Predictive Modeling and Categorizing Likelihoods of Quarantine Pest Introduction of Imported Propagative Commodities from Different Countries

The present study investigates U.S. Department of Agriculture inspection records in the Agricultural Quarantine Activity System database to estimate the probability of quarantine pests on propagative plant materials imported from various countries of origin and to develop a methodology ranking the risk of country–commodity combinations based on quarantine pest interceptions. Data collected from October 2014 to January 2016 were used for developing predictive models and validation study. A generalized linear model with Bayesian inference and a generalized linear mixed effects model were used to compare the interception rates of quarantine pests on different country–commodity combinations. Prediction ability of generalized linear mixed effects models was greater than that of generalized linear models. The estimated pest interception probability and confidence interval for each country–commodity combination was categorized into one of four compliance levels: “High,” “Medium,” “Low,” and “Poor/Unacceptable,” Using K‐means clustering analysis. This study presents risk‐based categorization for each country–commodity combination based on the probability of quarantine pest interceptions and the uncertainty in that assessment.     

The study of commission rate problem in real-time bidding

This paper studies the commission rate in real-time bidding based on the generalized first-price auction mechanism. Firstly, the equilibrium bidding strategies are provided when there are fixed commission rate and the linear commission rate, which proves that if the there is no reserve price, the expected payment of DSP is not related to the rate of commission. The commission rate affects the equilibrium bidding strategies only. Secondly, this paper shows that if there are the reserve price and the commission, the payment of DSP is increasing on the commission rate. That is, if there is reserve price, the DSP cannot control the increasing of the expected payment by adjusting the equilibrium bidding strategy, when the commission rate increases. Finally, provided that the reserve price and commission rate are exogenous respectively, this paper draws to the conclusion that the conditions of optimal commission rate and the optimal reserve price must be satisfied.     

人民币升值对大连与沈阳上市公司股价的弹性比较

针对人民币汇率变动对股价影响程度的问题,提出了基于弹性构建线性模型的方法,通过计算大连和沈阳各14家上市公司从2005年7月至2007年12月的月度数据,实证结果表明:(1)行业间弹性比较:对所选28家企业按主营业务划分行业,包括11家行业,按照行业间弹性系数对11家行业排序;(2)地区间弹性比较:比较大连和沈阳地区总体加权弹性,得到两地区受汇率变动影响程度的差别。结论为大连地区受汇率升值影响程度高于沈阳地区。     

Daily perceptions of relationship quality with leaders: implications for follower well-being

ABSTRACT

We examined how a key relationship at work, an employee’s relationship with their leader, affects employee daily well-being. In a study of 129 employees across a variety of industries, we examined how follower perceptions of their daily leader–member exchange (LMX) quality across a workweek influenced their well-being (n?=?468 observations). Results provided general support for our hypotheses. Specifically, we found that on days when employees perceived a higher quality LMX relationship with their leader, they were more likely to report a sense of belongingness, which was then positively associated with daily reports of vigor and negatively associated with emotional exhaustion. Lagged analyses showed that perceptions of LMX quality were also negatively associated with reports of emotional exhaustion the following workday suggesting that these effects may persist over time. Finally, we found that day-to-day variation in reports of LMX quality attenuated the beneficial effects of LMX on relatedness and vigor supporting our hypothesis that uncertainty related to resource availability may contribute to a threat mindset focused on resource conservation rather than engagement. Implications and future research on leadership and employee well-being are discussed.     

Partial Ordering and Aging Properties of Order Statistics When the Sample Size is Random: A Brief Review

In many practical situations, order statistics arise naturally with random sample size. In this article, we review results on partial orderings and aging properties of such order statistics. The comparison of order statistics for different sample sizes is also discussed here.     

How to build nomogram for type 2 diabetes using a naïve Bayesian classifier technique

In this study, we introduced a method for building a Bayesian nomogram and proposed an appropriate nomogram for type 2 diabetes (T2D) using data from 13,474 subjects collected from the 2013–2015 Korean National Health and Nutrition Examination Survey (KNHANES) data. We identified risk factors related to T2D, proposed a visual nomogram for T2D from a naïve Bayesian classifier model, and predicted incidence rates. Additionally, we computed confidence intervals for the influence of risk factors (attributes) and verified the proposed Bayesian nomogram using a receiver operating characteristic curve. Finally, we compared logistic regression and the Bayesian nomogram for T2D. The results of the analysis of the T2D data showed that the most influential factor among all attributes in the Bayesian nomogram was age group, and the highest risk factor for T2D incidence was cardiovascular disease. Dyslipidemia and hypertension also had significant impacts on T2D incidence while the effects of sex, smoking status, and employment status were relatively small compared to those of other variables. Using the proposed Bayesian nomogram, we can easily predict the incidence rate of T2D in an individual, and treatment plans can be established based on this information.     

Cystatin C as a predictor of mortality in elderly patients with chronic kidney disease

Background: The prevalence of chronic kidney disease (CKD) in the elderly is high. Serum cystatin C is an accurate marker of kidney function and it also has prognostic utility in CKD patients. The aim of our study was to determine the prediction of serum cystatin C and other markers of kidney function on long-term survival in elderly CKD patients.

Methods: Fifty eight adult Caucasian patients, older than 65 years, without known malignancy, thyroid disease and/or not on steroid therapy were enrolled in the study. In each patient, ⁵¹CrEDTA clearance, serum creatinine, serum cystatin C, and estimated glomerular filtration rate using different equations were determined on the same day and patients were then followed for 11 years or until their death.

Results: The means are as follows: ⁵¹CrEDTA clearance 53.3?±?17.4?ml/min/1.73?m², serum creatinine 1.62?±?0.5?mg/dl, serum cystatin C 1.79?±?0.5?mg/l, Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation 40.1?±?14?ml/min/1.73?m², Berlin Initiative Study 2 (BIS2) equation 38.9?±?10.7?ml/min/1.73?m², full age spectrum (FAS) creatinine equation 43.8?±?13.8?ml/min/1.73?m², FAS cystatin C equation 40.1?±?11.7?ml/min/1.73?m². In the follow up period, 47 (81%) patients died. Cox regression analysis showed different hazard ratios (HRs) for death: for ⁵¹CrEDTA clearance HR 1.022 (95% CI 1.004–1.042; p?=?.015), serum creatinine HR 1.013 (95% CI 1.006–1.019; p?=?.001), serum cystatin C HR 2.028 (95% CI 1.267–3.241; p?=?.003), CKD-EPI creatinine equation HR 1.048 (95% CI 1.019–1.076; p?=?.001), BIS2 equation HR 1.055 (95% CI 1.021–1.088; p?=?.001), FAS creatinine equation HR 1.046 (95% CI 1.017–1.074; p?=?.001), FAS cystatin C equation HR 1.039 (95% CI 1.010–1.071; p?=?.009).

Conclusions: Our results showed the highest HR for serum cystatin C among kidney function markers for prediction of outcome in elderly CKD patients.     

Estimating the Probability of Human Error by Incorporating Component Failure Data from User-Induced Defects in the Development of Complex Electrical Systems

This article proposes a methodology for incorporating electrical component failure data into the human error assessment and reduction technique (HEART) for estimating human error probabilities (HEPs). The existing HEART method contains factors known as error-producing conditions (EPCs) that adjust a generic HEP to a more specific situation being assessed. The selection and proportioning of these EPCs are at the discretion of an assessor, and are therefore subject to the assessor's experience and potential bias. This dependence on expert opinion is prevalent in similar HEP assessment techniques used in numerous industrial areas. The proposed method incorporates factors based on observed trends in electrical component failures to produce a revised HEP that can trigger risk mitigation actions more effectively based on the presence of component categories or other hazardous conditions that have a history of failure due to human error. The data used for the additional factors are a result of an analysis of failures of electronic components experienced during system integration and testing at NASA Goddard Space Flight Center. The analysis includes the determination of root failure mechanisms and trend analysis. The major causes of these defects were attributed to electrostatic damage, electrical overstress, mechanical overstress, or thermal overstress. These factors representing user-induced defects are quantified and incorporated into specific hardware factors based on the system's electrical parts list. This proposed methodology is demonstrated with an example comparing the original HEART method and the proposed modified technique.     

个人所得税制度的优化选择

米尔利斯认为非线性的个人所得税是最优化的；斯特恩则根据一些不同的劳动供给函数、财政收入的需要和公平观点，提出了最优线性所得税模型。我们需要重新探讨累进性个人所得税制的合理性；最优税制理论未必适用于发展中国家；个人所得税改革应综合考虑效率与公平两大目标。     

Discrimination analysis when the variates are grouped and observed in sequential order

Suppose that measurements Math', i = l,....,k, are consecutively taken on an individual at the prescribed costs C_i, i = l,....,k. the individual comes from one of the two populations H₁ and H₂, and it is desired to detect which population the individual belongs to. Given the loss incurreed in selecting population H_r when in fact it belongs to H_s, the prior probability P_r of H_r (r = 1,2), and assuming that H_r has the normal distribution N(µ_r, V), r = 1,2, we derive the sequential Bayesian solution of the discrimination problem when µ₁, µ₂ and V are known. When µ_r, V are unknown and must be estimated, we propose a solution which is asymptotic Bayesian with exponential convergence rate.