Spatio-Temporal Changes of Snow Cover and Its Response to Climate Change over Tibetan Plateau

Snow cover, as an important part of land cover, is one of the most active natural elements on the earth surface. This program used the MODIS/Terra-Aqua daily snow products (MOD10A1 and MYD10A1) and AMSR-E/Aqua daily snow water equivalent product (AE_DySno) from 2003 to 2010 of Tibetan Plateau (TP), together with systematic study on MODIS daily snow cover product composite and a merging of multi-sensor and snow line approaches (Liang et al. 2008) to put forward a new snow cover mapping algorithm. Daily cloud-free snow cover images were calculated based on the new algorithm and the response of climate change on snow cover dynamics was analysed

Speaker verification using attentive multi-scale convolutional recurrent network

In this paper, we propose a speaker verification method by an Attentive Multi-scale Convolutional Recurrent Network (AMCRN). The proposed AMCRN can acquire both local spatial information and global sequential information from the input speech recordings. In the proposed method, logarithm Mel spectrum is extracted from each speech recording and then fed to the proposed AMCRN for learning speaker embedding. Afterwards, the learned speaker embedding is fed to the back-end classifier (such as cosine similarity metric) for scoring in the testing stage. The proposed method is compared with state-of-the-art methods for speaker verification. Experimental data are three public datasets that are selected from two large-scale speech corpora (VoxCeleb1 and VoxCeleb2). Experimental results show that our method exceeds baseline methods in terms of equal error rate and minimal detection cost function, and has advantages over most of baseline methods in terms of computational complexity and memory requirement. In addition, our method generalizes well across truncated speech segments with different durations, and the speaker embedding learned by the proposed AMCRN has stronger generalization ability across two back-end classifiers.Comment: 21 pages, 6 figures, 8 tables. Accepted for publication in Applied Soft Computin

Monitoring Snow-Caused Disasters Using Remote Sensing and GIS Technologies in Pastoral Areas

To date, the emphasis in snow-caused disasters that occur in pastoral areas in China has been in monitoring the change in the distribution of snow and in assessing livestock loss in post-disaster. The lack of an operational model and information system for real-time warning of snow dis-asters has made it difficult to make risk assessments and provide early snow disaster warnings (Liu et al. 2008). The aim of this study is to establish an indicator system for the early warning of snow-caused livestock disasters based on data collected from 2001 to 2010 on the Tibetan Plateau, China

Spatio-Temporal Dynamics of Global Potential Vegetation Distributions Simulated by CSCS Approach

The study of Potential Natural Vegetation (PNV) has been proposed as a way to examine the impact of changes in climate on the distribution of vegetation. This study analyzes the influence of climate change in the potential vegetation distribution at global scale, using the Comprehensive Sequential Classification System (CSCS) approach to explore the changes of area, shift distance and direction for each broad vegetation category

Spatial and Temporal Variability of Sea Surface Temperature in the Yellow Sea and East China Sea over the Past 141 Years

The Yellow Sea and East China Sea (YES) are marginal seas in the northwest Pacific. There is in fact a smaller sea, the Bohai Sea, to the north of the Yellow Sea. For most discussions in the chapter, we shall treat the Bohai Sea as part of the Yellow Sea. The YES is one of the mostly intensively utilized sea in the world, for example, heavy fishery and marine aquaculture. The use of the YES is closely related to its climate variability, though it is not well-know because until now there has been a lack of adequate observational data. To know the climatology of sea surface temperature (SST, all the acronyms used in the chapter are listed in Table 1) in the YES and their relationship with regional and global climate have both scientific and social importance.https://digitalcommons.usu.edu/modern_climatology/1007/thumbnail.jp

Semiconducting nonperovskite ferroelectric oxynitride designed ab initio

Recent discovery of HfO2-based and nitride-based ferroelectrics that are compatible to the semiconductor manufacturing process have revitalized the field of ferroelectric-based nanoelectronics. Guided by a simple design principle of charge compensation and density functional theory calculations, we discover HfO2-like mixed-anion materials, TaON and NbON, can crystallize in the polar Pca21 phase with a strong thermodynamic driving force to adopt anion ordering spontaneously. Both oxynitrides possess large remnant polarization, low switching barriers, and unconventional negative piezoelectric effect, making them promising piezoelectrics and ferroelectrics. Distinct from HfO2 that has a wide band gap, both TaON and NbON can absorb visible light and have high charge carrier mobilities, suitable for ferroelectric photovoltaic and photocatalytic applications. This new class of multifunctional nonperovskite oxynitride containing economical and environmentally benign elements offer a platform to design and optimize high-performing ferroelectric semiconductors for integrated systems

Low-Complexity Acoustic Scene Classification Using Data Augmentation and Lightweight ResNet

We present a work on low-complexity acoustic scene classification (ASC) with multiple devices, namely the subtask A of Task 1 of the DCASE2021 challenge. This subtask focuses on classifying audio samples of multiple devices with a low-complexity model, where two main difficulties need to be overcome. First, the audio samples are recorded by different devices, and there is mismatch of recording devices in audio samples. We reduce the negative impact of the mismatch of recording devices by using some effective strategies, including data augmentation (e.g., mix-up, spectrum correction, pitch shift), usages of multi-patch network structure and channel attention. Second, the model size should be smaller than a threshold (e.g., 128 KB required by the DCASE2021 challenge). To meet this condition, we adopt a ResNet with both depthwise separable convolution and channel attention as the backbone network, and perform model compression. In summary, we propose a low-complexity ASC method using data augmentation and a lightweight ResNet. Evaluated on the official development and evaluation datasets, our method obtains classification accuracy scores of 71.6% and 66.7%, respectively; and obtains Log-loss scores of 1.038 and 1.136, respectively. Our final model size is 110.3 KB which is smaller than the maximum of 128 KB.Comment: 5 pages, 5 figures, 4 tables. Accepted for publication in the 16th IEEE International Conference on Signal Processing (IEEE ICSP

A Fluorogenic, Small Molecule Reporter for Mammalian Phospholipase C Isozymes

Phospholipase C isozymes (PLCs) catalyze the conversion of the membrane lipid phosphatidylinositol 4,5-bisphosphate (PIP2) into two second messengers, inositol 1,4,5-trisphosphate and diacylglycerol. This family of enzymes are key signaling proteins that regulate the physiological responses of many extracellular stimuli such as hormones, neurotransmitters, and growth factors. Aberrant regulation of PLCs has been implicated in various diseases including cancer and Alzheimer’s disease. How, when, and where PLCs are activated under different cellular contexts are still largely unknown. We have developed a fluorogenic PLC reporter, WH-15, that can be cleaved in a cascade reaction to generate fluorescent 6-aminoquinoline. When applied in enzymatic assays with either pure PLCs or cell lysates, this reporter displays more than a 20-fold fluorescence enhancement in response to PLC activity. Under assay conditions, WH-15 has comparable Km and Vmax with the endogenous PIP2. This novel reporter will likely find broad applications that vary from imaging PLC activity in live cells to high throughput screening of PLC inhibitors