Virologic and immunologic responses in treatment-naive patients to ritonavir-boosted atazanavir or efavirenz with a common backbone.

Background: Atazanavir boosted with ritonavir (ATV/r) and efavirenz (EFV) are both recommended as first-line therapies for HIV-infected patients. We compared the 2 therapies for virologic efficacy and immune recovery. Methods: We included all treatment-naïve patients in the Swiss HIV Cohort Study starting therapy after May 2003 with either ATV/r or EFV and a backbone of tenofovir and either emtricitabine or lamivudine. We used Cox models to assess time to virologic failure and repeated measures models to assess the change in CD4 cell counts over time. All models were fit as marginal structural models using both point of treatment and censoring weights. Intent-to-treat and various as-treated analyses were carried out: In the latter, patients were censored at their last recorded measurement if they changed therapy or if they were no longer adherent to therapy. Results: Patients starting EFV (n = 1,097) and ATV/r (n = 384) were followed for a median of 35 and 37 months, respectively. During follow-up, 51% patients on EFV and 33% patients on ATV/r remained adherent and made no change to their first-line therapy. Although intent-to-treat analyses suggest virologic failure was more likely with ATV/r, there was no evidence for this disadvantage in patients who adhered to first-line therapy. Patients starting ATV/r had a greater increase in CD4 cell count during the first year of therapy, but this advantage disappeared after one year. Conclusions: In this observational study, there was no good evidence of any intrinsic advantage for one therapy over the other, consistent with earlier clinical trials. Differences between therapies may arise in a clinical setting because of differences in adherence to therapy.

The Network Company in Catalonia : ICT, Productivity, Competitiveness, Salaries and Performance in Catalonia's Companies. Research report (synthesis document)

Resum en anglès del projecte de recerca L'empresa xarxa a Catalunya. TIC, productivitat, competitivitat, salaris i beneficis a l'empresa catalana té com a objectiu principal constatar que la consolidació d'un nou model estratègic, organitzatiu i d'activitat empresarial, vinculat amb la inversió i l'ús de les TIC (o empresa xarxa), modifica substancialment els patrons de comportament dels resultats empresarials, en especial la productivitat, la competitivitat, les retribucions dels treballadors i el benefici. La contrastació empírica de les hipòtesis de treball l'hem feta per mitjà de les dades d'una enquesta a una mostra representativa de 2.038 empreses catalanes. Amb la perspectiva de l'impacte de la inversió i l'ús de les TIC no s'aprecia una relació directa entre els processos d'innovació digital i els resultats de l'activitat de l'empresa catalana. En aquest sentit, hem hagut de segmentar el teixit productiu català per a buscar les organitzacions en què el procés de coinnovació tecnològica digital i organitzativa és més present i en què la intensitat de l'ús del coneixement és un recurs molt freqüent per a poder copsar impactes rellevants en els principals resultats empresarials. Això és així perquè l'economia catalana, avui, presenta una estructura productiva dual.

Schooling in the Network Society : Internet in Primary and Secondary Education. Research report (synthesis document)

Aquest projecte té la intenció d'identificar i analitzar els efectes de la introducció d'Internet a les escoles catalanes (educació primària i secundària). L'objectiu és posar de manifest la manera com s'utilitza la xarxa en aquest àmbit i en quina mesura contribueix a l'aparició, en els centres educatius, d'una nova cultura adaptada a les necessitats de la societat xarxa. Amb aquest propòsit, aquest projecte desplega les seves línies d'anàlisi per a fer atenció al procés d'incorporació d'Internet, principalment, en tres direccions: la pràctica pedagògica, les formes d'organització i gestió dels centres educatius i la seva vinculació amb la comunitat i el territori. Aquesta investigació ha estat desenvolupada pel grup de recerca ENS (Education and Network Society). Amb una perspectiva comparativa, el treball d'aquest grup vol contribuir, sobre la base de dades empíriques, a interpretar la transformació de l'àmbit educatiu no universitari en els paràmetres que estableix, avui dia, la nostra societat.

Internet and the Catalan Universities Network. Research report (synthesis document)

El desenvolupament de les tecnologies de la informació i la comunicació (TIC) durant els darrers quaranta anys del segle XX i la seva incorporació en els diferents àmbits de l'activitat humana ens porten a plantejar-nos, al començament del segle XXI, quines són les transformacions profundes que acompanyen aquests fets i quines són les conseqüències que, com a mínim a curt termini, comporten. El focus d'aquest projecte és l'anàlisi dels processos de transformació de la vida acadèmica universitària en l'àmbit català, la seva vinculació amb la realitat actual i les repercussions que els processos esmentats tenen en la societat en general. De manera més específica, l'objectiu és, en primer lloc, explorar amb una perspectiva global la incorporació d'Internet a les universitats catalanes i, en segon lloc, analitzar els processos de canvi que aquest fet comporta en els processos de formació i recerca de la Universitat Rovira i Virgili (URV). Aquest informe presenta els resultats de tres estudis concrets, cadascun dels quals té uns objectius, una metodologia i una discussió particulars: Configuració de la xarxa d'universitats catalanes: connexió física i projectes compartits, Presència de les universitats catalanes a Internet, i Estudi de cas: la URV.

Toxoplasma gondii: further studies on the subpellicular network

The association of the pellicle with cytoskeletal elements in Toxoplasma gondii allows this parasite to maintain its mechanical integrity and makes possible its gliding motility and cell invasion. The inner membrane complex (IMC) resembles the flattened membrane sacs observed in free-living protozoa and these sacs have been found to associate with cytoskeletal proteins such as articulins. We used immunofluorescence microscopy to characterise the presence and distribution of plateins, a sub-family of articulins, in T. gondii tachyzoites. A dispersed labelling of the whole protozoan body was observed. Electron microscopy of detergent-extracted cells revealed the presence of a network of 10 nm filaments distributed throughout the parasite. These filaments were labelled with anti-platein antibodies. Screening the sequenced T. gondii genome, we obtained the sequence of an IMC predicted protein with 25% identity and 42% similarity to the platein isoform alpha 1 present in Euplotes aediculatus, but with 42% identity and 55% similarity to that found in Euglena gracilis, suggesting strong resemblance to articulins.

Social network measures for "nosduocentered" networks, their predictive power on performance

Our purpose in this article is to define a network structure which is based on two egos instead of the egocentered (one ego) or the complete network (n egos). We describe the characteristics and properties for this kind of network which we call “nosduocentered network”, comparing it with complete and egocentered networks. The key point for this kind of network is that relations exist between the two main egos and all alters, but relations among others are not observed. After that, we use new social network measures adapted to the nosduocentered network, some of which are based on measures for complete networks such as degree, betweenness, closeness centrality or density, while some others are tailormade for nosduocentered networks. We specify three regression models to predict research performance of PhD students based on these social network measures for different networks such as advice, collaboration, emotional support and trust. Data used are from Slovenian PhD students and their s

Brain network analysis of patients with Temporal Lobe Epilepsy

Patients with Temporal Lobe Epilepsy (TLE) suffer from widespread subtle white matter abnormalities and abnormal functional connectivity extending beyond the affected lobe, as revealed by Diffusion Tensor MR Imaging, volumetric and functional MRI studies. Diffusion Spectrum Imaging (DSI) is a diffusion imaging technique with high angular resolution for improving the mapping of white matter pathways. In this study, we used DSI, connectivity matrices and topological measures to investigate how the alteration in structural connectivity influences whole brain structural networks. Eleven patients with right-sided TLE and hippocampal sclerosis and 18 controls underwent our DSI protocol at 3T. The cortical and subcortical grey matters were parcellated into 86 regions of interest and the connectivity between every region pair was estimated using global tractography and a connectivity matrix (the adjacency matrix of the structural network). We then compared the networks of patients and controls using topological measures. In patients, we found a higher characteristic path length and a lower clustering coefficient compared to controls. Local measures at node level of the clustering and efficiency showed a significant difference after a multiple comparison correction (Bonferroni). These significant nodes were located within as well outside the temporal lobe, and the localisation of most of them was consistent with regions known to be part of epileptic networks in TLE. Our results show altered connectivity patterns that are concordant with the mapping of functional epileptic networks in patients with TLE. Further studies are needed to establish the relevance of these findings for the propagation of epileptic activity, cognitive deficits in medial TLE and outcome of epilepsy surgery in individual patients.

A genome-wide significant linkage for severe depression on chromosome 3: the depression network study.

Objective: The purpose of this study was to find loci for major depression via linkage analysis of a large sibling pair sample. Method: The authors conducted a genome-wide linkage analysis of 839 families consisting of 971 affected sibling pairs with severe recurrent major depression, comprising waves I and II of the Depression Network Study cohort. In addition to examining affected status, linkage analyses in the full data set were performed using diagnoses restricted by impairment severity, and association mapping of hits in a large case-control data set was attempted. Results: The authors identified genome-wide significant linkage to chromosome 3p25-26 when the diagnoses were restricted by severity, which was a maximum LOD score of 4.0 centered at the linkage marker D3S1515. The linkage signal identified was genome-wide significant after correction for the multiple phenotypes tested, although subsequent association mapping of the region in a genome-wide association study of a U.K. depression sample did not provide significant results. Conclusions: The authors report a genome-wide significant locus for depression that implicates genes that are highly plausible for involvement in the etiology of recurrent depression. Despite the fact that association mapping in the region was negative, the linkage finding was replicated by another group who found genome-wide-significant linkage for depression in the same region. This suggests that 3p25-26 is a new locus for severe recurrent depression. This represents the first report of a genome-wide significant locus for depression that also has an independent genome-wide significant replication.

Testing of Diagnostic Methods for Detection of Influenza Virusfor Optimal Performance in the Context of an Influenza Surveillance Network

Influenza surveillance networks must detect early the viruses that will cause the forthcoming annual epidemics and isolate the strains for further characterization. We obtained the highest sensitivity (95.4%) with a diagnostic tool that combined a shell-vial assay and reverse transcription-PCR on cell culture supernatants at 48 h, and indeed, recovered the strain

A Bayesian network approach to the database serch problem in criminal proceedings

Background The 'database search problem', that is, the strengthening of a case - in terms of probative value - against an individual who is found as a result of a database search, has been approached during the last two decades with substantial mathematical analyses, accompanied by lively debate and centrally opposing conclusions. This represents a challenging obstacle in teaching but also hinders a balanced and coherent discussion of the topic within the wider scientific and legal community. This paper revisits and tracks the associated mathematical analyses in terms of Bayesian networks. Their derivation and discussion for capturing probabilistic arguments that explain the database search problem are outlined in detail. The resulting Bayesian networks offer a distinct view on the main debated issues, along with further clarity. Methods As a general framework for representing and analyzing formal arguments in probabilistic reasoning about uncertain target propositions (that is, whether or not a given individual is the source of a crime stain), this paper relies on graphical probability models, in particular, Bayesian networks. This graphical probability modeling approach is used to capture, within a single model, a series of key variables, such as the number of individuals in a database, the size of the population of potential crime stain sources, and the rarity of the corresponding analytical characteristics in a relevant population. Results This paper demonstrates the feasibility of deriving Bayesian network structures for analyzing, representing, and tracking the database search problem. The output of the proposed models can be shown to agree with existing but exclusively formulaic approaches. Conclusions The proposed Bayesian networks allow one to capture and analyze the currently most well-supported but reputedly counter-intuitive and difficult solution to the database search problem in a way that goes beyond the traditional, purely formulaic expressions. The method's graphical environment, along with its computational and probabilistic architectures, represents a rich package that offers analysts and discussants with additional modes of interaction, concise representation, and coherent communication.

Differential epipolar constraint in mobile robot egomotion estimation

The estimation of camera egomotion is a well established problem in computer vision. Many approaches have been proposed based on both the discrete and the differential epipolar constraint. The discrete case is mainly used in self-calibrated stereoscopic systems, whereas the differential case deals with a unique moving camera. The article surveys several methods for mobile robot egomotion estimation covering more than 0.5 million samples using synthetic data. Results from real data are also given

Evaluating the probability and the impact of a failure in GMPLS based networks

In this paper, we define a new scheme to develop and evaluate protection strategies for building reliable GMPLS networks. This is based on what we have called the network protection degree (NPD). The NPD consists of an a priori evaluation, the failure sensibility degree (FSD), which provides the failure probability, and an a posteriori evaluation, the failure impact degree (FID), which determines the impact on the network in case of failure, in terms of packet loss and recovery time. Having mathematical formulated these components, experimental results demonstrate the benefits of the utilization of the NPD, when used to enhance some current QoS routing algorithms in order to offer a certain degree of protection

Minimum interference routing with fast protection

One of the most effective techniques offering QoS routing is minimum interference routing. However, it is complex in terms of computation time and is not oriented toward improving the network protection level. In order to include better levels of protection, new minimum interference routing algorithms are necessary. Minimizing the failure recovery time is also a complex process involving different failure recovery phases. Some of these phases depend completely on correct routing selection, such as minimizing the failure notification time. The level of protection also involves other aspects, such as the amount of resources used. In this case shared backup techniques should be considered. Therefore, minimum interference techniques should also be modified in order to include sharing resources for protection in their objectives. These aspects are reviewed and analyzed in this article, and a new proposal combining minimum interference with fast protection using shared segment backups is introduced. Results show that our proposed method improves both minimization of the request rejection ratio and the percentage of bandwidth allocated to backup paths in networks with low and medium protection requirements

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

Efficient learning of reactive robot behaviors with a Neural-Q_learning approach

The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed