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To address the issues of image feature insensitivity, high requirement of expert experience, and low recognition accuracy of traditional machine vision methods in train wheelset bearing damage detection, this paper proposes an identification method based on the framework of convolutional and transformer fusion networks for identifying damage to train wheelset bearings. First, due to the complexity of train-bearing images, their category imbalance is more severe; an image preprocessing method called image enhancement category reorganization is used to improve the quality of the acquired image dataset and eliminate the effects of the imbalance dataset. Second, a convolutional neural network (CNN) has high model construction and training efficiency due to adopting a local sensing field and weight-sharing strategy, which can only sense local neighborhoods but has limited ability to capture global feature information. Transformer is a network model based on a self-attention mechanism. With strong parallel computing ability, it can learn the remote dependencies between image pixels in the global scope and has a more powerful global information extraction ability. However, the ability to mine the local features of the image is not sufficient. Therefore, this paper presents a VGG and transformer parallel fusion network that integrates the global contour features and local details of the image based on the fusion of convolution and self-attention. Furthermore, a multiscale dilation spatial pyramid convolution (MDSPC) module is constructed to fully mine the multiscale semantic features in the feature map using multiscale dilation convolution progressive fusion. The proposed method effectively solves the problem of feature information loss due to the mesh effect caused by the expansion convolution. Additionally, embedding coordinate attention (CA) after the MDSPC module can obtain remote dependencies and more precise positional relationships of feature images from two spatial directions, which can more accurately focus on specific regions in the feature map. Finally, experimental analyses were conducted using the NEU-DET image defect and self-constructed train wheelset bearing image datasets. The experimental results demonstrate that the proposed model has an accuracy of 99.44% and 98% for recognizing six types of defects and four types of images of wheelset bearings in NEU-DET data, respectively. The feature extraction capability of the proposed model was verified using model visualization methods. Compared with existing CNN models, ViT model with self-attention mechanism, and CNN-transformer fusion model, the proposed method shows significantly better evaluation metrics and accurately identifies different types of image samples without significantly increasing the model complexity.

Graphitic carbon nitride (g-C3N4)-based photocatalysts have garnered significant interest as a promising photocatalyst for hydrogen generation under visible light, to address energy and environmental challenges owing to their favorable electronic structure, affordability, and stability. In spite of that, issues such as high charge carrier recombination rates and low quantum efficiency impede its broader application. To overcome these limitations, structural and morphological modification of the g-C3N4-based photocatalysts is a novel frontline to improve the photocatalytic performance. Therefore, we briefly summarize the current preparation methods of g-C3N4. Importantly, this review highlights recent advancements in crafting high-performance g-C3N4-based photocatalysts, focusing on strategies like elemental doping, nanostructure design, bandgap engineering, and heterostructure construction. Notably, sophisticated doping techniques have propelled hydrogen production rates to a 104-fold increase. Ingenious nanostructure designs have expanded the surface area by a factor of 26, concurrently extending the fluorescence lifetime of charge carriers by 50%. Moreover, the strategic assembly of heterojunctions has not only elevated charge carrier separation efficiency but also preserved formidable redox properties, culminating in a dramatic hundredfold surge in hydrogen generation performance. This work provides a reliable and brief overview of the controlled modification engineering of g-C3N4-based photocatalyst systems, paving the way for more efficient hydrogen production.

This work has studied the co-addition of Sc and Zr elements into the Al-1.75wt%Fe-1.25wt%Ni eutectic alloy. The changes in the microstructure, electrical conductivity, and Vickers hardness of the Al-1.75wt%Fe-1.25wt%Ni-0.2wt%Sc-0.2wt%Zr alloy during heat treatment were studied. The results showed that two-step aging can effectively improve the aging response of the alloy over the single-step aging method. This was ascribed to the minimization of the diffusion difference between Sc and Zr elements. Furthermore, the homogenization treatment can also improve the aging response of the alloy by alleviating the uneven distribution of Sc and Zr. Nevertheless, the micro-alloyed elements exceeded the solid solubility limit in the Al-1.75wt%Fe-1.25wt%Ni-0.2wt%Sc-0.2wt%Zr alloy, and their strengthening effect has ever achieved the best prospect. Finally, both Sc and Zr contents were reduced simultaneously, and the aging response of the Al-1.75wt%Fe-1.25wt%Ni-0.15wt%Sc-0.1wt%Zr alloy was improved by optimized heat treatment. The underlying mechanisms for this alloy design and the corresponding microstructure–mechanical property relationship were analytically discussed.

The prognostic significance of the signet-ring cell component in gallbladder carcinoma (GBC) has not been systematically evaluated. The aim of this study was to assess the similarities and differences between gallbladder signet-ring cell carcinoma (GBSRCA) and gallbladder adenocarcinoma (GBAC) in terms of clinicopathological features and long-term survival. Using the Surveillance, Epidemiology, and End Results (SEER) database, we analyzed 6,612 patients diagnosed with gallbladder cancer between 2000 and 2021. The cohort included 147 patients with GBSRCA and 6,465 with GBAC. Patients with GBSRCA were significantly younger, with 33.3% being age 60 or younger compared to 23.9% of patients with GBAC (P = 0.009). There was a higher proportion of females in the GBSRCA group (77.6%) compared to the GBAC group (70.1%, P = 0.049). GBSRCA was associated with a more advanced tumor stage (T3-T4: 56.5% vs. 44.4%, P = 0.004), higher rates of lymph node metastasis (43.5% vs. 28.0%, P < 0.001), and poorer differentiation status (poorly to undifferentiated: 80.3% vs. 29.7%, P < 0.001). Survival analysis revealed that patients with GBSRCA had significantly worse overall survival (OS) and cancer-specific survival (CSS) compared to patients with GBAC (P < 0.001). GBSRCA was an independent prognostic factor for OS (P = 0.001) in the entire cohort, while the T stage and N stage were independent prognostic factors for OS and CSS in patients with GBSRCA. Even after propensity score matching, patients with GBSRCA still had a poorer prognosis. [ABSTRACT FROM AUTHOR]

Intrahepatic bile duct mucinous adenocarcinoma (IHBDMAC) is a rare pathological subtype of intrahepatic cholangiocarcinoma (IHCC), and its tumor biological features and survival outcomes have rarely been explored, especially when compared to the most common subtype, intrahepatic bile duct adenocarcinoma (IHBDAC). Therefore, the aim of this study was to explore the clinical features and survival outcomes of IHBDAC and IHBDMAC using the Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2021. A total of 1,126 patients were included, with 1,083 diagnosed with IHBDAC and 43 diagnosed with IHBDMAC. Patients with IHBDMAC presented with a more advanced T stage (55.8% vs. 36.9%, P = 0.012) and higher rate of lymph node metastasis (37.2% vs. 24.9%, P = 0.070). Cox regression identified advanced T stage, lymph node metastasis, and distant metastasis as poor survival predictors, while chemotherapy and surgery were protective factors. Survival analyses revealed significantly worse overall survival (OS) and cancer-specific survival (CSS) for IHBDMAC compared to IHBDAC (P < 0.05). Even after matching, patients with IHBDMAC still had a worse prognosis than those with IHBDAC. These findings highlight the aggressive nature of IHBDMAC and the need for tailored therapeutic strategies. Future research should focus on prospective studies and molecular insights to develop targeted treatments for IHBDMAC. [ABSTRACT FROM AUTHOR]