Search

Epidemic outbreaks can cause critical health concerns and severe global economic crises. For countries or regions with new infectious disease outbreaks, it is essential to generate preventive strategies by learning lessons from others with similar risk profiles. A Strategy Transfer and Decision Support Approach (STDSA) is proposed based on the profile similarity evaluation. There are four steps in this method: (1) The similarity evaluation indicators are determined from three dimensions, i.e., the Basis of National Epidemic Prevention & Control, Social Resilience, and Infection Situation. (2) The data related to the indicators are collected and preprocessed. (3) The first round of screening on the preprocessed dataset is conducted through an improved collaborative filtering algorithm to calculate the preliminary similarity result from the perspective of the infection situation. (4) Finally, the K-Means model is used for the second round of screening to obtain the final similarity values. The approach will be applied to decision-making support in the context of COVID-19. Our results demonstrate that the recommendations generated by the STDSA model are more accurate and aligned better with the actual situation than those produced by pure K-means models. This study will provide new insights into preventing and controlling epidemics in regions that lack experience., Comment: 20 pages, 9 figures

With the renaissance of neural networks, object detection has slowly shifted from a bottom-up recognition problem to a top-down approach. Best in class algorithms enumerate a near-complete list of objects and classify each into object/not object. In this paper, we show that strong performance can still be achieved using a bottom-up approach for vision-based object recognition tasks and achieve competitive video game play. We propose PuckNet, which is used to detect four extreme points (top, left, bottom, and right-most points) and one center point of objects using a fully convolutional neural network. Object detection is then a purely keypoint-based appearance estimation problem, without implicit feature learning or region classification. The method proposed herein performs on-par with the best in class region-based detection methods, with a bounding box AP of 36.4% on COCO test-dev. In addition, the extreme points estimated directly resolve into a rectangular object mask, with a COCO Mask AP of 17.6%, outperforming the Mask AP of vanilla bounding boxes. Guided segmentation of extreme points further improves this to 32.1% Mask AP. We applied the PuckNet vision system to the SuperTuxKart video game to test it's capacity to achieve competitive play in dynamic and co-operative multiplayer environments.

It is highly desirable to discover an electromechanical coupling that allows a dielectric material to generate curvature in response to a uniform electric field, which would add a new degree of freedom for designing actuators. Flexoelectricity, a two-way coupling between polarization and strain gradient, is a good candidate. But its applications are usually limited to the nanoscale due to its inherent size dependence. Here, an inverse flexoelectret effect in silicone elastomers is introduced to overcome this limitation. Based on this idea, a flexing actuator which can generate large curvature at the millimeter length scale is fabricated and shown to have excellent actuation performance comparable with current nanoscale flexoelectric actuators. Theoretical analysis indicates that the new phenomenon originates from the interplay of electrets and Maxwell stress. This work opens an avenue for applying macroscopic flexoelectricity in actuators and flexible electronics.

The neutron yield in $^{12}$C(d,n)$^{13}$N and the proton yield in $^{12}C(d,p)^{13}$C have been measured by deuteron beam from 0.6 MeV to 3 MeV which is delivered from a 4-MeV electro static accelerator bombarding on the thick carbon target. The neutrons are detected at $0\degree$, $24\degree$, $48\degree$ and the protons at $135\degree$ in the lab frame. The ratios of the neutron yield to the proton one have been calculated and can be used as an effective probe to pin down the resonances. The resonances are found at 1.4 MeV, 1.7 MeV, 2.5 MeV in $^{12}C(d,p)^{13}$C and at 1.6 MeV, 2.7 MeV in $^{12}$C(d,n)$^{13}$N. This method provides a way to reduce the systematic uncertainty and helps to confirm more resonances in compound nuclei., Comment: 7 pages, 2 tables, 6 pages; submitted to Nuclear Science and Techniques (http://link.springer.com/journal/41365)