101 research outputs found
Application of TiO2 Nanotubes Gas Sensors in Online Monitoring of SF6 Insulated Equipment
Titanium dioxide nanotube arrays (TNTAs) are a typical three-dimensional nanomaterial. TNTA has rich chemical and physical properties and low manufacturing costs. Thus, TNTA has broad application prospects. In recent years, research has shown that because of its large specific surface area and nanosize effect, the TNTAs have an enormous potential for development compared with other nanostructure forms in fields such as light catalysis, sensor, and solar batteries. TNTAs have become the hotspot of international nanometer material research. The tiny gas sensor made from TNTA has several advantages, such as fast response, high sensitivity, and small size. Several scholars in this field have achieved significant progress. As a sensitive material, TNTA is used to test O2, NO2, H2, ethanol, and other gases. In this chapter, three SF6 decomposed gases, namely SO2, SOF2 and SO2F2, are chosen as probe gases because they are the main by-products in the decomposition of SF6 under PD. Then, the adsorption behaviors of these gases on different anatase (101) surfaces including intrinsic, Pt-doped and Au-doped, are studied using the first principles density functional theory (DFT) calculations. The simulation results can be used as supplement for gas-sensing experiments of TNTA gas sensors. This work is expected to add insights into the fundamental understanding of interactions between gases and TNTA surfaces for better sensor design
The SF6 Decomposition Mechanism: Background and Significance
Gas Insulated Switchgear (GIS) has been widely used in substations. The insulating medium used in GIS is sulfur hexafluoride (SF6) gas. However, the internal insulation defect existed in GIS would inevitably lead to partial discharge (PD), and cause the composition of SF6 to SOF2, SO2F2 and SO2 and other characteristic component gases. The decomposition phenomenon would greatly reduce the insulation performance of SF6 insulated equipment, and even paralyze the whole power supply system. In this chapter, we first discuss the objective existence, decomposition mechanism and harmness of insulation defects. Then the methods for insulation defects detection used to avoid the insulation accidents are introduced. Comparing all of the detection methods, diagnosing the insulation defect through analyzing the decomposed gases of SF6 by chemical gas sensors is the optimal method due to its advantages, such as high detection accuracy and stability, signifying the importance of developing chemical gas sensor used in SF6 insulated equipment. In conclusion, there kinds of gas sensor material, carbon nanotubes, graphene, are chosen as the gas sensing materials to build specific gas sensors for detecting each kind of SF6 decomposed gases, and then enhance the gas sensitivity and selectivity by material modification
Identification of metabolism pathways directly regulated by sigma54 factor in Bacillus thuringiensis
Sigma54 (σ54) normally regulates nitrogen and carbon utilization in bacteria. Promoters that are σ54-dependent are highly conserved and contain short sequences located at the −24 and −12 positions upstream of the transcription initiation site. σ54 requires regulatory proteins known as bacterial enhancer-binding proteins (bEBPs) to activate gene transcription. We show that σ54 regulates the capacity to grow on various nitrogen sources using a Bacillus thuringiensis HD73 mutant lacking the sigL gene encoding σ54 (ΔsigL). A 2-fold-change cutoff and a false discovery rate cutoff of P < 0.05 were used to analyze the DNA microarray data, which revealed 255 genes that were downregulated and 121 that were upregulated in the ΔsigL mutant relative to the wild-type HD73 strain. The σ54 regulon (stationary phase) was characterized by DNA microarray, bioinformatics, and functional assay; 16 operons containing 47 genes were identified whose promoter regions contain the conserved −12/−24 element and whose transcriptional activities were abolished or reduced in the ΔsigL mutant. Eight σ54-dependent transcriptional bEBPs were found in the Bt HD73 genome, and they regulated night σ54-dependent promoters.The metabolic pathways activated by σ54 in this process have yet to be identified in Bacillus thuringiensis; nonetheless, the present analysis of the σ54 regulon provides a better understanding of the physiological roles of σ factors in bacteria
Comparative Study of Materials to SF6 Decomposition Components
In order to judge the inside insulation fault of SF6 insulated equipment, the gas-sensing properties to a series of characteristic SF6 decomposition components, SOF2, SO2F2, SO2, H2S, CF4, HF, and SF6, have been studied. In this study, a comparative study of these gas-sensing materials has been made in theoretical and experimental fields to find the optimal gas-sensing material, and put forward the effective approaches to improve the gas-sensing properties of materials
LightGrad: Lightweight Diffusion Probabilistic Model for Text-to-Speech
Recent advances in neural text-to-speech (TTS) models bring thousands of TTS
applications into daily life, where models are deployed in cloud to provide
services for customs. Among these models are diffusion probabilistic models
(DPMs), which can be stably trained and are more parameter-efficient compared
with other generative models. As transmitting data between customs and the
cloud introduces high latency and the risk of exposing private data, deploying
TTS models on edge devices is preferred. When implementing DPMs onto edge
devices, there are two practical problems. First, current DPMs are not
lightweight enough for resource-constrained devices. Second, DPMs require many
denoising steps in inference, which increases latency. In this work, we present
LightGrad, a lightweight DPM for TTS. LightGrad is equipped with a lightweight
U-Net diffusion decoder and a training-free fast sampling technique, reducing
both model parameters and inference latency. Streaming inference is also
implemented in LightGrad to reduce latency further. Compared with Grad-TTS,
LightGrad achieves 62.2% reduction in paramters, 65.7% reduction in latency,
while preserving comparable speech quality on both Chinese Mandarin and English
in 4 denoising steps.Comment: Accepted by ICASSP 202
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Cry78Aa, a novel Bacillus thuringiensis insecticidal protein with activity against Laodelphax striatellus and Nilaparvata lugens
Transgenic plants expressing insecticidal proteins originating from Bacillus thuringiensis (Bt) have successfully been used to control lepidopteran and coleopteran pests with chewing mouthparts. However, only a handful of Bt proteins have been identified that have bioactivity against sap sucking pests (Hemiptera), including aphids, whiteflies, plant bugs and planthoppers. A novel Bt insecticidal protein with significant toxicity against a hemipteran insect pest is described here. The gene encoding the 359 amino acid, 40.7 kDa protein was cloned from strain C9F1. After expression and purification of the toxin, its median lethal concentration (LC) values against Laodelphax striatellus and Nilaparvata lugens were determined as 6.89 μg/mL and 15.78 μg/mL respectively. Analysis of the toxin sequence revealed the presence of both Toxin_10 and Ricin_B_Lectin domains
ZeroPrompt: Streaming Acoustic Encoders are Zero-Shot Masked LMs
In this paper, we present ZeroPrompt (Figure 1-(a)) and the corresponding
Prompt-and-Refine strategy (Figure 3), two simple but effective
\textbf{training-free} methods to decrease the Token Display Time (TDT) of
streaming ASR models \textbf{without any accuracy loss}. The core idea of
ZeroPrompt is to append zeroed content to each chunk during inference, which
acts like a prompt to encourage the model to predict future tokens even before
they were spoken. We argue that streaming acoustic encoders naturally have the
modeling ability of Masked Language Models and our experiments demonstrate that
ZeroPrompt is engineering cheap and can be applied to streaming acoustic
encoders on any dataset without any accuracy loss. Specifically, compared with
our baseline models, we achieve 350 700ms reduction on First Token
Display Time (TDT-F) and 100 400ms reduction on Last Token Display Time
(TDT-L), with theoretically and experimentally equal WER on both Aishell-1 and
Librispeech datasets.Comment: accepted by interspeech 202
Fast-U2++: Fast and Accurate End-to-End Speech Recognition in Joint CTC/Attention Frames
Recently, the unified streaming and non-streaming two-pass (U2/U2++)
end-to-end model for speech recognition has shown great performance in terms of
streaming capability, accuracy and latency. In this paper, we present
fast-U2++, an enhanced version of U2++ to further reduce partial latency. The
core idea of fast-U2++ is to output partial results of the bottom layers in its
encoder with a small chunk, while using a large chunk in the top layers of its
encoder to compensate the performance degradation caused by the small chunk.
Moreover, we use knowledge distillation method to reduce the token emission
latency. We present extensive experiments on Aishell-1 dataset. Experiments and
ablation studies show that compared to U2++, fast-U2++ reduces model latency
from 320ms to 80ms, and achieves a character error rate (CER) of 5.06% with a
streaming setup.Comment: 5 pages, 3 figure
Use of redundant exclusion PCR to identify a novel Bacillus thuringiensis Cry8 toxin gene from pooled genomic DNA
With the aim of optimizing the cloning of novel genes from a genomic pool containing many previously identified, homologous, genes we designed a redundant exclusion PCR technique. In RE-PCR a pair of generic amplification primers are combined with additional primers that are designed to specifically bind to redundant, unwanted genes that are a subset of those copied by the amplification primers. During RE-PCR the specific primer blocks amplification of the full length redundant gene. Using this method we managed to clone a number of cry8 or cry9 toxin genes from a pool of Bacillus thuringiensis genomic DNA while excluding amplicons for cry9Da, cry9Ea and cry9Eb. The method proved very efficient at increasing the number of rare genes in the resulting library. One such rare, and novel, cry8-like gene was expressed and the encoded toxin was shown to be toxic to Anomola corpulenta
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