Both consumptive and non-consumptive effects of predators impact mosquito populations and have implications for disease transmission

Predator-prey interactions influence prey traits through both consumptive and non-consumptive effects, and variation in these traits can shape vector-borne disease dynamics. Meta-analysis methods were employed to generate predation effect sizes by different categories of predators and mosquito prey. This analysis showed that multiple families of aquatic predators are effective in consumptively reducing mosquito survival, and that the survival of Aedes, Anopheles, and Culex mosquitoes is negatively impacted by consumptive effects of predators. Mosquito larval size was found to play a more important role in explaining the heterogeneity of consumptive effects from predators than mosquito genus. Mosquito survival and body size were reduced by non-consumptive effects of predators, but development time was not significantly impacted. In addition, Culex vectors demonstrated predator avoidance behavior during oviposition. The results of this meta-analysis suggest that predators limit disease transmission by reducing both vector survival and vector size, and that associations between drought and human West Nile virus cases could be driven by the vector behavior of predator avoidance during oviposition. These findings are likely to be useful to infectious disease modelers who rely on vector traits as predictors of transmission.

Identification of Mode Shapes of a Composite Cylinder Using Convolutional Neural Networks

The aim of the following paper is to discuss a newly developed approach for the identification of vibration mode shapes of multilayer composite structures. To overcome the limitations of the approaches based on image analysis (two-dimensional structures, high spatial resolution of mode shapes description), convolutional neural networks (CNNs) are applied to create a three-dimensional mode shapes identification algorithm with a significantly reduced number of mode shape vector coordinates. The CNN-based procedure is accurate, effective, and robust to noisy input data. The appearance of local damage is not an obstacle. The change of the material and the occurrence of local material degradation do not affect the accuracy of the method. Moreover, the application of the proposed identification method allows identifying the material degradation occurrence.

An Analysis and Application of Fast Nonnegative Orthogonal Matching Pursuit for Image Categorization in Deep Networks

Nonnegative orthogonal matching pursuit (NOMP) has been proven to be a more stable encoder for unsupervised sparse representation learning. However, previous research has shown that NOMP is suboptimal in terms of computational cost, as the coefficients selection and refinement using nonnegative least squares (NNLS) have been divided into two separate steps. It is found that this problem severely reduces the efficiency of encoding for large-scale image patches. In this work, we study fast nonnegative OMP (FNOMP) as an efficient encoder which can be accelerated by the implementation ofQRfactorization and iterations of coefficients in deep networks for full-size image categorization task. It is analyzed and demonstrated that using relatively simple gain-shape vector quantization for training dictionary, FNOMP not only performs more efficiently than NOMP for encoding but also significantly improves the classification accuracy compared to OMP based algorithm. In addition, FNOMP based algorithm is superior to other state-of-the-art methods on several publicly available benchmarks, that is, Oxford Flowers, UIUC-Sports, and Caltech101.

Flexibility Method of Damage Identification for Transmission Tower Based on Signal Amplitude Vector

In this paper, the flexibility method of damage identification for transmission tower based on Wigner-Ville Distribution (WVD) signal amplitude vector is forwarded. The damage coefficient equation involving modal parameters and damage parameters is firstly established, on the basis of the linear relation of flexibility matrix and structure parameters. Then, the mathematical deduction of WVD signal term reveals the function relation between WVD signal terms and modal parameters. Lastly, the damage coefficient equation is solved by substituting mode shape vector with the signal amplitude vector of response under suddenly unloading to identified the position and extent of structural damage. A numerical example demonstrates its accuracy for damage identification and excellent noisy immunity.