Influence of “Internet plus” based continuous nursing intervention on hemodialysis self-management ability of patients with uremia and its countermeasures

Objective: To analyze the impact of “Internet Plus”oriented continuous nursing intervention on hemodialysis self-management ability (HSMA) of patients with uremia and its countermeasures.Methods: 60 uremia patients admitted to hemodialysis in the hospital from January to December 2018 were selected as the control group (using routine continuous nursing intervention); 60 uremia patients admitted to hemodialysis from January to December 2019 were also selected as the observation group (using "Internet Plus"oriented continuous nursing intervention); the changes in the score values of the two groups of patients according to the self-management scale (SMSH) and chronic disease health literacy after intervention respectively. Results: After intervention，the self-management score of the patients in the observation group in terms of problem solving，emotional processing and self-care was higher than that of the control group (P<0.05)，and the score value in terms of information acquisition ability，improvement of health willingness, communication and interaction ability was higher than that of the control group (P<0).0.05).Conclusion:the continuity of nursing intervention based on “Internet plus”self-management enhances the self-management ability of patients with uremic hemodialysis and improves their health literacy

An oral vaccine against CVA16 (Coxsackievirus A16) was developed by constructing a recombinant Lactococcus lactis

Purpose: To develop an oral vaccine against CVA16 (Coxsackievirus A16) by constructing a recombinant Lactococcus lactis that expresses VP1 from CVA16.Method: An oral CVA16 vaccine was prepared by expressing CVA16 VP1 protein with Lactococcus lactis. CVA16 VP1 gene was incorporated into a Lactobacillus expression vector, namely, pNZ8148, and then expressed in NZ9000, a food-grade lactic acid bacterium which serves as a carrier for oral vaccines.Results: There was statistically significant difference in CVA16-specific IgG antibody level between NZ9000-pNZ8148-CVA16-VP1 group (0.49 ± 0.05) and control group (0.05 ± 0.00) when the antiserum was diluted 1:10 (t = 19.84; p < 0.05). Furthermore, the level of CVA16-specific IgA antibody in NZ9000- pNZ8148-CVA16-VP1 group (0.17 ± 0.02) was significantly higher than in control group (0.05 ± 0.00) following antiserum dilution of 1:10 (t =12.08; p < 0.05).Conclusion: A CVA16 oral vaccine made from Lactobacillus elicits protective antibodies against CVA16. Thus, it is a potential as oral vaccine against CVA16 but further studies in vivo are required to ascertain its safety and effectiveness. Keywords: Coxsackievirus A16, Hand, foot and mouth disease, Lactococcus lactis, Oral vaccine, Enterovirus 7

Non-clausal multi-ary alpha-generalized resolution calculus for a finite lattice-valued logic

Due to the need of the logical foundation for uncertain information processing, development of efficient automated reasoning system based on non-classical logics is always an active research area. The present paper focuses on the resolution-based automated reasoning theory in a many-valued logic with truth-values defined in a lattice-ordered many-valued algebraic structure - lattice implication algebras (LIA). Specifically, as a continuation and extension of the established work on binary resolution at a certain truth-value level α (called α-resolution), a non-clausal multi-ary α-generalized resolution calculus is introduced for a lattice-valued propositional logic LP(X) based on LIA, which is essentially a non-clausal generalized resolution avoiding reduction to normal clausal form. The new resolution calculus in LP(X) is then proved to be sound and complete. The concepts and theoretical results are further extended and established in the corresponding lattice-valued first-order logic LF(X) based on LIA

Masked Language Model Based Textual Adversarial Example Detection

Adversarial attacks are a serious threat to the reliable deployment of machine learning models in safety-critical applications. They can misguide current models to predict incorrectly by slightly modifying the inputs. Recently, substantial work has shown that adversarial examples tend to deviate from the underlying data manifold of normal examples, whereas pre-trained masked language models can fit the manifold of normal NLP data. To explore how to use the masked language model in adversarial detection, we propose a novel textual adversarial example detection method, namely Masked Language Model-based Detection (MLMD), which can produce clearly distinguishable signals between normal examples and adversarial examples by exploring the changes in manifolds induced by the masked language model. MLMD features a plug and play usage (i.e., no need to retrain the victim model) for adversarial defense and it is agnostic to classification tasks, victim model's architectures, and to-be-defended attack methods. We evaluate MLMD on various benchmark textual datasets, widely studied machine learning models, and state-of-the-art (SOTA) adversarial attacks (in total $3*4*4 = 48$ settings). Experimental results show that MLMD can achieve strong performance, with detection accuracy up to 0.984, 0.967, and 0.901 on AG-NEWS, IMDB, and SST-2 datasets, respectively. Additionally, MLMD is superior, or at least comparable to, the SOTA detection defenses in detection accuracy and F1 score. Among many defenses based on the off-manifold assumption of adversarial examples, this work offers a new angle for capturing the manifold change. The code for this work is openly accessible at \url{https://github.com/mlmddetection/MLMDdetection}.Comment: 13 pages,3 figure

Research on the reasons for the disunity of knowing and doing in low-carbon consumption — based on the grounded theory

Under the background of "carbon peaking and carbon neutrality", the carbon emissions produced by the public’s daily consumption cannot be ignored. However, the data show that there is a disunity of knowing and doing in low-carbon consumption. How to get out of the dilemma, and how to guide the public to the low-carbon consumption mode has become an urgent issue to be solved. This study uses the research method of in-depth interview and the grounded theory to build a research model suitable for the analysis of low-carbon consumption behavior, and explains the disunity of knowing and doing. The results show that low-carbon knowledge, personal benefits, moral image and social norms have significant effects on low-carbon consumption behavior, and the mechanisms and paths of their effects are different. On this basis, this study explores and integrates the "knowledge-cognition-behavior" model to analyse low-carbon consumption behaviors, which can provide targeted policy ideas and implementation paths for relevant institutions

Crif1 Promotes Osteoporosis in Mice after Radiation

Abstract Radiation induces rapid bone loss and enhances bone resorption and RANKL expression. RANKL provides the crucial signal to induce osteoclast differentiation and plays an important role in bone resorption. However, the mechanisms of radiation-induced osteoporosis are not fully understood. Here, we show that Crif1 expression increases in bone marrow cells after radiation. Conditional Crif1 deletion in bone marrow cells causes decreases in RANKL expression and the RANKL/OPG ratio, and relieves bone loss after radiation in mice. We further demonstrated in vitro that Crif1 promotes RANKL secretion via the cAMP/PKA pathway. Moreover, protein-protein docking screening identified five compounds as Crif1 inhibitors; these compounds dramatically suppressed RANKL secretion and CREB phosphorylation when cells were exposed to forskolin. This study enriches current knowledge of the pathogenesis of osteoporosis and provides insights into potential therapeutic strategies for osteoporosis treatment

Analysis of Metabolites Difference of the Albino Tea Tree Variety 'Ming Guan'

‘Ming guan’ is a new excellent albino tea variety bred from the descendants of Bai jiguan. In order to explore the quality difference of Ming guan multi tea processing, the fresh leaves of Ming guan were used as raw materials to make the corresponding tea types according to the processing methods of green tea, black tea and white tea, and sensory quality evaluation, aroma and taste analysis were conducted. The results showed that the aroma of Ming guan green tea was tender, floral and fruity, with a mellow taste, the aroma of Ming guan black tea was sweet, floral, with a sweet taste, the aroma of Ming guan white tea was millets, floral, with a fresh taste, and the different processes of Ming guan tea had their own unique floral characteristics. Among the aroma components of Ming guan green tea, terpene aroma components with floral aroma were relatively more abundant, followed by ester aroma components with fruit aroma, which played an important role in the formation of the aroma of Ming guan green tea. The representative aroma components of Ming guan green tea were leaf alcohol ester of foliol caproate, 3-hexenyl caproate, 2-hexenyl caproate, nerolidol, leaf alcohol ester of butyric acid, olivetol and α-farnesene, the representative components of which were mainly esters with fruity aroma and alcohols with floral and fruity aroma, creating the characteristic of Ming guan green tea floral and fruity varieties. The representative components of Ming guan black tea were dihydrolinalool, α-cephalene, β-Ionone, γ-cadinene, methyl hexadecanoic acid and benzaldehyde, which were mainly terpenes and alcohols with floral and sweet aromas, contributing to the floral and sweet aromatic characteristics of Ming guan black tea. The representative components of Ming guan white tea were geraniol, myrcene, 3-carene, linalyl acetate and linalool, and the representative components are mainly alcohols and terpenes with floral aroma. The non-volatile components of Ming guan green tea, Ming guan black tea and Ming guan white tea vary greatly overall. The content of catechins, anthocyanins, some flavonols and flavonoid glycosides (quercetin-3-O-galactoside, quercetin-3-O-glucoside, quercetin-3-O-glucoside 7-O-rhamnoside, etc.) in Ming guan green tea was generally higher than that in Ming guan black tea and Ming guan white tea. The contents of theaflavins, phenolic acids, a few flavonol and flavonoid glycoside compounds (vitexin-2-O-galactoside, vitexin-2-O-rhamnoside, apigenin-6,8-di-C-glucoside, apigenin-6-C-glucoside, etc.) and some amino acid compounds (L-phenylalanine, L-tryptophan, L-isoleucine, L-valine, L-aspartic acid) in Ming guan black tea were higher than those in Ming guan green tea and Ming guan white tea.The content of some amino acid compounds (L-arginine, L-glutamine, L-lysine, L-histidine, L-tyrosine) in Ming guan white tea was higher than that in Ming guan green tea and Ming guan black tea, which may be affected by different processing technologies. This study could provide a theoretical basis for a comprehensive understanding of the chemical basis and quality differences of Ming guan green tea, Ming guan black tea and Ming guan white tea