Modelling analysis embodies drastic transition among global potential natural vegetations in face of changing climate

Potential natural vegetation(PNV)is a valuable reference for ecosystem renovation and has garnered increasing attention worldwide.However,there is limited knowledge on the spatio-temporal distributions,transitional processes,and underlying mechanisms of global natural vegetation,particularly in the case of ongoing climate warming.In this study,we visualize the spatio-temporal pattern and inter-transition procedure of global PNV,analyse the shifting distances and directions of global PNV under the influence of climatic disturbance,and explore the mechanisms of global PNV in response to temperature and precipitation fluctuations.To achieve this,we utilize meteorological data,mainly temperature and precipitation,from six phases:the Last Inter-Glacial(LIG),the Last Glacial Maximum(LGM),the Mid Holocene(MH),the Present Day(PD),2030(20212040)and 2090(2081–2100),and employ a widely-accepted comprehensive and sequential classification sy–stem(CSCS)for global PNV classification.We find that the spatial patterns of five PNV groups(forest,shrubland,savanna,grassland and tundra)generally align with their respective ecotopes,although their distributions have shifted due to fluctuating temperature and precipitation.Notably,we observe an unexpected transition between tundra and savanna despite their geographical distance.The shifts in distance and direction of five PNV groups are mainly driven by temperature and precipitation,although there is heterogeneity among these shifts for each group.Indeed,the heterogeneity observed among different global PNV groups suggests that they may possess varying capacities to adjust to and withstand the impacts of changing climate.The spatio-temporal distributions,mutual transitions and shift tendencies of global PNV and its underlying mechanism in face of changing climate,as revealed in this study,can significantly contribute to the development of strategies for mitigating warming and promoting re-vegetation in degraded regions worldwide.

Genome-edited rabbits:Unleashing the potential of a promising experimental animal model across diverse diseases

Animal models are extensively used in all aspects of biomedical research,with substantial contributions to our understanding of diseases,the development of pharmaceuticals,and the exploration of gene functions.The field of genome modification in rabbits has progressed slowly.However,recent advancements,particularly in CRISPR/Cas9-related technologies,have catalyzed the successful development of various genome-edited rabbit models to mimic diverse diseases,including cardiovascular disorders,immunodeficiencies,agingrelated ailments,neurological diseases,and ophthalmic pathologies.These models hold great promise in advancing biomedical research due to their closer physiological and biochemical resemblance to humans compared to mice.This review aims to summarize the novel gene-editing approaches currently available for rabbits and present the applications and prospects of such models in biomedicine,underscoring their impact and future potential in translational medicine.

Estimation of Potential Habitat of Caragana acanthophylla in Xinjiang Based on Maximum Entropy Model

[Objectives]To determine the potential habitat range of Caragana acanthophylla in Xinjiang.[Methods]The known distribution points of C.acanthophylla were used as samples,and a MaxEnt model was developed based on their climatic variables to identify key environmental factors affecting the potential habitats of C.acanthophylla through jackknife method and construction of a response relationship between representative variables and habitat suitability;the suitability of habitats for C.acanthophylla in Xinjiang was evaluated based on the output results of the model.[Results](i)The accuracy of the model verified by AUC curve was 0.971,indicating that the potential habitats of C.acanthophylla in Xinjiang predicted by MaxEnt model were highly credible.(ii)The optimum climatic characteristics for the distribution of C.acanthophylla in Xinjiang were:isothermality 18.8%-34%,minimum temperature of coldest month-30℃to-13℃,mean temperature of coldest quarter-18℃ to-4℃,annual precipitation 80-410 mm,precipitation of driest month 0-25 mm,precipitation of driest quarter 0-82 mm,and precipitation of coldest quarter 0-75 mm.(iii)The total potential distribution area of C.acanthophylla in Xinjiang was modeled to be 1.03×10^(5) km^(2),of which 8.54×10^(3)km^(2) was high suitability area,mainly in the front mountain belt of the north slope of Tianshan Mountain in Urumqi City,Changji Hui Autonomous Prefecture,Bortala Mongol Autonomous Prefecture,and Yili Kazak Autonomous Prefecture and the front mountain belt of Barluk Mountain in Tacheng Prefecture.[Conclusions]This study is of great significance for the future scientific management,regeneration,vegetation restoration and ecological protection of C.acanthophylla.

Wind Potential Modeling at Kanfarandé Site in the Republic of Guinea

The purpose of this work is to assess wind potential on the Kanfarandé site (Guinea). The data used for this research covers a period of 6 years (2018 to 2023) and consists of in situ data (Boké meteorological station) and satellite products via NASA Power Larc. The study is based on sorted hourly data (speed and direction). The treatments focus on the monthly, annual and seasonal average of speeds, by sector and their frequencies as well as the annual available powers. The obtained results made it possible, on the one hand, to assess wind potential and, on the other hand, to highlight the most favorable periods for wind energy exploitation. The analyzes show the months of July and August have the best average wind speeds with 5.01 m/s and 5.34 m/s respectively. Average wind speeds are higher during the day than at night with a peak observed at 6 p.m. The study also shows that the prevailing winds are oriented towards the South-West. The Weibull parameters determined for the site give an average of 4.5 m/s for the scale parameter and for the shape parameter 2.40 corresponding to an average power density of 65 w/m2 with an annual available power of 194.80 W/m2 and an annual available energy of 1706.45 kWh/m2.

Negative Stiffness Mechanism on An Asymmetric Wave Energy Converter by Using A Weakly Nonlinear Potential Model

Salter's duck,an asymmetrical wave energy converter(WEC)device,showed high efficiency in extracting energy from 2D regular waves in the past;yet,challenges remain for fluctuating wave conditions.These can potentially be addressed by adopting a negative stiffness mechanism(NSM)in WEC devices to enhance system efficiency,even in highly nonlinear and steep 3D waves.A weakly nonlinear model was developed which incorporated a nonlinear restoring moment and NSM into the linear formulations and was applied to an asymmetric WEC using a time domain potential flow model.The model was initially validated by comparing it with published experimental and numerical computational fluid dynamics results.The current results were in good agreement with the published results.It was found that the energy extraction increased in the range of 6%to 17%during the evaluation of the effectiveness of the NSM in regular waves.Under irregular wave conditions,specifically at the design wave conditions for the selected test site,the energy extraction increased by 2.4%,with annual energy production increments of approximately 0.8MWh.The findings highlight the potential of NSM in enhancing the performance of asymmetric WEC devices,indicating more efficient energy extraction under various wave conditions.

Estimation of Landfill Gas and Its Renewable Energy Potential from the Polesgo Controlled Landfill Using First-Order Decay (FOD) Models

Methane generation in landfills and its inadequate management represent the major avoidable source of anthropogenic methane today. This paper models methane production and the potential resources expected (electrical energy production and potential carbon credits from avoided CH4 emissions) from its proper management in a municipal solid waste landfill located in Ouagadougou, Burkina Faso. The modeling was carried out using two first-order decay (FOD) models (LandGEM V3.02 and SWANA) using parameters evaluated on the basis of the characteristics of the waste admitted to the landfill and weather data for the site. At the same time, production data have been collected since 2016 in order to compare them with the model results. The results obtained from these models were compared to experimental one. For the simulation of methane production, the SWANA model showed better consistency with experimental data, with a coefficient of determination (R²) of 0.59 compared with the LandGEM model, which obtained a coefficient of 0.006. Thus, despite the low correlation values linked to the poor consistency of experimental data, the SWANA model models methane production much better than the LandGEM model. Thus, despite the low correlation values linked to the poor consistency of the experimental data, the SWANA model models methane production much better than the LandGEM V3.02 model. It was noted that the poor consistency of the experimental data justifies these low coefficients, and that they can be improved in the future thanks to ongoing in situ measurements. According to the SWANA model prediction, in 27 years of operation a biogas plant with 33% electrical efficiency using biogas from the Polesgo landfill would avoid 1,340 GgCO2e. Also, the evaluation of revenues due to electricity and carbon credit gave a total revenue derived from methane production of US$27.38 million at a cost of US$10.5/tonne CO2e.

Constant charge method or constant potential method:Which is better for molecular modeling of electrical double layers?

In molecular modeling of electrical double layers(EDLs),the constant charge method(CCM)is prized for its computational efficiency but cannot maintain electrode equipotentiality like the more resourceintensive constant potential method(CPM),potentially leading to inaccuracies.In certain scenarios,CCM can yield results identical to CPM.However,there are no clear guidelines to determine when CCM is sufficient and when CPM is required.Here,we conduct a series of molecular simulations across various electrodes and electrolytes to present a comprehensive comparison between CCM and CPM under different charging modes.Results reveal that CCM approximates CPM effectively in capturing equilibrium EDL and current-driven dynamics in open electrode systems featuring ionic liquids or regular concentration aqueous electrolytes,while CPM is indispensable in scenarios involving organic and highly concentrated aqueous electrolytes,nanoconfinement effects,and voltage-driven dynamics.This work helps to select appropriate methods for modeling EDL systems,prioritizing accuracy while considering computationalefficiency.

Potential use of large language models for mitigating students’problematic social media use:ChatGPT as an example

The problematic use of social media has numerous negative impacts on individuals'daily lives,interpersonal relationships,physical and mental health,and more.Currently,there are few methods and tools to alleviate problematic social media,and their potential is yet to be fully realized.Emerging large language models(LLMs)are becoming increasingly popular for providing information and assistance to people and are being applied in many aspects of life.In mitigating problematic social media use,LLMs such as ChatGPT can play a positive role by serving as conversational partners and outlets for users,providing personalized information and resources,monitoring and intervening in problematic social media use,and more.In this process,we should recognize both the enormous potential and endless possibilities of LLMs such as ChatGPT,leveraging their advantages to better address problematic social media use,while also acknowledging the limitations and potential pitfalls of ChatGPT technology,such as errors,limitations in issue resolution,privacy and security concerns,and potential overreliance.When we leverage the advantages of LLMs to address issues in social media usage,we must adopt a cautious and ethical approach,being vigilant of the potential adverse effects that LLMs may have in addressing problematic social media use to better harness technology to serve individuals and society.

采用STAMP-24Model的多组织事故分析

安全生产事故往往由多组织交互、多因素耦合造成,事故原因涉及多个组织。为预防和遏制多组织生产安全事故的发生,基于系统理论事故建模与过程模型(Systems-Theory Accident Modeling and Process,STAMP)、24Model,构建一种用于多组织事故分析的方法,并以青岛石油爆炸事故为例进行事故原因分析。结果显示:STAMP-24Model可以分组织,分层次且有效、全面、详细地分析涉及多个组织的事故原因,探究多组织之间的交互关系;对事故进行动态演化分析,可得到各组织不安全动作耦合关系与形成的事故失效链及管控失效路径,进而为预防多组织事故提供思路和参考。

基于改进24Model-ISM-SNA建筑工人不安全行为关联路径研究

建筑施工现场环境复杂,为有效控制不安全行为发生,基于行为安全“2-4”模型对360份具有代表性的建筑安全事故调查报告进行分析,提取出22个不安全行为的主要影响因素。利用灰色关联分析方法(GRA)改进的集成ISM-SNA模型,将不安全行为风险因素划分为表层、过渡层与深层,然后对风险因素进行可视化分析、中心度分析及凝聚子群分析,揭示了各致因因素间的关联关系和传导路径。结果表明,建筑工人不安全行为影响因素可划分成7级3阶的多级递阶结构,安全意识、现场监管、外部环境是建筑工人不安全行为的关键影响因素,同时现场监管和隐患排查到位能有效降低不安全行为的发生。

Theoretical uncertainties of(d,^(3)He)and(^(3)He,d)reactions owing to the uncertainties of optical model potentials

The theoretical uncertainties of single proton transfer cross sections of the(^(3)He,d)and(d,^(3)He)reactions,owing to the uncertainties of the entrance-and exit-channel optical model potentials,are examined with the^(30)Si(^(3)He,d)^(31)P,^(13)B(d,^(3)He)^(12)Be,and^(34)S(^(3)He,d)^(35)Cl reactions at incident energies of 25,46,and 25 MeV,respectively,within the framework of the distorted wave Born approximation.The differential cross sections at the first peaks in the angular distributions of these reactions are found to have uncertainties of approximately 5%,owing to the uncertainties in the optical model potentials from 20,000 calculations of randomly sampled parameters.This amount of uncertainty is found to be nearly independent of the angular momentum transfer and the target masses within the studied range of incident energies.Uncertainties in the single proton spectroscopic factors obtained by matching the theoretical and experimental cross sections at different scattering angles are also discussed.

基于24Model-D-ISM的地铁站火灾疏散影响因素研究

为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾人员疏散影响因素指标体系;采用算子客观赋权法(C-OWA)改进决策试验与评价实验法(DEMATEL),确定地铁站火灾人员疏散的重要影响因素;在此基础上,采用解释结构模型(ISM)分析各个因素间的层次结构及相互作用路径,构建地铁站火灾人员疏散影响因素的多级递阶结构模型。研究结果表明:疏散引导、恐慌从众行为、人员拥挤为地铁站火灾人员疏散的关键影响因素;地铁站火灾人员疏散受表层因素、中间层因素、深层因素共同作用的影响,其中,疏散教育与培训、设施维护与检查、疏散预案等因素是根源影响因素,重视根源影响因素的改善有利于从本质上预防和控制事故的发生。

An accurate analytical surface potential model of heterojunction tunnel FET

Based on the accurate and efficient thermal injection method, we develop a fully analytical surface potential model for the heterojunction tunnel field-effect transistor(H-TFET). This model accounts for both the effects of source depletion and inversion charge, which are the key factors influencing the charge, capacitance and current in H-TFET. The accuracy of the model is validated against TCAD simulation and is greatly improved in comparison with the conventional model based on Maxwell–Boltzmann approximation. Furthermore, the dependences of the surface potential and electric field on biases are well predicted and thoroughly analyzed.

MicroRNAs in mouse and rat models of experimental epilepsy and potential therapeutic targets

Epilepsy is a common and serious neurological disease that causes recurrent seizures. The brain damage caused by seizures can lead to depression, anxiety, cognitive impairment, or disability. In almost all cases chronic seizures are difficult to cure. MicroRNAs are widely expressed in the central nervous system and play important roles in the pathogenesis of several neurological disorders, including epilepsy. A variety of animals(mostly mice and rats) have been used to induce experimental epilepsy using different protocols and miRNA profiling performed. Most of the recent studies reviewed had performed miRNA profiling in hippocampal tissues and a large number of microRNAs were dysregulated when compared to controls. Most notably, miR-132-3p,-146a-5p,-10a-5p,-21a-3p,-27a-3p,-142a-5p,-212-3p,-431-5p, and-155 were upregulated in both the mouse and rat studies. Overexpression of miR-137 and miR-219 decreased seizure severity in a mouse epileptic model, and suppression of miR-451,-10a-5p,-21a-5p,-27a-5p,-142a-5p,-431-5p,-155, and-134 had a positive influence on seizure behavior. In the rat studies, overexpression of miR-139-5p decreased neuronal damage in drug-resistant rats and inhibition of miR-129-2-3p,-27a-3p,-155,-134,-181a, and-146a had a positive effect on seizure behavior and/or reduced the loss of neuronal cells. Further studies are warranted using adult female and immature male and female animals. It would also be helpful to test the ability of specific agomirs and antagomirs to control seizure activity in a subhuman primate model of epilepsy such as adult marmosets injected intraperitoneally with pilocarpine or cynomolgus monkeys given intrahippocampal injections of kainic acid.

24Model与LCM原因因素定义对比研究

为探究损失致因模型(LCM)原因因素定义与事故致因“2-4”模型(24Model)存在的异同和优缺点,梳理2个模型各层面原因和结果的定义,对比定义内容及其对事故原因分析等安全实务的指导作用,并以一起瓦斯爆炸事故为例加以实证分析,获得二者分析结果之间的差异。研究结果表明:LCM是首个将管理因素纳入事故致因分析的一维事件序列模型,可明确各层面原因因素的定义和因素间的逻辑关系,但部分定义存在交叉重复的问题,并没有揭示安全工作指导思想等深层次事故致因因素;24Model作为系统性事故致因模型,对各类因素的定义均以组织为主体,描述事件、事故、安全的概念内涵,划分个体安全动作、安全能力和组织安全管理体系的类别并给出含义解析,探究组织安全文化层面的问题并以32个元素体现;2个模型的事故原因分析方法均建立在对各层级原因因素定义的基础上,并适用于模型理论体系本身。

Identification of injury type using somatosensory and motor evoked potentials in a rat spinal cord injury model

The spinal cord is at risk of injury during spinal surgery.If intraoperative spinal co rd injury is identified early,irreve rsible impairment or loss of neurological function can be prevented.Different types of spinal cord injury result in damage to diffe rent spinal cord regions,which may cause diffe rent somatosensory and motor evoked potential signal res ponses.In this study,we examined electrophysiological and histopathological changes between contusion,distra ction,and dislocation spinal cord injuries in a rat model.We found that contusion led to the most severe dorsal white matter injury and caused considerable attenuation of both somatosensory and motor evoked potentials.Dislocation resulted in loss of myelinated axons in the lateral region of the injured spinal cord along the rostrocaudal axis.The amplitude of attenuation in motor evoked potential responses caused by dislocation was greater than that caused by contusion.After distraction injury,extracellular spaces were slightly but not significantly enlarged;somatosensory evoked potential res ponses slightly decreased and motor evoked potential responses were lost.Correlation analysis showed that histological and electrophysiological findings we re significantly correlated and related to injury type.Intraope rative monitoring of both somatosensory and motor evoked potentials has the potential to identify iatrogenic spinal cord injury type during surgery.

Transient receptor potential-related risk model predicts prognosis of hepatocellular carcinoma patients

BACKGROUND Members of the transient receptor potential(TRP)protein family shape oncogenic development,but the specific relevance of TRP-related genes in hepatocellular carcinoma(HCC)has yet to be defined.AIM To investigate the role of TRP genes in HCC,their association with HCC development and treatment was examined.METHODS HCC patient gene expression and clinical data were downloaded from The Cancer Genome Atlas database,and univariate and least absolute shrinkage and selection operator Cox regression models were employed to explore the TRP-related risk spectrum.Based on these analyses,clinically relevant TRP family genes were selected,and the association between the key TRP canonical type 1(TRPC1)gene and HCC patient prognosis was evaluated.RESULTS In total,28 TRP family genes were screened for clinical relevance,with multivariate analyses ultimately revealing three of these genes(TRPC1,TRP cation channel subfamily M member 2,and TRP cation channel subfamily M member 6)to be significantly associated with HCC patient prognosis(P<0.05).These genes were utilized to establish a TRP-related risk model.Patients were separated into low-and high-risk groups based on the expression of these genes,and high-risk patients exhibited a significantly poorer prognosis(P=0.001).Functional analyses highlighted pronounced differences in the immune status of patients in these two groups and associated enriched immune pathways.TRPC1 was identified as a candidate gene in this family worthy of further study,with HCC patients expressing higher TRPC1 levels exhibiting poorer survival outcomes.Consistently,quantitative,immunohistochemistry,and western blot analyses revealed increased TRPC1 expression in HCC.CONCLUSION These three TRP genes help determine HCC patient prognosis,providing insight into tumor immune status and immunological composition.These findings will help design combination therapies including immunotherapeutic and anti-TRP agents.

Humanization for neurological disease modeling:A roadmap to increase the potential of Drosophila model systems

Neuroscience and neurology research is dominated by experimentation with rodents.Around 75%of neurology disease-associated genes have orthologs in Drosophila mel-anogaster,the fruit fly amenable to complex neurological and behavioral investiga-tions.However,non-vertebrate models including Drosophila have so far been unable to significantly replace mice and rats in this field of studies.One reason for this situ-ation is the predominance of gene overexpression(and gene loss-of-function)meth-odologies used when establishing a Drosophila model of a given neurological disease,a strategy that does not recapitulate accurately enough the genetic disease condi-tions.I argue here the need for a systematic humanization approach,whereby the Drosophila orthologs of human disease genes are replaced with the human sequences.This approach will identify the list of diseases and the underlying genes that can be adequately modeled in the fruit fly.I discuss the neurological disease genes to which this systematic humanization approach should be applied and provide an example of such an application,and consider its importance for subsequent disease modeling and drug discovery in Drosophila.I argue that this paradigm will not only advance our un-derstanding of the molecular etiology of a number of neurological disorders,but will also gradually enable researchers to reduce experimentation using rodent models of multiple neurological diseases and eventually replace these models.

Designing Artemisinins with Antimalarial Potential, Combining Molecular Electrostatic Potential, Ligand-Heme Interaction and Multivariate Models

Artemisinins tested against W-2 strains of malaria falciparum are investigated with molecular electrostatic potential (MEP), in an attempt to identify key features of the compounds that are necessary for their activities, as well as to investigate likely interactions with the receptor in a biological process and to use that information to propose new molecules. In order to discover the best geometry involving the ligand-receptor complexes (heme) studied and help in the proposition of the new derivatives, molecular simulations of interactions between the most negative charged region around the peroxide and heme locates (the ones around the Fe2+ ion) were carried out. In addition, PCA (principal components analysis), HCA (hierarchical cluster analysis), SDA (stepwise discriminant analysis), and KNN (K-nearest neighbor) multivariate models were employed to investigate which descriptors are responsible for the classification between the higher and lower antimalarial activity of the compounds, and also this information was used to propose new potentially active molecules. The information accumulated in studies of MEP, molecular docking, and multivariate analysis supported the proposal of new structures with potential antimalarial activities. The multivariate models constructed were applied to the new structures and indicated numbers 19 and 20 as the most prominent for syntheses and biological assays.

Verify the Function of a Potential Growth-Regulating Gene in Marine Bivalve Using a Candidate Model Organism Mulinia lateralis

A better understanding of genetic bases of growth regulation is essential for bivalve breeding,which is helpful to improve the yield of the commercially important bivalves.While previous studies have identified some candidate genes accounting for variation in growth-related traits through genotype-phenotype association analyses,seldom of them have verified the functions of these putative,growth-related genes beyond the genomic level due to the difficulty of culturing commercial bivalves under laboratory conditions.Fortunately,dwarf surf clam Mulinia lateralis can serve as a model organism for studying marine bivalves given its short generation time,the feasibility of being grown under experimental conditions and the availability of genetic and biological information.Using dwarf surf clam as a model bivalve,we characterize E2F3,a gene that has been found to account for variation in growth in scallops by a previous genome-wide association study,and verify its function in growth regulation through RNA interference(RNAi)experiments.For the first time,E2F3 in dwarf surf clam,which is termed as MulE2F3,is characterized.The results reveal that dwarf surf clams with MulE2F3 knocked down exhibit a reduction in both shell size and soft-tissue weight,indicating the functions of MulE2F3 in positively regulating bivalve growth.More importantly,we demonstrate how dwarf surf clam can be used as a model organism to investigate gene functions in commercial bivalves,shedding light on genetic causes for variation in growth to enhance the efficiency of bivalve farming.