Global minima of Al_N, Au_N and Pt_N, N=2-80, clusters described by Voter-Chen version of e
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英语在人工智能时代是否有必要存在英语作文The Importance of English in the Age of Artificial IntelligenceAs the world becomes increasingly interconnected and technology-driven, the role of language in facilitating communication and collaboration has become more crucial than ever before. In the age of artificial intelligence (AI), where machines are capable of processing and analyzing vast amounts of data, the question arises: is there a continued need for the English language?The answer is a resounding yes. English has long been recognized as the global lingua franca, a language that transcends geographical boundaries and enables individuals from diverse backgrounds to communicate effectively. This importance has only been amplified in the era of AI, where the ability to process and understand natural language is a fundamental aspect of many AI systems.One of the primary reasons why English remains essential in the age of AI is the sheer volume of data that is generated and processed in this domain. A significant portion of this data, including researchpapers, technical documentation, and online content, is produced in English. By mastering the English language, individuals and organizations can access and leverage this wealth of information, staying at the forefront of technological advancements.Moreover, the development of AI systems often involves teams of researchers and engineers from around the world. The ability to communicate effectively in English becomes crucial in facilitating collaboration, sharing ideas, and ensuring the successful implementation of AI projects. As AI technologies become increasingly sophisticated, the need for a common language to bridge cultural and linguistic divides becomes even more pressing.In addition to its practical applications, the English language also plays a crucial role in the dissemination of knowledge and the advancement of AI research. Many of the leading academic institutions and research centers in the field of AI are located in English-speaking countries, and the majority of the published literature in this domain is written in English. By mastering the English language, individuals can engage with the global AI community, contribute to cutting-edge research, and stay informed about the latest developments in the field.Furthermore, the prominence of English in the AI industry extends beyond the realm of research and development. As AI-poweredtechnologies become more prevalent in various sectors, such as healthcare, finance, and transportation, the demand for individuals who can effectively communicate in English and interact with AI systems grows. Professionals who possess strong English language skills are often better equipped to navigate the complexities of AI-driven environments and collaborate with international teams.It is important to note that the importance of English in the age of AI does not diminish the value of other languages. In fact, the ability to speak multiple languages, including non-English languages, can be a significant advantage in the field of AI. By leveraging linguistic diversity, individuals and organizations can gain a deeper understanding of cultural nuances, access a wider range of perspectives, and develop AI systems that are more inclusive and responsive to the needs of diverse communities.In conclusion, the English language remains an essential tool in the age of artificial intelligence. Its role in facilitating communication, enabling access to a vast pool of information, and fostering global collaboration makes it a vital component of the AI ecosystem. As the world continues to evolve and technology becomes increasingly integrated into our daily lives, the importance of English in the field of AI is only expected to grow, underscoring the need for individuals to prioritize the acquisition and mastery of this language.。
Package‘metadynminer3d’October13,2022Type PackageTitle Tools to Read,Analyze and Visualize Metadynamics3D HILLS Files from'Plumed'Version0.0.2Date2022-04-14Depends R(>=3.3.0),metadynminer,rglLinkingTo RcppDescription Metadynamics is a state of the art biomolecular simulation technique.'Plumed'Tribello,G.A.et al.(2014)<doi:10.1016/j.cpc.2013.09.018>program makes it possible to perform metadynamics using various simulation codes.The results ofmetadynamics done in'Plumed'can be analyzed by'metadynminer'.The package'metadynminer'reads1D and2D metadynamics hillsfiles from'Plumed'package.As an addendum,'metadynaminer3d'is used to visualize3D hills.It usesa fast algorithm by Hosek,P.and Spiwok,V.(2016)<doi:10.1016/j.cpc.2015.08.037>to calculate a free energy surface from hills.Minima can be located and plotted onthe free energy surface.Free energy surfaces and minima can be plotted to producepublication quality images.LazyData trueLicense GPL-3RoxygenNote6.1.0Imports Rcpp,misc3dSuggests testthatURL https://metadynamics.cz/metadynminer3d/NeedsCompilation yesAuthor V ojtech Spiwok[aut,cre](<https:///0000-0001-8108-2033>) Maintainer V ojtech Spiwok<****************>Repository CRANDate/Publication2022-04-1414:32:34UTC12acealanme3d R topics documented:acealanme3d (2)feprof.minima3d (3)fes.hillsfile3d (3)fes2.hillsfile3d (4)fesminima.fes3d (5)fespoint.hillsfile3d (5)head.hillsfile3d (6)max.fes3d (7)min.fes3d (7)oneminimum.fes3d (8)plot.fes3d (8)plot.hillsfile3d (9)plot.minima3d (10)plotheights.hillsfile3d (11)print.fes3d (12)print.hillsfile3d (12)print.minima3d (13)read.hills3d (13)read.plumed3d (14)summary.fes3d (15)summary.hillsfile3d (16)summary.minima3d (16)tail.hillsfile3d (17)Index18 acealanme3d Hills from30ns metadynamics of AceAlaNme in water with three col-lective variableDescriptionHills from30ns metadynamics of AceAlaNme(Amber99SB-ILDN)in water(TIP3P)with a Ra-machandran dihedral phi and psi and peptide bond torsion omega as the collective variable.Usageacealanme3dFormathillsfile3d objectSourcehttp://www.metadynamics.cz/metadynminer/data/HILLS3dfeprof.minima3d3 feprof.minima3d Calculate free energy profile for minima3d objectDescription‘feprof.minima3d‘calculates free energy profiles for free energy minima.Itfinds the global mini-mum at the‘imax‘and calculates the evolution of free energies of a local vs.the global free energy minimum.The free energy of the global minimum is constant(zero).Usage##S3method for class minima3dfeprof(minims,imax=NULL)Argumentsminims minima3d object.imax index of a hill from which summation stops(default the rest of hills). Exampleslibrary(metadynminer3d)tfes<-fes(acealanme3d,imax=5000)minima<-fesminima(tfes)prof<-feprof(minima)proffes.hillsfile3d Calculate3D free energy surface by Bias Sum algorithmDescription‘fes.hillsfile3d‘sums up hills using fast Bias Sum algorithm.Usage##S3method for class hillsfile3dfes(hills,imin=1,imax=NULL,xlim=NULL,ylim=NULL,zlim=NULL,npoints=NULL)4fes2.hillsfile3dArgumentshills hillsfile3d object.imin index of a hill from which summation starts(default1).imax index of a hill from which summation stops(default the rest of hills).xlim numeric vector of length1,giving the CV2coordinates range.ylim numeric vector of length2,giving the CV2coordinates range.zlim numeric vector of length2,giving the CV3coordinates range.npoints resolution of the free energy surface in number of points.Valuefes object.Examplestfes<-fes(acealanme3d,imax=5000)fes2.hillsfile3d Calculate3D free energy surface by conventional algorithmDescription‘fes2.hills3d‘sums up hills using slow conventional algorithm.It can be used as a reference or when hill widths are variable.Usage##S3method for class hillsfile3dfes2(hills,imin=1,imax=NULL,xlim=NULL,ylim=NULL,zlim=NULL,npoints=NULL)Argumentshills hillsfile3d object.imin index of a hill from which summation starts(default1).imax index of a hill from which summation stops(default the rest of hills).xlim numeric vector of length2,giving the CV1coordinates range.ylim numeric vector of length2,giving the CV2coordinates range.zlim numeric vector of length2,giving the CV3coordinates range.npoints resolution of the free energy surface in number of points.Valuefes object.fesminima.fes3d5Examplestfes<-fes2(acealanme3d,imax=100)fesminima.fes3d Find free energy minima in the fes3d objectDescription‘fesminima.fes3d‘finds free energy minima on3D free energy surface.The surface is divided by a3D grid and minima are found for each bin.Next the program determines whether the minimum of a bin is a local minimum of the whole free energy surface.Free energy minima are labeled constitutively by capital letters.Usage##S3method for class fes3dfesminima(inputfes,nbins=8)Argumentsinputfes fes3d object.nbins number of bins for each CV(default8).Valueminima object.Examplestfes<-fes(acealanme3d,imax=5000)minima<-fesminima(tfes)minimafespoint.hillsfile3d Calculate free energy at given point in the CV spaceDescription‘fespoint‘calculates free energy at given point in the CV space’coord’.Hills are summed from ’imin’to‘imax‘.Printed output can be suppressed by setting’verb’to TRUE.Usage##S3method for class hillsfile3dfespoint(hills,coord=NULL,imin=1,imax=NULL,verb=T)6head.hillsfile3d Argumentshills hillsfile3d object.coord coordinates of the point in the CV space.imin index of a hill from which calculation of difference starts(default1).imax index of a hill from which summation stops(default the rest of hills).verb if TRUE,the output is verbose(default TRUE).Examplesfespoint(acealanme3d,c(0,0,0),imax=5000)head.hillsfile3d Printfirst n lines of hillsfile3dDescription‘head.hillsfile3d‘printsfirst n lines of a hillsfile3d object.Usage##S3method for class hillsfile3dhead(x,n=10,...)Argumentsx hillsfile3d object.n number of lines(default10)....further arguments passed to or from other methods.Exampleshead(acealanme3d)max.fes3d7 max.fes3d Calculate maximum of3D free energy surfaceDescription‘max.fes3d‘calculates maximum of free energy in a fes3d object.Usage##S3method for class fes3dmax(inputfes,na.rm=NULL,...)Argumentsinputfes fes3d object.na.rm a logical indicating whether missing values should be removed....further arguments passed to or from other methods.Examplestfes<-fes(acealanme3d,imax=5000)max(tfes)min.fes3d Calculate minimum of3D free energy surfaceDescription‘min.fes3d‘calculates minimum of free energy in a fes3d object.Usage##S3method for class fes3dmin(inputfes,na.rm=NULL,...)Argumentsinputfes fes3d object.na.rm a logical indicating whether missing values should be removed....further arguments passed to or from other methods.Examplestfes<-fes(acealanme3d,imax=5000)min(tfes)8plot.fes3d oneminimum.fes3d Creates one ad hoc3D free energy minimum for a fes objectDescription‘oneminimum.fes3d‘creates an ad hoc3D free energy minimum on free energy surface.This can be used to calculate3D free energy surface evolution at arbitrary point of free energy surface. Usage##S3method for class fes3doneminimum(inputfes,cv1,cv2,cv3)Argumentsinputfes fes3d object.cv1the value of collective variable1.cv2the value of collective variable2.cv3the value of collective variable3.Valueminima object.Examplestfes<-fes(acealanme3d,imax=1000)minima<-fesminima(tfes)minima<-minima+oneminimum(tfes,cv1=0,cv2=0,cv3=0)minimaplot.fes3d Plot3D free energy surface objectDescription‘plot.fes3d‘plots3D free energy surface using.Usage##S3method for class fes3dplot(x,xlab=NULL,ylab=NULL,zlab=NULL,xlim=NULL,ylim=NULL,zlim=NULL,level=NULL,col=NULL,alpha=NULL,main=NULL,sub=NULL,fill=TRUE,...)plot.hillsfile3d9 Argumentsx fes3d object.xlab a title for the x axis:see’title’.ylab a title for the y axis:see’title’.zlab a title for the z axis:see’title’.xlim numeric vector of length2,giving the x coordinates range.ylim numeric vector of length2,giving the y coordinates range.zlim numeric vector of length2,giving the z coordinates range.main an overall title for the plot:see’title’.sub a sub title for the plot:see’title’.level number or numeric vector of levels at which to draw3D isosurface.col color of the free energy surface.It can be a single color or a vector with multiple colors for multiple3D isosurfaces.alpha number or numeric vector of alpha levels(transparency)of3D isosurfaces.fill a logical value indicating whether3D isosurface is ploted as solid surface(True) or wireframe(False)....further arguments passed to or from other methods.Examplestfes3d<-fes(acealanme3d,imax=5000)plot(tfes3d)plot.hillsfile3d Plot hillsfile3d objectDescription‘plot.hillsfile3d‘plots hillsfile object.It plots CV1vs CV2vs CV3.Usage##S3method for class hillsfile3dplot(x,xlab="CV1",ylab="CV2",zlab="CV3",main=NULL,sub=NULL,col="orange",...)10plot.minima3dArgumentsx hillsfile object.xlab a title for the x axis:see’title’.ylab a title for the y axis:see’title’.zlab a title for the z axis:see’title’.main an overall title for the plot:see’title’.sub a sub title for the plot:see’title’.col color code or name,see’par’....further arguments passed to or from other methods.Examplesplot(acealanme3d)plot.minima3d Plot minima3d objectDescription‘plot.minima3d‘plots3D free energy surface with minima.The free energy surface is plotted the same way as by plot.fes3d with additional minima labels.Usage##S3method for class minima3dplot(x,xlab="CV1",ylab="CV2",zlab="CV3",level=NULL,col=NULL,alpha=NULL,main=NULL,sub=NULL,fill=TRUE,...) Argumentsx minima3d object.main an overall title for the plot:see’title’.sub a sub title for the plot:see’title’.xlab a title for the x axis:see’title’.ylab a title for the y axis:see’title’.zlab a title for the z axis:see’title’.level number or numeric vector of levels at which to draw3D isosurface.col color of the free energy surface.It can be a single color or a vector with multiple colors for multiple3D isosurfaces.alpha number or numeric vector of alpha levels(transparency)of3D isosurfaces.fill a logical value indicating whether3D isosurface is ploted as solid surface(True) or wireframe(False)....further arguments passed to or from other methods.plotheights.hillsfile3d11Examplestfes<-fes(acealanme3d,imax=5000)minima<-fesminima(tfes)plot(minima)plotheights.hillsfile3dPlot evolution of heights of hills in hillsfile3d objectDescription‘plotheights.hillsfile3d‘plots evolution of heights of hills.In well tempered metadynamics hill heights decrees withflooding of the free energy surface.Evolution of heights may be useful to evaluate convergence of the simulation.Usage##S3method for class hillsfile3dplotheights(hills,ignoretime=FALSE,xlab=NULL,ylab=NULL,xlim=NULL,ylim=NULL,main=NULL,sub=NULL,col="black",asp=NULL,lwd=1,axes=TRUE)Argumentshills hillsfile object.ignoretime time in thefirst column of the HILLSfile will be ignored.xlab a title for the x axis:see’title’.ylab a title for the y axis:see’title’.xlim numeric vector of length2,giving the x coordinates range.ylim numeric vector of length2,giving the y coordinates range.main an overall title for the plot:see’title’.sub a sub title for the plot:see’title’.col color code or name,see’par’.asp the y/x aspect ratio,see’plot.window’.lwd line width for drawing symbols see’par’.axes a logical value indicating whether both axes should be drawn on the plot. Examplesplotheights(acealanme3d)12print.hillsfile3d print.fes3d Print minimum and maximum of3D free energy surfaceDescription‘print.fes3d‘prints dimensionality,minimum and maximum of free energy in a fes objectUsage##S3method for class fes3dprint(x,...)Argumentsx fes3d object...further arguments passed to or from other methods.Examplestfes<-fes(acealanme3d,imax=5000)tfesprint.hillsfile3d Print hillsfile3dDescription‘print.hillsfile3d‘prints dimensionality and size of a hillsfile object.Usage##S3method for class hillsfile3dprint(x,...)Argumentsx hillsfile3d object....further arguments passed to or from other methods.Examplesacealanme3dprint.minima3d13 print.minima3d Print minima3d objectDescription‘print.minima3d‘prints3D free energy minima(identifier,values of bins and collective variables and free energy).Usage##S3method for class minima3dprint(x,...)Argumentsx minima object....further arguments passed to or from other methods.Examplestfes<-fes(acealanme3d,imax=5000)minima<-fesminima(tfes)minimaread.hills3d Read3D HILLS from PlumedDescription‘read.hills3d‘reads a HILLSfile generated by Plumed and returns a hillsfile3d er can specify whether some collective variables are periodic.Usageread.hills3d(file="HILLS",per=c(FALSE,FALSE,FALSE),pcv1=c(-pi,pi),pcv2=c(-pi,pi),pcv3=c(-pi,pi),ignoretime=FALSE)Argumentsfile HILLSfile from Plumed.per logical vector specifying periodicity of collective variables.pcv1periodicity of CV1.pcv2periodicity of CV2.pcv3periodicity of CV3.ignoretime time in thefirst column of the HILLSfile will be ignored.14read.plumed3dValuehillsfile object.Examplesl1<-"1-1.587-2.969 3.0130.30.30.31.11110"l2<-"2-1.067 2.745 2.9440.30.30.31.10910"l3<-"3-1.376 2.697 3.0490.30.30.31.08010"l4<-"4-1.663 2.922-3.0650.30.30.31.07210"fourhills<-c(l1,l2,l3,l4)tf<-tempfile()writeLines(fourhills,tf)read.hills3d(tf,per=c(TRUE,TRUE))read.plumed3d Read3D free energy surface from PLUMED sum_hillsDescription‘read.plumed3d‘reads3D free energy surface from PLUMED sum_hills.The grid in the inputfile must contain the same number of points for CV1,CV2and CV3.It does not use the header of the file.Periodicity must be specified.Usageread.plumed3d(file="fes.dat",per=c(FALSE,FALSE,FALSE))Argumentsfile inputfile from PLUMED sum_hills.per logical vector specifying periodicity of collective variables.Valuefes3d object.Examplesl1<-"-3.14-3.14-3.14-61.13-47.4319.00 2.04"l2<-"-1.05-3.14-3.14-70.7225.9525.78 2.43"l3<-" 1.05-3.14-3.14-65.588.34 2.82-3.09"l4<-"-3.14-1.05-3.14-51.31-43.88-19.91 1.51"l5<-"-1.05-1.05-3.14-66.437.67-22.45-0.39"l6<-" 1.05-1.05-3.14-61.08-7.50-7.36-0.83"l7<-"-3.14 1.05-3.14-53.07-55.120.19-0.28"l8<-"-1.05 1.05-3.14-62.8136.19 1.650.45"l9<-" 1.05 1.05-3.14-65.2822.8411.470.59"l10<-"-3.14-3.14-1.05-13.03-32.178.24-35.25"summary.fes3d15 l11<-"-1.05-3.14-1.05-21.8817.8921.91-51.20"l12<-" 1.05-3.14-1.05-14.49 3.60 6.04-44.05"l13<-"-3.14-1.05-1.05-2.26-7.00-7.01-10.65"l14<-"-1.05-1.05-1.05-8.21 3.69-22.89-28.48"l15<-" 1.05-1.05-1.05-1.100.52 3.59-1.99"l16<-"-3.14 1.05-1.05-3.75-11.70-5.65-15.36"l17<-"-1.05 1.05-1.05-1.15 5.75 1.05-2.42"l18<-" 1.05 1.05-1.05-10.678.23-10.42-36.77"l19<-"-3.14-3.14 1.05-4.64-13.7910.5114.96"l20<-"-1.05-3.14 1.05-7.8012.2420.5923.03"l21<-" 1.05-3.14 1.05-5.32 3.46 3.1721.99"l22<-"-3.14-1.05 1.05-2.06-6.590.1710.04"l23<-"-1.05-1.05 1.05-9.698.43-0.9736.97"l24<-" 1.05-1.05 1.05-0.19-0.44-0.260.91"l25<-"-3.14 1.05 1.05-7.98-23.02 3.9726.98"l26<-"-1.05 1.05 1.05-4.6413.66-9.7410.15"l27<-" 1.05 1.05 1.05-13.4215.7816.3641.60"twentysevenpoints<-c(l1,l2,l3,l4,l5,l6,l7,l8,l9,l10,l11,l12,l13,l14,l15,l16,l17,l18,l19,l20,l21,l22,l23,l24,l25,l26,l27)tf<-tempfile()writeLines(twentysevenpoints,tf)read.plumed3d(tf,per=c(TRUE,TRUE,TRUE))summary.fes3d Print summary of3D free energy surfaceDescription‘summary.fes3d‘prints minimum and maximum of free energy in a fes object.Usage##S3method for class fes3dsummary(object,...)Argumentsobject fes3d object....further arguments passed to or from other methods.Examplestfes<-fes(acealanme3d,imax=5000)summary(tfes)16summary.minima3d summary.hillsfile3d Print summary for hillsfile3dDescription‘summary.hillsfile3d‘prints dimensionality,size and collective variable ranges of a hillsfile3d ob-ject.Usage##S3method for class hillsfile3dsummary(object,...)Argumentsobject hillsfile3d object....further arguments passed to or from other methods.Examplessummary(acealanme3d)summary.minima3d Print minima3d object summaryDescription‘summary.minima3d‘prints summary for3D free energy minima(identifier,values of bins and collective variables,free energy and equilibrium populations).Usage##S3method for class minima3dsummary(object,temp=300,eunit="kJ/mol",...)Argumentsobject minima3d objecttemp temperature in Kelvinseunit energy units(kJ/mol or kcal/mol,kJ/mol is default)...further arguments passed to or from other methods.Examplestfes<-fes(acealanme3d,imax=5000)minima<-fesminima(tfes)summary(minima)tail.hillsfile3d17 tail.hillsfile3d Print last n lines of hillsfile3dDescription‘tail.hillsfile3d‘prints last n lines of a hillsfile3d object.Usage##S3method for class hillsfile3dtail(x,n=10,...)Argumentsx hillsfile3d object.n number of lines(default10)....further arguments passed to or from other methods.Examplestail(acealanme3d)Index∗datasetsacealanme3d,2acealanme3d,2feprof.minima3d,3fes.hillsfile3d,3fes2.hillsfile3d,4fesminima.fes3d,5fespoint.hillsfile3d,5head.hillsfile3d,6max.fes3d,7min.fes3d,7oneminimum.fes3d,8plot.fes3d,8plot.hillsfile3d,9plot.minima3d,10plotheights.hillsfile3d,11print.fes3d,12print.hillsfile3d,12print.minima3d,13read.hills3d,13read.plumed3d,14summary.fes3d,15summary.hillsfile3d,16summary.minima3d,16tail.hillsfile3d,1718。
The Impact of Globalization on NationalIdentityThe Impact of Globalization on National Identity In today's interconnected world, globalization has become an undeniable reality. It has transformed the way we communicate, trade, and interact with each other. However, this globalintegration has also raised concerns about its impact on national identity.National identity refers to the sense of belonging and shared values thatindividuals associate with their nation. Globalization, with its emphasis onglobal interconnectedness and cultural diffusion, has the potential to challengeand reshape national identities in various ways. From one perspective,globalization can be seen as a threat to national identity. As cultures and traditions are exposed to external influences, there is a fear that they may be eroded or diluted. The increasing presence of global brands, multinational corporations, and Western cultural products can lead to the homogenization of cultures, making them indistinguishable from one another. This can result in aloss of distinctiveness and uniqueness that defines a nation's identity. Moreover, the spread of ideas and values through globalization can clash with traditional beliefs and practices, creating a sense of cultural dissonance and identity crisis. On the other hand, globalization can also be seen as an opportunity to enrich and redefine national identity. By exposing individuals to different cultures and ideas, globalization can foster a sense of openness and inclusivity. It allows people to learn from each other, appreciate diversity, and develop a more cosmopolitan outlook. This can lead to the emergence of hybrid identities, where individuals draw from both their national and global experiences to constructtheir sense of self. Globalization can also provide platforms for cultural expression and exchange, allowing nations to showcase their unique traditions and values on a global stage. Furthermore, globalization has the potential to strengthen national identity by promoting economic growth and prosperity. Asnations engage in global trade and investment, they can develop their industries, create jobs, and improve living standards. This can foster a sense of nationalpride and unity, as citizens benefit from the success and recognition of theirnation on the global stage. Additionally, globalization can enable nations to address global challenges collectively, such as climate change or terrorism, which can further enhance their sense of national identity and solidarity. However, it is important to acknowledge the complexities and contradictions that arise from the impact of globalization on national identity. While globalization canfacilitate the exchange of ideas and cultural practices, it can also lead to the commodification and appropriation of cultural symbols. This can result in the exploitation and misrepresentation of certain cultures, further marginalizing already vulnerable communities. Moreover, the unequal distribution of resources and power in the globalized world can exacerbate social and economic inequalities within nations, leading to divisions and conflicts that challenge the notion of a unified national identity. In conclusion, the impact of globalization on national identity is a multifaceted and nuanced issue. While it has the potential to erode traditional cultural identities, it can also foster new forms of identity that are more inclusive and cosmopolitan. Globalization can both challenge and strengthen national identity, depending on how it is navigated and embraced. It is essential to recognize the importance of preserving cultural diversity and ensuring that the benefits of globalization are shared equitably. By doing so, nations can navigate the complexities of globalization while maintaining a strong sense of national identity.。
世界人工智能研究报告英文World Artificial Intelligence Research ReportAbstract:This report provides an overview of the current state of artificial intelligence (AI) research worldwide. It highlights key areas of focus, advancements, and challenges faced by researchers in the field. The report is aimed at providing insights into the global AI research landscape and guiding future research directions.1. Introduction:- Brief overview of the importance and impact of AI research- Objectives of the report2. Methodology:- Data collection and analysis approach- Selection criteria for research papers and publications3. Global AI Research Landscape:- Major countries and institutions leading AI research- Distribution of research papers and publications across regions - Funding sources and investments in AI research4. Key Areas of Focus:- Machine learning and deep learning algorithms- Natural language processing and understanding- Computer vision and image recognition- Reinforcement learning and autonomous systems5. Advancements in AI Research:- Breakthroughs and milestones achieved in the past decade- Role of big data and computational power in advancing AI research- Impact of AI in various industries and sectors6. Challenges and Opportunities:- Ethical considerations in AI research- Bias and fairness in AI algorithms- Cybersecurity implications of AI advancements- Collaboration and knowledge sharing opportunities7. Future Directions:- Promising areas for future research and development- Potential impact of AI on societal and economic aspects- Considerations for policymakers and decision-makers8. Conclusion:- Summary of key findings and insights- Importance of continued research and development in the field of AI9. References:- List of sources and publications referenced in the reportThe World Artificial Intelligence Research Report aims to provide a comprehensive analysis of the global AI research landscape, promoting knowledge sharing and fostering collaboration among researchers worldwide.。
全球化的利弊英语作文•相关推荐全球化的利弊英语作文(精选24篇)在学习、工作或生活中,大家对作文都再熟悉不过了吧,作文一定要做到主题集中,围绕同一主题作深入阐述,切忌东拉西扯,主题涣散甚至无主题。
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全球化的利弊英语作文篇1What does globalization mean?We always hear this word on TV and read about it in newspapers. It means the world is now a village- The Global Village. The world has become smaller. Of course the world did not shrink and it isn't a village. Because of better transport, the Internet and more trading between countries, it is easier to do business. Japanese car makers have factories in Thailand. American computer companies employ thousands of people in China. That's globalization.And don't forget the millions of call centre jobs in India that workers in America and Europe used to do.Globalization also means it is easier to work in another country.So, is globalization a good or bad thing?That's a difficult question to answer.全球化的利弊英语作文篇2With the rapid social and economic development, globalization comes not to be an unfamiliar word to all of us. Though we are living in the affection of it, yet it is hard to tell it’s advantages and disadvantages.Globalization phenomenon is an outcome of socialdevelopment. The typical types are economic globalization, cultural globalization. As we all know, it is a double-edged sword. Therefore, we must pay more attention on this phenomenon and it’s development trend.Globalization has so many advantages, such as it makes the world become a small village and let people touch each other more convenient and easy, it increase free trade between nations and give the developing countries a terrific opportunity to develop themselves in all aspects quickly. What’s more, it can reduce the cultural barriers and let various of cultural get a better communication and development. On the contrary, it also has a lot of disadvantages. Because under globalization, every country’s economy can make a great influence of others, it make the economy of the world more fragile. In order to possess the good chance and precious resources, the disputes and even wars may take place between nations. In recent years, great risk of diseases being transported between nations has also become a threaten to people.As the globalization has become an irrevocable trend, we must adjust it. This phenomenon is an opportunity as well as a challenge. Consequently, every person, every nation should try the best to get a good position in the process of globalization and make full use of such a vital chance to be stronger.全球化的利弊英语作文篇3A prevailing phenomenon is that countries have less different between each other nowadays. Different person holds different views to this trend. As for me, I think its advantages outweigh the disadvantages.It is obvious that if all the countries share the same things, minority nationality regions are affected by the developedcountries. Then maybe their minority culture will vanish. Especially in today's word, the youth is more likely to understand modern culture, and they could forget some culture from their own countries.Though it is unnegligiblethat the problem, I mentioned above, I still stick on my opinion that it has more advantages. First, there will be an excellent chance for people who are from different countries to have a communication. People possess similar hobbies and life style, and they will have more common topics to talk about. It really can narrow the gap between two countries.Second, economic globalization can be seen from this trend, promoting all the countries' economy development. And we can get all the goods we want wherever you are. The third one is language and education. Countries are becoming less evident means people break the barrier of the differences between two languages, and it is quite good for academic communication and high level education. We can learn advanced ideas and views directly.All in all, the globalization is promoting many aspects of the countries, and actually we are experienced in it and benefit from this trend. As a result, I hold the view that the advantages outweigh the drawbacks.全球化的利弊英语作文篇4Globalization has found a significant place in the lives of the people. During the process of globalization, we have made a bridge where ideas and beliefs can cross the borders, and the walls of distrust and the barriers of suspicion between countries have graduallydisappeared. Though globalization is seen as a sign of a hopeful future by some, there are others who believe that it cancause a horrible disaster for the world economy.Counties benefit a lot from globalization, especially the developing countries. With it, there is a global market for companies to trade their products which can make the production sector develop rapidly. This gives lots of options to the manufacturers as well. Besides, competition keeps prices relatively low and it can provide a wider range of options for people, to choose from among the products of different nations. In addition, there is a sound flow of money, as a result, inflation is less likely to occur.But the disadvantages brought by globalization cannot be ignored. Globalization is causing Europeans to lose their jobs as work is being swerved to the Asian countries. The cost of labor in the Asian countriesis low as compared to other countries which is often argued that poor countries are exploited by the richer countries where the work force is taken advantage of and low wages are implemented. Moreover, companies are as opening their counterparts in other countries which can result in transferring the quality of their product to other countries, thereby increasing the chances of poor quality.Simply put, globalization is an ongoing process of integration of regional economies into global network of communication which the human being cannot hold back. So we should keep a positive attitude toward it, take good use of it and avoid disadvantages at the same time. Thus there will be a better world where all the people can have a brighter future.全球化的利弊英语作文篇5Even though globali zation affects the world’s economies in a positive way, its negative side should not be forgotten. Discussthe advantages and disadvantages of globalization.In the present age, globalization is playing an increasingly important role in our lives. But in the meantime whether it is a blessing or a curse has sparked a heated debate. Some people argue that globalization has a fundamentally beneficial influence on our lives, while many others contend that it has a detrimental effect as well.A convincing argument can be made about globalization is that it not only plays a pivotal role in the development of technology and economy, but also promotes the cultural exchange between different countries. To start with, it is the globalization that impelled many corporate to become an international group, thereby making a contribution to the local technology and employment. Specifically, when a multinational group establish a factory in a developing country, the new equipment, the new management skills and the job vacancies are all in the best interest of the local society. Moreover, people worldwide can get to know each other better through globalization. It is easy to see that more and more Hollywood blockbusters show cultures different from American, some recent exampl es are ‘Kungfu Panda’ and ‘The Mummy’.Admittedly, profit-driven globalization has severely affected young people. Today, in the metropolises in different countries, it is very common to see teenagers wearing NIKE T-shirts and Adidas footwear, playing Hip-Hop music on Apple iPods and eating at KFC. The culture that took a thousand years to form just seems similar in these cities; it looks like you can only distinguish them by their language. Meanwhile, in some developing countries, sweat workshops are always a concerning issue. For instance, reports show that some teenagers employed byNIKE’s contractors work in smelly factories over 14 hours a day, but are only paid fifty cents per hour.In summary, I would concede that globalization does come with some adverse effects. Despite that fact, benefits created by it far outweigh the disadvantages. Overall, I am convinced that we should further promote globalization and meanwhile the local government should take measures to combat cultural assimilation and sweat workshops.Increasing the price of petrol is the best way to solve growing traffic and pollution problems. To what extent do you agree or disagree? What other measures do you think might be effective? 全球化的利弊英语作文篇6The last decades has witnessed the accelerated advancement of economy,which brings the economic globalization,a tendence that we can never hold it back. Under the condition of economic globalization, cultural exchanges between countries and countries, regions and areas are frequent ,accompanied by opportunity it provides,we are also stood in front of the huge challenges to the culture.Just like a coin,which has two sides,on one aspect,the globalization is not only accelerating economic growth speed, spreading new technology and effective ways to improve the level of life rich and poor countries, but ,it is also a controversial process that may contribute to a national sovereignty, erosion infringement to local and traditional culture , and the threat of economic and social stability. Between globalization and culture that is a complementary relationship. And under the wave of economic globalization, how do we do at the same time of accepting foreign culture, can also maintain the development of traditional Chinese culture? From my perspective, For today'sChina,we’d better adhere to the use of Marxist ideological line and requirements of the socialist modernization, to analyze and criticize the traditional culture, to identify essence and dross with a calm and objective attitude, derive the traditional culture of all reasonable composition, gives our history a new contents and the era value, and Only in this way,can our china stride bravely forward under the impact of the globalization全球化的利弊英语作文篇7Globalization is a declarationof war upon all other cultures. And in culture wars, there is no exemption of civilians, there are no innocent bystanders. Why should it be expected that ancient and rooted civilizations are going to accept this peripheralisationwithout a struggle? The answer to that is that globalization carries an implicit promise that it will relieve poverty and offer securityperhaps the most ancient of human dreams. Because of the power of global capitalism to create wealth, it is assumed that this priority must sweep aside all other human preoccupations, including all existing institutions, interpretations and searches for meaning in the world.It is disingenuous to assume that economy, society and culture operate in separate spheres. This suggests that, one, exposed to the globalizing imperative, no aspect of social life, customary practice, traditionalbehaviour will remain the same.There have been, broadly, two principal responses in the world, which we may call the fatalistic and the resistant. It is significant that among the most fatalistic have been the leaders of G-7, Ex-President Clinton said globalization is a fact not a policy choice Tony Blair said it is inevitable and irreversible. It may be considered paradoxical that the leaders of the most dynamic and expanding economies in the world offer such a passive,unchallenging view of what are, after all, human-made arrangements. These are among the richest and most proactive regimes, which can wage endless war on the great abstraction, that is terror, topple regimes and lay down one WTO law for the poor and another for themselves. Is their helplessness in the presence of these mighty economic and cultural powers?全球化的利弊英语作文篇8Globalization can be found in five different areas: economic, cultural, political, religious, and social systems.It should not be narrowly confused with economic globalization, which is only one aspect. While some scholars and observers of globalization stress convergence of patterns of production and consumption and a resulting homogenization of culture, power, stress, and hunger, others stress that globalization has the potential to take many diverse forms. In economics, globalization is the convergence of prices, products, wages, rates of interest and profits.Globalization of the economy depends on the role of human migration, international trade, movement of capital, and integration of financial markets. The International Monetary Fund notes the growing economic interdependence of countries worldwide through increasing volume and variety of cross-border trade.全球化的利弊英语作文篇9People around the world may feel that the climate has been getting steadily warmer and warmer in recent years. Places which used to be abundant in snowfall have frequently experienced snowfree winters. Drought lasts longer in some dry areas. People find that without air conditioners they could hardly work or fall asleep on hotter summer daysg.The side effects of global warming are alarminS. A warmer global climate melts the ice caps, raising sea levels. What is more, it disturbs weather patterns, causing droughts severe storms, hurricanes . People suffer a lot from disasters relevant to global warming.To stop global warming we should make immediate and continual efforts. We hope the situation will soon change. Global warming catches and holds our concern, for it affects us and will affect our later generations. We cannot wait any longer. Do it. Do it right. Do it right now.全球化的利弊英语作文篇10With the development of economy, more and more greenhouse gases are being discharged into the air. CO2 makes up about 70% of the greenhouse gases, which is considered to be one of the greatest causes of global warming. It has harmful effects, causing the sea level to rise and many natural disasters to strike.So we must take effective measures to save our planet. First, we should use more clean energy and less coal and oil. Second, we should go to work on foot or by bus instead of driving a car if possible. Third, we should plant more trees, because plants can turn CO2 into oxygen. More importantly, we should form the habit of saving energy in our daily life.全球化的利弊英语作文篇11In this report, I learned a lot of things, but my first thought is that the cause of global warming is carbon dioxide increases.Why is carbon dioxide will increase? I think the reason is that people often feed drive, raising livestock, factories discharge smoke... And so on. But these are all can be solved together, perhaps can improve the earth continued warming, for example:close to the destination can ride a bike, Destination is far away, you can use public transport; Livestock waste processed into Hanoi again; Factory can build a waste treatment plant... And so on.Please do not underestimate the power of carbon dioxide, wait until the sea level rise, urban flooding and flooded farmland, in the end would have faced the crisis of insufficient food. Please join me shout: "stop hurt the behavior of the earth! The earth on which we live is only one."全球化的利弊英语作文篇12The cold winter has passed, but this winter with snow is not, is not how cold the weather, why is this so?I asked my mother, my mother said: "I don't know, you go online to check." I opened the computer, input -- global warming. There have been many answers on the layout.Because of human destruction of forests and other greenhouse gases from the burning of when, because these greenhouse gases with high transmittance in the visible light radiation from the sun, and the earth is reflected is highly absorbent, can strongly absorb infrared radiation on the ground, the greenhouse effect is often said that the "". Global warming may lead to consequences, will lead to a global redistribution of precipitation, melting glaciers and permafrost, rising sea levels, damage the balance of the ecosystem and the human food supply and living environment.Global warming is not only harmful to humans, but also endanger the survival of animals. For example, the polar bear, because of global warming, melting glaciers and polar bear hunting fish more difficult, and the ice melting fast, this continues, sooner or later the polar bears extinct species like the polar bear, Arctic wolf, Arctic animals arepenguins.Want to stop global warming, we should save every drop of water; plant more trees to reduce desertification; do not use disposable convenient bag; reduce the emission of carbon dioxide. I appeal to our homes, we act together now!全球化的`利弊英语作文篇13Recently,global warming has become a hot topic among people.It results from serious airpollution. As the environmental pollution is more and more strict, thetemperature of all the world has dramatic increased. Gradually, some disastersuch as drought, floodandGlaciers Melting follow. How terrible it is! Therefore,we need to protect our earth and fight against the disaster together.We shouldstart from the trivial side.Making contribution to protecting our home.全球化的利弊英语作文篇14With the development of economy, more and more greenhouse gases are being discharged into the air. CO2 makes up about 70% of the greenhouse gases, which is considered to be one of the greatest causes of global warming. It has harmful effects, causing the sea level to rise and many natural disasters to strike.So we must take effective measures to save our planet. First, we should use more clean energy and less coal and oil. Second, we should go to work on foot or by bus instead of driving a car if possible. Third, we should plant more trees, because plants can turn CO2 into oxygen. More importantly, we should form the habit of saving energy in our daily life.全球化的利弊英语作文篇15One of the most serious problem in front of the world is theglobal warming.There are some reasons that can cause such a problem.First,people cut down trees and forests freely.Besides,people burn things everywhere - even it is not allowed.People waste things out of control is another reason.So,we should try our best to save things as much as we can.We should encourage others to do so.If we do it,the stage will be better.If we don't take any action,as the warld is becoming warmer and warmer,the water level is rising.It can cause subsidence and threaten people's activities.全球化的利弊英语作文篇16People around the world may feel that the climate has been getting steadily warmer and warmer in recent years. Places which used to be abundant in snowfall have frequently experienced snowfree(无雪的)winters. Drought lasts longer in some dry areas. People find that without air conditioners they could hardly work or fall asleep on hotter summer daysg. The side effects of global warming are alarminS. A warmer global climate melts the ice caps, raising sea levels. What is more, it disturbs weather patterns, causing droughts, severe storms, hurricanes People suffer a lot from disasters relevant to global warming.To stop global warming we should make immediate and continual efforts. We hope the situation will soon change. Global warming catches and holds our concern, for it affects us and will affect our later generations. We cannot wait any longer. Do it. Do it right. Do it right now.全球化的利弊英语作文篇17Global Warming At present, with the development of economies around the world may feel that the climate is becoming more and more warmer. CO2 makes up about 70% of the greenhouse gases. It is considered to be one of the greatestreasons of global warming. It's very serious, but many people can't recognize that because the only think about themselves. They don't mind the climate becoming warmer. They don't mind the ice melting. They don't mind how many animals become extinct. They don't mind how many coastal cities become flooded . They don't mind…… They are wrong. Global warming can have many strong influences for us. For example: Global warming will make trouble with physiology. People will become more easily ill and even breed new diseases. People will pay more and more money for health care but more and more people die. No amount of money or even the best doctors, wll not be able to save your life. Even if you aren't dying, you will feel sad and alone. So many relatives and friends' death will make you want to kill yourself. Global warming will give the air and ocean huge power. Thus making large or even super typhoons, hurricanes, tsunamis and other disasters. Many houses will be destroyed. Many place will flood. We will be faced with more and more disasters, damning more and more money and life. Rising temperatures will not only create higher sea level, but also will cause droughts. Large-scale areas will become arid and thus food production will be less. We will be without food. People around the world will face food shortages and more and more war will happen for food. If temperatures continue to rise, animals will come out of hibernation early, but will not have the food supply necessary to survive. For example: Insects will eat a lot of forests and crops with no natural enemies. Without forests, global warming will become more and more sercious, creating a vicious cycle. No crops, means no human food. The greatest of global warming is at ice age like in the movie “The Day After Tomorrow”, this is a scenario that take place. So we must do something to avoid thesethings from happening. First, we should use more and more clean energy and less oil and coal. Second, we should go to work by bus or on foot instead of driving. Third, we should plant more trees. The most important point is we should make a habit of saving energy in everyday life.全球化的利弊英语作文篇18The summer melting of the Arctic, more severe hurricanes in the US, drought in China and Africa, wildfires in Australia; these impacts are all signs of an increasingly chaotic climate system that will undermine the economic and development goals of all nations.Time is running out. Dr James Hansen, a leading climatologist from the National Aeronautics and Space Administration (NASA), recently stated that the world is now in "imminent peril". Dr Qin Dahe from the Chinese Academy of Sciences also stated "Climate change has already brought severe and obvious threats to the economic and social development of China".The window for avoiding that peril is narrow, and closing rapidly, but it is not yet closed. With the right leadership, the world can bring global greenhouse gas emissions under control, set them on a downward trajectory, and avoid the most catastrophic impacts of global warming.China has begun work on a new energy law that places strong emphasis on reducing greenhouse gas emissions, demonstrating that greener development is not only possible but desirable. Should the new Energy Law be passed, it would provide guidance for China's energy strategy in its 12th Five Year Plan.As the largest global greenhouse emitters, the United Statesand China have an historic opportunity to show decisive leadership. Commitments from both nations may differ but the urgency of the task facing us means every nation must play their part. There are encouraging signs that the two nations have already started some Ping Pong diplomacy on climate and energy issues in the lead up to this week's meeting.全球化的利弊英语作文篇19With the development of economy, People around the world may feel that the climate has been getting steadily warmer and warmer in recent years.CO2 makes up about 70% of the greenhouse gases, which is considered to be one of the greatest causes of global warming.There are many harmful effects. It cause the sea level to rise and many natural disasters to strike.What is more, it disturbs weather patterns, causing droughts, severe storms, hurricanes. People suffer a lot from disasters relevant to global warming.It is urgent that immediate and effective actions should be taken right away. First, more trees need to be planted to help improve and beautify the environment. Besides, stricter laws concerning global warming and irresponsible use of fuel resources have to be put into effect and achieved good results. In a word, there is a long way to go before we can take a comfortable world for granted again .Do it. Do it right. Do it right now.全球化的利弊英语作文篇20People around the world may feel that the climate has been getting steadily warmer and warmer in recent years. Places which used to be abundant in snowfall have frequently experienced snowfree(winters. Drought lasts longer in some dry areas. People find that without air conditioners they could hardly workor fall asleep on hotter summer daysg. The side effects of global warming are alarminS. A warmer global climate melts the ice caps, raising sea levels. What is more, it disturbs weather patterns, causing droughts, severe storms, hurricanes(飓风). People suffer a lot from disasters relevant to global warming.To stop global warming we should make immediate and continual efforts. We hope the situation will soon change. Global warming catches and holds our concern, for it affects us and will affect our later generations. We cannot wait any longer. Do it. Do it right. Do it right now.全球化的利弊英语作文篇21The main cause of global warming is nearly a century of human heavy use of fossil fuels, large amount of greenhouse gas emission; the burning of coal, natural gas, a large amount of greenhouse gases; wanton cutting of forests, making the ability to absorb carbon dioxide and lead.The consequences of global warming, will lead to the redistribution of global precipitation, glaciers and permafrost to melt, sea-level rise, endangering not only the balance of the natural ecological system, but also a threat to the human food supply and living environment. A few days ago, polar bears are beginning to cut one another's throats, Hierro Island lizards due to climate variation on the verge of extinction, warm winter disrupted flowering, bloom all over Japan cherry blossom in advance; because the warm climate Moscow warm winter, bears suffer not hibernating; France this year suffered a warm winter, birds species were significantly reduced in number. The majority of our region also appeared in " warm winter ". Climate warming will make our country main crop breed to change, will cause water shortages and increased mortality. People have to pay for climate warming is more and more heavyprice.When I was informed of these circumstances, the mood is heavy. Chairman Mao taught us " the world is yours, is our, but in the final analysis is your. " At present, I, as a ordinary middle school students, and to the world difficult problem do? From now on, from daily bagatelle, lay a good foundation for tomorrow. T o save energy, protect environment is the key. Nowadays, some places due to depletion of energy while facing the crisis of survival, but in some places it in a tremendous waste of. We want to from their own work, to develop good saving habits, to save every drop of water, every degree of electricity. See others waste, to actively prevent. There is a need to identify effective methods, to solve the problem. This is not only a scientist things, but every man. As a middle school student, we can only grasp the rich scientific and cultural knowledge, in order to solve this problem is to make a great contribution to.All human beings are of concern to climate warming, let the world is full of alertness and consciousness. To save energy, protect environment, let us work together.全球化的利弊英语作文篇22Many people believe that human activity is causing the earth’s temperature to rise. They say that this global warming will have dreadful consequences for our environment, such as drought and flooding.What should governments do to help prevent global warming? Give reasons for your suggestions.The earth’s temperature is rapidly changing. As a result there has been a lot of climate change such as heat waves, droughts and floods. Scientists believe that this is the result of human activity, which is polluting the Earth’s atmosphere. This could become a disaster if governments do not act to help。
Package‘soma’October14,2022Version1.2.0Date2022-05-01Title General-Purpose Optimisation with the Self-Organising MigratingAlgorithmAuthor Jon ClaydenMaintainer Jon Clayden<****************>Depends R(>=2.5.0)Imports reportr(>=1.3.0)Suggests tinytest,covr,shadesDescription An R implementation of the Self-Organising Migrating Algorithm,a general-purpose,stochastic optimisation algorithm.The approach is similar to that of genetic algo-rithms,although it is based on the idea of a series of``migrations''by afixed set of individu-als,rather than the development of successive generations.It can be applied to any cost-minimisation problem with a bounded parameter space,and is robust to local minima.License GPL-2URL https:///jonclayden/soma/Encoding UTF-8RoxygenNote7.1.2NeedsCompilation noRepository CRANDate/Publication2022-05-0208:40:05UTCR topics documented:all2one (2)soma (4)Index71all2one Options for the available SOMA variantsDescriptionThese functions generate option lists(and provide defaults)for the SOMA algorithm variants avail-able in the package,which control how the algorithm will proceed and when it will terminate.Each function corresponds to a different top-level strategy,described in a different reference.Usageall2one(populationSize=10L,nMigrations=20L,pathLength=3,stepLength=0.11,perturbationChance=0.1,minAbsoluteSep=0,minRelativeSep=0.001)t3a(populationSize=30L,nMigrations=20L,nSteps=45L,migrantPoolSize=10L,leaderPoolSize=10L,nMigrants=4L,minAbsoluteSep=0,minRelativeSep=0.001)pareto(populationSize=100L,nMigrations=20L,nSteps=10L,perturbationFrequency=1,stepFrequency=1,minAbsoluteSep=0,minRelativeSep=0.001)ArgumentspopulationSize The number of individuals in the population.It is recommended that this be somewhat larger than the number of parameters being optimised over,and itshould not be less than2.The default varies by strategy.nMigrations The maximum number of migrations to complete.pathLength The distance towards the leader that individuals may migrate.A value of1corre-sponds to the leader’s position itself,and values greater than one(recommended)allow for some overshoot.stepLength The granularity at which potential steps are evaluated.It is recommended that the pathLength not be a whole multiple of this value.perturbationChanceThe probability that individual parameters are changed on any given step.minAbsoluteSep The smallest absolute difference between the maximum and minimum cost func-tion values.If the difference falls below this minimum,the algorithm will ter-minate.The default is0,meaning that this termination criterion will never bemet.minRelativeSep The smallest relative difference between the maximum and minimum cost func-tion values.If the difference falls below this minimum,the algorithm will ter-minate.nSteps The number of candidate steps towards the leader per migrating individual.This option is used instead of pathLength and stepLength under the T3A and Paretostrategies,where the step length is variable.migrantPoolSize,leaderPoolSizeThe number of randomly selected individuals to include in the migrant andleader pools,respectively,under the T3A strategy.nMigrants The number of individuals that will migrate,at each migration,under the T3A strategy.perturbationFrequency,stepFrequencyScale factors affecting how rapidly the perturbation probability and step sizesfluctuate under the Pareto strategy.DetailsAll To One(the all2one function)is the original SOMA strategy.At each“migration”,the cost function is evaluated for all individuals in the population,and the one with the lowest value is designated the“leader”.All other individuals migrate towards the leader’s position in some or all dimensions of the parameter space,with afixed probability of perturbation in each dimension.Each migration is evaluated against the cost function at several points on the line towards the leader,and the location with the lowest value becomes the individual’s starting position for the next migration.The Team To Team Adaptive(T3A)strategy(Diep,2019)differs in that only a random subset of individuals are selected into a migrant pool and a leader pool for any given migration.A subset of most optimal migrants are then migrated towards the single most optimal individual from the leader pool.The perturbation probability and step length along the trajectory towards the leader also vary according to formulae given by the strategy author as the algorithm progresses through the migrations.In the Pareto strategy(Diep et al.,2019),all individuals are sorted by cost function value at the start of each migration.The leader is selected randomly from the top4%(20%of20%)of most optimal individuals,and a single migrant is chosen at random from between the20th and the36th percentiles of the population(the top20%of the bottom80%).The perturbation probability and the step length again vary across migrations,but this time in a sinusoidal fashion,and the migrant is updated in all dimensions,but some more slowly than others.4somaValueA list of class"soma.options".Author(s)Jon Clayden<****************>ReferencesI.Zelinka(2004).SOMA-self-organizing migrating algorithm.In G.C.Onwubolu&B.V.Babu,eds,New optimization techniques in engineering.V olume141of“Studies in Fuzziness and Soft Computing”,pp.167-217.Springer.Q.B.Diep(2019).Self-Organizing Migrating Algorithm Team To Team Adaptive–SOMA T3A.In proceedings of the2019IEEE Congress on Evolutionary Computation(CEC),pp.1182-1187.IEEE.Q.B.Diep,I.Zelinka&S.Das(2019).Pareto-Based Self-Organizing Migrating Algorithm.Mendel 25(1):111-120.soma The Self-Organising Migrating AlgorithmDescriptionThe Self-Organising Migrating Algorithm(SOMA)is a general-purpose,stochastic optimisation algorithm.The approach is similar to that of genetic algorithms,although it is based on the idea of a series of“migrations”by afixed set of individuals,rather than the development of successive generations.It can be applied to any cost-minimisation problem with a bounded parameter space, and is robust to local minima.Usagesoma(costFunction,bounds,options=list(),init=NULL,...)bounds(min,max)##S3method for class somaplot(x,y=NULL,add=FALSE,...)ArgumentscostFunction A cost function which takes a numeric vector of parameters as itsfirst argument, and returns a numeric scalar representing the associated cost value.bounds A list with elements min and max,each a numeric vector giving the upper and lower bounds for each parameter,respectively.options A list of options for the SOMA algorithm itself,usually generated by functions like all2one.soma5 init An optional matrix giving the starting population’s positions in parameter space, one per column.If omitted,initialisation is random(as is usual for SOMA),butspecifying a starting state can be helpful when running the algorithm in stagesor investigating the consistency of solutions....Additional parameters to costFunction(for soma)or the default plotting method (for plot.soma).min,max Vectors of minimum and maximum bound values for each parameter to the costFunction.x An object of class"soma".y Ignored.add If TRUE,add to an existing plot canvas.ValueA list of class"soma",containing the following elements.leader The index of the“leader”,the individual in the population with the lowest cost.population A matrix whose columns give the parameter values for each individual in the popula-tion at convergence.cost A vector giving the cost function values for each individual at convergence.history A vector giving the cost of the leader for each migration during the optimisation.This should be nonincreasing.migrations The number of migrations completed.evaluations The number of times the costFunction was evaluated.A plot method is available for this class,which shows the history of leader cost values during theoptimisation.Author(s)R implementation by Jon Clayden<****************>.ReferencesI.Zelinka(2004).SOMA-self-organizing migrating algorithm.In G.C.Onwubolu&B.V.Babu,eds,New optimization techniques in engineering.V olume141of“Studies in Fuzziness and Soft Computing”,pp.167-217.Springer.See Alsosoma.options for setting options.optim implements other general-purpose optimisation methods.6somaExamples#Rastrigin s function,which contains many local minimarastrigin<-function(x)10*length(x)+sum(x^2-10*cos(2*pi*x))#Find the global minimum over the range-5to5in each parameterx<-soma(rastrigin,bounds(c(-5,-5),c(5,5)))#Find the location of the leader-should be near the true minimum of c(0,0)print(x$population[,x$leader])#Plot the cost history of the leadersplot(x)Indexall2one,2,4bounds(soma),4optim,5pareto(all2one),2plot.soma(soma),4soma,4soma.options,5soma.options(all2one),2t3a(all2one),27。
重点推介 Ocean World 2019lhe Nature Conservancy6。
0+ scientists •*<T 报告人:单良大自然保护协会(TNC)中国市场传播部总监—TNC 的做法1,400preserves man aged|自然保护协会(TNC, The NatureConservancy )成立于1951年,是国丿、际上最大的非营利性的自然环境保护组织之一。
一直致力于在全球保护具有重要生态价值的陆地和水域,维护自然环境、提升人类福 祉。
TNC 以科学为基础,研发创新实际方案,解决地球最严峻的挑战,维护自然环境,提升人 类福祉。
我们以全球视角来解决气候变化问题, 保护土地、河流及海洋,帮助推进城市可持续发展。
TNC 目前在全球72个国家及地区开展工作,管护着全球超过50万平方千米的1600多个自然 保护区,8000千米长的河流以及100多个海洋生态区。
TNC 衽中国1998年,TNC 受中国政府邀请进入中国,总部位于北京。
在陆地、淡水、气候变化、海 洋、城市等多个领域开展保护项目,并取得卓越成效。
2009年,TNC 大中华理事会成立,包括马云、马化腾、牛根生、吴鹰等一批中国知名企42工具和方法,为了减少在进行保护工作决策时的不确定性,TNC还会经常使用这一框架下的两个方法生态区评估(Eco-regional Assessment, ERA)和保护行动规划(ConservationAction Plan,CAP)o非对抗原则在坚持进行科学保护的同时,TNC遵循“非对业家的加入,极大地推动了TNC在中国的生态保护工作进程。
TNC的便命9保护代表地球生物多样性的动物、植物和自然群落赖以生存的陆地和水域,来实现对这些动物、植物和自然群落的保护。
TNC的保护方法陆地、气候变化、海洋、淡水以及保护地是TNC最为关注的五个方面.多方协作,坚持以科学为基础的保护方法和标准化分析方法,是TNC进行所有保护工作的前提。
金融安全文献综述金融安全是金融经济学研究的基本问题 ,在经济全球化加速发展的今天,金融安全在国家经济安全中的地位和作用日益加强。
特别是自1997年7月泰国发生严重的金融危机以来, 金融安全成为世界上几乎所有国家尤其是新兴国家此后一段时期的一个研究重点。
一、金融安全的概念从国外的研究来看,金融安全问题的提出由来已久,早期马克思就曾对金融体系的内在不稳定做出过深刻论述,马克思认为资本主义市场经济存在着内生的不稳定性,而且造成货币与金融不稳定的最终根源隐于资本积累过程之中。
他指出经济的不稳定与货币金融的风险紧密相关,而关于经济周期与货币金融风险的分析可以分为两个层次:一是在简单商品流通条件下,经济不稳定的可能性产生于货币的社会功能,二是在资本主义市场经济中,资本积累的周期性运动会不可避免地导致金融风险的累积甚至爆发金融危机①。
20世纪初凡勃伦(Thorstein B Veblen)(1904)②也提出了“金融体系不稳定”假说,他认为资本主义的经济发展最终导致社会资本所有者缺位,结果其本身内在地存在周期性动荡力量,这些力量主要集中在银行体系中。
欧文-费雪(Irving Fisher)又进一步发展了凡勃伦等的假说,提出了“债务-通货膨胀理论”,认为银行体系的脆弱性与宏观经济周期密切相关,尤其是与债务的清偿紧密相关,通货膨胀是由于过度负债引起的金融事件。
20世纪60年代后期和70年代,美国与日本的一些学者开始关注国家经济安全问题。
他们通常都将金融安全放在国家安全战略和国家经济安全的系统中来探讨,认为国家经济安全并不局限于金融领域,但金融无疑是影响国家经济安全的最重要方面,也就是说,金融安全并不等于经济安全,但金融安全是经济安全的必要条件,经济安全的国家一定拥有安全的金融体系,金融不安全意味着经济也不安全,因而金融安全直接决定着国家的经济安全。
①《马克思恩格斯全集》,中文1版,第26卷II,562-573页,北京,人民出版社,1973.②Thorstein B Veblen,《The Theory of Business Enterprise (l904)》, New Brunswick, Transaction Publishers, 1978。
Protein Engineering vol.14no.5pp.329–335,2001Solvent entropy-driven searching for protein modeling examined and tested in simplified modelsRainer Ko¨nig and Thomas Dandekar 1European Molecular Biology Laboratory,Meyerhofstr.1,Postfach 102209,D-69012Heidelberg,Germany1Towhom correspondence should be addressed.E-mail:dandekar@embl-heidelberg.deSolvent entropy is a force to consider in protein folding and protein design but is difficult to model.It is investigated here in the context of the hp model:Two types of residues,hydrophobic and hydrophilic,are modeled on a lattice.Nine chains and two-and three-dimensional simulations are compared.We show that considering solvent entropy alone,efficient folding of lattice chains (identification of the native fold)can be achieved by an entropy-driven simulation on its own.Moreover,in a detailed comparison over a wide range of parameters,entropy-guided searching outperforms an energy-driven search in the model.The combination of energy-and entropy-driven search yields the most efficient searching.It is compared in detail with the above results,indicating also how this solvent shell model may advantageously be implemented in more com-plex protein modeling simulations.Keywords :hp model/lattice simulation/local order/search optimization/search strategyIntroductionSolvent entropy has an impact on protein folding and protein interactions as well as protein design.However,the enumera-tion of the different microstates can become difficult.Imple-mentation of the solvent and especially its entropy is not often found in the literature (Shortle et al.,1992;Warwicker,1997).Exact calculations on entropy are difficult in real systems.Calculating the number of solvent microstates stresses a different perspective of protein folding and protein stability:The global minimum no longer appears as one rare state among a large number of alternative conformations,but as the protein conformation with the highest number of microstate representations of the solvent.A computationally unintensive way is to approximate the impact of the solvent by mean field calculations (Hsiang-Ai and Karplus,1988;Cramer and Truhlar,1992;Fraternali and van-Gunsteren,1996).The mean field calculations neglect the effect of locally ordered structures and can underestimate solvent–protein interactions (Smith and van-Gunsteren,1994).Simulations taking each water molecule of the protein surrounding shell into account (Levitt and Sharon,1988;Braxenthaler et al.,1997;Warwicker,1997;Scheraga and Hao,1999)are computationally intensive and usually are only done for simulation times of a few nanoseconds.We present here a promising implementation of solvent entropy in the context of the hp model.As a search method we took an application of the common Monte Carlo (MC)method (Metropolis et al.,1953,Kirkpatrick et al.,1983;©Oxford University Press329Aarts and Korst,1989),implemented in a standard way for this hp model [see Unger and Moult for further details of this standard implementation (Unger and Moult,1993)].The protein chain is modeled on a lattice and only two types of residues are considered,hydrophobic (h)and hydrophilic (p)(Lau and Dill,1989).We further take the local order of the solvent shell around the protein into account.Two-and three-dimensional models are compared.Long-range interactions in the rest of the solvent (e.g.long-range order brought about by solvating ions or exposed polar groups)are not considered in this simplified model.We show that efficient folding of lattice chains (identification of the native fold)can be achieved by an entropy-driven simulation completely on its own.Furthermore,we show in a detailed comparison in our model that entropy-guided searching can outperform an energy-driven search.A combination of energy-and entropy-driven searching yields the most efficient searching and is compared in detail with the above results.This illustrates,in addition,how our simple solvent shell model may advantageously be imple-mented in more complex simulations.Materials and methodsTwo-dimensional hp modelAll simulations used the hp model (Lau and Dill,1989)and modeled the protein chain on a lattice.Only two types of residues are considered,hydrophobic (H;filled squares)and hydrophilic (P;open squares).The model meets the basic characteristics of real proteins,e.g.similar distributions of secondary structure (Lau and Dill,1990).The protein is represented as a chain on a two-dimensional square lattice (Figure 1).At each point the chain can turn 90°left or right or continue ahead.The following chains with 12,18,24,33and 48residues,respectively,were tested:(1)P H P P H P P H P P H P(2)H H H P H P H P P H P H P P H P P H(3)P H P P H H P P P P H H P P P P H H P P P P H H (4)P H H P P H H P P P P P H H H H H H H P P H H P P P P H H P P H P(5)PP H P P H H P P H H P P P P P H H H H H H H H H HPP P P P P H H P P H H P P H P P H H H H HThese chains yield well-folded compact structures and their global energy minima were known a priori as –4,–9,–8,–14and –23,respectively.Three-dimensional hp modelIn the three-dimensional model at each point the chain can turn left,right,straight,up and down;otherwise the construction of the chain is similar to the two-dimensional model.Four chains with 12,14,22and 28residues and different topologies were tested (Figure 2a):R.Ko¨nig andT.DandekarFig.1.Three chains(18-mer,24-mer,33-mer)for the two-dimensional model,shown in their optimal folded lowest energy state.Their energies (direct hydrophobic contacts)are–9,–8and–14.Fig.2.(a)Chain3of the three-dimensional model,surrounded by ordered (gray spheres)and less ordered(black spheres)water.(b)Two structures of a12-mer on the two-dimensional lattice.L stands for an ensemble of less ordered water,O for a(higher)ordered ensemble.The energy implementation alone(algorithm A)would consider both stuctures the same (E leftϭE right).The objective function of B and C considers the amount of ordered water ensembles(O)and favors the left,globule like,native structure(N l eftϭ3ϽN rightϭ4,so F leftϾF right(for further details,seeMaterials and methods and Results).(1)H H P H P H P H P H P H(2)P H H H H P P P P H H H H P(3)H P P H P P H P P H P P H P P H P P H P P H(4)H P P H P P P P H P P H P P P P H P P H P P P P HP P HTheir energy minima were also known a priori as–5,–6,–4 and–12,respectively.Energy functionThe energy function∆E was kept simplistic.It adds–1for each direct(non-diagonal)lattice contact between two non-consecutive hydrophobic amino acids.‘Clashes’(i.e.two residues in the same place in the lattice)are not allowed. Trials with clashes had to be newly created. Implementation of entropyTo study entropy effects,lattice spaces adjacent to the protein chain were modeled to befilled by solvent in the following (small)water ensembles(Figure2a).Long-range interactions 330in the rest of the solvent(e.g.long-range order brought about by solvating ions or exposed polar groups)were not considered in this simple model.Small water ensembles with two different properties surrounded the model protein:ordered and less ordered.The ordered water ensembles are adjacent to hydro-phobic residues or the solvent(i.e.other water ensembles). The less ordered(with high entropy)exist if no hydrophobic residue is adjacent to them.An O-block(ordered)on the lattice is asigned to the ensemble of ordered water molecules,an L-block to a less ordered ensemble(Figure2b).The number of unordered water ensembles,N i,was counted.It has beenshown experimentally that hydrophobic molecules reduce theentropy of the surrounding(aqueous)solvent(Schulz andSchirmer,1996).The solvent entropy difference,S,betweenone protein chain conformation,N1and a tested next one,N2,during the simulation was set to be proportional to thedifference in the number of unordered adjacent lattice spacescounted(entropy is additive;we assigned1unordered blockϭ1high-entropy unitϭ1/f,with fϽ1;whereas1orderedblockϭ1low-entropy unitϭ1).With the order parameter f(see below)the probability for the new configuration to bechosen is p~e(TS/T)ϭf(N1–N2).This implementation considers the entropy of the solvent according to Boltzmann statistics.The derivation of this can be done by simple algebra(see http://www.embl-heidelberg.de/~dandekar/entropy.html).In contrast,the simple energy function from above does not differentiatebetween ordered and less ordered ensembles(Figure2b).Instead,it is derived(–1for any hydrophobic contact),if thesum(‘hydrogen bonds’in our model)of the connections of(water ensembles–water ensembles)and(water ensembles–hydrophilic residues)is counted and compared between twoconformations.The order parameter f allowed the testing of differententropy weights during simulations,either alone or multi-plying the entropy term,f(N1–N2)),with the energy term,e(–∆E/T),yielding p~e–F/Tϭe(∆E–TS)/T to consider also the energy difference∆E between two chain conformations.The model allowed the examination of three implementations:A, energy effects(∆E;simplified in the context of the model; only hydrophobic interactions are considered or,alternatively, the effect of‘hydrogen bonds’);B,entropy(∆S,difference of ordered small water ensembles);and C,the combination of them(more realistic implementation,FϭE–TS).F denotes the Helmholtz free energy(corresponding also to the Gibbs free energy if changes in volume and pressure are neglected). The new chain conformation was accepted if a random number between zero and1/constant was smaller than e–F/T. Simulation stepsA Monte Carlo algorithm was used with the following steps[implemented as in Unger and Moult(Unger and Moult,1993)]:(1)Start from a random conformation.(2)From a conformation C1with energy E1and entropy S1asingle random change yields conformation C2.If C2is notclash-free a new conformation is created.(3)Otherwise,the algorithms A,B and C decide by differentcriteria on the acceptance of the new conformation C2.The variable‘energy evaluations’is increased by one.This variable is taken as the time-counting variable sincethe energy evaluation is often the most time-demandingfunction in more complex protein folding simulations.TheMC implementation was,as in common classical statisticalSolvent entropy-driven searching for protein modelingmechanics,the probability of the system being in state i was p i ϭexp[(E –TS )/T ],where T is the arti ficial temperature,an optimized parameter (details are given below).The Boltzmann constant k was set to 1for simplicity.T was decreased for algorithms A and C as in the common simulated annealing method (Kirkpatrick et al.,1983).(4)Check if the stop criterion is met.Go back to step 2if thecounter for energy evaluations is Ͻ100000.The value 100000was taken as the limit to keep the runs fast (a few seconds for the smallest chain,30s for the longest)and results were collected from 100runs for each different parameter set.Moreover,this was suf ficient to allow identi fication of the global minimum for most of the chains.Two implementations were tested and compared for each algorithm.Implementation 2models and examines a more detailed partition function as a decision rule to change from conformation C 1to C 2(see Appendix for details),but this may prevent the algorithm from exploring new areas in search space when passing along flat surfaces.A decision constant (see Results)was introduced potentially to balance this effect and compare both implementations for a range of different values of the constant (including constant ϭ1,no constant introduced;the probability to accept C 2could maximally become 1,corresponding to accepting with certainty a change to conformation C 2).Implementation of algorithms A,B and C Algorithm A (energy)Accept C 2ifrnd Ͻconstant ϫe –∆E /T (standard,implementation 1)rnd Ͻconstant ϫ1/(1ϩe–∆E /T )(implementation 2)where rnd is a random number between 0and 1and T is anarti ficial temperature that gradually decreased (cooled)during the run to achieve convergence.T started with T 0ϭ2.00and was decreased after every 100energy evaluations with the cooling rate c :T ϭT i ϭT i –1c(c Ͻ1)c was optimized as a parameter (see Results).Algorithm B (entropy)Accept C 2ifrnd Ͻconstant ϫf (N 1–N 2)(standard,implementation 1)rnd Ͻconstant ϫ1/[1ϩf (N 2–N 1)](implementation 2)f Ͻ1was the order parameter and optimized (see Results).Note that the entropy of the protein conformations need not be considered as the algorithm itself samples over a representative ensemble of equally weighted protein micro-states.Long-range interactions in the rest of the solvent (e.g.long-range order brought about by solvating ions or exposed polar groups)were not considered in this simple model.Furthermore,calculation of the term is easily par-ison with the algorithm A above shows that the calculation is also not more computationally expensive.Algorithm C (energy and entropy)Algorithm C calculated F ϭE –TS (the free enthalpy F ,equal to the energy E minus the product of temperature T and entropy S )before the decision:rnd Ͻconstant ϫf (N 1–N 2)e –∆E /T (standard,implementation 1)rnd Ͻconstant ϫ1/[1ϩf (N 2–N 1)e –∆E /T ](implementation 2)331T and f were taken as in algorithms A and B,respectively.Note that in the comparisons,the optimal folded states (maximally packed,minimum energy but also highest solvent shell entropy)are always the same and known beforehand (cf.Figure 1).Only their energy values are given in the tables for comparison.However,in searching for these states in algorithms B and C their entropy is also considered,comparing alternative conformations.The objective function of the three different algorithms is different and favors different suboptimal folds during searching;the potential surface separating and leading to the optimal folded states is different for the three algorithms.ResultsIn our model the protein is surrounded by water composed of clusters with two different properties,ordered and less ordered,to calculate solvent shell entropy.The ordered water clusters are adjacent to hydrophobic residues and thus engage in hydrogen bonds with hydrophilic residues or the solvent.The less ordered clusters exist if no hydrophobic residue is adjacent to them.For our model no further knowledge about side chain properties is needed.This approach may be compared to an algorithm that favors a reduced hydrophobic surface of the protein.However,the latter would be a mean field approximation of the whole surface,whereas our model takes local structures,the solvent microstates,into account.The search ef ficiency of this entropy implementation in protein folding was compared with that of energy-driven searching.Different chains on both a two-and a three-dimensional lattice were tested to avoid effects depending on the lattice topography chosen.Three search strategies were compared in Monte Carlo (Metropolis et al.,1953;Kirkpatrick et al.,1983;Unger and Moult,1993)simulations:(A)Searching for the energy minimum.The number ofhydrogen bonds gave the energy for each conformation (Table I).(B)Searching for the conformation allowing the highestamount of microstates for the solvent shell (entropy search;Table II):at each step the new and the old conformation were compared.The conformation with the higher entropy (more microstate representations)of the solvent is taken for the next step.(C)A combination of energy and entropy (Table III).Boththe number of hydrogen bonds and the number of conformations were taken into account for search selection.All algorithms were run 100times with each parameter set (with different random seeds).The comparison was done with five chains in the two-dimensional model and four chains in the three-dimensional model.Except for the two longest chains in the two-dimensional model (33-mer and 48-mer),the global minimum was found quite reliable by all algorithms.If the global minimum was not found by each run,our comparisons indicate how often the minimum was found per 100runs and the standard deviation of this figure (numbers in parentheses).If the global minimum was found reliably,the number of conformation trials to find it was computed.A difference of Ͼ20%in the number of trials required was considered a signi ficant difference between the search strategies examined.Two different implementations (see Materials and methods)to evaluate the probability,including different values of theR.Ko ¨nig and T.DandekarT a b l e I .I d e n t i fic a t i o n o f t h e g l o b a l m i n i m u m i n 100t r i a l s (‘f o u n d ’)i s c o m p a r e d f o r t w o i m p l e m e n t a t i o n s (i m p 1a n d i m p 2)a n d d i f f e r e n t v a l u e s f o r t h e d e c i s i o n c o n s t a n t c t o a c c e p t a n e w c o n f o r m a t i o n :r e s u l t s c o n s i d e r i n g e n e r g y o n l y (a l g o r i t h m A )C h a i n a[E ]c ϭ1c ϭ2c Ͼ2i m p 1i m p 2i m p 1i m p 2i m p 1i m p 2F o u n dS t e p s aF o u n d S t e p s F o u n d S t e p s F o u n d S t e p s F o u n d S t e p s F o u n d S t e p s (d e v )b (d e v )(d e v )(d e v )(d e v )(d e v )[E ]c [E ][E ][E ][E ][E ]2D ,c h a i n 1[–4]54b(5)b53(5)52(5)50(5)53(5)47(5)2D ,c h a i n 2[–9]4(2)4(2)7(3)6(2)9(3)3(2)2D ,c h a i n 3[–8]11(3)5(2)5(2)5(2)10(3)8(3)2D ,c h a i n 4[–14]0c[–13,6ϫ]c0[–13,2ϫ]0[–13,6ϫ]0[–13,2ϫ]1(1)0[–13,2ϫ]2D ,c h a i n 5[–23]0[–20,1ϫ]0[–20,1ϫ]0[–19,3ϫ]0[–20,1ϫ]0[–20,1ϫ]0[–20,1ϫ]3D ,c h a i n 1[–5]3(2)0(2)4(2)2(1)4(2)5(2)3D ,c h a i n 2[–6]95(2)91(3)93(3)97(2)92(3)94(3)3D ,c h a i n 3[–4]100a28907a1002353698(1)99(1)98(1)99(1)3D ,c h a i n 4[–12]2(1)1(1)3(2)2(1)2(1)3(2)a N i n ec h a i n s w i t h t w o (2D )o r t h r e e (3D )d i me n s i o n s w e r e t e s t e d .T h e e n e r g y of t h e r e s p e c t i v eg l o b a l m i n i m u m i s g i v e n i n s q u a r e b r a c k e t s [E ].I f e v e r y t i m e th e g l o b a l mi n i m u m w a s f o u n d t h e a v e r a g e n u m b e r o f e n e r g y e v a l u a t i o n s (s t e p s )t o fin d i t i s g i v e n .b V a l u e s w i t h s t a n d a r d d e v i a t i o n s (d e v )a r e g i v e n i n p a r e n t h e s e s i f t h e g l o b a l m i n i m u m w a s n o t a l w a y s f o u n d i n 100t r i a l s .c F o r l o n g e r p r o t e i n c h a i n s (2D ,c h a i n s 4a n d 5)t h e 100000s i m u l a t i o n s t e p s u s e d i n t h i s s e a r c h s t r a t e g y c o m p a r i s o n w e r e o n a v e r a g e t o o f e w t o l o c a t e t h e g l o b a l m i n i m u m ;i n s t e a d t h e l o w e s t e n e r g y m i n i m u m f o u n d a n d h o w o f t e n i t w a s f o u n d i n 100t r i a l s i s g i v e n i n s q u a r e b r a c k e t s .332T a b l e I I .I d e n t i fic a t i o n o f t h e g l o b a l m i n i m u m i n 100t r i a l s (‘f o u n d ’)i s c o m p a r e d f o r t w o i m p l e m e n t a t i o n s (i m p 1a n d i m p 2)a n d d i f f e r e n t v a l u e s f o r t h e d e c i s i o n c o n s t a n t c t o a c c e p t a n e w c o n f o r m a t i o n :r e s u l t s c o n s i d e r i n g e n t r o p y o n l y (a l g o r i t h m B )C h a i n a[E ]c ϭ1c ϭ2c Ͼ2i m p 1i m p 2i m p 1i m p 2i m p 1i m p 2F o u n dS t e p s a F o u n d S t e p s F o u n dS t e p s F o u n d S t e p s F o u n d S t e p s F o u n d S t e p s (d e v )b(d e v )(d e v )(d e v )(d e v )(d e v )[E ]c [E ][E ][E ][E ][E ]2D ,c h a i n 1[–4]100a 13978a 1001679010080581008852100374810042282D ,c h a i n 2[–9]14b(4)b12(3)13(3)13(3)33(5)32(5)2D ,c h a i n 3[–8]4(2)10(3)11(3)10(3)25(4)26(4)2D ,c h a i n 4[–14]0c[–12,6ϫ]c0[–13,1ϫ]0[–12,16ϫ]0[–13,1ϫ]1(1)0[–13,3ϫ]2D ,c h a i n 5[–23]0[–20,1ϫ]0[–19,1ϫ]0[–20,1ϫ]0[–20,1ϫ]0[–21,1ϫ]0[–20,1ϫ]3D ,c h a i n 1[–5]2(1)1(1)1(1)2(1)2(1)3(2)3D ,c h a i n 2[–6]1008502100101611001380610019192100925510098793D ,c h a i n 3[–4]1005383100658210058981005872100596110052093D ,c h a i n 4[–12]2(1)1(1)1(1)0(1)4(2)3(2)a –c S e eT a b l e I .Solvent entropy-driven searching for protein modelingT a b l e I I I .I d e n t i fic a t i o n o f t h e g l o b a l m i n i m u m i n 100t r i a l s (‘f o u n d ’)i s c o m p a r e d f o r t w o i m p l e m e n t a t i o n s (i m p 1a n d i m p 2)a n d d i f f e r e n t v a l u e s f o r t h e d e c i s i o n c o n s t a n t c t o a c c e p t a n e w c o n f o r m a t i o n :r e s u l t s c o m b i n i n g e n t r o p y a n d e n e r g y (a l g o r i t h m C )C h a i n a[E ]c ϭ1c ϭ2c Ͼ2i m p 1i m p 2i m p 1i m p 2i m p 1i m p 2F o u n dS t e p s a F o u n dS t e p s F o u n dS t e p s F o u n d S t e p s F o u n dS t e p s F o u n dS t e p s (d e v )b(d e v )(d e v )(d e v )(d e v )(d e v )[E ]c[E ][E ][E ][E ][E ]2D ,c h a i n 1[–4]100a10686a1001186110095531008894100365910036862D ,c h a i n 2[–9]33b(5)b27(4)44(5)40(5)51(5)47(5)2D ,c h a i n 3[–8]22(4)16(4)34(5)24(4)50(5)45(5)2D ,c h a i n 4[–14]0c[–13,4ϫ]c0[–13,7ϫ]1(1)1(1)1(1)1(1)2D ,c h a i n 5[–23]0[–20,3ϫ]0[–20,1ϫ]0[–22,1ϫ]0[–21,1ϫ]0[–22,1ϫ]0[–21,2ϫ]3D ,c h a i n 1[–5]9(3)9(3)6(2)7(3)7(3)4(2)3D ,c h a i n 2[–6]1006428100707410066601005221100740010076423D ,c h a i n 3[–4]1003223100383710040661003070100363810039973D ,c h a i n 4[–12]6(2)5(2)13(3)5(2)4(2)4(2)a –c S e eT a b l e I .333Fig.3.Probability of accepting a new conformation C 2.The (standard)implementation 1and implementation 2are compared.(A )The probability curve of accepting C 2for implementation 2.(B )Probability curve for the (standard)implementation 1.It can be seen that in (A)even for F Ͻ0there is still the possibility of not accepting the step,whereas in (B)every new step with F Ͻ0is accepted.decision constant to accept a new conformation in the next step of the simulation,were compared in each strategy.Additionally,we compared different parameter values for the cooling rate c in A and C and for the entropy parameter f in B and C.We tested a broad range,for f between 0.9and 0.001(0.9,0.7,0.5,0.3,0.1,0.05,0.01,0.001),for c between 0.999999and 0.9(0.999999,0.99999,0.9999,0.999,0.99,0.9)and for the decision constant the values 1,2,4,8,16and 32.f ,c and decision constant were all optimized for the results given.The optimal range for f was 0.1to 0.7;f ϭ0.3produced the best results over all conditions.For c the optimal range was 0.99–0.99999with c ϭ0.99yielding the best results comparing all conditions.A decision constant Ͼ2was advanta-geous and constant ϭ4produced the best results.The search strategy on solvent shell entropy alone is effective in identifying the global minimum.It is more effective in searching than the standard Monte Carlo energy minimization procedure with the simpli fied energy function in more than 60%of the parameter conditions investigated (33of 54cases;including the longer chains).Sixteen cases showed no signi ficant difference,five cases were less ef ficient,including middle sized chain 3in two dimensions,implementation 1,constant ϭ1and chain 4in three dimensions,implementation 2,constant ϭ2.The combination of both search strategies is easily achieved (algorithm C).This yields a further signi ficant improvement for all tested chains including the longer ones in both lattices.It outperformed the energy-driven search (algorithm A)in 45of 54cases.In two of the remaining nine cases it showed a clear positive trend.It was also clearly and signi ficantly superior (but here only in 40of 54cases)than entropy alone (algorithm B);in 10cases there was no signi ficant difference.Implementation 2(see Materials and methods;Appendix for details)was not superior,but slightly less ef ficient than the standard implementation.Exactly 100000steps were compared for each strategy and each chain to allow a fair comparison of all search strategies,comparing batches of 100runs for each condition;100000steps were taken to collect a large amount of data for the algorithm comparison in a convenient time so that hundreds of runs could be compared and average statistics obtained.On average,this value was not suf ficient for the 48-mer on the two-dimensional lattice to find the global minimum.For the 33-mer it was found about once (out of 100trials)in the better strategies.Therefore,the energy of the best local minimum found was compared if the global minimum was not identi fied.It was not our aim to identify the global minimum under each condition but rather to compare the different algorithms underR.Ko¨nig and T.Dandekarsimple(global minimum always found)and demanding condi-tions(only the best strategies succeed sometimes).Note that a gain of one step lower in the energy of a local minimum is a significant search success as the number of local minima increases exponentially with higher energy(Lau and Dill, 1990).Solvent shell-guided searching was also here an improvement compared with the simple energy-guided search strategy and algorithm C also performed best in the comparison for longer chains.It found a local optimum with energy–22 for the48-mer.It also found the global optimum for the 33-mer four times(Tables I–III).DiscussionEntropy is an important concept in protein folding(Scheraga, 1998)including advances from recent work(e.g.Warwicker, 1997;Scheraga and Hao,1999).In general,the implementation of entropy is complex.It includes the correct enumeration of microstates in microcanonical ensembles and considering that protein entropy decreases while solvent shell entropy increases during protein folding.We have shown in a well established, simple model for protein folding(hp model)and for different types of lattices that consideration of the entropy of the adjacent water shell is sufficient to locate the correct fold for these lattice chains.The target function(high entropy,low number of hydrophobic residues on the surface)differs from the energy function(again focusing on hydrophobicity)with better access to the native fold in the overall comparison.As a result,the search speed of the entropy implementation outperformed an energy-driven search.Several factors are potentially involved in this:Considering the entropic forces of the solvent shell helps to enhance globular packing (cf.Schulz and Schirmer,1996).Some of the local minima and traps are more smoothed out as conformations with identical energy are distinguished by their solvent shell entropy differences(cf.Figure2b).Otherwise no further complications are introduced in this simplified model,in particular regarding the energy term.We did not observe trapping in new entropy-driven minima with HP contacts,probably as they can be more easily left than pure energy minima as both entropy forces and energy function may open up potentially favorable changes for such conformations.Considering the microstates focuses on a different perspect-ive of the folding problem.The preferred state of the protein chain is not one rare and single conformation but instead in the context of this model(and in the entropy aspect more realistic than in some other simple protein models)the global minimum of energy displays the highest number of micro-states.Furthermore,breathing(rearrangement of microstate ensembles)can be seen and investigated in such models(Ko¨nig and Dandekar,1999).This allows for the investigation of entropy effects as well as partial unfolding of the protein chain after the global minimum has been reached in these simulations. The solvent shell entropy model presented here achieves efficient folding for a number of simplified protein chains.In the context of the model it was not necessary to include long-range forces to achieve this.This will have to be tested further, in particular further refinement of the structures obtained by inclusion of such forces.The starting information required for any of the search strategies A,B and C was the same,the protein sequence was sufficient.An exhaustive enumeration for some of the smaller protein chains modeled is possible,but here we wanted to compare the speed and efficiency of the different search 334strategies.The hydrophobic effect was compared and consid-ered both by its entropic and energetic consequences.This focus was chosen as hydrophobic interactions are principal forces in protein folding and to compare both strategies with their respective effects on search success.The combined strategy where energy and entropy are both considered is easily achieved and can accommodate also more complex energy functions than the simplistic one chosen for testing.It identifies the native fold best.It yielded a significantly better search effectiveness on both lattices.Additionally,we com-pared the algorithms with a standard(as in common MC methods)and an alternative implementation(partition function motivated)of the decision constant and showed implementa-tion-independent,similar results for both implementations. Furthermore,both lattices tested(two-and three-dimensional) showed similar success as a control against effects from lattice choices.The use of a decision constant further improved search success.The search strategies compared fulfill ergodicity over suffi-cient long observation times and to the extent that the search space is non-reducible and contiguous,any conformation can be reached with some probability from any other conformation and it is aperiodic.Detailed balance is fulfilled for the three search strategies at least so far as reversibility for any conformational change effected is possible during the simulation.Entropy maximization was implemented in the model according to the natural behavior of proteins(Schulz and Schirmer,1996)and,in fact,entropy maximization occurs during time for any molecular interaction(more details on entropy maximization in protein–solvent systems are given on our Web page).Solvent shell optimization can certainly be considered to have an important impact on protein folding.In our simulations this aspect of folding was shown to be sufficient to localize the optimal protein structure of small model proteins.It should be noted that also other well known factors involved in protein folding such as hydrophobic forces,hydrogen bonds and cooperativity(Kolinski et al.,1999)are in part determined by solvent shell entropic forces.Nevertheless,exact experimental quantification of solvent shell effects remains a challenge.Our simplistic model suggests that at present their contribution to protein folding may perhaps be underestimated.Shortle et al.showed that consideration of entropic forces is helpful in predicting and understanding the effects of mutations(Shortle et al.,1992).Also antibody and other protein–protein interaction models are more precise if entropic effects are included.The inclusion of a simplified solvent shell entropy algorithm as given and compared in detail here improves the search success in protein folding simulations and will be taken to improve more complex folding simulations such as more extended,grid free models as a next step. AcknowledgementsWe thank Warren the,III for stylistic corrections.Part of the research was funded by Graduiertenkolleg(University of Heidelberg)and SFB544/B2.ReferencesAarts,E.and Korst,J.(1989)Simulated Annealing and Boltzmann Machines. Wiley,New York.Braxenthaler,M.,Unger,R.,Auerbach,D.,Given,J.A.and Moult,J.(1997) Proteins,29,417–425.Cramer,C.J.and Truhlar,D.G.(1992)Science,256,213–217.Fraternali,F.and van-Gunsteren,W.F.(1996)J.Mol.Biol.,256,939–948.。
The Impact of Globalization on Our World Globalization has been a buzzword for the past few decades and has significantly impacted the world. It refers to the process of integration and interconnectedness among people, businesses, and governments across the globe. The effects of globalization are far-reaching and have been both positive and negative. This essay aims to explore the impact ofglobalization on our world from multiple perspectives.To begin with, globalization has led to increased economic growth and development. The integration of economies has facilitated the flow of goods, services, and capital across borders, resulting in increased trade and investment. This has created employment opportunities, boosted productivity, and improved living standards for many people. For instance, countries like China and India have experienced significant economic growth due to globalization, lifting millions of people out of poverty.However, the benefits of globalization have not been equally distributed, and many people have been left behind. The increasing competition from cheap imports has led to the closure of many domestic industries, resulting in job losses and economic hardship for many workers. Moreover, globalization has led to the concentration of wealth in the hands of a few, exacerbating income inequality. This has led to social unrest, political instability, and the rise of populist movements in many countries.Furthermore, globalization has had a significant impact on the environment. The increased economic activity has resulted in theexploitation of natural resources, deforestation, and pollution. The emission of greenhouse gases from industries and transportation has contributed to climate change, which poses a significant threat to the planet. The negative impact of globalization on the environment has led to calls for sustainable development and the adoption of green technologies.Another significant impact of globalization is the cultural exchange that has taken place. The integration of cultures has led to the spread of ideas, knowledge, and values across borders. This has resulted in the emergence of a global culture, where people share common interests and aspirations. Moreover, the exchange of cultural ideas has led to the development of new forms of art, music, and literature, enriching theworld's cultural heritage.However, the cultural exchange has also led to the erosion oftraditional cultures and values. The increasing influence of Western culture, in particular, has led to the homogenization of cultures,resulting in the loss of diversity. This has led to cultural conflicts and tensions between different groups, as people struggle to preserve their cultural identity.In conclusion, globalization has had a significant impact on our world, both positive and negative. It has facilitated economic growth and development, cultural exchange, and the spread of ideas and knowledge. However, it has also led to income inequality, environmental degradation, and the erosion of traditional cultures and values. To maximize thebenefits of globalization while minimizing its negative impact, there is a need for policies that promote sustainable development, social justice, and cultural diversity.。
全球化链条定律全球化链条定律全球化链条定律 (Law of Global Chain)什么是全球化链条定律一部科幻小说中曾经有这样的故事:××年后,人类开始移民月球。
开拓者们携带着先进设备和必需的工具登陆月球,还带来了各种植物和牲畜甚至小小的蚂蚁。
几年过去了,这个离地球38万公里之遥的“生物圈”内,植物殖效率低下,动物吃不饱,连带人类也开始饿肚子。
最后查明的原因竟然是:当初忘记带蜜蜂了。
“全球化链条定律”是跨国企业一直遵循的定律,即:“follow your customers(追随客户)”和他们的“global key accounts(全球协议伙伴)”。
不可避免地,他们要“一串一串”地梯队性进人中国市场。
在商业价值链上互为客户,让跨国公司们形成了竖看一条线,横看一张网的类似于他们本土的商业环境。
他们知道,如果每一个环节都有他们熟悉和适应的伙伴,他们将如鱼得水”。
[编辑]一家美国公司的全球化链条管理定律A L续安慰剂效应卢维斯定理阿尔巴德定理蓝斯登定律暗箱模式蓝斯登原则阿尔布莱特法则垃圾桶理论阿姆斯特朗法则蓝柏格定理阿什法则雷鲍夫法则艾奇布恩定理懒蚂蚁效应阿罗的不可能定理牢骚效应艾德华定理洛克忠告艾科卡用人法则拉图尔定律阿伦森效应鲁尼恩定律暗示效应拉锯效应安泰效应 M氨基酸组合效应木桶原理B 墨菲定律彼得原理蘑菇管理定律不值得定律马太效应贝尔效应名片效应保龄球效应米格—25效应布里特定理马蝇效应比伦定律末位淘汰法则柏林定律麦克莱兰定律巴菲特定律目标置换效应彼得斯定律梅考克法则白德巴定理摩斯科定理布利丹效应美即好效应波特定律马斯洛理论布利斯定理曼狄诺定律波特法则冒进现象布朗定律毛毛虫效应伯恩斯定律摩尔定律布利斯原则木桶歪论名人效应拜伦法则 N冰淇淋哲学鲶鱼效应比林定律南风法则邦尼人力定律尼伦伯格原则玻璃天花板效应凝聚效应巴纳姆效应纳尔逊原则半途效应希尔十七项成功原则贝尔纳效应鸟笼效应贝勃规律 O边际效应奥卡姆剃刀定律菠菜法则奥格威法则标签效应奥狄思法则杯子理论奥美原则弼马瘟效应欧弗斯托原则搬铁块试验 PC 螃蟹效应长尾理论帕累托法则刺猬法则帕金森定律长鞭效应皮格马利翁效应磁石法则破窗效应磁力法则皮尔斯定律蔡戈尼效应皮京顿定理从众效应皮尔·卡丹定理权威效应披头士法则蔡格尼克记忆效应攀比效应超限效应 Q全球化链条定律群体压力传染效应乔布斯法则参与定律犬獒效应成事定理青蛙法则拆屋效应乔治定理出丑效应秋尾法则D 强手法则多米诺骨牌效应齐加尼克效应达维多定律情绪效应倒金字塔管理法 R定位法则热炉法则大荣法则柔性管理法则杜利奥定理儒佛尔定律杜根定律洛克定律迪斯忠告人性定理灯塔效应|锐化效应达维多夫定律 S德尼摩定律三强鼎立法则杜嘉法则手表定律杜邦定律水坝式经营法登门槛效应首因效应叠补丁效应生态位法则等待效应德西效应狄伦多定律多看效应E 生鱼片理论250定律隧道视野效应恶魔效应F 500强企业经典管理法则弗洛斯特法则双木桶理论失真效应适才适所法则飞轮效应史坦普定理弗里施法则史华兹论断肥皂水效应舍恩定理凡勃伦效应史提尔定律法约尔原则斯坦纳定理费斯诺定理矢泽定律费斯法则“4+2”法则复壮效应思维的定势效应反馈效应社会惰化效应反木桶原理苏东坡效应弗洛伊德口误森林效应G 圣人理论声誉磁场光环效应 T格雷欣法则同仁法则身体语言古狄逊定理跳蚤效应沟通的位差效应特雷默定律管理沟通论踢猫效应沟通无限论托利得定理古德曼定理特里法则古德定律铁钉效应格利定理蜕皮效应孤峰原理汤水效应果子效应托伊论断过度理由效应投射效应过度学习效应同群效应功能固着心理头鱼理论感觉剥夺实验鸵鸟政策铁锹试验态度改变—糖果实验 W感情效应王永庆法则共生效应韦特莱法则箍桶理论威尔逊法则H 威尔德定理花盆效应翁格玛丽效应花生试验环境蓄势黑洞效应蝴蝶效应沃尔森法则霍桑效应沃尔顿法则华盛顿合作定律沃森定律猴子理论王安论断互惠关系定律韦尔奇原则杰亨利法则温德定律海潮效应无折扣法则横山法则沃特曼定律海恩法则武器效应猴子大象法则 X赫勒法则新木桶定律信心获得怀特定律斜坡球体定律哈默定律夏皮罗法则坏苹果法则西点军校的经典法则霍布森选择效应希望效应海因里希法则虚荣效应和谐定理 Y哈罗效应羊群效应理论J “100-1=0”定律酒与污水定律鱼缸理论激励倍增法则影响世界的100个定律金鱼缸效应蚁群效应吉格勒定理雅格布斯定理吉尔伯特定律印刻效应吉格定理 150定律吉德林法则 Yerkes-Dodson 法则竞争优势效应约翰逊效应监狱角色模拟实验野鸭精神棘轮效应邮票效应近因效应优先效应经验的逻辑推理效应优势富集效应金属切削试验延迟满足实验K 因果定律苛希纳定律异性心理快鱼法则雁阵效应异性效应酝酿效应拥有效应坎特法则 Z卡贝定律智猪博弈理论克里奇定理坠机理论柯维定理自来水哲学卡尔岑定理煮蛙效应刻板效应自吃幼崽效应L 自我参照效应雷尼尔效应自我选择效应零和博弈帐篷理论柯维定理最高气温效应卡尔岑定理詹森效应雷尼尔效应责任分散效应蟑螂效应座椅舒适感[编辑]对于这家美国公司而言,业务分拆、业务全球化和业务收入构成转型这三种转变在过去十几年中同时发生。
Reducing Carbon Emissions? The Relative Effectiveness of Different Types of Environmental Tax: The Case of New ZealandFrank G. Scrimgeour a , Les Oxley b,c and Koli Fatai aa Department of Economics, University of Waikato,b Department of Economics, University of Canterburyc Adjunct Professor, Department of Economics, University of Western Australia Abstract: Although countries experiences on environmental taxation differ, discussions in New Zealand coincide with the recent announcement by the government of a new carbon tax and a new energy tax to be introduced before the first phase of the Kyoto protocol. This paper provides preliminary simulation results that may help answer some policy-related questions including the relative micro- and macro-level impacts of energy taxes or carbon taxes and the likely impacts of the carbon taxes on the competitiveness of energy intensive industries.Keywords: Carbon tax, greenhouse gas emissions, CGE model1.IntroductionRecent debates in the literature (Parry, 1995, Parry et.al., 1999; Bovenberg and Goulder, 1996) on the likely economic and social impacts of alternative types of environmental taxation have highlighted the importance of issues including externalities, environmental concerns, double dividend, revenue neutrality and equity. The recent Kyoto Protocol (henceforth, KP), has further reinforced the importance of these issues. The issues also raise the need for empirical-based analysis to guide policy makers. Indeed, it is partly this need that has generated a vast amount of literature studying some of the environmental and economic issues relating to international agreements such as the Kyoto Protocol. A challenge for many of the studies is to find options that ‘maximize society welfare’ and at the same time reduce greenhouse gas emissions (henceforth, GHG) and its likely costs.In the New Zealand context, some of the recent discussion has focused on conceptual issues relating to for example, revenue recycling, double dividends. Furthermore, there has been discussion of the likely impact of the KP on the environment, economic performance (eg. economic growth, competitiveness, employment, investment etc.) and income distribution. To date the New Zealand government seems to favour a combination of energy taxes, fuel taxes and carbon taxes. Additionally, there is on-going discussion related to the alignment of the government’s favoured policies with their implementation and governance, and the economic and social instruments that may be used to pursue those policies. Introducing a carbon tax may result in welfare losses. Does this imply that a policy committed to their introduction means that the macro and micro-economic impacts of an energy tax or fuel tax are more acceptable to New Zealanders? Are all sectors in the New Zealand economy likely to bear, equally, the adjustment costs as New Zealand ratifies the KP? What is the likely impact on economic growth, employment, investment and other macro-economic variables? What are the likely impacts on firms? This paper attempts to answer some of these questions using a CGE model of the New Zealand economy. The model is specifically designed to focus on the energy sector and can simulate the effects of, in particular, three types of GHG taxes: an energy tax on all fossil fuels, a carbon tax and finally a fuel tax on petroleum products.The paper is constructed as follows. Section 2 discusses the economics of carbon taxes and some international experiences. Section 3 briefly outlines the structure of the CGE model used and Section 4 discusses the simulation results. The final section concludes and summarizes the findings.2.The economics of carbon taxes and related issuesThe fundamental theoretical basis of environmental taxes have been well documented (early discussions include Baumol, 1972; Baumol and Oates, 1971, 1988) and will only bebriefly discussed in this section. TheThTT This early literature showed that society’s welfare would be improved if there were a tax on a good whose consumption or production resulted in a negative externality. Baumol and Oates (1971) further argue that an environmental tax would minimize the costs to society and at the same time achieve an ‘environmental greening’ objective when a negative externality to society existed. However, there is still no general consensus on the effectiveness of alternative instruments available to policy makers where they include, energy taxes, carbon taxes, subsidies and transfers. The main issue here is ‘which instrument or combination of instruments would be optimal?’ A carbon tax may be regressive as it may affect poorer households disproportionaly (Ekins and Parker, 2001). With any regressive tax, however, this may be resolved by reducing other taxes or the introduction of transfers, which may offset the negative impact of carbon taxes on poor households. Poor households may have the tendency to buy cheaper and perhaps less energy-efficient appliances than richer households. A carbon tax may also be advantageous to the economy if it lowered other taxes that are perceived to be more distortionary. This may include labour income taxes see for example, (Barker, 1995). On the other hand, Goulder (1995) argues that a carbon tax is more distortionary than labour tax because of too narrow tax base, the possibility of double taxation (i.e. on both intermediate input and final output) and its non-uniform content in energy products. Furthermore, Gaskins and Weyant (1993) have argued that the introduction of a carbon tax may create more distortions because of the extent to which a carbon tax or environmental change affects the prices faced by both consumers and producers. Thus, the debate on the effectiveness of a carbon tax remains active and ongoing.A recent survey by Ekins and Barker (2001) on carbon tax and carbon emission trading concluded that “market based instruments of carbon control will achieve a given level of emissions reduction at lower cost than regulations.” (p.368). Studies on the effectiveness of a carbon tax have generally concluded, however, that it generally achieves its objective of reducing GHG emissions.2.1.Carbon Taxes and InternationalExperienceAlthough a carbon tax is a relatively new option for to New Zealand, many other countries for example, The Netherlands, Norway, Sweden, Denmark, Finland and Switzerland introduced such taxes in the early 1990s. In fact, the majority of EU member states have used carbon taxes at some stage to reduce GHG emissions. The literature on this is extensive see Ekins and Barker (2001) for a review and will not be discussed in detail here.The experiences of European countries, however, may have important lessons for New Zealand where special importance may be attached to the so called “eco-leaders,” Denmark, Netherlands, Norway and Sweden. Other countries for example, Austria, Belgium, Finland, Germany and Switzerland have made small, but continuing steps towards a greater role to be played by CO2taxes in their economy. These countries may also offer important lessons, but currently they are typically less important than those from the “eco-leaders” on which we will now concentrate.The introduction of the carbon taxes by the “eco-leaders” generally involves three components. First, subsidies and taxes that may be distortionary are either modified or removed. Secondly, taxes are restructured including legislation to align them with environmental objectives. Thirdly, the new green taxes are introduced (Ekins and Barker, 2001). With these three main aspects identifies, a few observations and lessons may bee drawn from the literature.Bruce et. al.(1996) and Barker and Kohler (1998) have shown that eco-taxes can be regressive using data for OECD countries. Especially vulnerable are poorer households who may be hard hit by eco-taxes. However, the experience of the eco-leaders is that it is possible for the regressive tendency of eco-taxes to be moderated. In addition, eco-taxes may have trade-offs that are absent in other forms of taxation. In some European countries (eg. Norway, Finland, Austria and Denmark) for example, there is no leaded gasoline as high taxes have eliminated it from their respective markets (Ekins and Parker, 2001). This results in a change in consumption patterns where consumers substitute leaded gasoline for high GHG products, but at the same time keeping a large tax base (i.e. unleaded gasoline).From the literature discussed above, one can perhaps conclude that the experiences of the European eco-leaders seem to show that countries like New Zealand should not expect the eco-taxes to yield significant revenues, but should be encouraged by the fact that eco-taxes are likely to achieve environmental goals rather than fiscal objectives. However, one can argue that environmental taxes to reduce GHG can be used to reduce labour costs and, with revenues recycled back to industries and households, this is possible to cut energy consumption, create jobs and at the same time remain competitive.2.2New Zealand Government’s PreferredPolicyThe New Zealand government seems to prefer a combination of energy taxes, fuel taxes, carbon taxes and other measures. Other measures may include the new waste strategy announced in March 2002 introduced specifically to reduce the GHG emissions from the waste sector. In addition, other measures may also include an announcement that the government intends to fund measures to save electricity in the public sector by about 15%. Current policies as outlined in the government’s Energy Efficiency and Conservation Strategy, are estimated to cut GHG emissions by 25 million tonnes.The target for New Zealand, however, is to reduce emissions by about 365 million tonnes of CO2 equivalent in the first phase. This may be achieved by a range of measures including sink credits and environmental taxation. The government seems to support carbon taxes as in May 2002 they announced a new carbon tax to be introduced by 2007. The revenue from the carbon tax is expected to be recycled back through the tax system. The government does not plan to use the revenue to improve its own fiscal position. The introduction of the new carbon tax may result in an increase in the price for fuels. For example, if the price of carbon dioxide is NZ$25 a tonne tax, then this would raise retail petrol prices by around six percent, diesel by around 12 percent, electricity by around nine percent, gas by around eight percent and coal by around 19 percent.In addition to the new carbon tax, the government is also planning to introduce a new energy tax, which might be introduced by 2007.3The ModelThe model used here follows Dixon et.al. (1982) with the extensions by McDougall (1999), Truong (1999) and Hamasaki and Truong (1999) where there is an emphasis on modelling an energy sector which allows inter-fuel and capital-energy substitution possibilities. Furthermore, the model has structures that support both long-run and short-run analysis following McDougall (1999). The model also has various enhancements that enable it to be more detailed than the standard CGE model. We will concentrate on the comparative static side of the model to shed light on some of the issues raised above. The model represents an energy version of ORANI (Dixon et.al. 1982; McDougall, 1999), where investment is modelled in a way such that its initial value is proportional to the size of investments at the end of the simulation period. In turn, the size of the capital stock at the end of the period may be affected by exogenous shocks. The change in the size of the capital stock at the end of a simulated period causes changes in the growth rate of the capital stock. This treatment of investment follows closely with the suggestions by Horridge (1985).The main sectors in the model are the government, households and industries. The government sector is modelled as a collector of taxes, which are partially transferred to households. There is a constraint in the government such that its expenditure, including transfers, is equated with tax revenue. This is achieved by using two variables to model the government’s budget balance following McDougall (1999). The introduction of these two variables constrain the government’s expenditure to not only equal tax revenue but also, constrain the choice of tax rate should to achieve a certain tax revenue to balance the government’s account.The household sector is modelled such that it is the sole owner of all the factors including land and capital which means the sector has several sources of income. In addition to the standard household disposable income, households also receive income from other factors and non-labour income. The net wealth of the household is therefore determined by the value of income from labour, land and capital as well as their savings rate at the end of a simulation period. The values of the land and capital are given (exogenous) in the model. The balance between these three items represents the household’s net debt. This formulation determines how domestic physical capital is financed where it can either be financed internally by household’s net wealth or financed externally. In the second case, household’s net debt might increase.The household sector also has a consumption function, which is simply the value of the product of the household’s total labour income and the household’s propensity to consume. The household labour income is assumed to be net disposable income where income tax is deducted from the household’s gross disposable income. Household’s total income, however, is the sum of the income from land, capital and labour and transfers from government.The other main sector in the model is the industry sector. Here we follow closely the structure of production presented in McDougall (1999) and Abayasirisilva and Horridge (1996). Industries are modelled so that they can use the given factors to produce either a single or multi products. As each industry can either produce multi- or a single product with a number of different inputs, the modelling task is to allowfor the separation of these products and inputs(Abayasirisilva and Horridge, 1996). The separability assumption allows flexibility in the production sector and also makes it easier to estimate the parameters as it reduces the number of parameters to be estimated. In this model, the separable function of the output is derived from a constant elasticity of transformation aggregation function. The input separable function is divided into a number of nests. At the top of the nests for the input function, there is a composite commodity, which is a combination of the primary factor and ‘other’ costs. The composite commodities are combined using a Leontief production function. This implies that all inputs are used in proportion to Y, an index of the activity in that industry. Like many other CGE models, the Armington (1969) assumption is used. This means that the composite commodity produced is a constant elasticity of substitution function of either a domestic good or its imported equivalent.The composite input of the primary factor is a constant elasticity of substitution combination of land, capital and composite labour. The composite labour is a constant elasticity of substitution of skilled and unskilled labour. This combination of composite primary input is the same across all the industries, (in our case 22). However, this does not imply the same composite input and labour combination for every product produced because the input combination and the behavioural parameters are not the same across the 22 industries.Production and consumption in the household and industrial sector are affected by ‘bad commodities’, which are oil, gas, coal and electricity through the environmental taxes imposed on these ‘bad commodities.’ This is achieved by the introduction of three environmental taxes: carbon taxation, energy taxation and petroleum taxation. These taxes form part of the ad valorem commodity tax.The impact of these ‘bad’ taxes depends on the value of the intensity coefficients. The intensity coefficients for each of the taxes are the proportion of the ‘bad contents’ to the market value of the commodities. The ‘bad content’ is the energy content of the three types of taxes discussed. It is possible that the ‘bad content’ can be disaggregated into different types of fuels. For example, electricity can be disaggregated into steam turbine, hydroelectricity, gas turbine, coal generators and so forth. Coal, a fossil fuel, can also be disaggregated into lignite (brown coal) and briquettes. In this model, however, disaggregation of fossil fuels is left to a later study and not discussed further here.4Simulation and Results The simulations undertaken included the introduction of an energy tax, a carbon tax and a petroleum tax and measure the impact of each on the economy when the rate of taxation is set so that each type tax collects revenue equivalent to 0.6 percent of GDP in the base-case. Table 1 presents the tax rate set for each of the taxes. As the table shows, the tax rates for both the energy and carbon tax are not very different.The tax rate is highest for the energy commodity with the high energy intensity as well as high emission coefficients. The highest ad valorem tax rates are for coal while the lowest tax rates are for petroleum, oil and gas products. The simulation results were constructed to consider, in particular, the existence of likely significant differences in the micro and macro impacts of an energy tax, a carbon tax and a petroleum tax. The emphasis was particularly on understanding both the greenhouse impact and the non-greenhouse impact of the various environmental taxes.Table 1: Ad valorem tax rates on fossil fuels (%)Energytax Carbon taxPetroleumproducts tax Coal 131 123 0Gas 56 51 0Oil 14 18 0 Petroleumproducts 8 9 15The results of the impact of each of the environmental taxes on the carbon emissions and fossil fuel consumption shows that both the volume of carbon emissions and fossil fuel consumed declined (Table 2). The carbon tax, for example, leads to a reduction in energy consumption and carbon emission of about 14 and 18 percent respectively. The impact of the energy tax and carbon tax in reducing energy consumption and carbon emission are almost the same. An energy tax reduces energy consumption by 13 percent compared to 14 percent for the carbon tax. It also reduces carbon emissions by approximately 16 percent compared with 18 percent for the carbon tax. On the other hand, a petroleum tax is less effective in reducing energy consumption and carbon emissions as it reduces carbon emission and energy consumption by approximately 0.9 and 1.9 percent, respectively.Table 2: Estimated effects of each of the three taxes on fossil fuel energy consumption and carbon emissionsEnergy tax CarbontaxPetroleumproducts taxCarbonDioxideEmissions -14 -18 -0.9Fossil fuelenergy use -13 -16 -1.9 Turning to the macro effects of the three types of taxes, the impact of both the carbon and the energy taxes on some macro variables are similar, as shown by Table 4. Real household consumption falls by 0.1percent for the carbon tax and 0.09 percent of the energy tax. However, for the petroleum tax, consumption falls by 0.2 percent. Additional tax will incur a high penalty for the economy, with little effect on the environment.Table 3: Estimated effects of energy,carbon and petroleum products taxeson selected macro variablesPetroleum product tax Energytax Carbon taxIncome tax rate -0.82 -0.62 -0.68 Householdconsumption -0.2 -0.09 -0.1 Capital(working) -0.82 -1.12 -1.26 Volume ofexports -1.62 -1.54 -1.7Capital (fixed) -0.75 -1.58 -1.62 Investment -0.32 -0.51 -0.54 GDP -0.29 -0.38 -0.39 Volume ofimports -0.91 -0.78 -0.89 Like many CGE models that model the impact of energy and carbon emission reduction programmes, the impact of both the energy tax and the carbon tax is to reduce GDP by approximately 0.385 percent. The impact of the petroleum tax is slightly less, at 0.29 percent. The fall in GDP is associated with the fall in capital stock. As the capital stock is reduced investment also falls. The impact of the energy tax and the carbon tax on investment is approximately 0.51 and 0.54 respectively with the carbon tax having a slightly higher effect than the carbon tax.In addition, we can consider the impact in selected sectors, as shown in Table 4. The sectoral effects presented here relate to the energy intensive industries, mining, metal products, electricity and gas sectors. The impact on these energy intensive sectors exceeds, on average, 2 percent.For example, for mining there is a reduction of 4.1 and 4.5 percent with the energyand carbon tax respectively. The impact of the petroleum tax on mining is slightly less at approximately 2 percent. The impact on the metals’ sector and the electricity, gas and water sectors is also a decline of, an average, 3.8 percent for the metal sector and an average reduction of about 2.7 for the electricity, gas andwater sector. The slightly less than average impact on the electricity, gas and water sector isdue to the 1.2 percent increase in electricity, gasand water sector usage with a corresponding reduction in usage for the energy and carbon taxes. The other sectors are slightly less energy intensive than the previous three sectors discussed so the impacts of the three taxes areless than those of the energy intensive sectors. Generally, the impact of the energy taxes and the carbon taxes are greater than the petroleum taxes.Table 4: Estimated effects of energy, carbon and petroleum products on activity of selected sectorsPetroleumproduct taxEnergytax Carbon tax Services -0.26 0 0 Petroleum prod. -1.62 -1.52 -1.34 Construction -0.62 -0.93 -0.8 Mining -2 -4.12 -4.51 Transport -0.71 -0.55 -0.5 Wood products -0.41 -0.43 -0.52 Transport equip. -0.64 -0.52 -0.43 Electricity 1.27 -3.21 -3.62 Textiles 0 0 0 Non-metal products -0.81 -0.72 -0.91 Agriculture -0.4 -0.31 -0.42 Metal products -3.12 -3.66 -3.92 Food Products -0.11 0 0In addition to the output impacts on the above selected sectors, there are also employment effects. Table 5 shows the impact of the threetaxes on employment broadly divided into skilled an unskilled. The impact of the taxes iffelt most heavily on the unskilled workers with a reduction of 0.23 percent for the energy tax and0.28 for carbon tax.Table 5: Estimated effects of energy, carbonand petroleum products on employmentEnergytaxCarbontaxPetroleumproduct taxSkilled Workers 0.15 0.16 0.02 Unskilled Workers -0.23 -0.28 -0.06 OverallEmployment 0.00 0.00 0.00On the other hand, there is an increase in the level of employment of skilled workers. This may signal a change in the structure of the economy where firms prefer to substitute labour for less energy intensive capital.5ConclusionsThis paper attempts to assess the relative effectiveness of an energy tax, a carbon tax and a petroleum tax on the New Zealand economy. From the European experience we have learned that targeting carbon dioxide can be an efficient way to achieve environmental goals although efforts should be made to reduce the emissions of other harmful GHG such as sulphur dioxide, nitrogen oxide and methane as they are more effective in trapping heat in the earth’s atmosphere.This exercise has demonstrated that an energy tax based on the energy content of fossil fuel might be an effective instrument to reduce carbon emissions although the energy tax is not as effective as a carbon tax. Policy instruments such as a carbon tax might reduce the stock of both fixed and working capital. The reduction in the economy’s stock of capital might lead to reductions in GDP, household consumption (an indicator of welfare change) exports and investment. Therefore, some important trade-offs exist and require consideration.6. AcknowledgementsAll three authors wish to thank the New Zealand Public Good Science Fund, grant number UOWX:0010, Energy Resources and Energy Resource Economics, for supporting this research. The usual disclaimer applies.7.ReferencesAbayasiri-Silva, K. and Horridge, M. (1996) Economies of Scale and ImperfectCompetition in an Applied GeneralEquilibrium Model of the AustralianEconomy. Working Paper No. OP-84,March 1996.Armington (1969) A Theory of Demand for Products Distinguished by Place ofProduction, International Monetary FundStaff Paper Vol. 16, pp. 159-176. Barker, T. (1995). Taxing pollution instead of employment: greenhouse gas abatementthrough fiscal policy in the UK. Energyand Environment, 6,1,1-28. Barker, T. and J. Kohler (1998), Equity and Ecotax reform in the EU: Achieving a10% reduction in CO2emissions usingExcise Duties. Environmental FiscalReform. Working Paper No.10,University of Cambridge, Cambridge. Baumol, W. 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全空间无人体系管控中心通用技术要求英文1. IntroductionThe development of unmanned control centers for all-territory space is an important aspect of modern technology. In order to ensure the smooth operation and safety of these control centers, it is crucial to establish universal technical requirements that can be applied across different spaces and environments. This document 本人ms to outline the general technical requirements for unmanned control centers in all-territory spaces in English.2. System Architecture2.1. The unmanned control center should have a modular and scalable architecture that can be adapted to different space environments and requirements.2.2. The system should be capable of real-time data processing, analysis, and decision-making.2.3. The architecture should be designed to facilitate seamlessmunication and integration with other systems and devices.3. Communication3.1. The control center should have reliable andsecuremunication capabilities, including both terrestrial and satellitemunication.3.2. The system should be able to handle a large volume of data transmission and ensure low-latencymunication.3.3. Themunication network should be resistant to interference and capable of operating in harsh environmental conditions.4. Sensing and Perception4.1. The control center should be equipped with advanced sensing and perception technologies, including radar, lidar, and optical sensors.4.2. The system should be capable of detecting and tracking objects in real-time, including moving vehicles, humans, and natural obstacles.4.3. The sensing and perception capabilities should be able to operate in diverse weather and lighting conditions.5. Control and Decision-making5.1. The control center should have autonomous control and decision-making capabilities to ensure continuous and safe operation.5.2. The system should be able to dynamically adapt and respond to changing environments and situations.5.3. The control and decision-making processes should be transparent and auditable.6. Power and Energy6.1. The control center should have robust and reliable power and energy supply systems, including backup and emergency power sources.6.2. The system should be energy-efficient and capable of optimizing power usage for different operational scenarios.6.3. The power and energy systems should be resilient to potential disruptions and f本人lures.7. Cybersecurity7.1. The control center should implement state-of-the-art cybersecurity measures to protect ag本人nst unauthorized access, data breaches, and cyber-attacks.7.2. The system should have advanced encryption and authentication mechanisms to ensure the confidentiality and integrity of data.7.3. The cybersecurity measures shouldply with international standards and regulations.8. Human-Machine Interface8.1. The control center should provide an intuitive and user-friendly human-machine interface for operators and administrators.8.2. The interface should support multi-modal interaction, including touch screens, voicemands, and gesture recognition.8.3. The system should be designed to minimize cognitive load and enhance situational awareness for operators.9. M本人ntenance and Support9.1. The control center should have built-in diagnostic and monitoring capabilities for proactive m本人ntenance and support.9.2. The system should be easily upgradable and expandable to amodate future technological advancements.9.3. The m本人ntenance and support processes should be well-documented and standardized.10. ConclusionIn conclusion, the above technical requirements outline the fundamental capabilities and features that are essential for the successful operation of unmanned control centers in all-territory spaces. By adhering to these requirements, organizations and developers can ensure the reliability, efficiency, and safety ofunmanned control center systems, thereby contributing to the advancement of technology in the field of unmanned space control.。