A 21st century technique for food control: Electronic noses

This work examines the main features of modern electronic noses (e-noses) and their most important applications in food control in this new century. The three components of an electronic nose (sample handling system, detection system, and data processing system) are described. Special attention is devoted to the promising mass spectrometry based e-noses, due to their advantages over the more classical gas sensors. Applications described include process monitoring, shelf-life investigation, freshness evaluation, authenticity assessment, as well as other general aspects of the utilization of electronic noses in food control. Finally, some interesting remarks concerning the strengths and weaknesses of electronic noses in food control are also mentioned.     

A complementary mobile phase approach based on the peak count concept oriented to the full resolution of complex mixtures

Situations of minimal resolution are often found in liquid chromatography, when samples that contain a large number of compounds, or highly similar in terms of structure and/or polarity, are analysed. This makes full resolution with a single separation condition (e.g., mobile phase, gradient or column) unfeasible. In this work, the optimisation of the resolution of such samples in reversed-phase liquid chromatography is approached using two or more isocratic mobile phases with a complementary resolution behaviour (complementary mobile phases, CMPs). Each mobile phase is dedicated to the separation of a group of compounds. The CMPs are selected in such a way that, when the separation is considered globally, all the compounds in the sample are satisfactorily resolved. The search of optimal CMPs can be carried out through a comprehensive examination of the mobile phases in a selected domain. The computation time of this search has been reported to be substantially reduced by application of a genetic algorithm with local search (LOGA). A much simpler approach is here described, which is accessible to non-experts in programming, and offers solutions of the same quality as LOGA, with a similar computation time. The approach makes a sequential search of CMPs based on the peak count concept, which is the number of peaks exceeding a pre-established resolution threshold. The new approach is described using as test sample a mixture of 30 probe compounds, 23 of them with an ionisable character, and the pH and organic solvent contents as experimental factors.     

Triad count estimation in digraphs

One may use information about a random sample of network members to estimate quantities related to the triad census of a network. Various kinds of information about the graph may be observable from the sample; four observation schemes involving the local networks of the sampled vertices are considered here. Unbiased triad count estimators are defined, and their variances (and unbiased estimators of these variances) are derived. A main result is that under one of the observation schemes, the estimator can be written as a sum of vertex attributes; standard estimation formulas for various sampling designs, such as stratified sampling, are therefore effortlessly applied. The estimator properties are compared in a simulation study.     

跳跃扩散过程的期权定价模型

假定股票价格的跳过程为计数过程,建立了股票价格服从跳扩散过程的行为模型.运用随机分析中的鞅方法,推导出了股票价格的跳过程为计数过程的欧式期权定价公式,推广了已有的结果.     

利用计数统计模型方法评价大连星海公园旅游的经济价值

在非市场条件下如何评价旅游资源的经济价值是自然旅游公园管理工作中所面临的一个重要问题.正确地估计这类公园的旅游需求函数则是对其有效地进行经济价值评价的关键.由于旅游次数数据具有非负整数和截断的性质,使用传统的多元线性回归模型来估计旅游需求函数则会产生较大的偏差.因此。本文采用非线性最小二乘、截断泊松分布和截断负二项分布等计量经济学模型估计大连星海公园的旅游需求函数,以此来计算公园旅游的经济价值。     

Bayesian total loss estimation using shared random effects

The pricing of insurance policies requires estimates of the total loss. The traditional compound model imposes an independence assumption on the number of claims and their individual sizes. Bivariate models, which model both variables jointly, eliminate this assumption. A regression approach allows policy holder characteristics and product features to be included in the model. This article presents a bivariate model that uses joint random effects across both response variables to induce dependence effects. Bayesian posterior estimation is done using Markov Chain Monte Carlo (MCMC) methods. A real data example demonstrates that our proposed model exhibits better fitting and forecasting capabilities than existing models.     

基于零膨胀模型的我国银企关系规模影响因素研究

银企关系是学术界和实务界关注的焦点之一,然而,国内学者鲜有探讨银企关系数量的影响因素。本文使用我国A股上市公司2006-2013年的银企关系计数资料,利用零膨胀模型对企业建立银企关系规模的影响因素进行了分析。研究发现:规模大、资产负债率高、获利能力强的公司倾向于建立更多的银企关系;企业的长期负债率、第一大股东持股比例,是否是国有产权属性和企业的经营风险与银企关系的规模(数量)显著负相关;信贷合约的期限和信贷金额与银企关系的数量显著正相关;进一步比较了零膨胀模型与Poisson回归、负二项分布回归模型等计数模型,统计检验显示,零膨胀模型比较适合零值过多和过度离散的数据结构资料。