37 resultados para Energy Efficient Mobile Network


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The Swiss Medical Insurance Act (LAMaL) requires the planning of psychiatric care. This necessitates a coordination between the Department of Public Health and the institutional governance. Given the difficulties to draw comparisons between a wide range of systems in a federal country, the Swiss Conference of the State Directors of Health (CDS) proposed as a first step that each canton present some of the key programs they had developed. In the canton Vaud, the implementation of mobile community treatment teams and of an early intervention program for psychosis was chosen. The main challenges faced were to go past traditional divides within the organisation of the Swiss Health system and to conciliate the requirements of public health with the needs of treating teams, in order to promote early intervention in mental health disorders.

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BACKGROUND & AIMS: The hepatitis C virus (HCV) NS3-4A protease is essential for the HCV life cycle and a prime target of antiviral treatment strategies. Protease inhibitors, however, are limited by emergence of resistance-associated amino acid variants (RAVs). The capacity to cleave and inactivate mitochondrial antiviral-signaling protein (MAVS) in the RIG-I-signaling pathway is a cardinal feature of NS3-4A, by which HCV blocks induction of interferon-(IFN)-β, thereby promoting viral persistence. Here, we aimed to investigate the impact of NS3-4A RAVs on MAVS cleavage. METHODS: The impact of NS3-4A RAVs on MAVS cleavage was assessed using immunoblot analyses, luciferase reporter assays and molecular dynamics simulations to study the underlying molecular principles. IFN-β was quantified in serum from patients with different NS3-4A RAVs. RESULTS: We show that macrocyclic NS3-4A RAVS with substitutions at residue D168 of the protease result in an increased capacity of NS3-4A to cleave MAVS and suppress IFN-β induction compared with a comprehensive panel of RAVs and wild type HCV. Mechanistically, we show the reconstitution of a tight network of electrostatic interactions between protease and the peptide substrate that allows much stronger binding of MAVS to D168 RAVs than to the wild-type protease. Accordingly, we could show IFN-β serum levels to be lower in patients with treatment failure due to the selection of D168 variants compared to R155 RAVs. CONCLUSIONS: Our data constitutes a proof of concept that the selection of RAVs against specific classes of direct antivirals can lead to the predominance of viral variants with possibly adverse pathogenic characteristics.

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Cooperation and coordination are desirable behaviors that are fundamental for the harmonious development of society. People need to rely on cooperation with other individuals in many aspects of everyday life, such as teamwork and economic exchange in anonymous markets. However, cooperation may easily fall prey to exploitation by selfish individuals who only care about short- term gain. For cooperation to evolve, specific conditions and mechanisms are required, such as kinship, direct and indirect reciprocity through repeated interactions, or external interventions such as punishment. In this dissertation we investigate the effect of the network structure of the population on the evolution of cooperation and coordination. We consider several kinds of static and dynamical network topologies, such as Baraba´si-Albert, social network models and spatial networks. We perform numerical simulations and laboratory experiments using the Prisoner's Dilemma and co- ordination games in order to contrast human behavior with theoretical results. We show by numerical simulations that even a moderate amount of random noise on the Baraba´si-Albert scale-free network links causes a significant loss of cooperation, to the point that cooperation almost vanishes altogether in the Prisoner's Dilemma when the noise rate is high enough. Moreover, when we consider fixed social-like networks we find that current models of social networks may allow cooperation to emerge and to be robust at least as much as in scale-free networks. In the framework of spatial networks, we investigate whether cooperation can evolve and be stable when agents move randomly or performing Le´vy flights in a continuous space. We also consider discrete space adopting purposeful mobility and binary birth-death process to dis- cover emergent cooperative patterns. The fundamental result is that cooperation may be enhanced when this migration is opportunistic or even when agents follow very simple heuristics. In the experimental laboratory, we investigate the issue of social coordination between indi- viduals located on networks of contacts. In contrast to simulations, we find that human players dynamics do not converge to the efficient outcome more often in a social-like network than in a random network. In another experiment, we study the behavior of people who play a pure co- ordination game in a spatial environment in which they can move around and when changing convention is costly. We find that each convention forms homogeneous clusters and is adopted by approximately half of the individuals. When we provide them with global information, i.e., the number of subjects currently adopting one of the conventions, global consensus is reached in most, but not all, cases. Our results allow us to extract the heuristics used by the participants and to build a numerical simulation model that agrees very well with the experiments. Our findings have important implications for policymakers intending to promote specific, desired behaviors in a mobile population. Furthermore, we carry out an experiment with human subjects playing the Prisoner's Dilemma game in a diluted grid where people are able to move around. In contrast to previous results on purposeful rewiring in relational networks, we find no noticeable effect of mobility in space on the level of cooperation. Clusters of cooperators form momentarily but in a few rounds they dissolve as cooperators at the boundaries stop tolerating being cheated upon. Our results highlight the difficulties that mobile agents have to establish a cooperative environment in a spatial setting without a device such as reputation or the possibility of retaliation. i.e. punishment. Finally, we test experimentally the evolution of cooperation in social networks taking into ac- count a setting where we allow people to make or break links at their will. In this work we give particular attention to whether information on an individual's actions is freely available to poten- tial partners or not. Studying the role of information is relevant as information on other people's actions is often not available for free: a recruiting firm may need to call a job candidate's refer- ences, a bank may need to find out about the credit history of a new client, etc. We find that people cooperate almost fully when information on their actions is freely available to their potential part- ners. Cooperation is less likely, however, if people have to pay about half of what they gain from cooperating with a cooperator. Cooperation declines even further if people have to pay a cost that is almost equivalent to the gain from cooperating with a cooperator. Thus, costly information on potential neighbors' actions can undermine the incentive to cooperate in dynamical networks.

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Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed.

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Worldwide, about half the adult population is considered overweight as defined by a body mass index (BMI - calculated by body weight divided by height squared) ratio in excess of 25 kg.m-2. Of these individuals, half are clinically obese (with a BMI in excess of 30) and these numbers are still increasing, notably in developing countries such as those of the Middle East region. Obesity is a disorder characterised by increased mass of adipose tissue (excessive fat accumulation) that is the result of a systemic imbalance between food intake and energy expenditure. Although factors such as family history, sedentary lifestyle, urbanisation, income and family diet patterns determine obesity prevalence, the main underlying causes are poor knowledge about food choice and lack of physical activity3. Current obesity treatments include dietary restriction, pharmacological interventions and ultimately, bariatric surgery. The beneficial effects of physical activity on weight loss through increased energy expenditure and appetite modulation are also firmly established. Another viable option to induce a negative energy balance, is to incorporate hypoxia per se or combine it with exercise in an individual's daily schedule. This article will present recent evidence suggesting that combining hypoxic exposure and exercise training might provide a cost-effective strategy for reducing body weight and improving cardio-metabolic health in obese individuals. The efficacy of this approach is further reinforced by epidemiological studies using large-scale databases, which evidence a negative relationship between altitude of habitation and obesity. In the United States, for instance, obesity prevalence is inversely associated with altitude of residence and urbanisation, after adjusting for temperature, diet, physical activity, smoking and demographic factors.

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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.

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Chromosome 22q11.2 deletion syndrome (22q11DS) is a genetic disease known to lead to cerebral structural alterations, which we study using the framework of the macroscopic white-matter connectome. We create weighted connectomes of 44 patients with 22q11DS and 44 healthy controls using diffusion tensor magnetic resonance imaging, and perform a weighted graph theoretical analysis. After confirming global network integration deficits in 22q11DS (previously identified using binary connectomes), we identify the spatial distribution of regions responsible for global deficits. Next, we further characterize the dysconnectivity of the deficient regions in terms of sub-network properties, and investigate their relevance with respect to clinical profiles. We define the subset of regions with decreased nodal integration (evaluated using the closeness centrality measure) as the affected core (A-core) of the 22q11DS structural connectome. A-core regions are broadly bilaterally symmetric and consist of numerous network hubs - chiefly parietal and frontal cortical, as well as subcortical regions. Using a simulated lesion approach, we demonstrate that these core regions and their connections are particularly important to efficient network communication. Moreover, these regions are generally densely connected, but less so in 22q11DS. These specific disturbances are associated to a rerouting of shortest network paths that circumvent the A-core in 22q11DS, "de-centralizing" the network. Finally, the efficiency and mean connectivity strength of an orbito-frontal/cingulate circuit, included in the affected regions, correlate negatively with the extent of negative symptoms in 22q11DS patients, revealing the clinical relevance of present findings. The identified A-core overlaps numerous regions previously identified as affected in 22q11DS as well as in schizophrenia, which approximately 30-40% of 22q11DS patients develop.