Working memory dynamics and spontaneous activity in a flip-flop oscillations network model with a Milnor attractor

Many cognitive tasks require the ability to maintain and manipulate simultaneously several chunks of information. Numerous neurobiological observations have reported that this ability, known as the working memory, is associated with both a slow oscillation (leading to the up and down states) and the presence of the theta rhythm. Furthermore, during resting state, the spontaneous activity of the cortex exhibits exquisite spatiotemporal patterns sharing similar features with the ones observed during specific memory tasks. Here to enlighten neural implication of working memory under these complicated dynamics, we propose a phenomenological network model with biologically plausible neural dynamics and recurrent connections. Each unit embeds an internal oscillation at the theta rhythm which can be triggered during up-state of the membrane potential. As a result, the resting state of a single unit is no longer a classical fixed point attractor but rather the Milnor attractor, and multiple oscillations appear in the dynamics of a coupled system. In conclusion, the interplay between the up and down states and theta rhythm endows high potential in working memory operation associated with complexity in spontaneous activities

Optimization and performance evaluation of the analysis of glyphosate and AMPA in water by HPLC with fluorescence detection

International audienceThe object of this work was to optimize and validate an analytical method for the analysis of glyphosate and its main metabolite AMPA (aminomethylphosphonic acid) in natural and drinking water, for sanitary control. The method uses a derivatization step which transforms glyphosate and AMPA into fluorescent products by reaction with 9-fluorenylmethylchloroformate (FMOC-CI). The kinetics and yield of this reaction were studied by use of different samples. The derivatization products were injected directly into the liquid chromatograph and separated on an amino-functionalized silica gel column. The performance of the method (detection limit, quantification limit, linearity, and relative standard deviation) was studied and the results obtained showed the method was suitable for routine analysis of glyphosate and AMPA. An interlaboratory test with five laboratories confirmed that good results were obtained by use of this method

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Avionics systems are growing ever more complex to accommodate to the evolving needs of airlines. As such, their attack surface has greatly expanded, and the potential impact of a security incident touching these systems has become a critical concern for the aerospace industry. Countermeasures include defining security perimeters and monitoring network traffic, and in turn inspecting the logs generated by these systems to reveal security incidents and respond quickly accordingly. However, processing the large amount of system logs to extract valuable information is intractable through conventional means such as manual human investigation or regular expression matching. This thesis tackles the problem of automation of anomaly detection on security and functional system logs using advanced machine learning techniques. It investigates new methods to improve on the work done during a previous project at Collins Aerospace on Markov chains and LSTM neural networks. In particular, it evaluates the use of nonparametric Bayesian methods to perform this task, specifically the Hidden Dirichlet Process Hidden Markov Model. A complete log analysis system is proposed based on these models, and their performance is evaluated on real-life datasets using this framework.Allteftersom flygbolagens krav utvecklas, blir flygelektroniska system mer komplexa. Till följd av detta, har dessa systems utsatthet ökat och risken för säkerhetsincidenter har blivit en av flygindustrins största bekymmer. För att förebygga säkerhetsincidenter kan man, bland annat, bygga system för att skapa säkerhetsgränser och bevaka nätverkstrafik. Dessa förebyggande system generar loggar som man i sin tur analyserar för att upptäcka och lösa säkerhetsproblem. Det visar sig dock svårt att med konventionella metoder, som manuell undersökning eller mönstermatchning, behandla och finna värdefull information i de stora mängder loggar som genereras av dessa system. Genom att använda avancerade maskininlärningsalgoritmer, försöker detta examensarbete automatisera behandlingen av systemloggar. Detta examensarbete undersöker nya metoder för att förbättra ett projekt som tidigare utförts vid Collins Aerospace. Det tidigare projektet använde Markovkedjor och neurala nätverk av LSTM-typ, men i detta arbete undersöks istället icke-parametriska Bayesianska metoder för uppgiften, specifikt den modell som kallas Hidden Dirichlet Process Hidden Markov Model. Ett fullständigt logghanteringssystem baserat på denna modell föreslås och utvärderas i detta examensarbete

Differential pattern of HIF-1α expression in HNSCC cancer stem cells after carbon ion or photon irradiation: one molecular explanation of the oxygen effect

International audienceBackground: Head and neck squamous cell carcinoma (HNSCC) are resistant to standard treatments, partly due to cancer stem cells (CSCs) localised in hypoxic niches. Compared to X-rays, carbon ion irradiation relies on better ballistic properties, higher relative biological effectiveness and the absence of oxygen effect. Hypoxia-inducible factor-1a (HIF-1a) is involved in the resistance to photons, whereas its role in response to carbon ions remains unclear.Methods:Two HNSCC cell lines and their CSC sub-population were studied in response to photons or carbon ion irradiation, innormoxia or hypoxia, after inhibition or not of HIF-1a.Results:Under hypoxia, compared to non-CSCs, HIF-1ais expressed earlier in CSCs. A combined effect photons/hypoxia, lessobserved with carbon ions, results in a synergic and earlier HIF-1aexpression in both subpopulations. The diffuse ROS productionby photons is concomitant with HIF-1aexpression and essential to its activation. There is no oxygen effect in response to carbonions and the ROS localised in the track might be insufficient to stabilise HIF-1a. Finally, in hypoxia, cells were sensitised to bothtypes of radiations after HIF-1ainhibition.Conclusions:Hypoxia-inducible factor-1aplays a main role in the response of CSCs and non-CSCs to carbon ion and photonirradiations, which makes the HIF-1atargeting an attractive therapeutic challenge