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Analyzing the important nodes of complex systems by complex network theory can effectively solve the scientific bottlenecks in various aspects of these systems, and how to excavate important nodes has become a hot topic in complex network research. This paper proposes an algorithm for excavating important nodes based on the heat conduction model (HCM), which measures the importance of nodes by their output capacity. The number and importance of a node’s neighbors are first used to determine its own capacity, its output capacity is then calculated based on the HCM while considering the network density, distance between nodes, and degree density of other nodes. The importance of the node is finally measured by the magnitude of the output capacity. The similarity experiments of node importance, sorting and comparison experiments of important nodes, and capability experiments of multi-node infection are conducted in nine real networks using the SIR model as the evaluation criteria. The effectiveness of the HCM is demonstrated through a comparison with eight other algorithms for excavating important nodes.

Aim The study aimed to identifying critical long non-coding RNAs (lncRNAs) and constructed a prognostic signature to optimize prognosis predication of patients with Stomach Adenocarcinoma (STAD). Background STAD is a common malignant tumor with high metastasis rate and low survival rate. LncRNAs participate in the regulation process of epithelial-mesenchymal transition (EMT) and development of STAD. Methods RNAseq data was obtained from TCGA-STAD, while 200 EMT-associated genes (EAGs) from ‘HALLMARK_EPITHELIAL_MESENCHYMA-L _TRANSITION’ gene set. Differentially expressed EAGs and EMT-associated lncRNAs (EALs) were identified. Moreover, Lasso Cox regression analysis was used to construct a signature of differentially expressed EALs, and univariate and multivariate analyses, Kaplan-Meier analysis, receiver operating characteristic curve (ROC) analysis and nomogram were conducted to predict its prognostic value. Enrichment functional analysis was performed. Quantitative Real-Time PCR (qRT-PCR) was used to determine lncRNAs expressions in cell lines. Results A total of 52 differentially expressed EAGs and 320 EALs were identified in this study. Meanwhile, 16 EALs was used to construct the signature, and further analysis indicated that it had high prognostic value for STAD patients. Enrichment functional analysis revealed the signature was correlated to tumor immunity in STAD. Moreover, three novel EALs expressions were confirmed in cell lines. Conclusion A novel survival signature was established to predict and evaluate prognosis of STAD patients.

As the prognosis of early gastric cancer (EGC) is significantly better than that of advanced gastric cancer (AGC), the development of biomarkers to monitor the progression of chronic atrophic gastritis (CAG) to gastric cancer (GC) is essential.Stomach tissue miRNA and mRNA sequences from patients with chronic non-atrophic gastritis (CNAG), CAG, precancerous lesions of gastric cancer (PLGC), and GC were analyzed. A publicly available GC-related miRNA microarray dataset was obtained from the Gene Expression Omnibus database. Spearman's correlation and differential gene analyses, and clinical validation were used to identify novel miRNAs correlating with CAG progression to GC. miRNA targets were predicted using weighted gene co-expression analysis and databases. A dual-luciferase reporter assay was performed to check for direct interaction between miR-196a-5p and ACER2. The CCK-8 and wound healing assays, and flow cytometry were performed to evaluate cell proliferation, migration, and apoptosis.miR-196a-5p was correlated with CAG progression to GC. Overexpression of miR-196a-5p promoted GC cell proliferation and migration and inhibited apoptosis, whereas suppression of miR-196a-5p exerted the opposite effect. Based on the prediction and luciferase assays, ACER2 was identified as the target of miR-196a-5p. ACER2 was downregulated in GC cell lines. Knockdown of ACER2 increased GC cell proliferation rates and migration ability and inhibited apoptosis, while ACER2 overexpression led to the opposite effect.miR-196a-5p correlated with CAG progression to GC and induced malignant biological behaviors of GC cells by targeting ACER2, providing a novel monitoring biomarker and target for GC prevention.

Yanhua Yan,1 Kechao Nie,2 Junhui Zheng,1 Xiaotao Jiang,1 Yuancheng Huang,1 Zhihua Zheng,1 Yi Wen,3 Peiwu Li3 1The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, 510000, People’s Republic of China; 2Department of Integrated Traditional Chinese & Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, People’s Republic of China; 3Department of Gastroenterology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510000, People’s Republic of ChinaCorrespondence: Peiwu Li; Yi Wen Email doctorlipw@gzucm.edu.cn; 421491922@qq.comBackground: Stomach adenocarcinoma (STAD) is the most common gastrointestinal cancer and is associated with high mortality worldwide. Endothelin receptor type A (EDNRA) is associated with guanine-nucleotide-binding (G) proteins and plays important roles in cellular processes and various diseases.Purpose: To investigate the prognosis value of EDNRA expression and its correlation with immune infiltrates in patients with STAD.Methods: The association between clinical characteristics and EDNRA expression in STAD was analyzed using the Wilcoxon signed-rank test and logistic regression. The Kaplan–Meier plotter analysis and Cox regression were constructed to evaluate the influence of EDNRA on prognosis, and a receiver operating characteristic (ROC) curve and nomogram were constructed. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were conducted to analyze the correlation between EDNRA and immune infiltrates. In addition, Oncomine, TIMER databases and qRT-PCR of STAD cell lines were used to verify the EDNRA expression in STAD.Results: Our results revealed that EDNRA expression was significantly higher in patients with STAD than normal gastric tissues, and the results have been confirmed by RT-qPCR. KM-plotter analysis revealed that patients with STAD had shorter OS, FP, and PPS (P< 0.001). Multivariate Cox analysis further confirmed that high EDNRA expression was an independent risk factor for OS in patients with STAD. Moreover, other clinicopathologic features were related with worse prognosis in STAD, including age, lymph nodes metastases and primary outcome. More importantly, ROC analysis also confirmed the diagnostic value, and a prognostic nomogram involving age, T, M, N classification, pathologic stage, residual tumor and EDNRA was constructed. GSEA revealed that high EDNRA expression was correlated with immunoregulatory interactions between lymphoid and non lymphoid cells pathways, natural killer cell activation involved in immune response, interleukin 1 receptor binding and pathways in cancer, and ssGSEA showed that EDNRA is correlated with macrophages and NK cells.Conclusion: Collectively, EDNRA can be an independent prognostic biomarker and correlated with immune infiltration in stomach adenocarcinoma.Keywords: EDNRA, STAD, bioinformatics, prognosis

Background. Gastric cancer (GC), an extremely aggressive tumor with a very different prognosis, is the third leading cause of cancer-related mortality. We aimed to construct a ferroptosis-related prognostic model that can be distinguished prognostically. Methods. The gene expression and the clinical data of GC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO). The ferroptosis-related genes were obtained from the FerrDb. Using the “limma” R package and univariate Cox analysis, ferroptosis-related genes with differential expression and prognostic value were identified in the TCGA cohort. Last absolute shrinkage and selection operator (LASSO) Cox regression was applied to shrink ferroptosis-related predictors and construct a prognostic model. Functional enrichment, ESTIMATE algorithm, and single-sample gene set enrichment analysis (ssGSEA) were applied for exploring the potential mechanism. GC patients from the GEO cohort were used for validation. Results. An 8-gene prognostic model was constructed and stratified GC patients from TCGA and meta-GEO cohort into high-risk groups or low-risk groups. GC patients in high-risk groups have significantly poorer OS compared with those in low-risk groups. The risk score was identified as an independent predictor for OS. Functional analysis revealed that the risk score was mainly associated with the biological function of extracellular matrix (ECM) organization and tumor immunity. Conclusion. In conclusion, the ferroptosis-related model can be utilized for the clinical prognostic prediction in GC.

Abstract Since a novel coronavirus was discovered from a cluster of patients with emerging pneumonia of unknown etiology in Wuhan, China, it has spread rapidly through droplet and contact transmission. Recently, the novel coronavirus pneumonia which was named COVID-19 by the World Health Organization (WHO) has been raised as a worldwide problem. Radiological examinations were confirmed as effective methods for the screening and diagnosis of COVID-19. It is reported that some radiologists and radiological technologists were infected when giving examinations to the patients with COVID-19. In order to reduce the infection risk of medical staff in radiology department, we summarized the experience on prevention and control measures in radiology department for COVID-19, aiming to guide the prevention and practical work for radiologists and radiological technologists. Key Points • The novel coronavirus spreads rapidly through droplet and contact transmission. • Radiologists and radiological technologists were possibly infected by patients. • Prevention and control measures in radiology department for COVID-19 are important.

The graphene/PPy fiber nanocomposites were synthesized via a facile one-step solvothermal method. Moved by electrostatic interaction and hydrogen bonding between the tetra-functional NiPcTs and PPy chain, a self-sorting mechanism acts to align the PPy chains to form one-dimensional PPy nanofibers on graphene. The in situ grown nanostructure possesses a good interconnectivity and porosity facilities. The well-designed microstructure of the composites achieves a synergistic effect between the graphene and PPy and shows a good electrochemical performance for supercapacitors of 316 F g−1 even at a high current density of 5 A g−1.

Background: As early gastric cancer (EGC) has a far better prognosis than advanced gastric cancer (GC), early diagnosis and treatment are essential. However, understanding the mechanism of the process from gastric precancerous lesion (GPL) becoming EGC has made little advances. Besides, biomarkers that can monitor the progression of GPL-to-GC are still much insufficient.Methods: Key gene modules associated with GPL progression to EGC were identified by integrating two GPL-related data sets, GSE55696 and GSE130823, using the WGCNA method. Combining with the TCGA-STAD cohort, hub genes were identified. Immunofluorescence was conducted to validate the expression. To explore the implication of hub genes in GPL malignant transformation, a correlation test was conducted to identify their co-expression genes, co-expression cytokines, and co-expression immune cells. Least absolute shrinkage and selection operator (LASSO) Cox regression was applied to shrink CXCR4-related predictors and construct a prognostic model. Functional enrichment was applied for exploring the potential mechanism.Results: The green module in GSE55696 and the yellow module in GSE130823 were regarded as key gene modules associated with GPL progression to EGC, and 219 intersection genes from them were mainly enriched in critical immune biological processes. Combining with the TCGA-STAD cohort, CXCR4 was identified as a novel biomarker correlated with the malignant transformation of GPL, the positive rate of which was increased with GPL progression according to immunofluorescence. CXCR4 co-expression genes were found mainly involved in regulation of actin. CXCR4 co-expression cytokines were enriched in regulation of chemotaxis, cell chemotaxis, mononuclear cell migration, leukocyte chemotaxis, etc. As for co-expression immune cells, the expression level of CXCR4 was positively correlated with the abundance of macrophages but negatively correlated with that of effector memory T cells and NKT cells during GPL malignant transformation. In addition, the CXCR4-related prognostic model was able to predict the prognosis of GC and serve as an independent predictor for overall survival (OS).Conclusions: CXCR4 was a novel biomarker correlated with malignant transformation of GPL and played a vital role in the control of tumor immunity. CXCR4 is possible to serve as a therapeutic target for malignant transformation of GPL.

In recent years, deep-learning schemes have been widely and successfully used to diagnose bearing faults. However, as operating conditions change, the distribution of new data may differ from that of previously learned data. Training using only old data cannot guarantee good performance when handling new data, and vice versa. Here, we present an incremental learning scheme based on the Repeated Replay using Memory Indexing (R-REMIND) method for bearing fault diagnosis. R-REMIND can learn new information under various working conditions while retaining older information. First, we use a feature extraction network similar to the Inception-v4 neural network to collect bearing vibration data. Second, we encode the features by product quantization and store the features in indices. Finally, the parameters of the feature extraction and classification networks are updated using real and reconstructed features, and the model did not forget old information. The experiment results show that the R-REMIND model exhibits continuous learning ability with no catastrophic forgetting during sequential tasks.

Gout is an inflammatory joint disease caused by monosodium urate (MSU) crystals; however, the mechanism underlying MSU-induced inflammation is unclear. Previous research has suggested that inflammation or cancer can drive the expansion of myeloid-derived suppressor cells (MDSCs). In this study, the role of MDSCs in MSU-induced gout inflammation was evaluated. A total of 28 patients with gout, and 20 healthy controls were recruited for the study. MDSCs, and their functions, were analyzed by flow cytometry and a T cell co-culture assay, respectively. We observed a higher frequency of PMN-MDSCs, and a stronger immunosuppressive function, in patients with gout compared to the controls. Moreover, circulating PMN-MDSCs were positively correlated with pathological indicators, including uric acid and C-reactive protein levels. We also demonstrated that MSU can induce significant PMN-MDSC expansion, using in vivo and in vitro experiments. Finally, MSU-induced PMN-MDSCs produced higher levels of IL-1β, which mediated gout inflammatory progression. Our results demonstrate that MSU modulates the expansion and suppressive function of PMN-MDSCs, providing insights into a novel mechanism underlying the pathogenesis of MSU-induced gout. Thus, MDSCs may be useful for the development of novel therapeutic strategies for the prevention and treatment of gout.

Background: With the coming of immunotherapy era, immunotherapy is gradually playing a vital role in the treatment of gastric cancer (GC). However, immune microenvironment in gastric precancerous lesions (GPL) and early gastric cancer (EGC) still remain largely unknown. Methods: From the Gene Expression Omnibus (GEO), data of three GPL-related gene expression profiles (GSE55696, GSE87666 and GSE130823) and three GC data sets with clinical information (GSE66229, GSE15459 and GSE34942) were downloaded. Three GC data were consolidated as a GC meta-GEO cohort. RNA sequencing data of 375 stomach adenocarcinoma (STAD) samples with clinical information from The Cancer Genome Atlas (TCGA) and 175 stomach normal controls (NC) from Genotype-Tissue Expression (GTEx) datasets were obtained from the UCSC Xena browser, which were merged as a STAD TCGA-GTEx cohort. The abundance of immune cells in above datasets were estimated using Immune Cell Abundance Identifier (ImmuCellAI) algorithm. Firstly, key immune cells associated with GPL progression to EGC were identified using one‐way analysis of variance (ANOVA) test as well as Spearman’s correlation test in two GPL and EGC related datasets (GSE55696 and GSE87666). Then, weighted gene co-expression analysis (WGCNA) and pathway enrichment were adopted to identify hub gene co-expression network. Candidate hub genes were identified based on network parameters. Combining expression comparison and prognosis analysis in STAD TCGA-GTEx and GC meta-GEO cohort, Genes with significant difference between GC and NC and prognostic significance were identified as real hub genes. Correlation between real hub genes and key immune cells was evaluated using Pearson’s correlation test. The pattern of key immune cells infiltration and hub genes expression as well as their correlation during GPL progression to EGC were validated in an independent cohort GSE130823. The correlation was also verified in the GC datasets (STAD TCGA-GTEx and GC meta-GEO cohort).Results: Combining with GSE55696 and GSE87666 cohorts, NKT cell was found gradually decreased with GPL progression and negatively correlated with tumorigenesis significantly. It was identified as the key immune cell associated with GPL progression to EGC based on one-way ANOVA test and Spearman’s correlation test. Further verification indicated that it was significantly downregulated in GC in meta-GEO cohort and STAD TCGA-GTEx cohort. According to the results of WGCNA and KEGG pathway enrichment, green modules in GSE55696 and GSE87666 cohorts were considered as hub modules as they were negatively associated with NKT cell infiltration at a significant level and their overlapping genes were significantly enriched in immune-related pathways. In further screening, CXCR4 was found to be significantly upregulated in GC and had a poor prognosis, which was determined as the real hub gene. CXCR4 expression was found increased with GPL progression, positively correlated with tumorigenesis and negatively correlated with NKT cell infiltration significantly. The pattern of NKT cell infiltration and CXCR4 expression as well as their relationship stay consistent in the independent GPL cohort GSE130823. The negative correlation of CXCR4 with NKT cell infiltration was also confirmed in GC datasets (GC meta-GEO cohort and STAD TCGA-GTEx cohort).Conclusion: CXCR4 and NKT cell are possible to serve as biomarkers in monitoring GPL progression to EGC. Besides, CXCR4 may be involved in regulating NKT cell infiltration during GPL progression to EGC, which may provide a new immunotherapeutic target.

In this work, we report the synthesis of holmium(III)-doped carbon nanodots (HoBCDs) as fluorescence/magnetic resonance (FL/MR) dual-modal imaging probes via a facile hydrothermal process using citrate acid (CA), branched-polyethylenimine (BPEI) and diethylenetriamine pentaacetic acid hydrate holmium(III) dihydrogen salt (Ho-DTPA) as carbon source, passivating reagent and holmium source, respectively. The thus prepared HoBCDs exhibited ultra-small particle size (∼4 nm), high water solubility and bright fluorescence with an absolute quantum yield of 8%. Additionally, grey-scaled T1-weighted images of HoBCDs solution appeared to be apparently brighter than that of deionized water and un-doped blue carbon nanodots (BCDs) solution. In addition, in vitro toxicity assay validated superior biocompatibility of HoBCDs. Using HeLa cells as models, HoBCDs-treated cells were observed to emit blue fluorescence located both in plasma and nucleus, and presented positive contrast enhancement in T1-weighted images, suggesting their potentials for practical biomedical applications.

Fluorescence (FL)/magnetic resonance (MR) dual-modal imaging nanoprobes are significant not only for cutting edge research in molecular imaging, but also for clinical diagnosis with high precision and accuracy. However, synthesis of FL/MR dual-modal imaging nanoprobes that simultaneously exhibit strong fluorescent brightness and high MR response, long-term colloidal stability with uniform sizes, good biocompatibility and a versatile surface functionality has proven challenging. In this study, the well-defined core–shell structured Gd3+ chelate-conjugated fluorescent polymer nanoparticles (Gd-FPNPs) that consist of rhodamine B (RB)-encapsulated poly(methyl methacrylate) (PMMA) cores and Gd3+ chelate-conjugated branched polyethylenimine (PEI) shells, are facilely synthesized via a one-step graft copolymerization of RB-encapsulated MMA from PEI-DTPA-Gd induced by tert-butyl hydroperoxide (TBHP) at 80 °C for 2 h. The mild synthesis route not only preserves the chemical environment for Gd3+ coordination, but a...

In this study, an efficient and mild approach is reported for the facile synthesis of a carbon quantum dot (CQD)-based dual-modal fluorescence (FL)/magnetic resonance (MR) imaging probe by doping Gd(iii) into CQDs through a one-pot pyrolysis process at low temperature. The as-prepared Gd-encapsulated CQDs (GCDs), which have an average diameter of ∼15 nm, are highly water-soluble. The GCDs are observed to have a high MR response with a longitudinal relaxation of 57.42 mM-1 s-1 and a strong fluorescence brightness with an absolute quantum yield of 40% while containing only 1.0% (w/w) of Gd3+ content. Stemming from the minimum Gd-doping and the inert carbon coating, GCDs exhibit excellent biocompatibility and blood compatibility. Dual-modality bioimaging applications of GCDs are successfully demonstrated by the use of HeLa cells and mice as models, revealing their great potential in fundamental biomedical research studies and even clinical fields such as fluorescence-guided surgery and dual-modal FL/MR imaging of blood vessels.

In view of the current situation of increasing garbage production and insufficient awareness of garbage classification in China. Based on the cultivation of children's awareness of garbage classification, this paper designs a garbage classification education platform for children using image recognition technology. The platform takes raspberry pi as the main control module, uses machine vision to perform image acquisition, and cooperates with a rotary table for multi-angle recognition. At the same time, the label database and education information database are established, and the relevant education information is displayed through the display, LED lamp, and other ways. Through the combination of pictures, sound, and animation, children are educated about garbage classification and knowledge.

Multi-modal imaging probes through synergistically combining two or more imaging modalities into single nanoparticle, offer possibilities to address multiple issues such as resolution, sensitivity, and tissue penetration. In this study, we report a facile strategy to synthesize a dual-modal fluorescence/magnetic resonance (MR) imaging nanoprobe with bright fluorescence and significantly improved relaxivity, where Gd 3+ ions are simply chelated onto the outer surface of the cyclic DTPA dianhydride (cDTPAA) functionalized carbon quantum dots (CQDs). Transmission electron microscopy, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, and zeta potential measurements validated the successful preparation of CQD–DTPA–Gd. The surface conjugation of CQDs with cDTPAA and further Gd 3+ chelation does not perturb core optical properties of CQDs, and the thus prepared CQD–DTPA–Gd contain minimum Gd 3+ content (8.06%, w/w), while exhibiting significantly improved longitudinal relaxivity (56.72 mM −1 s −1 ). Excellent water solubility, good cell-membrane permeability and negligible cytotoxicity make CQD–DTPA–Gd an ideal dual-modal fluorescence/MR imaging probe, suggesting its potential and significance in practical bioimaging applications and medical translation in the future.

The aim of this study was to compare the coronary artery visibility and radiation dose in infants with CHD on cardiac 128-slice CT and on cardiac 64-slice CT. The images of 200 patients were analyzed in this study, 100 patients were selected randomly from a group of 789 infants (

BACKGROUND Squamous cell carcinoma (SCC) is the second most common type of skin cancer, for which non- or mini-invasive treatment is of critical importance. 5-aminolevulinic acids based photodynamic therapy (ALA-PDT) is a mini-invasive approach that causes focal tumor cell injury, apoptosis, and necrosis through light sensitivity. The efficacy of combining ALA-PDT and surgery in treating SCC, however, has not been demonstrated. MATERIAL AND METHODS A total of 60 SCC patients were randomly assigned into attrition plus ALA-PDT group (experimental group) and single ALA-PDT treatment group (control group). Clinical efficacy, recurrence rate, and adverse effects were analyzed in conjunction with H&E staining and immunohistochemistry (IHC) staining for p53 expression. RESULTS The overall effective rate of the experimental group was 73.3%, which was significantly higher than that of the control group (46.7%). The experimental group also had a lower recurrence rate (16.6% versus 30.0%, p

We aimed to evaluate the diagnostic performance of CT and MRI for distinguishing intraductal papillary neoplasm of the bile duct (IPNB) from cholangiocarcinoma (CC) with intraductal papillary growth (IPG). Forty-two patients with either IPNB or CC with IPG proven by histopathology were independently reviewed in retrospect. Strict criteria for diagnosis of IPNB included presence of the designated imaging features as follows: local dilatation of the bile duct, nodule within the dilated bile duct, growing along the interior wall of bile duct. Any lesion that was not consistent with the criteria was classified as CC with IPG. Sensitivity, specificity, positive and negative predictive values for characterization of IPNB were calculated, and k test was used to assess the level of agreement. Two imaging reviewers correctly identified 21 of 26 (80.8 %) and 22 of 26 (84.6 %) IPNB cases, respectively. Alternatively, they correctly identified 14 of 16 (87.5 %) and 15 of 16 (93.8 %) CC with IPG, respectively. Agreement between the two reviewers was perfect (k = 0.81) for the diagnosis of IPNB and differentiation from CC with IPG. By using our designated diagnostic criteria of CT and MRI, IPNB can be accurately identified and possible to be distinguished from CC with IPG. • IPNB can accurately be identified by using defined diagnostic criteria at CT/MRI. • IPNB has some characteristic CT and MR imaging features. • IPNB is a rare entity; up until now it might have been misdiagnosed.

The purpose of this study was to estimate patient doses during coronary angiography (CA) and different complex percutaneous transluminal coronary angioplasty (PTCA) procedures in China. Consecutive 290 patients (90 CA, 200 PTCA) with known or suspected coronary artery disease were enrolled prospectively into six groups. Differences in patient doses among the six groups were analysed, and the patient doses observed in this study were compared with the recent literature. The median dose area product values were 27.0 and 195.0 Gy cm(2) for CA and PTCA, respectively. The patient doses during CA were similar to those reported by other authors, while those during PTCA were higher. The differences in radiation doses depended on the complexity of the procedures. Enhanced knowledge of radiation doses may help cardiologists implement radiation-sparing procedures to minimise patient exposure.

With the rapid development of China's economy in recent years, the scale of students has expanded gradually, which has led to many new problems, including the problems of the quality and the quantity of teachers, and the teaching facilities being insufficient. The assessment of teaching quality is one of the most important aspects of teaching management, which come to the attention of every university. Therefore, it has become the current focus in the research of university teaching. At the same time, the traditional method of teaching quality assessment has not been able to deal with the phenomenon of big data in the field of education. As a new technology, cloud computing provides a broad space for the development of a new model in the aspects of hardware environment construction, software resource development, network teaching implementation and personal knowledge management. In order to effectively deal with the challenges of big data processing in the field of education, this paper proposes a GA-SVM teaching quality assessment algorithm which is based on MapReduce. Through the design of a map function and reduce function, this paper realizes the parallelization of the GA-SVM algorithm and the selection of the main parameters. Secondly, this paper uses a genetic algorithm to optimize the penalty coefficient and kernel parameters of SVM, and then solves the problem of difficulty in determining the parameters of support vectors. In addition, we improve the sensitivity of the search through the method of logarithmic transformation, and speed up the convergence rate of the GA model. Finally, we compare the parallel algorithm and the serial algorithm on the Hadoop platform. The results of experiments show that the GA-SVM based on MapReduce is suitable for teaching quality assessment under the environment of big data.

The teaching quality of the higher school is not only related to the development of the students, but also related to the future of our country. It can find out the problems of the higher education for colleges to evaluate the teaching quality of the higher education. And it can provide the reference for the students to apply for the colleges. In this paper, we combine the grey correlation with TOPSIS method and provide the improved Grey-TOPSIS method. Then, we evaluate the teaching quality of the higher education. The results show that the comprehensive evaluation model can evaluate reasonably the teaching quality of the higher education. And it proves the validity and reliability of the method.

This study was aimed to evaluate the effects of different echo time (TE) on the liver fat quantification using proton magnetic resonance spectroscopy (1H-MRS). Liver 1H-MRS was performed on 24 adult male wistar rats on a 1.5 T superconductor MR scanner. Spectrums were collected with a TR of 1500 ms and different TE of 35, 45, 55, 65, 75, 85, 95, 105, 144 ms, respectively. The water and lipid peaks, baseline of the spectrum and lipid to water ratio were evaluated. With the increment of TE, the amplitude and integrated area of the water and lipid peaks decreased, and the baseline of the spectrum and the lipid to water ratio became unstable. The lipid to water ratio determined by 1H-MRS was highly correlated with the liver fat content determined by pathological analysis at TE between 35 and 55 ms (r0.9) and poorly to moderately correlated at TEor =65 ms (r0.9). The results indicated that long TE would compromise the liver fat quantification using 1H-MRS, and therefore short TE was strongly recommended for liver fat quantification.

As the size keeps increasing and applications keep developing, current Internet and TCP/IP are facing severe technical challenges. It is not secure, hard to use, and unpredictable. The shortages of architecture of current Internet have created barriers rather than stimulant to further developments. To resolve the problems of current Internet, this paper proposes a new type of non-layered network architecture, which is called Service Combination based Network Architecture.

Service Unit based Network Architecture (SUNA) is a non-layered network architecture, which could resolve the problems of layered architecture such as reduplicate functions of different layers and poor expansibility due to fixed layers [1][2]. It uses end-to-end Virtual Circuit (VC) structure to transmit data. In order to guarantee reliable data transmission for SUNA, we propose an improved sliding window protocol called Sliding Window protocol with Immediate Retransmission (SWIR). After describing the mechanism of SWIR, we gives a Colored Petri Nets (CPN) model for it to verify the validity, integrity and feasibility of the protocol by analyzing the state space of the model.

This study aims to evaluate the multidetector computed tomography (CT) imaging features in differentiating exophytic renal angiomyolipoma (AML) from retroperitoneal liposarcoma. We retrospectively enrolled 42 patients with confirmed exophytic renal AML (31 patients) or retroperitoneal liposarcoma (11 patients) during 8 years period to assess: renal parenchymal defect at site of tumor contact, supply from branches of renal artery, tumoral vessel extending through the renal parenchyma, dilated intratumoral vessels, hemorrhage, non-fat-containing intratumoral nodules with postcontrast enhancement, calcification, renal sinus enlargement, anterior displacement of kidneys, and other associated AML. Renal parenchymal defect, renal arterial blood supply, tumoral vessel through the renal parenchyma, dilated intratumoral vessels, intratumoral/perirenal hemorrhage, renal sinus enlargement, and associated AML were seen only or mainly in exophytic renal AML (all P value