A Lagrangian approach for modeling road collisions using second-order models of traffic flow

In [M. Herty, A. Klein, S. Moutari, V. Schleper, and G. Steinaur, IMA J. Appl. Math., 78(5), 1087–1108, 2013] and [M. Herty and V. Schleper, ZAMM J. Appl. Math. Mech., 91, 763–776, 2011], a macroscopic approach, derived from fluid-dynamics models, has been introduced to infer traffic conditions prone to road traffic collisions along highways’ sections. In these studies, the governing equations are coupled within an Eulerian framework, which assumes fixed interfaces between the models. A coupling in Lagrangian coordinates would enable us to get rid of this (not very realistic) assumption. In this paper, we investigate the well-posedness and the suitability of the coupling of the governing equations within the Lagrangian framework. Further, we illustrate some features of the proposed approach through some numerical simulations.

Complexity of Inferences in Polytree-shaped Semi-Qualitative Probabilistic Networks

Semi-qualitative probabilistic networks (SQPNs) merge two important graphical model formalisms: Bayesian networks and qualitative probabilistic networks. They provide a very general modeling framework by allowing the combination of numeric and qualitative assessments over a discrete domain, and can be compactly encoded by exploiting the same factorization of joint probability distributions that are behind the Bayesian networks. This paper explores the computational complexity of semi-qualitative probabilistic networks, and takes the polytree-shaped networks as its main target. We show that the inference problem is coNP-Complete for binary polytrees with multiple observed nodes. We also show that inferences can be performed in linear time if there is a single observed node, which is a relevant practical case. Because our proof is constructive, we obtain an efficient linear time algorithm for SQPNs under such assumptions. To the best of our knowledge, this is the first exact polynomial-time algorithm for SQPNs. Together these results provide a clear picture of the inferential complexity in polytree-shaped SQPNs.

Semi-Qualitative Probabilistic Networks in Computer Vision Problems

This paper explores the application of semi-qualitative probabilistic networks (SQPNs) that combine numeric and qualitative information to computer vision problems. Our version of SQPN allows qualitative influences and imprecise probability measures using intervals. We describe an Imprecise Dirichlet model for parameter learning and an iterative algorithm for evaluating posterior probabilities, maximum a posteriori and most probable explanations. Experiments on facial expression recognition and image segmentation problems are performed using real data.

Belief Updating and Learning in Semi-Qualitative Probabilistic Networks

This paper explores semi-qualitative probabilistic networks (SQPNs) that combine numeric and qualitative information. We first show that exact inferences with SQPNs are NPPP-Complete. We then show that existing qualitative relations in SQPNs (plus probabilistic logic and imprecise assessments) can be dealt effectively through multilinear programming. We then discuss learning: we consider a maximum likelihood method that generates point estimates given a SQPN and empirical data, and we describe a Bayesian-minded method that employs the Imprecise Dirichlet Model to generate set-valued estimates.

Semi-interpenetrating polymer networks incorporating polygalacturonic acid for medical device applications

Background Over 20 million people in the US are living with an implantable medical device [ADDIN RW.CITE{{3114 Higgins,DavidM 2009}}1], with similar figures anticipated for Europe. Complications in the use of medical implants include the Foreign Body Response (FBR) characterised by macrophage adherence and fusion, and device-related infection due to bacterial biofilm formationADDIN RW.CITE{{3124 Harding,JacquelineL 2014}}2. Both can have detrimental consequences on the structural and functional integrity of the medical device [ADDIN RW.CITE{{3101 Anderson,JamesM 2008; 3124 Harding,JacquelineL 2014}}2,3], often necessitating removal; a painful and expensive procedure [ADDIN RW.CITE{{3121 Mah,Thien-FahC 2001}}4]. Materials are sought to attenuate both the FBR and device-related infection, leading to medical devices with improved biocompatibility and performance. Objectives The present work involves development of a semi-interpenetrating network (SIPN) hydrogel containing polygalacturonic acid (PGA), a biopolysaccharide similar in structure to hyaluronic acid. We aim to synthesise, characterise and determine the in vitro biocompatibility of the developed SIPN. Results & Discussion We have successfully incorporated PGA into a poly(HEMA) based hydrogel, which shows favourable swelling and wettability. The surface topography appears altered in comparison to the control material, with pronounced micrometer-scale features. In terms of in vitro performance, the SIPN showed increased protein adsorption, and biofilm formation (Staphylococcus epidermidis and Escherichia coli, up to 1 Log CFU/sample greater than control). However the SIPN displayed minimal cytotoxicity towards L929 fibroblasts, and was resistant to the adherence of RAW 264.7 macrophages. Conclusions The PGA incorporated SIPN lacks cytotoxicity and shows reduced macrophage adherence, however the increased biofilm formation highlights a concern regarding possible device related infection in clinical use. Future work will focus on strategies to reduce bacterial adherence, while maintaining biocompatibility.

A Novel Semi-Automated Method of Tracking Fetal Movements

We have designed software that can â€â€™look’’ at recorded ultrasound sequences. We analyzed fifteen video sequences representing recorded ultrasound scans of nine fetuses. Our method requires a small amount of user labelled pixels for processing the first frame. These initialize GrowCut 1 , a background removal algorithm, which was used for separating the fetus from its surrounding environment (segmentation). For each subsequent frame, user input is no longer necessary as some of the pixels will inherit labels from the previously processed frame. This results in our software’s ability to track movement. Two sonographers rated the results of our computer’s â€vision’ on a scale from 1 (poor fit) to 10 (excellent fit). They assessed tracking accuracy for the entire video as well as segmentation accuracy (the ability to identify fetus from non-fetus) for every 100th processed frame. There was no appreciable deterioration in the software’s ability to track the fetus over time. I