Clustering Spatially Correlated Functional Data With Multiple Scalar Covariates.

We propose a probabilistic model for clustering spatially correlated functional data with multiple scalar covariates. The motivating application is to partition the 29 provinces of the Chinese mainland into a few groups characterized by the epidemic severity of COVID-19, while the spatial dependence and effects of risk factors are considered. It can be regarded as an extension of mixture models, which allows different subsets of covariates to influence the component weights and the component densities by modeling the parameters of the mixture as functions of the covariates. In this way, provinces with similar spatial factors are a priori more likely to be clustered together. Posterior predictive inference in this model formalizes the desired prediction. Further, the identifiability of the proposed model is analyzed, and sufficient conditions to guarantee "generic" identifiability are provided. An L1 -penalized estimator is developed to assist variable selection and robust estimation when the number of explanatory covariates is large. An efficient expectation-minimization algorithm is presented for parameter estimation. Simulation studies and real-data examples are presented to investigate the empirical performance of the proposed method. Finally, it is worth noting that the proposed model has a wide range of practical applications, e.g., health management, environmental science, ecological studies, and so on.

Multistage Attack-Defense Graph Game Analysis for Protection Resources Allocation Optimization Against Cyber Attacks Considering Rationality Evolution.

Cyber vulnerabilities become ever more critical in modern industrial systems since the attacker can utilize the vulnerabilities to degrade their performance or even cause disasters. In 2015, a series of sequential and well-organized cyber attacks intruded into the Ukrainian power grid, compromised access to the control system, and interrupted the power supply system, finally causing a widespread power outage. To assist the defender, e.g., power grid operator, to allocate protection resources against cyber attacks, existing studies have devoted considerable efforts to risk and reliability analysis and interaction analysis using game theory. The defender's protection strategy includes preevent defense strategy and postevent repair strategy. The strategy spaces of both players were static in previous studies. However, facing Ukrainian-style cyber attacks, the strategy spaces could variate during the attacker-defender confrontation. In other words, the vulnerability compromised by the attacker in one stage could expose the subsequential vulnerabilities, leading to the change of strategy spaces. In this work, a multistage attack-defense graph game model is proposed to assist the defender in allocating protection resources optimally against sequential cyber attacks during multiple stages. In addition, we consider the existence of the rationality evolution of the attacker, which mainly results from asymmetric information, capacity limitation, and progressive learning during the confrontation. Compared to previous studies based on static strategy spaces and static rationalities, our model is more practical and effective in dealing with Ukrainian-style cyber attacks. The simulation results show the superiority of our approach, and some notable observations and practical suggestions are summarized for the defender.

Blockade of Endogenous Angiotensin-(1-7) in Hypothalamic Paraventricular Nucleus Attenuates High Salt-Induced Sympathoexcitation and Hypertension / 神经科学通报·英文版

Angiotensin (Ang)-(1-7) is an important biologically-active peptide of the renin-angiotensin system. This study was designed to determine whether inhibition of Ang-(1-7) in the hypothalamic paraventricular nucleus (PVN) attenuates sympathetic activity and elevates blood pressure by modulating pro-inflammatory cytokines (PICs) and oxidative stress in the PVN in salt-induced hypertension. Rats were fed either a high-salt (8% NaCl) or a normal salt diet (0.3% NaCl) for 10 weeks, followed by bilateral microinjections of the Ang-(1-7) antagonist A-779 or vehicle into the PVN. We found that the mean arterial pressure (MAP), renal sympathetic nerve activity (RSNA), and plasma norepinephrine (NE) were significantly increased in salt-induced hypertensive rats. The high-salt diet also resulted in higher levels of the PICs interleukin-6, interleukin-1beta, tumor necrosis factor alpha, and monocyte chemotactic protein-1, as well as higher gp91 expression and superoxide production in the PVN. Microinjection of A-779 (3 nmol/50 nL) into the bilateral PVN of hypertensive rats not only attenuated MAP, RSNA, and NE, but also decreased the PICs and oxidative stress in the PVN. These results suggest that the increased MAP and sympathetic activity in salt-induced hypertension can be suppressed by blockade of endogenous Ang-(1-7) in the PVN, through modulation of PICs and oxidative stress.

Characteristics of clinical studies of summer acupoint herbal patching: a bibliometric analysis.

BACKGROUND: Summer acupoint herbal patching (SAHP) has been widely used in China for thousands of years. This bibliometric analysis aims to provide a comprehensive review of the characteristics of clinical studies on SAHP for any condition. METHODS: We included clinical studies such as randomized clinical trials (RCTs), controlled clinical studies (CCTs), case series (CSs), case reports (CRs), and cross-sectional studies on SAHP for any condition. Six databases were searched from date of inception to March 2015. Bibliometric information and study details such as study type, characteristics of participants, details of the intervention and comparison, and outcome were extracted and analyzed. RESULTS: A total of 937 clinical studies were identified and which were published between 1977 and 2015. This included 404 RCTs, 52 CCTs, 458 CSs, 19 CRs and 4 cross-sectional studies and involved 232,138 participants aged 2 to 90 years from two countries. Almost all studies were from China (936, 99.89%). The five conditions most commonly treated by SAHP were asthma (401, 42.80%), chronic bronchitis (146, 15.58%), allergic rhinitis (117, 12.49%), chronic obstructive pulmonary disease (73, 7.79%), and recurrent respiratory tract infection (42, 4.48%). Among 502 controlled studies, the majority compared SAHP alone with different controls (16 categories, 275 comparisons). The most commonly used controls were western medicine, placebo, traditional Chinese medicine, no treatment and non-pharmaceutical traditional Chinese therapies. Composite outcome measures were the most frequently reported outcome (512, 69.19%). CONCLUSION: A substantial amount of research on SAHP has been published in China and which predominantly focuses on respiratory conditions. The findings from this study can be used to inform further research by highlighting areas of greatest impact for SAHP.

Ambient air monitoring of Beijing MSW logistics facilities in 2006.

In China, "green" integrated waste management methods are being implemented in response to environmental concerns. We measured the air quality at several municipal solid waste (MSW) sites to provide information for the incorporation of logistics facilities within the current integrated waste management system. We monitored ambient air quality at eight MSW collecting stations, five transfer stations, one composting plant, and five disposal sites in Beijing during April 2006. Composite air samples were collected and analyzed for levels of odor, ammonia (NH3), hydrogen sulfide (H2S), total suspended particles (TSPs), carbon monoxide (CO), sulfur dioxide (SO2), and nitrogen dioxide (NO2). The results of our atmospheric monitoring demonstrated that although CO and SO2 were within acceptable emission levels according to ambient standards, levels of H2S, TSP, and NO2 in the ambient air at most MSW logistics facilities far exceeded ambient limits established for China. The primary pollutants in the ambient air at Beijing MSW logistics facilities were H2S, TSPs, NO2, and odor. To improve current environmental conditions at MSW logistics facilities, the Chinese government encourages the separation of biogenic waste from MSW at the source.

[Fuzzy mathematics-based groundwater quality evaluation of six MSW landfills in Beijing].

The qualities of leachate and groundwater of six MSW landfills in wet period, water period and dry period in Beijing in 2006 were analyzed. The results demonstrated that: although BOD5 and suspended solids content in the leachate of Beishenshu landfill were within acceptable levels according to China standards, COD, ammonia, fecal coliform, BOD5 and suspended solids content in other landfills were greatly high above the permissible range of GB 16889-1997 standards. Ammonia and fecal coliform were mostly serious among assaying index. Using fuzzy mathematics, comprehensive evaluation was that: the underground water qualities of six MSW landfills are all substandard and 95% of groundwater quality was bad. The primary pollutants in groundwater of six MSW landfills were total hardness, followed by fecal coliform.

Predicting protein secondary structure by a support vector machine based on a new coding scheme.

Protein structure prediction is one of the most important problems in modern computational biology. Protein secondary structure prediction is a key step in prediction of protein tertiary structure. There have emerged many methods based on machine learning techniques, such as neural networks (NN) and support vector machine (SVM) etc., to focus on the prediction of the secondary structures. In this paper, a new method was proposed based on SVM. Different from the existing methods, this method takes into account of the physical-chemical properties and structure properties of amino acids. When tested on the most popular dataset CB513, it achieved a Q(3) accuracy of 0.7844, which illustrates that it is one of the top range methods for protein of secondary structure prediction.