Improved combustion stability of biogas at different CO_(2) concentrations using inhomogeneous partially premixed stratified flames

Biogas is a renewable and clean energy source that plays an important role in the current environment of lowcarbon transition.If high-content CO_(2) in biogas can be separated,transformed,and utilized,it not only realizes high-value utilization of biogas but also promotes carbon reduction in the biogas field.To improve the combustion stability of biogas,an inhomogeneous,partially premixed stratified(IPPS)combustion model was adopted in this study.The thermal flame structure and stability were investigated for a wide range of mixture inhomogeneities,turbulence levels,CO_(2) concentrations,air-to-fuel velocity ratios,and combustion energies in a concentric flow slot burner(CFSB).A fine-wire thermocouple is used to resolve the thermal flame structure.The flame size was reduced by increasing the CO_(2) concentration and the flames became lighter blue.The flame temperature also decreased with increase in CO_(2) concentration.Flame stability was reduced by increasing the CO_(2) concentration.However,at a certain level of mixture inhomogeneity,the concentration of CO_(2) in the IPPS mode did not affect the stability.Accordingly,the IPPS mode of combustion should be suitable for the combustion and stabilization of biogas.This should support the design of highly stabilized biogas turbulent flames independent of CO_(2) concentration.The data show that the lower stability conditions are partially due to the change in fuel combustion energy,which is characterized by the Wobbe index(WI).In addition,at a certain level of mixture inhomogeneity,the effect of the WI on flame stability becomes dominant.

Impact of the carbon market on investment benefits of power-grid enterprises in China: a system dynamics analysis

The power grid,as the hub connecting the power supply and consumption sides,plays an important role in achieving carbon neutrality in China.In emerging carbon markets,assessing the investment benefits of power-grid enterprises is essential.Thus,studying the impact of the carbon market on the investment and operation of powergrid enterprises is key to ensuring their efficient operation.Notably,few studies have examined the interaction between the carbon and electricity markets using system dynamics models,highlighting a research gap in this area.This study investigates the impact of the carbon market on the investment of power-grid enterprises using a novel evaluation system based on a system dynamics model that considers carbon-emissions from an established carbon-emission accounting model.First,an index system for benefit evaluation was constructed from six aspects:financing ability,economic benefit,reliability,social responsibility,user satisfaction,and carbon-emissions.A system dynamics model was then developed to reflect the causal feedback relationship between the impact of the carbon market on the investment and operation of power-grid enterprises.The simulation results of a provincial power-grid enterprise analyze comprehensive investment evaluation benefits over a 10-year period and the impact of carbon emissions on the investment and operation of power-grid enterprises.This study provides guidelines for the benign development of power-grid enterprises within the context of the carbon market.

Exploration of Interdisciplinary Integration in Teaching Reform of Legal Studies and Auditing

This paper attempts to explore interdisciplinary integration from four aspects:the necessity of interdisciplinary integration between legal studies and auditing,the difficulties and challenges encountered in this integration,the ideas for teaching reform in the context of interdisciplinary integration,and the expected outcomes.The aim is to achieve an organic integration of legal studies and auditing through systematic teaching reforms,thereby providing students with comprehensive and integrated knowledge and skills training,ensuring the quality of talent cultivation,and adapting to the needs of social development.

Coordinated restoration optimization of power-gas integrated energy system with mobile emergency sources

In an integrated energy system(IES) composed of multiple subsystems, energy coupling causes an energy supply blockage or shutdown in one subsystem, thereby affecting the energy flow distribution optimization of other subsystems.The energy supply should be globally optimized during the IES energy supply restoration process to produce the highest restoration net income. Mobile emergency sources can be quickly and flexibly connected to supply energy after an energy outage to ensure a reliable supply to the system, which adds complexity to the decision. This study focuses on a powergas IES with mobile emergency sources and analyzes the coupling relationship between the gas distribution system and the power distribution system in terms of sources, networks, and loads, and the influence of mobile emergency source transportation. The influence of the transient process caused by the restoration operation of the gas distribution system on the power distribution system is also discussed. An optimization model for power-gas IES restoration was established with the objective of maximizing the net income. The coordinated restoration optimization decision-making process was also built to realize the decoupling iteration of the power-gas IES, including system status recognition, mobile emergency source dispatching optimization, gas-to-power gas flow optimization, and parallel intra-partition restoration scheme optimization for both the power and gas distribution systems. A simulation test power-gas IES consisting of an 81-node medium-voltage power distribution network, an 89-node medium-pressure gas distribution network, and four mobile emergency sources was constructed. The simulation analysis verified the efficiency of the proposed coordinated restoration optimization method.

Daily rolling estimation of carbon emission cost of coal-fired units considering long-cycle interactive operation simulation of carbon-electricity market

The high overlap of participants in the carbon emissions trading and electricity markets couples the operations of the two markets.The carbon emission cost(CEC)of coal-fired units becomes part of the power generation cost through market coupling.The accuracy of CEC calculation affects the clearing capacity of coal-fired units in the electric power market.Study of carbon–electricity market interaction and CEC calculations is still in its initial stages.This study analyzes the impact of carbon emissions trading and compliance on the operation of the electric power market and defines the cost transmission mode between the carbon emissions trading and electric power markets.A long-period interactive operation simulation mechanism for the carbon–electricity market is established,and operation and trading models of the carbon emissions trading market and electric power market are established.A daily rolling estimation method for the CEC of coal-fired units is proposed,along with the CEC per unit electric quantity of the coal-fired units.The feasibility and effectiveness of the proposed method are verified through an example simulation,and the factors influencing the CEC are analyzed.

Inhibition of VEGF-A expression in hypoxia-exposed fetal retinal microvascular endothelial cells by exosomes derived from human umbilical cord mesenchymal stem cells

Objective:This study aimed to investigate the potential of human umbilical cord mesenchymal stem cell(hucMSC)-derived exosomes(hucMSC-Exos)in inhibiting hypoxia-induced cell hyper proliferation and overexpression of vascular endothelial growth factor A(VEGF-A)in immature human fetal retinal microvascular endothelial cells(hfRMECs).Methods:Exosomes were isolated from hucMSCs using cryogenic ultracentrifugation and characterized through various techniques,including transmission electron microscopy,nanoparticle tracking analysis,bicinchoninic acid assays,and western blotting.The hfRMECs were identified using von Willebrand factor(vWF)co-staining and divided into four groups:a control group cultured under normoxic condition,a hypoxic model group,a hypoxic group treated with low-concentration hucMSC-Exos(75μg/mL)and a hypoxic group treated with high-concentration hucMSC-Exos(100μg/mL).Cell viability and proliferation were assessed using Cell Counting Kit-8(CCK-8)assay and EdU(5-ethynyl-2′-deoxyuridine)assay respectively.Expression levels of VEGF-A were evaluated using RT-PCR,western blotting and immunofluorescence.Results:Hypoxia significantly increased hfRMECs’viability and proliferation by upregulating VEGF-A levels.The administration of hucMSC-Exos effectively reversed this response,with the high-concentration group exhibiting greater efficacy compared to the lowconcentration group.Conclusion:In conclusion,hucMSC-Exos can dose-dependently inhibit hypoxia-induced hyperproliferation and VEGF-A overexpression in immature fetal retinal microvascular endothelial cells.

2019新型冠状病毒信息库

2019年12月在中国武汉开始爆发的新型肺炎已造成全球25个国家/地区的31516人感染、638人死亡(截止2020年2月7日16时),引起该肺炎的病毒被世界卫生组织命名为2019新型冠状病毒(2019-nCoV)。为促进2019-nCoV数据共享应用并及时向全球公众提供病毒的相关信息,国家生物信息中心(CNCB)/国家基因组科学数据中心(NGDC)建立了2019新型冠状病毒信息库(2019nCoVR,https://bigd.big.ac.cn/ncov)。该信息库整合了来自德国全球流感病毒数据库、美国国家生物技术信息中心、深圳(国家)基因库、国家微生物科学数据中心及CNCB/NGDC等机构公开发布的2019-nCoV核苷酸和蛋白质序列数据、元信息、学术文献、新闻动态、科普文章等信息,开展了不同冠状病毒株的基因组序列变异分析并提供可视化展示。同时,2019nCoVR无缝对接CNCB/NGDC的相关数据库,提供新测序病毒株系的基因组原始测序数据、组装后序列的在线汇交、管理与共享、国际数据库同步发布等数据服务。本文对2019nCoVR数据汇交、管理、发布及使用等进行全面阐述,以方便用户了解该信息库各项功能及数据状况,为加速开展病毒的分类溯源、变异演化、快速检测、药物研发以及新型肺炎的精准预防与治疗等研究提供重要基础。

跨境审计监管、经济安全与会计师事务所国际化战略

“中概股”公司在美国资本市场中频频出现的财务造假等问题，使得中美两国的跨境审计监管冲突不断激化。本文基于这一背景，对放开跨境审计监管进行合作的必要性进行了探讨，同时从经济安全和国家利益的角度研究了进行跨境审计监管合作产生的影响，并且进一步探索和总结了应采取何种跨境审计监管合作形式维护我国国家利益。本文研究结论为跨境审计监管冲突产生的监管协调问题提供了新的视角，也有助于对跨境审计监管中亟待梳理和解决的问题提供理论上的突破，为跨境审计监管合作对外政策决策提供依据。这类问题的研究和总结也对我国跨境监管合作特别是跨境证券监管合作具有重要的理论和实践意义.

GenBase: A Nucleotide Sequence Database

The rapid advancement of sequencing technologies poses challenges in managing the large volume and exponential growth of sequence data efficiently and on time.To address this issue,we present GenBase(https://ngdc.cncb.ac.cn/genbase),an open-access data repository that follows the International Nucleotide Sequence Database Collaboration(INSDC)data standards and structures,for efficient nucleotide sequence archiving,searching,and sharing.As a core resource within the National Genomics Data Center(NGDC)of the China National Center for Bioinformation(CNCB;https://ngdc.cncb.ac.cn),GenBase offers bilingual submission pipeline and services,as well as local submission assistance in China.GenBase also provides a unique Excel format for metadata description and feature annotation of nucleotide sequences,along with a real-time data validation system to streamline sequence submissions.As of April 23,2024,GenBase received 68,251 nucleotide sequences and 689,574 annotated protein sequences across 414 species from 2319 submissions.Out of these,63,614(93%)nucleotide sequences and 620,640(90%)annotated protein sequences have been released and are publicly accessible through GenBase’s web search system,File Transfer Protocol(FTP),and Application Programming Interface(API).Additionally,in collaboration with INSDC,GenBase has constructed an effective data exchange mechanism with GenBank and started sharing released nucleotide sequences.Furthermore,GenBase integrates all sequences from GenBank with daily updates,demonstrating its commitment to actively contributing to global sequence data management and sharing.

Plant genomic resources at National Genomics Data Center:assisting in data-driven breeding applications

Genomic data serve as an invaluable resource for unraveling the intricacies of the higher plant systems,including the constituent elements within and among species.Through various efforts in genomic data archiving,integrative analysis and value-added curation,the National Genomics Data Center(NGDC),which is a part of the China National Center for Bioinformation(CNCB),has successfully established and currently maintains a vast amount of database resources.This dedicated initiative of the NGDC facilitates a data-rich ecosystem that greatly strengthens and supports genomic research efforts.Here,we present a comprehensive overview of central repositories dedicated to archiving,presenting,and sharing plant omics data,introduce knowledgebases focused on variants or gene-based functional insights,highlight species-specific multiple omics database resources,and briefly review the online application tools.We intend that this review can be used as a guide map for plant researchers wishing to select effective data resources from the NGDC for their specific areas of study.

Bi-level Energy Trading Model Incorporating Large-scale Biogas Plant and Demand Response Aggregator

Increasing intermittent renewable energy sources(RESs)intensifies the imbalance between demand and generation,entailing the diversification of the deployment of electrical energy storage systems(ESSs).A large-scale biogas plant(LBP)installed with heating devices and biogas energy storage(BES)usually exhibits a storage-like characteristic of accommodating an increasing penetration level of RES in rural areas,which is addressed in this paper.By utilizing the temperature-sensitive characteristic of anaerobic digestion that enables the LBP to exhibit a storage-like characteristic,this paper proposes a bi-level energy trading model incorporating LBP and demand response aggregator(DRA)simultaneously.In this model,social welfare is maximized at the upper level while the profit of DRA is maximized at the lower level.Compared with cases only with DRA,the results show that the proposed model with the LBP improves the on-site accommodation capacity of photovoltaic(PV)generation up to 6.3%,18.1%,and 18.9%at 30%,40%,and 50%PV penetration levels,respectively,with a better economic performance.This nonlinear bi-level problem is finally recast by a single-level mathematical program with equilibrium constraints(MPEC)using Karush-Kuhn-Tucker(KKT)conditions and solved by the Cplex solver.The effectiveness of the proposed model is validated using a 33-bus test system and a sensitivity analysis is provided for analyzing what parameter influences the accommodation capacity most.

Fine-Tuning of MiR528 Accumulation Modulates Flowering Time in Rice

In plants,microRNA (miRNA) functions in the post-transcriptional repression of target mRNAs have been well explored.However,the mechanisms regulating the accumulation of miRNAs remain poorly under.stood.Here,we report that distinct mechanisms regulate accumulation of a monocot-specific miRNA,rice (Oryza sativa) miR528.At the transcriptional level,miR528 accumulated to higher levels in older plants than in young seedlings and exhibited aging-modulated gradual accumulation and diurnal rhythms in leaves;at the post-transcriptional level,aging also modulated miR528 levels by enhancing pri-miR528 alter.native splicing.We found that miR528 promotes rice flowering under long-day conditions by targeting RED AND FAR-RED INSENSITIVE2 (OsRFI2).Moreover,natural variations in the MIR528 promoter region caused differences in miR528 expression among rice varieties,which are correlated with their different binding affinities with the transcription factor OsSPL9 that activates the expression of miR528.Taken together,our findings reveal rice plants have evolved sophisticated modes fine-tuning miR528 levels and provide insight into the mechanisms that regulate MIRNA expression in plants.

Genome Warehouse: A Public Repository Housing Genome-scale Data

The Genome Warehouse(GWH)is a public repository housing genome assembly data for a wide range of species and delivering a series of web services for genome data submission,storage,release,and sharing.As one of the core resources in the National Genomics Data Center(NGDC),part of the China National Center for Bioinformation(CNCB;https://ngdc.cncb.ac.cn),GWH accepts both full and partial(chloroplast,mitochondrion,and plasmid)genome sequences with different assembly levels,as well as an update of existing genome assemblies.For each assembly,GWH collects detailed genome-related metadata of biological project,biological sample,and genome assembly,in addition to genome sequence and annotation.To archive high-quality genome sequences and annotations,GWH is equipped with a uniform and standardized procedure for quality control.Besides basic browse and search functionalities,all released genome sequences and annotations can be visualized with JBrowse.By May 21,2021,GWH has received 19,124 direct submissions covering a diversity of 1108 species and has released 8772 of them.Collectively,GWH serves as an important resource for genomescale data management and provides free and publicly accessible data to support research activities throughout the world.GWH is publicly accessible at https://ngdc.cncb.ac.cn/gwh.

Long Non-coding RNAs and Their Biological Roles in Plants

With the development of genomics and bioinformatics, especially the extensive applications of high-throughput sequencing technology, more transcriptional units with little or no protein-coding potential have been discovered. Such RNA molecules are called non- protein-coding RNAs （npcRNAs or ncRNAs）. Among them, long npcRNAs or ncRNAs 0npcRNAs or lncRNAs） represent diverse classes of transcripts longer than 200 nucleotides. In recent years, the lncRNAs have been considered as important regulators in many essential biological processes. In plants, although a large number of lncRNA transcripts have been predicted and identified in few species, our current knowledge of their biological functions is still limited. Here, we have summarized recent studies on their identification, characteristics, classification, bioinformatics, resources, and current exploration of their biological functions in olants.

The Global Landscape of SARS-CoV-2 Genomes, Variants, and Haplotypes in 2019nCoVR

On January 22,2020,China National Center for Bioinformation(CNCB)released the 2019 Novel Coronavirus Resource(2019nCoVR),an open-access information resource for the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).2019nCoVR features a comprehensive integration of sequence and clinical information for all publicly available SARS-CoV-2 isolates,which are manually curated with value-added annotations and quality evaluated by an automated in-house pipeline.Of particular note,2019nCoVR offers systematic analyses to generate a dynamic landscape of SARS-CoV-2 genomic variations at a global scale.It provides all identified variants and their detailed statistics for each virus isolate,and congregates the quality score,functional annotation,and population frequency for each variant.Spatiotemporal change for each variant can be visualized and historical viral haplotype network maps for the course of the outbreak are also generated based on all complete and high-quality genomes available.Moreover,2019nCoVR provides a full collection of SARS-CoV-2 relevant literature on the coronavirus disease 2019(COVID-19),including published papers from PubMed as well as preprints from services such as bioRxiv and medRxiv through Europe PMC.Furthermore,by linking with relevant databases in CNCB,2019nCoVR offers data submission services for raw sequence reads and assembled genomes,and data sharing with NCBI.Collectively,SARS-CoV-2 is updated daily to collect the latest information on genome sequences,variants,haplotypes,and literature for a timely reflection,making 2019nCoVR a valuable resource for the global research community.2019nCoVR is accessible at https://bigd.big.ac.cn/ncov/.

Decision Support System for Adaptive Restoration Control of Transmission System

The power system restoration control has a higher uncertainty level than the preventive control of cascading failures. In order to ensure the feasibility of the decision support system of restoration control, a decision support framework for adaptive restoration control of transmission system is proposed, which can support the coordinated restoration of multiple partitions, coordinated restoration of units and loads, and coordination of multi-partition decision-making process and actual restoration process. The proposed framework is divided into two layers, global coordination layer and partition optimization layer. The upper layer partitions the transmission system according to the power outage scenario, constantly and dynamically adjusts the partitions during the restoration process, and optimizes the time-space decision-making of inter-partition connectivity. For each partition, the lower layer pre-selects restoration targets according to the estimated restoration income, optimizes the corresponding restoration paths, and evaluates the restoration plans according to the expected net income per unit of power consumption. During the restoration process, if the restoration operation such as energizing the outage branch fails, the current restoration plan will be adaptively switched to the sub-optimal one or re-optimized if necessary. The framework includes two operation modes, i.e., the on-line operation mode and training simulation mode, and provides an information interaction interface for collaborative restoration with related distribution systems. The effectiveness and adaptability of the proposed framework is demonstrated by simulations using the modified IEEE 118-bus system.

Scenario-based Unit Commitment Optimization for Power System with Large-scale Wind Power Participating in Primary Frequency Regulation

Continuous increase of wind power penetration brings high randomness to power system,and also leads to serious shortage of primary frequency regulation(PFR)reserve for power system whose reserve capacity is typically provided by conventional units.Considering large-scale wind power participating in PFR,this paper proposes a unit commitment optimization model with respect to coordination of steady state and transient state.In addition to traditional operation costs,losses of wind farm de-loaded operation,environmental benefits and transient frequency safety costs in high-risk stochastic scenarios are also considered in the model.Besides,the model makes full use of interruptible loads on demand side as one of the PFR reserve sources.A selection method for high-risk scenarios is also proposed to improve the calculation efficiency.Finally,this paper proposes an inner-outer iterative optimization method for the model solution.The method is validated by the New England 10-machine system,and the results show that the optimization model can guarantee both the safety of transient frequency and the economy of system operation.

IC4R-2.0:Rice Genome Reannotation Using Massive RNA-seq Data

Genome reannotation aims for complete and accurate characterization of gene models and thus is of critical significance for in-depth exploration of gene function.Although the availability of massive RNA-seq data provides great opportunities for gene model refinement,few efforts have been made to adopt these precious data in rice genome reannotation.Here we reannotate the rice(Oryza sativa L.ssp.japonica)genome based on integration of large-scale RNA-seq data and release a new annotation system IC4 R-2.0.In general,IC4 R-2.0 significantly improves the completeness of gene structure,identifies a number of novel genes,and integrates a variety of functional annotations.Furthermore,long non-coding RNAs(lncRNAs)and circular RNAs(circRNAs)are systematically characterized in the rice genome.Performance evaluation shows that compared to previous annotation systems,IC4 R-2.0 achieves higher integrity and quality,primarily attributable to massive RNA-seq data applied in genome annotation.Consequently,we incorporate the improved annotations into the Information Commons for Rice(IC4 R),a database integrating multiple omics data of rice,and accordingly update IC4 R by providing more user-friendly web interfaces and implementing a series of practical online tools.Together,the updated IC4 R,which is equipped with the improved annotations,bears great promise for comparative and functional genomic studies in rice and other monocotyledonous species.The IC4 R-2.0 annotation system and related resources are freely accessible at http://ic4 r.org/.

Optimal Placement of Wind Turbines in Wind Farm Layout Using Particle Swarm Optimization

An optimal geographical location of wind turbines can ensure the optimum total energy output of a wind farm.This study introduces a new solution to the optimization of wind farm layout(WFLO)problem based on a three-step strategy and particle swarm optimization as the main method.The proposed strategy is applied to a certain WFLO to generate highly efficient optimal output power.Three case scenarios are considered to formulate the non-wake and wake effects at various levels.The required wind turbine positions within the wind farm are determined by the particle swarm optimization method.The rule of thumb,which determines the wind turbine spacing,is thoroughly considered.The MATLAB simulation results verify the proposed three-step strategy.Moreover,the results are compared with those of existing research works,and it shows that the proposed optimization strategy yields a better solution in terms of total output power generation and efficiency with a minimized objective function.The efficiencies of the three case studies considered herein increase by 0.65%,1.95%,and 1.74%,respectively.Finally,the simulation results indicate that the proposed method is robust in WFLO design because it further minimizes the objective function.

Rice Expression Database(RED)：An integrated RNA-Seq-derived gene expression database for rice

Rice is one of the most important stable food as well as a monocotyledonous model organism for the plant research community.Here,we present RED（Rice Expression Database;http：//expression.ic4r.org）,an integrated database of rice gene expression profiles derived entirely from RNA-Seq data.RED features a comprehensive collection of 284 high-quality RNA-Seq experiments,integrates a large number of gene expression profiles and covers a wide range of rice growth stages as well as various treatments.Based on massive expression profiles,RED provides a list of housekeeping and tissue-specific genes and dynamically constructs co-expression networks for gene（s） of interest.Besides,it provides user-friendly web interfaces for querying,browsing and visualizing expression profiles of concerned genes.Together,as a core resource in BIG Data Center,RED bears great utility for characterizing the function of rice genes and better understanding important biological processes and mechanisms underlying complex agronomic traits in rice.