Search Results (7,751)

Cardiovascular disease encompasses a wide group of conditions that affect the heart and blood vessels. Of these diseases, cardiomyopathies and arrhythmias specifically have been well-studied in their relationship to cardiac dyads, nanoscopic structures that connect electrical signals to muscle contraction. The proper development and positioning of dyads is essential in excitation–contraction (EC) coupling and, thus, beating of the heart. Three proteins, namely CMYA5, JPH2, and BIN1, are responsible for maintaining the dyadic cleft between the T-tubule and junctional sarcoplasmic reticulum (jSR). Various other dyadic proteins play integral roles in the primary function of the dyad—translating a propagating action potential (AP) into a myocardial contraction. Ca²⁺, a secondary messenger in this process, acts as an allosteric activator of the sarcomere, and its cytoplasmic concentration is regulated by the dyad. Loss-of-function mutations have been shown to result in cardiomyopathies and arrhythmias. Adeno-associated virus (AAV) gene therapy with dyad components can rescue dyadic dysfunction, which results in cardiomyopathies and arrhythmias. Overall, the dyad and its components serve as essential mediators of calcium homeostasis and excitation–contraction coupling in the mammalian heart and, when dysfunctional, result in significant cardiac dysfunction, arrhythmias, morbidity, and mortality. Full article

The aim of this study was to evaluate the impact of autoclaving on the dimensional stability of surgical guides (SGs) for aesthetic crown lengthening (ACL) using different resins/printing methods. Fifty SGs for ACL were printed using five different resin/printer combinations (FL, SR, ND, KS and VC). All the SGs were scanned before (T0) and after (T1) sterilization. Autoclaving was conducted at 134 °C during 4 min. The STL files of each SG at T0 and T1 were compared with the original design (TR). Dimensional stability was measured using trueness and precision. Deviations from TR to T1 were calculated in the three space axes and by measuring the area between three reference landmarks. At T0, the FL group showed the best trueness and precision, while the SR group performed significantly worse than the other groups. At T1, all the groups except VC exhibited significant dimensional alterations compared with T0. Also, VC showed the best trueness and precision values. All the groups had a significant deviation in at least one space axis, while only the SR group exhibited significant variations from T1 to TR in the area between the reference landmarks. Most of the evaluated resin/3D printer combinations suffered significant dimensional alterations after autoclaving. Full article

This study evaluates the replacement of petroleum-based naphthenic oil with four types of soybean-derived alternatives—virgin soybean oil (SBO), epoxidized SBO (ESBO), expired SBO, and recycled SBO—in styrene–butadiene rubber (SBR) composites. The materials were tested in both staining rubber (SR) and non-staining rubber (NSR) systems to assess processing characteristics, mechanical performance, and environmental durability. Among the alternatives, SBO demonstrated the best overall performance, improving processability and tensile strength by over 10%, while ESBO enhanced ozone resistance by 35% due to its epoxide functionality. Expired and recycled SBOs maintained essential mechanical properties within 90% of virgin SBO values. The full replacement of CH450 with SBO in tire prototypes resulted in burst strength exceeding 1000 kPa and stable appearance after 5000 km of road testing. To validate industrial relevance, the developed green tire was exhibited at the 2025 Taipei International Cycle Show, attracting interest from international buyers and stakeholders for its eco-friendly composition and carbon footprint reduction potential, thereby demonstrating both technical feasibility and commercial viability. Full article

Background: This study was performed to validate the addition of capacitive-based pressure sensors to an existing smart sock developed by the research team. This study focused on evaluating the accuracy of soft robotic sensor (SRS) pressure data and its relationship with laboratory-grade Kistler force plates in collecting ground force reaction data. Methods: Nineteen participants performed walking trials while wearing the smart sock with and without shoes. Data was collected simultaneously with the sock and the force plates for each gait phase including foot-flat, heel-off, and midstance. The correlation between the smart sock and force plates was analyzed using Pearson’s correlation coefficient and R-squared values. Results: Overall, the strength of the relationship between the smart sock’s SRS data and the vertical ground reaction force (GRF) data from the force plates showed a strong correlation, with a Pearson’s correlation coefficient of 0.85 ± 0.1; 86% of the trials had a value higher than 0.75. The linear regression models also showed a strong correlation, with an R-squared value of 0.88 ± 0.12, which improved to 0.90 ± 0.07 when including a stretch-SRS for measuring ankle flexion. Conclusions: With these strong correlation results, there is potential for capacitive pressure sensors to be integrated into the proposed device and utilized in telehealth and sports performance applications. Full article

Currently, the trade-off between oxygen permeation flux and structural stability in conventional perovskite oxides restricts the practical application of oxygen permeable membranes. In this study, a high-entropy design was applied to the B-site of BSCF matrix materials, resulting in the successful synthesis of a high-entropy perovskite, Ba_0.5Sr_0.5Co_0.71Fe_0.2Ta_0.03Ni_0.03Zr_0.03O_3−δ. The crystal structure, microstructure, and elemental composition of the material were systematically characterized and analyzed. Theoretical analysis and experimental characterization confirm that the material exhibits a stable single-phase high-entropy perovskite oxide structure. Under He as the sweep gas, the membrane achieved an oxygen permeation flux of 1.28 mL·cm⁻²·min⁻¹ and operated stably for over 100 h (1 mm thick, 900 °C). In a 20% CO₂/He atmosphere, the flux remained above 0.92 mL·cm⁻²·min⁻¹ for over 100 h, demonstrating good CO₂ tolerance. Notably, when the sweep gas is returned to the pure He atmosphere, the oxygen permeation flux fully recovers to 1.28 mL·cm⁻²·min⁻¹, with no evidence of leakage. These findings indicate that the proposed B-site doping strategy can break the trade-off between oxygen permeability and structural stability in conventional perovskite membranes. This advancement supports the industrialization of oxygen permeable membranes and offers valuable theoretical guidance for the design of high-performance perovskite materials. Full article

Cloud computing offers a broad spectrum of services to users, particularly in multi-cloud environments where service-centric features are introduced to support users from multiple endpoints. To improve service availability and optimize the utilization of required services, cloud brokerage has been integrated into multi-cloud systems. The primary objective of a cloud broker is to ensure the quality and outcomes of services offered to customers. However, traditional cloud brokers face limitations in measuring service trust, ensuring validity, and anticipating future enhancements of services across different cloud platforms. To address these challenges, the proposed intelligent cloud broker integrates an intelligence mechanism that enhances decision-making within a multi-cloud environment. This broker performs a comprehensive validation and verification of service trustworthiness by analyzing various trust factors, including service response time, sustainability, suitability, accuracy, transparency, interoperability, availability, reliability, stability, cost, throughput, efficiency, and scalability. Customer feedback is also incorporated to assess these trust factors prior to service recommendation. The proposed model calculates service ranking (SR) values for available cloud services and dynamically includes newly introduced services during the validation process by mapping them with existing entries in the Service Collection Repository (SCR). Performance evaluation using the Google cluster-usage traces dataset demonstrates that the ICB outperforms existing approaches such as the Clustering-Based Trust Degree Computation (CBTDC) algorithm and the Service Context-Aware QoS Prediction and Recommendation (SCAQPR) model. Results confirm that the ICB significantly enhances the effectiveness and reliability of cloud service recommendations for users. Full article

Background: The development of brain metastases (BM) is a relatively uncommon but significantly adverse event in the spread of colorectal cancer (CRC). Although management of CRC BM has improved with advances in imaging and systemic therapies, clinical outcomes remain poor. Methods: This retrospective cohort study used the U.S. National Cancer Database to evaluate survival outcomes, treatment patterns, and prognostic factors in CRC patients diagnosed with BM between 2010 and 2020. Patients with isolated brain-only metastases formed the primary analytic cohort, while those with additional extracranial metastases were included for descriptive comparison. Multivariable Cox proportional hazards and logistic regression models were used to assess factors associated with of survival. Proportional hazards assumptions were tested using Schoenfeld residuals. Accelerated failure time models were also employed. Results: From a cohort of 1,040,877 individuals with CRC, 795 had metastatic disease present along with relevant data, of which 296 had isolated BM. Median overall survival (mOS) in BM-only metastatic disease group was 7.82 months (95% CI: 5.82–9.66). The longest survival was observed among patients treated with stereotactic radiosurgery combined with systemic therapy (SRS+Sys), with a median OS of 23.26 months (95% CI: 17.51–41.95) and a 3-year survival rate of 35.8%. In adjusted Cox models, SRS, systemic therapy, and definitive surgery of the primary site were each independently associated with reduced hazard of death. Rectal cancer patients had longer survival than those with colon primaries (mOS: 10.35 vs. 6.08 months). Age, comorbidity burden, and insurance status were not associated with survival in adjusted analyses. Conclusions: SRS+Sys was associated with longer survival compared to other treatment strategies. However, treatment selection is highly dependent on individual clinical factors such as performance status, comorbidities, and disease extent; therefore, these findings must be interpreted with caution Future prospective studies incorporating molecular and biomarker data are warranted to better guide care in this rare and high-risk group. Full article

Objective: This study aimed to evaluate whether modifying the post-processing algorithm of Twin-Spiral Dual-Energy computed tomography (DECT) improves infarct detection compared to conventional Dual-Energy CT (DECT) and Single-Energy CT (SECT) following endovascular therapy (EVT) for large vessel occlusion (LVO). Methods: We retrospectively analyzed 52 patients who underwent Twin-Spiral DECT after endovascular stroke therapy. Ten patients were used to generate a device-specific parameter (“y”) using an AI-based neural network (SynthSR). This parameter was integrated into the post-processing algorithm for edema map generation. Quantitative Hounsfield unit (HU) measurements were used to assess density differences in ischemic brain tissue across conventional virtual non-contrast (VNC) images and edema maps. Results: The median HU of infarcted tissue in conventional mixed DECT was 33.73 ± 4.58, compared to 22.96 ± 3.81 in default VNC images. Edema maps with different smoothing filter settings showed values of 14.39 ± 4.96, 14.50 ± 3.75, and 15.05 ± 2.65, respectively. All edema maps demonstrated statistically significant HU differences of infarcted tissue compared to conventional VNC images ($p<0.001$) while maintaining the density values of non-infarcted brain tissue. Conclusions: Enhancing the post-processing algorithm of conventional virtual non-contrast imaging improves infarct detection compared to standard mixed or virtual non-contrast reconstructions in Dual-Energy CT. Full article

This study analyzed the heavy metal tolerance and chromium reduction and the potential of plant growth to promote Rhizobium sp. OS-1. By genetic makeup, the Rhizobium strain is nitrogen-fixing and phosphate-solubilizing in metal-contaminated agricultural soil. Among the Rhizobium group, bacterial strain OS-1 showed a significant tolerance to heavy metals, particularly chromium (900 µg/mL), zinc (700 µg/mL), and copper. In the initial investigation, the bacteria strains were morphologically short-rod, Gram-negative, appeared as light pink colonies on media plates, and were biochemically positive for catalase reaction and the ability to ferment glucose, sucrose, and mannitol. Further, bacterial genomic DNA was isolated and amplified with the 16SrRNA gene and sequencing; the obtained 16S rRNA sequence achieved accession no. HE663761.1 from the NCBI GenBank, and it was confirmed that the strain belongs to the Rhizobium genus by phylogenetic analysis. The strain’s performance was best for high hexavalent chromium [Cr(VI)] reduction at 7–8 pH and a temperature of 30 °C, resulting in a total decrease in 96 h. Additionally, the adsorption isotherm Freundlich and Langmuir models fit best for this study, revealing a large biosorption capacity, with Cr(VI) having the highest affinity. Further bacterial chromium reduction was confirmed by an enzymatic test of nitro reductase and chromate reductase activity in bacterial extract. Further, from the metal biosorption study, an Artificial Neural Network (ANN) model was built to assess the metal reduction capability, considering the variables of pH, temperature, incubation duration, and initial metal concentration. The model attained an excellent expected accuracy (R² > 0.90). With these features, this bacterial strain is excellent for bioremediation and use for industrial purposes and agricultural sustainability in metal-contaminated agricultural fields. Full article

Image super-resolution (SR) is essential for enhancing image quality in critical applications, such as medical imaging and satellite remote sensing. However, existing methods were often limited in their ability to effectively process and integrate multi-scales information from fine textures to global structures. To address these limitations, this paper proposes DSCNN, a dynamic snake convolution neural network for enhanced image super-resolution. DSCNN optimizes feature extraction and network architecture to enhance both performance and efficiency: To improve feature extraction, the core innovation is a feature extraction and enhancement module with dynamic snake convolution that dynamically adjusts the convolution kernel’s shape and position to better fit the image’s geometric structures, significantly improving feature extraction. To optimize the network’s structure, DSCNN employs an enhanced residual network framework. This framework utilizes parallel convolutional layers and a global feature fusion mechanism to further strengthen feature extraction capability and gradient flow efficiency. Additionally, the network incorporates a SwishReLU-based activation function and a multi-scale convolutional concatenation structure. This multi-scale design effectively captures both local details and global image structure, enhancing SR reconstruction. In summary, the proposed DSCNN outperforms existing methods in both objective metrics and visual perception (e.g., our method achieved optimal PSNR and SSIM results on the Set5 $\times 4$ dataset). Full article

Sun-induced chlorophyll fluorescence (SIF) is an important indicator of vegetation photosynthesis. While remote sensing enables large-scale monitoring of SIF, existing products face the challenge of trade-offs between temporal and spatial resolutions, limiting their applications. To select the optimal model for SIF data downscaling, we used a consistent dataset combined with vegetation physiological and meteorological parameters to evaluate four different regression methods in this study. The XGBoost model demonstrated the best performance during cross-validation (R² = 0.84, RMSE = 0.137 mW/m²/nm/sr) and was, therefore, selected to downscale GOME-2 SIF data. The resulting high-resolution SIF product (HRSIF) has a temporal resolution of 8 days and a spatial resolution of 0.05° × 0.05°. The downscaled product shows high fidelity to the original coarse SIF data when aggregated (correlation = 0.76). The reliability of the product was ensured through cross-validation with ground-based and satellite observations. Moreover, the finer spatial resolution of HRSIF better matches the footprint of eddy covariance flux towers, leading to a significant improvement in the correlation with tower-based gross primary productivity (GPP). Specifically, in the mixed forest vegetation type with the best performance, the R² increased from 0.66 to 0.85, representing an increase of 28%. This higher-precision product will support more effective ecosystem monitoring and research. Full article

This article presents the potential use of a humic agent called ‘Superhumate’, obtained from weathered coal from the Shubarkol deposit in Kazakhstan. The experiment was conducted using model solutions and surface mine water samples from the “Degelen” site at the Semipalatinsk Test Site. The adsorption of heavy metals and toxic elements using the “Superhumate” agent was carried out under dynamic conditions using a chromatographic column. Tests were conducted at a natural pH range of 5–8 (mine waters) and with a model solution at pH 1.7. Assessing the sorption efficiency of this preparation revealed that at pH 1.7, the agent does not adsorb elements such as Cd, Cu, Pb, and Zn. Under dynamic experimental conditions, using the preparation for mine waters at natural pH levels (pH 5–8), elements such as Be, Sr, Mo, Cd, Cs, Zn, and U were efficiently adsorbed at levels of 60–95%. The sorption efficiency of Pb ions was found to be almost independent of pH. The experimental results obtained with mine water samples indicate that alkaline solutions have the highest sorption efficiency, with pH ≥ 7, which is attributed to the solubility of the agent. Full article

The commercialization of proton-conducting fuel cells (PCFCs) is hindered by the limited electroactivity and durability of cathodes at intermediate temperatures ranging from 400 to 700 °C, a challenge exacerbated by an insufficient understanding of high-entropy perovskite (HEP) materials for oxygen reduction reaction (ORR) optimization. This study introduces an yttrium-doped HEP to address these limitations. A comparative analysis of Ce_0.2−xY_xBa_0.2Sr_0.2La_0.2Ca_0.2CoO_3−δ (x = 0, 0.2; designated as CBSLCC and YBSLCC) revealed that yttrium doping enhanced the ORR activity, reduced the thermal expansion coefficient (19.9 × 10⁻⁶ K⁻¹, 30–900 °C), and improved the thermomechanical compatibility with the BaZr_0.1Ce_0.7Y_0.1Yb_0.1O_3−δ electrolytes. Electrochemical testing demonstrated a peak power density equal to 586 mW cm⁻² at 700 °C, with a polarization resistance equaling 0.3 Ω cm². Yttrium-induced lattice distortion promotes proton adsorption while suppressing detrimental Co spin-state transitions. These findings advance the development of durable, high-efficiency PCFC cathodes, offering immediate applications in clean energy systems, particularly for distributed power generation. Full article

This study involved the fabrication of poly (vinyl alcohol) (PVA) nanocomposite films using the solution-casting process, which incorporated strontium-coated silver oxide (Sr-Ag₂O) nanoparticles generated by a plant-extract assisted method. Various characterization techniques, such as XRD, SEM, TEM, UV, and FTIR, showed the formation and uniform distribution of Sr-Ag₂O nanoparticles in the PVA film, which are biocompatible nanocomposite films. The presence of hydroxyl groups leads to appreciable mixing and interaction between the Sr-Ag₂O nanoparticles and the PVA polymer. Mechanical and thermal results suggest enhanced tensile strength and increased thermal stability. In addition, the sample of PVA/Sr-Ag₂O (1.94/0.06 wt. ratio) nanocomposite film showed decreased hydrophilicity, lower hemolysis, non-toxicity, and appreciable cell migration activity, with nearly 19.95% cell migration compared to the standard drug, and the presence of Sr-Ag₂O nanoparticles favored the adhesion and spreading of cells, which triggered the reduction in the gaps. These research findings suggest that PVA/Sr-Ag₂O nanocomposite films with good mechanical, antimicrobial, non-toxic, and biocompatible properties could be applied in biological wound-healing applications. Full article

The vast majority of photocatalysts find it difficult to consistently and stably exhibit high performance due to the variability of sunlight intensity within a day, as well as the high energy consumption of artificial light sources. In this study, mechanoluminescent Sr₂MgSi₂O₇:Eu,Dy phosphors is combined with NiS@g-C₃N₄ composite to construct a ternary heterogeneous photocatalytic system, denoted as NCS. In addition to the enhanced separation efficiency of photogenerated charge carriers by the formation of a heterojunction, the introduction of Sr₂MgSi₂O₇:Eu,Dy provides an ultra-driving force for the photocatalytic reactions owing to its mechanoluminescence-induced excitation. Results show that the degradation rate of RhB increased significantly in comparison with pristine g-C₃N₄ and NiS@g-C₃N₄, indicating the obvious advantages of the ternary system for charge separation and migration. Moreover, the additional photocatalytic activity of NCS under ultrasound stimulation makes it a promising all-weather photocatalyst even in dark environments. This novel strategy opens up new horizons for the synergistic combination of light-driven and ultrasound-driven heterogeneous photocatalytic systems, and it also has important reference significance for the design and application of high-performance photocatalysts. Full article