the analytical method, use of authentic standards, experimental conditions, and confidence of compound identification. In fungi, the UV-B-induced conversion of abundant ergosterol to vitamin D₂ is well established. Microalgae represent a developing source of vitamin D₂ and vitamin D₃, whereas evidence for nutritionally relevant vitamin D accumulation in higher plants remains limited and heterogeneous. Although higher plants contain diverse phytosterols, the formation of vitamin D₄, vitamin D₅, or related analogues requires appropriate photoreactive 5,7-diene precursors and should not be inferred directly from the presence of common phytosterols such as β-sitosterol. Analytical detection remains challenging because of low concentrations, complex lipophilic matrices, and structural similarity among secosteroids and photoproducts; therefore, reliable identification requires validated analytical procedures. LC-MS/MS provides high sensitivity and selectivity but should be supported by authentic standards, preferably isotope-labelled internal standards, retention-time agreement, quantitative and qualifying ions, matrix-recovery assessment, limits of detection and quantification, and evaluation of ion suppression. Structurally similar analogues and photoproducts may additionally require orthogonal confirmation. Nutritionally, post-harvest UV-B enrichment of edible mushrooms is currently the best-validated strategy for increasing non-animal vitamin D₂ content. Microalgae constitute a developing platform for vitamin D₂ and vitamin D₃ production, whereas biofortification of higher plants remains experimental. Full article

The building envelope is a key lever for reducing energy demand and carbon emissions in the built environment. However, conventional envelope systems remain largely static and are unable to respond effectively to changing climatic conditions. Biomimetics has emerged as a promising approach for the development of climate-adaptive envelope solutions. Nevertheless, research in this field remains fragmented across disciplines, and its evolution and technological maturity have not yet been systematically assessed. This study proposes an integrated analytical framework combining a bibliometric analysis of 2.007 Scopus-indexed documents, based on a VOSviewer keyword co-occurrence network, with a cluster-guided state of the art review, and a Technology Readiness Level (TRL) assessment of selected biomimetic envelope solutions. The TRL assessment is conducted using explicit operational criteria. The analysis identifies three main research clusters: (C1) environmental-performative, focusing on energy efficiency and envelope optimisation; (C2) material-experimental, addressing biomimetic composites and innovative materials; and (C3) technological fabrication, centred on digital fabrication, smart materials, and 4D printing. Temporal trends reveal a shift after 2018 from materials science-oriented studies towards computational design and adaptive manufacturing, providing quantitative evidence of a transition previously described mainly in qualitative terms. The review highlights a strong focus on solar-shading applications, while energy harvesting and passive thermoregulation remain comparatively underexplored. The TRL assessment shows that more than 80% of the analysed solutions are concentrated at TRL 3, indicating an early stage of technological development. The main barriers include limited material durability, non-standardised production costs, and regulatory constraints. The findings suggest that future progress will depend less on the identification of new biological inspirations and more on advancing the technological maturity and industrial scalability of existing concepts. This will require integrated developments in materials, parametric design, life-cycle assessment, and regulatory frameworks. Full article

Soybean (Glycine max) is a key crop in China grown as a source of edible oil and plant-derived protein, and its production is closely linked to national food security. Insufficient nitrogen availability remains a key constraint on soybean yield. In legumes, symbiotic nitrogen fixation (SNF) enables the conversion of atmospheric nitrogen into bioavailable forms, thereby reducing reliance on synthetic fertilizers and improving soil quality. Nitrogenase activity is a central determinant of SNF efficiency; however, its regulatory mechanisms in soybean nodules are not yet fully understood. In this study, transcriptomic data from two soybean accessions with contrasting SNF performance (Suinong 14 and ZYD00006) were analyzed, leading to the identification of Glyma.04G013500 as a member of the GmRD22 gene family. This study verified that this gene is potentially associated with nitrogenase activity. Functional characterization revealed that this gene acts as a negative regulator of nodulation by influencing the expression of genes associated with nodule development. Haplotype analysis further uncovered a pattern consistent with domestication, as the elite haplotype (HapI) with enhanced nitrogen fixation capacity, exhibited a progressive increase in frequency from wild soybean populations to landraces and modern cultivars. These findings suggest that GmRD22 has undergone directional selection during soybean domestication and improvement. Overall, these results offer new insights into the genetic control of SNF and establish promising targets for breeding soybean varieties with improved nitrogen fixation efficiency. Full article

Background and Objectives: Baccharis dracunculifolia DC. (Asteraceae), the main botanical source of Brazilian green propolis, is recognized for its high content of bioactive secondary metabolites. Given this potential, this study aimed to characterize the chemical profile of the crude extract (CE) from the aerial parts of B. dracunculifolia and to investigate its anti-inflammatory, antiproliferative, antioxidant, and photoprotective properties. Predictive computational analyses were used to assist the interpretation of the experimental findings. Methods: The CE was obtained by dynamic maceration with ethanol and chemically characterized by UHPLC-MS/MS using external calibration curves. Anti-inflammatory activity was evaluated by inhibiting nitric oxide (NO) in RAW 264.7 macrophages, while cellular antioxidant activity (CAA) was determined in the same model. Antiproliferative activity was evaluated against the human tumor cell lines AGS, Caco-2, MCF-7, and NCI-H460, as well as non-tumor VERO cells. Additionally, antioxidant potential was investigated using classical colorimetric methods (DPPH, FRAP, and ABTS). The extract was also quantified for total phenolic and flavonoid content, as well as sun protection factor (SPF). Furthermore, complementary computational analyses included PASS prediction, SwissTargetPrediction, Gene Ontology enrichment using PANTHER, SwissADME profiling, and toxicity prediction with ProTox-III. Results: UHPLC-MS/MS analysis revealed a profile rich in flavonoids and phenolic acids and led to the identification of 14 compounds not previously reported in B. dracunculifolia according to the literature examined, notably the flavonoid morin and the phenylpropanoid coniferaldehyde detected at comparatively high concentrations (>600 µg/g). CE inhibited NO production (IC₅₀ = 62.00 µg/mL) suggesting anti-inflammatory activity, and reduced intracellular oxidation by 81% (at 2000 µg/mL) in RAW 264.7 macrophages. The extract showed total phenolic content (83.62 to 540.40 µg gallic acid equivalents/mg of CE) and high levels of flavonoids (472.00–515.00 µg quercetin equivalents/mg of CE), antioxidant activity in the DPPH assay (IC₅₀ = 0.86 mg/mL), and relevant photoprotective potential (SPF = 7.79–19.30). Antiproliferative activity was moderate to weak (GI₅₀ = 165.00–257.00 µg/mL). In silico analyses identified predicted activities, molecular targets, and enriched biological processes related to redox homeostasis, inflammation, apoptosis, and cellular responses to UV radiation, suggesting biological functions potentially associated with the identified metabolites. Conclusions: The crude extract of B. dracunculifolia demonstrated significant cellular anti-inflammatory and antioxidant activities, likely associated with its phenolic composition and the presence of metabolites reported in this study for the first time in this species, particularly morin and coniferaldehyde. These findings expand the phytochemical knowledge of B. dracunculifolia and reinforce its potential as a source of bioactive compounds for pharmaceutical, nutraceutical, and photoprotective applications. Full article

The chemical composition of chocolate is influenced by multiple factors, including cocoa genotype, fermentation, roasting, and formulation, which complicate the identification of reliable compositional descriptors. In this study, amino acid and biogenic amine profiles were determined by LC–MS/MS in 91 commercial dark chocolates (56–100% cocoa content) to assess their potential for product characterization. Because the analytical sequence extended over several days, different signal-correction strategies (including internal standard normalization and quality-control-based drift correction) were evaluated to compensate for instrumental variability prior to chemometric analysis. Signal reductions of up to 91% were observed, and the selected correction procedures improved measurement precision by up to 18-fold. A total of 19 amino acids and 8 amines were detected, with tyrosine, hydroxyproline, proline, leucine, phenylalanine, and valine being the most abundant compounds. Principal Component Analysis revealed a compositional gradient primarily associated with cocoa content, whereas classifications based on cocoa variety, geographical origin, and certification status showed limited discrimination. In contrast, Partial Least Squares-Discriminant Analysis achieved a balanced classification accuracy of 75.2% under repeated M-fold cross-validation when classifying samples according to manufacturer. Furthermore, permutation tests were carried out, confirming that the observed classification performance was highly unlikely to arise by chance. These findings indicate that amino acid and biogenic amine profiles in commercial dark chocolates are influenced mainly by cocoa content and manufacturer-related factors, whereas the effects of cocoa origin and variety appear less evident within the products evaluated. Full article

Staphylococcus aureus (S. aureus) is a significant pathogen that causes foodborne diseases. Meat, with its abundant nutrients and high water activity, constitutes an ideal niche for S. aureus colonization. Numerous studies have shown that human digestive tract diseases caused by consuming meat products contaminated with S. aureus occur frequently. It is of great significance to strictly monitor S. aureus in meat matrices. A novel biosensor employing dual-signal output was developed through the combination of efficient magnetic separation and dual-modal precise detection. Designed for the rapid enrichment of S. aureus, it significantly boosts detection sensitivity and accuracy, thereby enabling the earlier identification of potential contamination sources. This method uses vancomycin-modified magnetic beads as the capture element, and aptamer-modified nanozymes as the signal element. After magnetic separation, the 3,3′,5,5′-tetramethylbenzidine color reaction can be used to quickly and sensitively detect S. aureus. It achieved a detection limit as low as 10 cfu/mL. Moreover, this dual-signal sensor based on efficient magnetic separation can sensitively detect S. aureus in meat products, thus showing good application prospects in food matrices and further improving the reliability and specificity of detection. Full article

Potato late blight, Phytophthora infestans, remains a major global threat to potato production due to the rapid genetic change, long-distance dispersal and fungicide resistance. To clarify the genetic structure and phenotypic characteristics of P. infestans populations in southwestern China during 2019–2025, this study analyzed 241 isolates collected from Sichuan, Chongqing, Guizhou, Yunnan and Hubei. The isolates were characterized using 14 SSR markers, together with mating-type determination, metalaxyl sensitivity assays, mitochondrial haplotype identification and virulence profiling. A total of 70 alleles and 118 multilocus genotypes were detected, with certain genotypes (SW-40, SW-48 and SW-81) broadly distributed across regions, while the simultaneous presence of numerous low-frequency genotypes reflected high overall genetic diversity. Population genetic analyses revealed weak regional differentiation and strong genetic connectivity, with most genetic variation occurring within regional populations, where self-fertile isolates, metalaxyl-resistant phenotypes and mitochondrial haplotype Ia were predominant. Cluster and principal component analyses separated the isolates into three major genetic groups, with the largest group containing most isolates and showing close genetic similarity to the Blue_13 reference genotype. These findings indicate that southwestern China harbors a highly diverse and admixed P. infestans population, likely driven by frequent pathogen movement among potato-growing regions. Full article