Search Results (34,468)

The bifunctional glutathione synthase (GshF) is able to catalyze glutathione synthesis and is favored for industrial application due to its lack of product inhibition. However, its practical use is limited by moderate catalytic efficiency and poor thermostability. Here, we applied ancestral sequence reconstruction (ASR) to engineer a more robust ancestral GshF (Anc427) with thermal denaturation temperature of 56.2 ± 0.2 °C, representing an increase of 10.8 ± 0.2 °C over the probe enzyme (St-GshF). Additionally, Anc427 exhibited a thermal half-life (t_1/2) of 3465.7 min at 40 °C, representing a 20-fold increase over that of St-GshF. Under optimal conditions (pH 7.0, 37 °C), Anc427 displayed a specific activity of 3.3 ± 0.02 U·mg⁻¹, representing a 20% enhancement compared to St-GshF. Structural modeling and molecular dynamics simulations indicated that the improved stability can be attributed to increased structural rigidity in Anc427. These findings demonstrate that ASR effectively enhances both thermostability and catalytic activity of GshF, significantly advancing its potential for industrial biocatalysis. Full article

A first-principles investigation was conducted to characterize the novel Cr₂ZnC MAX phase and its exfoliated MXene nanosheet, Cr₂C. The study critically examines the effect of electron correlations on the bulk phase, revealing that the PBE+U framework, unlike standard PBE, yields a dramatically enhanced magnetic moment of 12.80 μ_B (vs. 1.88 μ_B), confirming the necessity of this approach for Cr-based carbides. The phase stability is confirmed through rigorous analysis of its thermodynamic, dynamic, and mechanical properties. For the derived 2D Cr₂C, results confirm a robust half-metallic state with a total magnetic moment of 8.00 μ_B, characterized by a metallic spin-majority channel and a semiconducting spin-minority channel with a 2.41 eV direct gap, leading to near-ideal spin polarization. These combined features establish Cr₂C as a highly promising candidate for next-generation spintronic applications and 2D magnetic devices requiring room-temperature stability. Full article

Background: Composite restorations are the standard of care for posterior teeth due to their aesthetic properties and conservative nature. However, the choice between direct and semi-direct techniques can influence clinical longevity and performance. Objectives: This study aimed to compare the clinical performance of two restorative approaches: a direct technique and the semi-direct onlay technique in terms of aesthetic quality, surface finish, wear resistance, marginal integrity, and overall clinical efficiency over a two-year period. Methods: A total of 348 composite restorations were placed in 192 patients. Each restoration was evaluated at four timepoints: baseline (T0), 6 months (T1), 1 year (T2), and 2 years (T3). Clinical performance was assessed using standardised 5-point rating scales across the five dimensions. Repeated-measures ANOVA assessed changes over time, while Wilcoxon signed-rank and Mann–Whitney U tests were used for intra- and inter-group comparisons. Results: Significant time effects were observed across all clinical parameters (p < 0.0001). The direct technique exhibited superior initial results in aesthetics and surface finish at T0 and T1 (p < 0.001), but differences diminished by T3. In contrast, the semi-direct technique demonstrated improved performance in wear resistance and marginal integrity at T2 and T3. Both techniques showed progressive deterioration, particularly in marginal adaptation. Conclusions: The direct technique offers enhanced short-term aesthetics and procedural efficiency, while the semi-direct approach provides superior long-term durability and marginal adaptation. Full article

The Weather Research and Forecasting Model (WRF-ARW) version 4.5 was used to simulate the synoptic to mesoscale evolving atmosphere of Tropical Cyclone (TC) Hilary’s (2023) remnant passage over the southwestern United States. The atmospheric dynamic processes conducive to the precursor rain events were extensively studied to determine the effects of mid-level jetogenesis. Concurrently, the dynamics of mesoscale processes related to the interaction of TC Hilary over the complex topography of the western United States were studied with several sensitivity simulations on a nested 2 km × 2 km grid. The differential surface heating between the cloudy California coast and clear/elevated Great Basin plateau had a profound impact on the lower-mid-tropospheric mass field resulting in mid-level jetogenesis. Diagnostic analyses of the ageostrophic flow support the importance of both isallobaric and inertial advective forcing of the mid-level jetogenesis in response to differential surface sensible heating. This ageostrophic mesoscale jet ultimately transported tropical moisture in multiple plumes more than 1000 km poleward beyond the location of the extratropical transition of the storm, resulting in anomalous flooding precipitation within a massive arid western plateau. Full article

Accurate prognosis of the remaining useful life (RUL) for lithium-ion batteries is critical for mitigating range anxiety and ensuring the operational safety of electric vehicles. However, existing data-driven methods often struggle to maintain robustness when transferring from controlled laboratory conditions to complex, sensor-limited, real-world environments. To bridge this gap, this study presents U-H-Mamba, a novel uncertainty-aware hierarchical framework trained on a massive hybrid repository comprising over 146,000 charge–discharge cycles from both laboratory benchmarks and operational electric vehicle datasets. The proposed architecture employs a two-level design to decouple degradation dynamics, where a Multi-scale Temporal Convolutional Network functions as the base encoder to extract fine-grained electrochemical fingerprints, including derived virtual impedance proxies, from high-frequency intra-cycle measurements. Subsequently, an enhanced Pressure-Aware Multi-Head Mamba decoder models the long-range inter-cycle degradation trajectories with linear computational complexity. To guarantee reliability in safety-critical applications, a hybrid uncertainty quantification mechanism integrating Monte Carlo Dropout with Inductive Conformal Prediction is implemented to generate calibrated confidence intervals. Extensive empirical evaluations demonstrate the framework’s superior performance, achieving a RMSE of 3.2 cycles on the NASA dataset and 5.4 cycles on the highly variable NDANEV dataset, thereby outperforming state-of-the-art baselines by 20–40%. Furthermore, SHAP-based interpretability analysis confirms that the model correctly identifies physics-informed pressure dynamics as critical degradation drivers, validating its zero-shot generalization capabilities. With high accuracy and linear scalability, the U-H-Mamba model offers a viable and physically interpretable solution for cloud-based prognostics in large-scale electric vehicle fleets. Full article

Within natural rock masses, discontinuous joints are more prevalent than continuous joints. Discontinuous joints refer to non-persistent structural planes separated by intact rock bridges and can be quantified by the continuity coefficient K_A. They significantly affect the macroscopic mechanical properties of rock masses. Therefore, investigating discontinuous jointed rock masses with diverse morphologies carries considerable theoretical and engineering significance. Using 3D printing technology, resin-based specimens with discontinuous joints were subjected to laboratory mechanical tests to explore the evolution of failure mechanisms and mechanical properties of discontinuous jointed rock masses with different inclinations, undulation amplitudes, and structural plane continuity. Results show that under compression, discontinuous jointed rock masses consistently undergo combined tensile and shear stresses, with joint undulation amplitude and continuity governing coplanar crack initiation. As the joint inclination angle ranges from 0° to 90°, the peak compressive strength first decreases and then increases: specimens with continuous joints or discontinuous joints (continuity coefficient K_A < 0.25) follow a “V”-shaped trend, while those with K_A > 0.25 exhibit a “U”-shaped trend. Joint continuity is a key factor governing rock mass strength: at the same rock column radius, higher continuity results in lower strength, and vice versa. Joint morphology also influences strength, with specimens with regular zigzag joints and rectangular corrugated joints exhibiting 6.7% and 11.2% higher strength than smooth-jointed specimens, respectively. These results clarify the effects of joint continuity and undulation on rock mass strength, providing a theoretical foundation for the rapid determination of K_A via borehole imaging and laser scanning in engineering practice, and enabling direct prediction of rock mass strength trends. Full article

Background: Patient-reported outcome measures (PROMs) provide important insights into recovery after anterior cruciate ligament reconstruction (ACLR). Previous research suggests that males and females recover differently after ACLR, with females reporting greater pain, slower functional gains, and lower psychological readiness at later stages of rehabilitation. However, it is unknown if patient-reported outcomes differ by sex early after ACLR. To address this gap, we conducted a cross-sectional analysis comparing patient-reported outcome measures between sexes three months after ACLR. We hypothesized that females would report worse PROMs compared to males. Methods: This cross-sectional analysis used data from a prospectively maintained ACL reconstruction cohort. Fifty-six individuals (female: 23 and male: 33) with primary, unilateral ACLR completed PROMs three months after surgery. These PROMs included the Knee Injury and Osteoarthritis Outcome Score (KOOS; Symptoms, Pain, Activities of Daily Living, Sport and Recreation, Quality of Life), International Knee Documentation Committee (IKDC) subjective score, Knee Outcome Survey–Activities of Daily Living Scale (KOS-ADLS), Anterior Cruciate Ligament–Return to Sport After Injury (ACL-RSI), and the Tampa Scale of Kinesiophobia (TSK). All outcomes were expressed on a 0 to 100 percent scale, with higher scores indicating better outcomes, except for TSK, where lower scores indicated better outcomes. Normality was assessed within sex, using the Shapiro–Wilk test. Two-tailed independent-samples t-tests with Welch correction were used for approximately normal variables; otherwise, Mann–Whitney U tests were utilized (α = 0.05). Several outcomes had limited statistical power to detect MCID-sized differences, and findings for these measures should be interpreted cautiously. Results: No significant differences between sexes were found for any of the PROMs. Males trended towards having better KOOS Sport and Recreation and IKDC, but these were not statistically significant, and the effect sizes were small-to-moderate. Conclusions: No statistically significant sex-based differences were detected in PROMs at approximately 3 months after ACLR, indicating that any sex-related divergences between these measures may not occur until later in recovery. Full article

The photovoltaic field has seen significant development in recent years, with continuously expanding installation capacity and increasing grid integration. However, due to the intermittency of solar energy and meteorological variability, PV output power poses serious challenges to grid security and dispatch reliability. Traditional forecasting methods largely rely on modeling historical power and meteorological data, often neglecting the consideration of cloud movement, which constrains further improvement in prediction accuracy. To enhance prediction accuracy and model interpretability, this paper proposes a dual-branch attention-based PV power prediction model that integrates physical features from ground-based cloud images. Regarding input features, a cloud segmentation model is constructed based on the vision foundation model DINO encoder and an improved U-Net decoder to obtain cloud cover information. Based on deep feature point detection and an attention matching mechanism, cloud motion vectors are calculated to extract cloud motion speed and direction features. For feature processing, feature attention and temporal attention mechanisms are introduced, enabling the model to learn key meteorological factors and critical historical time steps. Structurally, a parallel architecture consisting of a linear branch and a nonlinear branch is adopted. A context-aware fusion module adaptively combines the prediction results from both branches, achieving collaborative modeling of linear trends and nonlinear fluctuations. Comparative experiments were conducted using two years of engineering data. Experimental results demonstrate that the proposed model outperforms the benchmarks across multiple metrics, validating the predictive advantages of the dual-branch structure that integrates physical features under complex weather conditions. Full article

Maca (Lepidium meyenii Walp.), a Brassicaceae species native to the high Andes of Peru, has gained global attention as a functional food and herbal medicinal product due to its endocrine-modulating, fertility-enhancing, and neuroprotective properties. Although numerous studies have addressed its biological effects, a systematic and up-to-date summary of its chemical constituents and analytical methodologies is lacking. This review aims to provide a critical overview of the chemical constituents of L. meyenii and to evaluate analytical studies published between 2000 and 2025, focusing on recent advances in extraction strategies and qualitative and quantitative analytical techniques for quality control. Major compound classes include macamides, macaenes, glucosinolates, and alkaloids, each contributing to maca’s multifaceted activity. Ultra-(high-)performance liquid chromatography (U(H)PLC), often coupled with ultraviolet, diode array, or mass spectrometric detection, is the primary and most robust analytical platform due to its sensitivity, selectivity, and throughput, while ultrasound-assisted extraction improves efficiency and reproducibility. Emerging techniques such as metabolomics and chemometric approaches enhance quality control by enabling holistic, multivariate assessment of complex systems and early detection of variations not captured by traditional univariate methods. As such, they provide complementary, predictive, and more representative insights into maca’s phytochemical complexity. The novelty of this review lies in its integration of conventional targeted analysis with emerging approaches, comprehensive comparison of analytical workflows, and critical discussion of variability related to phenotype, geographic origin, and post-harvest processing. By emphasizing analytical standardization and quality assessment rather than biological activity alone, this review provides a framework for quality control, authentication, and safety evaluation of L. meyenii as a functional food and dietary supplement. Full article

Flooding remains one of the most disruptive and costly natural hazards worldwide. Conventional approaches for estimating flood damage cost rely on empirical loss curves or historical insurance data, which often lack spatial resolution and predictive robustness. This study develops a data-driven framework for estimating flood damage costs across the contiguous United States, where comprehensive hydrologic, climatic, and socioeconomic data are available. A database of 17,407 flood events was compiled, incorporating approximately 38 parameters obtained from the National Oceanic and Atmospheric Administration (NOAA), the National Water Model (NWM), the United States Geological Survey (USGS NED), and the U.S. Census Bureau. Data preprocessing addressed missing values and outliers using the interquartile range and Walsh tests, followed by partitioning into training (70%), testing (15%), and validation (15%) subsets. Four modeling configurations were examined to improve predictive accuracy. The optimal hybrid regression–classification framework achieved correlation coefficients of 0.97 (training), 0.77 (testing), and 0.81 (validation) with minimal bias (−5.85, −107.8, and −274.5 USD, respectively). The findings demonstrate the potential of nationwide, event-based predictive approaches to enhance flood-damage cost assessment, providing a practical tool for risk evaluation and resource planning. Full article

Background: Semi-occluded vocal tract exercises (SOVTE) improve vocal quality and capacity. Water resistance therapy (WRT), a specific form of SOVTE with a tube submerged under water, generates increased and oscillating oral pressure through bubble formation during phonation, thereby influencing transglottal pressure and vocal fold dynamics. While the physiological effects of WRT using tube-based systems have been extensively studied, the influence of vowel-specific vocal tract configurations during WRT remains unclarified. This study examined how different vowel qualities during WRT affect vocal fold oscillation using the DoctorVox^® mask, which allows near-natural mouth opening and vowel articulation. Methods: Ten vocally healthy, untrained adults (25–50 years) performed a continuous vowel glide (/i/–/a/–/u/-/i/) at constant fundamental frequency and habitual loudness during WRT using the DoctorVox^® mask, with the tube submerged 2 cm in water. Simultaneous recordings included transnasal high-speed videoendoscopy (20,000 fps), electroglottography (EGG), acoustic signals and intra-tube oral pressure measurements. Glottal area waveforms (GAW) were derived to calculate the open quotient (OQ_GAW) and closing quotient (ClQ_GAW). Analyses were conducted separately for intra-tube pressure maxima, minima and intermediate phases within the bubble cycle during WRT. Statistical analysis used Wilcoxon signed-rank tests with Bonferroni correction. Results: In the baseline condition without WRT, significant vowel-related differences were found: /u/ showed a higher open quotient than /i/ and /a/ (p < 0.05) and a higher closing quotient than /a/ (p < 0.05). During WRT, these vowel-specific differences were no longer statistically significant. A non-significant trend toward reduced OQ_GAW during WRT was observed, most notably for /u/, while differences between pressure phases within the bubble cycle were minimal. Conclusions: WRT using the DoctorVox^® mask reduces vowel-specific differences in vocal fold vibration patterns, suggesting that for voice therapy, vowel quality modifications during WRT have little impact on vocal outcomes. Full article

Background: Glaucoma is an age-related optic neuropathy frequently accompanied by systemic comorbidities. Vitamin D deficiency (VDD) has been associated with cardiovascular and renal diseases in the general population, yet its relationship with long-term systemic outcomes in glaucoma remains unclear. This study evaluated the association between baseline vitamin D status and subsequent mortality and cardiorenal events in patients with primary glaucoma. Methods: We conducted a retrospective cohort study using deidentified electronic health records from the TriNetX U.S. Collaborative Network, a federated network of participating healthcare organizations. Adults (≥18 years) with incident primary glaucoma (2005–2020) and a serum 25-hydroxyvitamin D (25(OH)D) test within 12 months prior to diagnosis were categorized as VDD (<30 ng/mL) or vitamin D adequacy (VDA; ≥30 ng/mL). After 1:1 propensity score matching across 47 demographic, clinical, medication, and laboratory variables, 11,855 patients per group were followed for up to 5 years. Outcomes included all-cause mortality, major adverse cardiovascular events (MACE), acute kidney injury (AKI), and renal function decline (eGFR < 60 mL/min/1.73 m²). Analyses incorporated Kaplan–Meier curves, Cox models, landmark tests, sensitivity analyses, and competing risk methods. Results: Among the 35,100 eligible patients, the matched cohorts demonstrated higher 5-year risks associated with VDD for all-cause mortality (HR 1.104; 95% CI 1.001–1.217), MACE (HR 1.151; 95% CI 1.078–1.229), and AKI (HR 1.154; 95% CI 1.056–1.261), whereas the risks of renal function decline did not differ (HR 0.972; 95% CI 0.907–1.042). Risk divergence emerged within the first year of follow-up and persisted through the 5-year observation period. Conclusions: In patients with primary glaucoma, vitamin D deficiency was associated with higher long-term risks of mortality and cardiorenal complications, but not renal function decline. Taken together, the results are consistent with vitamin D status serving as a marker of broader systemic vulnerability in glaucoma and highlight the need for prospective studies to further clarify its prognostic significance. Full article

Underwater optical images are the primary carriers of underwater scene information, playing a crucial role in marine resource exploration, underwater environmental monitoring, and engineering inspection. However, wavelength-dependent absorption and scattering severely deteriorate underwater images, leading to reduced contrast, chromatic distortions, and loss of structural details. To address these issues, we propose a U-shaped underwater image enhancement framework that integrates Swin-Transformer blocks with lightweight attention and residual modules. A Dual-Window Multi-Head Self-Attention (DWMSA) in the bottleneck models long-range context while preserving fine local structure. A Global-Aware Attention Map (GAMP) adaptively re-weights channels and spatial locations to focus on severely degraded regions. A Feature-Augmentation Residual Network (FARN) stabilizes deep training and emphasizes texture and color fidelity. Trained with a combination of Charbonnier, perceptual, and edge losses, our method achieves state-of-the-art results in PSNR and SSIM, the lowest LPIPS, and improvements in UIQM and UCIQE on the UFO-120 and EUVP datasets, with average metrics of PSNR 29.5 dB, SSIM 0.94, LPIPS 0.17, UIQM 3.62, and UCIQE 0.59. Qualitative results show reduced color cast, restored contrast, and sharper details. Code, weights, and evaluation scripts will be released to support reproducibility. Full article

In this article, we investigate a nonlinear $\psi$-Hilfer fractional order Volterra integro-delay differential equation ($\psi$-Hilfer FRVIDDE) and a nonlinear $\psi$-Hilfer fractional Volterra delay integral equation ($\psi$-Hilfer FRVDIE), both of which incorporate multiple variable time delays. We establish sufficient conditions for the existence of a unique solution and the Ulam–Hyers stability (U-H stability) of both the $\psi$-Hilfer FRVIDDE and $\psi$-the Hilfer FRVDIE through two new main results. The proof technique relies on the Banach contraction mapping principle, properties of the Hilfer operator, and some additional analytical tools. The considered $\psi$-Hilfer FRVIDDE and $\psi$-Hilfer FRVDIE are new fractional mathematical models in the relevant literature. They extend and improve some available related fractional mathematical models from cases without delay to models incorporating multiple variable time delays, and they also provide new contributions to the qualitative theory of fractional delay differential and fractional delay integral equations. We also give two new examples to verify the applicability of main results of the article. Finally, the article presents substantial and novel results with new examples, contributing to the relevant literature. Full article

Uncertainty quantification in science and engineering has become increasingly important due to advances in computational mechanics and numerical simulation techniques. In this work, the relationship between uncertainty in soil material parameters and the variability of failure loads and displacements of a shallow foundation is investigated. A Drucker–Prager constitutive law is implemented within a stochastic finite element framework. The random material variables considered are the critical state line slope c, the unload–reload path slope $\kappa$, and the hydraulic permeability k defined by Darcy’s law. The novelty of this work lies in the integrated stochastic u–p finite element framework. The framework combines Drucker–Prager plasticity with spatially varying material properties, and Latin Hypercube Sampling. This approach enables probabilistic prediction of failure loads, displacements, stresses, strains, and limit-state initiation points at reduced computational cost compared to conventional Monte Carlo simulations. Statistical post-processing of the output parameters is performed using the Kolmogorov–Smirnov test. The results indicate that, for the investigated configurations, the distributions of failure loads and displacements can be adequately approximated by Gaussian distributions, despite the presence of material nonlinearity. Furthermore, the influence of soil depth and load eccentricity on the limit-state response is quantified within the proposed probabilistic framework. Full article