We consider the sequential (i.e., online) detection of false data injection attacks in smart grid, which aims to manipulate the state estimation procedure by injecting malicious data to the ...monitoring meters. The unknown parameters in the system, namely the state vector, injected malicious data and the set of attacked meters pose a significant challenge for designing a robust, computationally efficient, and high-performance detector. We propose a sequential detector based on the generalized likelihood ratio to address this challenge. Specifically, the proposed detector is designed to be robust to a variety of attacking strategies, and load situations in the power system, and its computational complexity linearly scales with the number of meters. Moreover, it considerably outperforms the existing first-order cumulative sum detector in terms of the average detection delay and robustness to various attacking strategies. For wide-area monitoring in smart grid, we further develop a distributed sequential detector using an adaptive sampling technique called level-triggered sampling. The resulting distributed detector features single bit per sample in terms of the communication overhead, while preserving the high performance of the proposed centralized detector.
Increased vascular permeability facilitates metastasis. Emerging evidence indicates that secreted microRNAs (miRNAs) may mediate the crosstalk between cancer and stromal cells. To date, whether and ...how secreted miRNAs affect vascular permeability remains unclear. Based on deep sequencing and quantitative PCR, we found that higher level of serum miR‐103 was associated with higher metastasis potential of hepatocellular carcinoma (HCC). The in vitro endothelial permeability and transendothelial invasion assays revealed that the conditioned media or exosomes derived from high miR‐103‐expressing hepatoma cells increased the permeability of endothelial monolayers, but this effect was attenuated if exosome secretion of hepatoma cells was blocked by silencing ALIX and HRS or if miR‐103 within hepatoma or endothelial cells was antagonized. Most importantly, pretreating endothelial monolayers with exosomes that were from stable miR‐103‐expressing hepatoma cells facilitated the transendothelial invasion of tumor cells, and this role of exosomes was abrogated by inhibiting miR‐103 in endothelial cells. Further in vivo analyses disclosed that mice with xenografts of stable miR‐103‐expressing hepatoma cells exhibited higher vascular permeability in tumor, higher level of exosomal miR‐103 and greater number of tumor cells in blood circulation, and increased rates of hepatic and pulmonary metastases, compared to control mice. Mechanism investigations revealed that hepatoma cell‐secreted miR‐103 could be delivered into endothelial cells via exosomes, and then attenuated the endothelial junction integrity by directly inhibiting the expression of VE‐Cadherin (VE‐Cad), p120‐catenin (p120) and zonula occludens 1. Moreover, miR‐103 could also promote tumor cell migration by repressing p120 expression in hepatoma cells. Conclusion: Hepatoma cell‐secreted exosomal miR‐103 increases vascular permeability and promotes tumor metastasis by targeting multiple endothelial junction proteins, which highlights secreted miR‐103 as a potential therapeutic target and a predictive marker for HCC metastasis. (Hepatology 2018).
We developed an integrated gas diffusion layer (GDL) for proton exchange membrane (PEM) fuel cells by growing carbon nanofibers (CNFs) in situ on carbon paper via the electro-polymerization of ...polyaniline (PANI) on carbon paper followed by a subsequent carbonization treatment process. The CNF/carbon paper showed a microporous structure and a significantly increased pore volume compared to commercial carbon paper. By utilizing this CNF/carbon paper in a PEM fuel cell, it was found that the cell with CNF/carbon paper had superior performance compared to the commercial GDL at both high and low humidity conditions, and its power density was as high as 1.21 W cm
at 100% relative humidity, which is 26% higher than that of a conventional gas diffusion layer (0.9 W cm
). The significant performance enhancement was attributed to a higher pore volume and porosity of the CNF/carbon paper, which improved gas diffusion in the GDL. In addition, the superior performance of the cell with CNF/carbon paper at low relative humidity demonstrated that it had better water retention than the commercial GDL. This study provides a novel and facile method for the surface modification of GDLs to improve the performance of PEM fuel cells. The CNF/carbon paper with a microporous structure has suitable hydrophobicity and lower through-plane resistance, which makes it promising as an advanced substrate for GDLs in fuel cell applications.
In order to clarify the effect of pulsating fracturing on gas comprehensive desorption, experimental study of gas desorption characteristics effected by the pulsating hydraulic fracturing (PHF) and ...static hydraulic fracturing (SHF) were carried out, the gas displacement amount (GDA) and natural desorption amount (NDA) under different hydraulic fracturing methods are investigated. The results show that the GDA generated by the SHF is significantly less than the PHF. At the same time, the GDA increases linearly first, and then logarithmically with the fracturing frequency; with the increase of pulsating peak pressure, it showed a logarithmic increase. The water has an inhibitory effect on the natural desorption of gas. With the increase of pulsating pressure and frequency, the effect of pulsation fracturing suppressing the natural desorption of gas is weakened. According to the effect of different fracturing methods on gas desorption, the PHF is divided into four types: low pressure-low frequency, low pressure-high frequency, high pressure-low frequency and high pressure-high frequency. Because the gas displacement rate (ƞd) determines the changes of gas comprehensive desorption effect, the low pressure-low frequency inhibits gas desorption, while the low pressure-high frequency, high pressure-low frequency and high pressure-high frequency can promote gas desorption. The results provide theoretical guidance for optimizing pulsating parameters, increasing gas desorption and promoting coal seam gas drainage.
Although supervised deep learning has revolutionized speech and audio processing, it has necessitated the building of specialist models for individual tasks and application scenarios. It is likewise ...difficult to apply this to dialects and languages for which only limited labeled data is available. Self-supervised representation learning methods promise a single universal model that would benefit a wide variety of tasks and domains. Such methods have shown success in natural language processing and computer vision domains, achieving new levels of performance while reducing the number of labels required for many downstream scenarios. Speech representation learning is experiencing similar progress in three main categories: generative, contrastive, and predictive methods. Other approaches rely on multi-modal data for pre-training, mixing text or visual data streams with speech. Although self-supervised speech representation is still a nascent research area, it is closely related to acoustic word embedding and learning with zero lexical resources, both of which have seen active research for many years. This review presents approaches for self-supervised speech representation learning and their connection to other research areas. Since many current methods focus solely on automatic speech recognition as a downstream task, we review recent efforts on benchmarking learned representations to extend the application beyond speech recognition.
Abstract
We all know that China is the largest developing country, China has the largest population in the world, China is also a large agricultural country, the development of agriculture is very ...important, China’s annual grain production is also very rich, food is the basic situation of our countryThe analysis of food security in China by computer software is helpful to solve the problem of food security in China, which is a very good technology and is very beneficial to the food security of our country.
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•Metal nanocluster-based nanocomposites are novel functional materials with many distinct physicochemical properties.•Different strategies have been developed to fabricate composites ...of metal NCs and many other functional materials.•Metal nanocluster-based nanocomposites show great potential for application in sensing, imaging and catalysis.
Metal nanoclusters (NCs) are a type of ultrasmall nanomaterials with unique physicochemical properties. Novel nanocomposites with exciting new and sometimes exotic properties can be created by combination of metal NCs with other functional materials, greatly expanding the range of possible applications. To exploit this potential, intensive research efforts have been made in recent years, resulting in a wide range of metal NC-based nanocomposites. In this review, we systematically summarize different strategies of fabricating nanocomposites and illustrate their application in sensing, imaging and catalysis. A brief outlook on the future development of metal NC-based nanocomposites is also presented.
We introduce a self-supervised speech pre-training method called TERA, which stands for Transformer Encoder Representations from Alteration. Recent approaches often learn by using a single auxiliary ...task like contrastive prediction, autoregressive prediction, or masked reconstruction. Unlike previous methods, we use alteration along three orthogonal axes to pre-train Transformer Encoders on a large amount of unlabeled speech. The model learns through the reconstruction of acoustic frames from their altered counterpart, where we use a stochastic policy to alter along various dimensions: time, frequency, and magnitude. TERA can be used for speech representations extraction or fine-tuning with downstream models. We evaluate TERA on several downstream tasks, including phoneme classification, keyword spotting, speaker recognition, and speech recognition. We present a large-scale comparison of various self-supervised models. TERA achieves strong performance in the comparison by improving upon surface features and outperforming previous models. In our experiments, we study the effect of applying different alteration techniques, pre-training on more data, and pre-training on various features. We analyze different model sizes and find that smaller models are strong representation learners than larger models, while larger models are more effective for downstream fine-tuning than smaller models. Furthermore, we show the proposed method is transferable to downstream datasets not used in pre-training.
Odorant-binding proteins (OBPs) are essential in insect's daily behaviors mediated by olfactory perception. Megachile saussurei Radoszkowski (Hymenoptera, Megachilidae) is a principal insect ...pollinating alfalfa (Medicago sativa) in Northwestern China. The olfactory function have been less conducted, which provides a lot of possibilities for our research.
Our results showed that 20 OBPs were identified in total. Multiple sequence alignment analysis indicated MsauOBPs were highly conserved with a 6-cysteine motif pattern and all belonged to the classic subfamily, coding 113-196 amino acids and sharing 41.32%-99.12% amino acid identity with known OBPs of other bees. Phylogenetic analysis indicated there were certain homologies existed among MsauOBPs and most sequences were clustered with that of Osmia cornuta (Hymenoptera, Megachilidae). Expression analysis showed the identified OBPs were mostly enriched in antennae instead of other four body parts, especially the MsauOBP2, MsauOBP3, MsauOBP4, MsauOBP8, MsauOBP11 and MsauOBP17, in which the MsauOBP2, MsauOBP4 and MsauOBP8 presented obvious tissue-biased expression pattern. Molecular docking results indicated MsauOBP4 might be the most significant protein in recognizing alfalfa flower volatile 3-Octanone, while MsauOBP13 might be the most crucial protein identifying (Z)-3-hexenyl acetate. It was also found the lysine was a momentous hydrophilic amino acid in docking simulations.
In this study, we identified and analyzed 20 OBPs of M. saussurei. The certain homology existed among these OBPs, while some degree of divergence could also be noticed, indicating the complex functions that different MsauOBPs performed. Besides, the M. saussurei and Osmia cornuta were very likely to share similar physiological functions as most of their OBPs were clustered together. MsauOBP4 might be the key protein in recognizing 3-Octanone, while MsauOBP13 might be the key protein in binding (Z)-3-hexenyl acetate. These two proteins might contribute to the alfalfa-locating during the pollination process. The relevant results may help determine the highly specific and effective attractants for M. saussurei in alfalfa pollination and reveal the molecular mechanism of odor-evoked pollinating behavior between these two species.
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