Optical detection of spin transport in non-magnetic metals

We determine the dynamic magnetization induced in non-magnetic metal wedges composed of silver, copper and platinum by means of Brillouin light scattering (BLS) microscopy. The magnetization is transferred from a ferromagnetic Ni80Fe20 layer to the metal wedge via the spin pumping effect. The spin pumping efficiency can be controlled by adding an insulating but transparent interlayer between the magnetic and non-magnetic layer. By comparing the experimental results to a dynamical macroscopic spin-transport model we determine the transverse relaxation time of the pumped spin current which is much smaller than the longitudinal relaxation time

Extractive Text-Based Summarization of Arabic videos: Issues, Approaches and Evaluations

International audienceIn this paper, we present and evaluate a method for extractive text-based summarization of Arabic videos. The algorithm is proposed in the scope of the AMIS project that aims at helping a user to understand videos given in a foreign language (Arabic). For that, the project proposes several strategies to translate and summarize the videos. One of them consists in transcribing the Ara-bic videos, summarizing the transcriptions, and translating the summary. In this paper we describe the video corpus that was collected from YouTube and present and evaluate the transcription-summarization part of this strategy. Moreover, we present the Automatic Speech Recognition (ASR) system used to transcribe the videos, and show how we adapted this system to the Algerian dialect. Then, we describe how we automatically segment into sentences the sequence of words provided by the ASR system, and how we summarize the obtained sequence of sentences. We evaluate objectively and subjectively our approach. Results show that the ASR system performs well in terms of Word Error Rate on MSA, but needs to be adapted for dealing with Algerian dialect data. The subjective evaluation shows the same behaviour than ASR: transcriptions for videos containing dialectal data were better scored than videos containing only MSA data. However, summaries based on transcriptions are not as well rated, even when transcriptions are better rated. Last, the study shows that features, such as the lengths of transcriptions and summaries, and the subjective score of transcriptions, explain only 31% of the subjective score of summaries

Acoustic-phonetic decoding of speech : problems and solutions

Acoustic phonetic decoding of speech recognition constitutes a major step in the process of continuous speech recognition . This paper reminds the difficulties of the problem together with the main methods proposed so far in order to solve it . We then concentrate on the différent complementary approaches Chat have been investigated by our group : expert system based on spectrogram reading, recognition by phonetic triphones, connectionist model based on the cortical column unit and stochastic recognition without segmentation .Le décodage acoustico-phonétique constitue une étape importante en reconnaissance de la parole continue . Cet article rappelle d'abord les difficultés du problème et les principales méthodes qui ont été proposées pour le résoudre . Il présente ensuite les diverses approches complémentaires adoptées par notre équipe : système expert fondé sur l'activité de lecture de spectrogrammes, reconnaissance par triplets phonétiques, modèle connexionniste de colonne corticale et reconnaissance par méthode stochastique sans segmentation

International organisations and anti-terrorist sanctions: no accountability for human rights violations?

The targeted sanctions adopted by the UN Security Council against individuals and entities suspected of association with terrorism are managed through procedures that infringe fundamental human rights, and there are no mechanisms for actual accountability. With the exception of the ECJ in Kadi, municipal and regional courts tend to consider the UN Security Council's resolutions and domestic measures implementing them outside the scope of judicial review. This article argues that the Security Council is bound to observe human rights even in the context of international security action, and that States are not exonerated from international responsibility for violations committed under the umbrella of Chapter VII resolutions

Protein-Binding Microarray Analysis of Tumor Suppressor AP2α Target Gene Specificity

Cheap and massively parallel methods to assess the DNA-binding specificity of transcription factors are actively sought, given their prominent regulatory role in cellular processes and diseases. Here we evaluated the use of protein-binding microarrays (PBM) to probe the association of the tumor suppressor AP2α with 6000 human genomic DNA regulatory sequences. We show that the PBM provides accurate relative binding affinities when compared to quantitative surface plasmon resonance assays. A PBM-based study of human healthy and breast tumor tissue extracts allowed the identification of previously unknown AP2α target genes and it revealed genes whose direct or indirect interactions with AP2α are affected in the diseased tissues. AP2α binding and regulation was confirmed experimentally in human carcinoma cells for novel target genes involved in tumor progression and resistance to chemotherapeutics, providing a molecular interpretation of AP2α role in cancer chemoresistance. Overall, we conclude that this approach provides quantitative and accurate assays of the specificity and activity of tumor suppressor and oncogenic proteins in clinical samples, interfacing genomic and proteomic assays

Chapter 1 State of the art in Acoustic Speech Recognition

1.1 Statistical speech recognition The goal of an automatic speech recognition system is to deduce meaningful linguistic units (i.e., words) from acoustic waveforms. Due to the random nature of the process and interferences, it is not possible to derive a deterministic formulation that provides a mapping between acoustic signal and conceptual meanings. Instead the problem is generally formulated in a probabilistic framework. In probabilistic setting the speech recognition is stated as the estimation of ‘most probable ’ linguistic representation of a ‘given ’ acoustic waveform. The mathematical formulation of this problem is: �Ï � �Ö � Ñ�Ü Ï È Ï�Ç where Ç is a set of observations from the acoustic waveform and Ï is a random variable that takes its values from the possible linguistic representations in the language under consideration. È Ï�Ç is the conditional probability distribution of the linguistic representation given the observations. This conditional distribution constitutes the knowledge base of the recognizer. This knowledge base is constructed using statistical learning techniques and a priori expertise on speech production mechanisms. The role of a priori expertise on the domain is to provide a set of simplification assumptions that will guide th