Stress triggering mechanism of strong mine earthquake in huge thick strata revealed by inversion of joint source rupture information by Yao YANG, Anye CAO, Yaoqi LIU, Xianxi BAI, Changbin WANG, Chengchun XUE, Qiang WANG

“…In order to solve the problem of inaccurate source information and unclear stress triggering mechanism, which makes it difficult to prevent and control SME, the working face of a mine in the area where SME occurred frequently is used as a background for the study, based on preliminary detection of stratigraphic rock movement characteristics, the principal component analysis (PCA) was applied to extract the effective components of waveforms, the hybrid moment tensor inversion (HMTI) are used to solve focal mechanism of SME, stress inversion model modified, and stress inversion algorithm optimised, based on the algorithm, solved the distribution characteristics of the stress field before and after the occurrence of SME, introduced instability coefficients to evaluate the stability of the overburden, and analysed the stress triggering mechanism of SME. …”
Get full text

RED-Net: A Neural Network for 3D Thyroid Segmentation in Chest CT Using Residual and Dilated Convolutions for Measuring Thyroid Volume by Min-Ji Kim, Jin-A Kim, Naae Kim, Yul Hwangbo, Hyun Jeong Jeon, Dong-Hwa Lee, Ji Eun Oh

“…The results showed that it achieved state-of-the-art performance with a Dice similarity coefficient of 0.8901.…”
Get full text

GPU Ray Tracing for the Analysis of Light Deflection in Inhomogeneous Refractive Index Fields of Hot Tailored Forming Components by Pascal Kern, Max Brower-Rabinowitsch, Lennart Hinz, Markus Kästner, Eduard Reithmeier

“…Although hybrid components are key to meeting modern technical requirements and saving resources, they exhibit complex shrinkage behavior due to differing thermal expansion coefficients. …”
Get full text

Assessment of seasonal soil moisture forecasts over the Central Mediterranean by L. Silvestri, M. Saraceni, B. Brunone, S. Meniconi, G. Passadore, P. Bongioannini Cerlini

“…These regions correspond to those with the largest memory timescale of soil moisture and do not exhibit a complex orography. The obtained results show that seasonal forecasts are useful to detect wet and dry events for the deepest soil layer in the mentioned regions, with lead times of up to 6 months. …”
Get full text

Spatial Gap-Filling of Himawari-8 Hourly AOD Products Using Machine Learning with Model-Based AOD and Meteorological Data: A Focus on the Korean Peninsula by Youjeong Youn, Seoyeon Kim, Seung Hee Kim, Yangwon Lee

“…Given the complex spatiotemporal variability of aerosols, high-frequency satellite observations are essential for accurately mapping their distribution. …”
Get full text

Molecular Layering Synthesis and Investigation of Nanostructured Oxide Layers in High Aspect Ratio Substrates by A. P. Baraban, V. A. Dmitriev, A. V. Drozd, V. A. Moshnikov

“…The MCP structures containing aluminum oxide layers obtained by ML technology were experimentally tested to detect beam collisions (FBBC) for work in detectors at the NICA accelerator complex. …”
Get full text

Comparative analysis using UPLC and UV methods for concurrent quantification of therapeutic drugs for overactive bladder: Effective approach in green and white chemistry by Asma S. Al-Wasidi, Mahmoud A. Mohamed, Hoda A. Ahmed, Manal A. Almalki, Alaa A. Ahmed-Anwar

“…The second method, UPLC densitometry, separates pharmaceuticals using a UPLC C18 1.7 µm (2.1 × 50 mm) column with Ethanol: phosphate buffer pH 4.2 (35:65 v/v) mobile phase at a 0.6 ml/min flow rate, detecting drugs at 210 nm. Calibration curves for both techniques showed a correlation coefficient greater than 0.999 for SOL and MIR in the 1–65 µg mL−1, 1–60 µg mL−1, and 5–25 µg mL−1, respectively. …”
Get full text

CSTFNet: A CNN and Dual Swin-Transformer Fusion Network for Remote Sensing Hyperspectral Data Fusion and Classification of Coastal Areas by Dekai Li, Harold Neira-Molina, Mengxing Huang, Syam M.S., Yu Zhang, Zhang Junfeng, Uzair Aslam Bhatti, Muhammad Asif, Nadia Sarhan, Emad Mahrous Awwad

“…In recent years, the convolutional neural network (CNN) framework and transformer models have demonstrated strong performance in HSI classification, especially in applications requiring precise change detection and analysis. However, due to the high dimensionality of HSI data and the complexity of spectral-spatial feature extraction, achieving accurate results in coastal areas remains challenging. …”
Get full text

Calculation Method of Phenotypic Traits for Tomato Canopy in Greenhouse Based on the Extraction of Branch Skeleton by Xiaodan Ma, Qiu Jiang, Haiou Guan, Lu Wang, Xia Wu

“…The experimental results show that the detection accuracies of branches and leaves were above 88% and 93%, respectively, and the coefficients of determination between the calculated and measured values of mean leaf inclination, digital biomass, and light penetration depth were 0.9419, 0.9612, and 0.9093, respectively. …”
Get full text

UAV LiDAR expands the understanding of forest tree diversity by Jianyang Liu, Ying Quan, Guoqiang Zhao, Baozhong Yuan, Bin Wang, Mingze Li

“…Recent studies have emphasized the importance of light detection and ranging (LiDAR) features in explaining tree diversity. …”
Get full text

Experimental and Numerical Study on the Vortical Flow of MULDICON Wing Configuration by Ibrahim Madan, Jiun-Jih Miau, Shabudin Bin Mat

“…This paper highlights the results and comparison of the flow topology investigation above the unmanned combat aerial vehicle (UCAV) configuration, namely, multidisciplinary design configuration (MULDICON), with modified leading-edge profile at the apex region from a sharp to a blunt profile to reduce the complexity of the flow structure above the wing. It was found from the flow visualization results that at a low angle of attack, for instance, 10°, the onset of the flow separation took place near the apex region; the onset of a tip vortex at the wing tip was also detected. …”
Get full text

Colorectal cancer unmasked: A synergistic AI framework for Hyper-granular image dissection, precision segmentation, and automated diagnosis by Akella S. Narasimha Raju, K. Venkatesh, M. Rajababu, Ranjith Kumar Gatla, Shaik Jakeer Hussain, G. Satya Mohan Chowdary, T. Ganga Bhavani, Mohammed Kareemullah, Sameer Algburi, Ali Majdi, Ahmed M. Abdulhadi, Wahaj Ahmad Khan

“…The DeepLabV3 + achieved segmentation state-of-the-art for tasks of localisation with 0.88 Dice Coefficient and 0.71 Intersection over Union (IoU), ensuring sharp delineation of areas that are malignant. …”
Get full text

CLINICAL MANIFESTATIONS, IMAGING FEATURES, AND TREATMENT FOLLOW-UP OF 29 CASES WITH HEPATIC TUBERCULOSIS by Saiduo, Wei, Jichan, Xinchun, Hongye, Ning, Xiangao Jiang

“…However, the lesions' apparent diffusion coefficient values reflected high signals. The Xpert MTB/RIF test detected Mycobacterium TB complex in the liver biopsy fluid from 10 patients. …”
Get full text

The assessment of magnesium-contained feed additive efficiency on nutrient digestibility and productivity in laying hens by O. S. Orishchuk, S. V. Tsap, R. V. Mylostyvyi, O. I. Chernenko, O. M. Chernenko

“…The most meaningful increase in egg production rate was detected in the groups exposed to 0.3% and 0.4% doses. …”
Get full text

Toward Adaptive Unsupervised and Blind Image Forgery Localization with ViT-VAE and a Gaussian Mixture Model by Haichang Yin, KinTak U, Jing Wang, Wuyue Ma

“…Despite their success, there are still some limitations: (1) A simple Gaussian distribution assumption in the latent space constrains performance due to the diverse distribution of forged images. (2) Gaussian Mixture Models (GMMs) introduce non-convex log-sum-exp functions in the Kullback–Leibler (KL) divergence term, leading to gradient instability and convergence issues during training. (3) Estimating GMM mixing coefficients typically involves either the expectation-maximization (EM) algorithm before VAE training or a multilayer perceptron (MLP), both of which increase computational complexity. …”
Get full text

LI-RADS-based hepatocellular carcinoma risk mapping using contrast-enhanced MRI and self-configuring deep learning by Róbert Stollmayer, Selda Güven, Christian Marcel Heidt, Kai Schlamp, Pál Novák Kaposi, Oyunbileg von Stackelberg, Hans-Ulrich Kauczor, Miriam Klauss, Philipp Mayer

“…Median per lesion Sørensen–Dice coefficients were between 0.61–0.74/0.52–0.77/0.84 (LR-5: 0.74/0.77/0.84). …”
Get full text

A deep neural network model with spectral correlation function for electrocardiogram classification and diagnosis of atrial fibrillation by Sara Mihandoost

“…The obtained results demonstrate that the proposed approach efficiently represents ECG signals through SCF coefficients, leading to the accurate detection of AF with an average accuracy of 92.76% and an average F1-score of 89.1%.…”
Get full text

Research and application of dynamic simulation method for water accumulation in goaf by Guijin BIAN

“…After the mining of the coal mining face is completed, the internal environment of the goaf formed is complex, and it is very difficult to accurately detect the range of accumulated water and calculate the amount of accumulated water. …”
Get full text

Intra- and Inter-Examiner Reliability of Kinovea for Hip Flexion Angle Measurement During Straight Leg Raise Test by Gabriel Rabanal-Rodríguez, Marcos José Navarro-Santana, Juan Antonio Valera-Calero, Ana Muñoz-Rodríguez, Elías Hernández-González, Gustavo Plaza-Manzano

“…Intra- and inter-examiner reliability were assessed using the Intraclass Correlation Coefficient (ICC), Standard Error of Measurement (SEM), and Minimal Detectable Change (MDC). …”
Get full text

Speckle Noise Removal in OCT Images via Wavelet Transform and DnCNN by Fangfang Li, Qizhou Wu, Bei Jia, Zhicheng Yang

“…The quality of OCT images is a crucial factor influencing diagnostic effectiveness, highlighting the importance of OCT image denoising. (2) Methods: The OCT image undergoes a Discrete Wavelet Transform (DWT) to decompose it into multiple scales, isolating high-frequency wavelet coefficients that encapsulate fine texture details. These high-frequency coefficients are further processed using a Shift-Invariant Wavelet Transform (SWT) to generate an additional set of coefficients, ensuring an enhanced feature preservation and reduced artifacts. …”
Get full text