44 research outputs found
The role of MRI in the diagnosis and treatment of gastric cancer
Gastric cancer is the fifth most common malignancies and the third leading cause of cancer-related death worldwide, with more than 40% of new cases occurring in China. With the advancement of treatment methods, the application of adjuvant therapy and targeted drugs, the prognosis of patients with gastric cancer has been significantly improved. In recent years, more and more studies have reported that magnetic resonance imaging (MRI) showed great value in the clinical application among patients with gastric cancer, including preoperative staging, treatment response evaluation, predicting prognosis and histopathological features, treatment guidance, and molecular imaging. The remarkable research progress of MRI in gastric cancer will provide new evaluation and treatment approaches for clinical diagnosis and treatment. This article aims to review the current status of the application and research progress of MRI in patients with gastric cancer
Numerical investigation of Rayleigh waves in layered composite piezoelectric structures using the SIGA-PML approach
Existence of surface acoustic waves(SAW) on a piezoelectric layer with the half-infinite elastic layer is investigated. This structure belongs to an open waveguide with the unbounded boundary in the transverse direction. Except for trapped modes, leaky modes have often been considered in SAW applications, which requires waves of low attenuation in order to maximize the propagation distance. Therefore, we develop an another formulation of piezoelectric layer structures for the computation of trapped and leaky modes in open waveguides. This method combines the so-called semi-analytical isogeometric analysis and a perfectly matched layer technique (SIGA-PML). The comparison between semi-analytical finite element (SAFE-PML) and SIGA-PML is given, in order to show the effective and accuracy of SIGA-PML. Finally, we analyze propagation properties of Rayleigh waves and discuss the impact of the thickness of Cu films on the dispersive relationships
A Journey into the City. Migrant Workers' Relation with the Urban Space and Struggle for Existence in Xu Zechen's Early Jingpiao Fiction
In contemporary China, rural-urban migrants constitute a new urban subject with entirely new identity-related issues. This study aims at demonstrating how literature can be a valid field in investigating such evolving subjectivities, through an analysis of Xu Zechen’s early novellas depicting migrants’ vicissitudes in Beijing. Combining a close reading of the texts and a review of the main social problems characterising rural-urban migration in China, this paper focuses on the representation of the identity crisis within the migrant self in Xu’s stories, taking into account the network of meanings employed by the writer to signify the objective and subjective tension between the city and the countryside
Multi-scale U-like network with attention mechanism for automatic pancreas segmentation.
In recent years, the rapid development of deep neural networks has made great progress in automatic organ segmentation from abdominal CT scans. However, automatic segmentation for small organs (e.g., the pancreas) is still a challenging task. As an inconspicuous and small organ in the abdomen, the pancreas has a high degree of anatomical variability and is indistinguishable from the surrounding organs and tissues, which usually leads to a very vague boundary. Therefore, the accuracy of pancreatic segmentation is sometimes below satisfaction. In this paper, we propose a 2.5D U-net with an attention mechanism. The proposed network includes 2D convolutional layers and 3D convolutional layers, which means that it requires less computational resources than 3D segmentation models while it can capture more spatial information along the third dimension than 2D segmentation models. Then We use a cascaded framework to increase the accuracy of segmentation results. We evaluate our network on the NIH pancreas dataset and measure the segmentation accuracy by the Dice similarity coefficient (DSC). Experimental results demonstrate a better performance compared with state-of-the-art methods
News Recommendation With Word-Related Joint Topic Prediction
As the problem of information overload becomes more severe, it has become increasingly difficult for users to browse news that they are interested in. News recommendation is an effective method to alleviate this problem. In news recommendation, accurately obtaining rich semantic news representations and modeling user’s historical interests are long-standing challenges. Based on these two issues, we propose a News recommendation approach with Word-related joint Topic prediction(NWT). The core of our approach is the topic perceptron and the news encoder that emphasizes word relevance. The topic information and word relevance information are fused through joint training, enhancing the abilities of topic prediction and news representation. In the news encoder, we employ multi-head self-attention network to emphasize word relevance, capturing the semantic relationships between any two words in the news title and enhancing the representation of the news. In the topic perceptron, we use the enhanced word relevance-based news representation as input and learn the topic information in the news by assigning weights to different topics. During joint training, the overall news recommendation module obtains the news topic information. Additionally, the user encoder learns the user’s topic preferences and utilizes attention networks to highlight news articles that are more representative of the user’s interests, thereby acquiring a more accurate user representation. We conduct extensive experiments on the MIND dataset, and the results demonstrate that NWT outperforms most existing baseline methods across various evaluation metrics
Expression and characterization of a novel mesophilic protease from metagenomic library derived from Antarctic coastal sediment
National High Technology Research and Development Program (863 program) [2007AA091407]; China Ocean Mineral Resources R&D Association (COMRA) [DYXM-115-02-2-04]A metagenomic cosmid library was constructed, in which the insert DNA was derived from the coastal sediment near Antarctic China Zhongshan Station. One clone (ACPRO001) expressing protease activity was isolated from the library using milk agar plates. Sequencing of the clone revealed a novel protease gene. The amino acid sequence comparison and phylogenetic analysis indicated that it could be classified as a subtilisin-like serine protease, though the highly conserved residue Asp was replaced by Ala. The ACPRO001 protease gene was expressed in pET-His and purified for characterization. The optimal temperature and pH for the activity of the ACPRO001 protease were 60A degrees C and pH 9.0, respectively. The enzyme retained about 73% of residual activity after 2 h incubation at 50A degrees C in the presence of Ca(2+). The presence of Ca(2+) increased the thermostability of ACPRO001 protease obviously. The enzymatic activity was inhibited by 1 mM phenylmethyl sulfonylfluoride (PMSF) and hydrochloride 4-(2-aminoethyl)-benzenesulfonyl fluoride (AEBSF), indicating that it was a serine protease
Improved SIC-SVD Hybrid Precoding Algorithm for Indoor Sub-THz Systems
Emerging terahertz (THz) communication will become the main way of wireless communication in the future, it will also use hybrid precoding which combines analog and digital hybrid precoding like millimeter wave communication systems, to reduce the system energy consumption. Indoor as a main scenario for communication, to better meet the demands for data transmission. In this paper, an improved hybrid precoding method based on successive interference cancelation and singular value decomposition (SIC-SVD) is proposed for indoor Sub-THz communication system with sub-connected structures. However, the introduction of phase shifters imposes constant modulus constraints, making the problem of hybrid precoding difficult to solve directly. The proposed method first decomposes the optimization problem of achievable rates for the system, based on the special structure of sub-connected, into a series of equivalent sub-problems. The algorithm first designs the analog precoding matrix according to the SIC method, after obtaining the designed analog precoding matrix, the algorithm defines an equivalent channel and employs singular value decomposition (SVD) to obtain the digital precoding matrix. The simulation results show that compared with the existing method based on SIC, the proposed algorithm has slightly higher achievable rate and is closer to the optimal full-digital precoding method. At the same time, this paper also presents a simple analysis of the proposed algorithm for imperfect channel state information (CSI) with different accuracy. Simulation results show that the spectral efficiency is also very near to the perfect CSI case when the accuracy of the CSI is 0.9
Research on Priority Evaluation Model of Project Associated Clusters
At present, there are still some urgent problems to be solved, such as repeated reserve projects, unreasonable timing arrangement of investment in project execution, poor effect of capital use and poor process connection. In this paper, through the related cluster demonstration of the comprehensive plan projects, we strengthen the pre-management and control of the reserve projects from the source, and improve the quality and efficiency of the comprehensive plan management. Firstly, this paper classifies the projects based on the perspective of business association, establishes the association cluster, and then constructs the priority evaluation model of the project association cluster with the help of the portfolio management theory, so as to maximize the project benefit
Rapid selection of environmentally friendly layered alkaline-earth metal phosphates as solid lubricants using crystallographic data
Abstract Lubricating technologies are essential for saving energy and identifying effective, environmentally friendly layered materials that meet the demands of solid lubricants is an important direction. Herein, we probed the relationships between load-carrying capacity and crystal structure. The results showed that increasing the sliding resistance of interlayers using corrugated layers increased the load-carrying capacity of layered solid lubricants. This finding expands on the traditional lubrication mechanism of layered materials. Following the rules, rapid selection of layered potassium magnesium and calcium phosphates (K-LMP and K-LCP) as effective solid lubricants was achieved using crystallographic data and strict filtering criteria. In order to prepare materials suitable for lubrication, the synthesis of K-LMP and K-LCP was optimised. These materials could be utilised in the food, textile or marine machinery industries in the future. The developed method could successfully guide the synthesis of application-oriented materials