Les neurones dopaminergiques (DA) de l’aire tegmentale ventrale (VTA) sont influencés par différents stimuli comme des récompenses naturelles et d’autres stimuli moins physiologiques tels que les drogues d’abus. Ces drogues agissent en détournant les mécanismes d’apprentissage qui sous-tendent normalement la motivation pour des renforçateurs naturels. Les neurones DA, en conditions physiologiques, sont subtilement régulés par une balance entre tonus GABA et glutamatergique. Ils sont soumis à de multiples sources inhibitrices dont le noyau accumbens, les interneurones locaux ou les neurones GABA de la queue de la VTA (tVTA). Le glutamate est également important dans leur modulation. Il contrôle leur activité en bursts, qui est le mode de décharge le plus efficace pour libérer de la dopamine et coder des informations associées à la récompense. Il permet des adaptations synaptiques à long terme qui se sont révélées importantes dans la prise de drogue. La connaissance des facteurs endogènes qui contrôlent l’excitabilité des cellules DA de la VTA est essentielle à la compréhension des processus physiologiques (recherche de plaisir…) mais aussi pathologiques (addiction…). L’objectif de mon travail a été de comprendre les circuits de régulation des neurones DA en conditions physiologiques et lors de l’exposition à la morphine. Dans un premier temps, nous avons étudié les mécanismes de régulation des neurones DA par la formation hippocampique ventrale incluant le subiculum ventral et l’aire CA1 ventrale (vSUB/CA1). Grâce à l’utilisation d’approches d’électrophysiologie in vivo chez le rat anesthésié, nous avons montré que le vSUB/CA1 exerce un contrôle excitateur glutamatergique des neurones DA. Nous avons mis en évidence que cette voie vSUB/CA1-VTA est polysynaptique, faisant intervenir le BNST comme relais. J’ai aussi pu confirmer le rôle fonctionnel de la tVTA en tant que nouvelle structure GABA modulant l’activité des neurones DA, renforçant ainsi l’idée d’une balance entre tonus GABA et glutamatergique régulant les neurones DA in vivo.La deuxième partie de ma thèse a consisté en l’étude des circuits neuronaux à l’origine des effets excitateurs de la morphine sur les neurones DA de la VTA in vivo. L’hypothèse actuelle est que la morphine excite les neurones DA par un mécanisme de désinhibition en inhibant les neurones GABA de la VTA. Grâce à l’utilisation d’approches multiples, nous avons proposé un nouveau circuit expliquant les effets de la morphine. Ces effets sont la conséquence d’une modification de la balance GABA/glutamate par la morphine. Elle se traduit par une diminution du tonus GABA et d’une augmentation du tonus glutamatergique. Enfin, nous avons pu démontrer qu’une seule exposition à la cocaïne augmente l’activité de base des neurones DA. Chez ces animaux, les effets excitateurs de la morphine sont potentialisés confirmant ainsi l’hypothèse que l’amplitude de l’activation des neurones DA par la morphine dépend de leur état d’excitabilité. / Dopaminergic (DA) neurons of the ventral tegmental area (VTA) are influenced by several stimuli such as natural rewards or drugs of abuse. Drugs shunt learning mechanisms which underlie motivation for natural reinforcers. Under physiological conditions, DA neurons are regulated by a balance between GABA and glutamatergic inputs. They receive several inhibitory inputs especially from the nucleus accumbens, VTA local interneurons and GABA neurons of the tail of the VTA (tVTA). Glutamate is also important in modulating DA neuron activity. It controls their bursting activity which is the most efficient way to release dopamine and to encode reward-associated informations. It allows long term synaptic adaptations important for addiction. Knowing how these endogenous factors control VTA DA neuron excitability is essential to understand physiological (search for pleasure…) and pathological (drug addiction…) processes.In the first part of my thesis, we studied the regulation of the VTA by the hippocampal formation including the ventral subiculum and the ventral CA1 area (vSUB/CA1). Using electrophysiological approaches in anesthetized animal, we showed that the vSUB/CA1 controls VTA DA neurons and that this input is glutamatergic. We also demonstrated that the vSUB/CA1-VTA pathway is polysynaptic implicating the BNST as a relay. I also confirmed the inhibitory control of the VTA by tVTA, new GABA input to DA neurons. Thus, in vivo, DA neurons are regulated by a balance between GABA and glutamatergic inputs. The second part of my research consisted in studying the neuronal circuits underlying excitatory effects of morphine on VTA DA neurons in vivo. The actual hypothesis is that morphine excites DA neurons by a disinhibition mechanism inhibiting VTA GABA neurons. Using several approaches (electrophysiological approaches in anesthetized animal, tract-tracing methods), we proposed a new circuitry explaining morphine effects. These excitatory effects result from a modification of the balance between GABA and glutamatergic inputs with a decrease of the GABA tone and an increase of the glutamatergic tone. Finally, we demonstrated that an acute cocaine exposure increases DA neuron activity. In animals exposed to cocaine, morphine excitatory effects are potentiated. This last experiment confirms the hypothesis that the amplitude of morphine-induced activation of VTA DA neurons depends on their excitability state.

<p>Minimum cycle mean (MCM) is an important concept in directed graphs. From clock period optimization, timing analysis to layout optimization, minimum cycle mean algorithms have found widespread use in VLSI system design optimization. With transistor size scaling to 10nm and below, complexities and size of the systems have grown rapidly over the last decade. Scalability of the algorithms both in terms of their runtime and memory usage is therefore important. </p> <p><br></p> <p>Among the few classical MCM algorithms, the algorithm by Young, Tarjan, and Orlin (YTO), has been particularly popular. When implemented with a binary heap, the YTO algorithm has the best runtime performance although it has higher asymptotic time complexity than Karp's algorithm. However, as an efficient implementation of YTO relies on data redundancy, its memory usage is higher and could be a prohibitive factor in large size problems. On the other hand, a typical implementation of Karp's algorithm can also be memory hungry. An early termination technique from Hartmann and Orlin (HO) can be directly applied to Karp's algorithm to improve its runtime performance and memory usage. Although not as efficient as YTO in runtime, HO algorithm has much less memory usage than YTO. We propose several improvements to HO algorithm. The proposed algorithm has comparable runtime performance to YTO for circuit graphs and dense random graphs while being better than HO algorithm in memory usage. </p> <p><br></p> <p>Minimum balancing of a directed graph is an application of the minimum cycle mean algorithm. Minimum balance algorithms have been used to optimally distribute slack for mitigating process variation induced timing violation issues in clock network. In a conventional minimum balance algorithm, the principal subroutine is that of finding MCM in a graph. In particular, the minimum balance algorithm iteratively finds the minimum cycle mean and the corresponding minimum-mean cycle, and uses the mean and cycle to update the graph by changing edge weights and reducing the graph size. The iterations terminate when the updated graph is a single node. Studies have shown that the bottleneck of the iterative process is the graph update operation as previous approaches involved updating the entire graph. We propose an improvement to the minimum balance algorithm by performing fewer changes to the edge weights in each iteration, resulting in better efficiency.</p> <p><br></p> <p>We also apply the minimum cycle mean algorithm in latency insensitive system design. Timing violations can occur in high performance communication links in system-on-chips (SoCs) in the late stages of the physical design process. To address the issues, latency insensitive systems (LISs) employ pipelining in the communication channels through insertion of the relay stations. Although the functionality of a LIS is robust with respect to the communication latencies, such insertion can degrade system throughput performance. Earlier studies have shown that the proper sizing of buffer queues after relay station insertion could eliminate such performance loss. However, solving the problem of maximum performance buffer queue sizing requires use of mixed integer linear programming (MILP) of which runtime is not scalable. We formulate the problem as a parameterized graph optimization problem where for every communication channel there is a parameterized edge with buffer counts as the edge weight. We then use minimum cycle mean algorithm to determine from which edges buffers can be removed safely without creating negative cycles. This is done iteratively in the similar style as the minimum balance algorithm. Experimental results suggest that the proposed approach is scalable. Moreover, quality of the solution is observed to be as good as that of the MILP based approach.</p><p><br></p>

Dans cette de thèse, nous nous intéressons à la modélisation non paramétrique de données extrêmes spatiales. Nos résultats sont basés sur un cadre principal de la théorie des valeurs extrêmes, permettant ainsi d’englober les lois de type Pareto. Ce cadre permet aujourd’hui d’étendre l’étude des événements extrêmes au cas spatial à condition que les propriétés asymptotiques des estimateurs étudiés vérifient les conditions classiques de la Théorie des Valeurs Extrêmes (TVE) en plus des conditions locales sur la structure des données proprement dites. Dans la littérature, il existe un vaste panorama de modèles d’estimation d’événements extrêmes adaptés aux structures des données pour lesquelles on s’intéresse. Néanmoins, dans le cas de données extrêmes spatiales, hormis les modèles max stables,il n’en existe que peu ou presque pas de modèles qui s’intéressent à l’estimation fonctionnelle de l’indice de queue ou de quantiles extrêmes. Par conséquent, nous étendons les travaux existants sur l’estimation de l’indice de queue et des quantiles dans le cadre de données indépendantes ou temporellement dépendantes. La spécificité des méthodes étudiées réside sur le fait que les résultats asymptotiques des estimateurs prennent en compte la structure de dépendance spatiale des données considérées, ce qui est loin d’être trivial. Cette thèse s’inscrit donc dans le contexte de la statistique spatiale des valeurs extrêmes. Elle y apporte trois contributions principales. • Dans la première contribution de cette thèse permettant d’appréhender l’étude de variables réelles spatiales au cadre des valeurs extrêmes, nous proposons une estimation de l’indice de queue d’une distribution à queue lourde. Notre approche repose sur l’estimateur de Hill (1975). Les propriétés asymptotiques de l’estimateur introduit sont établies lorsque le processus spatial est adéquatement approximé par un processus M−dépendant, linéaire causal ou lorsqu'il satisfait une condition de mélange fort (a-mélange). • Dans la pratique, il est souvent utile de lier la variable d’intérêt Y avec une co-variable X. Dans cette situation, l’indice de queue dépend de la valeur observée x de la co-variable X et sera appelé indice de queue conditionnelle. Dans la plupart des applications, l’indice de queue des valeurs extrêmes n’est pas l’intérêt principal et est utilisé pour estimer par exemple des quantiles extrêmes. La contribution de ce chapitre consiste à adapter l’estimateur de l’indice de queue introduit dans la première partie au cadre conditionnel et d’utiliser ce dernier afin de proposer un estimateur des quantiles conditionnels extrêmes. Nous examinons les modèles dits "à plan fixe" ou "fixed design" qui correspondent à la situation où la variable explicative est déterministe et nous utlisons l’approche de la fenêtre mobile ou "window moving approach" pour capter la co-variable. Nous étudions le comportement asymptotique des estimateurs proposés et donnons des résultats numériques basés sur des données simulées avec le logiciel "R". • Dans la troisième partie de cette thèse, nous étendons les travaux de la deuxième partie au cadre des modèles dits "à plan aléatoire" ou "random design" pour lesquels les données sont des observations spatiales d’un couple (Y,X) de variables aléatoires réelles. Pour ce dernier modèle, nous proposons un estimateur de l’indice de queue lourde en utilisant la méthode des noyaux pour capter la co-variable. Nous utilisons un estimateur de l’indice de queue conditionnelle appartenant à la famille de l’estimateur introduit par Goegebeur et al. (2014b). / In this thesis, we investigate nonparametric modeling of spatial extremes. Our resultsare based on the main result of the theory of extreme values, thereby encompass Paretolaws. This framework allows today to extend the study of extreme events in the spatialcase provided if the asymptotic properties of the proposed estimators satisfy the standardconditions of the Extreme Value Theory (EVT) in addition to the local conditions on thedata structure themselves. In the literature, there exists a vast panorama of extreme events models, which are adapted to the structures of the data of interest. However, in the case ofextreme spatial data, except max-stables models, little or almost no models are interestedin non-parametric estimation of the tail index and/or extreme quantiles. Therefore, weextend existing works on estimating the tail index and quantile under independent ortime-dependent data. The specificity of the methods studied resides in the fact that theasymptotic results of the proposed estimators take into account the spatial dependence structure of the relevant data, which is far from trivial. This thesis is then written in thecontext of spatial statistics of extremes. She makes three main contributions.• In the first contribution of this thesis, we propose a new approach of the estimatorof the tail index of a heavy-tailed distribution within the framework of spatial data. This approach relies on the estimator of Hill (1975). The asymptotic properties of the estimator introduced are established when the spatial process is adequately approximated by aspatial M−dependent process, spatial linear causal process or when the process satisfies a strong mixing condition.• In practice, it is often useful to link the variable of interest Y with covariate X. Inthis situation, the tail index depends on the observed value x of the covariate X and theunknown fonction (.) will be called conditional tail index. In most applications, the tailindexof an extreme value is not the main attraction, but it is used to estimate for instance extreme quantiles. The contribution of this chapter is to adapt the estimator of the tail index introduced in the first part in the conditional framework and use it to propose an estimator of conditional extreme quantiles. We examine the models called "fixed design"which corresponds to the situation where the explanatory variable is deterministic. To tackle the covariate, since it is deterministic, we use the window moving approach. Westudy the asymptotic behavior of the estimators proposed and some numerical resultsusing simulated data with the software "R".• In the third part of this thesis, we extend the work of the second part of the framemodels called "random design" for which the data are spatial observations of a pair (Y,X) of real random variables . In this last model, we propose an estimator of heavy tail-indexusing the kernel method to tackle the covariate. We use an estimator of the conditional tail index belonging to the family of the estimators introduced by Goegebeur et al. (2014b).

With the shifting landscape of computing hardware architectures and the emergence of new computing environments (e.g., large main-memory systems, hundreds of CPUs, distributed and virtualized cloud-based resources), state-of-the-art designs of transaction processing systems that rely on conventional wisdom suffer from lost performance optimization opportunities. This dissertation challenges conventional wisdom to rethink the design and implementation of transaction processing systems for modern computing environments.<div><br></div><div>We start by tackling the vertical hardware scaling challenge, and propose a deterministic approach to transaction processing on emerging multi-sockets, many-core, shared memory architecture to harness its unprecedented available parallelism. Our proposed priority-based queue-oriented transaction processing architecture eliminates the transaction contention footprint and uses speculative execution to improve the throughput of centralized deterministic transaction processing systems. We build QueCC and demonstrate up to two orders of magnitude better performance over the state-of-the-art.<br></div><div><br></div><div>We further tackle the horizontal scaling challenge and propose a distributed queue-oriented transaction processing engine that relies on queue-oriented communication to eliminate the traditional overhead of commitment protocols for multi-partition transactions. We build Q-Store, and demonstrate up to 22x improvement in system throughput over the state-of-the-art deterministic transaction processing systems.<br></div><div><br></div><div>Finally, we propose a generalized framework for designing distributed and replicated deterministic transaction processing systems. We introduce the concept of speculative replication to hide the latency overhead of replication. We prototype the speculative replication protocol in QR-Store and perform an extensive experimental evaluation using standard benchmarks. We show that QR-Store can achieve a throughput of 1.9 million replicated transactions per second in under 200 milliseconds and a replication overhead of 8%-25%compared to non-replicated configurations.<br></div>

Historically, the United States (US) electric grid has been a stable one-way power delivery infrastructure that supplies centrally-generated electricity to its predictably consuming demand. However, the US electric grid is now undergoing a huge transformation from a simple and static system to a complex and dynamic network, which is starting to interconnect intermittent distributed energy resources (DERs), portable electric vehicles (EVs), and load-altering home automation devices, that create bidirectional power flow or stochastic load behavior. In order for this grid of the future to effectively embrace the high penetration of these disruptive and fast-responding digital technologies without compromising its safety, reliability, and affordability, plug-and-play interoperability within the field area network must be enabled between operational technology (OT), information technology (IT), and telecommunication assets in order to seamlessly and securely integrate into the electric utility's operations and planning systems in a modular, flexible, and scalable fashion. This research proposes a potential approach to simplifying the translation and contextualization of operational data on the electric grid without being routed to the utility datacenter for a control decision. This methodology integrates modern software technology from other industries, along with utility industry-standard semantic models, to overcome information siloes and enable interoperability. By leveraging industrial engineering tools, a framework is also developed to help devise a reference architecture and use-case application process that is applied and validated at a US electric utility.

In Sweden, where a decentralized healthcare system is applied, all patients are registered at a primary healthcare center. To access most of the publicly funded specialized care clinics, patients need to be referred by a general physician at the primary healthcare center. However, long waiting times and queues to access specialized care clinics in Sweden, has been a serious problem and concern for decades. Addressing this issue is important for improving patients’ transition to specialized care and the functionality of the Swedish healthcare system. The aim of this thesis is to explore the Swedish healthcare system to analyze the transition of patients to specialized care clinics and identify the reasons for long waiting times and queues. This was done by analyzing the Swedish healthcare system and develop a serious game prototype which models the process of access to specialized care within the Swedish healthcare system. The prototype was used to understand the delay that happens in patients’ transition and access process to specialized care services.  A system analysis including a literature review is conducted to gain an understanding of the Swedish healthcare system and gather data to be used in the designed prototype. The outcome of the system analysis is a visual representation of the Swedish healthcare system including laws and stakeholders. A game frame is developed from the system analysis. Maps, tables, and a flow-diagram are developed to visualize patients’ access to specialized care. All of this was used to design the game prototype. The final prototype is developed through an iterative process, where several prototypes are designed and tested through game sessions with experts. The prototypes are evaluated after each game session. Finally, learning and findings gained from the prototypes design and the game sessions are documented. This includes reasons for long waiting times for a first visit at a specialized care clinic such as the structure of the Swedish healthcare system, mainly that the PHC is the foundation of the system. Staff shortages, and the need for a referral to access most of the specialized clinics are also discussed and stated along with other reasons. / I Sverige tillämpas decentraliserat sjukvårdssystem där alla patienter registeras vid en vårdscentral. För att få tillgång till de flesta offentligt finansierade specialistvårdsmottagningar remitteras patienterna av en allmänläkare vid vårdscentralen. Dock har långa väntetider och köer till specialiserad sjukvård varit ett allvarligt problem och bekymmer i Sverige i årtionden. Att hantera denna fråga är avgörande för att förbättra patienternas övergång till specialiserad vård och för att den svenska sjukvården ska fungera smidigt. Målet med detta projekt är att utforska det svenska sjukvårdssystemet för att analysera patientövergångar till specialistvårdsmottagningar och identifiera orsakerna till de långa väntetiderna och köerna. Detta uppnåddes genom att analysera det svenska sjukvårdssystemet och utveckla en prototyp av ett seröst simuleringssspel som simulerarr processen att få tillgång till specialiserad vård inom det svenska sjukvårdssystemet. Prototypen användes för att förstå förseningar som uppstår under patientövergångar och tillgång till specialvårdtjänster. En systemanalys inklusive en litteraturöversikt genomförs för att få en djupare förståelse för det svenska sjukvårdssystemet och samla in data som kommer att användas i den utformade prototypen. Resultatet av systemanalysen är en visuell representation av det svenska sjukvårdssystemet, inklusive juridiska lagar och berörda parter. Genom systemanalys utvecklas ett spelramverk. Kartor, tabeller och ett flödesschema utvecklas för att visuellt framställa patienternas tillgång till specialiserad vård. Allt detta användes sedan för att designa spelprototypen. Den slutliga prototypen utvecklas genom en iterativ process, där flera prototyper designas och testas genom spel sessioner med experter. Prototyperna utvärderas och dokumenteras efter varje spel-sessioner. Slutligen dokumenteras de lärdomar och resultat som erhållits från prototyputformningen och spel-sessionerna. Detta inkluderar orsaker till långa väntetider för ett första besök på en specialiserad vårdmottagning såsom strukturen i den svenska sjukvården, främst att PHC är grunden i systemet. Personalbrist och behovet av remiss för att komma åt de flesta specialiserade klinikerna diskuteras också och anges tillsammans med andra skäl.