Development of a miniaturized microscope for depth-scanning imaging at subcellular resolution in freely behaving animals

Le fonctionnement du cerveau humain est fascinant. En seulement quelques millisecondes, des milliards de neurones synchronisés perçoivent, traitent et redirigent les informations permettant le contrôle de notre corps, de nos sentiments et de nos pensées. Malheureusement, notre compréhension du cerveau reste limitée et de multiples questions physiologiques demeurent. Comment sont exactement reliés le fonctionnement neuronal et le comportement humain ? L’imagerie de l’activité neuronale au moyen de systèmes miniatures est l’une des voies les plus prometteuses permettant d’étudier le cerveau des animaux se déplaçant librement. Cependant, le développement de ces outils n’est pas évident et de multiples compromis techniques doivent être faits pour arriver à des systèmes suffisamment petits et légers. Les outils actuels ont donc souvent des limitations concernant leurs caractéristiques physiques et optiques. L’un des problèmes majeur est le manque d’une lentille miniature électriquement réglable et à faible consommation d’énergie permettant l’imagerie avec un balayage en profondeur. Dans cette thèse, nous proposons un nouveau type de dispositif d’imagerie miniature qui présente de multiples avantages mécaniques, électriques et optiques par rapport aux systèmes existants. Le faible poids, la petite dimension, la capacité de moduler électriquement la distance focale à l’aide d’une lentille à cristaux liquides (CL) et la capacité d’imager des structures fines sont au cœur des innovations proposées. Dans un premier temps, nous présenterons nos travaux (théoriques et expérimentaux) de conception, assemblage et optimisation de la lentille à CL accordable (TLCL, pour tunable liquid crystal lens). Deuxièmement, nous présenterons la preuve de concept macroscopique du couplage optique entre la TLCL et la lentille à gradient d’indice (GRIN, pour gradient index) en forme d’une tige. Utilisant le même système, nous démontrerons la capacité de balayage en profondeur dans le cerveau des animaux anesthésiés. Troisièmement, nous montrerons un dispositif d’imagerie (2D) miniature avec de nouvelles caractéristiques mécaniques et optiques permettant d’imager de fines structures neuronales dans des tranches de tissus cérébraux fixes. Enfin, nous présenterons le dispositif miniaturisé, avec une TLCL intégrée. Grâce à notre système, nous obtenons ≈ 100 µm d’ajustement électrique de la profondeur d’imagerie qui permet d’enregistrer l’activité de fines structures neuronales lors des différents comportements (toilettage, marche, etc.) de la souris.The functioning of the human brain is fascinating. In only a few milliseconds, billions of finely tuned and synchronized neurons perceive, process and exit the information that drives our body, our feelings and our thoughts. Unfortunately, our understating of the brain is limited and multiple physiological questions remain. How exactly are related neural functioning and human behavior ? The imaging of the neuronal activity by means of miniaturized systems is one of the most promising avenues allowing to study the brain of the freely moving subjects. However, the development of these tools is not obvious and multiple technical trade-offs must be made to build a system that is sufficiently small and light. Therefore, the available tools have different limitations regarding their physical and optical characteristics. One of the major problems is the lack of an electrically adjustable and energy-efficient miniature lens allowing to scan in depth. In this thesis, we propose a new type of miniature imaging device that has multiple mechanical, electrical and optical advantages over existing systems. The low weight, the small size, the ability to electrically modulate the focal distance using a liquid crystal (LC) lens and the ability to image fine structures are among the proposed innovations. First, we present our work (theoretical and experimental) of design, assembling and optimization of the tunable LC lens (TLCL). Second, we present the macroscopic proof-of-concept optical coupling between the TLCL and the gradient index lens (GRIN) in the form of a rod. Using the same system, we demonstrate the depth scanning ability in the brain of anaesthetized animals. Third, we show a miniature (2D) imaging device with new mechanical and optical features allowing to image fine neural structures in fixed brain tissue slices. Finally, we present a state-of-the-art miniaturized device with an integrated TLCL. Using our system, we obtain a ≈ 100 µm electrical depth adjustment that allows to record the activity of fine neuronal structures during the various behaviours (grooming, walking, etc.) of the mouse

Développement d’un système intelligent de reconnaissance automatisée pour la caractérisation des états de surface de la chaussée en temps réel par une approche multicapteurs

Le rôle d’un service dédié à l’analyse de la météo routière est d’émettre des prévisions et des avertissements aux usagers quant à l’état de la chaussée, permettant ainsi d’anticiper les conditions de circulations dangereuses, notamment en période hivernale. Il est donc important de définir l’état de chaussée en tout temps. L’objectif de ce projet est donc de développer un système de détection multicapteurs automatisée pour la caractérisation en temps réel des états de surface de la chaussée (neige, glace, humide, sec). Ce mémoire se focalise donc sur le développement d’une méthode de fusion de données images et sons par apprentissage profond basée sur la théorie de Dempster-Shafer. Les mesures directes pour l’acquisition des données qui ont servi à l’entrainement du modèle de fusion ont été effectuées à l’aide de deux capteurs à faible coût disponibles dans le commerce. Le premier capteur est une caméra pour enregistrer des vidéos de la surface de la route. Le second capteur est un microphone pour enregistrer le bruit de l’interaction pneu-chaussée qui caractérise chaque état de surface. La finalité de ce système est de pouvoir fonctionner sur un nano-ordinateur pour l’acquisition, le traitement et la diffusion de l’information en temps réel afin d’avertir les services d’entretien routier ainsi que les usagers de la route. De façon précise, le système se présente comme suit :1) une architecture d’apprentissage profond classifiant chaque état de surface à partir des images issues de la vidéo sous forme de probabilités ; 2) une architecture d’apprentissage profond classifiant chaque état de surface à partir du son sous forme de probabilités ; 3) les probabilités issues de chaque architecture ont été ensuite introduites dans le modèle de fusion pour obtenir la décision finale. Afin que le système soit léger et moins coûteux, il a été développé à partir d’architectures alliant légèreté et précision à savoir Squeeznet pour les images et M5 pour le son. Lors de la validation, le système a démontré une bonne performance pour la détection des états surface avec notamment 87,9 % pour la glace noire et 97 % pour la neige fondante

Monitoring of security properties using BeepBeep

Runtime enforcement is an effective method to ensure the compliance of program with user-defined security policies. In this paper we show how the stream event processor tool BeepBeep can be used to monitor the security properties of Java programs. The proposed approach relies on AspectJ to generate a trace capturing the program’s runtime behavior. This trace is then processed by BeepBeep, a complex event processing tool that allows complex data-driven policies to be stated and verified with ease. Depending on the result returned by BeepBeep, AspectJ can then be used to halt the execution or take other corrective action. The proposed method offers multiple advantages, notable flexibility in devising and stating expressive user-defined security policies

Incorporating Cognitive Neuroscience Techniques to Enhance User Experience Research Practices

User Experience (UX) involves every interaction that customers have with products, and it plays a crucial role in determining the success of a product in the market. While there are numerous methods available in literature for assessing UX, they often overlook the emotional aspect of the user\u27s experience. As a result, cognitive neuroscience methods are gaining popularity, but they have certain limitations such as difficulty in collecting neurophysiological data, potential for errors, and lengthy procedures. This article aims to examine the most effective research practices using cognitive neuroscience techniques and develop a standardized procedure for conducting UX research. To achieve this objective, the study conducts a comprehensive review of UX research that employs cognitive neuroscience methods published between 2017 and 2022

Prise en charge des douleurs à l'épaule en première ligne de soins : écarts de pratique, déterminants et stratégies de mobilisation des connaissances

Les troubles douloureux de l’épaule (TDE) affectent jusqu’à 55% de la population générale et sont souvent difficiles à traiter. L’objectif de cette thèse était de développer une intervention de mobilisation des connaissances permettant d’implanter les recommandations de guides de pratique clinique (GPC) couvrant la prise en charge des TDE. Pour ce faire, un processus basé sur le cadre conceptuel Knowledge-to-Action a été utilisé. D’abord, une revue systématique des recommandations des GPC à implanter pour améliorer la prise en charge des TDE a été effectuée. Puis, les écarts dans la pratique des cliniciens ont été identifiés à l’aide d’un sondage documentant la prise en charge des TDE ainsi qu’une étude évaluant la concordance entre les physiothérapeutes et les orthopédistes au niveau du diagnostic et de la prise en charge des TDE. Ensuite, les déterminants à l’implantation des recommandations des GPC ont été identifiés en procédant à deux études qualitatives ciblant les expériences et les attentes des patients vivant avec un TDE, puis les barrières et facilitateurs à l’implantation des recommandations des GPC identifiés par les cliniciens. Enfin, l’utilisation du Behaviour Change Wheel et des déterminants ont permis d’identifier des stratégies visant à implanter les recommandations de GPC sur la prise en charge des TDE en première ligne de soins. La revue systématique des GPC a permis de déterminer qu’initialement, les TDE ne requièrent généralement pas d’imagerie médicale et de référence à un médecin spécialiste, mais qu’un programme de réadaptation actif est requis. Selon les résultats du sondage, les médecins de famille (n=76) ont recommandé plus d’imagerie que les physiothérapeutes (n=175). Jusqu’à deux physiothérapeutes sur trois ont sélectionné des traitements non recommandés par les GPC. Les résultats de l’étude de concordance démontrent que l’accord entre physiothérapeutes et orthopédistes était bon au niveau du diagnostic et modéré au niveau du triage des candidats chirurgicaux. Les patients souffrant de TDE interrogés (n=13) ont mentionné, dans la première étude qualitative, avoir attendu que leur douleur soit incapacitante avant de consulter un professionnel. Ces participants s’attendaient alors à recevoir un diagnostic clair et à être référés pour des tests d’imagerie. Finalement, ils espéraient recevoir des explications complètes et se voir proposer des options pertinentes de traitements. Les 19 physiothérapeutes et 16 médecins de famille interrogés dans la deuxième étude qualitative ont indiqué comme barrières à l’utilisation des recommandations des GPC : le manque de connaissances, le manque d’habileté à réaliser une évaluation clinique de l’épaule et la crainte de ne pas détecter une pathologie grave, si présente, sans un test d’imagerie. Le temps insuffisant de consultation avec les patients, leurs attentes et le manque d’accès à certains soins ont aussi été indiqués comme des barrières. Les principales stratégies identifiées suivant ces études incluent donc des interventions éducatives, la préparation de champions cliniques et la création d’équipes cliniques interdisciplinaires. À l’aide de ces stratégies, l’implantation pilote de l’intervention sera réalisée dans des groupes de médecine familiale. L’impact potentiellement bénéfique de cette implantation pourrait, à terme, améliorer la prise en charge des patients atteints de TDE.Shoulder pain is a common and difficult to manage condition that can affect up to 55% of the general population. To optimize shoulder pain management in primary care, the main objective of this thesis was to develop a knowledge mobilization intervention to implement the recommendations from clinical practice guidelines (CPGs) covering the management of different shoulder disorders. A knowledge mobilization process based on four steps of the Knowledge-to-Action framework was used in this thesis. First, a systematic review of CPGs was performed to identify recommendations to be implemented for improving shoulder pain management in primary care. Then, the evidence-practice gaps were assessed using a survey documenting family physicians and physiotherapists shoulder pain management as well as in a study evaluating the concordance between physiotherapists and orthopedists for shoulder pain diagnosis and management. The determinants influencing CPGs recommendations’ implementation were identified by conducting two qualitative studies. The first study explored the experiences and expectations of patients living with shoulder pain and the second aimed to interview clinicians for identifying barriers and facilitators to the implementation of CPGs recommendations. Finally, based on the identified determinants and using the Behaviour Change Wheel method, we identified strategies for implementing CPGs recommendations covering the management of shoulder pain in primary care. Based on the systematic review of shoulder CPGs, we identified that shoulder pain generally does not initially require diagnostic imaging and referral to a medical musculoskeletal specialist, but that an active rehabilitation program is required. According to the survey results, family physicians (n=76) recommended more imaging than physiotherapists (n=175) for rotator cuff tendinopathy and adhesive capsulitis, although this is not indicated. Up to two out of three physiotherapists selected treatments not recommended by CPGs in the management of shoulder pain. The results of the concordance study showed that the agreement between physiotherapists and orthopedists was good in terms of diagnosis and moderate in terms of triage of surgical candidates. Patients (n=13) interviewed in the first qualitative study reported waiting until their shoulder pain was disabling before seeing a family physician or a physiotherapist. Participants expected a clear diagnosis and imaging tests to explain their shoulder pain. They also wished to receive clear and thorough explanations and relevant treatment options. The 19 physiotherapists and 16 family physicians that participated in focus groups indicated as barriers to the use of CPGs recommendations: lack of knowledge, poor skills in performing a clinical evaluation and fear of not identifying a serious pathology without medical imaging. Patients’ expectations, insufficient consultation time with patients and lack of patients’ access to certain care, such as rehabilitation treatments were also identified as barriers. The main strategies identified following these studies therefore include educational interventions, the preparation of clinical champions and the creation of interdisciplinary clinical teams. Using these strategies, pilot implementation of the intervention will be carried out in family medicine groups. The potentially beneficial impact of this implantation could ultimately improve the management of patients with shoulder pain in primary care

Acetylation reprograms MITF target selectivity and residence time

The ability of transcription factors to discriminate between different classes of binding sites associated with specific biological functions underpins effective gene regulation in development and homeostasis. How this is achieved is poorly understood. The microphthalmia-associated transcription factor MITF is a lineage-survival oncogene that plays a crucial role in melanocyte development and melanoma. MITF suppresses invasion, reprograms metabolism and promotes both proliferation and differentiation. How MITF distinguishes between differentiation and proliferation-associated targets is unknown. Here we show that compared to many transcription factors MITF exhibits a very long residence time which is reduced by p300/CBP-mediated MITF acetylation at K206. While K206 acetylation also decreases genome-wide MITF DNA-binding affinity, it preferentially directs DNA binding away from differentiation-associated CATGTG motifs toward CACGTG elements. The results reveal an acetylation-mediated switch that suppresses differentiation and provides a mechanistic explanation of why a human K206Q MITF mutation is associated with Waardenburg syndrome

Acetylation reprograms MITF target selectivity and residence time

Abstract The ability of transcription factors to discriminate between different classes of binding sites associated with specific biological functions underpins effective gene regulation in development and homeostasis. How this is achieved is poorly understood. The microphthalmia-associated transcription factor MITF is a lineage-survival oncogene that plays a crucial role in melanocyte development and melanoma. MITF suppresses invasion, reprograms metabolism and promotes both proliferation and differentiation. How MITF distinguishes between differentiation and proliferation-associated targets is unknown. Here we show that compared to many transcription factors MITF exhibits a very long residence time which is reduced by p300/CBP-mediated MITF acetylation at K206. While K206 acetylation also decreases genome-wide MITF DNA-binding affinity, it preferentially directs DNA binding away from differentiation-associated CATGTG motifs toward CACGTG elements. The results reveal an acetylation-mediated switch that suppresses differentiation and provides a mechanistic explanation of why a human K206Q MITF mutation is associated with Waardenburg syndrome

Mobip: a lightweight model for driving perception using MobileNet

The visual perception model is critical to autonomous driving systems. It provides the information necessary for self-driving cars to make decisions in traffic scenes. We propose a lightweight multi-task network (Mobip) to simultaneously perform traffic object detection, drivable area segmentation, and lane line detection. The network consists of a shared encoder for feature extraction and two decoders for handling detection and segmentation tasks collectively. By using MobileNetV2 as the backbone and an extremely efficient multi-task architecture to implement the perception model, our network has great advantages in inference speed. The performance of the multi-task network is verified on a challenging public Berkeley Deep Drive(BDD100K) dataset. The model achieves an inference speed of 58 FPS on NVIDIA Tesla V100 while still maintaining competitive performance on all three tasks compared to other multi-task networks. Besides, the effectiveness and efficiency of the multi-task architecture are verified via ablative studies

3D Convolutional Networks for Action Recognition: Application to Sport Gesture Recognition

3D convolutional networks is a good means to perform tasks such as video segmentation into coherent spatio-temporal chunks and classification of them with regard to a target taxonomy. In the chapter we are interested in the classification of continuous video takes with repeatable actions, such as strokes of table tennis. Filmed in a free marker less ecological environment, these videos represent a challenge from both segmentation and classification point of view. The 3D convnets are an efficient tool for solving these problems with window-based approaches.Comment: Multi-faceted Deep Learning, 202

Optimized traffic scheduling and routing in smart home networks

Home networks are evolving rapidly to include heterogeneous physical access and a large number of smart devices that generate different types of traffic with different distributions and different Quality of Service (QoS) requirements. Due to their particular architectures, which are very dense and very dynamic, the traditional one-pair-node shortest path solution is no longer efficient to handle inter-smart home networks (inter-SHNs) routing constraints such as delay, packet loss, and bandwidth in all-pair node heterogenous links. In addition, Current QoS-aware scheduling methods consider only the conventional priority metrics based on the IP Type of Service (ToS) field to make decisions for bandwidth allocation. Such priority based scheduling methods are not optimal to provide both QoS and Quality of Experience (QoE), especially for smart home applications, since higher priority traffic does not necessarily require higher stringent delay than lower-priority traffic. Moreover, current QoS-aware scheduling methods in the intra-smart home network (intra-SHN) do not consider concurrent traffic caused by the fluctuation of intra-SH network traffic distributions. Thus, the goal of this dissertation is to build an efficient heterogenous multi-constrained routing mechanism and an optimized traffic scheduling tool in order to maintain a cost-effective communication between all wired-wireless connected devices in inter-SHNs and to effectively process concurrent and non-concurrent traffic in intra-SHN. This will help Internet service providers (ISPs) and home user to enhance the overall QoS and QoE of their applications while maintaining a relevant communication in both inter-SHNs and intra-SHN. In order to meet this goal, three key issues are required to be addressed in our framework and are summarized as follows: i) how to build a cost-effective routing mechanism in heterogonous inter-SHNs ? ii) how to efficiently schedule the multi-sourced intra-SHN traffic based on both QoS and QoE ? and iii) how to design an optimized queuing model for intra-SHN concurrent traffics while considering their QoS requirements? As part of our contributions to solve the first problem highlighted above, we present an analytical framework for dynamically optimizing data flows in inter-SHNs using Software-defined networking (SDN). We formulate a QoS-based routing optimization problem as a constrained shortest path problem and then propose an optimized solution (QASDN) to determine minimal cost between all pairs of nodes in the network taking into account the different types of physical accesses and the network utilization patterns. To address the second issue and to solve the gaps between QoS and QoE, we propose a new queuing model for QoS-level Pair traffic with mixed arrival distributions in Smart Home network (QP-SH) to make a dynamic QoS-aware scheduling decision meeting delay requirements of all traffic while preserving their degrees of criticality. A new metric combining the ToS field and the maximum number of packets that can be processed by the system's service during the maximum required delay, is defined. Finally, as part of our contribution to address the third issue, we present an analytic model for a QoS-aware scheduling optimization of concurrent intra-SHN traffics with mixed arrival distributions and using probabilistic queuing disciplines. We formulate a hybrid QoS-aware scheduling problem for concurrent traffics in intra-SHN, propose an innovative queuing model (QC-SH) based on the auction economic model of game theory to provide a fair multiple access over different communication channels/ports, and design an applicable model to implement auction game on both sides; traffic sources and the home gateway, without changing the structure of the IEEE 802.11 standard. The results of our work offer SHNs more effective data transfer between all heterogenous connected devices with optimal resource utilization, a dynamic QoS/QoE-aware traffic processing in SHN as well as an innovative model for optimizing concurrent SHN traffic scheduling with enhanced fairness strategy. Numerical results show an improvement up to 90% for network resource utilization, 77% for bandwidth, 40% for scheduling with QoS and QoE and 57% for concurrent traffic scheduling delay using our proposed solutions compared with Traditional methods