State estimation for nonlinear state-space transmission models of tuberculosis

Given the high prevalence of tuberculosis (TB) and the mortality rate associated with the disease, numerous models, such as the Gammaitoni and Nucci (GN) model, were developed to model the risk of transmission. These models typically rely on a quanta generation rate as a measurement of infectivity. Since the quanta generation rate cannot be measured directly, the unique contribution of this work is to develop state estimators to estimate the quanta generation rate from available measurements. To estimate the quanta generation rate, the GN model is adapted into an augmented single-room GN model and a simplified two-room GN model. Both models are shown to be observable, i.e., it is theoretically possible to estimate the quanta generation rate given available measurements. Kalman filters are used to estimate the quanta generation rate. First, a continuous-time extended Kalman filter is used for both adapted models using a simulation and measurement sampling rate of 60 s. Accurate quanta generate rate estimates are achieved in both cases. A more realistic scenario is also considered with a measurement sampling rate of one day. For these estimates, a hybrid extended Kalman filter (HEKF) is used. Accurate quanta generation rate estimates are achieved for the more realistic scenario. Future work could potentially use the HEKFs, the adapted models, and real-time measurements in a control system feedback loop to reduce the transmission of TB in confined spaces such as hospitals.     

最低收购价政策对我国稻谷市场价格预期的影响研究

稻谷最低收购价是我国粮食价格支持政策的重要措施。2004年以来，政策实施的基本目标围绕稳定国内粮食生产、保障国内粮食安全展开，其关键在于把握最低收购价格形成的市场预期效应。基于早、中、晚籼稻和粳稻的省级数据，采用面板估计方法分析稻谷最低收购价格在不同区域和时期对其市场价格预期的影响。研究发现：（1）无论在非政策执行区，还是政策执行区的非执行期内，稻谷最低收购价均有助于形成积极的市场预期，但其影响在非执行区弱于前1期市场价格的影响，而在执行区强于前1期市场价格的影响。（2）在政策执行区的执行期内，基于最低收购价格的托市效应，前1期市场价格对预期的价格差额（市场价格与最低收购价的预期差额）具有正向影响，最低收购价格则呈负向影响。因此，最低收购价格政策的改革应围绕政策执行目标充分考虑未来政策改革对市场预期的冲击。     

Using a hybrid data collection tool: Analysis of youth labour market trajectories integrating quantitative,qualitative and social network data

This article explains the factors that led to the use of a hybrid data collection tool—i.e., a single questionnaire designed to collect both quantitative and qualitative data—in two different research projects that focused on the relation between the labour market trajectories of young people and the use and accumulation of network social capital in these trajectories. The article describes the characteristics of this tool and the methodological challenges posed by its use. The advantages and disadvantages of this specific type of data collection are also addressed. Among the main advantages, the improvement of data quality and the overarching picture obtained of the career path and use of personal networks are highlighted. The most important downside found is the amount of time needed in the interview, which shows the need to pay attention to the balance between quantitative and qualitative elements in the structure of the questionnaire.     

当代新闻叙事的“受众转向”及其“诗学功能”的生成

伴随着新媒体的崛起，普通人参与媒介叙述的潜能得到释放，受众在新闻叙事中的主体性得到彰显。从公共新闻到公民新闻的发展，使受众的新闻叙述控制权得到扩张。新媒体环境下普通受众参与的互动叙述从不同角度延伸新闻故事的情节线，使之成为一个开放性文本。“受众叙述”所具备的动态生成的特性，导致文本边界趋于消解，由此建构了新闻叙事的“全文本”。受众以“游猎”姿态展开新闻叙述，对主流媒体的新闻文本进行挪用、拼贴和戏仿，生成具有“杂交”性质的叙述文本，成为当下年轻世代新闻消费的“间接化”与“娱乐化”的重要表征。作为一种“生产者式文本”，受众叙述不再受制于新闻类别的“常规”，为新闻“诗学功能”的实现提供了更多可能，并在集体意义建构中发挥重要作用。     

策略性补偿下混合渠道下游企业创新激励研究

电子商务环境下,以创新降低物流和库存等分销成本是零售商赢得生存与发展的重要途径,在渠道和谐和利润最大化的双重驱使下,策略性创新补偿成为制造商的首选策略.针对传统零售渠道与在线直销渠道的价格竞争,利用Stackelberg博弈,研究创新投入及其策略性补偿对混合渠道供应链的影响.结果表明,当零售商以创新投入降低其物流和库存等边际分销成本时,制造商将维持批发价和在线直销价不变,零售商将降低传统零售价,制造商和零售商的利润都得到改进;当制造商对零售商实施一定补偿以激励零售商进行更大的创新投入时,制造商将提高批发价并维持在线直销价不变,零售商将降低其零售价并增加创新投入,制造商和零售商的利润将得到进一步改善.因此,创新投入及其策略性补偿能实现混合渠道成员收益的Pareto改进.     

Bayesian neural tree models for nonparametric regression

Frequentist and Bayesian methods differ in many aspects but share some basic optimal properties. In real-life prediction problems, situations exist in which a model based on one of the above paradigms is preferable depending on some subjective criteria. Nonparametric classification and regression techniques, such as decision trees and neural networks, have both frequentist (classification and regression trees (CARTs) and artificial neural networks) as well as Bayesian counterparts (Bayesian CART and Bayesian neural networks) to learning from data. In this paper, we present two hybrid models combining the Bayesian and frequentist versions of CART and neural networks, which we call the Bayesian neural tree (BNT) models. BNT models can simultaneously perform feature selection and prediction, are highly flexible, and generalise well in settings with limited training observations. We study the statistical consistency of the proposed approaches and derive the optimal value of a vital model parameter. The excellent performance of the newly proposed BNT models is shown using simulation studies. We also provide some illustrative examples using a wide variety of standard regression datasets from a public available machine learning repository to show the superiority of the proposed models in comparison to popularly used Bayesian CART and Bayesian neural network models.     

不充分就业感知对员工兼职创业投入的影响机制研究

基于情感-认知评价的理论视角,在控制了工作满意度路径之后,通过对311名兼职创业者的实证数据进行分析,探究了员工不充分就业感知的两个维度——资质过剩感和成长缺乏感对员工兼职创业投入的作用机理。研究结果表明:资质过剩感、成长缺乏感以及两者的交互作用会强化员工与本职工作的疏离感;工作疏离感正向影响员工兼职创业投入;工作疏离感在资质过剩感、成长缺乏感及其交互作用对兼职创业投入的影响中发挥了中介作用。