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pale的用法及总结一、背景介绍Pale是一个英语单词，读音为 /peɪl/，可以作为动词或形容词使用。
下面将从不同的角度来探讨这个词的用法和总结。
二、作为动词的用法1. 表示使苍白或变淡：例如，She paled at the sight of blood.（她看到血后脸色变得苍白。
）2. 表示减弱或消失：例如，The stars paled as the sun rose.（太阳升起时星星逐渐隐没。
）3. 表示相形见绌：例如，His achievements pale in comparison with hers.（与她相比，他的成就黯然失色。
）三、作为形容词的用法1. 表示苍白或暗淡：例如，He had a pale complexion.（他有一张苍白的脸色。
）2. 表示含蓄或不强烈：例如，She offered only a pale smile.（她只微笑了一下。
）3. 表示无足轻重：例如，Their complaints seemed pale in comparison to the magnitude of the problem.（与问题的严重性相比，他们的抱怨显得微不足道。
）四、相关表达搭配在实际使用中，与pale相关的表达搭配进一步丰富了其用法。
1. Pale in significance：在重要性上失去色彩。
例如，His achievements pales in significance compared to what he managed in the past.（与过去相比，他的成就现在显得无足轻重。
）2. Pale imitation：苍白的模仿。
例如，The artwork was a pale imitation of the original masterpiece.（这幅艺术品只是原作的苍白模仿。
）3. Pale shadows：黯淡的阴影。
例如，Their happiness was overshadowed by pale shadows of doubt and mistrust.（怀疑和不信任带来了他们幸福感的阴影。
critical ratios of differencesCritical ratios of differences refer to the comparison of the size or magnitude of differences between two or more variables or groups in a statistical analysis. It is used to determine whether the observed differences are statistically significant or can be attributed to chance. In this article, we will explore the concept of critical ratios of differences and provide some examples to enhance understanding.When conducting statistical analyses, researchers often compare the means or proportions of different groups or variables to assess the significance of the differences observed. The critical ratio of differences helps to determine whether the observed differences are meaningful or can be considered statistically significant.To calculate the critical ratio of differences, one must first estimate the standard error of the difference between the means or proportions being compared. The standard error is a measure of the variability or spread of the data, and it is used to determine how much difference would be expected due to random chance alone.The critical ratio is then calculated by dividing the observed difference by the standard error. If the resulting ratio is larger than a predetermined critical value, it suggests that the observed difference is statistically significant. On the other hand, if the ratio is smaller than the critical value, it implies that the observed difference is likely due to chance.For instance, let's consider a study comparing the effectiveness of two different teaching methods on student performance. Theresearchers collect data from two groups of students – one taught using method A and the other using method B. They compute the mean scores for each group and find a difference of 5 points between the two means.To determine the significance of this difference, the researchers use the formula for the critical ratio of differences. They also estimate the standard error of the difference based on the sample sizes and variances of each group.If the calculated critical ratio is, for example, 1.96, which corresponds to a 95% confidence level, and the observed ratio is 2.5, then the researchers can conclude that the difference in student performance between the two teaching methods is statistically significant. This means that the observed difference is unlikely to have occurred by chance alone.The critical ratio of differences is also commonly used in hypothesis testing. Hypothesis testing involves setting up a null hypothesis and an alternative hypothesis and using statistical analyses to determine which hypothesis is supported by the data. The critical ratio helps researchers to make this determination.In conclusion, critical ratios of differences play a crucial role in statistical analyses by allowing researchers to assess the significance of observed differences between variables or groups. By comparing the observed difference to the standard error and the critical value, researchers can determine whether the observed difference is statistically meaningful or can be attributed to chance. This helps to ensure the accuracy and reliability of researchfindings and provides a basis for making informed decisions based on the data.。
Comparison of Chain and Step PolymerizationsChain polymerization proceeds by a distinctly different mechanism from step polymerization. Themost significant difference is that high-molecular-weight polymer is formed immediately in a chainpolymerization. A radical, anionic, or cationic reactive center, once produced, adds many monomerunits in a chain reaction and grows rapidly to a large size. The monomer concentration decreasesthroughout the course of the reaction as the number of high-polymer molecules increases. At anyinstant the reaction mixture contains only monomer, high polymer, and the growing chains. The 4 molecular weight of the polymer is relatively unchanged during the polymerization, although theoverall percent conversion of monomer to polymer increases with reaction time.The situation is quite different for a step polymerization. Whereas only monomer and thepropagating species can react with each other in chain polymerization, any two molecular speciespresent can react in step polymerization. Monomer disappears much faster in step polymerization asone proceeds to dimer, trimer, tetramer, and so on. The molecular weight increases throughout thecourse of the reaction, and high-molecular-weight polymer is not obtained until the end of thepolymerization. Long reaction times are necessary for both high percent conversion and highmolecular weights.Whether a particular monomer can be converted to polymer depends on both thermodynamic andkinetic considerations. The polymerization will be impossible under any and all reaction conditions ifit does not pass the test of thermodynamic feasibility. Polymerization is possible only if the free-energy difference ΔG between monomer and polymer is negative.A negative ΔG does not, however, mean that polymerization will be observed under a particular setof reaction conditions (type of initiation, temperature, etc.). The ability to carry out athermodynamically feasible polymerization depends on its kinetic feasibility—on whether the processproceeds at a reasonable rate under a proposed set of reaction conditions. Thus, whereas thepolymerization of a wide variety of unsaturated monomers is thermodynamically feasible, veryspecific reaction conditions are often required to achieve kinetic feasibility in order to accomplish aparticular polymerization.The carbon–carbon double bond in vinyl monomers and the carbon–oxygen double bond inaldehydes and ketones are the two main types of linkages that undergo chain polymerization. Thepolymerization of the carbon–carbon double bond is by far the most important of the two types ofmonomers. The carbonyl group is not prone to polymerization by radical initiators because of itspolarized nature:Aldehydes and ketones are polymerized by both anionic and cationic initiators.Effects of SubstituentsUnlike the carbonyl linkage, the carbon–carbon double bond undergoes polymerization by bothradical and ionic initiators. The difference arises because the p-bond of a vinyl monomer can respondappropriately to the initiator species by either homolytic or heterolytic bond breakage:A wide range of carbon–carbon double bonds undergo chain polymerization. Table 3-1 shows monomers with alkyl, alkenyl, aryl, halogen, alkoxy, ester, amide, nitrile, and heterocyclic substituents on the alkene double bond.4Whether a vinyl monomer polymerizes by radical, anionic, or cationic initiators depends on the inductive and resonance characteristics of the substituent(s) present. The effect of the substituent manifests itself by its alteration of the electron-cloud density on the double bond and its ability to stabilize the possible radical, anion, or cation formed. Electrondonating substituents such as alkoxy, alkyl, alkenyl, and phenyl increase the electron density on the carbon–carbon double bond and facilitate its bonding to a cationic species. Further, these substituents stabilize the cationic propagating species by resonance. Electron-withdrawing substituents such as cyano and carbonyl (aldehyde, ketone, acid, or ester) facilitate the attack of an anionic species by decreasing the electron density on the double bond.Contrary to the high selectivity shown in cationic and anionic polymerization, radical initiators bring about the polymerization of almost any carbon–carbon double bond. Radical species are neutral and do not have stringent requirements for attacking the p-bond or for the stabilization of the propagating radical species. Resonance stabilization of the propagating radical occurs with almost all substituents. Thus, almost all substituents are able to stabilize the propagating radical by delocalization of the radical over two or more atoms.Almost all monomers containing the carbon–carbon double bond undergo radical polymerization, while ionic polymerizations are highly selective (Table 3-1). Cationic polymerization is essentially limited to those monomers with electron-releasing substituents such as alkoxy, phenyl, vinyl, and 1,1-dialkyl. Anionic polymerization takes place with monomers possessing electron-withdrawing groups such as nitrile, carbonyl, phenyl, and vinyl. The selectivity of ionic polymerization is due to the very strict requirements for stabilization of anionic and cationic propagating species.Ionic polymerizations, especially cationic polymerizations, are not as well understood as radicalpolymerizations because of experimental difficulties involved in their study. The nature of the reaction media in ionic polymerizations is often not clear since heterogeneous inorganic initiators are often involved. Further, it is extremely difficult in most instances to obtain reproducible kinetic data because ionic polymerizations proceed at very rapid rates and are extremely sensitive to the presence of small concentrations of impurities and other adventitious materials. The rates of ionic polymerizations are usually greater than those of radical polymerizations.Ionic polymerizations are usually carried out in solvents of low or moderate polarity such as 4 tetrahydrofuran, ethylene dichloride, and pentane, although moderately high polarity solvents such as nitrobenzene are also used. In such solvents one usually does not have only a single type of propagating species. For any propagating species such as ~BA in cationic polymerization, one can visualize the range of behaviors from one extreme of a completely covalent species (I) to the other of a completely free (and highly solvated) ion (IV )The intermediate species include the tight or contact ion pair (II) (also referred to as the intimate ion pair) and the solvent-separated or loose ion pair (III). The intimate ion pair has a counter- or gegenion of opposite charge close to the propagating center (unseparated by solvent). the solvent-separated ion pair involves ions that are partially separated by solvent molecules. The propagating cationic chain end has a negative counterion. For an anionic polymerization the charges in species II-IV are reversed; that is, B carries the negative charge and A the positive charge. There is a propagating anionic chain end with a positive counterion. Alternate terms used for free ion and ion pair are unpaired ion and paired ion, respectively.Most ionic polymerizations involve two types of propagating species, an ion pair and a free ion IV, coexisting in equilibrium with each other. The identity of the ion pair (i.e., whether the ion pair is best described as species II or III) depends on the particular reaction conditions, especially the solvent employed. Increased solvent polarity favors the loose ion pair while the tight ion pair predominates in solvents of low polarity. The ion pairs in cationic polymerization tend to be loose ion pairs even in solvent of low or moderate polarity since the counterions (e.g., bisulfate, SbClˉ6 , perchlorate) are typically large ions. The lower charge density of a large counterion results in smaller electrostatic attractive forces between the propagating center and counterion. The nature of the ion pairs is much more solvent-dependent in anionic polymerizations where the typical counterion (e.g., Li+, Na+) is small. The covalent species I is generally ignored since it is usually unreactive (or much lower in reactivity) compared to the other species. Free ion concentrations are generally much smaller than ionpair concentrations but the relative concentrations are greatly affected by the reaction conditions. Increased solvent polarity results in a shift from ion pairs to free ions. The nature of the solvent has a large effect in ionic polymerization since the different types of propagating species have different reactivities. Loose ion pairs are more reactive than tight ion pairs. Free ions are orders of magnitude higher in reactivity than ion pairs in anionic polymerization. Ion pairs are generally no more than an order of magnitude lower in reactivity compared to free ions in cationic polymerization.Various initiators can be used to bring about the polymerization of monomers with electronreleasing. Substituents Protonic (Brønsted) acids initiate cationic polymerization by protonation of the olefin. The method depends on the use of an acid that is strong enough to produce a resonable concentration of the protonated speciesbut the anion of the acid should not be highly nucleophilic; otherwise it will terminate the 4 protonated olefin by combination (i.e., by covalent bond formation).The nomenclature for positively charged organic ions has undergone some change. The older term, no longer used, for the trivalent, trigonal sp2-hybridized species such as those in Eqs. 5-1 and 5-2 is carbonium ion. Olah [1972, 1988] proposed that carbenium ion be used instead with the term carbonium ion being reserved for pentavalent charged carbon ions (e.g., nonclassical ions) and the term carbocation encompassing both carbenium and carbonium ions. The term carbenium ion for the trivalent carnbon ion has not taken firm hold. Most text and journal references use the term carbocation, and so will this text. The term carbocation polymerization is used synonymously with cationic polymerization in the literature.The requirement for the anion not to be excessively nucleophilic generally limits the utility of most strong acids as cationic initiators. Hydrogen halides are ineffective as initiators of cationic polymerization because of the highly nucleophilic character of halide ions.Various Lewis acids are used to initiate cationic polymerization, generally at low temperatures, with the formation of high-molecular-weight polymers in high yield. These include metal halides (e.g., AlCl3, BF3, SnCl4, SbCl5, ZnCl2, TiCl4) and their organometallic derivatives (e.g., RAlCl2, R2AlCl, R3Cl). Lewis acids are the most important means of initiating cationic polymerization. Aluminium, boron, tin, and titanium halides are the most frequently used Lewis acids.Initiation by Lewis acids almost always requires and/or proceeds much faster in the presence of either a proton donor (protogen) such as water, hydrogen halide, alcohol, and carboxylic acid, or a carbocation donor (cationogen) such as an alkyl halide (e.g., t-butyl chloride and triphenylmethyl chloride), ester, ether, or anhydride. Thus, dry isobutylene is unaffected by dry boron trifluoride but polymerization occurs immediately when trace amounts of water are added. The terminology of Kennedy and Marechal is used in here; the protogen or cationogen is referred to as the initiator, while the Lewis acid is the coinitiator. The reader is cautioned that much of the published literature until 1990 or so used the reverse terminology. The protogen or cationogen is referred to as the initiator since it supplies the proton or cation that ultimately adds to monomer to initiate polymerization. The initiator and coinitiator, representing an initiating system, react to form an initiator–coinitiator complex (or syncatalyst system), which then proceeds to donate a proton or carbocation to monomer and, thus, to initiate propagation.（Principles of Polymerization（Fourth Edition）, edited by George Odian，John Wiley & Sons, Inc. 2004）。
作比较和列数字的100字作文英文回答：Comparison and Listing of Numbers.When it comes to comparing and listing numbers, it's important to consider their magnitude and significance. For example, when comparing the population of two cities, we can see that New York City has a population of over 8 million, while Los Angeles has a population of around 4 million. This shows that New York City has a significantly larger population than Los Angeles.In terms of listing numbers, it's important to organize them in a clear and logical manner. For example, whenlisting the top 10 highest mountains in the world, Mount Everest stands at the top with a height of 29,029 feet, followed by K2 at 28,251 feet, and Kangchenjunga at 28,169 feet.Overall, when comparing and listing numbers, it's essential to consider their context and relevance to accurately convey their significance.中文回答：和数字进行比较和列举时，重要的是考虑它们的大小和重要性。
CCD与PMT的区别CCD vs. PMT技术特点描述（光电倍增管简称PMT，以下用PMT简称）1、 PMT与CCD都是光谱仪的检测器。
PMT使用1000V的高压作为工作电压，而CCD使用42V低压作为工作电压。
在检测高纯物质，如99.997%的电解铝或者电解铜的时候，PMT的优势是显而易见的，CCD检测器是无法检测此类高纯物质的。
但是在各种合金分析方面，这两种检测器是基本一致的。
2、 CCD检测器由于使用了全谱技术，能够将全部的谱线接收，所以能够做到实时的波峰校正，省去了PMT型光谱仪所必须的波峰校正工作，大大提高了工作效率。
实际是CCD型光谱仪在激发样品的第一秒自动完成波峰校正工作。
3、 CCD型光谱仪由于接收了全谱的谱线，所以为以后增加元素和基体打下了完善的硬件基础。
客户以后要增加元素或者基体，不需要改动硬件，只需使用标准样品建立工作曲线即可。
为客户的以后发展提供了方便。
D型光谱仪能够显示所有的谱图，所以能够实现高端用户的定性需求。
5、分析精度方面，我们可以达到甚至由于如下国标：《GB-T 7999-2007 铝合金光电直读光谱分析法》；《GB11170-2008 不锈钢光谱分析方法》；《GB-T 4336-2002碳钢和中低合金钢光谱分析方法》。
甚至可以根据用户的技术要求，协商技术协议中的分析精度要求，和验收标准。
下面是一个高工总结的CCD检测器的优势，从他的描述中也能够看到，CCD检测器是一个发展趋势。
CCD vs. PMTCCD的优势(一)•整个波长范围内的所有谱线均可利用，我们可以选择所有的最佳线来进行分析，不会因为空间有限而被迫放弃某些最佳线•对于任何一个元素，都有许多谱线可供选择，能够覆盖完整的含量范围。
对于某个特定的含量范围，我们也可以同时选择几条谱线进行分析，对这些谱线的结果进行平均，这样可以提高分析结果的再现性•根据用户的需要，可以添加额外的谱线（针对不常见的元素）。
这可以在仪器生产时完成，或者在用户现场完成•在用户现场可以添加新的基体，而且无须对硬件做任何改动CCD的优势(二)•仪器整机的价格不再取决于谱线的数目；仪器的测量范围更宽；某些特殊的元素（如铁基里的Zr或者铝基里的Sr）已包含在标准配置里面。
Direct Comparison of the Magnitude and Phase of Measured S-parameters of Metamaterials with Finite Element SimulationVasundara V. Varadan and Zhongyan Sheng*Microwave and Optics Laboratory for Imaging and Characterization, Department of Electrical Engineering, University of Arkansas, 700 Research CenterBoulevard, Fayetteville, AR 72701* zsheng@IntroductionMetamaterials, especially the Negative Index Materials (NIMs), have caught much intention recently (see, for example, the review papers [1], [2]). The artificial materials present interesting phenomena such as plasmonic resonances and the associated negative property, and the applications of these metamaterial are very promising and attainable even up to optical frequencies [3]. The combination of a negative permittivity metamaterial and a negative permeability metamaterial can produce an NIM [4]. Metal wires have negative permittivity at a frequency lower than the plasma frequency [5] and are relatively easy to implement, so negative permeability materials are the focus of this paper. Split Ring Resonators (SRR) [6] and Omega [7] are two typical structures having the potential to have a negative effective permeability, because they are able to produce a resonance at a low frequency. They structures are planar and easy to fabricate using conventional lithography on dielectric and integrated circuit substrates. This paper considers samples with Omega structures.One of the most effective ways to determine the electromagnetic properties of a metamaterial is to retrieve the effective values from the complex S-parameters of a material slab, including both magnitude and phase information (refer to [8] for property retrieval). In this paper, we calculate the S-parameters of the metamaterial structure using finite element simulation. To verify the simulation, we prepared a slab composed of arrays of the Omega structures, and measure the S-parameters of the metamaterial slab sample by a focused beam free-space microwave measurement setup [9]. The direct comparison of S-parameters shows perfect agreement of the simulation and the measurement. A strong resonance at about 7.5 GHz is observed. This is the first time that direct comparisons have been made of the measured phase data with simulation attesting to the accuracy of the calibration and measurement set-up.S-parameter SimulationThe Omega cell with simulation region 5 mm ×5 mm ×15 mm is shown in Figure 1. Incident wave propagates along z-axial from left to right while the E-field is polarized along x-axis and H-field along y-axis. Absorption boundary conditions are set on the left and the right faces of the outer box to reduce the sizeof the calculation region and avoid the multiple reflections. Periodic or symmetry boundary conditions are applied on the remaining four faces, which effectively repeats the Omega cell an infinite number of times in the x and y direction, forming an Omega slab. Omega shaped metal structures are patterned on commercial circuit board material FR4 with a thickness of 0.76 mm. The relative permittivity of FR4 is set to 4.4 + 0.088i and the relative permeability is 1. In the simulation we assume the metallization to be a perfect conductor of negligible thickness.We use a commercial Finite Element Method (FEM) code, Ansoft HFSS [10], to simulate the Omega cell structure. In HFSS, the calculation space is divided into about 20,000 elements, which corresponds to a discretization density of 60 grid points per wavelength at 18 GHz.Focused Beam Free-space MeasurementTo ensure that the simulation results are comparable with the measurements, a suitable measurement setup should be considered. In this paper we use a focused beam free-space measurement developed precisely for material characterization of complex, inhomogeneous materials, which has been successfully applied to the non-destructive, non-contact characterization of a variety of materials as a function of both frequency and temperature [8], [11]. This set-up makes it possible to obtain accurate phase information, and together with the magnitude, a complete set of S-parameters can be measured accurately. In the experimental samples, the metallization is copper of 17 microns thickness. The electric and magnetic fields associated with the reflected and transmitted waves are calculated on the two planes as identified in Figure 1. They are in correspondence with the free-space S-parameter measurement at the calibration planes of the Omega slab sample. In the measurement, after TRL calibration, the reflection plane is used asEH k wrg dl h Reflection/reference plane Transmission planex y z Figure 1, Simulation cell for Omega sample (w = 0.4 mm, r = 1.9 mm, h = 4.2 mm, g = 0.2 mm, l = 6 mm; outer box dimension, 5 mm × 5 mm ×the reference plane and the amplitude and phase of the incident wave on this plane are used to normalize the S-parameters.Results and DiscussionFigure 3 shows the magnitude and phase of the S-parameters. The simulation starts from 1 GHz to 18 GHz with 0.5 GHz spacing while the measurement starts from 5.8 GHz with much denser points (600 frequency points).Omega metamaterials(a) S21 and S11 magnitude; (b) S21 and S11 phase.It can be seen that both the magnitude and the phase of the measured S-parameters and simulated results agree very well, even at high frequencies with wavelength comparable to the cell dimension. A strong resonance is observed in the results of both the measurement and the simulation at ~7.5 GHz. The wavelength is much large than the lattice size, which ensures the homogenization of the metamaterial in the frequencies near the resonance. The good agreement between measurement and simulation is because of the excellent measurement setup with focused beam excitation and the simulation model with uniform plane wave excitation. Because the usual calculation of transmission and reflection of a medium slab and the retrieval of the material properties are based on infinite uniform plane wave, which does not exist and cannot be implemented, we have to find another form of plane wave that has approximately the same effect, here we generate a Gaussian plane wave beam. Our results show the focused beam free-space measurement is a robust and accurate method for the characterization of the metamaterials.References:[1]D. R. Smith, J. B. Pendry, M. C. K. Wiltshire, Metamaterials and NegativeRefractive Index, Science, Vol. 305. no. 5685, pp. 788 – 792, (2004).[2]J. B. Pendry, Negative Refraction, Contemporary Physics, Volume 45,Number 3, pp. 191-202 (2004).[3]Stefan Linden, Christian Enkrich, Martin Wegener, Jiangfeng Zhou, ThomasKoschny, Costas M. Soukoulis, Magnetic Response of Metamaterials at 100 Terahertz, Science, Vol. 306. no. 5700, pp. 1351 – 1353 (2004).[4]R. A. Shelby, D. R. Smith, S. Schultz, Experimental Verification of aNegative Index of Refraction, Science Vol. 292. no. 5514, pp. 77 – 79 (2001).[5]J. B. Pendry, A. J. Holden, D. J. Robbins and W. J. Stewart, Low frequencyplasmons in thin-wire structures, Journal of Physics: Condensed Matter, Volume 10, pp 4785-4809 (1998).[6]Koray Aydin, Kaan Guven, Nikos Katsarakis, Costas M. Soukoulis, EkmelOzbay, Effect of Disorder on Magnetic Resonance Band Gap of Split-ring Resonator Structures, Optics Express, Volume 12, Number 24, pp.5896-5901 (2004).[7]Simovski, Constantin R., He, Sailing, Frequency range and explicitexpressions for negative permittivity and permeability for an isotropic medium formed by a lattice of perfectly conducting Omega particles, Physics Letters A, Volume 311, Issue 2-3, pp. 254-263 (2003).[8]Ghodgaonkar, D.K., Varadan, V.V., Varadan, V.K., A free-space method formeasurement of dielectric constants and loss tangents at microwave frequencies, IEEE Transactions on Instrumentation and Measurement, Volume 38, Issue 3, pp. 789-793 (1989).[9]Vasundara V. Varadan, Vijay K. Varadan, Deepak K. Ghodgaonkar, 5-100GHz free-space microwave characterization setup, Proceedings of SPIE, Volume 1307, pp. 116-121 (1990).[10]R. Remski, Analysis of photonic bandgap surfaces using Ansoft HFSS,Microwave Journal, Volume 43, pp. 190-200 (2000).[11]Ru-Yen Ro, Vasundara V. Varadan, and Vijay K. Varadan, Experimentalstudy of chiral composites, Proceedings of SPIE, Volume 1558, pp. 269-287 (1991).。
