Search Results (36,507)

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by complex immune cell associations and continuous joint damage. Personalized clinical assessment and treatment options for RA remain hindered by a precision gap due to an inability to precisely match current global treatment strategies to individual molecular and spatial disease profiles. Recent advances in spatial transcriptomics and proteomics offer unprecedented opportunities to map molecular heterogeneity and spatial heterogeneity within RA tissues by identifying immune microenvironments activated during the disease, thus enabling precise therapeutic targeting. These techniques address the precision gap in RA by identifying distinct pathogenic subpopulations and cellular niches, providing insights into the biomolecules that possess significant therapeutic responses and are involved in disease progression. This review synthesizes recent findings demonstrating how spatial omics technologies, including spatial transcriptomics and proteomics, together with artificial intelligence, are transforming precision rheumatology. Full article

Skin-whitening products (SWPs) are widely used, yet many contain prohibited or misdeclared depigmenting agents posing safety concerns. This study developed and validated a sensitive and reliable HPLC-DAD method for the simultaneous determination of hydroquinone (HQ), salicylic acid (SAL), and niacinamide (NIC) in commercial and homemade SWPs. Validation followed ICH Q2(R1), demonstrating good specificity, linearity (R² > 0.9999), method precision (%RSD < 2%), and LOD/LOQ values of 0.2 and 0.7 µg/mL for all analytes. Recoveries of 97.48–99.83% for HQ, 99.37–101.26% for NIC, and 83.04–95.38% for SAL were also obtained. Analysis of 51 products revealed major discrepancies between declared and measured contents. HQ was detected in 18.60% of commercial samples despite its prohibition in OTC cosmetic formulations; none of the SAL-containing products matched their labels, and NIC appeared in 25.58% of samples, with only one sample compliant with its declared content. Homemade products showed undeclared HQ in 62.50% of samples, 25% of samples exceeded the 2% permitted SAL limit, and unregulated multi-ingredient combinations. Risk assessment showed all HQ-containing commercial products and several homemade formulations posed unacceptable systemic exposure risks (MoS < 100). Overall, the proposed method provides a practical and accessible approach for routine quality control and market surveillance of cosmetic products. Full article

Under non-independent and identically distributed (Non-IID) conditions, significant variations exist in local model updates across clients and training phases during the collaborative modeling process of differential privacy federated learning (DP-FL). Fixed clipping thresholds and noise scales struggle to accommodate these diverse update differences, leading to mismatches between local update intensity and noise perturbations. This imbalance results in data privacy leaks and suboptimal model accuracy. To address this, we propose a differential privacy federated learning method based on adaptive clipping thresholds. During each communication round, the server adaptively estimates the global clipping threshold for that round using a quantile strategy based on the statistical distribution of client update norms. Simultaneously, clients adaptively adjust their noise scales according to the clipping threshold magnitude, enabling dynamic matching of clipping intensity and noise perturbation across training phases and clients. The novelty of this work lies in a quantile-driven, round-wise global clipping adaptation that synchronizes sensitivity bounding and noise calibration across heterogeneous clients, enabling improved privacy–utility behavior under a fixed privacy accountant. Using experimental results on the rail damage datasets, our proposed method slightly reduces the attacker’s MIA ROC-AUC by 0.0033 and 0.0080 compared with Fed-DPA and DP-FedAvg, respectively, indicating stronger privacy protection, while improving average accuracy by 1.55% and 3.35% and achieving faster, more stable convergence. We further validate its effectiveness on CIFAR-10 under non-IID partitions. Full article

Psychological comorbidity is increasingly recognized as a critical factor influencing outcomes in chronic illness management, particularly in patients with end-stage renal disease (ESRD). The present study examines the psychological burden associated with long-term hemodialysis in patients with ESRD, focusing on emotional distress and maladaptive personality traits. Specifically, it explores group differences between hemodialysis patients and matched healthy controls in levels of stress, anxiety, depression, and psychopathological tendencies, including neuroticism, paranoia, and psychopathy-related traits, as well as exploratory associations with treatment duration. A purposive sample of 60 participants (30 patients undergoing chronic hemodialysis and 30 age- and sex-matched healthy controls) was assessed using validated psychometric instruments: The Hospital Anxiety and Depression Scale, the Pichot Neuroticism and Psychopathy Questionnaire, and a 23-item stress measurement questionnaire adapted to the dialysis context. Both descriptive and inferential statistical analyses were conducted, including independent-samples t-tests and effect size calculations (Cohen’s d). Compared to healthy controls, hemodialysis patients exhibited significantly higher levels of psychological distress across multiple domains. Large between-group effect sizes were observed for depression (Cohen’s d = 1.26) and perceived stress (d = 1.51), while moderate effects were identified for anxiety (d = 0.70), neuroticism (d = 0.58), and psychopathy-related traits (d = 0.82). Exploratory analyses indicated that patients with less than 10 years of dialysis experience reported significantly higher stress levels than those with longer treatment duration, whereas differences in anxiety, depression, and personality traits by dialysis duration were not statistically significant. These findings highlight the substantial emotional burden associated with long-term hemodialysis and underscore the importance of routine psychological screening and early psychosocial interventions to support adaptation, treatment adherence, and quality of life in nephrology care. Full article

Wind-tunnel experiments were conducted on Trionda, the official match ball of the 2026 FIFA World Cup. Aerodynamic force coefficients derived from these measurements were incorporated into numerical trajectory simulations of kicked balls. The resulting aerodynamic characteristics and simulated flight behavior were compared with those of the four previous World Cup match balls: Al Rihla (2022), Telstar 18 (2018), Brazuca (2014), and Jabulani (2010). Relative to its predecessors, Trionda exhibits a drag crisis at lower flow speeds, consistent with an apparently rougher surface. Although its turbulent-regime drag coefficient is more stable than those of earlier designs, its magnitude is modestly larger. Trajectory simulations therefore indicate the potential for small but perceptible reductions in range for long kicks. This study therefore provides the first aerodynamic characterization of the 2026 FIFA World Cup match ball (Trionda) and places its drag-crisis behavior and flight characteristics in direct quantitative comparison with those of recent World Cup balls examined under identical experimental conditions. Full article

Passenger fuel cell vehicles (FCVs) require high-gain DC/DC converters to achieve voltage matching between the low-power fuel cell (FC) stack (50–200 V) and the vehicle DC bus (400–800 V). To address the challenges in existing step-up DC/DC converters in relation to balancing the requirements of high voltage gain, wide input voltage range, low input current ripple and voltage stress, the common ground of input–output, and high efficiency in passenger FCV applications, this paper proposes three types of high-gain DC/DC converters based on an interleaved structure, incorporating quadratic Boost, quasi-Z source, and switched-inductor impedance networks. These designs effectively balance the scenario requirements of passenger FCVs. Meanwhile, taking one of the proposed converters (Interleaved-Quadratic Boost; I-QB) as an example, its steady-state performance such as voltage gain is analyzed and compared in detail with existing voltage step-up DC/DC converters. Furthermore, a scaled-down SiC-based experimental platform is constructed. Steady-state experiments validate the converter’s maximum voltage step-up capability of ten times, wide input voltage range of 30–80 V, input current ripple of less than 0.3 A, and low voltage stress on devices (≤U_o/2), thereby confirming the feasibility of these converters and the correctness of the performance analysis. The dynamic experimental results indicated that under input voltage step changes of 50–80 V and 100–50% load step changes, the I-QB converter exhibits a minor voltage overshoot with settling time under 200 ms. The prototype achieves a peak efficiency of 94.2%, confirming these converters’ suitability for passenger FCV powertrains. Full article

The wheels of lunar rovers are prone to bouncing during travel in the low gravity and rugged terrain conditions of the lunar surface, and poor matching of wheel alignment parameters can easily lead to tire wear in such conditions. Focusing on the double-wishbone suspension of lunar rovers, this study presents a wheel alignment parameter optimization method for tire wear reduction. First, a tire brush model is established, and it is determined that the toe angle and camber angle are the main factors affecting the tire wear work. And as the camber angle and toe angle increase, the tire wear work becomes greater. Then, a multi-body dynamic model of the double-wishbone independent suspension in a low-gravity environment is established. Taking the minimum tire wear as the optimization objective, the optimal solution set of alignment parameters such as the tire camber angle and toe angle obtained and the optimal hardpoint coordinate positions are determined. The variation range of the toe angle is optimized from [−0.55°, 1.58°] to [−0.37°, 1.32°]. After optimization, the variation in the toe angle is reduced by 20.4%, the change rate of the camber angle becomes smoother, and the comprehensive wear work of the tire is reduced by 17.47%. The research results provide theoretical guidance for the optimization of wheel alignment parameters of the double-wishbone suspension of the lunar rover. Full article

Achieving natural esthetics has become essential for successful dental restorations and supports the use of modern non-metal materials. However, complexity in esthetic features of natural teeth, determined by both inherent color factors and hierarchical and gradient microstructures, makes recording, determination, and reproduction difficult. This often leads to misunderstanding during manufacturing and dissatisfaction with the final outcome, even when using advanced digital tools. The aim of this study was to investigate a new, easy-to-handle digital tool for determining the color of restorative materials. An industrial-level handheld color identifier, the NCS Colourpin SE, together with the corresponding NCS color system, was tested on three materials: dental resin nanocomposite, self-glazed zirconia (SGZ), and Decore zirconia pellets. The repeatability and impacts of geometrical contributions such as surface roughness and thickness on different colors were measured. The Colourpin SE offered promising repeatability. Decore zirconia showed more than 90% repeatability for most of the colors, independent of thickness. The NCS scanner showed slightly better repeatability than earlier in clinical trials with an intraoral scanner. The shades A3.5 and A3 had lower repeatability, varying from 50 to 90%. It identified effects of material thickness and surface roughness, where the thicker samples were identified with higher blackness levels, and surface roughness seemed to be coupled with a lower blackness level in color identification codes. Small but consistent differences between materials were detected, suggesting that material and manufacturing methods affect the final shade. The NCS Colourpin SE shows potential to be developed into an affordable and easy-to-handle scanner for the identification of a patient’s tooth color, enabling synchronization with digital workflows and improving the match between restoration and the patient’s natural teeth. Nevertheless, further research and development in customized applications for color identification in esthetic dentistry is still required through multidisciplinary collaboration. Full article

Harmonics and interharmonics have a significant impact on the safe operation of power systems, and accurately identifying interharmonics in power systems is the basis of harmonic suppression. The accuracy with which interharmonic components in power systems are detected is easily affected by mode aliasing and noise; to address this issue, a method of detecting them based on an adjusted Fourier-based synchrosqueezing transform (AFSST) and the three-point symmetric difference energy operator (DEO3S) is proposed. First, in order to reduce the influence of endpoint effects on detection accuracy, an improved waveform feature-matching extension method is utilized to reduce endpoint effects generated during the FSST decomposition process. Then, because it is difficult to adaptively determine the number of ridges in the FSST decomposition process, the energy difference and normalized cross-correlation coefficient are utilized as the criterion for determining the number of modal decompositions in the FSST, thereby improving the accuracy of the ridge number. Finally, using AFSST, the harmonic/interharmonic signals are decomposed into a set of intrinsic mode functions (IMFs). The instantaneous frequency and amplitude of each component are extracted using DEO3S, enabling the accurate detection of harmonics and interharmonics in the power system. Experimental analysis was conducted using simulation data, arc furnace experimental system data, and hardware experimental platform data. The results showed that the proposed method can accurately detect harmonic/interharmonic parameters under different levels of noise interference. Compared with the FSST, EMD, EEMD, and CEEMDAN methods, the amplitude detection accuracy of the proposed method is improved by 0.21%, 0.78%, 0.64%, and 0.75%, respectively, and the amplitude detection accuracy is improved by 1.39%, 3.31%, 2.04%, and 3.14%, respectively. Full article

Papillary thyroid cancer (PTC) is the most common endocrine malignancy with especially high incidence in Middle Eastern populations. While classical hereditary syndromes explain a minority of cases, the broader germline landscape of non-syndromic PTC remains unclear. whole-exome sequencing was performed on 245 unselected Saudi PTC patients to identify germline pathogenic or likely pathogenic variants (PVs/LPVs) in cancer predisposition genes. Clinical and molecular characteristics, and family history were integrated to assess phenotypic correlations. Eleven patients (4.5%) harbored germline PVs/LPVs in cancer susceptibility genes including STK11, TP53, BRCA1, BRCA2, FANCA, SLX4, RAD50, MSH6, POLD1 and NF1. Four patients (36.4%) carried PVs/LPVs in canonical FA pathway genes; this increased to five patients (45.5%) when RAD50 was included. Two unrelated patients harbored the same STK11 variant (p.R304Q) without classical Peutz–Jeghers syndrome features. A TP53 hotspot mutation (p.R175H) was identified in a patient with a personal history of gastric cancer, a malignancy associated with Li–Fraumeni syndrome. Notably, the BRCA1 PV detected matches a known Saudi founder mutation in hereditary breast cancer, now observed in PTC. Most germline positive cases lacked syndromic manifestations, underscoring limitations of phenotype or family history-driven genetic testing strategies. These findings suggest that a small subset of non-syndromic PTC cases may carry germline PVs/LPVs in cancer predisposition genes, highlighting the need for broader genetic screening frameworks. Unbiased whole-exome analysis in unselected cohorts can uncover under-recognized genetic risk and guide screening strategies to address the unique hereditary landscape of thyroid cancer in underrepresented populations. Full article

Lesions of the tendons and manica flexoria (MF) within the digital flexor tendon sheath (DFTS) are a common cause for lameness in horses. This prospective study compared and quantified the agreement and disagreement of positive contrast computed tomographic tenography (CTT), positive contrast radiographic tenography (RXT), ultrasonography (US) and tenoscopy for diagnosing naturally occurring lesions within the DFTS, without application of a gold standard. Lesions affecting the deep (DDFT) and/or superficial digital flexor tendon (SDFT), and/or the MF and/or constriction of the palmar/plantar annular ligament (PAL) were evaluated in eighteen horses with distention of the DFTS. For DDFT lesions, comparing CTT with tenoscopy, US, and the combined results of US and RXT (US+RXT) attained the highest agreements, with 83% matching results (κ: 0.65). For SDFT lesions, CTT and tenoscopy showed the highest agreement with 94% matching results (κ: 0.89), followed by tenoscopy with US+RXT (78%; κ: 0.56). The highest agreement for MF-tear detection was found comparing CTT with tenoscopy (83%; κ: 0.67), followed by CTT with RXT (78%; κ: 0.56). None of the modalities agreed on positive diagnoses of PAL constriction. CTT achieved the highest agreement with tenoscopy and US for the diagnosis of lesions within the DDFT and is, therefore, considered the most useful modality for preoperative evaluation. Full article

The purpose of this study is to examine whether analyst-level credit can be assigned quantitatively in a lightweight human-feedback decision-support pipeline. In intelligence and national security workflows, analysts often provide edits, comments, and evaluative feedback during the production of analytic products, yet these intermediate contributions are usually discarded, leaving no auditable record of how individual feedback shaped the final output. To address this problem, this study proposes a proof-of-concept Analyst-of-Record framework that combines synthetic analyst feedback, a linear ridge reward model, first-order influence functions, and additive Shapley aggregation to estimate both feedback-item and analyst-level contribution scores. The research design uses the Fact Extraction and VERification (FEVER) fact-verification dataset under controlled experimental settings. The pipeline retrieves evidence with Best Matching 25 (BM25), generates a grounded template-based response, derives three synthetic analyst feedback channels from FEVER annotations, trains a reward model on simple claim–answer and analyst-identity features, and aggregates per-feedback influence scores into an Analyst Contribution Index (ACI). The main experiments are conducted on a 500-claim subset across five random seeds, with additional ablation and bootstrap analyses used to assess sensitivity and stability. The findings show that the reward model achieves a mean validation $R^2$ of $0.801\pm 0.037$, indicating that the synthetic feedback signals are learnable under the selected featureization. The analyst-level contribution scores remain stable across random seeds, with approximately half of the total influence magnitude attributed to the explanation-quality channel and the remainder split across the other two channels. Ablation results further show that removing the explanation-quality channel collapses validation fit, while bootstrap resampling demonstrates tight concentration of absolute ACI magnitudes. Theoretically, this study extends attribution research beyond document-only grounding by showing how analyst feedback itself can be modeled as an object of contribution analysis. It also demonstrates that influence functions and Shapley-style aggregation can be adapted into a tractable framework for estimating interpretable analyst-level credit in a reproducible experimental setting. Practically, the proposed framework offers an initial foundation for more traceable and accountable decision-support workflows in which intermediate analyst contributions can be preserved rather than lost. The results also provide a feasible implementation path for future systems that incorporate stronger generators, richer evidence representations, and real analyst annotations. Full article

This work presents a compact microwave sensor for noninvasive blood glucose monitoring based on a substrate-integrated waveguide loaded with a complementary split-ring resonator on RO4350. The sensing principle uses shifts in resonance frequency and changes in S-parameters to track the dielectric dispersion of glucose-containing tissue. The resonator is constructed using Substrate-Integrated Waveguide (SIW) technology, which mimics the propagation characteristics of a conventional rectangular waveguide. To validate its versatility, the sensor implements three practical sample delivery modes: direct liquid contact with the sensing surface, a glass tube holder mounted over the active region, and a non-invasive fingertip interface. Electromagnetic simulations and benchtop measurements confirm clear glucose-dependent frequency shifts with stable matching and insertion levels. Across the physiological range of 20 to 200 mg·dL⁻¹, the sensor exhibits clear glucose-dependent resonance shifts in all configurations. In direct contact mode, the resonance frequency shifts from 10.83 GHz to 10.45 GHz with sensitivities up to 2.47 MHz per mg·dL⁻¹. The tube configuration shows a shift from 10.49 GHz to 10.38 GHz with sensitivity up to 0.80 MHz per mg·dL⁻¹, while reducing contamination. In the non-invasive fingertip mode, the resonance shifts from 2.56 GHz to 2.52 GHz with sensitivities up to 0.25 MHz per mg·dL⁻¹. These results confirm the sensor’s compactness, reliability, and suitability for portable, low-cost glucose monitoring. The results indicate that the proposed sensor can support practical continuous or spot monitoring and offers a clear path toward portable and low-cost glucose assessment. Full article

To address the issue that multipath effect severely restricts the performance of indoor visible light positioning (VLP) systems and multipath interference intensity varies significantly across different regions, this paper proposes a spatial adaptive multipath suppression scheme for the first time. At the transmitter, a hybrid transmission architecture of time division multiplexing (TDM) and direct current biased-orthogonal frequency division multiplexing (DCO-OFDM) is employed, providing ideal observation vectors for sparse channel modeling at the receiver through specialized pilot symbol design. At the receiver, a novel Spatial Adaptive–Main Path Energy Constraint–Orthogonal Matching Pursuit (SA-MPEC-OMP, SMO) algorithm is proposed to adapt to the spatial region characteristics with varying multipath intensities, enabling low-latency and accurate separation of Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) paths. Simulation results verify that the SMO algorithm achieves high main path extraction accuracy exceeding 90% in all regions, with its LOS energy ratio 2.7 to 3 times higher than that of the traditional OMP algorithm. Based on the results of the multipath suppression scheme, a high-precision 3D VLP scheme is proposed by integrating the SMO multipath suppression with intelligent algorithms. Specifically, a point classification model performs regional partitioning and dynamic threshold matching, while a height estimation model driven by LOS power extracted via SMO estimates the height of the target point. Finally, 3D coordinates are calculated using trilateration. Simulation results indicate that through the synergy of signal design and algorithm optimization, the proposed scheme achieves centimeter-level positioning across the entire space with a single positioning time of less than 18.7 ms, featuring strong multipath robustness and promising engineering application potential. Full article

A novel catalyst, Tm₂FeSbO₇, was synthesized by employing the solid-phase high-temperature sintering method, and, for the first time, it was utilized to create a Z-type heterojunction with BiYO₃. A direct Z-scheme Tm₂FeSbO₇/BiYO₃ heterojunction photocatalyst (TBHP) was successfully produced by employing the ball-milling technique. X-ray diffraction analysis results indicated that Tm₂FeSbO₇ crystallized in a cubic pyrochlorestructure which owned the Fd-3m space group, with a unit cell parameter of 10.1769 Å, whereas BiYO₃ displayed a fluorite structure in the Fm-3m space group, with a unit cell parameter of 5.4222 Å. The Mossbauer spectrum of Tm₂FeSbO₇ showed that Fe³⁺ ions might locate at octahedral sites. The measured bandgap widths for the TBHP, Tm₂FeSbO_7, and BiYO₃ were 2.14 eV, 2.21 eV, and 2.30 eV, respectively. Multiple experimental results demonstrated that the TBHP exhibited a higher valence band ionization potential, a narrower band gap width, and a higher removal efficiency of the sulfamethoxazole (SMX) compared with the Dy₂TmSbO₇/BiHoO₃ heterojunction photocatalyst. Under visible-light irradiation (VISLI) of 115 min, the TBHP showcased exceptional photocatalytic elimination performance; therefore, the elimination rate of the SMX and the total organic carbon (TOC) mineralization rate reached 99.51% and 98.10%, respectively. In contrast to single-component Tm₂FeSbO₇, BiYO_3, or conventional nitrogen-doped titanium dioxide (N-TiO₂) catalyst, the TBHP exhibited removal efficiency enhancement for degrading the SMX by 1.17 times, 1.31 times, or 4.06 times. Simultaneously, the matching mineralization rate for removing the TOC density by employing the TBHP was 1.20 times, 1.34 times, or 4.73 times higher than that by employing Tm₂FeSbO₇, BiYO₃, or conventional N-TiO₂. Above experimental results indicated that the mineralization efficiency for removing TOC density by employing the TBHP was higher than that by employing Tm₂FeSbO₇, BiYO₃, or N-TiO₂. Radicals trapping experiments and the electron paramagnetic resonance spectroscopy results revealed that hydroxyl radicals, superoxide anions, and photoinduced holes were the primary active species during the catalytic elimination course of the SMX by employing the TBHP under VISLI. The results demonstrated that the direct Z-scheme TBHP, which was developed in this study, exhibited the maximal removal efficiency for degrading the SMX in contrast to Tm₂FeSbO₇, BiYO₃, or N-TiO₂. Additionally, the possible elimination routes and elimination mechanisms of the SMX were proposed. Therefore, an important scientific foundation for developing high-performance heterojunction catalysts was established. Full article