An interprofessional, intercultural, immersive short-term study abroad program: public health and service systems in rome

The purpose of this paper is to describe a short-term study abroad program that exposes engineering and nursing undergraduate students from the United States and Italy to an intercultural and interprofessional immersion experience. Faculty from Purdue University and Sapienza Università di Roma collaborated to design a technical program that demonstrates the complementary nature of engineering and public health in the service sector, with Rome as an integral component of the program. Specifically, the intersection of topics including systems, reliability, process flow, maintenance management, and public health are covered through online lectures, in-class activities and case study discussions, field experiences, and assessments. Herein, administrative issues such as student recruitment, selection, and preparation are elucidated. Additionally, the pedagogical approach used to ensure constructive alignment among the program goals, the intended learning outcomes, and the teaching and learning activities is described. Finally, examples of learning outcomes resulting from this alignment are provided

Strategies for designing transformable production networks

The effective design of a production network has a significant impact on the continued success of any manufacturing company, especially those that produce many products across numerous facilities. The production network design problem is composed of two distinct phases which are traditionally considered separately. The first phase is the location of facilities and the sourcing of products to the facilities. In the case where facilities already exist the first phase is just the sourcing of products to these facilities. Once products have been allocated to the facilities each facility can be designed. The specific sourcing of products to a facility is the major determinant of the production system design, and therefore, the overall facility design. By considering the sourcing of products and the facility design separately, there is the potential for facility designs that do not take advantage of efficient production system designs. Therefore, there is a natural trade-off that exists between product sourcing and facility design, especially when the facility is capable of transformation. Products should be sourced to facilities closest to their demand sources to minimize shipping costs, but should be also be located in a facility best equipped to produce efficiently. It may not always be the case where the same facility satisfies both desires. Furthermore, traditional modeling techniques do not make provision for the simultaneous consideration of product sourcing and production system design. Furthermore, since consumer demand changes frequently the ability of a production network to adapt to changes must be studied. Such a production network is classified as a transformable production network. A transformable production network is one where each facility within the network is capable of being redesigned regularly, and that resources can be shared among the facilities, as needed, to cope with changes in customer demand. In this research, the production network design problem is studied. A general model is developed for the static production network design problem that assumes a functional layout structure at each facility. An example case is generated and solved which illustrate the usage of the model. An additional static production network design model is developed to consider cellular layout structure at each facility. This model is an improvement on a previous (and, to the author, only known) production network design model. In addition, the model is extended to the time-domain to allow for network transformability. This research presents the first production network design models considering functional layout structure (for both static and time-dependent cases). In addition, a strategy for improving the machine layout problem (MLP) is developed based on the concept of variable bounding. It is well known that the MLP is a hard problem to solve due to its combinatorial and nonlinear structure. This is especially true when there is no assumption made of the facility design in which the machines are to be arranged. The bounding scheme is developed in the context of the single-row machine layout problem and extended to two dimensions. The developed bound is tighter than previously existing bounds. Statistical tests were performed on two different formulations for the MLP and the bounding scheme does not significantly reduce time to solution for the MLP; however, the majority of test cases experienced a reduction in time to solution

Predictive factors of diagnostic accuracy of CT-guided transthoracic fine-needle aspiration for solid noncalcified, subsolid and mixed pulmonary nodules

Purpose: The aim of this study was to analyse factors predicting the diagnostic accuracy of computed tomography (CT)-guided transthoracic fine-needle aspiration (TTFNA) for solid noncalcified, subsolid and mixed pulmonary nodules, with particular attention to those responsible for false negative results with a view to suggesting a method for their correction. Materials and methods: From January 2007 to March 2010, we retrospectively reviewed the CT images of 198 patients of both sexes (124 males and 74 females; mean age, 70 years; range age, 44-90) used for the guidance of TTFNA of pulmonary nodules. Aspects considered were: lesion size and density, distance from the pleura, and lesion site. Multiplanar reformatted images (MPR) were retrospectively obtained in the sagittal and axial oblique planes relative to needle orientation. Results: The overall diagnostic accuracy of TTFNA CTguided biopsy was 86% for nodules between 0.7 and 3 cm, 83.3% for those between 0.7 and 1.5 cm, and 92% for those between 2 and 3 cm. Accuracy was 95.1% for solid pulmonary nodules, 84.6% for mixed nodules, and 66.6% for subsolid nodules. The diagnostic accuracy of CT-guided TTFNA in relation to the distance between the nodule and the pleural plane was 95.6% for lesions adhering to the pleura and 83.5% for central ones. The diagnostic accuracy was 84.2% for the pulmonary upper lobe nodules, 85.3% for the lower lobe and 90.9% for those in the lingula and middle lobe. In 75% of false negative and inadequate/insufficient cases the needle was found to lie outside the lesion, after reconstruction of the needle path by MPR. Conclusions: The positive predictive factors of CT-guided TTFNA are related to the nodule size, density and distance from the pleural plane. The most common negative predictive factor of CT-guided TTFNA is the wrong position of the needle tip, as observed in the sagittal and axial oblique sections of the MPR reconstructions. The diagnostic accuracy of CT-guided TTFNA can therefore be improved by using the MPR technique to plan the needle path during the FNA procedure