China carbon emission accounts 2020-2021

In the past a few years, the outbreak of the COVID-19 epidemic has significantly changed global emission patterns and increased the challenges in emission reduction. However, a comprehensive analysis of the most recent trends of China's carbon emissions has not been conducted due to a lack of up-to-date emission accounts by regions and sectors. This study compiles the latest CO2 emission inventories for China and its 30 provinces during the epidemic (2020−2021), following the administrative-territorial approach from the International Panel on Climate Change (IPCC). Our inventories cover energy-related emissions from 17 types of fossil fuel combustion and cement production across 47 economic sectors. To provide a holistic view of emission patterns, we esitamted consumption-based emissions in China. We find that the COVID-19 epidemic led to a 50% reduction in the growth rate of territorial emissions in 2020 compared to 2019. This trend then reversed in 2021 as lockdown measures gradually relaxed. Our study reveals the impact of the rapid expansion of exports, driven by epidemic prevention materials and “stay-at-home economy” products on widening the differences between territorial- and consumption-based emissions. Our study offers a timely blueprint for designing strategies towards carbon peak and neutrality, especially in the context of sustainable recoveries and carbon mitigation post-pandemic.</p

Spatiotemporal evolution and drivers of carbon inequalities in urban agglomeration:An MLD-IDA inequality indicator decomposition

Increasing countries are articulating ambitious goals of carbon neutrality. However, large inequalities in regional emissions within a country may hinder progress toward a carbon–neutral future, as the unequal distribution of reduction responsibilities among regions could impair just transition and exacerbate uneven development, which necessitates an in-depth understanding of the mechanism of multi-scale carbon inequalities within country, region, and city. Yet, the evolution of carbon inequalities within urban agglomerations and the differences between adjacent or distant urban agglomerations have not been well understood, especially in countries undergoing rapid urbanization. Using the data of 89 cities in China’s Yangtze River Economic Belt (YREB) during 2006–2021, this paper quantifies carbon emissions inequality (CEI) at different scales in a systematic regional-urban agglomeration-city hierarchical structure. Then, under the integrated mean logarithmic deviation-logarithmic mean Divisia index (MLD-LMDI) decomposition framework, multi-scale CEIs are perfectly decomposed into six interrelated drivers, i.e., industrial emission structure, energy emission intensity, industrial energy mix, energy intensity, industrial structure, and economic development. The results show that economic development, energy intensity, and industrial energy mix disparities are the main determinants accounting for CEIs at different scales. The decreasing CEI in YREB is mainly due to the changes in industrial structure and economic development, while the energy intensity effect partially hinders the mitigation of CEI. In the upper reaches of the YREB, the energy intensity effect accounts for over 94% growth of CEI during 2006–2021, while the decline in CEIs in middle and lower reaches is primarily caused by the effects of industrial energy mix and industrial structure, respectively. Further spatial decomposition analysis reveals more refined city-level heterogeneous effects and emphasizes the prioritized emission reduction direction for each city. This paper offers implications for reducing carbon inequality and insights into coordinated carbon emissions mitigation at the regional level for a carbon–neutral future

A dataset of low-carbon energy transition index for Chinese cities 2003–2019

Cities are at the heart of climate change mitigation as they account for over 70% of global carbon emissions. However, cities vary in their energy systems and socioeconomic capacities to transition to renewable energy. To address this heterogeneity, this study proposes an Energy Transition Index (ETI) specifically designed for cities, and applies it to track the progress of energy transition in Chinese cities. The city-level ETI framework is based on the national ETI developed by the World Economic Forum (WEF) and comprises two sub-indexes: the Energy System Performance sub-index, which evaluates the current status of cities’ energy systems in terms of energy transition, and the Transition Readiness sub-index, which assesses their socioeconomic capacity for future energy transition. The initial version of the dataset includes ETI and its sub-indexes for 282 Chinese cities from 2003 to 2019, with annual updates planned. The spatiotemporal data provided by the dataset facilitates research into the energy transition roadmap for different cities, which can help China achieve its energy transition goals

Notoginseng root enhances healing in imiquimod-induced psoriasis mice model via anti-inflammatory and antiproliferative properties

Purpose: To evaluate the beneficial effect of Panax notoginseng (PN) gel against imiquimod-induced psoriasis in a mice model.Methods: Psoriasis was induced by topical application of imiquimod cream (5 %) on the shaved skin of mice for 7 days. PN group received PN gel (1 %) twice a day with imiquimod cream (5 %) once a day for one week. The effect of PN gel was estimated by scoring skin thickness, scaling and erythema. Reverse transcription polymerase chain reaction (RT-PCR) was used for the determination of the expressions of inflammatory mediators in skin tissues of mice. Moreover, the severity of inflammation was determined by histopathological and immunohistochemical assessment of skin tissues.Results: The severity of inflammation and the expressions of inflammatory mediators were significantly reduced in PN gel-treated group, relative to the negative control group. Treatment with PN gel attenuated the histopathology of skin tissue in the imiquimod-induced psoriatic mice, and significantly decreased the level of intercellular adhesion molecule (ICAM-1), when compared to the negative control group.Conclusion: These results show that PN gel attenuates psoriasis in imiquimod-induced psoriasis mice model by decreasing skin inflammation. Thus, PN gel may be suitable for the management of psoriasis.Keywords: Psoriasis, Panax notoginseng, Inflammatory mediators, Imiquimod, Intercellular Adhesion Molecule-

Genomic prediction based on a joint reference population for the Xinjiang Brown cattle

Introduction: Xinjiang Brown cattle constitute the largest breed of cattle in Xinjiang. Therefore, it is crucial to establish a genomic evaluation system, especially for those with low levels of breed improvement.Methods: This study aimed to establish a cross breed joint reference population by analyzing the genetic structure of 485 Xinjiang Brown cattle and 2,633 Chinese Holstein cattle (Illumina GeneSeek GGP bovine 150 K chip). The Bayes method single-step genome-wide best linear unbiased prediction was used to conduct a genomic evaluation of the joint reference population for the milk traits of Xinjiang Brown cattle. The reference population of Chinese Holstein cattle was randomly divided into groups to construct the joint reference population. By comparing the prediction accuracy, estimation bias, and inflation coefficient of the validation population, the optimal number of joint reference populations was determined.Results and Discussion: The results indicated a distinct genetic structure difference between the two breeds of adult cows, and both breeds should be considered when constructing multi-breed joint reference and validation populations. The reliability range of genome prediction of milk traits in the joint reference population was 0.142–0.465. Initially, it was determined that the inclusion of 600 and 900 Chinese Holstein cattle in the joint reference population positively impacted the genomic prediction of Xinjiang Brown cattle to certain extent. It was feasible to incorporate the Chinese Holstein into Xinjiang Brown cattle population to form a joint reference population for multi-breed genomic evaluation. However, for different Xinjiang Brown cattle populations, a fixed number of Chinese Holstein cattle cannot be directly added during multi-breed genomic selection. Pre-evaluation analysis based on the genetic structure, kinship, and other factors of the current population is required to ensure the authenticity and reliability of genomic predictions and improve estimation accuracy

Multi-label classification for biomedical literature: an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations

The coronavirus disease 2019 (COVID-19) pandemic has been severely impacting global society since December 2019. The related findings such as vaccine and drug development have been reported in biomedical literature—at a rate of about 10 000 articles on COVID-19 per month. Such rapid growth significantly challenges manual curation and interpretation. For instance, LitCovid is a literature database of COVID-19-related articles in PubMed, which has accumulated more than 200 000 articles with millions of accesses each month by users worldwide. One primary curation task is to assign up to eight topics (e.g. Diagnosis and Treatment) to the articles in LitCovid. The annotated topics have been widely used for navigating the COVID literature, rapidly locating articles of interest and other downstream studies. However, annotating the topics has been the bottleneck of manual curation. Despite the continuing advances in biomedical text-mining methods, few have been dedicated to topic annotations in COVID-19 literature. To close the gap, we organized the BioCreative LitCovid track to call for a community effort to tackle automated topic annotation for COVID-19 literature. The BioCreative LitCovid dataset—consisting of over 30 000 articles with manually reviewed topics—was created for training and testing. It is one of the largest multi-label classification datasets in biomedical scientific literature. Nineteen teams worldwide participated and made 80 submissions in total. Most teams used hybrid systems based on transformers. The highest performing submissions achieved 0.8875, 0.9181 and 0.9394 for macro-F1-score, micro-F1-score and instance-based F1-score, respectively. Notably, these scores are substantially higher (e.g. 12%, higher for macro F1-score) than the corresponding scores of the state-of-art multi-label classification method. The level of participation and results demonstrate a successful track and help close the gap between dataset curation and method development. The dataset is publicly available via https://ftp.ncbi.nlm.nih.gov/pub/lu/LitCovid/biocreative/ for benchmarking and further development

SoccerNet 2023 Challenges Results

peer reviewedThe SoccerNet 2023 challenges were the third annual video understanding challenges organized by the SoccerNet team. For this third edition, the challenges were composed of seven vision-based tasks split into three main themes. The first theme, broadcast video understanding, is composed of three high-level tasks related to describing events occurring in the video broadcasts: (1) action spotting, focusing on retrieving all timestamps related to global actions in soccer, (2) ball action spotting, focusing on retrieving all timestamps related to the soccer ball change of state, and (3) dense video captioning, focusing on describing the broadcast with natural language and anchored timestamps. The second theme, field understanding, relates to the single task of (4) camera calibration, focusing on retrieving the intrinsic and extrinsic camera parameters from images. The third and last theme, player understanding, is composed of three low-level tasks related to extracting information about the players: (5) re-identification, focusing on retrieving the same players across multiple views, (6) multiple object tracking, focusing on tracking players and the ball through unedited video streams, and (7) jersey number recognition, focusing on recognizing the jersey number of players from tracklets. Compared to the previous editions of the SoccerNet challenges, tasks (2-3-7) are novel, including new annotations and data, task (4) was enhanced with more data and annotations, and task (6) now focuses on end-to-end approaches. More information on the tasks, challenges, and leaderboards are available on https://www.soccer-net.org. Baselines and development kits can be found on https://github.com/SoccerNet

Host and Viral Genetic Variation in HBV-Related Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common cancer in men and the second leading cause of cancer deaths globally. The high prevalence of HCC is due in part to the high prevalence of chronic HBV infection and the high mortality rate is due to the lack of biomarkers for early detection and limited treatment options for late stage HCC. The observed individual variance in development of HCC is attributable to differences in HBV genotype and mutations, host predisposing germline genetic variations, the acquisition of tumor-specific somatic mutations, as well as environmental factors. HBV genotype C and mutations in the preS, basic core promoter (BCP) or HBx regions are associated with an increased risk of HCC. Genome-wide association studies have identified common polymorphisms in KIF1B, HLA-DQ, STAT4, and GRIK1 with altered risk of HBV-related HCC. HBV integration into growth control genes (such as TERT), pro-oncogenic genes, or tumor suppressor genes and the oncogenic activity of truncated HBx promote hepatocarcinogenesis. Somatic mutations in the TERT promoter and classic cancer signaling pathways, including Wnt (CTNNB1), cell cycle regulation (TP53), and epigenetic modification (ARID2 and MLL4) are frequently detected in hepatic tumor tissues. The identification of HBV and host variation associated with tumor initiation and progression has clinical utility for improving early diagnosis and prognosis; whereas the identification of somatic mutations driving tumorigenesis hold promise to inform precision treatment for HCC patients

A study on Static behavior of New Reinforced concrete column-steel beam Composite Joints

Through Experiment, we study the aseismic behavior of inserted reinforced concrete column-steel beam (RCS) composite joints. In order to design an RCS with endplate combination joint, we analyze simulation test joints on a basis of the static load test combining with finite element software ABAQUS. The numerical simulation results and the contract test results which include finite element simulation of load–displacement curve of bending moment–rotation curve and the components of yield sequence are basically the same as the experiment results. This uniformity verifies the reliability to use numerical simulation upon such problems. To compare with the ordinary reinforced concrete structures, the new type of inserted RCS composite joints is safer, and it presents a better seismic performance under the static load of the beam end. After we use numerical simulation to study the influential factors of six kinds of RCS combination of static performance including the axial compression ratio, steel insert length, the thickness of endplate, the ratio of the width of column section and beam section, the column concrete grade and four kinds of joint structure, we found that it does not only well perform on mechanical aspect but also is simple and convenient on the structure and construction of RCS composite nodes