311 research outputs found
The modular serine proteases of the complement cascade
No full textModular serine proteases are central to the complement cascade of the mammalian humoral immune system. These proteases form protein complexes through multi-domain interactions to achieve their proteolytic activity. We review the structural insights into complement initiation by auto-activation of the hetero-tetrameric proteases of the large danger-recognition protein complexes, amplification and labelling of particles by the formation and activity of C3 convertases, and regulation by convertase dissociation and degradation to prevent ‘bystander’ damage to healthy host cells and tissues. The data reveal that complex formation and large domain–domain rearrangements underlie the proteolytic reactions of the complement cascade, which enables the host to recognize and clear invading microbes and host debris from its blood and fluids surrounding tissues. -------------------------------------------------------------------------------
YoloP-Based Pre-processing for Driving Scenario Detection
No full textRecognition of driving scenarios is getting ever more relevant in research, especially for assessing performance of advanced driving assistance systems (ADAS) and automated driving functions. However, the complexity of traffic situations makes this task challenging. In order to improve the detection rate achieved through state-of-the-art deep learning models, we have investigated the use of the YoloP fully convolutional neural network architecture as a pre-processing step to extract high-level features for a residual 3D convolutional neural network We observed thar this approach reduces computational complexity, resulting in optimized model performance, also in terms of generalization from training on a synthetic dataset to testing in a real-world one
Complement convertase formation based on the structures of C3b in complex with factors B and D
No full textElectroencéphalographie et interfaces cerveau-machine : nouvelles méthodes pour étudier les états mentaux
No full textAvec les avancées technologiques dans le domaine de l'imagerie cérébrale fonctionnelle et les progrès théoriques dans la connaissance des différents éléments neurophysiologiques liés à la cognition, les deux dernières décennies ont vu l'apparition d'interfaces cerveau-machine (ICM) permettant à une personne d'observer en temps réel, ou avec un décalage qui se limite à quelques secondes, sa propre activité cérébrale. Le domaine clinique en général, et plus particulièrement celui de la neuropsychologie et des pathologies conduisant à un handicap moteur lourd, pour lesquels les applications potentielles sont nombreuses qu'elles soient thérapeutiques ou en vue d'une réhabilitation fonctionnelle, a constitué un moteur important de la recherche sur ce nouveau domaine des neurosciences temps réel. Parmi ces applications, le neurofeedback, ou neurothérapie, qui vise l'acquisition par le sujet du contrôle volontaire de certains aspects de son activité cérébrale en vue de les amplifier ou au contraire les diminuer dans un but thérapeutique, voire d'optimisation cognitive, représente une technique prometteuse, alternative aux thérapies et traitements médicamenteux. Cependant, la validation de ce type d'intervention et la compréhension des mécanismes mis en jeux en sont encore à leurs balbutiements. L'entraînement par neurofeedback est souvent long, pouvant s'étaler sur plusieurs semaines. Il est donc très probable que ce type de rééducation cérébrale sollicite des phénomènes de plasticité qui s'inscrivent dans une dynamique lente, et de ce fait, requiert une durée relativement longue d'entraînement pour atteindre les effets à long terme recherchés. Cependant, à cela peuvent s'ajouter de nombreux éléments perturbateurs qui pourraient être à l'origine de la difficulté de l'apprentissage et des longs entraînements nécessaires pour obtenir les résultats attendus. Parmi eux, les perturbations qui viennent déformer le signal enregistré, ou les éléments artefactuels qui ne font pas partie du signal d'intérêt, sont une première cause potentielle. Le manque de spécificité fonctionnelle du signal retourné au sujet pourrait en constituer une deuxième. Nous avons d'une part développé des outils méthodologiques de traitement du signal en vue d'améliorer la robustesse des analyses des signaux EEG, principalement utilisés jusqu'à maintenant dans le domaine du neurofeedback et des ICM, face aux artefacts et au bruit électromagnétique. D'autre part, si l'on s'intéresse au problème de la spécificité fonctionnelle du signal présenté au sujet, des études utilisant l'IRM fonctionnelle ou des techniques de reconstruction de sources à partir du signal EEG, qui fournissent des signaux ayant une meilleure spécificité spatiale, laissent entrevoir de possibles améliorations de la vitesse d'apprentissage. Afin d'augmenter la spécificité spatiale et la contingence fonctionnelle du feedback présenté au sujet, nous avons étudié la stabilité de la décomposition de l'EEG en différentes sources d'activité électrique cérébrale par Analyse en Composantes Indépendantes à travers différentes séances d'enregistrement effectuées sur un même sujet. Nous montrons que ces décompositions sont stables et pourraient permettre d'augmenter la spécificité fonctionnelle de l'entraînement au contrôle de l'activité cérébrale pour l'utilisation d'une ICM. Nous avons également travaillé à l'implémentation d'un outil logiciel permettant l'optimisation des protocoles expérimentaux basés sur le neurofeedback afin d'utiliser ces composantes indépendantes pour rejeter les artefacts en temps réel ou extraire l'activité cérébrale à entraîner. Ces outils sont utiles dans le cadre de l'analyse et de la caractérisation des signaux EEG enregistrés, ainsi que dans l'exploitation de leurs résultats dans le cadre d'un entraînement de neurofeedback. La deuxième partie de ce travail s'intéresse à la mise en place de protocoles de neurofeedback et à l'impact de l'apprentissage. Nous décrivons tout d'abord des résultats obtenus sur une étude pilote qui cherche à évaluer chez des sujets sains l'impact d'un protocole de neurofeedback basé sur le contrôle du rythme Mu. Les changements comportementaux ont été étudiés à l'aide d'un paradigme de signal stop qui permet d'indexer les capacités attentionnelles et d'inhibition de réponse motrice sur lesquelles on s'attend à ce que l'entraînement ICM ait une influence. Pour clore cette partie, nous présentons un nouvel outil interactif immersif pour l'entraînement cérébral, l'enseignement, l'art et le divertissement pouvant servir à évaluer l'impact de l'immersion sur l'apprentissage au cours d'un protocole de neurofeedback. Enfin, les perspectives de l'apport des méthodes et résultats présentés sont discutées dans le contexte du développement des ICMs de nouvelle génération qui prennent en compte la complexité de l'activité cérébrale. Nous présentons les dernières avancées dans l'étude de certains aspects des corrélats neuronaux liés à deux états mentaux ou classes d'états mentaux que l'on pourrait qualifier d'antagonistes par rapport au contrôle de l'attention : la méditation et la dérive attentionnelle, en vue de leur intégration à plus long terme dans un entraînement ICM par neurofeedback.With new technological advances in functional brain imaging and theoretical progress in the knowledge of the different neurophysiologic processes linked to cognition, the last two decades have seen the emergence of Brain-Machine Interfaces (BCIs) allowing a person to observe in real-time, or with a few seconds delay, his own cerebral activity. Clinical domain in general, and more particularly neuropsychology and pathologies leading to heavy motor handicaps, for which potential applications are numerous, whether therapeutic or for functional rehabilitation, has been a major driver of research on this new field of real-time neurosciences. Among these applications, neurofeedback, or neurotherapy, which aims the subject to voluntary control some aspects of his own cerebral activity in order to amplify or reduce them in a therapeutic goal, or for cognitive optimization, represents a promising technique, and an alternative to drug treatments. However, validation of this type of intervention and understanding of involved mechanisms are still in their infancy. Neurofeedback training is often long, up to several weeks. It is therefore very likely that this type of rehabilitation is seeking brain plasticity phenomena that are part of slow dynamics, and thus require a relatively long drive to achieve the desired long-term effects. However, other disturbing elements that could add up to the cause of the difficulty of learning and long training sessions required to achieve the expected results. Among them, the disturbances that come from recorded signal distortions, or artifactual elements that are not part of the signal of interest, are a first potential cause. The lack of functional specificity of the signal returned to the subject could be a second one. We have developed signal processing methodological tools to improve the robustness to artifacts and electromagnetic noise of EEG signals analysis, the main brain imaging technique used so far in the field of neurofeedback and BCIs. On the other hand, if one looks at the issue of functional specificity of the signal presented to the subject, studies using functional MRI or source reconstruction methods from the EEG signal, which both provide signals having a better spatial specificity, suggest improvements to the speed of learning. Seeing Independent Component Analysis as a potential tool to increase the spatial specificity and functional contingency of the feedback signal presented to the subject, we studied the stability of Independent Component Analysis decomposition of the EEG across different recording sessions conducted on the same subjects. We show that these decompositions are stable and could help to increase the functional specificity of BCI training. We also worked on the implementation of a software tool that allows the optimization of experimental protocols based on neurofeedback to use these independent components to reject artifacts or to extract brain activity in real-time. These tools are useful in the analysis and characterization of EEG signals recorded, and in the exploitation of their results as part of a neurofeedback training. The second part focuses on the development of neurofeedback protocols and the impact of learning. We first describe the results of a pilot study which seeks to evaluate the impact of a neurofeedback protocol based on the Mu rhythm control on healthy subjects. The behavioral changes were studied using a stop signal paradigm that indexes the attentional abilities and inhibition of motor responses on which the BCI training can possibly have influence. To conclude this section, we present a new tool for immersive interactive brain training, education, art and entertainment that can be used to assess the impact of immersion on learning during a neurofeedback protocol. Finally, prospects for methods and results presented are discussed in the context of next-generation BCI development which could take brain activity complexity into account. We present the latest advances in the study of certain aspects of the neural correlates associated with two mental states or classes of mental states that could be described as antagonistic with respect to the control of attention: meditation and mind wandering, for their integration in the longer term in an BCI training using neurofeedback
Fabrication of quantum emitters in aluminum nitride by Al-ion implantation and thermal annealing
No full textSingle-photon emitters (SPEs) within wide-bandgap materials represent an appealing platform for the development of single-photon sources operating at room temperatures. Group III-nitrides have previously been shown to host efficient SPEs, which are attributed to deep energy levels within the large bandgap of the material, in a configuration that is similar to extensively investigated color centers in diamond. Antibunched emission from defect centers within gallium nitride and aluminum nitride (AlN) have been recently demonstrated. While such emitters are particularly interesting due to the compatibility of III-nitrides with cleanroom processes, the nature of such defects and the optimal
conditions for forming them are not fully understood. Here, we investigate Al implantation on a commercial AlN epilayer through subsequent steps of thermal annealing and confocal microscopy measurements. We observe a fluence-dependent increase in the density of the emitters, resulting in the creation of ensembles at the maximum implantation fluence. Annealing at 600 C results in the optimal yield in SPEs formation at the maximum fluence, while a significant reduction in SPE density is observed at lower fluences. These findings suggest that the mechanism of vacancy formation plays a key role in the creation of the emitters and open enticing perspectives in the defect engineering of SPEs in solid state
Direct experimental observation of nonclassicality in ensembles of single-photon emitters
No full textIn this work we experimentally demonstrate a recently proposed criterion addressed to detect nonclassical behavior in the fluorescence emission of ensembles of single-photon emitters. In particular, we apply the method to study clusters of nitrogen-vacancy centers in diamond characterized with single-photon-sensitive confocal microscopy. Theoretical considerations on the behavior of the parameter at any arbitrary order in the presence of Poissonian noise are presented and, finally, the opportunity of detecting manifold coincidences is discussed
Electrical control of deep NV centers in diamond by means of sub-superficial graphitic micro-electrodes
No full textThe control of the charge state of nitrogen-vacancy (NV) centers in
diamond is of primary importance for the stabilization of their
quantum-optical properties, in applications ranging from quantum sensing
to quantum computing. In this work buried current-injecting graphitic
micro-electrodes were fabricated in bulk diamond by means of a 6 MeV C3+
scanning micro-beam. The electrodes were exploited to control the
variation in the relative population of the negative (NV-) and neutral
(NV0) charge states of a sub superficial NV0 centers ensemble located in
the inter-electrode gap region. Photoluminescence spectra exhibited an
electrically-induced increase up to 40% in the NV- population at the
expense of the NV0 charge state, with a linear dependence from the
injected current at applied biases smaller than 350 V, and was
interpreted as the result of electron trapping at NV0 sites. An abrupt
current increase at similar to 350 V bias resulted in a strong
electroluminescence from the NV0 centers, in addition to two spectrally
sharp emission lines at 563.5 nm and 580 nm, not visible under optical
excitation and attributed to self interstitial defects. These results
disclose new possibilities in the electrical control of the charge state
of NV centers located in the diamond bulk, which are characterized by
longer spin coherence times. (C) 2016 Elsevier Ltd. All rights reserved
Realization of a diamond based high density multi electrode array by means of Deep Ion Beam Lithography
No full textA biocompatible technique for magnetic field sensing at (sub)cellular scale using Nitrogen-Vacancy centers
No full textWe present an innovative experimental set-up that uses Nitrogen-Vacancy centres in diamonds to measure magnetic fields with the sensitivity of eta = 68 +/- 3 nT/root Hz at demonstrated (sub)cellular scale. The presented method of magnetic sensing, utilizing a lock-in based ODMR technique for the optical detection of microwave-driven spin resonances induced in NV centers, is characterized by the excellent magnetic sensitivity at such small scale and the full biocompatibility. The cellular scale is obtained using a NV-rich sensing layer of 15 nm thickness along z axis and a focused laser spot of (10x10) mu m(2) in x-y plane. The biocompatibility derives from an accurate choice of the applied optical power. For this regard, we also report how the magnetic sensitivity changes for different applied laser power and discuss the limits of the sensitivity sustainable with biosystem at such small volume scale. As such, this method offers a whole range of research possibilities for biosciences
- …
