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A multi-attribute group decision-making (MAGDM) method based on intuitionistic fuzzy preference information is proposed for the multi-attribute intuitionistic fuzzy group decision-making problem where the decision-makers weight and attribute weight are completely unknown and the decision-maker has preference information for the scheme. Firstly, an intuitionistic fuzzy interval judgment matrix is established to describe the original data of the key decision indicators for multiple network public opinion emergencies that erupt simultaneously. Secondly, the attribute weights are determined based on the improved intuitionistic fuzzy entropy construction method, and the expert weights are determined by using objective decision information, taking into account the intuitionistic fuzzy entropy of decision matrix. MAGDM can not only synthesize experts' professional experience in different aspects, but also avoid experts' decision-making errors caused by insufficient domain knowledge. It is necessary to continuously adjust the expert weight based on decision-making information to make the comprehensive decision-making information more accurate. Thirdly, a scheme preference model and an attribute weight optimization model are established to determine the ranking method of intuitionistic fuzzy interval values. Then, a modified distance measure of intuitionistic fuzzy sets (IFSs) is introduced to make the evaluation result more accurate and reasonable when it comes to solving the deviation between the evaluation value and ideal solution of each scheme. Finally, the effectiveness and practicability of the proposed decision-making method are verified by an example of emergency crisis severity, It assists decision makers in selecting and implementing the optimal emergency response plan in a timely and efficient manner, which improves the emergency treatment efficiency of network public opinion crisis, helps emergency departments to better deal with the network public opinion crisis, improves the ability of public opinion guidance and control, and provides a new method and idea for multi-attribute intuitionistic fuzzy group decision-making problem.

Focusing on risky decision-making problems taking the interval number of normal distribution as the information environment, this paper proposes a decision-making method based on the interval number of normal distribution. Firstly, the normalized matrix based on the decision maker&rsquo, s attitude is obtained through analysis and calculation. Secondly, according to the existing properties of standard normal distribution, the risk preference factors of the decision makers are considered to confirm the possibility degree of each scheme. The possibility degree is then used for establishing a possibility degree matrix and, consequently, sequencing of all schemes is conducted according to existing theories of possibility degree meaning and the value size of possibility degree. Finally, the feasibility and validity of this method is verified through calculation example analysis.

Objective: To investigate the effects of sublingual dust mite drops on Pulmonary function, immunoglobulin and T lymphocyte subsets in patients with allergic rhinitis. Methods: One hundred and ten patients with allergic rhinitis treated in our hospital from June 2014 to December 2016 were retrospectively analyzed. According to the treatment methods, the patients were divided into control group and observation group, with 53 cases in control group and 57 cases in observation group. The patients were given oral kastitium and risperidone nasal spray. The observation group was given sublingual dust mite droplet on the basis of the control group. Afterwards, the Pulmonary function, immunoglobulin and T lymphocyte subsets Group level testing. Results: After treatment, the levels of FEV1, FVC and PEF increased significantly in the two groups. After treatment, the levels of FEV1, FVC and PEF in the observation group were (2.97±0.09) L, (3.96±0.07) L and (6.61±0.03) L/S, were significantly higher than the control group; After treatment, the levels of sIgE and T-IgE in both groups were significantly decreased, sIgG4 levels were significantly increased,After treatment, the levels of sIgE and T-IgE in the observation group were (12.22±1.08) kUA/L and (155.32 ± 9.51) kUA/L, respectively, which were significantly lower than those in the control group,The level of sIgG4 was (434.17±12.31) mg/L, which was significantly higher than that of the control group; After treatment, the levels of CD3+, CD4+ and CD4+/CD8+ in both groups were significantly higher than those before treatment, and the levels of CD8+ in the two groups were significantly lower than those before treatment. The levels of CD3+, CD4+ and CD4+/CD8 in the two groups were (65.90±2.11)%, (39.18±0.33)% and (1.75±0.07), respectively, were significantly higher than that of the control group after treatment, the level of CD8+ was (24.13±0.77)%, which was significantly lower than that of the control group Significance. Conclusion: Sublingual dust mite drops can effectively improve pulmonary ventilation in patients with allergic rhinitis, regulate patient immune function, a significant effect, worthy of further clinical application.

Immunotherapeutic agents have demonstrated encouraging signs of clinical utility in non-Hodgkin lymphoma. The goal of this study is to analyze the immune characteristics of Chinese patients with diffuse large B-cell lymphoma (DLBCL) to inform the development of immunotherapies in this patient population. Tumor samples from 211 DLBCL patients were analyzed for cell of origin (COO) and immune characteristics using the NanoString platform as well as MYC protein expression through immunohistochemistry. Lower incidence of the germinal center B-cell (GCB) subtype (93/211, 44.1%) was observed in this cohort. Compared to the GCB subtype, the activated B-cell (ABC) subtype was associated with significantly increased expression of multiple pro-inflammatory gene signatures and decreased expression of anti-inflammatory gene signatures. Instead of affecting the pro-inflammatory genes, MYC protein overexpression showed a negative correlation with the expression of T-cell receptor (TCR) and T regulatory genes as well as the OX40 gene. Regardless of COO, higher PD-L1 or IDO1 gene expression correlated with increased expression of T effector and Interferon-γ gene signatures while the expression of multiple oncogenes including ACTR3B, ERBB2, AKT2 and SMARCD1 was down-regulated. Our findings may thus be helpful in guiding further development of immunotherapies for the different subsets of Chinese DLBCL patients., Highlights • The ABC subtype has higher pro-inflammatory gene expression than the GCB subtype. • MYC protein expression correlates with lower TCR and T regulatory gene expression. • Higher PD-L1 or IDO1 gene expression indicates more inflammatory phenotypes. The revolutionary efficacy of immunotherapies in some solid tumors has prompted much enthusiasm for applying such treatments in lymphomas including diffuse large B-cell lymphoma (DLBCL). To help inform and guide the drug development efforts in this field, it is important to gain a deep understanding of immune characteristics of DLBCL patients. Currently such data are lacking, especially in Chinese patients. NanoString is a high-throughput, easy-to-use platform that allows accurate quantification of the mRNA expression of hundreds of genes simultaneously. In addition, there is a commercialized DLBCL subtying assay, Lymph2Cx, available on this platform. Therefore, we used mainly the NanoString platform to analyze tumor samples from 211 Chinese DLBCL patients to understand their immune characteristics.

A large number of viruses can individually and concurrently cause various respiratory illnesses. Metagenomic sequencing using next-generation sequencing (NGS) technology is capable of identifying a variety of pathogens. Here, we describe a method using a large panel of oligo probes to enrich sequence targets of 34 respiratory DNA and RNA viruses that reduces non-viral reads in NGS data and achieves high performance of sequencing-based pathogen identification. The approach can be applied to total nucleic acids purified from respiratory swabs stored in viral transport medium. Illumina TruSeq RNA Access Library procedure is used in targeted sequencing of respiratory viruses. The samples are subjected to RNA fragmentation, random reverse transcription, random PCR amplification, and ligation with barcoded library adaptors. The libraries are pooled and subjected to two rounds of enrichments by using a large panel of oligos designed to capture whole genomes of 34 respiratory viruses. The enriched libraries are amplified and sequenced using Illumina MiSeq sequencing system and reagents. This method can achieve viral detection sensitivity comparable with molecular assay and obtain partial to complete genome sequences for each virus to allow accurate genotyping and variant analysis. Electronic supplementary material: The online version of this chapter (10.1007/978-1-4939-8682-8_10) contains supplementary material, which is available to authorized users.

The name ambiguity problem affects the accuracy of the web search, document retrieval, and information fusion. A lot of work has been done to solve the name disambiguation problem for publication or paper, but we propose a model to solve this problem for the National Natural Science Foundation of China fund. In this paper, we propose a probabilistic Markov random fields framework to solve the problem of the National Natural Science Foundation of China fund name disambiguation. We define an objective function and use parameters learning algorithm to get the suitable parameters. Experimental results indicate that our approach significantly outperforms other different traditional clustering methods.

This article describes a decision analysis method with attribute correlation and attribute values of interval-valued intuitionistic fuzzy numbers (IVIFN). This considers the correlation between attributes and undetermined attribute weight information was put forward against the case where solution attribute values are interval-valued intuitionistic fuzzy numbers. To achieve a comprehensive consideration of the undetermined evaluation attribute weight information, experts' positive and negative ideal solutions against each attribute are taken as reference points, attribute weight is obtained via decision making trial and evaluation laboratory (DEMATEL) method according to the direct relation matrix provided by experts against attribute sets. On this basis, evaluation information is aggregated by using weighted arithmetic average operators. Then, the closeness degree formula of interval-valued intuitionistic fuzzy numbers relative to the maximum IVIFN is provided by combining the Euclidean distance of IVIFN, thus determining closeness degree and making an ordering of all solutions. Finally, the feasibility and validity of the method proposed in this study are verified via a case analysis of the best information system decision-making.

C7H6BrN5, orthorhombic, Acam (no. 64; unconventional setting of Cmce formerly known as Cmca), a = 12.3735(8) Å, b = 20.8690(11) Å, c = 6.8385(6) Å, V = 1765.9(2) Å3, Z = 8, R gt(F) = 0.0471, wR ref(F 2) = 0.1152, T = 293(2) K.