Implementació d'un demostrador wireless: network cording i virtualització d'interfícies sense fils

El treball realitzat en aquest projecte es basa en l'implementació d'un demostrador wireless, i més específicament, en l'estudi de les tècniques network coding i virtualització. Network coding és un nou mètode de transmissió de dades que es basa en la codificació de paquets per incrementar el rendiment fins ara obtingut als mètodes de transmissió convencionals. La virtualització és una tècnica que consisteix en compartir de forma més eficient els recursos d'un sistema. En el nostre cas s'utilitzarà la virtualització per dividir una interfície sense fils en diferents usuaris virtuals transmetent i rebent dades simultàniament. L'objectiu del projecte és realitzar un seguit de proves i estudis per veure els avantatges d'aquestes dues tècniques.

Enhancing fault management performance of two-step QoS routing algorithms in GMPLS networks

In this paper a novel methodology aimed at minimizing the probability of network failure and the failure impact (in terms of QoS degradation) while optimizing the resource consumption is introduced. A detailed study of MPLS recovery techniques and their GMPLS extensions are also presented. In this scenario, some features for reducing the failure impact and offering minimum failure probabilities at the same time are also analyzed. Novel two-step routing algorithms using this methodology are proposed. Results show that these methods offer high protection levels with optimal resource consumption

Influence on screening performance of second reading strategies in two lowvolume programs

BACKGROUND: The European Guidelines specify a minimum of 5,000 screening cases to be read yearly by radiologists carrying out second reading in non-centralized programs. This professional requirement is difficult to reach and/or to implement in regional programs covering a sparse population with a high number of participating radiology units, so that alternative blind double reading strategies must be devised. OBJECTIVE: To evaluate the effect on breast cancer screening performances of two second reading strategies used in non-centralized, low-volume programs. METHODS: Reading performances in two Swiss regional breast cancer screening programs (cantons of Wallis and Vaud), covering female populations, aged 50-69, of about 31'000 and 72'000 inhabitants were computed and compared. Both programs had similar screening regimens and organizations, but differed with respect to second reading. One setting applied a selective strategy whereby only experienced radiologists performed second reading; the other elicited not to restrict second readers on the basis of their individual screening activity. Analysis included some 140,000 mammograms performed between 1999 and 2005. RESULTS: Overall, screening performances improved with increasing total volume of reading, albeit not in a linear fashion. Regardless of setting, radiologists attained a higher level of screening accuracy when performing second rather than first readings, and incident rather than prevalent screening cases. The effect of a selective, small group of second readers appeared to impact favorably on the false-positive rate and other indicators of screening quality. As the learning curve depends on the number of mammograms read, these distinct strategies may bear different outcome in the long run. Implications and practical issues for low-volume programs are discussed.

Networks of PhD Students and Academic Performance: A Comparison across Countries

In this article we compare regression models obtained to predict PhD students’ academic performance in the universities of Girona (Spain) and Slovenia. Explanatory variables are characteristics of PhD student’s research group understood as an egocentered social network, background and attitudinal characteristics of the PhD students and some characteristics of the supervisors. Academic performance was measured by the weighted number of publications. Two web questionnaires were designed, one for PhD students and one for their supervisors and other research group members. Most of the variables were easily comparable across universities due to the careful translation procedure and pre-tests. When direct comparison was notpossible we created comparable indicators. We used a regression model in which the country was introduced as a dummy coded variable including all possible interaction effects. The optimal transformations of the main and interaction variables are discussed. Some differences between Slovenian and Girona universities emerge. Some variables like supervisor’s performance and motivation for autonomy prior to starting the PhD have the same positive effect on the PhD student’s performance in both countries. On the other hand, variables like too close supervision by the supervisor and having children have a negative influence in both countries. However, we find differences between countries when we observe the motivation for research prior to starting the PhD which increases performance in Slovenia but not in Girona. As regards network variables, frequency of supervisor advice increases performance in Slovenia and decreases it in Girona. The negative effect in Girona could be explained by the fact that additional contacts of the PhD student with his/her supervisor might indicate a higher workload in addition to or instead of a better advice about the dissertation. The number of external student’s advice relationships and social support mean contact intensity are not significant in Girona, but they have a negative effect in Slovenia. We might explain the negative effect of external advice relationships in Slovenia by saying that a lot of external advice may actually result from a lack of the more relevant internal advice

THE ROLE OF SPINDLES FOR SLEEP: MANIPULATING OSCILLATORY ACTIVITY IN THE THALAMOCORTICAL NETWORK

Modern urban lifestyle encourages the prolongation of wakefulness, leaving less and less time for sleep. Although the exact functions of sleep remain one of the biggest mysteries in neuroscience, the society is well aware of the negative consequences of sleep loss on human physical and mental health and performance. Enhancing sleep's recuperative functions might allow shortening sleep duration while preserving the beneficial effects of sleep. During sleep, brain activity oscillates across a continuum of frequencies. Individual oscillations have been suggested to underlie distinct functions for sleep and cognition. Gaining control about individual oscillations might allow boosting their specific functions. Sleep spindles are 11 - 15 Hz oscillations characteristic for light non-rapid-eye-movement sleep (NREMS) and have been proposed to play a role in memory consolidation and sleep protection against environmental stimuli. The reticular thalamic nucleus (nRt) has been identified as the major pacemaker of spindles. Intrinsic oscillatory burst discharge in nRt neurons, arising from the interplay of low-threshold (T-type) Ca2+ channels (T channels) and small conductance type 2 (SK2) K+ channels (SK2 channels), underlies this pacemaking function. In the present work we investigated the impact of altered nRt bursting on spindle generation during sleep by studying mutant mice for SK2 channels and for CaV3.3 channels, a subtype of T channels. Using in vitro electrophysiology I showed that nRt bursting was abolished in CaV3.3 knock out (CaV3.3 KO) mice. In contrast, in SK2 channel over-expressing (SK2-OE) nRt cells, intrinsic repetitive bursting was prolonged. Compared to wildtype (WT) littermates, altered nRt burst discharge lead to weakened thalamic network oscillations in vitro in CaV3.3 KO mice, while oscillatory activity was prolonged in SK2-OE mice. Sleep electroencephalographic recordings in CaV3.3 KO and SK2-OE mice revealed that reduced or potentiated nRt bursting respectively weakened or prolonged sleep spindle activity at the NREMS - REMS transition. Furthermore, SK2-OE mice showed more consolidated NREMS and increased arousal thresholds, two correlates of good sleep quality. This thesis work suggests that CaV3.3 and SK2 channels may be targeted in order to modulate sleep spindle activity. Furthermore, it proposes a novel function for spindles in NREMS consolidation. Finally, it provides evidence that sleep quality may be improved by promoting spindle activity, thereby supporting the hypothesis that sleep quality can be enhanced by modulating oscillatory activity in the brain. Le style de vie moderne favorise la prolongation de l'éveil, laissant de moins en moins de temps pour le sommeil. Même si le rôle exact du sommeil reste un des plus grands mystères des neurosciences, la société est bien consciente des conséquences négatives que provoque un manque de sommeil, à la fois sur le plan de la santé physique et mentale ainsi qu'au niveau des performances cognitives. Augmenter les fonctions récupératrices du sommeil pourrait permettre de raccourcir la durée du sommeil tout en en conservant les effets bénéfiques. Durant le sommeil, on observe des oscillations à travers un continuum de fréquences. Il a été proposé que chaque oscillation pourrait être à l'origine de fonctions spécifiques pour le sommeil et la cognition. Pouvoir de contrôler les oscillations individuelles permettrait d'augmenter leurs fonctions respectives. Les fuseaux sont des oscillations de 11 à 15 Hz caractéristiques du sommeil à ondes lentes léger et il a été suggéré qu'elles jouent un rôle majeur pour la consolidation de la mémoire ainsi que dans la protection du sommeil contre les stimuli environnementaux. Le nucleus réticulaire du thalamus (nRt) a été identifié en tant que générateur de rythme des fuseaux. Les bouffées oscillatoires intrinsèques des neurones du nRt, provenant de l'interaction de canaux calciques à bas seuil de type T (canaux T) et de canaux potassiques à faible conductance de type 2 (canaux SK2), sont à l'origine de la fonction de générateur de rythme. Dans ce travail, j'ai étudié l'impact de la modulation de bouffées de nRT sur la génération des fuseaux pendant le sommeil en investiguant des souris génétiquement modifiées pour les canaux SK2 et les canaux CaV3.3, un sous-type de canaux T. En utilisant l'électrophysiologie in vitro j'ai démontré que les bouffées du nRT étaient abolies dans les souris knock-out du type CaV3.3 (CaV3.3 KO). D'autre part, dans les cellules nRT sur-exprimant les canaux SK2 (SK2-OE), les bouffées oscillatoires intrinsèques étaient prolongées. Par rapport aux souris wild type, les souris CaV3.3 KO ont montré un affaiblissement des oscillations thalamiques en réponse à un changement des bouffées de nRT, alors que l'activité oscillatoire était prolongée dans les souris SK2-OE. Des enregistrements EEG du sommeil dans des souris de type CaV3.3 KO et SK2-OE ont révélé qu'une réduction ou augmentation des bouffées nRT ont respectivement affaibli ou prolongé l'activité des fuseaux durant les transitions du sommeil à ondes lentes au sommeil paradoxal. De plus, les souris SK2-OE ont montré des signes de consolidation du sommeil à ondes lentes et un seuil augmenté pour le réveil, deux mesures qui corrèlent avec une bonne qualité du sommeil. Le travail de cette thèse propose que les canaux CaV3.3 et SK2 pourrait être ciblés pour moduler l'activité des fuseaux. De plus, je propose une fonction nouvelle pour les fuseaux dans la consolidation du sommeil à ondes lentes. Finalement je suggère que la qualité du sommeil peut être améliorée en promouvant l'activité des fuseaux, soutenant ainsi l'idée que la qualité du sommeil peut être améliorée en modulant l'activité oscillatoire dans le cerveau.

Multimarket contact externalities: the effect of rival's multimarket contacts on focal firm performance

Given that firms develop their activities in a network of multiple players, interfirm rivalry is not only a matter of direct competitors, but also of indirect competition. In spite of this, the literature on competitive dynamics tends to focus on analyzing rivalry as an exclusive function of the competitive relationship between a focal firm and its direct rivals. In this article, we extend competitive dynamics literature by considering how focal firms are affected by the relationships of their rivals with third-party firms. Specifically, we study the effect that the multimarket contacts of rivals produces on the performance of the focal firm. Additionally, we incorporate the idea that there are different strategic options for operating in an industry that affect the intensity of multimarket contact externalities. Our results show that multimarket contact among firms causes externalities that indirectly affect firms that are not directly involved in this competitive relationship. We find that multimarket contact externalities differ between and within strategic groups.

Kinship in entrepreneur networks: Performance effects of resource assembly in Africa

We examine the relationship between structural social capital, resource assembly, and firm performance of entrepreneurs in Africa. We posit that social capital primarily composed of kinship or family ties helps the entrepreneur to raise resources, but it does so at a cost. Using data drawn from small firms in Kampala, Uganda, we explore how shared identity among the entrepreneur's social network moderates this relationship. A large network contributed a higher quantity of resources raised, but at a higher cost when shared identity was high. We discuss the implications of these findings for the role of family ties and social capital in resource assembly, with an emphasis on developing economies.

Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

Spontaneous pre-stimulus fluctuations in the activity of right fronto-parietal areas influence inhibitory control performance.

Inhibitory control refers to the ability to suppress planned or ongoing cognitive or motor processes. Electrophysiological indices of inhibitory control failure have been found to manifest even before the presentation of the stimuli triggering the inhibition, suggesting that pre-stimulus brain-states modulate inhibition performance. However, previous electrophysiological investigations on the state-dependency of inhibitory control were based on averaged event-related potentials (ERPs), a method eliminating the variability in the ongoing brain activity not time-locked to the event of interest. These studies thus left unresolved whether spontaneous variations in the brain-state immediately preceding unpredictable inhibition-triggering stimuli also influence inhibitory control performance. To address this question, we applied single-trial EEG topographic analyses on the time interval immediately preceding NoGo stimuli in conditions where the responses to NoGo trials were correctly inhibited [correct rejection (CR)] vs. committed [false alarms (FAs)] during an auditory spatial Go/NoGo task. We found a specific configuration of the EEG voltage field manifesting more frequently before correctly inhibited responses to NoGo stimuli than before FAs. There was no evidence for an EEG topography occurring more frequently before FAs than before CR. The visualization of distributed electrical source estimations of the EEG topography preceding successful response inhibition suggested that it resulted from the activity of a right fronto-parietal brain network. Our results suggest that the fluctuations in the ongoing brain activity immediately preceding stimulus presentation contribute to the behavioral outcomes during an inhibitory control task. Our results further suggest that the state-dependency of sensory-cognitive processing might not only concern perceptual processes, but also high-order, top-down inhibitory control mechanisms.

PhD Students’ Research Group Social Capital in Two Countries: A Clustering Approach with Duocentred Network Measures

The article examines the structure of the collaboration networks of research groups where Slovenian and Spanish PhD students are pursuing their doctorate. The units of analysis are student-supervisor dyads. We use duocentred networks, a novel network structure appropriate for networks which are centred around a dyad. A cluster analysis reveals three typical clusters of research groups. Those which are large and belong to several institutions are labelled under a bridging social capital label. Those which are small, centred in a single institution but have high cohesion are labelled as bonding social capital. Those which are small and with low cohesion are called weak social capital groups. Academic performance of both PhD students and supervisors are highest in bridging groups and lowest in weak groups. Other variables are also found to differ according to the type of research group. At the end, some recommendations regarding academic and research policy are drawn

A randomized concave programming method for choice network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.

A new compact linear programming formulation for choice network revenue management

The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.

Parallel scheduling of multiclass M/M/m queues: Approximate and heavy-traffic optimization of achievable performance

We address the problem of scheduling a multiclass $M/M/m$ queue with Bernoulli feedback on $m$ parallel servers to minimize time-average linear holding costs. We analyze the performance of a heuristic priority-index rule, which extends Klimov's optimal solution to the single-server case: servers select preemptively customers with larger Klimov indices. We present closed-form suboptimality bounds (approximate optimality) for Klimov's rule, which imply that its suboptimality gap is uniformly bounded above with respect to (i) external arrival rates, as long as they stay within system capacity;and (ii) the number of servers. It follows that its relativesuboptimality gap vanishes in a heavy-traffic limit, as external arrival rates approach system capacity (heavy-traffic optimality). We obtain simpler expressions for the special no-feedback case, where the heuristic reduces to the classical $c \mu$ rule. Our analysis is based on comparing the expected cost of Klimov's ruleto the value of a strong linear programming (LP) relaxation of the system's region of achievable performance of mean queue lengths. In order to obtain this relaxation, we derive and exploit a new set ofwork decomposition laws for the parallel-server system. We further report on the results of a computational study on the quality of the $c \mu$ rule for parallel scheduling.

An analysis of the accounting principles applied by the European Farm Accountancy Data Network

In spite of its relative importance in the economy of many countriesand its growing interrelationships with other sectors, agriculture has traditionally been excluded from accounting standards. Nevertheless, to support its Common Agricultural Policy, for years the European Commission has been making an effort to obtain standardized information on the financial performance and condition of farms. Through the Farm Accountancy Data Network (FADN), every year data are gathered from a rotating sample of 60.000 professional farms across all member states. FADN data collection is not structured as an accounting cycle but as an extensive questionnaire. This questionnaire refers to assets, liabilities, revenues and expenses, and seems to try to obtain a "true and fair view" of the financial performance and condition of the farms it surveys. However, the definitions used in the questionnaire and the way data is aggregated often appear flawed from an accounting perspective. The objective of this paper is to contrast the accounting principles implicit in the FADN questionnaire with generally accepted accounting principles, particularly those found in the IVth Directive of the European Union, on the one hand, and those recently proposed by the International Accounting Standards Committee’s Steering Committeeon Agriculture in its Draft Statement of Principles, on the other hand. There are two reasons why this is useful. First, it allows to make suggestions how the information provided by FADN could be more in accordance with the accepted accounting framework, and become a more valuable tool for policy makers, farmers, and other stakeholders. Second, it helps assessing the suitability of FADN to become the starting point for a European accounting standard on agriculture.