Incorporating Time‐Dose‐Response into Legionella Outbreak Models

A novel method was used to incorporate in vivo host–pathogen dynamics into a new robust outbreak model for legionellosis. Dose‐response and time‐dose‐response (TDR) models were generated for Legionella longbeachae exposure to mice via the intratracheal route using a maximum likelihood estimation approach. The best‐fit TDR model was then incorporated into two L. pneumophila outbreak models: an outbreak that occurred at a spa in Japan, and one that occurred in a Melbourne aquarium. The best‐fit TDR from the murine dosing study was the beta‐Poisson with exponential‐reciprocal dependency model, which had a minimized deviance of 32.9. This model was tested against other incubation distributions in the Japan outbreak, and performed consistently well, with reported deviances ranging from 32 to 35. In the case of the Melbourne outbreak, the exponential model with exponential dependency was tested against non‐time‐dependent distributions to explore the performance of the time‐dependent model with the lowest number of parameters. This model reported low minimized deviances around 8 for the Weibull, gamma, and lognormal exposure distribution cases. This work shows that the incorporation of a time factor into outbreak distributions provides models with acceptable fits that can provide insight into the in vivo dynamics of the host‐pathogen system.     

The Role of Innovation Characteristics and Perceived Voluntariness in the Acceptance of Information Technologies

The often paradoxical relationship between investment in information technology and gains in productivity has recently been attributed to a lack of user acceptance of information technology innovations. Diverse streams of research have attempted to explain and predict user acceptance of new information technologies. A common theme underlying these various research streams is the inclusion of the perceived characteristics of an innovation as key independent variables. Furthermore, prior research has utilized different outcomes to represent user acceptance behavior. In this paper we focus on individual's perceptions about the characteristics of the target technology as explanatory and predictive variables for acceptance behavior, and present an empirical study examining the effects of these perceptions on two frequently used outcomes in the context of the innovation represented by the World Wide Web. The two outcomes examined are initial use of an innovation and intentions to continue such use in the future, that is, to routinize technology use. Two research questions motivated and guided the study. First, are the perceptions that predict initial use the same as those that predict future use intentions? Our results confirm, as hypothesized by prior research, that innovation characteristics do explain acceptance behavior. The results further reveal that the specific characteristics that are relevant for each acceptance outcome are different. The second research question asks if perceived voluntariness plays a role in technology acceptance. Results show that external pressure has an impact on adopters' acceptance behavior. Theoretical and practical implications that follow are presented.     

An efficient and fast algorithm for estimating the parameters of two-dimensional sinusoidal signals

In this paper we propose a computationally efficient algorithm to estimate the parameters of a 2-D sinusoidal model in the presence of stationary noise. The estimators obtained by the proposed algorithm are consistent and asymptotically equivalent to the least squares estimators. Monte Carlo simulations are performed for different sample sizes and it is observed that the performances of the proposed method are quite satisfactory and they are equivalent to the least squares estimators. The main advantage of the proposed method is that the estimators can be obtained using only finite number of iterations. In fact it is shown that starting from the average of periodogram estimators, the proposed algorithm converges in three steps only. One synthesized texture data and one original texture data have been analyzed using the proposed algorithm for illustrative purpose.     

Supplies from developing countries: Optimal order quantities under loss risks

When raw material suppliers of a global supply chain are situated in developing countries, not only will there be long lead times but there could also be a possibility of material losses in transit. The magnitude of the losses will be uncertain and can be significant. We consider the optimization of order quantity decisions in such situations. The long lead times imply that we need to take into account the uncertainty in finished goods demands for which the raw materials are to be ordered. The order quantities have to be optimized carefully as they determine the “real options” that become available later in production plans. Using data from the plywood industry and using stochastic programming we demonstrate a method for solving such problems. The method combines simulation and optimization. An interesting observation we make is that the optimal order quantity of a material need not be monotonic in expected loss of that material. In addition, we offer explanations as to why the expected loss need not be monotonic.     

Beyond the mirror towards a plurilingual prism: exploring the creation of plurilingual ‘identity texts’ in English and French classrooms in Toronto and Montpellier

In an age of transnational mobility, there has been a growing recognition of the need for both English and French mainstream classroom teachers to be trained to teach increasingly plurilingual student populations. In this article, I begin by describing the context for an exploratory comparative and collaborative ethnographic action research study in four English and French schools in Toronto, Canada and one school in Montpellier, France that engaged children as co-researchers of their lived plurilingualism. I analyse in particular the process of creating plurilingual multimodal books with students and teachers across the five different school cases. This paper focuses on the iterative ‘identity text’ creation process across all five schools by examining one plurilingual identity text from each case, along with students’ research conversations about their creative productions, and interviews with their classroom teachers and parents. Finally, I summarize five features of inclusive plurilingual pedagogy that emerged across the five cases and call for further collaborative research across English and French schools and scholarly communities investigating creative plurilingual language and literacy production in the twenty-first century.     

Non-parametric recursive estimates of a probability density function and its derivatives

Recursive estimates of a probability density function (pdf) are known. This paper presents recursive estimates of a derivative of any desired order of a pdf. Let f be a pdf on the real line and p?0 be any desired integer. Based on a random sample of size n from f, estimators f^(p)_n of f^(p), the pth order derivatives of f, are exhibited. These estimators are of the form $\text{n}{}^{\mathrm{?1}}\text{∑n}\text{j=1}\text{δ}{}_{\mathrm{jp}}$, where δ_jp depends only on p and the jth observation in the sample, and hence can be computed recursively as the sample size increases. These estimators are shown to be asymptotically unbiased, mean square consistent and strongly consistent, both at a point and uniformly on the real line. For pointwise properties, the conditions on f^(p) have been weakened with a little stronger assumption on the kernel function.     

Additive risks regression model for middle censored exponentiated-exponential lifetime data

Jammalamadaka and Mangalam introduced middle censoring which refers to data arising in situations, where the exact lifetime becomes unobservable if it falls within a random censoring interval. In the present article, we propose an additive risks regression model for a lifetime data subject to middle censoring, where the lifetimes are assumed to follow exponentiated exponential distribution. The regression parameters are estimated using the Expectation-Maximization algorithm. Asymptotic normality of the estimator is proposed. We report a simulation study to assess the finite sample properties of the estimator. We then analyze a real-life data on survival times of larynx cancer patients studied by Karduan.     

Prevalence of job strain among Indian foundry shop floor workers

Global competition in manufacturing sector demand higher productivity levels. In this context, workers in this sector are set with high output targets, leading to job strain. In addition to the strain, hazardous conditions also prevail in some of the manufacturing processes like foundry activities. This paper attempts to appraise the prevalence of job strain among foundry shop floor workers in India with the help of Demands-Control model [8]. In this study, data was collected through a survey using 49-item Job Content Questionnaire (JCQ) [9], a widely used and well-validated test for job strain. Then the data was subjected to statistical analysis after ascertaining the reliability. This survey has revealed that 25% of workers in foundry were experiencing high job strain. Hazardous working conditions, limited decision making authority, etc. appear to be the main contributing factors for the higher levels of strain.     

Lead Time and Price Quotation Mode Selection: Uniform or Differentiated?

Firms in service and make‐to‐order manufacturing industries often quote lead times and prices to customers. We define uniform quotation mode (UQM) as the strategy where a firm offers a single lead time and price quotation, and differentiated quotation mode (DQM) is where a firm offers a menu of lead times and prices for customers to choose from. Both modes are followed in practice. Firms should determine which is more profitable. We classify customers into two groups: lead time sensitive (LS) and price sensitive (PS). LS customers value lead time reduction more than PS customers. We develop mathematical models of both quotation modes and analyze them to determine the most profitable mode under specified situations as well as the best lead time and price quotations within each mode. We find that DQM is dominated by UQM whenever PS customers have positive utilities from UQM or LS customers have positive utilities from DQM. Otherwise, which quotation mode is better depends on multiple factors, such as customer characteristics (including lead time reduction valuation and product valuation of a customer, and the proportion of LS customers) and production characteristics (including the desired service level and service or production cost).     

A comparison of model selection criteria

There has been significant new work published recently on the subject of model selection. Notably Rissanen (1986, 1987, 1988) has introduced new criteria based on the notion of stochastic complexity and Hurvich and Tsai(1989) have introduced a bias corrected version of Akaike's information criterion. In this paper, a Monte Carlo study is conducted to evaluate the relative performance of these new model selection criteria against the commonly used alternatives. In addition, we compare the performance of all the criteria in a number of situations not considered in earlier studies: robustness to distributional assumptions, collinearity among regressors, and non-stationarity in a time series. The evaluation is based on the number of times the correct model is chosen and the out of sample prediction error. The results of this study suggest that Rissanen's criteria are sensitive to the assumptions and choices that need to made in their application, and so are sometimes unreliable. While many of the criteria often perform satisfactorily, across experiments the Schwartz Bayesian Information Criterion (and the related Bayesian Estimation Criterion of Geweke-Meese) seem to consistently outperfom the other alternatives considered.