Relative deprivation as a cause of risky behaviors

ABSTRACT

Combining a standard measure of concern about low relative wealth and a standard measure of relative risk aversion leads to a novel explanation of variation in risk-taking behavior identified and documented by social psychologists and economists. We obtain two results: (1) Holding individual i’s wealth and his rank in the wealth distribution constant, the individual’s relative risk aversion decreases when he becomes more relatively deprived as a result of an increase in the average wealth of the individuals who are wealthier than he is. (2) If relative deprivation enters the individual’s utility function approximately linearly then, holding constant individual i’s wealth and the average wealth of the individuals who are wealthier than he is, the individual’s relative risk aversion decreases when he becomes more relatively deprived as a result of a decline in his rank. Our findings provide a theoretical support for evidence about the propensity of relatively deprived individuals to gamble and resort to other risky behaviors.     

Finite groups with a given number of relative centralizers

We will study all finite groups and their subgroups with at most four relative centralizers.     

Empirical Likelihood Inference for Functional Coefficient ARCH-M Model

Empirical likelihood inference for parametric and nonparametric parts in functional coefficient ARCH-M models is investigated in this paper. Firstly, the kernel smoothing technique is used to estimate coefficient function δ(x). In this way we obtain an estimated function with parameter β.Secondly, the empirical likelihood method is developed to estimate the parameter β. An estimated empirical log-likelohood ratio is proved to be asymptotically standard chi-squred, and the maximum empirical likelihood estimation(MELE) for β is shown to be asymptotically normal. Finally, based on the MELE of β, the empirical likelihood approach is again applied to reestimate the nonparametric part δ(x). The empirical log-likelohood ratio for δ(x) is proved to be also asymptotically standard chi-squred. Simulation study shows that the proposed method works better than the normal approximation method in terms of average areas of confidence regions for β, and the empirical likelihood confidence belt for δ(x) performs well.     

Tutorial review on validation of liquid chromatography–mass spectrometry methods: Part II

This is the part II of a tutorial review intending to give an overview of the state of the art of method validation in liquid chromatography mass spectrometry (LC–MS) and discuss specific issues that arise with MS (and MS–MS) detection in LC (as opposed to the “conventional” detectors). The Part II starts with briefly introducing the main quantitation methods and then addresses the performance related to quantification: linearity of signal, sensitivity, precision, trueness, accuracy, stability and measurement uncertainty. The last section is devoted to practical considerations in validation. With every performance characteristic its essence and terminology are addressed, the current status of treating it is reviewed and recommendations are given, how to handle it, specifically in the case of LC–MS methods.     

Power of isotopic fine structure for unambiguous determination of metabolite elemental compositions: In silico evaluation and metabolomic application

In mass spectrometry (MS)-based metabolomics studies, reference-free identification of metabolites is still a challenging issue. Previously, we demonstrated that the elemental composition (EC) of metabolites could be unambiguously determined using isotopic fine structure, observed by ultrahigh resolution MS, which provided the relative isotopic abundance (RIA) of ¹³C, ¹⁵N, ¹⁸O, and ³⁴S. Herein, we evaluated the efficacy of the RIA for determining ECs based on the MS peaks of 20,258 known metabolites. The metabolites were simulated with a ≤25% error in the isotopic peak area to investigate how the error size effect affected the rate of unambiguous determination of the ECs. The simulation indicated that, in combination with reported constraint rules, the RIA led to unambiguous determination of the ECs for more than 90% of the tested metabolites. It was noteworthy that, in positive ion mode, the process could distinguish alkali metal-adduct ions ([M + Na]⁺ and [M + K]⁺). However, a significant degradation of the EC determination performance was observed when the method was applied to real metabolomic data (mouse liver extracts analyzed by infusion ESI), because of the influence of noise and bias on the RIA. To achieve ideal performance, as indicated in the simulation, we developed an additional method to compensate for bias on the measured ion intensities. The method improved the performance of the calculation, permitting determination of ECs for 72% of the observed peaks. The proposed method is considered a useful starting point for high-throughput identification of metabolites in metabolomic research.     

Contractivity results in ordered spaces. Applications to relative operator bounds and projections with norm one

This paper provides various “contractivity” results for linear operators of the form where C are positive contractions on real ordered Banach spaces X . If A generates a positive contraction semigroup in Lebesgue spaces , we show (M. Pierre's result) that is a “contraction on the positive cone ”, i.e. for all provided that .  We show also that this result is not true for 1 ⩽ . We give an extension of M. Pierre's result to general ordered Banach spaces X under a suitable uniform monotony assumption on the duality map on the positive cone . We deduce from this result that, in such spaces, is a contraction on for any positive projection C with norm 1. We give also a direct proof (by E. Ricard) of this last result if additionally the norm is smooth on the positive cone. For any positive contraction C on base‐norm spaces X (e.g. in real spaces or in preduals of hermitian part of von Neumann algebras), we show that for all where N is the canonical half‐norm in X . For any positive contraction C on order‐unit spaces X (e.g. on the hermitian part of a algebra), we show that is a contraction on . Applications to relative operator bounds, ergodic projections and conditional expectations are given.     

Rapid separation and simultaneous quantitative determination of 13 constituents in Psoraleae Fructus by a single marker using high‐performance liquid chromatography with diode array detection

Psoraleae Fructus is one of the most popular traditional Chinese medicines. Coumarins, flavonoids, and meroterpenes are the main contributors to the biological activity of Psoraleae Fructus. In this study, a new method for the quality control of Psoraleae Fructus was developed, through the quantitative analysis of multicomponents by single marker with diode array detector. Thirteen components, including psoralenoside, isopsoralenoside, psoralen, isopsoralen, psoralidin, neobavaisoflavone, bavachin, corylin, isobavachalcone, corylifol A, bavachinin, bavachalcone, and bakuchiol were rapidly separated and identified within 12 min by the newly developed method. The feasibility and reliability of this method were corroborated. The method was also compared to the external standard method and detection by corona charged aerosol detector. The results of percent difference (%) and cos (θ) have shown that there were no significant differences observed between the quantitative analysis of multicomponents by single marker and external standard method analyses; psoralen and isopsoralen were undetectable with the corona charged aerosol detector due to their but the sensitivity for all the compounds except bakuchiol detected by corona charged aerosol detector are higher than those obtained by diode array detector. In addition, the newly method developed was applied to the quality evaluation of Chinese patent medicines containing Psoraleae Fructus.     

用指数型整函数的最佳限制逼近

我们研究了由仅有实零点的代数多项式导出的微分算子确定的广义Sobolev类利用指数型整函数作为逼近工具的最佳限制逼近问题.利用Fourier变换和周期化等方法,得到在L_2(R)范数下的广义Sobolev光滑函数类的相对平均宽度和最佳限制逼近的精确常数,以及当0是这个代数多项式的一个至多2重的零点时,得到最佳限制逼近在L_1(R)范数和一致范数下的广义Sobolev类的精确到阶的结果.     

聚集数据线性模型广义聚集双参数估计的相对效率

对于聚集数据的线性模型,提出了广义聚集双参数估计的概念,给出了广义聚集双参数估计的两种相对效率,并得到了这两种相对效率的上界.     

一类奇异非线性多重调和方程存在正整解的充分必要条件

研究一类奇异非线性多重调和方程?~mu=f(|x|,u,|▽u|)u~(-β),给出了方程存在正的径向对称整体解的充分必要条件和解的性质.