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Depth information is crucial for perceiving three-dimensional scenes. However, depth maps captured directly by depth sensors are often incomplete and noisy, our objective in the depth-completion task is to generate dense and accurate depth maps from sparse depth inputs by fusing guidance information from corresponding color images obtained from camera sensors. To address these challenges, we introduce transformer models, which have shown great promise in the field of vision, into the task of image-guided depth completion. By leveraging the self-attention mechanism, we propose a novel network architecture that effectively meets these requirements of high accuracy and resolution in depth data. To be more specific, we design a dual-branch model with a transformer-based encoder that serializes image features into tokens step by step and extracts multi-scale pyramid features suitable for pixel-wise dense prediction tasks. Additionally, we incorporate a dual-attention fusion module to enhance the fusion between the two branches. This module combines convolution-based spatial and channel-attention mechanisms, which are adept at capturing local information, with cross-attention mechanisms that excel at capturing long-distance relationships. Our model achieves state-of-the-art performance on both the NYUv2 depth and SUN-RGBD depth datasets. Additionally, our ablation studies confirm the effectiveness of the designed modules. [ABSTRACT FROM AUTHOR]

Suspension drying, a non-contact drying method, enables simultaneous drying on both sides of the electrodes, thereby meeting the demand for efficient and high-quality production. This study introduces a fluid–structure coupling simulation model, developed based on force balance analysis during the suspension drying process. The model is designed to explore the parameters that facilitate stable levitation at the equilibrium position. Further investigation, based on the conditions for stable electrode levitation, examines the factors influencing the extent of flexible deformation in the electrodes. The results indicate that to achieve stable suspension during drying, the fluid flow rate at the lower nozzle must exceed that at the upper nozzle by about 6.5% to balance the load on the electrodes. Notably, when the coating areal density is increased from 100 to 500 g/m2, a corresponding increase in the lower nozzle wind speed is required to maintain equilibrium. Moreover, a predictive relational equation has been established for the maximum flexible deformation of the electrode in the y-direction under various working conditions and tensile forces. Specifically, at an areal density of 200 g/m2, a tensile force exceeding 70.00 N is sufficient to limit the maximum deformation to less than 6.00 mm, thus preventing nozzle contact and defects. This equation provides valuable theoretical guidance for the practical application of stable suspension drying in lithium-ion battery electrode manufacturing, facilitating process optimization and enhancing product quality. [ABSTRACT FROM AUTHOR]

The development of a sparse-invariant depth completion model capable of handling varying levels of input depth sparsity is highly desirable in real-world applications. However, existing sparse-invariant models tend to degrade when the input depth points are extremely sparse. In this paper, we propose a new model that combines the advantageous designs of depth completion and monocular depth estimation tasks to achieve sparse invariance. Specifically, we construct a dual-branch architecture with one branch dedicated to depth prediction and the other to depth completion. Additionally, we integrate the multi-scale local planar module in the decoders of both branches. Experimental results on the NYU Depth V2 benchmark and the OPPO prototype dataset equipped with the Spot-iToF316 sensor demonstrate that our model achieves reliable results even in cases with irregularly distributed, limited or absent depth information. [ABSTRACT FROM AUTHOR]

The drying process of porous medium electrodes is crucial for optimizing the performance of lithium-ion batteries. Among various drying methods, convection drying has been proven to be an effective double-sided and contactless technique for these electrodes, enhancing manufacturing quality and efficiency. This study investigates the impact of different drying parameters on the drying process of porous medium electrodes by establishing a coupling model for convective drying. The particle swarm algorithm optimized the drying parameters to minimizing drying time and energy consumption. As a result of this optimization, the optimal drying temperature and Reynolds number were found to be 104.77 °C and 3082.55, respectively. Furthermore, implementing a multi-stage drying process effectively prevents internal binder migration within the porous medium and ensures even distribution of components, thereby enhancing electrode performance. This study examines the effects of different multi-stage drying schemes on the drying time and energy consumption of porous medium electrodes based on the optimal drying parameters. The optimal multi-stage drying scheme, characterized by temperature profiles of 104.77 (0–15 s) − 90 (15–44 s) − 104.77 (>44 s) °C, was proposed to achieve both reduced drying time and low energy consumption. With this scheme, the drying process of porous medium electrodes achieved a suitable drying time of 137.50 s and a low energy consumption of 285 110.09 kJ/m3. The proposed model explores the drying process and provides valuable theoretical guidance for establishing appropriate drying parameters in the actual production of lithium-ion battery electrodes. [ABSTRACT FROM AUTHOR]

Ureteral obstruction caused by extrinsic compression from advanced pelvic malignancies are not unusual in urology, with gynecological origin being the most common. As minimally invasive treatments for malignant ureteral obstruction (MUO), metallic ureteral stents have been promoted to provide long-lasting urinary patency and overcome the inherent limits of traditional double-J stents. In this review, we demonstrated three types of frequently used metal stents, including coiled stents, self-expendable stents and thermo-expendable stents. The Wallstent presented discrepant patency rates ranging from 6% to 100%, along with a high occlusion rate. The Memokath 051 stent showed satisfactory patency rates, often > 90%, but also a specific higher migration rate. The Resonance stent provided overall promising results with published success rates ranging from 20% to 100%, which on the whole remains relatively high. The long-term effectiveness rendered metal stents as viable options for managing MUO. [ABSTRACT FROM AUTHOR]

In this paper, we study Galerkin finite element methods for a class of higher dimensional multi-term fractional diffusion equations. The finite difference approximation of Caputo derivative on non-uniform meshes is used in temporal direction and Galerkin finite element method is used in spatial direction. We prove that semi-discrete and fully discrete finite element schemes are unconditionally stable. Meanwhile,-norm convergence properties of the two schemes are proved rigorously. To confirm our theoretical analysis, we give some numerical examples in both two-dimensional (2D) and three-dimensional (3D) spaces. Finally, a moving local refinement technique in temporal direction is used to improve the accuracy of numerical solution. [ABSTRACT FROM AUTHOR]

In this work, we propose two classes of two-step Milstein-type schemes : the double-implicit Milstein scheme and the split two-step Milstein scheme, to solve stochastic differential equations (SDEs). Our results reveal that the two new schemes are strong convergent with order one. Moreover, with a restriction on stepsize, these two schemes can preserve the exponential mean square stability of the original SDEs, and the decay rate of numerical solution will converge to the decay rate of the exact solution. Numerical experiments are performed to confirm our theoretic findings. [ABSTRACT FROM AUTHOR]

Introduction: Chronic kidney disease(CKD) is a global medical problem. Serum methylmalonic acid(MMA) is a serum marker associated with many diseases. This study aimed to investigate the association between MMA and CKD., Methods: Data from the National Health and Nutrition Examination Survey (NHANES) 2013-2014 were downloaded and analyzed. The association between MMA and CKD was confirmed by using multiple logistic regression modeling. The smooth curve fitting method was used to investigate the nonlinear relationship between them. Subgroup analyses and interaction tests were used to verify the stability of the association between different subgroups. Threshold effect analysis was used to determine the optimal control point for MMA., Results: There was a unique W-shaped nonlinear relationship between MMA and the risk of CKD, with a positive correlation between them (OR=1.66,95% CI:1.27, 2.17; P=0.0002). As the stage of CKD progressed, MMA levels increased. Age, hypertension, and serum vitamin B 12 had significant influences on the association between MMA and the risk of CKD., Conclusion: Our findings revealed that serum MMA accumulation was positively associated with the risk of CKD. Serum MMA level may be a novel index to predict the development and course of CKD. This study may help in the early identification of people at risk for chronic kidney disease and provide new ideas and approaches for prevention and treatment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhang, Lv, Guan, Jiang, He, Song, Sun, Jiang and Tian.)

Purpose: This study aimed to clarify the expression of a gene associated with Retinoid- Interferon-Induced Mortality-19 (GRIM-19) in Upper Urinary Tract Urothelial Carcinoma (UUTUC) and its prognostic significance for UUTUC patients., Materials and Methods: Immunohistochemical (IHC) staining was used to determine the GRIM-19 expression in 70 paired samples. Progression-Free Survival (PFS) and Cancer-Specific Survival (CSS) were assessed using the Kaplan-Meier method. The independent prognostic factors for PFS and CSS were analyzed by multivariable Cox regression models., Results: IHC staining showed that GRIM-19 expression was significantly decreased in UUTUC, and its cellular location changed from being both cytoplasmic and nuclear to only cytoplasmic. Kaplan- Meier analysis revealed that the patients with tumors expressing low GRIM-19 had a significantly higher risk for tumor progression (P = 0.002) and cancer-specific mortality (P < 0.001) compared to those with high GRIM-19 levels. The Cox regression showed that both GRIM-19 expression (P = 0.025) and lymph node metastasis (LN) (P = 0.007) were independent predictors of progression in the muscle-invasive (MIC) subgroup. GRIM-19 expressions (entire cohort: P = 0.011; MIC subgroup: P = 0.025), LN (entire cohort: P = 0.019; MIC subgroup: P = 0.007), and progression (entire cohort: P < 0.001; MIC subgroup: P < 0.001) were independent predictors of cancer-specific survival., Conclusion: Low expression of GRIM-19 in patients with UUTUC had significantly shorter PFS or CSS compared to those with high GRIM-19-expressing tumors. High GRIM-19 expression was also strongly associated with longer PFS in MIC patients. It indicates that GRIM-19 might serve as a promising prognostic biomarker for UUTUC patients., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)