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Current analysis of fragile bronzes mainly relies on the research of two-dimensional aspects such as sample cross-sections and surfaces while typically utilizing optical and electronic microscopy, Raman spectroscopy, and X-ray fluorescence spectroscopy (XRF). As a fast and nondestructive testing method, computer tomography (CT) can be used to characterize and detect the internal structures, corrosion conditions, and corrosion distribution of bronzes. This study used the CT imaging results of fragile bronzes to analyze, locate, and measure corrosion in fragile bronzes quickly and accurately, thus providing strong support for corrosion evaluation and protection research of fragile bronzes. The results verified the value and application prospects of CT technology in the protection of cultural relics.

Abstract Single image super‐resolution (SISR) is a promising research direction in computer vision and image processing for improving the visual perception of low‐quality images. In recent years, deep learning algorithms have driven tremendous development in SR, and SR methods based on various network architectures have significantly improved the quality of reconstructed images. Although there has been a large amount of reviews focusing on SISR, few studies have focused specifically on network architectures for SISR. This paper aims to provide a systematic overview of the design ideas of SISR using multiple architectures, including Convolutional Neural Networks (CNN), Generative Adversarial Networks (GAN), Transformer, and Diffusion model. In addition, an experimental analysis and comparison of state‐of‐the‐art SR algorithms have been performed on publicly available quantitative and qualitative datasets. Finally, some future directions are discussed that may help other community researchers.

The internal three-dimensional characteristics of X-ray microtomography (micro-CT) has great application potential in the field of bronze corrosion. This work presents a method of simulating bronze disease based on an in situ micro-CT image to study the characteristics of the oxidative hydrolysis reactions of copper(I) chloride and copper(II) chloride dihydrate. A series of high-resolution reconstruction images were obtained by carrying out micro-CT at three key points throughout the experiment. We found that the reactions of copper(I) chloride and copper(II) chloride dihydrate showed different characteristics at different stages of the simulation in the micro-CT view. The method proposed in this work specifically simulated one single type of bronze corrosion and characterized the evolution characteristics of simulated bronze disease. It provides a new perspective to investigate bronze disease and can help improve the subsequent use of micro-CT to distinguish real bronze corrosions.

The mismatch of geometric parameters in a nanotomography system bears a significant impact on the reconstructed images. Moreover, projection image noise is increased due to limitations of the X-ray power source. The accuracy of the existing self-calibration method, which uses only the grayscale information of the projected image, is easily affected by noise and leads to reduced accuracy. This paper proposes a geometric parameter self-calibration method based on feature matching of mirror projection images. Firstly, the fast extraction and matching feature points in the mirror projection image are performed by speeded-up robust features (SURF). The feature triangle is then designed according to the stable position of the system’s rotation axis to further filter the feature points. In turn, the influence of the mismatched points on the calculation accuracy is reduced. Finally, the straight line where the rotation axis is located is fitted by the midpoint coordinates of the filtered feature points, thereby realizing geometric parameter calibration of the system. Simulation and actual data from the experimental results show that the proposed method effectively realizes the calibration of geometric parameters, and the blurring and ghosting caused by geometric artifacts are corrected. Compared with existing methods, the image clarity can be improved by up to 14.4%.

The resolution of 3D structure reconstructed by laboratory nanoCT is often affected by changes in ambient temperature. Although correction methods based on projection alignment have been widely used, they are time-consuming and complex. Especially in piecewise samples (e.g., chips), the existing methods are semi-automatic because the projections lose attenuation information at some rotation angles. Herein, we propose a fast correction method that directly processes the reconstructed slices. Thus, the limitations of the existing methods are addressed. The method is named multiscale dense U-Net (MD-Unet), which is based on MIMO-Unet and achieves state-of-the-art artifacts correction performance in nanoCT. Experiments show that MD-Unet can significantly boost the correction performance (e.g., with three orders of magnitude improvement in correction speed compared with traditional methods), and MD-Unet+ improves 0.92 dB compared with MIMO-Unet in the chip dataset.

A self-correction method for the drift artifacts of laboratory cone-beam nanoscale X-ray computed tomography (nano-CT) based on the trajectory of projection centroid (TPC) is proposed. This method does not require additional correction phantoms, simplifying the correction process. The whole TPC is estimated by the partial TPC in the optimal projection set. The projection drift is calculated by the measured TPC and the estimated TPC. The interval search method is used so that the proposed method can adapt to the case of a truncated projection due to drift. The fixed-angle scanning experiment of the Siemens star and the partial derivative analysis of the projection position show the necessity of correcting drift artifacts. Further, the Shepp–Logan phantoms with different drift levels are simulated. The results show that the proposed method can effectively estimate the horizontal and vertical drifts within the projection drift range of ±2 mm (27 pixels) with high accuracy. Experiments were conducted on tomato seed and bamboo stick to validate the feasibility of the proposed method for samples with different textures. The correction effect on different reconstructed slices indicates that the proposed method provides performance superior to the reference scanning method (RSM) and global fitting. In addition, the proposed method requires no extra scanning, which improves the acquisition efficiency, as well as radiation utilization.

Metal artifacts seriously degrade the quality of the CT data and bring great difficulties to subsequent image processing and analysis, which nowadays become a great concern in X-ray CT applications. In this paper, we introduce a U-net-based metal artifact reduction method into CT image domain. The proposed network reduces metal artifacts by learning an end-to-end mapping of images from metal-corrupted CT images to their corresponding artifact-free ground truth images. We design and optimize the network through the simulation experiments. The experimental results show that the proposed method can well reduce metal artifacts of CT images, and this method has higher computational efficiency and greatly shortens the processing time. It avoids complex image preprocessing and can accept input images of any size. Therefore, it can be a more automated way to handle large amounts of data, making it ideal for existing CT workflows.

In computed tomography (CT) images, the presence of metal artifacts leads to contaminated object structures. Theoretically, eliminating metal artifacts in the sinogram domain can correct projection deviation and provide reconstructed images that are more real. Contemporary methods that use deep networks for completing metal-damaged sinogram data are limited to discontinuity at the boundaries of traces, which, however, lead to secondary artifacts. This study modifies the traditional U-net and adds two sinogram feature losses of projection images—namely, continuity and consistency of projection data at each angle, improving the accuracy of the complemented sinogram data. Masking the metal traces also ensures the stability and reliability of the unaffected data during metal artifacts reduction. The projection and reconstruction results and various evaluation metrics reveal that the proposed method can accurately repair missing data and reduce metal artifacts in reconstructed CT images.

Thermal drift of nano-computed tomography (CT) adversely affects the accurate reconstruction of objects. However, feature-based reference scan correction methods are sometimes unstable for images with similar texture and low contrast. In this study, based on the geometric position of features and the structural similarity (SSIM) of projections, a rough-to-refined rigid alignment method is proposed to align the projection. Using the proposed method, the thermal drift artifacts in reconstructed slices are reduced. Firstly, the initial features are obtained by speeded up robust features (SURF). Then, the outliers are roughly eliminated by the geometric position of global features. The features are refined by the SSIM between the main and reference projections. Subsequently, the SSIM between the neighborhood images of features are used to relocate the features. Finally, the new features are used to align the projections. The two-dimensional (2D) transmission imaging experiments reveal that the proposed method provides more accurate and robust results than the random sample consensus (RANSAC) and locality preserving matching (LPM) methods. For three-dimensional (3D) imaging correction, the proposed method is compared with the commonly used enhanced correlation coefficient (ECC) method and single-step discrete Fourier transform (DFT) algorithm. The results reveal that proposed method can retain the details more faithfully.

For X-ray cone-beam computed tomography (CBCT), non-calibrated system geometry causes indistinct and blurring artifacts in reconstructed images, which impacts on the image quality badly. This paper presents a practical industrial CBCT geometric calibration method, which aims to determine the geometric parameter without extra phantom and benefit to efficiency for calibration. In our method, the geometric parameter is divided into system parameter and imaging parameter to be calibrated, respectively. First, the system parameter was determined precisely at the first beginning via average for multiple measurements. Next, the imaging parameter was determined via a designed algorithm in this paper based on the invariance of rotation axis. Furthermore, the proposed method only utilizes the projection data without reconstruction iteration to calibrate geometric parameter, which benefits to efficiency and practical industrial application. 3-D simulation data have been through test with and without noise, and the results show robust and accuracy on the proposed algorithm. In addition, it is also validated with various real data include printed circuit board and industrial components acquired at actual industrial CBCT. The results of reconstructed images demonstrate that the proposed method can achieve comparable image quality in the reconstruction as some phantom-based methods. Furthermore, the advantages and obstacle of the proposed method are analyzed and discussed in this paper.

Deep learning techniques have significantly improved image restoration tasks in recent years. As a crucial component of deep learning, the loss function plays a key role in network optimization and performance enhancement. However, the currently prevalent loss functions assign equal weight to each pixel point during loss calculation, which hampers the ability to reflect the roles of different pixel points and fails to exploit the image’s characteristics fully. To address this issue, this study proposes an asymmetric loss function based on the image and data characteristics of the image recovery task. This novel loss function can adjust the weight of the reconstruction loss based on the grey value of different pixel points, thereby effectively optimizing the network training by differentially utilizing the grey information from the original image. Specifically, we calculate a weight factor for each pixel point based on its grey value and combine it with the reconstruction loss to create a new loss function. This ensures that pixel points with smaller grey values receive greater attention, improving network recovery. In order to verify the effectiveness of the proposed asymmetric loss function, we conducted experimental tests in the image super-resolution task. The experimental results show that the model with the introduction of asymmetric loss weights improves all the indexes of the processing results without increasing the training time. In the typical superresolution network SRCNN, by introducing asymmetric weights, it is possible to improve the peak signal-to-noise ratio (PSNR) by up to about 0.5%, the structural similarity index (SSIM) by up to about 0.3%, and reduce the rootmean- square error (RMSE) by up to about 1.7% with essentially no increase in training time. In addition, we also further tested the performance of the proposed method in the denoising task to verify the potential applicability of the method in the image restoration task. [ABSTRACT FROM AUTHOR]

Objective: Based on the visualization and analysis of the CiteSpace software, we aimed to explore the current research status and development trend of depression caused by external therapies in traditional Chinese medicine (TCM) and to provide a reference for further research in this field. Methods: In the China National Knowledge Infrastructure, Wanfang, Web of Science, and PubMed databases, relevant articles on external therapies in TCM for depression were selected as the research objects, and CiteSpace performed the bibliometric analysis. Results: In total, 1672 Chinese and 441 English articles were included after CiteSpace was used to remove duplicate articles and perform manual screening. The Chinese articles were analyzed, and the overall issuance showed an upward trend; the core author was Tu Ya, and the institution with the highest article production was Heilongjiang University of Traditional Chinese Medicine. The English articles were analyzed, and the overall issuance showed an upward trend; the core author was Macpherson, Hugh, and the institution with the highest article production was Guangzhou University of Traditional Chinese Medicine. China ranked first in terms of number and centrality of publications, followed by the United States. The keywords of Chinese and English articles were analyzed to conclude that the research trends in this field were an exploration of therapeutic mechanisms, acupoint application therapy, and assessment of sleep quality, and the research hotspots were the clinical application of external therapies in TCM and the types of underlying diseases. Conclusion: This study comprehensively and objectively summarized the relevant literature on external therapies in TCM for depression. It highlights the direction for further exploration by revealing and analyzing the research hotspots and trends in this field.

Introduction: Facial nerve injury significantly impacts both the physical and psychological] wellbeing of patients. Despite advancements, there are still limitations associated with autografts transplantation. Consequently, there is an urgent need for effective artificial grafts to address these limitations and repair injuries. Recent years have witnessed the recognition of the beneficial effects of chitosan (CS) and graphene in the realm of nerve repair. Dental pulp stem cells (DPSCs) hold great promise due to their high proliferative and multi-directional differentiation capabilities.Methods: In this study, Graphene/CS (G/CST) composite tubes were synthesized and their physical, chemical and biological properties were evaluated, then DPSCs were employed as seed cells and G/CST as a scaffold to investigate their combined effect on promoting facial nerve injury repair.Results and Disscussion: The experimental results indicate that G/CST possesses favorable physical and chemical properties, along with good cyto-compatibility. making it suitable for repairing facial nerve transection injuries. Furthermore, the synergistic application of G/CST and DPSCs significantly enhanced the repair process for a 10 mm facial nerve defect in rabbits, highlighting the efficacy of graphene as a reinforcement material and DPSCs as a functional material in facial nerve injury repair. This approach offers an effective treatment strategy and introduces a novel concept for clinically managing facial nerve injuries.

Person search, which involves identifying target pedestrians in extensive galleries through person detection and re-identification, has experienced significant advancements across various applications. However, it remains a challenging research area due to factors such as appearance changes, lighting variations, background interference, and pedestrian occlusion. This paper proposes an end-to-end person search framework, termed the Global-Response Pedestrian Attention Network (GPAN-PS), designed to tackle these challenges. Specifically, GPAN-PS includes a novel Global Response Pedestrian Attention (GRPA) module that samples pedestrian features using three shared-weight convolutional layers with distinct dilation rates. This enables the network to adaptively select the optimal receptive field through the Squeeze-and-Excitation (SE) module and the Global Response Normalization (GRN) module, enhancing feature stability. Furthermore, we design a GsConvNeXt Head module to bolster feature expressiveness and facilitate inter-channel information interaction. Rather than employing the ConvNeXt (conv5) module as the Box Head for generating refined proposals, our approach employs the GsConvNeXt Head module. This module is also integrated into the Re-ID Head for the extraction of pedestrian features. Both the GRPA and GsConvNeXt Head modules are flexible and adaptable, allowing for seamless integration into other models. Extensive experiments conducted on two benchmark datasets, CUHK-SYSU and PRW, underscore the superior performance of our proposed method. Notably, on the challenging PRW dataset, our approach achieves a mean Average Precision (mAP) of 59.2% and a Top-1 accuracy of 92.2%.

Abstract As a significant type of traumatic brain injury (TBI), blast-induced traumatic brain injury (bTBI) frequently results in severe neurological and psychological impairments. Due to its unique mechanistic and clinical features, bTBI presents diagnostic and therapeutic challenges compared to other TBI forms. The hippocampus, an important site for secondary injury of bTBI, serves as a key niche for neural regeneration and repair post-injury, and is closely associated with the neurological outcomes of bTBI patients. Nonetheless, the pathophysiological alterations of hippocampus underpinning bTBI remain enigmatic, and a corresponding transcriptomic dataset for research reference is yet to be established. In this investigation, the single-nucleus RNA sequencing (snRNA-seq) technique was employed to sequence individual hippocampal nuclei of mice from bTBI and sham group. Upon stringent quality control, gene expression data from 17,278 nuclei were obtained, with the dataset’s reliability substantiated through various analytical methods. This dataset holds considerable potential for exploring secondary hippocampal injury and neurogenesis mechanisms following bTBI, with important reference value for the identification of specific diagnostic and therapeutic targets for bTBI.

Objective: Peroxiredoxin-3 (Prx-3) is widely acknowledged as an antioxidant that protects against mitochondrialreactive oxygen species. Nonetheless, its role in cardiac fibrosis has not been elucidated. We aim to explore the roleand mechanism of Prx-3 in cardiac fibrosis.Materials and Methods: In this experimental study, mice received subcutaneous injections of isoproterenol (ISO) for 14consecutive days (10 mg/kg/d for three days, followed by 5 mg/kg/d for 11 days) to establish a cardiac fibrosis model. Themice were subsequently injected with adenovirus-Prx-3 (ad-Prx-3) to enable Prx-3 overexpression. Echocardiographywas used to evaluate cardiac function. Mice heart fibroblasts were isolated and stimulated with transforming growthfactor β1 (TGFβ1) to induce fibrosis in vitro. Cells were also transfected with ad-Prx-3 for overexpression of Prx-3.Results: Echocardiographic diameters and fibrosis markers indicated that Prx-3 could inhibit ISO-induced cardiacdysfunction and fibrosis. Fibroblasts with Prx-3 overexpression exhibited reduced activation, proliferation, and collagentranscription. We found that Prx-3 reduced the expression of NADPH oxidase 4 (NOX4) and reduced P38 levels. Aftertreatment with a P38 inhibitor, the Prx-3 overexpression-induced anti-fibrosis effect was mitigated.Conclusion: Prx-3 could protect against ISO-induced cardiac fibrosis by inhibiting the NOX4-P38 pathway.

Lung cancer is the second most common, and the deadliest, disease globally. Because it is often diagnosed late, surgical resection is not a viable treatment option for ∼75 % of patients, often resulting in a poor prognosis. Of the available treatments, radioactive iodine-125 (125-I) seed implantation therapy, or brachytherapy, has emerged as a promising option. In this procedure, small radioactive seeds are implanted inside tumor cells to produce sustained effects. Because of the short radial distance of this radiation, 125-I brachytherapy selectively and efficiently kills cancer cells while minimizing injury to adjacent cells. The present review describes the mechanism of 125-I seed implantation in the treatment of lung cancer, its efficacy and safety, and its combination with other therapies. We conclude that radioactive 125-I seed implantation and its use in combination with other therapies are good options for the management of local tumor growth, pain palliation, and improving the life span of patients suffering from lung cancers. This technique can enhance the clinical efficacy of treatment and improve the overall survival of patients with lung cancers. However, standardized dosage regimens and other procedures are still required to achieve treatment homogeneity and provide guidance for the clinical implementation of this technique.

Abstract Explosive blast-related traumatic brain injuries (bTBI) are common in war zones and urban terrorist attacks. These bTBIs often result in complex neuropathologic damage and neurologic complications. However, there is still a lack of specific strategies for diagnosing and/or treating bTBIs. The sub-ventricular zone (SVZ), which undergoes adult neurogenesis, is critical for the neurological maintenance and repair after brain injury. However, the cellular responses and mechanisms that trigger and modulate these activities in the pathophysiological processes following bTBI remain poorly understood. Here we employ single-nucleus RNA-sequencing (snRNA-seq) of the SVZ from mice subjected to a bTBI. This data-set, including 15272 cells (7778 bTBI and 7494 control) representing all SVZ cell types and is ideally suited for exploring the mechanisms underlying the pathogenesis of bTBIs. Additionally, it can serve as a reference for future studies regarding the diagnosis and treatment of bTBIs.

Abstract Background Coronary heart disease (CHD) has become a leading cause of morbidity and premature death worldwide. Cardiac rehabilitation (CR) was proved to have substantial benefits for patients with CHD. The CR was divided into three phases. Phase 2 is the important part of CR which involves hospital-based structured and closely monitored exercises and activities. However, CR utilization is low worldwide. The barriers to hospital-based phase 2 CR in China have not been well identified. Aims To investigate barriers to hospital-based phase 2 cardiac rehabilitation among coronary heart disease patients in China and to explore the reasons. Methods This study employed an explanatory sequential mixed-methods design. The study was conducted in a university hospital in China from July 2021 to December 2021. Quantitative data was collected through the Cardiac Rehabilitation Barrier Scale. Qualitative data was collected through unstructured face-to-face interviews. Data analysis included descriptive statistics and inductive qualitative content analysis. Results One hundred and sixty patients completed the Cardiac Rehabilitation Barrier Scale and 17 patients participated in unstructured face-to-face interviews. The main barriers identified were distance (3.29 ± 1.565), transportation (2.99 ± 1.503), cost (2.76 ± 1.425), doing exercise at home (2.69 ± 1.509) and time constraints (2.48 ± 1.496). Six themes were identified; logistical factors, social support, misunderstanding of cardiac rehabilitation, program and health system-level factors, impression of CR team and psychological distress. The first four themes confirmed the quantitative results and provide a deeper explanation for the quantitative results. The last two themes were new information that emerged in the qualitative phase. Conclusion This study provides a better understanding of the barriers to hospital-based phase 2 cardiac rehabilitation among coronary heart disease patients in the Chinese context during the Covid-19 pandemic. Innovative programs such as home-based CR, mobile health, and hybrid programs might be considered to overcome some of these barriers. In addition, psychosocial intervention should be included in these programs to mitigate some of the barriers associated with the impression of CR team and psychological distress.

BackgroundTension-type headache (TTH) is one of the most common primary headaches. Several studies have confirmed the efficacy of acupuncture therapies for TTH, but it is uncertain which treatment is most effective.ObjectiveThis study aimed to compare the effectiveness and safety of different acupuncture therapies for TTH using Bayesian Network Meta-analysis to provide new ideas for treating TTH.MethodsNine databases were searched for randomized controlled trials (RCTs) about different acupuncture therapies for TTH up to December 1, 2022. The outcome indicators analyzed in our study were total effective rate, visual analog scale (VAS), headache frequency, and safety. Pairwise meta-analysis and risk of bias assessment were performed using Review Manager 5.4. Stata 15.0 generated a network evidence plot and detected publication bias. Finally, a Bayesian network meta-analysis of the data was used by RStudio.ResultsThe screening process resulted in 30 RCTs that met the inclusion criteria, including 2,722 patients. Most studies failed to report details of trials and were therefore assessed as unclear risks. Two studies were considered high risk because they did not report on all pre-specified outcome indicators or had incomplete data on outcome indicators. The NMA results showed that for total effective rate, bloodletting therapy had the most considerable SUCRA value (0.93156136), for VAS, head acupuncture combined with Western medicine ranked first (SUCRA = 0.89523571), and acupuncture combined with herbal medicine was the most effective in improving headache frequency (p > 0.05).ConclusionAcupuncture can be used as one of the complementary or alternative therapies for TTH; bloodletting therapy better improves the overall symptoms of TTH, head acupuncture combined with Western medicine is more effective in reducing VAS scores, and acupuncture combined with herbal medicine seems to reduce headache frequency, but the difference is not statistically significant. Overall, acupuncture for TTH is effective with mild side effects, but future high-quality studies are still necessary.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, PROSPERO [CRD42022368749].

Abstract Background Cell division cycle 6 (CDC6) has been proven to be associated with the initiation and progression of human multiple tumors. However, it’s role in glioma, which is ranked as one of the common primary malignant tumor in the central nervous system and is associated with high morbidity and mortality, is unclear. Methods In this study, we explored CDC6 gene expression level in pan-cancer. Furthermore, we focused on the relationships between CDC6 expression, its prognostic value, potential biological functions, and immune infiltrates in glioma patients. We also performed vitro experiments to assess the effect of CDC6 expression on proliferative, apoptotic, migrant and invasive abilities of glioma cells. Results As a result, CDC6 expression was upregulated in multiple types of cancer, including glioma. Moreover, high expression of CDC6 was significantly associated with age, IDH status, 1p/19q codeletion status, WHO grade and histological type in glioma (all p

The superstructure of the metro depot is not only convenient for traffic but also solves the land-use problem. However, the construction of the superstructure comes after the metro depot has been put into normal operation. The foundation of the depot is bound to produce secondary settlement. Based on the calculation method of the friction-end bearing pile of Mindlin’s solution in the specification, the superstructure construction project above the Beijing Guogongzhuang metro depot is taken as the basis. Under certain conditions, the settlement of the pile foundation under the action of secondary load and the influence on the track structure are calculated. Moreover, the finite element analysis software ANSYS 18.0 is used to establish the analysis model of the construction of the superstructure of the applied depot. The results show that the influence of the pile foundation settlement produces a certain additional influence on the surrounding tracks, and the maximum value locates at the center of the bearing platform and gradually decreases outward. Under the conditions of informative construction, uniform loading of the structure and control of the construction process, local bias loads and uneven settlements are avoided. The impact of the construction on the track can be effectively controlled, and the impact on the structure can be kept within the allowable limits. By comparing this instance with a number of similar superstructure projects in Beijing, this study shows that the overall risk of this type of project can be controlled and can provide a technical reference for similar superstructure projects on top of a metro depot construction in the future.

Abstract Background The Trunk Impairment Scale (TIS) has been translated into Chinese, but the psychometric properties of the Chinese version of the TIS (TIS-C) have not yet been established. We aimed to examine the reliability and validity of the TIS-C for assessing sitting balance among Chinese people with a stroke. Methods A descriptive, cross-sectional design was used. We recruited a convenience sample of 170 subacute stroke patients aged 18 years or over from the neurology departments of four traditional Chinese medicine hospitals in China. Patients completed the TIS-C, the Berg Balance Scale and the Modified Barthel Index. The psychometric properties of the TIS-C were examined to establish test–retest reliability, internal consistency, equivalence, and content, criterion, and construct validity. Results Intraclass correlation coefficients for inter-rater and intra-rater reliability ranged from 0.75 to 0.89 and from 0.90 to 0.97, respectively. The TIS-C Cronbach α was 0.86. The strong correlation between the total score of the TIS-C and the Berg Balance Scale (r s = 0.81, p