Search Results (2,274)

Accurate conductor-to-pad alignment is essential in PCB wire welding because misalignment increases rework, lowers yield, and affects product quality. In manufacturing images, precise conductor localization is challenging because the target structures are small, the boundaries are subtle, and the conductors often resemble nearby PCB pads. This study proposes an integrated vision pipeline for precision wire welding under deployment-oriented runtime requirements. The framework combines YOLOv9-Tiny for rapid conductor localization with EfficientViT-SAM for box-prompted mask refinement, enabling accurate conductor segmentation while maintaining practical inference speed. A total least squares (TLS)-based geometric method is introduced to generate x-axis correction offsets from predicted masks for alignment support. The models were validated on data from a 4-conductor system collected under production-like conditions. For box-prompted segmentation, EfficientViT-SAM-L2 achieved an mIoU of 95.9% with a mean inference time of 2.264 s, satisfying the target requirement of high segmentation accuracy and inference time below 3 s. Compared with heavier SAM variants and a transformer-based benchmark, the selected model provided a more practical balance between mask quality and computational efficiency. These results support the feasibility of mask-based offset generation for precision wire welding. Full article

Industrial polypropylene portfolios comprise multiple commercial grades differentiated by molecular architecture, phase morphology, processability, and performance. In this study, 81 industrial polypropylene grades, including 38 homopolymers, 21 random copolymers, and 22 impact copolymers, were analyzed to evaluate the chemometric organization and structure–property relationships of a complete commercial portfolio. The dataset integrated melt flow index, xylene-soluble fraction, total ethylene content, ethylene content of the rubber phase, rubber-phase fraction, and mechanical, thermal, and optical performance variables obtained from routine industrial quality-control and product-certification activities. Principal component analysis, partial least squares discriminant analysis, and variable importance in projection analysis were used to examine portfolio organization, evaluate consistency with the predefined polypropylene families, and identify the descriptors contributing most strongly to family-level discrimination. The first two principal components explained 83.8% of the total variance. They revealed a low-dimensional organization consistent with the molecular and morphological differences among homopolymer, random copolymer, and impact copolymer grades. The full-descriptor PLS-DA model achieved 98.8% cross-validated accuracy and correctly classified 80 of the 81 grades using two latent variables. This performance reflects the internal consistency between the descriptor matrix and the existing industrial family classification rather than independently validated predictive capability for unknown grades. Homopolymer differentiation was mainly associated with molecular-weight-related flow behavior, random copolymer organization with ethylene-induced modification of crystallinity, and impact copolymer differentiation with heterophasic rubber-phase characteristics. The results provide a portfolio-specific chemometric workflow for grade organization and structure–property interpretation. However, the numerical domain boundaries and their transferability require validation using independent polypropylene portfolios from other producers. Full article

Although vegetation restoration is widely applied to reverse desertification in alpine sandy lands, its duration-dependent coordination of soil phosphorus (P) pools and biological P cycling remains unclear. We examined alpine sandy lands restored with Salix cupularis for 5, 10, 15, and 20 years on the eastern Qinghai-Tibet Plateau, using non-restored natural sandy land (CK) as the control. Systematic measurements included soil total P (TP), available P (AP), the P activation coefficient (PAC), labile, moderately labile, and non-labile P fractions, microbial biomass P (MBP), five phosphatase activities, and the relative abundances of phoC, phoD, and pqqC. Relative to CK, restoration significantly increased every measured indicator except non-labile P. After 20 years of restoration, surface-soil AP and PAC exceeded the control by 174.9% and 133.7%, respectively. Non-labile P content remained statistically unchanged, although its proportional contribution declined as TP and the more available P pools increased. Exploratory partial least-squares structural equation modeling summarized positive associations from P-cycling genes to enzymes (path coefficient = 0.980), from enzymes to active P fractions (0.893), and from active P fractions to P-availability indicators (0.800; all p < 0.01). Whereas, the direct enzyme–P availability association was not significant. This study shows that restoration duration is associated with P accumulation and coordinated microbial–enzymatic cycling that redistributes soil P toward more available pools without detectable depletion of non-labile P. Full article

Soil microbial carbon use efficiency (CUE) is an essential metric for assessing soil carbon cycling efficiency. In contemporary biogeochemical models, microbial CUE is often treated as a constant, but it is intricately regulated by biotic and abiotic factors, especially in heterogeneous karst rocky desertification (KRD) ecosystems. In the Guizhou Huajiang KRD area, this study used ecological stoichiometry, high-throughput sequencing, analysis of variance, and partial least squares regression to evaluate CUE across three restoration types, Zanthoxylum bungeanum (ZB), Selenicereus undatus (SU), and Pennisetum × sinese (PS), with Zea mays (ZM) as control. Results showed that restoration types affected CUE. Soil bulk density (SBD), total potassium (TK), and available phosphorus (AP) were key predictors of CUE, significantly correlating with generalist communities such as Planctomycetota, Gemmatimonadota, unclassified_Gemmatimonadaceae, unclassified_Roseiflexaceae, and unclassified_Trichomeriaceae. Inconsistent variations in α- and β- diversity across types indicated CUE regulation was driven by integrated structural and functional responses. These findings highlight the importance of soil physical properties, potassium cycling, low-phosphorus adaptation, and generalist communities for species selection. Future studies must isolate vegetation and management effects, extending observations from winter to the full growing season to clarify seasonal plant-soil-microbial feedbacks. Full article

Open banking enables customers to provide third parties with financial information, yet this will be successful only when customers are ready to share it. Previous research concentrates on security, trust, and usefulness as direct motivators without paying attention to mechanisms. This research fills this gap by evaluating the effect of Perceived Security Assurance, Trust in Banks and FinTech Providers, and Perceived Usefulness on Willingness to Share Financial Data based on Perceived Data Control, which is based on Privacy Calculus Theory. A combination of cluster and purposive sampling was used to collect data from digital banking users in five regions in Saudi Arabia. There were a total of 384 valid responses that were analysed. SmartPLS 4 was used to run Partial Least Squares Structural Equation Modelling. The results reveal that PSA, TBFP, PUOB, and PDC directly impact WSFD and that PSA, TBFP, and PUOB also have a considerable impact on PDC. The outcomes of the mediation confirm that PDC mediates these relationships partially. Multi-group analysis also shows that these effects are greater amongst users with less experience in FinTech and with younger customers, especially in the pathways that involve perceived data control. The work adds to the theory in two ways. The extension of the Privacy Calculus Theory by adding the perceived control and pointing out the heterogeneity of users in data-sharing behaviour. It also changes the attention from the general adoption intention to the actual data-sharing behaviour in open banking. Practically, the results suggest that to foster customer engagement in open banking ecosystems, it is necessary to improve security, develop trust, prove value, provide user control, and use segment-specific actions. Full article

Artificial intelligence (AI)-powered online shopping is profoundly reshaping the way in which consumers engage with sustainable clothing. However, the relationships between digital multisensory cues and perceived quality with sustainable consumption intention still need to be explored. Based on the Stimulus–Organism–Response (S-O-R) framework, the present study explores the relationships of digital multisensory cues and perceived quality with consumers’ flow experience, pleasure, and responses (e.g., engagement, loyalty, and sustainable consumption intention) in the context of AI-powered online shopping using a cross-sectional, scenario-based, assisted recall survey. A total of 571 valid responses were retained for analysis. Partial least squares structural equation modelling (PLS-SEM) was adopted for data analysis. The findings indicate that digital multisensory cues showed a positive relationship with pleasure, whereas perceived quality was positively associated with both flow experience and pleasure. Flow experience was positively linked to pleasure, which was further associated with engagement and sustainable consumption intention. Statistically significant indirect effects on sustainable consumption intention through pleasure were observed for flow experience, digital multisensory cues, and perceived quality. The results of this study offer practical implications for retailers seeking to design emotionally engaging AI-powered shopping experiences that may support sustainable consumption intention. Full article

Due to its high content of bioactive constituents and associated health benefits, Aronia melanocarpa is considered a superfood, and its consumption has increased substantially in recent years. This growing demand has led to the generation of large quantities of processed by-products, which remain rich in valuable phytochemicals and require sustainable utilization. In this study, four extraction techniques—conventional solvent extraction (CSE), pressurized liquid extraction (PLE), pulsed electric field extraction (PEF), and ultrasound-assisted extraction (UAE)—were comparatively evaluated and optimized for the recovery of bioactive compounds from aronia pomace. A second-order polynomial model (Fit Least Squares) was applied to determine the optimal conditions for each technique. The optimized extracts exhibited distinct phytochemical profiles: total polyphenol content reached 71.5 (UAE), 70.0 (CSE), 67.0 (PLE), and 48.0 (PEF) mg GAE/g dw, while total anthocyanins were 15.5 (UAE), 13.0 (CSE), 11.0 (PEF), and 3.5 (PLE) mg CyE/g dw. Antioxidant capacity ranged from 538.0 to 800.0 µmol AAE/g dw (FRAP) and 17.0 to 39.0 mmol AAE/g dw (DPPH). HPLC analysis confirmed cyanidin-3-O-glucoside as the predominant compound, with concentrations of 5.0 (UAE), 4.6 (CSE), 3.2 (PEF), and 0.8 mg/g dw (PLE). Overall, ultrasound-assisted extraction under optimal conditions provided the highest recovery of bioactive constituents, highlighting its suitability for the valorization of aronia by-products. Full article

Accurate identification of customer transformer relationships in distribution sub-zones is a fundamental prerequisite for the refined management of low-voltage distribution networks and the integration of distributed generation sources. Addressing current issues such as missing records, non-standard wiring and unclear boundaries between multiple sub-zones, this paper proposes an identification method based on the Power Admittance Regression Algorithm (PARA). Based on the fundamental laws of electrical circuits, this method constructs a regressible model of the linear relationship between the total admittance at the transformer end and the admittances at each consumer end. By utilising electrical data collected simultaneously from smart metres and distribution transformer terminals, it formulates the identification of consumer transformer relationships as a problem of minimising regression residuals. For three typical operating conditions—pure residential load, mixed residential and commercial load, and photovoltaic connection at the feeder terminus—constrained least-squares regression models and binary regression models incorporating PV variables were established respectively; ridge regression regularisation was introduced to suppress multicollinearity and enhance model robustness. Simulation tests were conducted using a dataset comprising 150 consecutive time sections and 70 test nodes (of which 60 were customers within the local substation area and 10 were interference nodes from other substation areas) for validation. The results indicate that, under the three conditions described above, in engineering simulations accounting for three-phase imbalance, random perturbations in line parameters and measurement noise, the average accuracy of this method, as determined by 100 Monte Carlo simulations, was 86.2 percent, 92.8 percent and 93.1 percent respectively, with standard deviations ranging from 1.6% to 1.9%, thereby validating its effectiveness and superiority in scenarios involving complex load structures and the integration of renewable energy. As this work is based on simulation data, further online validation using actual feeder data from electricity consumption data acquisition systems is required. Full article

This study established an activity-oriented analysis method based on offline two-dimensional liquid chromatography–electrochemical detection (2D-LC-ECD) combined with ultra-high-performance liquid chromatography–Orbitrap-MS/MS (UHPLC-Orbitrap-MS/MS), which was used to comprehensively characterize the antioxidant components of Polygonum multiflorum Thunb. leaves (PML) and screen for differential compounds in samples from different origins. Antioxidant components were screened using 2D-LC-ECD combined with in vitro radical scavenging experiments; structure identification was conducted via UHPLC-Orbitrap-MS/MS, and chemometric analysis alongside quantitative determination of 19 major components was carried out across 31 batches of samples. A total of 43 potential antioxidant compounds were identified from PML, including 11 phenolic acids, 29 flavonoids, 2 stilbene glycosides, and 1 amino acid; phenolic acids and their derivatives, along with flavonoids, were identified as major contributors to antioxidant activity. Hierarchical clustering analysis and principal component analysis both grouped samples into four categories by origin; the orthogonal partial least squares discriminant analysis model (R²X = 0.933, R²Y = 0.941, Q² = 0.846) screened 10 key markers (VIP > 1). The quantitative results showed that polygonacetophenoside had the highest content in PML. In summary, the 2D-LC-ECD coupled with LC-Orbitrap-MS/MS strategy confirmed that phenolic acids and flavonoids are the core material basis for PML’s antioxidant capacity, providing scientific evidence for the industrial development of PML as a natural antioxidant. Full article

Straw-derived biochar is increasingly used for residue recycling and soil fertility improvement, but its effects on soil inorganic phosphorus (P) fractions and their relationships with available P (AP) remain unclear. Here, we synthesized 1170 paired observations from 51 studies using meta-analysis, partial least squares path modeling, and machine learning to quantify straw biochar effects on soil AP, inorganic P fractions, microbial biomass P (MBP), and phosphatase activities, and to identify important variables related to these responses. Straw biochar increased soil AP by 77.0% and altered the distribution of inorganic P fractions. The relationships between inorganic P fractions and AP differed: Fe-bound P and occluded P showed positive and negative associations with AP, respectively, whereas Ca-bound P and Al-bound P showed no significant associations with AP. Fe-bound P and Al-bound P increased more strongly in soils with low initial AP, while higher biochar total P corresponded to weaker Fe-bound P accumulation but greater Ca-bound P accumulation. Straw biochar showed a positive response in MBP, while acid and neutral phosphatase activities showed decreasing trends, suggesting distinct microbial P cycling responses involving changes in microbial biomass P and phosphatase activities. These findings provide a P-fraction perspective for evaluating straw biochar as a site-specific amendment for soil P management. Full article

Rhododendron yedoense var. poukhanense is an important medicinal plant, but still little is known about how its bioactive flavonoids are made in different organs. Comprehensive metabolomic profiling was performed using ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS), coupled with reference-based RNA sequencing (RNA-seq), to analyze root, stem, and leaf tissues from three independent biological replicates. Subsequently, we performed two-way orthogonal partial least squares (O2PLS) regression, canonical correlation analysis (CCA), and Pearson correlation analyses. A total of 2182 metabolites were detected. Among these, 1116, 896, and 1264 metabolites exhibited differential accumulation across the three pairwise comparisons. Concurrently, 9836, 5457, and 8007 genes were differentially expressed across the three pairwise comparisons, yielding a total of 13,019 unique differentially expressed genes (DEGs). The bifunctional flavanone 3-hydroxylase/flavonol synthase (F3H/FLS) enzyme exhibited the highest expression level in roots, consistent with root-preferential biosynthesis of flavonoid skeletons and the subsequent accumulation of flavonol glycosides in this tissue. In contrast, dihydroflavonol 4-reductase (DFR) exhibited predominant activity in roots, consistent with its role in farrerol biosynthesis. The multi-omics integration model demonstrated excellent goodness-of-fit to the experimental data. Canonical correlation analysis (CCA) further revealed a robust positive association between dihydrokaempferol accumulation and kaempferol biosynthesis. These findings collectively support flavanone 3-hydroxylase (F3H) as a candidate regulatory node governing organ-specific flavonoid partitioning. However, functional validation is required to substantiate this inference. Full article

Multicomponent beef adulteration is challenging to detect rapidly due to high concealment, complex composition, and overlapping spectral features. This study employed visible–near-infrared hyperspectral imaging (400–1000 nm) combined with a Deep Feature-Enhanced Partial Least Squares Regression (DF-PLSR) model for quantitative detection and visualization of adulteration in beef. A total of 2322 samples were prepared across seven adulteration systems—single (chicken, duck, pork), binary, and ternary—with adulteration ratios from 5% to 50%. The DF-PLSR model outperformed traditional PLSR in all systems, achieving the best performance for chicken adulteration (R²p = 0.9942, RMSEP = 1.31%), with RPD > 5 for all systems. CARS and SPA reduced spectral dimensionality by 85.9% while maintaining R²p > 0.93. Pixel-level visualization achieved prediction errors < 3%, enabling intuitive identification of adulterant spatial distribution. This method provides a rapid, non-destructive, and accurate approach for detecting complex adulteration in beef, with strong potential for food safety monitoring. Full article

Background/Objectives: Medication safety is a critical concern in older adults due to age-related vulnerability, multimorbidity, and polypharmacy. Pro Re Nata (PRN, “as needed”) prescribing is common in geriatric care but may be interpreted inconsistently across healthcare professionals, potentially increasing the risk of medication errors. This study aimed to evaluate PRN prescribing patterns in hospitalized older adults and assess interprofessional perceptions of the clarity and appropriateness of PRN prescribing for conditions. Methods: We conducted a prospective, single-day observational study in a French geriatric university hospital, including all patients aged ≥65 years with at least one medication prescription. PRN prescriptions were extracted from electronic medical records and independently assessed by a pharmacist, nurse, and physician for clarity and appropriateness. Descriptive statistics summarized PRN use, chi-square tests assessed interprofessional differences, and multivariate logistic regression identified predictors of appropriate PRN wording. Results: Among 316 patients, 1035 PRN prescriptions were analyzed, representing 24.5% of all medication entries. Only 51.3% (n = 531) were deemed appropriate by all evaluators. Significant differences in interpretation were observed across professional groups (p < 0.001 for most pairwise comparisons). PRN prescriptions were most frequent in long-term care units and primarily involved gastrointestinal agents, analgesics, and psychotropic medications. Multivariate analysis showed that hospitalization in long-term care (OR = 4.17; 95% CI 2.48–7.03) or rehabilitation units (OR = 2.07; 95% CI 1.22–3.53) with a higher number of prescriptions administered under a therapeutic protocol PRN (OR = 2.27; 95% CI 1.39–3.63) were independently associated with appropriate wording, while a higher total number of PRN prescriptions reduced appropriateness (OR = 0.87; 95% CI 0.82–0.94). Conclusions: PRN prescribing is frequent in hospitalized older adults and often involves high-risk or potentially inappropriate medications. Substantial interprofessional variability in the interpretation of PRN medication wording requires appropriate, standardized, and clinical PRN guidelines to improve medication safety and reduce potential adverse events in geriatric practice. Full article

This study examined the effects of replacing 25% (P25) or 50% (P50) of concentrate dry matter (DM) with sun-dried carob (Ceratonia siliqua L.) pods on growth performance, apparent nutrient digestibility, carcass traits, meat quality, serum biochemistry, and rumen microbiology in growing Assaf lambs. Twenty-four weaned male Assaf lambs (initial body weight [BW] 27.0 ± 0.5 kg; 2.5 months of age) were randomly assigned to three dietary treatments (n = 8 per group) in a completely randomized design and fed for 16 weeks. P50 achieved the highest ANCOVA-adjusted least squares mean final BW (53.0 kg) and average daily gain (ADG) (220.8 g/d), followed by P25 (51.1 kg; 203.3 g/d) and the control (46.2 kg; 160.2 g/d) (p < 0.001). Feed conversion ratio (FCR) improved from 8.99 in the control to 6.16 and 6.11 in P25 and P50, respectively, with no significant difference between the two carob-supplemented groups (p < 0.001). Apparent DM and organic matter (OM) digestibility increased with carob inclusion at both 3 and 6 months of age (p ≤ 0.0001). Cold carcass weight (CCW) was higher in carob-supplemented lambs (p < 0.001), whereas carcass muscle proportion did not differ among treatments (p = 0.688), and carcass fat proportion was higher in P25 than in the control (p = 0.039). Warner–Bratzler shear force declined progressively with carob inclusion (p < 0.001), indicating improved meat tenderness. Serum total protein was highest in P25, whereas blood urea nitrogen (BUN), low-density lipoprotein (LDL), and glutamate oxaloacetate transaminase (GOT) decreased with carob inclusion (p < 0.001). Rumen pH was highest in P25 (6.40), total bacterial and lactic acid bacteria (LAB) counts increased, and protozoa counts declined (p < 0.001). Because carob pods replaced concentrate, rather than being added to an isonitrogenous diet, the combined effects of pods per se, reduced crude protein supply, and altered energy density must all be considered when interpreting the results. These findings support carob pods as a practical, locally available partial substitute for concentrate feed in Assaf lamb production under Mediterranean and Near Eastern conditions. Full article

Designing multi-ingredient preservation systems is crucial for reducing the use of synthetic additives while maintaining food safety. This study evaluated the antimicrobial efficacy of ternary mixtures combining two natural antimicrobials (thymol, carvacrol, eugenol, citral, vanillin) and potassium sorbate (PS) against Listeria innocua and Salmonella Typhimurium at pH 4.5 and 5.5. The fractional inhibitory concentration index (FICI) and the total minimum inhibitory concentration (MIC) were determined to identify optimal synergistic combinations. Multivariate analysis, including Principal Component Analysis and Partial Least Squares (PLS) regression with standardized coefficients, was applied to decipher the relative impact and hierarchy of the predictor variables. At pH 4.5, concentrations of PS ≤ 64 ppm combined with any of the natural components resulted in higher synergistic mixtures (low FICI 0.318–0.378) for L. innocua. For Salmonella, only combinations of thymol, carvacrol, eugenol, and PS ≤ 32 ppm obtained the lowest FICI (0.252–0.344) at pH 4.5, while at pH 5.5, 128 ppm PS, thymol, and vanillin were required for a similar FICI (0.363). The PLS models revealed a distinct shift in variable importance between the synergistic index and the MIC. For the FICI model, mixture components exerted the primary influence; potassium sorbate displayed the highest predictive weight (standardized coefficient: +0.8736), followed by eugenol (+0.7757), carvacrol (+0.6206), and citral (+0.5119). This indicates that maximum synergism (lowest FICI) is constrained to lower fractional concentrations of natural compounds, thereby avoiding saturation of the cellular target site. Bacterial species (+0.2418) and pH (+0.3146) contributed less, indicating a homogeneous effect across the tested bacteria. For the total MIC model, potassium sorbate (+0.4701) and vanillin (+0.4492) regulated the antimicrobial quantity requirements. For the strains evaluated, the coefficients of the bacterial type in both models indicate that the ternary mixtures performed similarly. These findings demonstrate that integrating multivariate PLS modeling provides a robust framework for optimizing natural-synthetic antimicrobial blends, significantly reducing dependence on potassium sorbate through tailored synergism. Full article