On the computation of reducible invariant tori on a parallel computer

We present an algorithm for the computation of reducible invariant tori of discrete dynamical systems that is suitable for tori of dimensions larger than 1. It is based on a quadratically convergent scheme that approximates, at the same time, the Fourier series of the torus, its Floquet transformation, and its Floquet matrix. The Floquet matrix describes the linearization of the dynamics around the torus and, hence, its linear stability. The algorithm presents a high degree of parallelism, and the computational effort grows linearly with the number of Fourier modes needed to represent the solution. For these reasons it is a very good option to compute quasi-periodic solutions with several basic frequencies. The paper includes some examples (flows) to show the efficiency of the method in a parallel computer. In these flows we compute invariant tori of dimensions up to 5, by taking suitable sections.

MRI/TRUS fusion software-based targeted biopsy: the new standard of care?

The advent of multiparametric MRI has made it possible to change the way in which prostate biopsy is done, allowing to direct biopsies to suspicious lesions rather than randomly. The subject of this review relates to a computer-assisted strategy, the MRI/US fusion software-based targeted biopsy, and to its performance compared to the other sampling methods. Different devices with different methods to register MR images to live TRUS are currently in use to allow software-based targeted biopsy. Main clinical indications of MRI/US fusion software-based targeted biopsy are re-biopsy in men with persistent suspicious of prostate cancer after first negative standard biopsy and the follow-up of patients under active surveillance. Some studies have compared MRI/US fusion software-based targeted versus standard biopsy. In men at risk with MRI-suspicious lesion, targeted biopsy consistently detects more men with clinically significant disease as compared to standard biopsy; some studies have also shown decreased detection of insignificant disease. Only two studies directly compared MRI/US fusion software-based targeted biopsy with MRI/US fusion visual targeted biopsy, and the diagnostic ability seems to be in favor of the software approach. To date, no study comparing software-based targeted biopsy against in-bore MRI biopsy is available. The new software-based targeted approach seems to have the characteristics to be added in the standard pathway for achieving accurate risk stratification. Once reproducibility and cost-effectiveness will be verified, the actual issue will be to determine whether MRI/TRUS fusion software-based targeted biopsy represents anadd-on test or a replacement to standard TRUS biopsy.

Communication challenges in virtual teams – a case study of implementing computer-mediated communication technologies in inter-organisational virtual teams

This thesis seeks to answer, if communication challenges in virtual teams can be overcome with the help of computer-mediated communication. Virtual teams are becoming more common work method in many global companies. In order for virtual teams to reach their maximum potential, effective asynchronous and synchronous methods for communication are needed. The thesis covers communication in virtual teams, as well as leadership and trust building in virtual environments with the help of CMC. First, the communication challenges in virtual teams are identified by using a framework of knowledge sharing barriers in virtual teams by Rosen et al. (2007) Secondly, the leadership and trust in virtual teams are defined in the context of CMC. The performance of virtual teams is evaluated in the case study by exploiting these three dimensions. With the help of a case study of two virtual teams, the practical issues related to selecting and implementing communication technologies as well as overcoming knowledge sharing barriers is being discussed. The case studies involve a complex inter-organisational setting, where four companies are working together in order to maintain a new IT system. The communication difficulties are related to inadequate communication technologies, lack of trust and the undefined relationships of the stakeholders and the team members. As a result, it is suggested that communication technologies are needed in order to improve the virtual team performance, but are not however solely capable of solving the communication challenges in virtual teams. In addition, suitable leadership and trust between team members are required in order to improve the knowledge sharing and communication in virtual teams.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

L'informatique: un outil remarquable pour l'enseignement de la médecine interne générale [The informatics: a remarkable tool for teaching general internal medicine].

INTERMED training implies a three week course, integrated in the "primary care module" for medical students in the first master year at the school of medicine in Lausanne. INTERMED uses an innovative teaching method based on repetitive sequences of e-learning-based individual learning followed by collaborative learning activities in teams, named Team-based learning (TBL). The e-learning takes place in a web-based virtual learning environment using a series of interactive multimedia virtual patients. By using INTERMED students go through a complete medical encounter applying clinical reasoning and choosing the diagnostic and therapeutic approach. INTERMED offers an authentic experience in an engaging and safe environment where errors are allowed and without consequences.

Prevention of vascular dysfunction and arterial hypertension in mice generated by assisted reproductive technologies by addition of melatonin to culture media.

Assisted reproductive technologies (ART) induce vascular dysfunction in humans and mice. In mice, ART-induced vascular dysfunction is related to epigenetic alteration of the endothelial nitric oxide synthase (eNOS) gene, resulting in decreased vascular eNOS expression and nitrite/nitrate synthesis. Melatonin is involved in epigenetic regulation, and its administration to sterile women improves the success rate of ART. We hypothesized that addition of melatonin to culture media may prevent ART-induced epigenetic and cardiovascular alterations in mice. We, therefore, assessed mesenteric-artery responses to acetylcholine and arterial blood pressure, together with DNA methylation of the eNOS gene promoter in vascular tissue and nitric oxide plasma concentration in 12-wk-old ART mice generated with and without addition of melatonin to culture media and in control mice. As expected, acetylcholine-induced mesenteric-artery dilation was impaired (P = 0.008 vs. control) and mean arterial blood pressure increased (109.5 ± 3.8 vs. 104.0 ± 4.7 mmHg, P = 0.002, ART vs. control) in ART compared with control mice. These alterations were associated with altered DNA methylation of the eNOS gene promoter (P < 0.001 vs. control) and decreased plasma nitric oxide concentration (10.1 ± 11.1 vs. 29.5 ± 8.0 μM) (P < 0.001 ART vs. control). Addition of melatonin (10(-6) M) to culture media prevented eNOS dysmethylation (P = 0.005, vs. ART + vehicle), normalized nitric oxide plasma concentration (23.1 ± 14.6 μM, P = 0.002 vs. ART + vehicle) and mesentery-artery responsiveness to acetylcholine (P < 0.008 vs. ART + vehicle), and prevented arterial hypertension (104.6 ± 3.4 mmHg, P < 0.003 vs. ART + vehicle). These findings provide proof of principle that modification of culture media prevents ART-induced vascular dysfunction. We speculate that this approach will also allow preventing ART-induced premature atherosclerosis in humans.

Development of a systematic computer vision-based method to analyse and compare images of false identity documents for forensic intelligence purposes-Part I: acquisition, calibration and validation issues

Following their detection and seizure by police and border guard authorities, false identity and travel documents are usually scanned, producing digital images. This research investigates the potential of these images to classify false identity documents, highlight links between documents produced by a same modus operandi or same source, and thus support forensic intelligence efforts. Inspired by previous research work about digital images of Ecstasy tablets, a systematic and complete method has been developed to acquire, collect, process and compare images of false identity documents. This first part of the article highlights the critical steps of the method and the development of a prototype that processes regions of interest extracted from images. Acquisition conditions have been fine-tuned in order to optimise reproducibility and comparability of images. Different filters and comparison metrics have been evaluated and the performance of the method has been assessed using two calibration and validation sets of documents, made up of 101 Italian driving licenses and 96 Portuguese passports seized in Switzerland, among which some were known to come from common sources. Results indicate that the use of Hue and Edge filters or their combination to extract profiles from images, and then the comparison of profiles with a Canberra distance-based metric provides the most accurate classification of documents. The method appears also to be quick, efficient and inexpensive. It can be easily operated from remote locations and shared amongst different organisations, which makes it very convenient for future operational applications. The method could serve as a first fast triage method that may help target more resource-intensive profiling methods (based on a visual, physical or chemical examination of documents for instance). Its contribution to forensic intelligence and its application to several sets of false identity documents seized by police and border guards will be developed in a forthcoming article (part II).

Efficient total variation algorithm for fetal MRI reconstruction

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy [1], Total Variation (TV)based energies [2,3] and more recently non-local means [4]. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm for fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n(2)) and O(1/root epsilon), while existing techniques are in O(1/n) and O(1/epsilon). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

Time to identify cardiac arrest and provide dispatch-assisted cardio-pulmonary resuscitation in a criteria-based dispatch system.

INTRODUCTION: Dispatch-assisted cardiopulmonary resuscitation (DA-CPR) plays a key role in out-of-hospital cardiac arrests. We sought to measure dispatchers' performances in a criteria-based system in recognizing cardiac arrest and delivering DA-CPR. Our secondary purpose was to identify the factors that hampered dispatchers' identification of cardiac arrests, the factors that prevented them from proposing DA-CPR, and the factors that prevented bystanders from performing CPR. METHODS AND RESULTS: We reviewed dispatch recordings for 1254 out-of-hospital cardiac arrests occurring between January 1, 2011 and December 31, 2013. Dispatchers correctly identified cardiac arrests in 71% of the reviewed cases and 84% of the cases in which they were able to assess for patient consciousness and breathing. The median time to recognition of the arrest was 60s. The median time to start chest compression was 220s. CONCLUSIONS: This study demonstrates that performances from a criteria-based dispatch system can be similar to those from a medical-priority dispatch system regarding out-of-hospital cardiac arrest (OHCA) time recognition and DA-CPR delivery. Agonal breathing recognition remains the weakest link in this sensitive task in both systems. It is of prime importance that all dispatch centers tend not only to implement DA-CPR but also to have tools to help them reach this objective, as today it should be mandatory to offer this service to the community. In order to improve benchmarking opportunities, we completed previously proposed performance standards as propositions.

Connectivity and tissue microstructural alterations in right and left temporal lobe epilepsy revealed by diffusion spectrum imaging.

Focal epilepsy is increasingly recognized as the result of an altered brain network, both on the structural and functional levels and the characterization of these widespread brain alterations is crucial for our understanding of the clinical manifestation of seizure and cognitive deficits as well as for the management of candidates to epilepsy surgery. Tractography based on Diffusion Tensor Imaging allows non-invasive mapping of white matter tracts in vivo. Recently, diffusion spectrum imaging (DSI), based on an increased number of diffusion directions and intensities, has improved the sensitivity of tractography, notably with respect to the problem of fiber crossing and recent developments allow acquisition times compatible with clinical application. We used DSI and parcellation of the gray matter in regions of interest to build whole-brain connectivity matrices describing the mutual connections between cortical and subcortical regions in patients with focal epilepsy and healthy controls. In addition, the high angular and radial resolution of DSI allowed us to evaluate also some of the biophysical compartment models, to better understand the cause of the changes in diffusion anisotropy. Global connectivity, hub architecture and regional connectivity patterns were altered in TLE patients and showed different characteristics in RTLE vs LTLE with stronger abnormalities in RTLE. The microstructural analysis suggested that disturbed axonal density contributed more than fiber orientation to the connectivity changes affecting the temporal lobes whereas fiber orientation changes were more involved in extratemporal lobe changes. Our study provides further structural evidence that RTLE and LTLE are not symmetrical entities and DSI-based imaging could help investigate the microstructural correlate of these imaging abnormalities.

Noves funcionalitats per desenvolupar el treball en grup a dins de l'ACME

La plataforma ACME (Avaluació Continuada i Millora de l’Ensenyament) va ser creada l’any 1998 per un grup de professors del departament d’Informàtica i Matemàtica Aplicada. L’ACME es va concebre com una plataforma d’e-learning, és a dir, un sistema que mitjançant l’ús d’Internet afavorís l’aprenentatge, permeten la interactivitat entre l’alumne i el professor. La creació de la plataforma ACME tenia com a objectiu reduir el fracàs dels alumnes en les assignatures de matemàtiques, però degut a l’èxit que va suposar en aquestes, es va decidir incorporar la metodologia de treball ACME a altres disciplines com la programació, les bases de dades, la química, l’economia, etc. de manera que actualment es poden desenvolupar activitats ACME en moltes disciplines. Actualment l’ACME s’utilitza com a complement a les classes presencials, on el professor exposa de manera magistral els conceptes i resol algun exercici a mode d’exemple, per a que després l’alumne, utilitzant la plataforma ACME, intenti resoldre els exercicis proposats pel professor.L’objectiu d’aquest projecte és desenvolupar l’anàlisi, disseny i implementació de les modificacions necessàries a incorporar a la plataforma ACME per tal de millorar el gestor de grups, els exercicis Excel i finalment permetre el treball en grup. El projecte consta de tres parts: millorar les interfícies del professor i de l’alumne, la millora del exercicis Excel i la resolució d’exercicis en grup

Módulo para gestionar el modelo de usuario y permisos, el sistema de archivos y el de noticias en la plataforma CoSpace

CoSpace és una plataforma web dissenyada per proporcionar un espai virtual d’interacció i col•laboració entre formadors en comunitats virtuals. Es va originar com a resultat de les necessitats addicionals que van sorgir quan els professors que treballen en temes educatius en context de diversitat (en àrees de llenguatge, matemàtiques i ciències) van necessitar una eina per afavorir o recolzar la interacció i la col•laboració entre ells per compartir idees, experiències, objectes virtuals d’aprenentatge, entre d’altres, des d’una perspectiva actual de l’ús de la tecnologia i des d’una visió més propera a l’usuari final. Aquest paradigma promou la idea que les aplicacions han de ser concebudes per a usuaris poc experts i tenint en compte els principis d’usabilitat i accessibilitat.L’abast del projecte està definit per la necessitat de gestió per part dels professors, de la informació del seu perfil personal, permetent als usuaris la creació, edició, consulta i eliminació d’aquesta informació. També la necessitat de compartir arxius, publicar notícies entre comunitats de pràctica i, finalment, de la necessitat de gestionar els permisos d’usuari per tal que gestionin mòduls de la plataforma

Integración de recursos digitales en las tareas de aprendizaje de lenguas: portafolios electrónicos y traducción asistida por ordenador

Las herramientas informáticas abren un amplio campo de posibilidades pedagógicas a las asignaturas de lengua. En el presente artículo se propone un modelo de combinación de recursos digitales (portafolios electrónicos y traducción asistida por ordenador) que refuerzan proyectos docentes del ámbito de las lenguas desde un enfoque pedagógico socioconstructivista. En algunos casos, las actividades se pueden integrar en proyectos reales. Por otra parte, los proyectos relacionados con el uso de estas herramientas pueden tener un enfoque multidisciplinar que implique tanto a los departamentos de las lenguas extranjeras y como a los de las lenguas maternas.