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A neutrosophic clustering approach to handle recommendation uncertainty for gray sheep users
Abstract Recommender systems play a crucial role in reducing information overload by providing personalized suggestions based on user preferences. However, gray sheep users are individuals whose preferences are inconsistent or partially aligned with both majority and minority groups, overlooked by conventional collaborative filtering methods, resulting in inaccurate or inconsistent recommendations. To address this challenge, this paper introduces an uncertainty-aware integration framework for gray sheep users, combining neutrosophic k-means clustering with item-based collaborative filtering (IBCF). Neutrosophic logic is an extension of fuzzy logic that describes data using three membership degrees: truth (support), indeterminacy (uncertainty), and falsity (contradiction), allowing for the flexible and reliable identification of users with ambiguous or non-conforming behaviors. IBCF uses item similarity to generate customized recommendations in the high-indeterminacy (gray sheep) cluster, whereas standard item-based collaborative filtering is used to process mainstream users. The performance gains for the high-indeterminacy (gray sheep) cluster are the only focus of this study. Experimental evaluation on the MovieLens 100 K dataset demonstrates that the proposed model improves gray sheep user treatment significantly, achieving higher precision (88.70%), recall (90.90%), F1-score (89.79%), reduced error rates (MAE = 0.534, RMSE = 0.719) and accuracy (84.07%) presented as an additional indication. In addition, neutrosophic k-means is evaluated on Book-Crossing and Last.fm, demonstrating generalizability beyond movies. These results confirm that explicit uncertainty modeling within collaborative filtering architectures can improve the quality of identification and recommendations for gray sheep users, reaching out to a key segment of the user base that conventional techniques have neglected.
Comparative metabolomic and physiological analysis uncovers distinct drought tolerance mechanisms in four rice cultivars
Abstract Drought stress is a major abiotic challenge threatening global food security by negatively affecting rice morphology, physiology, and biochemistry. This study explored the morpho-physiological and metabolomic responses of four rice cultivars (Giza 179, Hassawi, Super 300, and Y EGY) to drought stress induced by 15% PEG for 14 days. Measurements included fresh weight, relative water content (RWC), proline content, and plant height, while leaf and root tissues underwent detailed GC-MS metabolomic profiling followed by multivariate analyses such as PCA, VIP scoring, volcano plots, and pathway enrichment. Results showed Y EGY experienced the greatest decline in fresh weight, whereas Giza 179 maintained higher biomass. Stress tolerance indices ranked the cultivars as Giza 179 (85.2%), Super 300 (65.5%), Hassawi (61.7%), and Y EGY (52.2%). Metabolomic analysis identified 114 leaf and 97 root metabolites, with 40 showing VIP > 1.0. Volcano plot analysis revealed distinct variety-specific responses: Giza 179 demonstrated broad metabolic activation with upregulation of methylgalactoside, glycerol-3-phosphate, and citric acid in leaves; Hassawi showed effective targeted responses with strategic trehalose upregulation, while Y EGY exhibited extensive root metabolic disruption. Pathway enrichment identified alanine, aspartate, and glutamate metabolism, arginine and proline metabolism, and the TCA cycle as most significantly affected in leaves, while the TCA cycle was the main response pathway in roots. Post-hoc analysis confirmed that drought-tolerant cultivars exhibited more balanced metabolic regulation. These findings suggest that superior drought tolerance is associated with either efficient targeted metabolic responses that conserve resources (Hassawi, Super 300) or robust integrated mechanisms that coordinate osmoregulation and metabolic reprogramming (Giza 179), providing valuable insights for breeding drought-tolerant rice varieties.
On the min-entropy of equilibrium graphs in network creation games
Coupled aerodynamic–electromagnetic modeling for RCS estimation of million-scale chaff clouds with arbitrarily curved 3D geometries
One-pot multicomponent diastereoselective synthesis of indoline spirobicyclics using a recyclable chiral nanomagnetic L-proline catalyst under mild conditions
mRNA profiling of mesenchymal stem cell-derived exosomes reveals their function in accelerating wound healing
Hidden in the pollen: tracing 3000 years of human footprints in a mountain landscape
VR-guided deep breathing during needle procedures in children
Lived experiences and perceptions of social support in diabetes self-management among patients, families, and friends in Ethiopia
Rapid earthquake damage assessment via hybrid LSTM-RNN with a quantum-inspired classification head based on Autonomous Perceptron Model APM
The quality and reliability of short videos about depression on TikTok (Douyin): a cross-sectional study
Abstract Depression is one of the most prevalent mental health disorders worldwide. Despite its significant impact on patients’ well-being, its etiology remains unclear, and diagnosis is often challenging. Currently, effective depression management requires long-term patient engagement, which includes consistent self-care, adherence to treatment plans, and ongoing mental health literacy. However, the quality of depression-related videos on short-video platforms varies widely, and some may contain misinformation that patients struggle to identify. This study aims to assess the information quality of depression-related short videos on TikTok (Douyin), the largest short-video platform in China. Based on the composite ranking, the top 200 depression-related videos on TikTok (Douyin) were rigorously screened by two independent psychiatrists according to predefined inclusion/exclusion criteria. Videos were categorized by publisher type, and detailed engagement metrics (likes, shares, comments, favorites) were recorded. Video quality was assessed using the Global Quality Scale (GQS), JAMA Benchmark Criteria, and the modified DISCERN tool (mDISCERN). Content analysis covered six key domains: definition, symptoms, risk factors, diagnosis, treatment, and outcomes. Finally, correlation analysis was conducted to evaluate the relationship between video quality and engagement metrics. The study ultimately included 121 depression-related videos, the majority of which (62%) were published by healthcare professionals, including psychiatrists (39.7%) and psychologists (13.2%). Overall, video quality was low, with median scores of 2 (IQR: 1–3) for both GQS and JAMA, and 0 (IQR: 0–1) for mDISCERN. In contrast, videos authored by psychiatrists provided more comprehensive coverage of depression-related content and demonstrated superior reliability and quality, with median scores of 3 (IQR: 2–3) for DISCERN, 2.5 (IQR: 2–3) for GQS, and 1 (IQR: 1–2) for JAMA. Notably, psychiatrist-produced videos also achieved higher public engagement metrics. Correlation analysis revealed a significant positive association between video quality scores and public engagement. Overall, the quality of depression-related video content on TikTok (Douyin) remains suboptimal and requires significant improvement. There is a pressing need for more high-quality, evidence-based depression-related videos to facilitate long-term and effective self-management among individuals with depression. Simultaneously, such efforts would help improve public awareness and accurate understanding of depression.
Absorption, dispersion, and emission characteristics of novel Chitosan blends thin films tuned by UV-Ozone
Abstract In current study, two novel polymers derived from original Chitosan is synthetized. Polymeric blends from Chitosan and the new polymers are used to fabricate spin coated thin films. The effect of UV irradiation on the optical properties of pristine Chitosan and two novel Chitosan derived polymers blends in form of thin film structure are studied. The optical parameters of the blends thin films such as the refractive index (n), extinction coefficient (k) and dielectric constants are determined by spectrophotometric technique in the spectral range 200–2500 nm. The energy gap values (E g ), dielectric constants at infinity (ε ∞ ), lattice permittivity (ε L ) and dispersion parameters are calculated. E g is found to be 5.14 eV for Chitosan film and it is reduced to 4.25 and 4 eV for the two polymeric blends. ε ∞ is calculated to be 2.96 for Chitosan film which is reduced to 2.88 upon UV irradiation. The influence of exposing thin films to UV light demonstrates interesting modifications in linear and nonlinear optical properties (third order non-linear susceptibility and the non-linear refractive index) of Chitosan and its derivatives. The emission characteristics of the blends are also investigated. The fluorescence intensity of the polymeric films is decreased upon UV exposure. The obtained results propose that Chitosan and its derivatives are possible candidates for opto-electronic applications such as optical switching, optical limiters and OLED.
Differences in distant metastasis risk of breast cancer originating from various primary sites: a retrospective analysis based on the SEER database
Comparing daylight performance of dynamic and static shadings in office façades across multiple U.S. cities with various sky conditions
Low-resolution FAIMS for increased peptide coverage in low-load and single-cell proteomics
A novel unified lightweight temporal-spatial transformer approach for intrusion detection in drone networks
Eco-friendly spectrophotometric approach for the determination of anti-diabetic drugs in fixed-dose formulation together with metformin’s toxic impurity: comprehensive method assessment
Abstract Environmentally benign and straightforward spectrophotometric methods were developed and validated for the simultaneous determination of saxagliptin (SAX), metformin (MET), and the pharmacopeial impurity of MET, melamine (MEL), in bulk powder and pharmaceutical formulations. These proposed approaches provide reliable, low-cost, and accessible alternatives to conventional chromatographic techniques, which often require complex instrumentation, extended analysis times, and significant solvent consumption. Two complementary spectrophotometric methods were established. Method A, the ratio-difference approach, utilized MEL as a divisor for the quantification of SAX, while SAX served as a divisor for determining MET and MEL. Method B, based on the first derivative of ratio spectra, applied MEL as a divisor under optimized conditions (scaling factor = 10, Δλ = 4 nm). However, MEL could not be quantified by Method B because its derivative ratio signals in the selected spectral region were too weak and overlapped extensively with those of SAX and MET, preventing the establishment of a reliable linear calibration curve for this impurity. The methods exhibited linearity over the ranges of 5–90 µg/mL for SAX, 1–40 µg/mL for MET, and 0.5–10 µg/mL for MEL. Validation in accordance with ICH Q2(R1) guidelines confirmed their accuracy, precision, selectivity, and specificity. The results obtained by the proposed methods were statistically compared with those of a reported RP‑HPLC method, confirming the reliability of the proposed procedures. The environmental impact was assessed using the principles of green analytical chemistry (GAC), which incorporates sustainability by promoting methods that limit hazardous reagents, reduce energy consumption, and minimize waste while maintaining suitable analytical performance. Holistic evaluation tools such as the analytical greenness metric (AGREE), the green analytical procedure index (GAPI), the national environmental methods index (NEMI), the blue applicability grade index (BAGI), and the RGB 12 model enable simultaneous assessment of analytical quality, environmental impact, and practical applicability. These tools foster the development of “white” analytical chemistry and complement emerging indices like the environmental and practical performance index (EPPI).Overall, these spectrophotometric approaches represent sustainable, efficient, and accessible analytical alternatives for the routine quality control of Saxagliptin and Metformin in combined pharmaceutical formulations.