Search Results (1,750)

The molecular structure and mechanical resilience of the binder are crucial for mitigating volume expansion, maintaining electrode structural integrity, and enhancing the cycling stability of silicon-based anode materials in lithium-ion batteries. In this study, from the perspective of binder molecular structural design, commercial carboxymethyl cellulose (CMC) was modified with silk protein (SF), which has good mechanical properties and abundant surface functional groups, to address issues such as high brittleness, poor compliance and easy cracking of the electrode structure during charge and discharge cycles, and to enhance the mechanical properties of the CMC-based binder and its interaction with silicon particles, so as to improve the cycle stability of silicon-based materials. The mechanical properties of the CMC binder were significantly improved and the interaction between the binder and the surface of the silicon particles was enhanced by the addition of SF. When the SF content was optimized at 6 wt%, the electrode exhibited the best electrochemical performance, delivering a specific capacity of 1182 mAh/g at a high current density of 5000 mA/g, and retaining a capacity of 1138 mAh/g after 50 cycles at 1000 mA/g, demonstrating excellent electrochemical durability. Full article

The three-dimensional (3D) structure of clouds is a key factor in atmospheric processes, profoundly influencing solar radiation transfer, weather patterns, and climate dynamics. However, accurately representing this complex structure in radiative transfer models remains a significant challenge. As part of the Deep 3D Scattering of Solar Radiation in the Atmosphere due to Clouds (D3D) project, we conducted a comprehensive study on the role of all-sky imagers (ASIs) in reconstructing observational 3D cloud fields and integrating them into advanced 3D cloud modeling. Since November 2022, a network of four ASIs has been operating across the broader Patras region in Greece, continuously capturing atmospheric measurements over an area of approximately 50 km². Using simultaneously captured images from the ASIs within the network, a 3D cloud reconstruction was performed utilizing advanced image processing techniques, with a primary focus on cumulus cloud scenarios. The Structure from Motion (SfM) technique was employed to reconstruct the 3D structural characteristics of clouds from two-dimensional images. The resulting 3D cloud fields were then integrated into the MYSTIC three-dimensional radiative transfer model to simulate and reconstruct solar irradiance fields. Full article

Background/Objectives: Colorectal carcinoma (CRC) is among the most commonly diagnosed cancers in both men and women. Although CRC mortality is generally decreasing, new therapeutic options are needed for unresponsive subgroups of CRC patients. Methods: A series of known and new tyrphostin derivatives was tested for their efficacy against three CRC cell lines with varying KRAS, p53, and/or BRAF statuses. Growth inhibition, apoptosis induction, and inhibition of EGFR and VEGFR-2 were investigated. Results: Tyrphostin A9, the known RG13022-related tyrphostin 1a and its dichlorido(p-cymene)ruthenium(II) complex 1b, and the new SF₅-substituted compounds 2a and 2b showed selective antiproliferative activity against KRAS-mutant HCT-116 CRC cells expressing wildtype p53, while p53-knockout HCT-116 and KRAS-wildtype BRAF/p53-mutant HT-29 CRC cells were distinctly less sensitive. In HCT-116 cells, only tyrphostin A9 increased mRNA expression of caspases 3 and 8, as well as the kinases MEK1 and MEK2, whereas 2a reduced caspase 8 mRNA levels. Tyrphostin A9 increased caspase 3 activity and induced apoptosis in HCT-116 p53-wildtype cells while simultaneously inhibiting the receptor tyrosine kinases EGFR and VEGFR-2 at low nanomolar concentrations. Conclusions: Tyrphostin A9 could be a promising therapeutic option for the treatment of KRAS-mutant CRC that expresses wildtype p53. Full article

Neural Radiance Fields (NeRF) reconstruction faces significant challenges under non-ideal conditions, such as sparse viewpoints or missing camera pose information. Existing approaches frequently assume accurate camera poses and validate their effectiveness on standard datasets, which restricts their applicability in real-world scenarios. To tackle the challenge of sparse viewpoints and the inability of Structure-from-Motion (SfM) to accurately estimate camera poses, we propose a novel approach. Our method replaces SfM with the MASt3R-SfM algorithm to robustly compute camera poses and generate dense point clouds, which serve as depth–space constraints for NeRF reconstruction, mitigating geometric information loss caused by limited viewpoints. Additionally, we introduce a high-frequency annealing encoding strategy to prevent network overfitting and employ a depth loss function leveraging Pearson correlation coefficients to extract low-frequency information from images. Experimental results demonstrate that our approach achieves high-quality NeRF reconstruction under conditions of sparse viewpoints and missing camera poses while being better suited for real-world applications. Its effectiveness has been validated on the Real Forward-Facing dataset and in real-world scenarios. Full article

Crumb rubber, obtained from discarded tires, presents a sustainable alternative in the construction industry, particularly in rubberized concrete. Treated crumb rubber offers improved mechanical performance; however, limited reports are available on its behavior at elevated temperatures. This study investigates the performance of rubberized concrete containing treated and untreated crumb rubber when exposed to elevated temperatures. The treatments employed are chemical (sodium hydroxide (NaOH)) and physical (cement coating) methods. M30-grade concrete was used as a control mix, and crumb rubber (CR) was added by replacing a portion of the fine aggregate. In order to mitigate the strength reduction, silica fume and polypropylene fibers were added. An optimal mix was determined using Taguchi’s L9 orthogonal array, by varying proportions of crumb rubber, silica fume (SF), and polypropylene (PP) fiber. The ideal mix contained 10% CR, 5% SF, and 0.2% PP fiber based on compressive strength. Specimens were cured for 28 days and exposed to temperatures of 200 °C, 400 °C, 600 °C, and 800 °C for 1 h. Mechanical properties such as compressive strength, split tensile strength, and modulus of elasticity were evaluated, along with an ultrasonic pulse velocity test. The results indicate that treated crumb rubber enhances bonding, improving the mechanical and thermal performance of rubberized concrete under high temperature. Full article

The implementation and application of a safety factor (SF)-based numerical framework in FLAC3D-IMASS (Itasca Model for Advanced Strain Softening) is presented for the evaluation of the short-term stability of unsupported underground excavations in sedimentary rock masses during pillar recovery in bord-and-pillar mining. The stability of underground openings during the initial hours post-excavation must be ensured, as they are not accessed thereafter; therefore, short-term stability assessment is essential. The framework was specifically calibrated to field observations and applied to a case study from an Australian bord-and-pillar mine, focusing on plunge and bellout configurations commonly used during the pillar extraction stage to enhance ore recovery. The modelling approach was integrated with rock mass degradation behavior under static loading conditions and was used to calculate three-dimensional distributions of SF to identify potential failure zones. The results demonstrate that the coal (CO) roof scenario generally maintains structural stability, while the impure coal (Cox) roof scenario is observed to exhibit significant instability, particularly at greater excavation advancement. Among the tested bellout geometries, 8.0 m spans were observed to provide improved performance due to shorter tunnel lengths that enhance confinement and reduce the volume of disturbed rock. Overall, the proposed SF framework effectively captures localized failure mechanisms and is demonstrated as a practical design tool for assessing the short-term stability of unsupported structures during critical stages of underground mining operations. Full article

This research investigates the influence of incorporating perlite aggregate and silica fume on the properties of cement mortar, with a focus on compressive strength, flexural strength, density, water absorption, and thermal conductivity. The results show that increasing the percentage of perlite (Pe) in the mixes causes a marked reduction in the compressive strength, reflecting the lightweight nature and low density of perlite. For mixes with Pe-20% through Pe-100%, the compressive strength decreased by up to 78% compared to the reference mix. However, the addition of silica fume (SF) in mixes with SF-20% to SF-100% partially offset this effect, limiting the strength losses to 18–71%, which indicates that silica fume contributes to strength enhancement over time. The flexural strength followed a similar trend, decreasing with a higher perlite content: reductions of up to 40% were observed for Pe mixtures, while SF mixes showed slightly smaller decreases, reaching 36%. The density also declined consistently with increasing perlite replacement, with a maximum reduction of 57% in mix Pe-100% due to the inherent porosity of perlite. The water absorption increased substantially in the same mix (Pe-100%), by 327% compared to the reference one, whereas the addition of silica fume (SF-100%) limited the increase to 181%, confirming its role in refining the pore structure. The thermal conductivity decreased with a higher perlite content, attributed to the formation of voids in the matrix. The lowest value was observed for Pe-100%, with an 82% reduction, while silica fume mixes also showed reductions of 37–81% relative to the reference mix. Based on a comprehensive evaluation of strength, density, water absorption, and thermal performance, mix SF-60% was identified as the optimal mixture, offering a balanced profile with a compressive strength of 4.4 MPa, thermal conductivity of 0.28 W/(m·K), and density of 1089 kg/m³. These performance levels make the developed mortars particularly suitable for non-load-bearing masonry units, lightweight blocks, and insulation panels, where reduced weight and enhanced thermal efficiency are essential. The study therefore provides practical guidance for the design of sustainable, lightweight mortars for energy-efficient construction applications. Full article

Potato above-ground biomass (AGB) and tuber yield estimation remain challenging due to the subjectivity of farmer-based assessments, the high data requirements of spectral analysis methods, and the sensitivity of traditional Structure from Motion (SfM) techniques to soil elevation variability. To address these challenges, this study proposes a novel UAV-based visible-light remote sensing framework to estimate the AGB and predict the tuber yield of potato crops. First, a new vegetation index, the Green-Red Combination Vegetation Index (GRCVI), was developed to improve the separability between vegetation and non-vegetation pixels. Second, an improved single-period SfM method was designed to mitigate errors in canopy height estimation caused by terrain variations. Fractional vegetation coverage (FVC) and plant height (PH) derived from UAV imagery were then integrated into a feedforward neural network (FNN) to predict AGB. Finally, potato tuber yield was predicted using polynomial regression based on AGB. Results showed that GRCVI combined with the numerical intersection method and SVM classification achieved FVC extraction accuracy exceeding 95%. The improved SfM method yielded canopy height estimates with R² values ranging from 0.8470 to 0.8554 and RMSE values below 2.3 cm. The AGB estimation model achieved an R² of 0.8341 and an RMSE of 19.9 g, while the yield prediction model obtained an R² of 0.7919 and an RMSE of 47.0 g. This study demonstrates the potential of UAV-based visible-light imagery for cost-effective, non-destructive, and scalable monitoring of potato growth and yield, providing methodological support for precision agriculture and high-throughput phenotyping. Full article

Three-dimensional (3D) reconstruction technology is not only a core and key technology in computer vision and graphics, but also a key force driving the flourishing development of many cutting-edge applications such as virtual reality (VR), augmented reality (AR), autonomous driving, and digital earth. With the rise in novel view synthesis technologies such as Neural Radiation Field (NeRF) and 3D Gaussian Splatting (3DGS), 3D reconstruction is facing unprecedented development opportunities. This article introduces the basic principles of traditional 3D reconstruction methods, including Structure from Motion (SfM) and Multi View Stereo (MVS) techniques, and analyzes the limitations of these methods in dealing with complex scenes and dynamic environments. Focusing on implicit 3D scene reconstruction techniques related to NeRF, this paper explores the advantages and challenges of using deep neural networks to learn and generate high-quality 3D scene rendering from limited perspectives. Based on the principles and characteristics of 3DGS-related technologies that have emerged in recent years, the latest progress and innovations in rendering quality, rendering efficiency, sparse view input support, and dynamic 3D reconstruction are analyzed. Finally, the main challenges and opportunities faced by current 3D reconstruction technology and novel view synthesis technology were discussed in depth, and possible technological breakthroughs and development directions in the future were discussed. This article aims to provide a comprehensive perspective for researchers in 3D reconstruction technology in fields such as digital twins and smart cities, while opening up new ideas and paths for future technological innovation and widespread application. Full article

Co-electrolysis of CO₂ and H₂O offers a promising route for efficient and controllable syngas production from greenhouse gases and water. However, the atomic-scale reaction mechanism remains elusive, especially on complex oxide surfaces. In this study, we employ density functional theory (DFT) to investigate the adsorption and activation of CO₂ and H₂O on the FeMoO-terminated (001) surface of Sr₂Fe_1.5Mo_0.5O₆ (SFM), a double perovskite of growing interest for solid oxide electrolysis. Our results show that CO₂ strongly interacts with surface lattice oxygen, adopting a bent configuration with substantial charge transfer. In contrast, H₂O binds more weakly at Mo sites through predominantly electrostatic interactions. Co-adsorption analyses reveal a bidirectional interplay: pre-adsorbed H₂O enhances CO₂ binding by altering its adsorption geometry, whereas pre-adsorbed CO₂ weakens H₂O adsorption due to competitive site occupation. This balance suggests that moderate co-adsorption may facilitate proton–electron coupling, while excessive coverage of either species suppresses activation of the other. Bader charge analysis, charge density differences, and projected density of states highlight the key role of Fe/Mo–O hybridized states near the Fermi level in mediating surface reactivity. These results, obtained for a perfect defect-free surface, provide a theoretical benchmark for disentangling intrinsic molecule–surface and molecule–molecule interactions, and offer guidance for designing high-performance perovskite electrocatalysts for CO₂ + H₂O co-electrolysis. Full article

Healthcare professionals (HCPs) working in paediatric settings are routinely exposed to respiratory pathogens, increasing their risk of asymptomatic colonisation by meningitis-associated bacteria. This study is the first to assess oropharyngeal and nasopharyngeal carriage of major bacterial meningitis pathogens among paediatric HCPs in Benin, and to identify associated risk factors. A cross-sectional analytical study was conducted in nine hospitals between 1 September 2023 and 30 September 2024. Data collection involved a structured questionnaire and paired oropharyngeal and nasopharyngeal swabs. Culture-based identification and antimicrobial susceptibility testing were performed according to CA-SFM guidelines. By culture method, Streptococcus pneumoniae was the most frequently isolated pathogen, mainly from oropharyngeal samples (47.5%). Most of these strains exhibited multidrug resistance. In nasopharyngeal samples analysed by real-time PCR, detection rates for S. pneumoniae were markedly higher (24.4%) compared to culture (5.0%), highlighting the limited sensitivity of conventional methods in detecting asymptomatic carriage. Pneumococcal colonisation was significantly associated with recent respiratory tract infections, and residence in high-risk areas (p < 0.05). These findings underscore the need for enhanced molecular surveillance, along with strengthened infection control measures and targeted vaccination strategies, to mitigate the risk of horizontal transmission in paediatric wards. Full article

Introduction: Mild traumatic brain injury (mTBI) in older adults (≥65 years) is often underestimated, despite being associated with significant morbidity. Age-related vulnerability, comorbidities, and medication use may exacerbate outcomes. This study aimed to identify predictors of brain health and functional recovery in older adults following mTBI, focusing on acute symptoms, CT imaging findings, and sociodemographic factors. Methods: We analyzed a cohort of 93 older adult patients with mTBI (GCS 13–15) who were prospectively enrolled at a tertiary neurosurgical center. All patients underwent baseline CT, structured clinical assessment, and follow-up at six months with standardized instruments (Glasgow Outcome Scale–Extended-GOSE, 12-Item Short Form Health Survey (quality-of-life measure)-SF-12, Rivermead Post-Concussion Symptoms Questionnaire-RPQ, Patient Health Questionnaire-9 (depression measure)-PHQ-9, PTSD (Post Traumatics Stress Disorder) Checklist for DSM (Diagnostic and Statistical Manual for Mental Disorders)-PCL-5, Timed up and Go Test (mobility measure-TUG test). Multivariate regression was performed to identify independent predictors of recovery. Results: At six months, 94.9% of older adults achieved functional independence (GOSE ≥ 5), though only 43% attained complete recovery (GOSE = 8). Patients with acute intracranial lesions on CT had worse physical outcomes, including slower mobility (mean TUG 17.6 vs. 16.3 s, p = 0.012). Severe acute headache independently predicted poorer recovery (lower GOSE and SF-12 PCS). Lower educational attainment correlated with worse functional and quality-of-life outcomes, consistent with reduced cognitive reserve. Psychological outcomes (PTSD and depression rates) were not associated with CT findings but were influenced by social support and sex. Prompt anticoagulation reversal in patients on anticoagulants markedly reduced hemorrhagic complications. Discussion: Older adults with mTBI generally maintain independence but experience reduced physical health and mobility compared to younger patients. Predictors of poorer outcomes include severe acute symptoms, CT-detected lesions, advanced age, and lower educational levels. Psychosocial support mitigated mental health complications. Conclusions: mTBI in older adults is not benign. Clinical, imaging, and sociodemographic factors collectively shape recovery. Early identification of high-risk patients and targeted interventions are essential to preserve brain health and independence in this growing population. Full article

This study proposes a novel structural deflection measurement method using a single smartphone with an innovative scale factor (SF) calibration technique, eliminating reliance on laser rangefinders and industrial cameras. Conventional off-axis digital image correlation (DIC) techniques require laser rangefinders to measure discrete points for SF calculation, suffering from high hardware costs and sunlight-induced ranging failures. The proposed approach replaces physical ranging by deriving SF through geometric relationships of known structural dimensions (e.g., bridge length/width) within the measured plane. A key innovation lies in developing a versatile SF calibration framework adaptable to varying numbers of reference dimensions: a non-optimized calculation integrates smartphone gyroscope-measured 3D angles when only one dimension is available; a local optimization model with angular parameters enhances accuracy for 2–3 known dimensions; and a global optimization model employing spatial constraints achieves precise SF resolution with ≥4 reference dimensions. Indoor experiments demonstrated sub-0.05 m ranging accuracy and deflection errors below 0.30 mm. Field validations on Beijing Subway Line 13′s bridge successfully captured dynamic load-induced deformations, confirming outdoor applicability. This smartphone-based method reduces costs compared to traditional setups while overcoming sunlight interference, establishing a hardware-adaptive solution for vision-based structural health monitoring. Full article

Accurate stockpile volume estimation is essential for industries that manage bulk materials across various stages of production. Conventional ground-based methods such as walking wheels, total stations, Global Navigation Satellite Systems (GNSSs), and Terrestrial Laser Scanners (TLSs) have been widely used, but often involve significant safety risks, particularly when accessing hard-to-reach or hazardous areas. Unmanned Aerial Systems (UASs) provide a safer and more efficient alternative for surveying irregularly shaped stockpiles. This study evaluates UAS-based methods for estimating the volume of coal stockpiles at a storage facility near Cadiz, Ohio. Two sensor platforms were deployed: a Freefly Alta X quadcopter equipped with a Real-Time Kinematic (RTK) Light Detection and Ranging (LiDAR, active sensor) and a WingtraOne UAS with Post-Processed Kinematic (PPK) multispectral imaging (optical, passive sensor). Three approaches were compared: (1) LiDAR; (2) Structure-from-Motion (SfM) photogrammetry with a Digital Surface Model (DSM) and Digital Terrain Model (DTM) (SfM–DTM); and (3) an SfM-derived DSM combined with a kriging-interpolated DTM (SfM–intDTM). An automated boundary detection workflow was developed, integrating slope thresholding, Near-Infrared (NIR) spectral filtering, and Canny edge detection. Volume estimates from SfM–DTM and SfM–intDTM closely matched LiDAR-based reference estimates, with Root Mean Square Error (RMSE) values of 147.51 m³ and 146.18 m³, respectively. The SfM–intDTM approach achieved a Mean Absolute Percentage Error (MAPE) of ~2%, indicating strong agreement with LiDAR and improved accuracy compared to prior studies. A sensitivity analysis further highlighted the role of spatial resolution in volume estimation. While RMSE values remained consistent (141–162 m³) and the MAPE below 2.5% for resolutions between 0.06 m and 5 m, accuracy declined at coarser resolutions, with the MAPE rising to 11.76% at 10 m. This emphasizes the need to balance the resolution with the study objectives, geographic extent, and computational costs when selecting elevation data for volume estimation. Overall, UAS-based SfM photogrammetry combined with interpolated DTMs and automated boundary extraction offers a scalable, cost-effective, and accurate approach for stockpile volume estimation. The methodology is well-suited for both the high-precision monitoring of individual stockpiles and broader regional-scale assessments and can be readily adapted to other domains such as quarrying, agricultural storage, and forestry operations. Full article

Objectives: Accumulating clinical evidence from experimental and observational studies with humans suggests that edible mushrooms may have beneficial effects on markers of brain health. This study examined the effects of daily consumption of fresh Agaricus bisporus (cremini mushrooms) exposed to ultraviolet (UV) light on indices of anxiety, depression, mood, cognitive function, and well-being in middle-aged and older adults. Methods: Over a 6-week period, adults (n = 41 (19 M/22 F), age 43 ± 11 y; BMI 29.8 ± 5.9 kg/m², mean ± SD) without severe depression, cardiovascular disease, or Type 2 Diabetes consumed two daily servings (168 g/d wet weight) of cremini mushrooms intended to provide 400 IU/serving (800 IU/d) of vitamin D₂ (n = 20) or 2 tsp/d of breadcrumbs (control, n = 21). Assessments conducted at baseline and week 6 included General Anxiety Disorder-7 (GAD-7), Beck’s Depression Inventory (BDI-II), Patient Health Questionnaire (PHQ-9), Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), Profile of Mood States (POMS), and Medical Outcomes Study 36-Item Short-Form Health Survey Version 2 (SF36v2). Results: Consuming UV light-exposed mushrooms did not improve brain health outcomes. Independent of mushroom consumption, over time, there were improvements in immediate memory (RBANS), language (RBANS), and depression (BDI-II and PHQ-9). Conclusions: There were no differences observed between groups in the investigated indices of brain health. However, improvements over time were observed in Beck’s Depression Inventory and the Immediate Memory and Language domains in the RBANS, independent of mushroom consumption. Overall, consuming 2 servings/d of UV-exposed mushrooms for six weeks may not improve indices of brain health. Full article