Lattice path combinatorics and asymptotics of multiplicities of weights in tensor powers

We give asymptotic formulas for the multiplicities of weights and irreducible summands in high-tensor powers V_λ^⊗N of an irreducible representation V_λ of a compact connected Lie group G. The weights are allowed to depend on N, and we obtain several regimes of pointwise asymptotics, ranging from a central limit region to a large deviations region. We use a complex steepest descent method that applies to general asymptotic counting problems for lattice paths with steps in a convex polytope.     

Minimum Disparity Estimation in Linear Regression Models: Distribution and Efficiency

This paper deals with the minimum disparity estimation in linear regression models. The estimators are defined as statistical quantities which minimize the blended weight Hellinger distance between a weighted kernel density estimator of errors and a smoothed model density of errors. It is shown that the estimators of the regression parameters are asymptotic normally distributed and efficient at the model if the weights of the density estimators are appropriately chosen.     

Effect of reaction conditions on the molecular weight and polydispersity of linear poly(arylene ether phosphine oxide)s prepared from an AB monomer

A thorough study of the polymerization behavior of 4‐fluoro‐4′‐hydroxytriphenyl‐phosphine oxide, 2 , under nucleophilic aromatic substitution reactions has been carried out. The synthesis of 2 was achieved in excellent yields by the reaction of bis(4‐fluorophenyl)phenylphosphine oxide, 1 , with one equivalent of potassium hydroxide in DMSO/water. The structure and purity of 2 were confirmed via ¹H, ¹³C, and ³¹P NMR spectroscopy along with elemental analysis. Polymerization reactions of 2 in NMP or DMSO at 180 °C provided the corresponding linear poly(arylene ether phosphine oxide)s, PAEPOs, with number average molecular weights, M_n, ranging from 11,700 to 36,500 Da. All of the polymer samples were completely soluble in chloroform, tetrahydrofuran, DMSO, NMP, and DMAc. The polymerization reactions were accompanied by a competing intramolecular process that resulted in the formation of cyclic oligomeric species that were removed via a final precipitation from methanol. Analysis using ³¹P NMR spectroscopy and size exclusion chromatography (SEC) confirmed that the majority of the lower molecular weight cyclic species were removed via this process. The polymer samples formed tough films when chloroform solutions were slowly evaporated on a glass slide. The PAEPO samples prepared in this study exhibited excellent thermal stability with T_d (5%) values between 503 and 542 in air while the glass transition temperatures ranged from 223 to 237 °C. © 2006 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 44: 2099–2106, 2006     

Synthesis of polyacrylonitrile via reverse atom transfer radical polymerization catalyzed by FeCl3/isophthalic acid

FeCl₃ coordinated by isophthalic acid was first used as a catalyst in the azobisisobutyronitrile‐initiated reverse atom transfer radical polymerization of acrylonitrile. N,N‐Dimethylformamide was used as a solvent to improve the solubility of the ligand. An FeCl₃‐to‐isophthalic acid ratio of 0.5 not only gave the best control of the molecular weight and its distribution but also provided rather a rapid reaction rate. The effects of different solvents on the polymerization of acrylonitrile were also investigated. The rate of the polymerization in N,N‐dimethylformamide was faster than that in propylene carbonate and toluene. The molecular weight of polyacrylonitrile agreed reasonably well with the theoretical molecular weight in N,N‐dimethylformamide. The rate of polymerization increased with increasing polymerization temperature, and the apparent activation energy was calculated to be 59.9 kJ mol^?1. Reverse atom transfer radical polymerization was first used to successfully synthesize acrylonitrile polymers with a molecular weight higher than 80,000 and a narrow polydispersity as low as 1.22. © 2005 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 44: 219–225, 2006     

Mathematical modeling of crystallization analysis fractionation (Crystaf) of polyethylene

Four polyethylene samples (PE) with different molecular weight distributions (MWD) were analyzed by crystallization analysis fractionation (Crystaf) at several cooling rates to investigate the effect of MWD and cooling rate on their Crystaf profiles. Using these results, we developed a mathematical model for Crystaf that considers crystallization kinetic effects, which are ignored in all previous Crystaf models. The Crystaf model we proposed can fit the experimental Crystaf profiles of the 4 polyethylene resins very well. © 2006 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 44: 2749–2759, 2006     

On degeneracy and collapsing in the construction of the set of objective values in a multiple objective linear program

In this paper an algorithm is developed to generate all nondominated extreme points and edges of the set of objective values of a multiple objective linear program. The approach uses simplex tableaux but avoids generating unnecessary extreme points or bases of extreme points. The procedure is based on, and improves, an algorithm Dauer and Liu developed for this problem. Essential to this approach is the work of Gal and Kruse on the neighborhood problem of determining all extreme points of a convex polytope that are adjacent to a given (degenerate) extreme point of the set. The algorithm will incorporate Gal's degeneracy graph approach to the neighborhood problem with Dauer's objective space analysis of multiple objective linear programs.     

A minimum average risk approach to shrinkage estimators of the normal mean

For the problem of estimating the normal mean based on a random sample X ₁,...,X _n when a prior value ₀ is available, a class of shrinkage estimators % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqdbaGafqiVd0MbaKaaaaGccaqGGaGaaiikaiaa% dUgacaGGPaGaeyypa0Jaam4AaiaacIcadaqfqaqabKqaahaacaqGUb% aaleqaneaacaqGubaaaOGaaiykaiaabccadaqfqaqabKqaahaacaWG% UbaaleqaneaaceqGybGbaebaaaGccaqGGaGaey4kaSIaaeiiaiaacI% cacaaIXaGaaeiiaiabgkHiTiaabccacaWGRbGaaiikamaavababeqc% baCaaiaab6gaaSqab0qaaiaabsfaaaGccaGGPaGaaiykamaavababe% qcbaCaaiaad6gaaSqab0qaaiabeY7aTbaaaaa!5615!\[\mathop {\hat \mu }\nolimits_n {\rm{ }}(k) = k(\mathop {\rm{T}}\nolimits_{\rm{n}} ){\rm{ }}\mathop {{\rm{\bar X}}}\nolimits_n {\rm{ }} + {\rm{ }}(1{\rm{ }} - {\rm{ }}k(\mathop {\rm{T}}\nolimits_{\rm{n}} ))\mathop \mu \nolimits_n \] is considered, where % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqcdawaaiaadsfaaaGccaqGGaGaaeypaiaabcca% caWGUbWaaWbaaSqabeaacaaIXaGaai4laiaaikdaaaGccaGGOaWaa0% aaaeaacaWGybaaamaaBaaajeaWbaGaamOBaaWcbeaakiaabccacqGH% sislcaqGGaWaaubeaeqajeaWbaGaaGimaaWcbeqdbaGaaeiVdaaaki% aacMcacaqGGaGaae4laiabeccaGiabeo8aZbaa!4C33!\[\mathop T\nolimits_n {\rm{ = }}n^{1/2} (\overline X _n {\rm{ }} - {\rm{ }}\mathop {\rm{\mu }}\nolimits_0 ){\rm{ /}} \sigma \] and k is a weight function. For certain choices of k, % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqdbaGafqiVd0MbaKaaaaGccaqGGaGaaiikaiaa% dUgacaGGPaaaaa!3CEE!\[\mathop {\hat \mu }\nolimits_n {\rm{ }}(k)\] coincides with previously studied preliminary test and shrinkage estimators. We consider choosing k from a natural non-parametric family of weight functions so as to minimize average risk relative to a specified prior p. We study how, by varying p, the MSE efficiency (relative to \-X) properties of % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqdbaGafqiVd0MbaKaaaaGccaqGGaGaaiikaiaa% dUgacaGGPaaaaa!3CEE!\[\mathop {\hat \mu }\nolimits_n {\rm{ }}(k)\] can be controlled. In the process, a certain robustness property of the usual family of posterior mean estimators, corresponding to the conjugate normal priors, is observed.     

灵芝子实体水溶性多糖的分离和分子量测定

用磷酸盐缓冲液、热水、碱和热碱水分别从灵芝子实体分离出五种水溶性杂多糖ＧＬ１、ＧＬ２、ＧＬ３、ＧＬ４和ＧＬ５．紫外光谱、红外光谱、气相色谱及硫酸咔唑分析结果表明，它们主要由葡聚糖、木糖、甘露糖、半乳糖组成，ＧＬ３、ＧＬ４和ＧＬ５含葡萄糖醛酸．由粘度、光散射和膜渗透压法测定了特性粘度［η］、重均分子量Ｍｗ及数均分子量Ｍｎ，ＧＬ２、ＧＬ３和ＧＬ５多糖的Ｍｗ值分别为１２４×１０４、１２８×１０４和５８×１０４．实验结果表明这些杂多糖含水溶性Ｄ 葡聚糖，并且初步推断，用磷酸盐缓冲液提取出的杂多糖ＧＬ２中包含刚性链β Ｄ 葡聚糖     

α—甲基苯乙烯离子聚合体分子量分布

聚α-甲基苯乙烯-丁二烯-α-甲基苯乙烯嵌段共聚物是一种性能优异的热塑性弹性体。常温下,α-甲基苯乙烯的聚合是在极性添加剂存在下进行的,添加剂的种类,用量及聚合温度不仅影响聚合动力学,尚且影响聚合物分子量及其分布,控制α-甲基苯乙烯聚合速率、