Hydrogels greffés stimulables comme actionneurs microfluidiques

We develop a new method to build microactuators using stimuli-responsive hydrogels. The hydrogel is synthesized with covalent attachment to the microchannel bottom walls prior to closing the microsystem, contrarily to previous approaches. We use a new stimuli-responsive hydrogel films synthesis pathway. This synthesis is based on thiol-ene click chemistry. The formation of films is achieved by adding bifunctional thiol molecules as cross-linkers to ene-functionalized preformed polymers on thiol-modified surfaces. The cross-linking and grafting are simultaneously performed either by thermal activation or UV-irradiation. Hydrogel films and micro-patterns are easily obtained in a wide range of thickness from hundred nanometers to several microns. We show that these responsive hydrogels patterns can be integrated into microfluidics channels to build microactuators. We focus on thermo-sensitive actuators made from poly(N-isopropylacrylamide). Under temperature, hydrogel patterns reversibly swell and collapse by absorbing/expulsing water. The phase transition is rapid (lower than 1 second), abrupt (a few degrees around the LCST at 32°C) and the deformation amplitude is high (400% swelling). Microvalves obtained by this approach exhibit high performances and durability. Moreover, we develop new reconfigurable actuators functioning as microfluidic traps. These new-concept microfluidic actuators offer wide possibilities because of their ease of fabrication, their performances and their ability to be integrated into high density.Nous développons une nouvelle approche des actuateurs microfluidiques à base d’hydrogels stimulables. Contrairement aux approches précédentes, les hydrogels sont synthétisés et greffés à la paroi inférieure du microcanal avant la fermeture du système. Nous utilisons une nouvelle stratégie de synthèse pour les films d’hydrogels stimulables par chimie click thiol-ène. Les films sont obtenus par dépôt, sur des surfaces fonctionnalisées avec des thiols, d’un mélange de chaînes polymères préformées et d’un réticulant dithiol. Le greffage et la réticulation s’obtiennent simultanément par une activation thermique ou par irradiation UV. Des films et des micro-motifs sont obtenus sur une large gamme d’épaisseur allant de la centaine de nanomètres à plusieurs microns. Nous intégrons les motifs d’hydrogels stimulables dans les microcanaux pour réaliser des actionneurs. Nous étudions des actionneurs thermosensibles réalisés avec des hydrogels de poly(N-isopropylacrylamide). Avec la température, les motifs d’hydrogels gonflent ou dégonflent en absorbant/expulsant l’eau de manière réversible. L’effet est rapide (inférieur à la seconde), la transition abrupte (quelques degrés autour de la LCST à 32°C) et l’amplitude de déformation est importante (gonflement de 400%). Les micro-vannes réalisées avec cette nouvelle approche présentent de très bonnes performances et une grande durabilité. Nous avons aussi réalisé de nouveaux actionneurs reconfigurables fonctionnant comme des pièges microfluidiques. Ces actionneurs microfluidiques innovants offrent de nombreuses perspectives de par la facilité de leur mise en œuvre, leurs performances et l’intégration sur des micro-puces à haute densité

Near-wall nanovelocimetry based on Total Internal Reflection Fluorescence with continuous tracking

The goal of this work is to make progress in the domain of near-wall velocimetry. The technique we use is based on the tracking of nanoparticles in an evanescent field, close to a wall, a technique called TIRF (Total Internal Reflection Fluorescence)-based velocimetry. At variance with the methods developed in the literature, we permanently keep track of the light emitted by each particle during the time the measurements of their positions ('altitudes') and speeds are performed. By performing the Langevin simulation, we quantified effect of biases such as Brownian motion, heterogeneities induced by the walls, statistical biases, photo bleaching, polydispersivity and limited depth of field. Using this method, we obtained slip length on hydrophilic surfaces of 1$\pm$5 nm for sucrose solution, and 9$\pm$10 nm for water; On hydrophobic surface, 32$\pm$5 nm for sucrose solution, and 55$\pm$9 nm for water. The errors (based on 95% confidence intervals) are significantly smaller than the state-of-the-art, but more importantly, the method demonstrates for the first time a capacity to measure slippage with a satisfactory accuracy, while providing a local information on the flow structure with a nanometric resolution. Our study confirms the discrepancy already pointed out in the literature between numerical and experimental slip length estimates. With the progress conveyed by the present work, TIRF based technique with continuous tracking can be considered as a quantitative method for investigating flow properties close to walls, providing both global and local information on the flow.Comment: 24 pages, 13 figure

Lignin Nanoparticles as A Promising Way for Enhancing Lignin Flame Retardant Effect in Polylactide

International audienceThe present study investigates the effect of using lignin at nanoscale as new flame-retardant additive for polylactide (PLA). Lignin nanoparticles (LNP) were prepared from Kraft lignin microparticles (LMP) through a dissolution-precipitation process. Both micro and nano lignins were functionalized using diethyl chlorophosphate (LMP-diEtP and LNP-diEtP, respectively) and diethyl (2-(triethoxysilyl)ethyl) phosphonate (LMP-SiP and LNP-SiP, respectively) to enhance their flame-retardant effect in PLA. From the use of inductively coupled plasma (ICP) spectrometry, it can be considered that a large amount of phosphorus has been grafted onto the nanoparticles. It has been previously shown that blending lignin with PLA induces degradation of the polymer matrix. However, phosphorylated lignin nanoparticles seem to limit PLA degradation during melt processing and the nanocomposites were shown to be relatively thermally stable. Cone calorimeter tests revealed that the incorporation of untreated lignin, whatever its particle size, induced an increase in pHRR. Using phosphorylated lignin nanoparticles, especially those treated with diethyl (2-(triethoxysilyl)ethyl) phosphonate allows this negative effect to be overcome. Moreover, the pHRR is significantly reduced, even when only 5 wt% LNP-SiP is used

Automated detection of atrial fibrillation using long short-term memory network with RR interval signals

Atrial Fibrillation (AF), either permanent or intermittent (paroxysnal AF), increases the risk of cardioembolic stroke. Accurate diagnosis of AF is obligatory for initiation of effective treatment to prevent stroke. Long term cardiac monitoring improves the likelihood of diagnosing paroxysmal AF. We used a deep learning system to detect AF beats in Heart Rate (HR) signals. The data was partitioned with a sliding window of 100 beats. The resulting signal blocks were directly fed into a deep Recurrent Neural Network (RNN) with Long Short-Term Memory (LSTM). The system was validated and tested with data from the MIT-BIH Atrial Fibrillation Database. It achieved 98.51% accuracy with 10-fold cross-validation (20 subjects) and 99.77% with blindfold validation (3 subjects). The proposed system structure is straight forward, because there is no need for information reduction through feature extraction. All the complexity resides in the deep learning system, which gets the entire information from a signal block. This setup leads to the robust performance for unknown data, as measured with the blind fold validation. The proposed Computer-Aided Diagnosis (CAD) system can be used for long-term monitoring of the human heart. To the best of our knowledge, the proposed system is the first to incorporate deep learning for AF beat detection

IRIM at TRECVID 2012: Semantic Indexing and Instance Search

International audienceThe IRIM group is a consortium of French teams work- ing on Multimedia Indexing and Retrieval. This paper describes its participation to the TRECVID 2012 se- mantic indexing and instance search tasks. For the semantic indexing task, our approach uses a six-stages processing pipelines for computing scores for the likeli- hood of a video shot to contain a target concept. These scores are then used for producing a ranked list of im- ages or shots that are the most likely to contain the tar- get concept. The pipeline is composed of the following steps: descriptor extraction, descriptor optimization, classi cation, fusion of descriptor variants, higher-level fusion, and re-ranking. We evaluated a number of dif- ferent descriptors and tried di erent fusion strategies. The best IRIM run has a Mean Inferred Average Pre- cision of 0.2378, which ranked us 4th out of 16 partici- pants. For the instance search task, our approach uses two steps. First individual methods of participants are used to compute similrity between an example image of in- stance and keyframes of a video clip. Then a two-step fusion method is used to combine these individual re- sults and obtain a score for the likelihood of an instance to appear in a video clip. These scores are used to ob- tain a ranked list of clips the most likely to contain the queried instance. The best IRIM run has a MAP of 0.1192, which ranked us 29th on 79 fully automatic runs

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Fire behavior study of polymer materials containing functionalized bio-based nanoparticles

La volonté croissante de diminuer l’empreinte écologique des matières plastiques favorise le développement de polymères et d’additifs issus de ressources renouvelables afin de limiter leur impact environnemental. Les retardateurs de flamme sont une famille d’additifs qui jouent un rôle crucial dans de nombreux domaines d’application où le risque d’incendie est avéré. Cette étude vise donc à développer de nouveaux systèmes retardateurs de flamme à partir de composés issus de la biomasse afin d’améliorer le comportement au feu d’un polymère bio-sourcé, l’acide polylactique (PLA). La lignine et la cellulose ont été choisies comme composés de base. Des procédés adaptés ont permis de transformer ces composés à l’état nanoparticulaire, puis ils ont été fonctionnalisés avec des produits phosphorés ou alors mélangés avec du polyphosphate d’ammonium, et incorporés dans l’acide polylactique au mélangeur interne. La stabilité thermique, l’inflammabilité et le comportement au feu des composites ainsi obtenus ont été étudiés. Les résultats obtenus avec certains systèmes sont prometteurs.The growing desire to reduce the ecological footprint of plastic materials promotes the development of polymers and additives from renewable resources in order to limit their environmental impact. Flame retardants represent an important family of additives that play a crucial role in many fields where fire hazard is encountered. Thus this study aims at developing new flame retardant systems from biomass compounds to improve the fire behavior of polylactide (PLA), a bio-based polymer. Lignin and cellulose were chosen as pristine compounds. These compounds have been transformed into nanoparticles with adapted processes. Then, they were functionalized with phosphorous moieties or mixed with ammonium polyphosphate, and incorporated into polylactide with in internal mixer. Thermal, flammability and fire properties of these compounds were evaluated. The results obtained with some systems are promising