Quantitative Amenability for Actions of Finitely Generated Groups

We generalize the notion of isoperimetric profiles of finitely generated groups to their actions by measuring the boundary of finite subgraphings of the orbit graphing. We prove that like the classical isoperimetric profiles for groups, decay of the isoperimetric profile for the essentially-free action is equivalent to amenability of the action in the sense of Zimmer. For measure-preserving actions, we find the bounds between the original and generalized isoperimetric profiles for measure-preserving actions.Comment: 12 page

Relations of blood lead levels to echocardiographic left ventricular structure and function in preschool children

Lead (Pb) has been proved to exert adverse effect on human cardiovascular system. However, the cardiotoxicity of Pb on children is still unclear. The aim of this study was to evaluate left ventricular (LV) structure and function, by using echocardiographic indices, in order to elucidate the effect of Pb on low-grade inflammation related to left ventricle in healthy preschool children. We recruited a total of 486 preschool children, 310 from Guiyu (e-waste-exposed area) and 176 from Haojiang (reference area). Blood Pb levels, complete blood counts, and LV parameters were evaluated. Associations between blood Pb levels and LV parameters and peripheral leukocyte counts were analyzed using linear regression models. The median blood level of Pb and the counts of white blood cells (WBCs), monocytes, and neutrophils were higher in exposed group. In addition, the exposed group showed smaller left ventricle (including interventricular septum, LV posterior wall, and LV mass index) and impaired LV systolic function (including LV fractional shortening and LV ejection fraction) regardless gender. After adjustment for confounding factors, elevated blood Pb levels were significantly associated with higher counts of WBCs and neutrophils, and lower levels of LV parameters. Furthermore, counts of WBCs, monocytes, and neutrophils were negatively correlated with LV parameters. Taken together, smaller left ventricle and impaired systolic function were found in e-waste-exposed children and associated with chronic low-grade inflammation and elevated blood Pb levels. It indicates that the heart health of e-waste-exposed children is at risk due to the long-term environmental chemical insults. (C) 2020 Elsevier Ltd. All rights reserved

Information recoverability of noisy quantum states

Extracting classical information from quantum systems is an essential step of many quantum algorithms. However, this information could be corrupted as the systems are prone to quantum noises, and its distortion under quantum dynamics has not been adequately investigated. In this work, we introduce a systematic framework to study how well we can retrieve information from noisy quantum states. Given a noisy quantum channel, we fully characterize the range of recoverable classical information. This condition allows a natural measure quantifying the information recoverability of a channel. Moreover, we resolve the minimum information retrieving cost, which, along with the corresponding optimal protocol, is efficiently computable by semidefinite programming. As applications, we establish the limits on the information retrieving cost for practical quantum noises and employ the corresponding protocols to mitigate errors in ground state energy estimation. Our work gives the first full characterization of information recoverability of noisy quantum states from the recoverable range to the recovering cost, revealing the ultimate limit of probabilistic error cancellation

Two-stage Neural Network for ICASSP 2023 Speech Signal Improvement Challenge

In ICASSP 2023 speech signal improvement challenge, we developed a dual-stage neural model which improves speech signal quality induced by different distortions in a stage-wise divide-and-conquer fashion. Specifically, in the first stage, the speech improvement network focuses on recovering the missing components of the spectrum, while in the second stage, our model aims to further suppress noise, reverberation, and artifacts introduced by the first-stage model. Achieving 0.446 in the final score and 0.517 in the P.835 score, our system ranks 4th in the non-real-time track.Comment: Accepted by ICASSP 202

GLM-130B: An Open Bilingual Pre-trained Model

We introduce GLM-130B, a bilingual (English and Chinese) pre-trained language model with 130 billion parameters. It is an attempt to open-source a 100B-scale model at least as good as GPT-3 (davinci) and unveil how models of such a scale can be successfully pre-trained. Over the course of this effort, we face numerous unexpected technical and engineering challenges, particularly on loss spikes and divergence. In this paper, we introduce the training process of GLM-130B including its design choices, training strategies for both efficiency and stability, and engineering efforts. The resultant GLM-130B model offers significant outperformance over GPT-3 175B (davinci) on a wide range of popular English benchmarks while the performance advantage is not observed in OPT-175B and BLOOM-176B. It also consistently and significantly outperforms ERNIE TITAN 3.0 260B -- the largest Chinese language model -- across related benchmarks. Finally, we leverage a unique scaling property of GLM-130B to reach INT4 quantization without post training, with almost no performance loss, making it the first among 100B-scale models and more importantly, allowing its effective inference on 4$\times$RTX 3090 (24G) or 8$\times$RTX 2080 Ti (11G) GPUs, the most affordable GPUs required for using 100B-scale models. The GLM-130B model weights are publicly accessible and its code, training logs, related toolkit, and lessons learned are open-sourced at \url{https://github.com/THUDM/GLM-130B/}.Comment: Accepted to ICLR 202

Comparison of the transcriptome and metabolome of wheat (Triticum aestivum L.) proteins content during grain formation provides insight

IntroductionWheat is a food crop with a large global cultivation area, and the content and quality of wheat glutenin accumulation are important indicators of the quality of wheat flour.MethodsTo elucidate the gene expression regulation and metabolic characteristics related to the gluten content during wheat grain formation, transcriptomic and metabolomic analyses were performed for the high gluten content of the Xinchun 26 cultivar and the low proteins content of the Xinchun 34 cultivar at three periods (7 d, 14 d and 21 d) after flowering.ResultsTranscriptomic analysis revealed that 5573 unique differentially expressed genes (DEGs) were divided into two categories according to their expression patterns during the three periods. The metabolites detected were mainly divided into 12 classes. Lipid and lipid-like molecule levels and phenylpropanoid and polyketide levels were the highest, and the difference analysis revealed a total of 10 differentially regulated metabolites (DRMs) over the three periods. Joint analysis revealed that the DEGs and DRMs were significantly enriched in starch and sucrose metabolism; the citrate cycle; carbon fixation in photosynthetic organisms; and alanine, aspartate and glutamate metabolism pathways. The genes and contents of the sucrose and gluten synthesis pathways were analysed, and the correlation between gluten content and its related genes was calculated. Based on weighted correlation network analysis (WGCNA), by constructing a coexpression network, a total of 5 specific modules and 8 candidate genes that were strongly correlated with the three developmental stages of wheat grain were identified.DiscussionThis study provides new insights into the role of glutenin content in wheat grain formation and reveals potential regulatory pathways and candidate genes involved in this developmental process

Information recoverability of noisy quantum states

Extracting classical information from quantum systems is an essential step of many quantum algorithms. However, this information could be corrupted as the systems are prone to quantum noises, and its distortion under quantum dynamics has not been adequately investigated. In this work, we introduce a systematic framework to study how well we can retrieve information from noisy quantum states. Given a noisy quantum channel, we fully characterize the range of recoverable classical information. This condition allows a natural measure quantifying the information recoverability of a channel. Moreover, we resolve the minimum information retrieving cost, which, along with the corresponding optimal protocol, is efficiently computable by semidefinite programming. As applications, we establish the limits on the information retrieving cost for practical quantum noises and employ the corresponding protocols to mitigate errors in ground state energy estimation.Comment: 18 pages including appendi

Elevator Safety Monitoring System Based on Internet of Things

In view of the frequent occurrence of elevator accidents, an elevator safety monitoring system based on the Internet of things (IOT) was designed. First, the requirements of elevator safety monitoring system were analyzed in terms of function and performance, andthe feasibility of the system was evaluated from perspectives of demand, technology, and practical operation. The design scheme of the system was then presented, which combined the Brower/Server (B/S) and Client/Server (C/S) architectures. As the client of the command and control center, the front-end monitoring system communicated and interacted with it and used the standard real-time transport protocol (RTP) for transmission. Finally, the elevator safety monitoring system was implemented. The test showed that the function and performance of the proposed elevator safety monitoring system achieved the designed target of the system and had practical application value

Estimating Vehicle Fuel Consumption and Emissions Using GPS Big Data

The energy consumption and emissions from vehicles adversely affect human health and urban sustainability. Analysis of GPS big data collected from vehicles can provide useful insights about the quantity and distribution of such energy consumption and emissions. Previous studies, which estimated fuel consumption/emissions from traffic based on GPS sampled data, have not sufficiently considered vehicle activities and may have led to erroneous estimations. By adopting the analytical construct of the space-time path in time geography, this study proposes methods that more accurately estimate and visualize vehicle energy consumption/emissions based on analysis of vehicles’ mobile activities (MA) and stationary activities (SA). First, we build space-time paths of individual vehicles, extract moving parameters, and identify MA and SA from each space-time path segment (STPS). Then we present an N-Dimensional framework for estimating and visualizing fuel consumption/emissions. For each STPS, fuel consumption, hot emissions, and cold start emissions are estimated based on activity type, i.e., MA, SA with engine-on and SA with engine-off. In the case study, fuel consumption and emissions of a single vehicle and a road network are estimated and visualized with GPS data. The estimation accuracy of the proposed approach is 88.6%. We also analyze the types of activities that produced fuel consumption on each road segment to explore the patterns and mechanisms of fuel consumption in the study area. The results not only show the effectiveness of the proposed approaches in estimating fuel consumption/emissions but also indicate their advantages for uncovering the relationships between fuel consumption and vehicles’ activities in road networks