AR3D: Attention Residual 3D Network for Human Action Recognition

At present, in the field of video-based human action recognition, deep neural networks are mainly divided into two branches: the 2D convolutional neural network (CNN) and 3D CNN. However, 2D CNN’s temporal and spatial feature extraction processes are independent of each other, which means that it is easy to ignore the internal connection, affecting the performance of recognition. Although 3D CNN can extract the temporal and spatial features of the video sequence at the same time, the parameters of the 3D model increase exponentially, resulting in the model being difficult to train and transfer. To solve this problem, this article is based on 3D CNN combined with a residual structure and attention mechanism to improve the existing 3D CNN model, and we propose two types of human action recognition models (the Residual 3D Network (R3D) and Attention Residual 3D Network (AR3D)). Firstly, in this article, we propose a shallow feature extraction module and improve the ordinary 3D residual structure, which reduces the parameters and strengthens the extraction of temporal features. Secondly, we explore the application of the attention mechanism in human action recognition and design a 3D spatio-temporal attention mechanism module to strengthen the extraction of global features of human action. Finally, in order to make full use of the residual structure and attention mechanism, an Attention Residual 3D Network (AR3D) is proposed, and its two fusion strategies and corresponding model structure (AR3D_V1, AR3D_V2) are introduced in detail. Experiments show that the fused structure shows different degrees of performance improvement compared to a single structure

A Working Fluid Assessment for a Biomass Organic Rankine Cycle under Different Conditions

Many thermal resources are not reasonably used in the chemical industry’s production process. To recover the waste heat from organic waste residue-calcium carbonate (CaCO3), which is added to inhibit hydrogen production, an organic Rankine cycle (ORC) system is applied in this research. An ORC system can reuse the low-temperature waste heat that is not fully utilized. In this study, the mathematical model of the biomass ORC power generation system is constructed. Five organic working fluids, R11, R113, R123, R141b, and R245fa, were selected from the physical characteristics and safety of working fluids. The system application case is the low-temperature heat absorption in a chemical industry’s production process. The system is simulated by Aspen Plus V11 software, so as to study and analyze the influence of different working fluids and working conditions on the system performance and to obtain the preferred working fluids under different working conditions. At the same time, the economic evaluation and entropy method of the system are evaluated by using the investment profit rate PRI from different angles. It can be found that R11 and R141b have advantages, but R11 does not have advantages in environmental aspects. Through research, it is found that it is difficult to have a working fluid that can adapt to the biomass ORC power generation system under any working conditions. This paper can provide a basis for the subsequent research and selection of working fluids in the biomass ORC system

A Working Fluid Assessment for a Biomass Organic Rankine Cycle under Different Conditions

Many thermal resources are not reasonably used in the chemical industry’s production process. To recover the waste heat from organic waste residue-calcium carbonate (CaCO3), which is added to inhibit hydrogen production, an organic Rankine cycle (ORC) system is applied in this research. An ORC system can reuse the low-temperature waste heat that is not fully utilized. In this study, the mathematical model of the biomass ORC power generation system is constructed. Five organic working fluids, R11, R113, R123, R141b, and R245fa, were selected from the physical characteristics and safety of working fluids. The system application case is the low-temperature heat absorption in a chemical industry’s production process. The system is simulated by Aspen Plus V11 software, so as to study and analyze the influence of different working fluids and working conditions on the system performance and to obtain the preferred working fluids under different working conditions. At the same time, the economic evaluation and entropy method of the system are evaluated by using the investment profit rate PRI from different angles. It can be found that R11 and R141b have advantages, but R11 does not have advantages in environmental aspects. Through research, it is found that it is difficult to have a working fluid that can adapt to the biomass ORC power generation system under any working conditions. This paper can provide a basis for the subsequent research and selection of working fluids in the biomass ORC system

Whole Genome Analyses of Chinese Population and De Novo Assembly of A Northern Han Genome

To unravel the genetic mechanisms of disease and physiological traits, it requires comprehensive sequencing analysis of large sample size in Chinese populations. Here, we report the primary results of the Chinese Academy of Sciences Precision Medicine Initiative (CASPMI) project launched by the Chinese Academy of Sciences, including the de novo assembly of a northern Han reference genome (NH1.0) and whole genome analyses of 597 healthy people coming from most areas in China. Given the two existing reference genomes for Han Chinese (YH and HX1) were both from the south, we constructed NH1.0, a new reference genome from a northern individual, by combining the sequencing strategies of PacBio, 10× Genomics, and Bionano mapping. Using this integrated approach, we obtained an N50 scaffold size of 46.63 Mb for the NH1.0 genome and performed a comparative genome analysis of NH1.0 with YH and HX1. In order to generate a genomic variation map of Chinese populations, we performed the whole-genome sequencing of 597 participants and identified 24.85 million (M) single nucleotide variants (SNVs), 3.85 M small indels, and 106,382 structural variations. In the association analysis with collected phenotypes, we found that the T allele of rs1549293 in KAT8 significantly correlated with the waist circumference in northern Han males. Moreover, significant genetic diversity in MTHFR, TCN2, FADS1, and FADS2, which associate with circulating folate, vitamin B12, or lipid metabolism, was observed between northerners and southerners. Especially, for the homocysteine-increasing allele of rs1801133 (MTHFR 677T), we hypothesize that there exists a “comfort” zone for a high frequency of 677T between latitudes of 35–45 degree North. Taken together, our results provide a high-quality northern Han reference genome and novel population-specific data sets of genetic variants for use in the personalized and precision medicine. Keywords: De novo assembly, Reference genome, Variation map, Phenotype association, Large populatio

Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2021

The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a suite of database resources to support worldwide research activities in both academia and industry. With the explosive growth of multiomics data, CNCB-NGDC is continually expanding, updating and enriching its core database resources through big data deposition, integration and translation. In the past year, considerable efforts have been devoted to 2019nCoVR, a newly established resource providing a global landscape of SARS-CoV-2 genomic sequences, variants, and haplotypes, as well as Aging Atlas, BrainBase, GTDB (Glycosyltransferases Database), LncExpDB, and TransCirc (Translation potential for circular RNAs). Meanwhile, a series of resources have been updated and improved, including BioProject, BioSample, GWH (Genome Warehouse), GVM (Genome Variation Map), GEN (Gene Expression Nebulas) as well as several biodiversity and plant resources. Particularly, BIG Search, a scalable, one-stop, cross-database search engine, has been significantly updated by providing easy access to a large number of internal and external biological resources from CNCB-NGDC, our partners, EBI and NCBI. All of these resources along with their services are publicly accessible at https://bigd.big.ac.cn