Search Results (40,751)

This research proposes an adaptation of the quality–loyalty model in which affective commitment is integrated as a key factor in the proposed framework. The study presented a comprehensive framework encompassing 11 hypotheses formulated from an extensive literature review. Empirical data collected from 679 environmentally conscious consumers predominantly residing in Vietnam’s three principal urban centers were employed to evaluate these hypotheses. The assessment was executed utilizing the partial least squares structural equation modeling technique. The results of this research authenticate the appropriateness of the integrated model in studying green consumption, verify the critical role of affective commitment in the newly introduced model, and identify the high impact of affective commitment on green loyalty intention and green purchase behavior. This research also shows that other factors of the quality–loyalty model have significant influences on affective commitment and green loyalty intention. Moreover, this study signifies the crucial role of green perceived quality in fostering affective commitment and green loyalty intention. Green perceived quality was identified as a key factor influencing green loyalty intention and played a crucial role in encouraging customers to purchase environmentally friendly products. Full article

Despite extensive research on early childhood education (ECE) quality at the preschool level, toddler settings remain comparatively understudied, particularly in Chile and Latin America. Research suggests that quality ECE strengthens child development, while low-quality services can be harmful. ECE quality comprises structural features like ratios and classroom resources, and process features related to interactions within classrooms. This study examines how process and structural quality indicators are related in nurseries serving disadvantaged backgrounds. Data were collected from 51 Chilean urban classrooms serving children aged 12–24 months. Classrooms were evaluated using the Classroom Assessment Scoring System (CLASS) for toddlers, questionnaires, and checklists. Latent Profile Analysis identified process quality patterns, while multinomial regression examined associations with structural quality indicators. The results revealed low-to-moderate process quality across classrooms (M = 4.78 for Emotional and Behavioral Support; M = 2.35 for Engaged Support for Learning), with three distinct quality clusters emerging. Marginally significant differences were found between high- and low-performing clusters regarding classroom space (p = 0.06), number of toys (p = 0.08), and staff educational credentials (p = 0.01–0.07). No significant differences emerged for group sizes or adult-to-child ratios, which are heavily regulated in Chile. These findings underscore the need to strengthen quality assurance mechanisms ensuring all children access quality ECE. Full article

Reliable, non-destructive grading of fresh fruit requires simultaneous assessment of external morphology and hidden internal defects. Camera-based grading of fresh fruit using colorimetric (RGB) and near-infrared (NIR) imaging often misses subsurface bruising and cannot capture the fruit’s true shape, leading to inconsistent quality assessment and increased waste. To address this, we developed a 4D-grading pipeline that fuses visible and near-infrared (VNIR) and short-wave infrared (SWIR) hyperspectral imaging with structured-light 3D scanning to non-destructively evaluate both internal defects and external form. Our contributions are (1) flagging the defects in fruits based on the reflectance information, (2) accurate shape and defect measurement based on the 3D data of fruits, and (3) an interpretable, decision-tree framework that assigns USDA-style quality (Premium, Grade 1/2, Reject) and size (Small–Extra Large) labels. We demonstrate this approach through preliminary results, suggesting that 4D hyperspectral imaging may offer advantages over single-modality methods by providing clear, interpretable decision rules and the potential for adaptation to other produce types. Full article

As direct detection methods of Borrelia burgdorferi are limited, serology plays an important role in diagnosing Lyme disease (LD). There are various types of Lyme serological tests with varying diagnostic accuracy, so it is necessary to compare and rank them. The aim of this study is to compare the accuracy of various serological diagnostic methods for LD using network meta-analysis (NMA). We searched the Cochrane Library and PubMed databases for all serological diagnostic accuracy studies published from the discovery of LD until June 2024. After screening, we assessed the quality of the included studies with QUADAS-C and extracted relevant data. We calculated the Q* index of the receiver operating characteristic curve for each diagnostic test. Meta-disc 2.0 and Stata 15.0 were used to perform traditional meta-analysis and NMA with the gold standard (the comprehensive evaluation) as a reference. We then compared the Q* index values between different methods using two-by-two comparisons and ranked them accordingly. A total of 52 studies with 181,032 participants, including 5318 patients with LD, were included. These studies covered 14 diagnostic methods. The results of the NMA suggest that modified two-tiered testing (MTTT), C6 enzyme immunoassay (EIA), and standard two-tiered testing (STTT) rank in the top three among the 14 methods in terms of Q* index, with MTTT being the highest, followed by C6 EIA and STTT. MTTT and C6 EIA have higher overall diagnostic performance, and their accuracy is not inferior to that of the widely used STTT (PROSPERO CRD42022378326). Full article

Background/Objective: Chemotherapy-induced peripheral neuropathy (CIPN) is a common dose-limiting adverse effect of various chemotherapeutic agents. Previous work demonstrated that cannabis alleviates symptoms of oxaliplatin-induced CIPN. To evaluate the effects of cannabis components, cannabidiol (CBD) and tetrahydrocannabinol (THC), on CIPN-related symptoms. Methods: We reviewed a patient-reported outcomes dataset from “Tikun Olam,” a major medical cannabis provider. Of 1493 patients, 802 reported at least one CIPN symptom at baseline, including a burning sensation, cold sensation, paresthesia (prickling) and numbness, and 751 of them met the study inclusion criteria. Patients were categorized into THC-high/CBD-low and CBD-high/THC-low groups. Symptom changes after six months of cannabis use were analyzed using K-means clustering and logistic regression, incorporating interactions between baseline symptoms and THC and CBD doses. Linear regression assessed changes in activities of daily living (ADL) and quality of life (QOL). Results: Both groups reported symptom improvement. The THC-high group showed significantly greater improvement in burning sensation and cold sensation (p = 0.024 and p = 0.008). Improvements in ADL and QOL were also significantly higher in the THC group (p = 0.029 and p = 0.006). A significant interaction between THC and CBD was observed for symptom improvement (p < 0.0001). Conclusion: Cannabis effectively reduces CIPN symptoms and improves QOL and ADL. Higher THC doses were more effective than lower doses, with combined CBD and THC doses yielding greater symptom relief. Full article

Objective: The accurate visualization of root canal systems on periapical radiographs is critical for successful endodontic treatment. This study aimed to evaluate and compare the effectiveness of several image enhancement algorithms—including a novel Total Variation–Contrast-Limited Adaptive Histogram Equalization (TV-CLAHE) technique—in improving the detectability of root canal configurations in mandibular incisors, using cone-beam computed tomography (CBCT) as the gold standard. A null hypothesis was tested, assuming that enhancement methods would not significantly improve root canal detection compared to original radiographs. Method: A retrospective analysis was conducted on 60 periapical radiographs of mandibular incisors, resulting in 420 images after applying seven enhancement techniques: Histogram Equalization (HE), Contrast-Limited Adaptive Histogram Equalization (CLAHE), CLAHE optimized with Pelican Optimization Algorithm (CLAHE-POA), Global CLAHE (G-CLAHE), k-Caputo Fractional Differential Operator (KCFDO), and the proposed TV-CLAHE. Four experienced observers (two radiologists and two dentists) independently assessed root canal visibility. Subjective evaluation was performed using an own scale inspired by a 5-point Likert scale, and the detection accuracy was compared to the CBCT findings. Quantitative metrics including Peak Signal-to-Noise Ratio (PSNR), Signal-to-Noise Ratio (SNR), image entropy, and Structural Similarity Index Measure (SSIM) were calculated to objectively assess image quality. Results: Root canal detection accuracy improved across all enhancement methods, with the proposed TV-CLAHE algorithm achieving the highest performance (93–98% accuracy), closely approaching CBCT-level visualization. G-CLAHE also showed substantial improvement (up to 92%). Statistical analysis confirmed significant inter-method differences (p < 0.001). TV-CLAHE outperformed all other techniques in subjective quality ratings and yielded superior SNR and entropy values. Conclusions: Advanced image enhancement methods, particularly TV-CLAHE, significantly improve root canal visibility in 2D radiographs and offer a practical, low-cost alternative to CBCT in routine dental diagnostics. These findings support the integration of optimized contrast enhancement techniques into endodontic imaging workflows to reduce the risk of missed canals and improve treatment outcomes. Full article

Background/Objectives: Pressure injuries are a significant concern among older adults, particularly in community-based long-term care settings where prolonged immobility is prevalent. This study aimed to identify factors influencing sacral interface pressure in community-dwelling older adults, with an emphasis on support surface usage and clinical risk indicators. Methods: A total of 210 participants aged 65 years and older, all receiving long-term care services in South Korea, were enrolled in this study. Sacral interface pressure was measured in the supine position using a portable pressure mapping device (Palm Q7). General characteristics, Braden Scale scores, Huhn Scale scores, and mattress usage were assessed. Data were analyzed using descriptive statistics, t-tests, chi-square tests, and logistic regression. Results: Mattress non-use was identified as the strongest predictor of elevated sacral interface pressure (OR = 6.71, p < 0.001), followed by Braden Scale scores indicating moderate risk (OR = 4.8, p = 0.006). Huhn Scale scores were not significantly associated with interface pressure. These results suggest that support surface quality and skin condition have a stronger impact on interface pressure than mobility-related risk factors. Conclusions: The findings highlight the importance of providing high-quality pressure-relieving mattresses and implementing standardized nursing assessments to reduce the risk of pressure injuries. Integrating smart technologies and expanding access to advanced support surfaces may aid in developing tailored preventive strategies for vulnerable older adults. Full article

(1) Virtual reality (VR) technologies have shown significant potential for diagnosing and treating vision-related impairments. This rapid review evaluates and characterizes the existing literature on VR technologies for diagnosing and treating vision-based diseases. (2) Methods: A systematic search was conducted across Ovid MEDLINE, Ovid Embase, the Cochrane Database of Systematic Reviews (Ovid), and the Cochrane Central Register of Controlled Trials (Ovid). Abstracts were screened using Rayyan QCRI, followed by full-text screening and data extraction. Eligible studies were published in peer-reviewed journals, written in English, focused on human participants, used immersive and portable VR devices as the primary intervention, and reported on the clinical effectiveness of VR for therapeutic, diagnostic, or screening purposes for vision or auditory–visual impairments. Various study characteristics, including design and participant details, were extracted, and the MMAT assessment tool was used to evaluate study quality. (3) Results: Seventy-six studies met the inclusion criteria. Among these, sixty-four (84.2%) were non-randomized studies exploring VR’s effectiveness, while twenty-two (15.8%) were randomized-controlled trials. Of the included studies, 38.2% focused on diagnosing, 21.0% on screening, and 38.2% on treating vision impairments. Glaucoma and amblyopia were the most commonly studied visual impairments. (4) Conclusions: The use of standalone, remotely controlled VR headsets for screening and diagnosing visual diseases represents a promising advancement in ophthalmology. With ongoing technological developments, VR has the potential to revolutionize eye care by improving accessibility, efficiency, and personalization. Continued research and innovation in VR applications for vision care are expected to further enhance patient outcomes. Full article

Teledermatology relies on digital transfer of dermatological images, but compression and resolution differences compromise diagnostic quality. Image enhancement techniques are crucial to compensate for these differences and improve quality for both clinical assessment and AI-based analysis. We developed a customized image degradation pipeline simulating common artifacts in dermatological images, including blur, noise, downsampling, and compression. This synthetic degradation approach enabled effective training of DermaSR-GAN, a super-resolution generative adversarial network tailored for dermoscopic images. The model was trained on 30,000 high-quality ISIC images and evaluated on three independent datasets (ISIC Test, Novara Dermoscopic, PH²) using structural similarity and no-reference quality metrics. DermaSR-GAN achieved statistically significant improvements in quality scores across all datasets, with up to 23% enhancement in perceptual quality metrics (MANIQA). The model preserved diagnostic details while doubling resolution and surpassed existing approaches, including traditional interpolation methods and state-of-the-art deep learning techniques. Integration with downstream classification systems demonstrated up to 14.6% improvement in class-specific accuracy for keratosis-like lesions compared to original images. Synthetic degradation represents a promising approach for training effective super-resolution models in medical imaging, with significant potential for enhancing teledermatology applications and computer-aided diagnosis systems. Full article

Background/Objectives: The aim of this systematic review was to compare the effectiveness of virtual reality (VR)-based training with conventional exercise programs in improving functional outcomes related to fall risk among older adults with various health conditions. Methods: The review was conducted in accordance with the PRISMA 2020 guidelines and registered in PROSPERO (registration number CRD42022345678). The databases Scopus, PubMed, Web of Science, and EBSCO were searched up to 31 March 2025. Randomized controlled trials (RCTs) were included if they involved participants aged ≥60 years, a VR intervention lasting ≥6 weeks, and a control group performing traditional exercises or receiving usual care. Methodological quality was assessed using the PEDro scale, and a narrative synthesis was performed across four outcome domains: balance, mobility, cognitive function, and fall risk. Results: Seven RCTs were included in the analysis (totaling 664 participants). VR training was found to be at least as effective as conventional exercise in improving balance (e.g., Berg Balance Scale) and mobility (e.g., Timed Up and Go), with some studies showing superior effects of VR. One RCT demonstrated that combining VR with balance exercises (MIX) yielded the greatest improvements in muscle strength and physical performance. Additionally, two studies reported cognitive benefits (e.g., MoCA) and a 42% reduction in fall incidence within six months following VR intervention. The methodological quality of the included studies was moderate to high (PEDro score 5–9/10). Conclusions: VR-based training represents a safe and engaging supplement to geriatric rehabilitation, effectively improving balance, mobility, and, in selected cases, cognitive function, while also reducing fall risk. Full article

China has identified the high-quality development of its green manufacturing transition as the top priority for upgrading their industrial structure system which will lead to the sustainable development of an innovation ecosystem. To assess their progress in this area, this study selects the panel data of 31 provinces in China from 2011 to 2021 and constructs an evaluation index system for the green transformation of the manufacturing industry from four dimensions: environment, resources, economy, and industrial structure. This not only comprehensively and systematically reflects the dynamic changes in the green transformation of the manufacturing industry but also addresses the limitations of currently used indices. The entropy value method is used to calculate the comprehensive score of the green transformation of the manufacturing industry, while the key factors influencing the convergence of the green transformation of the manufacturing industry are further explored. The results show that first, the overall level of the green transformation of the manufacturing industry has significantly improved as evidenced by an approximate 32% increase. Second, regional differences are significant with the eastern region experiencing significantly higher levels of transformation compared to the central and western regions, along with a decreasing trend from the east to the central and western regions. From a policy perspective, the findings suggest that tailored production methods for each region should be adopted with a greater emphasis on knowledge exchanges to promote green transition in less developed regions. In addition, further regulations are required which, in part, focus on increasing the degree of openness to the outside world to promote the level of green manufacturing transition. Full article

This study presents the first systematic evaluation of in-context learning for Tarifit machine translation, a low-resource Amazigh language spoken by 5 million people in Morocco and Europe. We assess three large language models (GPT-4, Claude-3.5, PaLM-2) across Tarifit–Arabic, Tarifit–French, and Tarifit–English translation using 1000 sentence pairs and 5-fold cross-validation. Results show that 8-shot similarity-based demonstration selection achieves optimal performance. GPT-4 achieved 20.2 BLEU for Tarifit–Arabic, 14.8 for Tarifit–French, and 10.9 for Tarifit–English. Linguistic proximity significantly impacts translation quality, with Tarifit–Arabic substantially outperforming other language pairs by 8.4 BLEU points due to shared vocabulary and morphological patterns. Error analysis reveals systematic issues with morphological complexity (42% of errors) and cultural terminology preservation (18% of errors). This work establishes baseline benchmarks for Tarifit translation and demonstrates the viability of in-context learning for morphologically complex low-resource languages, contributing to linguistic equity in AI systems. Full article

Constipation is a prevalent gastrointestinal disorder that significantly impairs quality of life. While pharmacological agents such as loperamide are widely used to induce constipation in experimental models, there is increasing interest in natural alternatives for alleviating intestinal dysfunction. In this study, we investigated the laxative effects of soybean powder fermented by Bacillus subtilis DKU_09 in a loperamide-induced rat model of constipation. The probiotic strain was isolated from cheonggukjang, a traditional Korean fermented soybean paste, and its identity was confirmed through 16S rRNA sequencing. Fermented soybean powder was characterized morphologically via scanning electron microscopy and chemically via HPLC to assess its isoflavone content. Rats were administered loperamide (5 mg/kg) for four days to induce constipation and were then treated with fermented soybean powder at doses of 100, 200, or 300 mg/kg. No pharmacological laxatives (e.g., PEG) were used as a positive control; instead, values from the treatment groups were compared with those from the loperamide-only constipation group. Key outcomes of fecal output, water content, colonic fecal retention, and gastrointestinal transit ratio were measured. The fermented product significantly improved stool frequency and moisture content, reduced colonic fecal retention, and restored gastrointestinal transit in a dose-dependent manner. Notably, the 300 mg/kg group demonstrated nearly complete recovery of fecal parameters without affecting body weight. Statistical analysis was performed using one-way ANOVA followed by Tukey’s post hoc test. These findings suggest that Bacillus subtilis-fermented soybean powder exerts synergistic laxative effects through the combined action of probiotic viability and fermentation-enhanced bioactive compounds such as aglycone isoflavones. This study supports the potential use of fermented soybean-based nutraceuticals as a natural and safe intervention for constipation and gastrointestinal dysregulation. Full article

This study evaluated the effects of different storage conditions, varying in light exposure, relative humidity (RH), and packaging materials, on the physicochemical stability of Lobosphaera sp. biomass, the retention of bioactive compounds, and the bioactivity of its extracts. Under light and 75% RH, the biomass absorbed moisture over time, reaching 0.779 ± 0.003 g/g dry weight (DW) after three months. This was accompanied by a decline in luminosity, chroma, and hue values. In contrast, samples stored under other conditions showed minimal changes, indicating that high humidity, combined with light exposure, compromises biomass stability. Packaging in metalized polyethylene terephthalate (PETmet/PE) effectively preserved the water content, color, and carotenoid levels during a two-month storage period. Bioactive compounds extracted via hydroethanolic ultrasound-assisted extraction yielded 15.48 ± 1.35% DW. Total phenolic content (TPC) of the extracts declined over time in both PETmet/PE and low-density polyethylene (LDPE) packaging, though the decrease was less pronounced in PETmet/PE. Antioxidant activity, assessed via the ABTS assay, remained stable, regardless of storage duration or packaging. Antimicrobial activity of the extract decreased over time but remained more effective against Gram-positive bacteria (Staphylococcus aureus, Bacillus cereus, and Listeria monocytogenes), with PETmet/PE packaging better preserving antimicrobial efficacy than LDPE. These findings underscore the importance of optimized storage conditions and packaging for maintaining the quality and bioactivity of Lobosphaera sp. biomass and its extracts. Full article

Optical coordinate measurement is a universal technique that aligns with the rapid development of industrial technologies and new materials. Nevertheless, can this technique be consistently effective when applied to the precise measurement of all types of materials? As shown in this article, an analysis of optical measurement systems reveals that some materials cause difficulties during the scanning process. This article details the matting process, resulting, as demonstrated, in lower measurement uncertainty values compared to the pre-matting state, and identifies materials for which applying a matting spray significantly improves the measurement quality. The authors propose a classification of materials into easy-to-scan and hard-to-scan groups, along with specific procedures to improve measurements, especially for the latter. Tests were conducted in an accredited Laboratory of Coordinate Metrology using an articulated arm with a laser probe. Measured objects included spheres made of ceramic, tungsten carbide (including a matte finish), aluminum oxide, titanium nitride-coated steel, and photopolymer resin, with reference diameters established by a high-precision Leitz PMM 12106 coordinate measuring machine. Diameters were determined from point clouds obtained via optical measurements using the best-fit method, both before and after matting. Color measurements using a spectrocolorimeter supplemented this study to assess the effect of matting on surface color. The results revealed correlations between the material type and measurement accuracy. Full article