7,244 research outputs found

    A message from the Associate Dean for Diversity and Community Engagement

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    Diversity: the richness in human differences. Why is diversity important? A wide variety of experiences and points of view mean that we get to look at issues from all angles rather than just one. Inclusion: the active, intentional, and ongoing engagement with diversity. Why is inclusion important? It is not enough to have diversity - inclusion means that we value and cherish the wide variety of experiences and viewpoints. Creating and enhancing this environment is important as we set the stage to provide service to our most important customer - our patients. Since September 2013 when I was appointed as the Associate Dean for Diversity and Community Engagement, SKMC has greatly expanded our efforts in D & I. A wide range of activities have greatly enhanced the environment in which we educate our learners and care for our patients. SKMC has expanded its D & I successes

    Electronic Ticket and Check-in System for Indico Conferences

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    Project Specification: This project should build on the existing participant registration module of Indico and provide additional functionalities for managing the check-in process. While in small conferences it is easy to keep track of participants with a simple paper list, such techniques become inefficient when the need to scale the process up arises. Therefore Indico’s participant registration module would be extended with the functionality to generate electronic tickets. This will allow conference organizers to keep track of attendees after they finish the registration process. As part of this project it is also necessary to develop a mobile application that will be used to scan the electronic tickets, identify the user and mark them as checked in when they arrive at the conference. Additionally Indico’s HTTP API would be extended to be used by the mobile application to retrieve data about conferences and attendees. Abstract: The main goal of this project is to simplify the check-in process for conferences that use the Indico conference management system. This is archived by extending Indico’s core to include electronic ticket generation functionality and developing a mobile application that is used to scan the electronic tickets during the check-in process. Indico’s HTTP API is also extended to provide the mobile application with the necessary data

    Explaining the distribution of manufacturing productivity in the EU regions

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    Regional inequalities in product per capita and labour productivity in the EU are large and persistent. Building on a model in which aggregate increasing returns is the result of the increase in the number of varieties of composite services, under competitive manufactures, we derive a simple and empirically tractable reduced form linking manufacturing productivity growth to the growth of manufacturing output. This specification is used to simulate the equilibrium distribution of labour productivity in the EU regions, that is compared with "virtual" distributions obtained by equalizing, for instance, the amount of returns to scale and the stock of human capital across regions. This way, the impact of some growth determinants on the whole EU regional equilibrium distribution can be assessed.

    High-ISO long-exposure image denoising based on quantitative blob characterization

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    Blob detection and image denoising are fundamental, sometimes related tasks in computer vision. In this paper, we present a computational method to quantitatively measure blob characteristics using normalized unilateral second-order Gaussian kernels. This method suppresses non-blob structures while yielding a quantitative measurement of the position, prominence and scale of blobs, which can facilitate the tasks of blob reconstruction and blob reduction. Subsequently, we propose a denoising scheme to address high-ISO long-exposure noise, which sometimes spatially shows a blob appearance, employing a blob reduction procedure as a cheap preprocessing for conventional denoising methods. We apply the proposed denoising methods to real-world noisy images as well as standard images that are corrupted by real noise. The experimental results demonstrate the superiority of the proposed methods over state-of-the-art denoising methods

    A Message from the Diversity Dean, Dr. Bernard Lopez

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    Welcome to the first newsletter from the Office of Diversity & Inclusion, intended to reach our students, residents, and faculty and spread awareness about diversity initiatives at the Sidney Kimmel Medical College at Thomas Jefferson University

    Physically consistent simulation of transport of inertial particles in porous media

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    A new numerical approach is presented for simulating the movement of test particles suspended in an incompressible fluid flowing through a porous matrix. This two-phase particle-laden flow is based on the Navier-Stokes equations for incompressible fluid flow and equations of motion for the individual particles in which Stokes drag is dominant. The Immersed Boundary method is applied to incorporate the geometric complexity of the porous medium. A symmetry-preserving finite volume discretization method in combination with a volume penalization method resolves the flow within the porous material. The new Lagrangian particle tracking is such that for mass-less test particles no (numerical) collision with the coarsely represented porous medium occurs at any spatial resolution

    Immersed boundary method predictions of shear stresses for different flow topologies occuring in cerebral aneurysms

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    A volume-penalizing immersed boundary method is presented that facilitates the computation of incompressible fluid flow in complex flow domains. We apply this method to simulate the flow in cerebral aneurysms, and focus on the accuracy with which the flow field and the corresponding shear stress field are computed. The method is applied to laminar, incompressible flow in curved cylindrical vessels and in a model aneurysm. The time-dependent shear stress distributions over the vessel walls are visualized and interpreted in terms of the flow fields that develop. We compute shear stress levels at two different Reynolds numbers, corresponding to a steady and an unsteady flow. In the latter situation strong fluctuations in the shear stress are observed, that may be connected to raised risk-levels of aneurysm rupture

    Aortic dissection presenting as gait disturbance: a case report.

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    Emergency medicine dogma traditionally teaches that aortic dissection presents as tearing chest pain, radiating to the back. This case report describes a 55 year old woman presenting with a left homonymous hemianopsia and resultant gait disturbance. Initial head CT demonstrated a right parietal infarct, and chest radiograph demonstrated a markedly widened mediastinum. Acute Stanford Type A aortic dissection was subsequently confirmed. This report provides further evidence for atypical, painless presentations of aortic dissection. Given recent literature on the increasing prevalence of painless dissection, the disease entity should be included in the differential diagnosis for stroke, and a simple portable chest x-ray should always be obtained prior to administering thrombolytics

    On the Role of Context-Awareness in Binary Image Comparison

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    The quantification of image similarity has been a key topic in the computer vision literature for the past few years. Different mathematical theories have been used in the development of these measures, which we will refer to as comparison measures. An interesting aspect in the study of comparison measures is the natural requirement to replicate human behavior. In almost all cases, it is appropriate for a comparison measure to produce results that are consistent with how humans would perform that assessment. However, despite accepting this premise, most of the proposals in the literature ignore a fundamental characteristic of the way in which humans carry out this evaluation: the context of comparison. In this work we present a comparison measure for binary images that incorporates the context of comparison; more precisely, we introduce an approach for the generation of ultrametrics for the context-aware comparison of binary images
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