Search Results (4,407)

The conflict between the deployment cost of high-precision intelligent standard instruments and the accuracy of intelligent verification is an unavoidable challenge in the intelligent transformation of charging-pile metering verification. To address this issue, this paper proposes a joint estimation method for charging-pile metering errors based on limited standard data. Specifically, correlated data sample groups are constructed based on the charging records of electric vehicles at different piles, a regularized least-squares convex programming model for joint estimation is established, and the Alternating Least Squares (ALS) algorithm is introduced to solve the model. Simulation results demonstrate that with only 10% of charging piles equipped with standard instruments, the estimation Root Mean Square Error (RMSE) is as low as 0.0069, and the overall identification accuracy reaches 91.25%, whose performance is significantly superior to that of the single-pile independent analysis scheme. Unlike conventional single-pile independent strategies that cannot identify systematic errors or leverage inter-pile data correlation, the proposed method employs an Alternating Least Squares (ALS) algorithm to fuse high-precision standard device data with pile-side reported data, achieving an overall identification accuracy of 91.25%, an F1-score of 72.00%, and an RMSE of 0.0069 for error estimation on a network of 80 charging piles with only 10% standard device coverage—significantly outperforming single-pile independent analysis. Full article

We propose a field-transformation-based framework for generating phase-only light-field holograms from a single RGB image. The method establishes an explicit pipeline from monocular scene inference to holographic wavefront synthesis, without requiring multi-view capture or task-specific hologram-network training. First, we construct a layered occlusion RGB-D model from the input image using monocular depth estimation, connectivity-based layer decomposition, and occlusion-aware inpainting, which provides a lightweight 3D prior for sparse-view rendering in the small-parallax regime. Second, we transform the rendered sparse RGB-D light field into a target complex wavefront on the recording plane through local frequency mapping, thereby bridging explicit scene geometry and wave-optical field construction. Third, we optimize the phase-only hologram under multi-plane amplitude constraints using a geometrically consistent initial phase and an error-driven adaptive depth-sampling strategy, which improves convergence stability and reconstruction quality under a limited computational budget. Numerical experiments show that the proposed method achieves better depth continuity, occlusion fidelity, and lower speckle noise than representative layer-based and point-based methods, and improves the average PSNR and SSIM by approximately 3 dB and 0.15, respectively, over Hogel-Free Holography. Optical experiments further confirm the physical feasibility and robustness of the proposed framework. Full article

In GNSS-denied environments, UAV visual positioning faces the critical bottleneck of low matching accuracy between heterogeneous images. To address this, we propose SemGeoFrame, a visual matching framework that leverages surface semantic information to enhance robustness. The key innovations are threefold: First, we construct a semantic prior from the probability distributions of image semantic segmentation and design a consistency screening mechanism based on Jensen–Shannon divergence to eliminate false matches by leveraging pixel-level semantic consistency for cross-view image matching. Second, a confidence-guided partition sampling strategy ensures balanced distribution of matches in both spatial and semantic categories, overcoming the limitations of conventional spatial-only sampling. Third, geometric, semantic, and confidence constraints are jointly optimized to achieve robust homography estimation. SemGeoFrame adopts a plug-and-play design and consistently improves the performance of mainstream matching algorithms (e.g., ORB, SuperPoint, LoFTR) on multiple heterogeneous datasets. The experimental results demonstrate that our framework significantly enhances matching accuracy and robustness across diverse scenarios. Full article

Hyperspectral image (HSI) classification in few-shot scenarios faces two core challenges. Limited samples and high spectral similarity lead to insufficient inter-class feature discriminability, and commonly used deep models suffer from the risk of overfitting. To address these problems, this paper proposes a Class-Adaptive Dictionary Reconstruction with Broad Learning (CADR-BL) method. Specifically, the method constructs an exclusive adaptive dictionary for each category and adopts an alternating minimization strategy to achieve sparse reconstruction of intra-class pixels, thereby enhancing intra-class spectral consistency and suppressing inter-class interference. On this basis, an improved Hyperspectral Broad Learning (HS-BL) model is introduced to efficiently classify the reconstructed features. Random feature mapping and closed-form solutions of output weights are utilized to alleviate overfitting in few-shot learning. Experiments conducted on three benchmark datasets, namely Indian Pines, Salinas, and WHU-Hi-HanChuan, show that CADR-BL outperforms several mainstream few-shot classification methods in terms of overall accuracy, average accuracy, and Kappa coefficient. Notably, CADR-BL maintains robust performance even with extremely limited training samples, and is less sensitive to variations in sample size than other comparative methods, demonstrating strong generalization ability. The proposed method provides a reliable technical reference for few-shot HSI classification in applications such as precision agriculture, environmental monitoring, and resource exploration. Full article

High-quality genomic DNA extraction remains a major bottleneck for fungal genomics, particularly for worldwide aerobic and non-photosynthetic mushroom species that rely on their rigid cell walls, interference between metabolites, polysaccharides, etc., and complex genomes. This study systematically compares five DNA extraction protocols involving four distinct sample preparation procedures (fresh (A), filtered (B), frozen (C) and cryogenic mycelium (D)) across mycelial cultures of eight Tunisian fungal strains representing Ascomycota and Basidiomycota to identify the optimal combination for genomic DNA extraction from mycelium. The eight phylogenetically diverse fungal species were analyzed using short-read (MiSeq and NextSeq550) and/or long-read (MinION Mk1C) sequencing technologies, giving a depth coverage between 3.7× and 83×. The generation and quality of the assemblies were assessed within the Galaxy platform, which revealed a gap percentage of 0–0.509%. Taxonomic characterization and phylogenetic inference were performed with SANGER technology using the Internal Transcribed Spacer (ITS) and D1/D2 region of the 26S rRNA gene, assigning the species to our eight different strains: Clitopilus baronii (BS6), Porostereum spadiceum (BS200), Trametes versicolor (BS22-9), Schizophyllum commune (BS23-13), Gloeophyllum abietinum (BS23-14), Irpex laceratus (BS100), Trichoderma asperellum (GC9) and Trichoderma harzianum (S3). The optimized DNeasy Plant Pro Kit protocol with cryogenic biomass treatment presents a safe and cost-effective method for fungal genome sequencing and taxonomic resolution. This integrated comparative evaluation of extraction for sequencing identifies an optimal Qiagen-based extraction strategy combined with cryogenic treatment for eight diverse Tunisian fungal species, guiding method selection based on specific cell wall characteristics rather than proposing a universal protocol limited by unequal replication and strain numbers. Full article

Background: We synthesized evidence from randomized clinical trials (RCTs) published between 2019 and 2025 on repetitive transcranial magnetic stimulation (rTMS) in post-stroke cognitive impairment (PSCI) and compared different stimulation parameters, cortical targets, and combinations with rehabilitation interventions. Methods: A systematic review according to PRISMA guidelines examined the RCTs applying rTMS in adults with PSCI compared with control or sham groups. The primary outcome was improvement in cognitive function and functional outcomes measured with standardized scales. Results: Fifteen studies, involving a total of 732 patients, were included. The most frequently investigated were high-frequency (≥10 Hz) stimulation protocols of the left dorsolateral prefrontal cortex, with treatment cycles ranging from 2 to 6 weeks. Overall, rTMS was generally safe and well tolerated, with rare and mild adverse events. Several studies reported improvements in cognitive performance following rTMS, although effects were variable across trials and need caution in light of heterogeneity in stimulation protocols, sample sizes, outcome measures, and methodological quality. In most cases, rTMS or intermittent theta burst stimulation combined with structured cognitive training yielded greater cognitive and functional gains than stimulation or rehabilitation alone. This suggests a positive interaction between rTMS and cognitive training, although current evidence does not yet allow definitive conclusions. Conclusions: rTMS appears to be a promising strategy for post-stroke cognitive rehabilitation, particularly for attention and executive functioning. However, heterogeneity in stimulation protocols and outcome measures, along with limited sample sizes and short follow-up, reduces the certainty and comparability of current evidence. The widespread reliance on global screening tools may further underestimate domain-specific effects. Future multicentre trials with standardized protocols and more sensitive cognitive assessments are needed to clarify efficacy and guide further clinical application of rTMS in PSCI. Full article

The diffusion model (DM) is a hot topic in deep generative models and is widely applied in image generation. In diffusion models, there are four main “secrets” that affect high-quality image generation: constructing the diffusion model, improving the sampling velocity, designing the diffusion process, and guiding diffusion models. How should one construct the diffusion model? How can one improve the sampling velocity? How should one design the diffusion process? How should one guide diffusion models? These questions are critical to enhancing diffusion model performance. However, most existing review papers focus on applications, while discussion of the four key technical aspects remains limited. In response, this paper summarizes four key technologies and six representative application directions. First, the basic principles of diffusion models are reviewed from three perspectives: denoising diffusion probabilistic models, noise conditional score network models, and stochastic differential equation models. Second, key techniques for improving sampling velocity are summarized from three perspectives: non-Markovian sampling, knowledge distillation sampling, and discrete optimization sampling. Third, the diffusion process design is summarized from three perspectives: latent space, Transformer-based diffusion, and non-Euclidean space. Fourth, guidance strategies are summarized from three perspectives: classifier guidance, classifier-free guidance, and multimodal guidance. Fifth, the advantages and applications of diffusion models are discussed in high-quality text-to-image generation, high-quality text-to-video generation, and high-quality image-to-image generation. Finally, this paper discusses the challenges faced by diffusion models in image generation. Overall, this review systematically discusses the four “secrets” of diffusion models for image generation and provides a useful reference for future research in this field. Full article

Background/Objectives: The presented study aimed to understand the relationship between knowledge, attitudes, and practices, as well as consumers’ preferences for the consumption of Spirulina-enriched fruit and vegetable juices. Methods: A survey about the consumers’ attitudes towards consumption of algae in general and especially Spirulina was conducted to better understand the target groups and marketing strategies for this novel non-alcoholic beverage product. Knowledge–Attitude–Practice (KAP) model in combination with structural equation modelling (SEM) was applied to test the hypothesised relationships between the variables. Additionally, consumers’ preference test was done using a seven-point hedonic scale and ranking of the six juice samples: plain sour cherry juice (SC1), sour cherry juice with 0.8% (SC2) and 1.6% (SC3) of blue Spirulina powder; plain tomato juice (T1), tomato juice with 0.8% (T2) and 1.6% (T3) of blue Spirulina powder. Results: The SEM results showed that there is a limited direct impact of knowledge on social motivation, while personal behaviour strongly predicts social motivation. Namely, perceived nutritional value and health benefits were shown to be the main factors for consumers’ willingness to drink Spirulina-enriched juice. Conclusions: The result of the consumer preference evaluation exposed that the juices containing sour cherry and Spirulina achieved better sensory acceptance and ranking than those containing tomato, pointing out the importance of the product matrix for achieving consumer acceptance. Full article

We propose a sequential design method aiming at the estimation of an extreme quantile based on a sample of binary data corresponding to peaks over a given threshold. This study is motivated by an industrial challenge in material reliability and consists of estimating a failure quantile from trials whose outcomes are reduced to indicators of whether the specimen has failed at the tested stress levels. The proposed approach relies on a splitting strategy that decomposes the target extreme probability into a product of higher-order conditional probabilities, enabling a progressive exploration of the tail of the distribution through sampling under truncated laws. We consider GEV and Weibull models for the underlying distribution, and the sequential estimation of their parameters is carried out using an enhanced maximum likelihood procedure specifically adapted to binary data, addressing the substantial uncertainty inherent to such limited information. Full article

Human milk oligosaccharides (HMOs) exhibit substantial inter-individual and secretor-dependent variation, yet comprehensive quantitative data across diverse maternal phenotypes remain limited. In this study, we analyzed 578 human milk samples from four Asian populations using a dual mass spectrometry approach, combining quadrupole time-of-flight (Q-TOF) for structural profiling and triple quadrupole (QQQ) mass spectrometry for absolute quantitation of 15 major HMOs. Samples were classified into Secretor (76.7%) and Non-Secretor (23.3%) groups based on α-1,2-fucosylated HMO profiles. Secretor milk was enriched in α-1,2-fucosylated HMOs, whereas Non-Secretor milk showed markedly reduced levels of these structures. However, Non-Secretor retained substantial total fucosylated HMOs (65–76% of Secretor levels), accompanied by increased α-1,3/4-fucosylated structures, including up to 3.2-fold higher levels of 3-fucosyllactose (3-FL). Sensitive QQQ quantitation further revealed trace levels of α-1,2-fucosylated HMOs in Non-Secretor at concentrations 10–100-fold lower than in Secretor. Correlation analysis indicated an inverse relationship between α-1,2- and α-1,3-fucosylation patterns, consistent with redistribution of fucosylation pathways. These findings suggest that the Non-Secretor phenotype represents a distinct compositional state rather than a simple loss of α-1,2-fucosylation and provide a quantitative framework for phenotype-informed nutritional strategies. Full article

Background: Gastroesophageal reflux disease (GERD) is a common digestive disorder with a substantial impact on quality of life. Emerging evidence suggests that dietary patterns and lifestyle behaviors are associated with the occurrence and severity of GERD symptoms; however, integrated data from Romania remain limited. Objective: The aim of this study was to evaluate associations between pro- and anti-inflammatory dietary patterns, lifestyle-related behavioral factors, and the presence and severity of gastroesophageal reflux symptoms in an adult Romanian population. Methods: A national cross-sectional observational study was conducted using a self-administered online questionnaire. All participants included in the study reported a prior diagnosis of gastroesophageal reflux disease (GERD), and participant classification was based exclusively on current symptomatology assessed using the GERD-Q score. Therefore, comparisons were not performed between patients and a healthy population, but rather between individuals at different stages of clinical expression of the same condition, characterized by a fluctuating course. The instrument included standardized GERD-Q items for symptom assessment, together with questions regarding dietary intake and lifestyle behaviors. Pro-inflammatory (PRO), anti-inflammatory (ANTI), and combined (PRO–ANTI) dietary scores were established. Statistical analyses included comparative and correlational tests as well as multivariable logistic regression models. Results: Among the 340 participants included in the study, 72.4% reported symptoms consistent with GERD according to the GERD-Q score. A higher pro-inflammatory dietary score was significantly associated with GERD, with participants in the highest PRO category showing more than a fourfold higher likelihood of GERD in multivariable analyses. Consumption of spicy foods and carbonated beverages was associated with an increased risk of GERD in univariate analyses; however, these associations did not remain significant in multivariable models. Late meals (defined as consumption of one’s last meal of the day less than two hours before bedtime) were independently associated with GERD. Combined analyses indicated a higher risk among participants who reported eating late meals, particularly when combined with large evening meals. Most foods considered protective, along with classical lifestyle factors (smoking, alcohol consumption, and sleeping position), were not independently associated with GERD. Conclusions: These findings suggest that overall dietary patterns with pro-inflammatory potential and meal timing in relation to the sleep–wake cycle may be more consistently associated with GERD symptoms in this sample than isolated food items or traditional lifestyle risk factors. Nutritional and behavioral interventions focused on improving overall dietary patterns and avoiding late meals may represent potential strategies for GERD management. Full article

Background: Patients with advanced chronic kidney disease (CKD) experience disproportionately high ischemic and bleeding risks following acute coronary syndrome (ACS), yet remain markedly underrepresented in randomized trials of antiplatelet therapy. Consequently, real-world data describing antiplatelet prescribing patterns and clinical outcomes in this population are limited. Objectives: To describe real-world antiplatelet use and 12-month clinical outcomes in patients with advanced CKD and end-stage renal disease (ESRD) following ACS. Methods: We conducted a single-center, retrospective cohort study including adults with advanced CKD (stage 4–5) or dialysis-dependent ESRD hospitalized with ACS and discharged on dual antiplatelet therapy. Baseline characteristics, revascularization strategies, and clinical outcomes were collected. Outcomes of interest included all-cause mortality, recurrent ischemic events (recurrent myocardial infarction, stroke or transient ischemic attack, or repeat revascularization), and bleeding events defined by Thrombolysis in Myocardial Infarction (TIMI) criteria over 12 months. All analyses were descriptive in nature. Results: A total of 222 patients were included; clopidogrel was prescribed in 96.0% of patients and ticagrelor in 4.0%. The cohort was elderly, highly comorbid, and predominantly dialysis-dependent. At 12 months, all-cause mortality occurred in approximately one-third of patients, recurrent ischemic events were frequent, and bleeding complications were common. Most bleeding events occurred in dialysis-dependent individuals. Outcomes among ticagrelor-treated patients are reported descriptively only due to the very small sample size. Conclusions: In this real-world cohort of patients with advanced CKD and ESRD following ACS, a substantial burden of mortality, recurrent ischemic events, and bleeding complications was observed, underscoring the narrow therapeutic window in this high-risk population. These findings are descriptive and hypothesis-generating, supporting the need for individualized antiplatelet strategies and prospective studies specifically enrolling patients with advanced CKD. Full article

Groundwater plays an indispensable role in daily life. However, with the continuous advancement of industrialization, more attention should be paid to the quality of groundwater and the associated potential health risks in areas surrounding industrial parks. In this study, groundwater samples collected in the city of the Tibetan Plateau during the wet season (WS) and dry season (DS) were analyzed using Piper diagrams, Gibbs diagrams, and correlation analysis. The results elucidated the hydrochemical characteristics, formation mechanisms, and controlling factors of groundwater in the area. Groundwater potability was assessed using the Entropy-weighted Water Quality Index (EWQI) method. In addition, the health risk assessment model was applied to evaluate potential risks for four population groups, with NO₃⁻ and F⁻ selected as representative groundwater pollutants. The findings revealed that groundwater in the study zone was typically moderately alkaline and characterized primarily as soft–fresh and hard–fresh. The groundwater in both seasons mainly exhibited HCO₃–Ca chemical facies. Water–rock interactions involving silicate and carbonate minerals were identified as key processes controlling the hydrochemical composition in both seasons. EWQI results showed that groundwater quality for drinking purposes was excellent in the seasons. Sensitivity analysis further showed that Cl− exerted the greatest influence on the drinking water quality evaluation in both seasons. Health risk assessments revealed that the risks posed by NO₃⁻ and F⁻ to infants, children, adult females, and adult males remained within acceptable limits (with max values of 0.63, 0.39, 0.28, and 0.33 in the WS, and 0.59, 0.36, 0.26, and 0.31 in the DS, respectively). However, infants exhibited greater susceptibility than the other groups across seasons, with a risk index approximately twice that of adults. Overall, the findings contribute valuable insights for the sustainable management and planning of groundwater resources in the study zone. Future research could refine the risk assessment model with localized data and explore mitigation strategies for elevated risks in specific seasons or regions. Full article

Background/Objectives: This exploratory, cross-sectional study examined the relationships between personal factors and the nutrition intentions of participants in Healthy Choices for Your Recovering Body (HCYRB), a nutrition education program for limited-resource adults in substance use recovery (SUR). Methods: The study used a single-sample survey design where HCYRB participants (n = 2163) completed a post-participation survey. Linear regression models were tested to assess the effects of personal factors such as nutrition knowledge, cooking skills, self-efficacy beliefs and current nutrition and physical activity practices on participants’ nutrition intentions. Variables were measured with a self-reported survey that participants completed after participation in HCRYB. Results: The final model (R² = 0.39) showed statistically significant effects of self-efficacy beliefs, specifically, food resource management confidence and confidence to choose nutritious foods; current levels of water, soda, and energy drink consumption; physical activity level; and gender on nutrition intentions. Conclusions: Overall, the findings suggest that nutrition-related self-efficacy and current practices influence nutrition intentions of HCYRB participants. Future programs may focus on building participants’ nutrition-related confidence during SUR to enhance intentions and eventual behavior change. Such strategies may include programming activities that promote and affirm participants’ current positive nutrition-related behaviors (e.g., adequate consumption of water and involvement in physical activity). As participants master these healthy practices throughout the nutrition education experience, they will be more likely to gain confidence and motivation toward continuing the behavior throughout their recovery journey. Full article

Background/Objectives: Squamous cell metaplastic breast carcinoma (SCMBC) is a rare and aggressive breast cancer subtype with limited imaging and prognostic data. This study aimed to characterize the multimodal imaging features, clinicopathological profiles, and prognostic outcomes of SCMBC in a single-center cohort. Methods: We retrospectively analyzed 22 patients with histopathologically confirmed SCMBC treated between January 2012 and May 2025. Clinicopathological profiles, multimodal imaging features, and prognostic outcomes were collected and evaluated. Results: All patients were female (median age 64.5 years; range, 34–82). The majority (59.1%) presented with clinical stage II disease. Axillary lymph node metastasis was present in eight (36.4%) patients at diagnosis, with one case of distant lung metastasis. The mean tumor diameter was 4.24 cm (range, 2.1–11.8). MRI findings (n = 13) included heterogeneous internal structure, a low mean apparent diffusion coefficient (ADC) value of 0.98 × 10⁻³ mm²/s, and frequent necrosis (92.3%). Pathologically, 54.5% of tumors were high-grade, and 81.8% exhibited a triple-negative phenotype. After a median follow-up of 34 months, the 5-year overall survival (OS) rate was 64.3%, while the 3-year disease-free survival (DFS) rate was 42.1%. The recurrence/metastasis rate was 22.7% (5/22), and all five deaths occurred in this subgroup. Conclusions: SCMBC is characterized by suggestive multimodal imaging features, a predominant triple-negative phenotype, and a high risk of early recurrence. Given the exploratory nature of this single-center study with a limited sample size, these findings require validation in larger, prospective cohorts. Early radiological identification and aggressive personalized treatment strategies may improve outcomes for patients with this aggressive disease. Full article