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Observational data on ocean subsurface temperature and salinity are patently insufficient because in situ observations are complex and costly, while satellite remote-sensed measurements are abundant but mainly focus on sea surface data. To make up for the ocean interior data shortage and entirely use the abundant satellite data, we developed a data-driven deep learning model named Convformer to reconstruct ocean subsurface temperature and salinity fields from satellite-observed sea surface data. Convformer is designed by deeply optimizing Vision Transformer and ConvLSTM, consisting of alternating residual connections between multiple temporal and spatial attention blocks. The input variables consist of sea surface temperature (SST), sea surface salinity (SSS), sea surface height (SSH), and sea surface wind (SSW). Our results demonstrate that Convformer exhibits superior performance in estimating the temperature-salinity structure of the tropical Pacific Ocean. The all-depth average root mean square error (RMSE) of the reconstructed subsurface temperature (ST)/subsurface salinity (SS) is 0.353 °C/0.0695 PSU, with correlation coefficients (R²) of 0.98663/0.99971. In the critical thermocline, although the root mean square errors of ST and SS reach 0.85 °C and 0.121 PSU, respectively, they remain smaller compared to other models. Furthermore, we assessed Convformer's performance from various perspectives. Notably, we also delved into the potential of Convformer to extract physical and dynamic information from a model mechanism perspective. Our study offers a practical approach to reconstructing the subsurface temperature and salinity fields from satellite-observed sea surface data. [ABSTRACT FROM AUTHOR]

Estimating the intensity of tropical cyclones (TCs) is beneficial for preventing and reducing the impact of natural disasters. Most existing methods for estimating TC intensity utilize single-satellite or single-band remote sensing images, but they lack the ability to quantify the uncertainty of the estimation results. However, TC, as a typical chaotic system, often requires confidence intervals for intensity estimates in real-world emergency decision-making scenarios. Additionally, the use of multi-source image inputs contributes to the uncertainty of the model. Consequently, this study introduces a neural network (MTCIE) that utilizes multi-source satellite images to provide probabilistic estimates of TC intensity. The model utilizes infrared and microwave images from multiple satellites as inputs. It uses a dual-branch self-attention encoder to extract TC image features and provides uncertainty estimates for TC intensity. Furthermore, a dataset for estimating the intensity of multi-source TC remote sensing images (MTCID) is constructed through the registration of latitude, longitude, and time, along with data augmentation. The proposed method achieves a MAE of 7.42 kt in deterministic estimation, comparable to mainstream networks like TCIENet. In uncertain estimation, it outperforms methods like MC Dropout in the PICP metric, providing reliable probability estimates. This supports TC disaster emergency decision making, enhancing risk mitigation in real-world applications. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) materials, characterized by their atomically thin nature and exceptional properties, hold significant promise for future nano-electronic applications. The precise control of carrier density in these 2D materials is essential for enhancing performance and enabling complex device functionalities. In this study, we present an electron-beam (e-beam) doping approach to achieve controllable carrier doping effects in graphene and MoS2 field-effect transistors (FETs) by leveraging charge-trapping oxide dielectrics. By adding an atomic layer deposition (ALD)-grown Al2O3 dielectric layer on top of the SiO2/Si substrate, we demonstrate that controllable and reversible carrier doping effects can be effectively induced in graphene and MoS2 FETs through e-beam doping. This new device configuration establishes an oxide interface that enhances charge-trapping capabilities, enabling the effective induction of electron and hole doping beyond the SiO2 breakdown limit using high-energy e-beam irradiation. Importantly, these high doping effects exhibit non-volatility and robust stability in both vacuum and air environments for graphene FET devices. This methodology enhances carrier modulation capabilities in 2D materials and holds great potential for advancing the development of scalable 2D nano-devices. [ABSTRACT FROM AUTHOR]

In underground coal mines, the stability of the retracement channel in the surrounding rock is crucial for the safe and efficient retracement of the equipment and to guarantee the continuity of the retracement work. To reveal the deformation and damage mechanism of the surrounding rock of an auxiliary retracement channel (ARC) and the determination method for the reasonable spacing of two retracement channels during the end of the mining period, the deviatoric stress field in front of the working face and the change in the shape characteristics of the plastic zone in the ARC are investigated in this paper. The formation of ultimate stress equilibrium, high deviatoric stress, decreasing deviatoric stress, and low deviatoric stress environments in front of the working face during the end of mining occur successively, and the different deviatoric stress environments are the main reasons for the different shape characteristics of the plastic zone in the surrounding rock. The changes in the shape characteristics of the plastic zone correspond to the changes in the shape characteristics in the zone with deviatoric stress and exhibit the following order: full plastic deformation zone, butterfly-shaped zone, elliptical zone, and circular plastic zone. A reasonable spacing determination method for the two retracement channels is proposed: the ARC is arranged in the decreasing deviatoric stress environment, where the surrounding rock plastic zone shape is elliptical, and the ARC is relatively stable. Based on this research result, the spacing of the double retracement channels at the Lijiahao 22-116 working face was determined to be 25 m, which achieved a positive application effect and allowed the safe and efficient retracement of the working face equipment. [ABSTRACT FROM AUTHOR]

Directed at the problems of low positioning accuracy and irregular section forming of cutting heads of road header in coal mine production sites, a new cutting head positioning system based on ultra-wideband positioning technology is proposed based on the cutting head motion model and the working principle of ultra-wideband positioning technology, which verifies the anti-interference and the accuracy of its positioning. Combined with the simulation experiment under on-site working conditions, the influence degree of three typical influencing factors on positioning accuracy was obtained, and the accuracy optimization of the ultra-wideband positioning system was guided. Through the dynamic solution experiment, the positioning accuracy of the system is measured, and the results are verified based on the positioning system solution accuracy evaluation standard. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the efficacy of balloon dilation in ureteral stricture and to analyze the risk factors for the failure of balloon dilation, which will hopefully provide some reference for clinicians to develop treatment plans. We retrospectively analyzed 196 patients who underwent balloon dilation between January 2012 and August 2022, 127 of whom had complete baseline and follow-up data. General clinical data, perioperative data, balloon parameters at the time of surgery, and follow-up results were collected from the patients. Univariate and multivariate logistic regression analyses were performed for the risk factors for surgical failure in patients undergoing balloon dilatation. The success rates of balloon dilatation (n = 30) and balloon dilatation combined with endoureterotomy (n = 37) for lower ureteral stricture at 3 months, 6 months, and 1 year were 81.08%, 78.38%, and 78.38% and 90%, 90%, and 86.67%, respectively. The success rates of balloon dilation at 3 months, 6 months, and 1 year in patients with recurrent upper ureteral stricture after pyeloplasty (n = 15) and primary treatment (n = 30) were 73.33%, 60%, and 53.33% and 80%, 80%, and 73.33%, respectively. The success rates of surgery at 3 months, 6 months, and 1 year for patients with recurrence of lower ureteral stricture after ureteral reimplantation or endoureterotomy (n = 4) and primary treatment with balloon dilatation (n = 34) were 75%, 75%, and 75% and 85.29%, 79.41%, and 79.41%, respectively. Multivariate analysis of the failure of balloon dilation showed that balloon circumference and multiple ureteral strictures were risk factors for balloon dilation failure (OR = 0.143, 95% CI: 0.023–0.895, p = 0.038; OR = 1.221, 95% CI: 1.002–1.491, p = 0.05). Balloon dilation combined with endoureterotomy in lower ureteral stricture had a higher success rate than balloon dilation alone. The success rate of balloon dilation in the primary treatment of the upper and lower ureter was higher than that of balloon dilation in the secondary treatment after failed repair surgery. Balloon circumference and multiple ureteral strictures are risk factors for balloon dilation failure. [ABSTRACT FROM AUTHOR]

The ionosphere serves as a critical medium for radio signal propagation in outer space. A good morphology of the global TEC distribution is very useful for both ionospheric studies and their relative applications. In this work, a deep learning framework was constructed for better spatial estimation in ionospheric TEC. Both the DCGAN and WGAN-GP were considered, and their performances were evaluated with spatial completion for a regional TEC. The performances were evaluated using the correlation coefficient, RMSE, and MAE. Moreover, the IAAC rapid products were used to make comparisons. The results show that both the DCGAN and WGAN-GP outperformed the IAAC CORG rapid products. The spatial TEC estimation clearly goes well with the solar activity trend. The RMSE differences had a maximum of 0.5035 TECu between the results of 2009 and 2014 for the DCGAN and a maximum of 0.9096 TECu between the results of 2009 and 2014 for the WGAN-GP. Similarly, the MAE differences had a maximum of 0.2606 TECu between the results of 2009 and 2014 for DCGAN and a maximum of 0.3683 TECu between the results of 2009 and 2014 for WGAN-GP. The performances of the CORG, DCGAN, and WGAN-GP were also verified for two selected strong geomagnetic storms in 2014 and 2017. The maximum RMSEs were 1.8354 TECu and 2.2437 TECu for the DCGAN and WGAN-GP in the geomagnetic storm on 18 February 2014, respectively, and the maximum RMSEs were 1.3282 TECu and 1.4814 TECu in the geomagnetic storm on 7 September 2017. The GAN-based framework can extract the detailed features of spatial TEC daily morphologies and the responses during geomagnetic storms. [ABSTRACT FROM AUTHOR]

Background and Objectives: To clinically validate the computed tomography (CT)-based three-dimension (3D) model for treatment planning and intraoperative navigation of ureteropelvic junction obstruction (UPJO) complicated with renal calculi. Materials and Methods: We retrospectively collected the data of 26 patients with UPJO and renal calculi who were surgically treated in our institution from January 2019 to December 2021. Before surgery, 3D models based on preoperative CT scans were constructed in all patients. Additionally, the patients were divided into three groups according to the results of 3D models, distinguished by different treatment of renal calculi, that is, left untreated (1), pyelolithotomy (2), and endoscopic lithotomy (3). The quantitative analysis of renal calculi parameters, and perioperative and follow-up data were compared. Results: The mean number of involved renal calyces (p = 0.041), and the mean maximum cross-sectional area (p = 0.036) of renal stones were statistically different among the three groups. There were no significant differences among the three groups in the mean operative time, mean estimated blood loss, mean pararenal draining time, and mean hospital stay. The intraoperative stone clearance rates were 100% (11/11) and 77.8% (7/9) in group 2 and group 3, respectively. The trends of increased estimated glomerular filtration rate and decreased creatinine on the average levels after surgery were observed, although these changes were not statistically significant. At a mean follow-up of 19.4 ± 6.4 months, the overall surgical success rate of the UPJO was 96.2% (25/26), and the overall success rate of renal calculi removal was 80.8% (21/26). Renal stones in 66.7% (4/6) of patients in group 1 spontaneously passed out. Conclusions: Preoperative 3D CT models have exact clinical value in the surgical planning and intraoperative navigation of UPJO patients complicated with renal calculi. [ABSTRACT FROM AUTHOR]