A program slicing method for a wide spectrum language

This thesis describes the implementation of a program slicer for WSL - a Wide Spectrum Language - which is a language that allows different levels of abstraction to coexist in the same program. WSL contains constructs not found in conventional languages, e.g. action systems (which model a segment of code with GOTOs and labels) and non deterministic constructs. Program slicing is a method for restricting a program to a specified behaviour of interest. Usually this behaviour of interest is expressed in terms of a variable or a set of variables. The method used in the thesis to slice a program is different from the classical ones in that slices do not need to be computed from an output statement, and in that slices are computed on a wide spectrum language closer to a functional language, instead of being computed on a more conventional, procedural language. A slicer for a subset of WSL has been designed and implemented based on the data flow analysis techniques for while-programs of Bergeretti and Carré [10]. It has been necessary to modify the algorithm to permit incremental slicing. Modifications of their algorithm were also needed to accommodate the specific WSL constructs mentioned above. The implementation has been developed using a rapid prototyping approach. The prototype has provided new ideas and enhancements for a more comprehensive sheer which could be implemented in the future. The slicer has assisted the maintainer using ReForm - a reverse engineering project developed at Durham University - in understanding and debugging a program by decomposing it. At the end of this thesis results showing how slicing has helped the maintainer are presented. Conclusions on the method used, the validity of the tool, and its engineering are also summarized

New findings of Prototherium ausetanum (Mammalia, Pan-Sirenia) from paving stones in Girona (Catalonia, Spain)?

Taxonomic and morphological approaches on Eocene sirenians from Catalonia (Spain) benefit from a newly discovered specimen found in a quite unusual locality, the pedestrian zone in the city of Girona. Two fossil-bearing limestone slabs from middle Eocene (Bartonian) layers of a quarry in the wider surrounding area north-west of Barcelona, were CT-scanned in the Clínica Girona to enhance more detailed investigations. Post-processing of the scans and, as far as possible, 3D-reconstruction of the preserved elements in the slabs was performed at Museum für Naturkunde Berlin. Thereby, a skull of a Dugong specimen was used as a reference point. Based on the combined analysis of macroscopic and CT-data, the specimen most likely represents Prototherium ausetanum Balaguer & Alba, 2016 and complements the available information of the holotype and hitherto only known specimen of that species. The Girona specimen is an adult, but small individual that corroborates P. ausetanum as a generally small-sized species compared to other known Prototherium taxa

Casa eficiente. Rehabilitación energética

El reto era intervenir en una vivienda construida en 1918, conservando la volumetría y fachada original a la calle y mejorando notablemente sus prestaciones de confort térmico y acústico. Aunque algunos factores añadían dificultad a la operación: la mala orientación de la vivienda y poca libertad volumétrica –se trata de una vivienda entre medianeras con el jardín a noroeste-; un presupuesto cerrado y un plazo de ejecución ajustado, se han cumplido los objetivos inicialmente planteados. La intervención se ha llevado a cabo mediante el estándar de Casa Pasiva. El sistema requiere conocer en fases muy iniciales (anteproyecto) las características técnicas de todos los materiales, sistemas constructivos e instalaciones que se van a emplear. Para cumplir con los requisitos del estándar se ha dotado la vivienda de un elevado grado de aislamiento térmico, ausencia de puentes térmicos, hermeticidad al aire y de sistema de ventilación mecánica de doble flujo, con recuperación de calor y un alto rendimiento nominal. Mediante el programa PHPP (Pasive House Projecting Package), herramienta tipo excel, calibrada con el programa de simulación dinámica DYNBUILD, se ha simulado y optimizado el comportamiento energético del edificio. En tan solo 120 días se ha transformado una edificación tradicional en una Casa Pasiva, disminuyendo la demanda energética de 171 kWh/m2a a tan solo 17 kWh/m2a (rehabilitación energética de factor 10). Para obtener las excelentes prestaciones se han utilizado también materiales de bioconstrucción, reduciendo el impacto ambiental y mejorando la biohabitabilidad del espacio.Consejo General de la Arquitectura Técnica de Españ

One-shot domain adaptation in multiple sclerosis lesion segmentation using convolutional neural networks

In recent years, several convolutional neural network (CNN) methods have been proposed for the automated white matter lesion segmentation of multiple sclerosis (MS) patient images, due to their superior performance compared with those of other state-of-the-art methods. However, the accuracies of CNN methods tend to decrease significantly when evaluated on different image domains compared with those used for training, which demonstrates the lack of adaptability of CNNs to unseen imaging data. In this study, we analyzed the effect of intensity domain adaptation on our recently proposed CNN-based MS lesion segmentation method. Given a source model trained on two public MS datasets, we investigated the transferability of the CNN model when applied to other MRI scanners and protocols, evaluating the minimum number of annotated images needed from the new domain and the minimum number of layers needed to re-train to obtain comparable accuracy. Our analysis comprised MS patient data from both a clinical center and the public ISBI2015 challenge database, which permitted us to compare the domain adaptation capability of our model to that of other state-of-the-art methods. For the ISBI2015 challenge, our one-shot domain adaptation model trained using only a single image showed a performance similar to that of other CNN methods that were fully trained using the entire available training set, yielding a comparable human expert rater performance. We believe that our experiments will encourage the MS community to incorporate its use in different clinical settings with reduced amounts of annotated data. This approach could be meaningful not only in terms of the accuracy in delineating MS lesions but also in the related reductions in time and economic costs derived from manual lesion labeling

Normalization of T2W-MRI Prostate Images using Rician a priori

International audienceProstate cancer is reported to be the second most frequently diagnosed cancer of men in the world. In practise, diagnosis can be affected by multiple factors which reduces the chance to detect the potential lesions. In the last decades, new imaging techniques mainly based on MRI are developed in conjunction with Computer-Aided Diagnosis (CAD) systems to help radiologists for such diagnosis. CAD systems are usually designed as a sequential process consisting of four stages: pre-processing, segmentation, registration and classification. As a pre-processing, image normalization is a critical and important step of the chain in order to design a robust classifier and overcome the inter-patients intensity variations. However, little attention has been dedicated to the normalization of T2W-Magnetic Resonance Imaging (MRI) prostate images. In this paper, we propose two methods to normalize T2W-MRI prostate images: (i) based on a Rician a priori and (ii) based on a Square-Root Slope Function (SRSF) representation which does not make any assumption regarding the Probability Density Function (PDF) of the data. A comparison with the state-of-the-art methods is also provided. The normalization of the data is assessed by comparing the alignment of the patient PDFs in both qualitative and quantitative manners. In both evaluation, the normalization using Rician a priori outperforms the other state-of-the-art methods

Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: A review

International audienceProstate cancer is the second most diagnosed cancer of men all over the world. In the last decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have been developed improving diagnosis.In practise, diagnosis can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. In this regard, computer-aided detection and computer-aided diagnosis systemshave been designed to help radiologists in their clinical practice. Research on computer-aided systems specifically focused for prostate cancer is a young technology and has been part of a dynamic field ofresearch for the last ten years. This survey aims to provide a comprehensive review of the state of the art in this lapse of time, focusing on the different stages composing the work-flow of a computer-aidedsystem. We also provide a comparison between studies and a discussion about the potential avenues for future research. In addition, this paper presents a new public online dataset which is made available to theresearch community with the aim of providing a common evaluation framework to overcome some of the current limitations identified in this survey

Trapping of Organochlorine Compounds in High Mountain Lakes

High mountain areas have recently been observed to be polluted by organochlorine compounds (OC) despite their isolation. These persistent pollutants arrive at these remote regions through atmospheric transport. However, the mechanisms involving the accumulation of these compounds from the atmospheric pool to the lacustrine systems still need to be elucidated. These mechanisms must be related to the processes involving the transfer of these pollutant from low to high latitudes[1] as described in the global distillation effect[2]