Evolving parametrized Loss for Image Classification Learning on Small Datasets

This paper proposes a meta-learning approach to evolving a parametrized loss function, which is called Meta-Loss Network (MLN), for training the image classification learning on small datasets. In our approach, the MLN is embedded in the framework of classification learning as a differentiable objective function. The MLN is evolved with the Evolutionary Strategy algorithm (ES) to an optimized loss function, such that a classifier, which optimized to minimize this loss, will achieve a good generalization effect. A classifier learns on a small training dataset to minimize MLN with Stochastic Gradient Descent (SGD), and then the MLN is evolved with the precision of the small-dataset-updated classifier on a large validation dataset. In order to evaluate our approach, the MLN is trained with a large number of small sample learning tasks sampled from FashionMNIST and tested on validation tasks sampled from FashionMNIST and CIFAR10. Experiment results demonstrate that the MLN effectively improved generalization compared to classical cross-entropy error and mean squared error

Full-Duplex Massive MIMO Relaying Systems with Low-Resolution ADCs

International audienceThis paper considers a multipair amplify-and-forward massive MIMO relaying system with low-resolution analog-to-digital converters (ADCs) at both the relay and destinations. The channel state information (CSI) at the relay is obtained via pilot training, which is then utilized to perform simple maximum-ratio combining/maximum-ratio transmission processing by the relay. Also, it is assumed that the destinations use statistical CSI to decode the transmitted signals. Exact and approximated closed-form expressions for the achievable sum rate are presented, which enable the efficient evaluation of the impact of key system parameters on the system performance. In addition, optimal relay power allocation scheme is studied, and power scaling law is characterized. It is found that, with only low-resolution ADCs at the relay, increasing the number of relay antennas is an effective method to compensate for the rate loss caused by coarse quantization. However, it becomes ineffective to handle the detrimental effect of low-resolution ADCs at the destination. Moreover, it is shown that deploying massive relay antenna arrays can still bring significant power savings, i.e., the transmit power of each source can be cut down proportional to 1/M to maintain a constant rate, where M is the number of relay antennas

Screening and identification of the dominant antigens of the African swine fever virus

African swine fever is a highly lethal contagious disease of pigs for which there is no vaccine. Its causative agent African swine fever virus (ASFV) is a highly complex enveloped DNA virus encoding more than 150 open reading frames. The antigenicity of ASFV is still unclear at present. In this study, 35 proteins of ASFV were expressed by Escherichia coli, and ELISA was developed for the detection of antibodies against these proteins. p30, p54, and p22 were presented as the major antigens of ASFV, positively reacting with all five clinical ASFV-positive pig sera, and 10 pig sera experimentally infected by ASFV. Five proteins (pB475L, pC129R, pE199L, pE184L, and pK145R) reacted well with ASFV-positive sera. The p30 induced a rapid and strong antibody immune response during ASFV infection. These results will promote the development of subunit vaccines and serum diagnostic methods against ASFV

Layer-by-Layer Degradation of Methylammonium Lead Tri-iodide Perovskite Microplates

The methylammonium lead iodide (MAPbI3) perovskite has attracted considerable interest for its high-efficiency, low-cost solar cells, but is currently plagued by its poor environmental and thermal stability. To aid the development of robust devices, we investigate here the microscopic degradation pathways of MAPbI3 microplates. Using in situ transmission electron microscopy to follow the thermal degradation process, we find that under moderate heating at 85°C the crystalline structure shows a gradual evolution from tetragonal MAPbI3 to trigonal lead iodide layered crystals with a fixed crystallographic direction. Our solid-state nudged elastic band calculations confirm that the surface-initiated layer-by-layer degradation path exhibits the lowest energy barrier for crystal transition. We further show experimentally and theoretically that encapsulation of the perovskites with boron nitride flakes suppresses the surface degradation, greatly improving its thermal stability. These studies provide mechanistic insight into the thermal stability of perovskites that suggests new designs for improved stability

Layer-by-Layer Degradation of Methylammonium Lead Tri-iodide Perovskite Microplates

The methylammonium lead iodide (MAPbI3) perovskite has attracted considerable interest for its high-efficiency, low-cost solar cells, but is currently plagued by its poor environmental and thermal stability. To aid the development of robust devices, we investigate here the microscopic degradation pathways of MAPbI3 microplates. Using in situ transmission electron microscopy to follow the thermal degradation process, we find that under moderate heating at 85°C the crystalline structure shows a gradual evolution from tetragonal MAPbI3 to trigonal lead iodide layered crystals with a fixed crystallographic direction. Our solid-state nudged elastic band calculations confirm that the surface-initiated layer-by-layer degradation path exhibits the lowest energy barrier for crystal transition. We further show experimentally and theoretically that encapsulation of the perovskites with boron nitride flakes suppresses the surface degradation, greatly improving its thermal stability. These studies provide mechanistic insight into the thermal stability of perovskites that suggests new designs for improved stability