管理能力如何影响企业出口行为——兼论出口竞争新优势培育

面对国内外复杂严峻的经济环境和日趋激烈的国际竞争,稳外贸除了继续坚持科技自主创新,加快培育以管理能力为基础的企业出口竞争新优势也具有重要意义。本文基于世界银行对中国企业展开的微观调查问卷数据度量了企业的管理能力,在此基础上采用Heckman两阶段回归实证检验了制造业企业的管理能力对出口行为的影响。研究发现:(1)管理能力提升能够显著提高企业的出口倾向和出口强度,这一结论在考虑样本选择偏差及其他一系列稳健性检验后依然成立;(2)管理能力主要通过提高企业的生产效率和创新水平进而促进企业出口;(3)管理能力的出口促进作用对东部地区、融资约束较小、运营规模较大的企业更加突出。本研究有助于从改善企业自身管理能力的视角为提升企业出口竞争力及进一步培育我国出口竞争优势提供新的思路和理论经验借鉴。

Recent developments of neuroprotective agents for degenerative retinal disorders

Retinal degeneration is a debilitating ocular complication characterized by the progressive loss of photoreceptors and other retinal neurons,which are caused by a group of retinal diseases affecting various age groups,and increasingly prevalent in the elderly.Age-related macular degeneration,diabetic retinopathy and glaucoma are among the most common complex degenerative retinal disorders,posing significant public health problems worldwide largely due to the aging society and the lack of effective therapeutics.Whilst pathoetiologies vary,if left untreated,loss of retinal neurons can result in an acquired degeneration and ultimately severe visual impairment.Irrespective of underlined etiology,loss of neurons and supporting cells including retinal pigment epithelium,microvascular endothelium,and glia,converges as the common endpoint of retinal degeneration and therefore discovery or repurposing of therapies to protect retinal neurons directly or indirectly are under intensive investigation.This review overviews recent developments of potential neuroprotectants including neuropeptides,exosomes,mitochondrial-derived peptides,complement inhibitors,senolytics,autophagy enhancers and antioxidants either still experimentally or in clinical trials.Effective treatments that possess direct or indirect neuroprotective properties would significantly lift the burden of visual handicap.

Basic theories and development of Miao medicine

Miao is an important ethnic minority in China.Miao medicine(MM)is a pivotal of traditional Chinese medicine.It is an accumulation of the Miao people's experience fighting against diseases for thousands of years and has been an important part of the Miao culture.The origin of MM is closely related to Miao culture,customs,and habits.MM gradually formed a traditional medical theoretical system with obvious regional characteristics,distinctive cultural characteristics,and unique efficacy.In this paper,we intro-duce and review the unique theoretical system of MM,including the basic theory of MM,the theory of medicine,nature,taste,and channel tropism,and the theory of entering the shelf.In addition,we summarize the development of MM to provide an overview of the theoretical characteristics and industrialisation of MM that is accessible to everyone.

Pseudomonas aeruginosa infections and improper storage conditions influence the performance of 1,3‐β‐D‐glucan in diagnosis of invasive fungal infections

Background:The association between 1,3-β-D-glucan(BDG)levels and in-fections caused by Pseudomonas aeruginosa or Streptococcus pneumoniae,and the stability of BDG under different storage conditions are unclear.Methods:Strains of Pseudomonas aeruginosa and S.pneumoniae were grown in medium and human serum.The BDG concentrations in culture superna-tants were measured.The specificity and stability of BDG were also evaluated.Results:P.aeruginosa produced high levels of BDG in Luria-Bertani medium(>4×10^(4)pg/mL)and human serum(527.0 pg/mL),whereas S.pneumoniae produced low levels of BDG in THY medium(175.6 pg/mL)and human serum(78.3 pg/mL).The BDG produced by these two bacteria was specifically degraded by 1,3-β-D-glucanase.BDG was degraded when stored at different temperatures,decreasing by 22.5%and 9.3%at−20℃and−70℃,respectively,for 63 days;by 30.7%at 4℃for 12 days;and by 12.6%and 22.0%at 37℃for 6 and 12 h.Conclusion:BDG false-positivity must be considered in patients with bacteremia caused by P.aeruginosa when diagnosing invasive fungal infection.Human serum samples for the BDG test in medical facilities should be tested as soon as possible or stored at low temperatures before testing.

METTL3-mediated m^(6)A modification of HMGA2 mRNA promotes subretinal fibrosis and epithelial-mesenchymal transition

Subretinal fibrosis is a major cause of the poor visual prognosis for patients with neovascular age-related macular degeneration(nAMD).Myofibroblasts originated from retinal pigment epithelial(RPE)cells through epithelial-mesenchymal transition(EMT)contribute to the fibrosis formation.N^(6)-Methyladenosine(m^(6)A)modification has been implicated in the EMT process and multiple fibrotic diseases.The role of m^(6)A modification in EMT-related subretinal fibrosis has not yet been elucidated.In this study,we found that during subretinal fibrosis in the mouse model of laser-induced choroidal neovascularization,METTL3 was upregulated in RPE cells.Through m^(6)A epitranscriptomic microarray and further verification,high-mobility group AT-hook 2(HMGA2)was identified as thekey downstream target of METTL3,subsequently activating potent EMT-inducing transcription factor SNAIL.Finally,by subretinal injections of adeno-associated virus vectors,we confirmed that METTL3 deficiency in RPE cells could efficiently attenuate subretinal fibrosis in vivo.In conclusion,our present research identified an epigenetic mechanism of METTL3-m^(6)A-HMGA2 in subretinal fibrosis and EMT of RPE cells,providing a novel therapeutic target for subretinal fibrosis secondary to nAMD.

Multi-agent Simulation for Strategic Bidding in Electricity Markets Using Reinforcement Learning

In this paper,a theoretical framework of Multiagent Simulation(MAS)is proposed for strategic bidding in electricity markets using reinforcement learning,which consists of two parts:one is a MAS system used to simulate the competitive bidding of the actual electricity market;the other is an adaptive learning strategy bidding system used to provide agents with more intelligent bidding strategies.An ExperienceWeighted Attraction(EWA)reinforcement learning algorithm(RLA)is applied to the MAS model and a new MAS method is presented for strategic bidding in electricity markets using a new Improved EWA(IEWA).From both qualitative and quantitative perspectives,it is compared with three other MAS methods using the Roth-Erev(RE),Q-learning and EWA.The results show that the performance of the MAS method using IEWA is proved to be better than the others.The four MAS models using four RLAs are built for strategic bidding in electricity markets.Through running the four MAS models,the rationality and correctness of the four MAS methods are verified for strategic bidding in electricity markets using reinforcement learning.

Extracellular RNAs-TLR3 signaling contributes to cognitive impairment after chronic neuropathic pain in mice

Chronic pain is often associated with cognitive decline,which could influence the quality of the patient’s life.Recent studies have suggested that Toll-like receptor 3(TLR3)is crucial for memory and learning.Nonetheless,the contribution of TLR3 to the pathogenesis of cognitive decline after chronic pain remains unclear.The level of TLR3 in hippocampal neurons increased in the chronic constriction injury(CCI)group than in the sham group in this study.Importantly,compared to the wild-type(WT)mice,TLR3 knockout(KO)mice and TLR3-specific neuronal knockdown mice both displayed improved cognitive function,reduced levels of inflammatory cytokines and neuronal apoptosis and attenuated injury to hippocampal neuroplasticity.Notably,extracellular RNAs(exRNAs),specifically double-stranded RNAs(dsRNAs),were increased in the sciatic nerve,serum,and hippocampus after CCI.The co-localization of dsRNA with TLR3 was also increased in hippocampal neurons.And the administration of poly(I:C),a dsRNA analog,elevated the levels of dsRNAs and TLR3 in the hippocampus,exacerbating hippocampus-dependent memory.In additon,the dsRNA/TLR3 inhibitor improved cognitive function after CCI.Together,our findings suggested that exRNAs,particularly dsRNAs,that were present in the condition of chronic neuropathic pain,activated TLR3,initiated downstream inflammatory and apoptotic signaling,caused damage to synaptic plasticity,and contributed to the etiology of cognitive impairment after chronic neuropathic pain.

Unveiling the crucial role of iron mineral phase transformation in antimony(V)elimination from natural water

Antimony(Sb)in natural water has long-term effects on both the ecological environment and human health.Iron mineral phase transformation(IMPT)is a prominent process for removing Sb(V)from natural water.However,the importance of IMPT in eliminating Sb remains uncertain.This study examined the various Sb–Fe binding mechanisms found in different IMPT pathways in natural water,shedding light on the underlying mechanisms.The study revealed that the presence of goethite(Goe),hematite(Hem),and magnetite(Mag)significantly affected the concentration of Sb(V)in natural water.Elevated pH levels facilitated higher Fe content in iron solids but impeded the process of removing Sb(V).To further our understanding,polluted natural water samples were collected from various locations surrounding Sb smelter sites.Results confirmed that converting ferrihydrite(Fhy)to Goe significantly reduced Sb levels(<5μg/L)in natural water.The emergence of secondary iron phases resulted in greater electrostatic attraction and stabilized surface complexes,which was the most likely cause of the decline of Sb concentration in natural water.The comprehensive findings offer new insights into the factors governing IMPT as well as the Sb(V)behavior control.

Performance evaluation for sustainability of wind energy project using improved multi-criteria decision-making method

Wind power can be an efficient way to alleviate energy shortage and environmental pollution,and to realize sustainable development in terms of energy generation.The sustainability assessment of a wind project among its alternatives is a complex task that cannot be solely simplified to environmental or economic feasibility.It requires the consideration of its technological and social aspects as well as other circumstances.This paper proposes a new method for selecting the most sustainable wind projects.The method is based on multi-criteria decision-making techniques.The analytic hierarchy process and entropy weight method are combined to determine the weights of evaluation indexes,and an innovative index-weight optimization method based on the Lagrange conditional extremum algorithm.The fuzzy technique for order preference by similarity to the ideal solution is applied to rank wind project alternatives considering functionality and proportionality of the system.Moreover,the sensitive analysis is applied to verify the robustness of the proposed method.The applicability of the method is demonstrated on a case study from China,where three main wind projects are analytically compared and ranked.The results indicated that the sustainable level of calculated wind power can provide a reference point for the planning and operation of the wind project.The results show that the proposed method is of both theoretical significance and practical application in engineering.

Voltage Security Operation Region Calculation Based on Improved Particle Swarm Optimization and Recursive Least Square Hybrid Algorithm

Large-scale voltage collapse incidences, which result in power outages over large regions and extensive economic losses, are presently common occurrences worldwide. To avoid voltage collapse and operate more safely and reliably, it is necessary to analyze the voltage security operation region(VSOR) of power systems, which has become a topic of increasing interest lately. In this paper, a novel improved particle swarm optimization and recursive least square(IPSO-RLS) hybrid algorithm is proposed to determine the VSOR of a power system. Also, stability analysis on the proposed algorithm is carried out by analyzing the errors and convergence accuracy of the obtained results. Firstly, the voltage stability and VSOR-surface of a power system are analyzed in this paper. Secondly, the two algorithms,namely IPSO and RLS algorithms, are studied individually.Based on this understanding, a novel IPSO-RLS hybrid algorithm is proposed to optimize the active and reactive power,and the voltage allowed to identify the VSOR-surface accurately. Finally, the proposed algorithm is validated by using a simulation case study on three wind farm regions of actual Hami Power Grid of China in DIg SILENT/Power Factory software.The error and accuracy of the obtained simulation results are analyzed and compared with those of the particle swarm optimization(PSO), IPSO and IPSO-RLS hybrid algorithms.

pH and H2O2 dual-responsive carbon dots for biocatalytic transformation monitoring

Development of sensitive biosensors for biocatalytic transformations monitoring is in high demand but remains a great challenge. It is ascribed to the current strategies that focused on the single metabolite detection, which may bring about the relatively low sensitivity and false diagnosis result. Herein, we report the design and fabrication of novel carbon dots(CDs) with strong orange light emission, pH and H2O2 dual-responsive characteristics. The fluorescence quenching of CDs by H+and H2O2 enables the highly sensitive detection of H+/H2O2-generating biocatalytic transformations. This is exemplified by the glucose oxidase-mediated catalytic oxidation reaction on glucose, in which H+and H2O2 would be formed. As compared to the case in which glucose is present, significant fluorescence reduction is detected, and the fluorescence intensity is negatively proportional to glucose concentration. Thus, highly sensitive detection of glucose was readily achieved with a detection limit down to 10.18 nmol/L. The prepared CDs not only realize the highly sensitive detection of glucose, but also allows the probing other substances by changing the enzymes, thus providing a versatile platform, and demonstrating good potential to be used for biocatalytic transformations effective monitoring.

Agent-based dynamic simulation of an electricity market with multilateral bidding

The electricity market is a complex system in which participants interact and compete with each other,which makes description of them with mathematical models difficult.To solve these difficulties,computer simulation has become one of the main methods for studying electricity market problems.How to establish a reasonable electricity market has always been a major research issue in the electric power industry,for which a key point is the bidding mechanism.Agent-based modeling and a simulation(ABMS)method are used in this paper to study the imperfect competitive electricity market.An agent-based simulation method of multilateral bargaining game theory in the dynamics of the power bidding market is presented,and a multi-agent power market bidding dynamics simulation model based on game theory is established.The dynamic bidding game behavior among the government,power grid companies,power plant companies,and consumer parties is simulated in the market,and the simulation method is realized by Anylogic software.Finally,an agent-based four-party competitive dynamic game simulation in the electricity market is implemented,which provides a theoretical reference for further understanding resource optimization problems in the electricity market.

Defensins as a promising class of tick antimicrobial peptides: a scoping review

Background: Ticks are hematophagous parasites that transmit an extensive range of pathogens to their vertebrate hosts.Ticks can destroy invading microorganisms or alleviate infection via their rudimentary but orchestrated innate immune system.Antimicrobial peptides(AMPs)are important components of tick innate immunity.Among these humoral effector molecules,defensins are well-studied and widely identified in various species of Ixodidae(hard ticks)and Argasidae(soft ticks).This review was aimed at presenting the characterization of tick defensins from structure-based taxonomic status to antimicrobial function.Main text: All published papers written in English from 2001 to May 2022 were searched through PubMed and Web of Science databases with the combination of relevant terms on tick defensins.Reports on identification and characterization of tick defensins were included.Of the 329 entries retrieved,57 articles were finally eligible for our scoping review.Tick defensins mainly belong to the antibacterial ancient invertebrate-type defensins of the cis-defensins superfamily.They are generally small,cationic,and amphipathic,with six cysteine residues forming three intra-molecular disulfide bonds.Tick defensins primarily target membranes of a variety of pathogens,including Gram-positive and Gram-negative bacteria,fungi,viruses,and protozoa.Since tick defensins have a high degree of variability,we summarize their common biological properties and enumerate representative peptides.Along with the various and potent antimicrobial activities,the role of tick defensins in determining vector competence is discussed.Conclusions: Due to their broad-spectrum antimicrobial activities,tick defensins are considered novel candidates or targets for controlling infectious diseases.

Simultaneous photoelectrochemical detection of dual microRNAs by capturing CdS quantum dots and methylene blue based on target-initiated strand displaced amplification

Herein,we propose a novel photoelectrochemical(PEC) biosensor for dual microRNAs(miRNAs) highly sensitive and simultaneous biosensing based on strand displaced amplification(SDA) reaction.The recognition of HmiR-21 and Hlet-7 a by microRNA-21 and let-7 a leads to their change in hairpin structures,subsequently initiating the immobilization of abundant CdS quantum dots(CdS QD s) and methylene blue(MB) based on SDA reaction.The immobilized CdS QDs and MB produce both high PEC currents under430 nm light and 627 nm light illumination,respectively,and the generated PEC currents are closely relied on target miRNAs amounts.Thus,highly sensitive and simultaneous detection of microRNA-21 and let-7 a was readily achieved with detection limit at 6.6 fmol/L and 15.4 fmol/L based on 3σ,respectively.Further,this PEC biosensor was applied in simultaneous analysis of miRNA-21 and let-7 a in breast cancer patient’s serum with acceptable results.We expect this biosensor will find more useful application in diagnosis of miRNA-related diseases.