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Neutron radiography, also called neutron imaging, is a significant radiographic non-destructive testing (NDT) technology. In the process of neutron imaging, electronic equipment, space fluctuation of neutrons, collimator structure, high-energy particle irradiation imaging detector, and other factors can introduce different degrees of degradation on the neutron radiographic images, mainly in the form of Gaussian noise, Poisson noise, geometric unsharpness (blur), white spot noise, and other image distortions, especially in compact neutron radiography systems with limited neutron flux. Most of the existing distortion suppression algorithms for neutron radiographic images require some prior information on distortion, such as noise intensity and blur intensity. Moreover, the distortion-suppression effect depends greatly on the estimation accuracy of the distortion parameters. However, the distortion model of neutron radiographic images contains a variety of mixed noise and blurring. Suppressing some single distortion may introduce or aggravate other kinds of distortions. Therefore, it is difficult to effectively improve the image quality with a single distortion-suppression scheme. In order to solve this issue, the multiple-degradation models of neutron radiographic images were first analyzed. Then, a large-scale image distortion dataset consistent with the real distortion types of neutron radiography was constructed, including different levels of Gaussian noise, Poisson noise, white spot noise, and Gaussian blur. A novel image restoration network based on the generative adversarial network (GAN) and coordinate attention mechanism was designed. Through end-to-end training, multiple distortions of real neutron radiographic images can be effectively suppressed by the proposed method. Moreover, because of the different imaging mechanisms and distortion types of natural images and neutron radiographic images, a no-reference image quality assessment scheme was further proposed for neutron radiographic images in this paper. A series of experiments on the real neutron radiographic images show that the proposed restoration method achieves good performance in the subjective evaluation. Meanwhile, the objective quality assessment method also verifies the effectiveness of the proposed method. Specifically, according to the subjective scores of 30 groups of researchers on the effects of different restoration schemes, the proposed image restoration scheme achieves the best performance in subjective evaluation. At the same time, based on the quantitative analysis of the objective image quality assessment method proposed in this paper, it can be seen that the quality score of the proposed restoration scheme increases by more than 10% compared with other deep learning and traditional image restoration methods, thus demonstrating the effectiveness of the proposed restoration and quality assessment for the compact neutron radiography system.

BackgroundThe quality of neutron radiographic images is mainly evaluated by human visual system (HVS), but HVS cannot be used as a real-time auxiliary for optimization parameters of neutron imaging systems.PurposeThis study aims to evaluate the quality of neutron radiographic images by no-reference image quality assessment (NR-IQA) and provide an effective approach for the parameters optimization of neutron imaging systems.MethodsFirstly, the plain natural images distorted with different distortion levels and types were labelled with quality scores to construct an experimental dataset by the gradient magnitude similarity deviation (GMSD) method. Then, the residual network (ResNet) model was employed to evaluate the quality of neutron radiographic images without reference images. Finally, the goal of extracting features and assessing the quality of neutron radiographic images was achieved by training the ResNet.ResultsThe model performs well in the test set of the experimental dataset and the quality prediction of the two group authentic neutron radiographic images.ConclusionsThe proposed quality assessment method could be used for the quality prediction of neutron radiographic images.

Over the past decade, there has been a growing emphasis on investigating the role of immunotherapy in cancer treatment. However, it faces challenges such as limited efficacy, a diminished response rate, and serious adverse effects. Nanozymes, a subset of nanomaterials, demonstrate boundless potential in cancer catalytic therapy for their tunable activity, enhanced stability, and cost-effectiveness. By selectively targeting the metabolic vulnerabilities of tumors, they can effectively intensify the destruction of tumor cells and promote the release of antigenic substances, thereby eliciting immune clearance responses and impeding tumor progression. Combined with other therapies, they synergistically enhance the efficacy of immunotherapy. Hence, a large number of metabolism-regulating nanozymes with synergistic immunotherapeutic effects have been developed. This review summarizes recent advancements in cancer immunotherapy facilitated by nanozymes, focusing on engineering nanozymes to potentiate antitumor immune responses by disturbing tumor metabolism and performing synergistic treatment. The challenges and prospects in this field are outlined. We aim to provide guidance for nanozyme-mediated immunotherapy and pave the way for achieving durable tumor eradication. [ABSTRACT FROM AUTHOR]

The Compact thermal neutron imaging systems have become an important development trend. Compact thermal neutron imaging systems can use neutron tubes as neutron sources because of their low cost, small size, and portability. In order to achieve optimal imaging quality, the moderator and collimator in a neutron imaging system based on neutron tubes source are designed and simulated using SuperMC. The entrance position of the collimator is determined by analyzing the performance of different materials with their parameter's optimization. It is suggested that a cylinder-shaped structure made of carbon, hydrogenous materials, and heavy metals can significantly increase the thermal neutron flux at the sample location. Further dimension optimization is carried out to improve the neutron beam collimation performance. A vertically divergent collimator with a divergence angle of 5° and an air gap is selected, along with the addition of a B4C lining material. According to the modelling results, the sample position can be as far away from the neutron source as 77 cm with a neutron source yield of 1.14 × 109 n/s. The collimation ratio is 29, the thermal neutron flux is 1.08 × 103 n/cm2·s, and n/γ is 1.44 × 1012 n/cm2·Sv, which is suitable for thermal neutron radiography. [ABSTRACT FROM AUTHOR]

From the perspective of principal-agent, the theory of financial acceleration holds that due to the defects of the financial market, external shocks will be amplified by the financial market and accelerate the transmission in the real economy, and the impact on small enterprises is greater than that on large enterprises. According to the theory of financial deceleration, the agency cost caused by financial friction is counter-cyclical, which restrains credit scale to some extent, prevents excessive debt, and thus alleviates external shocks. According to the empirical analysis of panel data of iron and steel enterprises and the existing empirical results of the real estate industry, it is found that there is no financial accelerator effect or financial reducer effect in the field of iron and steel enterprises. China’s financial accelerator is more focused on bubbly assets where growth is expected and continues to be overheated despite policy tightening. That would trigger a bigger debt crisis and greater economic volatility.

Minor enterprises have made an indelible contribution to economic development, while financing has always been a problem hindering the sustainable development of them. Under the influence of the epidemic, the business environment of minor enterprises has changed, and the financing demand has also changed. However, the degree and scope of assistance are limited. There is a contradiction between supply and demand in fund allocation. Based on this, this project puts forward policy suggestions by studying the changes of financing demand and fund supplier of minor enterprises in Wuhan in the post epidemic era, which will help to solve the financing difficulties and promote healthy and sustainable development of the national economy.