Nonparametric Evaluation of Dynamic Disease Risk: A Spatio-Temporal Kernel Approach

Quantifying the distributions of disease risk in space and time jointly is a key element for understanding spatio-temporal phenomena while also having the potential to enhance our understanding of epidemiologic trajectories. However, most studies to date have neglected time dimension and focus instead on the “average” spatial pattern of disease risk, thereby masking time trajectories of disease risk. In this study we propose a new idea titled “spatio-temporal kernel density estimation (stKDE)” that employs hybrid kernel (i.e., weight) functions to evaluate the spatio-temporal disease risks. This approach not only can make full use of sample data but also “borrows” information in a particular manner from neighboring points both in space and time via appropriate choice of kernel functions. Monte Carlo simulations show that the proposed method performs substantially better than the traditional (i.e., frequency-based) kernel density estimation (trKDE) which has been used in applied settings while two illustrative examples demonstrate that the proposed approach can yield superior results compared to the popular trKDE approach. In addition, there exist various possibilities for improving and extending this method

A Single E627K Mutation in the PB2 Protein of H9N2 Avian Influenza Virus Increases Virulence by Inducing Higher Glucocorticoids (GCs) Level

While repeated infection of humans and enhanced replication and transmission in mice has attracted more attention to it, the pathogenesis of H9N2 virus was less known in mice. PB2 residue 627 as the virulent determinant of H5N1 virus is associated with systemic infection and impaired TCR activation, but the impact of this position in H9N2 virus on the host immune response has not been evaluated. In this study, we quantified the cellular immune response to infection in the mouse lung and demonstrate that VK627 and rTsE627K infection caused a significant reduction in the numbers of T cells and inflammatory cells (Macrophage, Neutrophils, Dendritic cells) compared to mice infected with rVK627E and TsE627. Further, we discovered (i) a high level of thymocyte apoptosis resulted in impaired T cell development, which led to the reduced amount of mature T cells into lung, and (ii) the reduced inflammatory cells entering into lung was attributed to the diminished levels in pro-inflammatory cytokines and chemokines. Thereafter, we recognized that higher GCs level in plasma induced by VK627 and rTsE627K infection was associated with the increased apoptosis in thymus and the reduced pro-inflammatory cytokines and chemokines levels in lung. These data demonstrated that VK627 and rTsE627K infection contributing to higher GCs level would decrease the magnitude of antiviral response in lung, which may be offered as a novel mechanism of enhanced pathogenicity for H9N2 AIV

An Improved Rotation Forest for Multi-Feature Remote-Sensing Imagery Classification

Multi-feature, especially multi-temporal, remote-sensing data have the potential to improve land cover classification accuracy. However, sometimes it is difficult to utilize all the features efficiently. To enhance classification performance based on multi-feature imagery, an improved rotation forest, combining Principal Component Analysis (PCA) and a boosting naïve Bayesian tree (NBTree), is proposed. First, feature extraction was carried out with PCA. The feature set was randomly split into several disjoint subsets; then, PCA was applied to each subset, and new training data for linear extracted features based on original training data were obtained. These steps were repeated several times. Second, based on the new training data, a boosting naïve Bayesian tree was constructed as the base classifier, which aims to achieve lower prediction error than a decision tree in the original rotation forest. At the classification phase, the improved rotation forest has two-layer voting. It first obtains several predictions through weighted voting in a boosting naïve Bayesian tree; then, the first-layer vote predicts by majority to obtain the final result. To examine the classification performance, the improved rotation forest was applied to multi-feature remote-sensing images, including MODIS Enhanced Vegetation Index (EVI) imagery time series, MODIS Surface Reflectance products and ancillary data in Shandong Province for 2013. The EVI imagery time series was preprocessed using harmonic analysis of time series (HANTS) to reduce the noise effects. The overall accuracy of the final classification result was 89.17%, and the Kappa coefficient was 0.71, which outperforms the original rotation forest and other classifier ensemble results, as well as the NASA land cover product. However, this new algorithm requires more computational time, meaning the efficiency needs to be further improved. Generally, the improved rotation forest has a potential advantage in remote-sensing classification

Adsorption of bis(2-hydroxy-3-chloropropyl) dodecylamine on quartz surface and its implication on flotation

In order to clarify the effect of polar group modification on flotation performance of amine collector, flotation properties of quartz and hematite using bis(2-hydroxy-3-chloropropyl) dodecylamine (N23) as a collector were investigated. And the adsorption mechanism of N23 on quartz surface was established by zeta potential measurements, SEM/EDS measurements, and molecular structure analysis. Single mineral flotation results indicated that N23 showed stronger collecting ability on quartz and hematite than DDA-CH3COOH. However, starch could depress the flotation of hematite. Flotation recovery of 98.10% for quartz could be achieved, when N23 concentration was 43.33 mg/L and starch concentration was 16.67 mg/L at natural slurry pH. Separation of artificially mixed minerals of hematite and quartz was achieved effectively using N23 as the collector. The optimized separation result with 66.29% iron grade and 90.06% iron recovery in concentrate was obtained when slurry pH was 7.34 with 43.33 mg/L N23 and 23.33 mg/L starch. The interaction energies of N23 with mineral surface also showed well consistency with flotation results. SEM/EDS analyses and zeta potential measurements revealed that N23 could absorb on quartz surface in the forms of strong electrostatic and hydrogen bonding interaction. Compared with DDA, N23 had a higher HLB value and better water-solubility, which resulted in better dispersion in water and stronger adsorption on mineral surface. Keywords: Flotation, Adsorption, Bis(2-hydroxy-3-chloropropyl) dodecylamine, Quartz, Hematit

Secure Communication for Two-Way Relay Networks with Imperfect CSI

This paper considers a two-way relay network, where two legitimate users exchange messages through several cooperative relays in the presence of an eavesdropper, and the Channel State Information (CSI) of the eavesdropper is imperfectly known. The Amplify-and-Forward (AF) relay protocol is used. We design the relay beamforming weights to minimize the total relay transmit power, while requiring the Signal-to-Noise-Ratio (SNRs) of the legitimate users to be higher than the given thresholds and the achievable rate of the eavesdropper to be upper-bounded. Due to the imperfect CSI, a robust optimization problem is summarized. A novel iterative algorithm is proposed, where the line search technique is applied, and the feasibility is preserved during iterations. In each iteration, two Quadratically-Constrained Quadratic Programming (QCQP) subproblems and a one-dimensional subproblem are optimally solved. The optimality property of the robust optimization problem is analyzed. Simulation results show that the proposed algorithm performs very close to the non-robust model with perfect CSI, in terms of the obtained relay transmit power; it~achieves higher secrecy rate compared to the existing work. Numerically, the proposed algorithm converges very quickly, and more than 85% of the problems are solved optimally

Study on Optimization of Extracting Magnesium Sulfate from Acid-leaching Eluent of Serpentine by Solventing-out Crystallization

In order to make full use of China's non-metallic mineral resources containing magnesium, and improve the comprehensive recovery rate of magnesium in serpentine, a new process of enriching magnesium from serpentine leaching solution at normal temperature and pressure was proposed. In this process, the solution crystallization method was used to recover the magnesium from the acid leaching solution of serpentine. The test conditions were optimized by response surface methodology to determine the optimal crystallization process conditions. In this study, response surface method was employed to optimize test conditions and select the best crystallization process conditions. In addition, the effect and interaction of crystallization time, temperature, and absolute ethanol consumption on magnesium sulfate crystallization efficiency were study. The results showed that the magnesium sulfate crystallization efficiency reached 93.52% under the optimum condition (crystallization time: 97 min, crystallization temperature: 18°C and absolute ethanol consumption: 68 mL). Moreover, the absolute ethanol consumption exhibited significant influence on magnesium sulfate crystallization, while temperature had the least effect, and the interaction between absolute ethanol consumption and crystallization temperature or time was significant. The crystalline product was rod-shaped magnesium sulfate hexahydrate, which met the production requirements of domestic class IV MgSO4·nH2O products