dataesr/scientific-paragraphs-categorization huggingface dataset:
Analyse de données patients Les RNA pourraient être utilisés en anatomie pathologique pour leur qualité en classification et en pronostic (régression). Ces deux tâches sont réalisées à partir de l'analyse de bases de données biomédicales. Ainsi, en classification, les tumeurs de Spitz sont des tumeurs mélanocytaires rares pour lesquelles l'analyse histologique est difficile et les critères de diagnostic entre naevus de Spitz et tumeur de Spitz atypique encore discutés. L'utilisation d'immunomarqueurs peut aider à cette classification. Les RNA pourraient permettre d'étudier la pertinence de certains critères à partir de données cliniques, immunohistochimiques et analytiques histopathologiques  [18]. Dans un autre champ d'application, en pronostic, les carcinomes mammaires sont actuellement classés suivant des critères classiques histopathologiques que sont le grade, le stade TNM et des biomarqueurs évalués par immunohistochimie : RE, RP, ki67 et HER2.
RELATED WORK Over the last decade, facial animation received considerable attention from industries and research communities for reducing their production cost and their fidelity. At the early days of this filed, facial animations were made by hand and required the expertise of professional animators. The 3D models were first rigged, weighted and then animated frame by frame. This process is time-consuming and varies with the animators. More recently, the use of performance capture allowed to semi-automatize facial animations. Facial movements are recorded with specific software and hardware by tracking markers on human actors in real-time. The collected data is then transferred to the 3D character model. The results are highly dependent on the actor morphology and appearance and require intensive cleaning  [7, 8, 9].
Nowadays, the Deep Learning community has been able to solve similar issues in translation. Instead of discretizing the input and output space to find bindings, the system learns how to map those spaces together directly. Hence, results are consistent in the output space. In the animation field, recent contributions present significant improvements using such approaches known as audio-driven or speech-driven facial animation. Such frameworks allow to synthesize facial movements and can include an emotional dimension  [16, 17]. Unfortunately, the authors did not share their dataset, limiting reproducibility for future contributions. Recently, ObamaNet from Rithesh and al. introduced the first approach for text-driven mouth animations  [18]. Using text as input, their model can generate an audio waveform and its photorealistic lip-sync frames.
Their results are impressive and can lead to future approaches. However, this method is not suitable for other applications requiring the control of a 3D character model. Our contribution includes: • A methodology for the creation of text-driven mouth animation datasets from a video bank, including audio. First, the speaker's face is automatically detected and cropped from the video. Then, facial 3D landmarks are identified and projected into an invariant space. Finally, the mouth's key points are extracted and normalized, providing natural synchronicity with the audio. • A new Deep Learning pipeline for text-driven mouth animation following best practices from state of the art. The speech synthesis module has been replaced by more recent contributions. We also introduce a new module to focus on 3D landmarks controls instead of 2D rendered frames.
ADMA DATASET In this section, we describe the methodology used to generate our dataset ADMA-TED for Audio-Driven Mouth Animation (ADMA) TED based on the Lip Reading Sentence (LRS3-TED) dataset  [19]. This dataset is composed of 400 hours of TED and TEDx English talks videos distributed over 4004 videos for training and validation, and 451 for testing. Each video varies from 1 to 6 seconds and is cropped on the speaker's face with a 224 by 224 pixels resolution. This dataset has been chosen for its diversity and quality, such as the faces are almost always visible continuously. The rejection rate is lower than 1% and concerns recordings with microphone glitches or where the face is not visible enough. For each video, we provide 20 normalized 3D mouth landmarks every 40 ms to ensure continuous face tracking during the sentence pronunciation, as illustrated in Figure  2.
Mouth Landmarks Face Alignment Network (FAN), proposed in Bulat and al. [20] , is a popular model for face landmark inference on pictures. It has been applied on the entire LRS3-TED dataset at 25 FPS rate, providing 68 3D face landmarks for each frame as illustrated Figure  3. Only mouth landmarks are extracted, as illustrated in Figure  4. They are then projected into a head rotation invariant and normalized space. We defined the top of the nose and the chin as our y axis, both eye's landmarks as our x axis and their cross product as our z axis. These axes define the face referential. Using the transformation matrix T M in Eq. 1, the mouth's landmarks are projected into a new front-facing referential. These landmarks are normalized between [0; 1] with the center of the mouth located at 0.
5 in each axis. x 0 y 0 z 0 0 x 1 y 1 z 1 0 x 2 y 2 z 2 0 0 0 0 1 3 7 5 (1) Finally, as people possess different types of mouth, identity is removed by computing the median lips thickness over the entire dataset to reduce this bias. Depending on given thresholds, some videos are rejected for being out of the maximum and minimum range of the mouths' opening and closing.
Audio Processing Each video's audio channel from LRS3-TED is sampled at 16kHz. Their Mel-spectrogram are computed using 32 frequency bands, 128 hop length, and 512 window size. Each extracted mouth is associated with a centered 64 window size of the Mel-spectrogram and filtered to remove high-frequency glitches. Each datum of the dataset contains a spectrogram with its associated mouth landmarks. The dataset is composed of 1,032,219 elements for training and 35,473 for testing.
Text-Driven Mouth Skeleton Rithesh and al. [18]  proposed the first contribution of end-to-end neural architecture for text-driven lip-syncing. Their work inspired our proposed architecture. We upgraded their architecture with state of the art contributions and extended it from 2D space coordinates to 3D ones. We replaced the Char2Wav module by Tacotron2  [21]  to convert text input into a Mel-spectrogram and WaveGlow  [22]  for phase reconstruction.
Neural Architecture Pipeline Our proposal is an end-to-end neural architecture for text-driven mouth animations composed of different modules. Each one of those is a crucial step because of cumulative approximation errors throughout the entire model. During development, we tried different approaches for the pipeline. One of them was to connect our CNN regressor directly to the Tacotron2 output. However, the output resolution was not sufficient to allow our model to learn the mouth landmarks properly. The Mel-spectrogram use by our architecture is computed using an STFT on the waveform produced by WaveGlow, as illustrated in Figure  6 , to allow control on its resolution. First one is in charge of learning frequency correlations at each time step whereas the second stage learns their dynamics according to the incoming Mel-spectrogram.
CONCLUSION In this work, we present an end-to-end Text-driven Mouth Animation model. Contributions in generative animations traditionally benefit the entertainment sector for video games and animated movies. We explore such technology to the use of virtual avatars for personal assistants. Visual feedback often enables more natural ways to interact, especially when combined with audio. Our focus in this work is the generation of text-driven mouth animations for such personal assistants to improve the user experience. To this end, we proposed a methodology for the creation of datasets dedicated to text-driven 3D mouth animations. This approach does not require the use of performance capture and can easily be extended to future applications. We also developed an endto-end neural network model combining state of the art in speech synthesis and a custom neural regressor inspired by previous work trained on our dataset.
Limitations Major limitations observed in our work are directly inherited from deep learning sensitivity to the data it is trained on and its heavy computation costs. • The visual realism fidelity of our mouth animations seems affected by the lack of horizontal movement. Our model does not seem to capture the horizontal mouth movements as good as the vertical ones. To tackle this issue, we plan to retrain our regressor network using different regularization techniques. • The computation cost of our pipeline is limited by the requirement of a powerful GPU. It cannot be suitable in some applications requiring limited physical space, power consumption, and network constraints. Hence, two aspects of the pipeline could be improved. On the one hand, WaveGlow, used in the TTS module, is a bottleneck for being able to integrate such project on Sytem On a Chip (SOC) devices and could be optimized by different approaches such as batch inference.
On the other hand, our visual rendering engine is limited by the mouth's 3D vertices and normals computation occurring on each frame and could be optimized by re-targeting the 3D landmarks on a 3D mouth model instead. • The unique voice used in our Speech Synthesizer can induce biases and is not suitable for applications requiring different gender, race or age characteristics or even neutrality. We plan to address this issue by retaining and conditioning each module of the TTS on a speaker latent variable using a multi-speaker dataset.
Généalogie Toute personne a une histoire personnelle, mais cette histoire n'existe que pour autant que des traces ont pu être laissées. Il n'y a pas d'histoire sans trace. En outre, le micro-historien -mais aussi l'historien en général -se doit de distinguer avec rigueur les sources primaires et les sources secondaires. Ici, je parlerai essentiellement des premières. Dès lors que l'état civil a été instauré, l'état a constitué des bases de données fondées sur des informations limitées, mais basiques : la date de naissance, la date de mariage et la date de décès. En ce sens, il avait été précédé par les églises qui tenaient déjà à jour ce type de registre. Si l'état civil -fondé en France après la Révolution, et en Espagne, à partir du 1 er janvier 1871 -n'est jamais totalement parfait (des erreurs de transcription peuvent s'y glisser parfois), il offre une base d'une très grande rigueur scientifique pour tout chercheur.
19 On peut consulter un article sur ce film sur la base de données du Grimh : https://www. grimh. org/index. php?option=com_content&view=article&layout=edit&id=532&lang=fr 20 La Unión republicana, Palma de Majorque (20 août 1900), p. 3. Para mañana se preparan grandiosas funciones, extrenándose la película de costumbres locales, titulada «Discurso del Sr. Miró en el Borne de Palma» Además se proyectarán las vistas que más han llamado la atención entre ellas "La Corrida de toros en Las Arenas de Barcelona" 21. Tout d'abord, nous pouvons remarquer que c'est au nom du Cinematógrafo Balear que ces tournages vont s'effectuer. Par ailleurs, l'article attribue la « dirección » du film sur le Ron Africana à Eduardo Crespo qui est, en réalité, le gérant de la marque en question. S'il est probable que ce dernier ait donné quelques instructions pour le tournage, la seule personne alors capable de tourner un film et de le développer à Palma de Majorque semble bien être Fructuoso Gelabert lui-même.
Le temps de traitement estimé était limité, inférieur à 400 s. Les plans de traitements ont été vérifiés avec Octavius & 2DArray (PTW, Freiburg). Les caractéristiques dosimétriques et des volumes ont été décrites par leurs médianes, valeurs extrêmes, moyennes et écart-types. La comparaison des données a été réalisée à l'aide du test des rangs signés de Wilcoxon Mann-Whitney pour données appariées, avec un seuil de signification p<0,05. Le logiciel utilisé était Stata v13. 1. Le résultat était à la limite de la signification pour le volume recevant 5 Gy.
Acknowledgments: We are indebted for the scientific and technical support given by  N. Pontius ,  Ch. Schüßler-Langeheine  and  R. Mitzner  at the slicing facility at the BESSY II storage ring. The authors are grateful for financial support received from the following agencies: the  French "Agence National de la Recherche "  via Project  No. ANR-11-LABX-0058_NIE  and Project EQUIPEX.
These two steps can be controlled by a "programmable sequencer" that generates the multiple RF pulses trains and control the delays during the experiment. For very simple experiments (pulse-acquisition), a laboratory pulse generator is sufficient. Finally, data processing and visualization can be performed by a simple oscilloscope, but in a more modern way using a computer (PC) with its software interface. It should be noted that the probe is connected to the excitation and reception blocks via a unit called duplexer. This element can be seen as a signal "switcher" that aims to protect the preamplifiers of the detection channel from high RF excitation power. The duplexer directs all RF power to the probe during the excitation step (by closing access to the receiving channel) first, and then redirects the detected NMR signal to the preamplification/demodulation chain.
Experimental set-up (except otherwise in the text). All NMR and test experiments have been made with the electronic setup outlined in Figure  4. A permanent magnet with a field of 1500 G (6. 4 MHz) is used for the static magnetic B0 field (see Figure  2 ). A home-made solenoidtype probe device and a 5-mm water sample tube were used for the tests. The frequency and the RF pulse duration have been set with the frequency generator and the pulse generator mentioned in the text. Data have been acquired and processed with some digital oscilloscopes with a sensitivities of 1 or 2 mV/div. 2  provides the characteristics and nomenclature of the electronic components used.
Contrary to usual optical layers processes, no ion beam assistance was used for depositing these layers in order to reduce the cost of the evaporation equipment. These results were implemented and used in optical simulation performed with Optilayer software in order to optimize the thicknesses to deposit on glass for white LED lighting  [19]. We purchased the maximum in total transmission (100%) at an incidence angle of 0° for the white LED spectral response wavelengths (350-800nm) described in Figure  1. Concerning single layers and multilayers configurations, optimized thicknesses were determined from refractive indexes and the optical target specifications described above. Concerning MgF2, an optimum thickness of 93nm has to be deposited in order to achieve the best total transmission. Concerning multilayer ZrO2/SiO2 coating, a simulation study was conducted to optimize the number of layers for achieving the best antireflective performance.
6 weeks, at 2 Gy/fraction. Bladder dose-volume histograms (DVHs) were compiled either with GETUG recommendations as maximum dose <80 Gy or with PROFIT recommendations as 50% and 70% of the bladder wall receiving less than 53 Gy and 71 Gy, respectively. Patient and treatment characteristics are described in Table  A1  (Supplementary material). All the patients provided informed consent. The trials were approved by the XXX (BLIND) Institutional Review Board and are registered in ClinicalTrials. gov (NCTXXX (BLIND) for the STIC-IGRT trial, NCTXXX (BLIND) for the PROFIT trial). The median follow-up was 50 months (range: 6-102 months). Acute (≤3 months from RT start date) and late (> 3months) urinary toxicity was scored using the CTCAE v. 3. 0 (210 patients from the STIC-IGRT trial) or the RTOG (62 patients from the PROFIT trial) radiation morbidity-scoring schema.
DISCUSSION A robust nonrigid registration strategy, coupled with voxel-wise comparisons, allowed us to investigate the local dose-effect relationship for acute and 5-years late urinary toxicity after prostate cancer RT. The dose on five SRSs located in the urethra and the bladder were identified as good predictors for five grade ≥ 1 symptoms (acute incontinence and retention, late retention, dysuria and hematuria). The predictive capabilities of these SRSs outperformed the predictive capabilities of the whole bladder. To our knowledge, this is the first study to explicitly correlate the dose to specific subregions of the bladder and the urethra with urinary toxicity, within a voxel-based framework. Given that the data were collected from clinical trials, these results may be generalized to a large part of the patient population.
Acknowledgements This work was supported by the  Institut National du Cancer (INCa)  for the STIC IGRT-P and PROFIT trials, and received a  French government grant  (through the  CominLabs excellence laboratory  and managed by the  National Research Agency  in the '' Investing for the Future" program , under reference  ANR-10-LABX-07-01 ). We also thank  Marion Renouf  for her help to collect the data. This phrase was blinded in the manuscript and the ansers to the reviewers: The trials were approved by the  French Institutional Review Board  and are registered in ClinicalTrials. gov( NCT00433706  for the STIC-IGRT trial,  NCT00304759  for the PROFIT trial).
Statistical analysis Statistical analysis was performed by using XLSTAT TM (Addinsoft) software. Quantitative variables were expressed as means, SD, and ranges. Qualitative variables were expressed as raw numbers, proportions, and percentages. Comparisons between the groups were performed using Student t-test for continuous variables and chi-square tests with Yates correction for categorical variables. Correlation between axial tumor short diameter at one month after treatment and MWA duration was searched using the Pearson correlation test. P-values < 0. 05 were considered indicative of statistical significance.
Critères d'éligibilité Des études publiées en anglais et en français traitant de la radiothérapie adaptative et de l& radiothérapie guidée par l'image dans les cancers de prostate, de vessie, du col utérin, bronchiques non à petites cellules, ORL et dans les cancers digestifs (OEsophage, foie, pancréas et rectum) ont été sélectionnées selon les critères suivants : -articles publiés entre 2000 et 2019. -articles utilisant des techniques de radiothérapie externe photonique. -articles dont la pertinence clinique était jugée suffisante, ainsi les études rétrospectives de moins de cinq patients ont été exclues. -articles dont les techniques de radiothérapie étaient suffisamment détaillées pour pouvoir être reproduites. Après examen des publications identifiées sur les bases de données, seules les études principales répondant aux critères mentionnés ci-dessus ont été retenues.
Acknowledgements We are grateful to the families of the nineteen villages of Camotán and Jocotán for their time, knowledge sharing and their willingness to collaborate. Thanks to the  Real Embassy of Norway  for their funding and to the Mesoamerican Agro-environmental Program for their institutional support. We would also like to thank  Muhammad Ibrahim ,  Alejandro Imbach ,  Danilo Padilla  and  Julio López  for their help with the research. We are grateful to  Alix Villanueva  and  Casi Avard  for translating and editing.
Cela permet par exemple d'évaluer la contribution des aérosols à base d'ammoniac à la pollution particulaire. Un focus particulier est fait sur les zones périurbaines pour analyser l'impact des sources agricoles (NH 3 et particules secondaires, PPP) sur la qualité de l'air urbain et la santé. La mise en place de réseaux d'observation pour des produits tels que les molécules phytopharmaceutiques a demandé d'importantes mises au point méthodologiques et des collaborations avancées entre acteurs de la recherche en métrologie et chimie analytique (pour la mise au point des protocoles de mesure ainsi que pour l'harmonisation des mesures en termes de prélèvements mais aussi des substances actives recherchées) et les associations agréées de surveillance de la qualité de l'air (AASQA) qui assurent le suivi des mesures et des bases de données afférentes.
Nephelometer data have been corrected for truncation and non-Lambertian illumination errors using the method described by  Anderson and Ogren (1998). The scanning mobility particle sizer (SMPS) composed of an electrostatic classifier (TSI Mod. 3080) and a condensation particle counter (CPC; TSI Mod. 3772) measures the sub-micron particle number size distribution within the 12-615 nm particle mobility diameter range with 5 min temporal resolution. Aerosol and sheath flow rates were 1. 0 and 5. 0 L min -1 , respectively. SMPS data have been corrected for internal diffusion losses and multiple charges with the AIM software (version 9. 0. 0, TSI, Inc. , St Paul MN, USA). Following calibration procedures, uncertainty in the measured particle size distribution is within 10 % and 20 % for the size range of  20-200 and 200-800 nm, respectively (Wiedensohler et al.
, 2014). 8 Large Scale Particule Image Velocimetry. 9 L'ensemble des résultats du projet FLOODSCALE est disponible dans le rapport scientifique : Braud I, Andrieu J, Ayral P-A, Bouvier C, Branger F, Carreau J, Delrieu G, Douvinet J, Freydier R, Leblois E, Le Coz J, Martin Ph, Nord G, Patris N, Perez S, Renard B, Seidel J-L, Vandervaere J-P. 2016. FloodScale: Observation et modélisation hydro-météorologique multi-échelles pour la compréhension et la simulation des crues éclairs, Rapport scientifique final du projet, ANR-2011 BS56 027 01, 149 p. , https://floodscale. irstea. fr/donnees/ rapports-finaux-flodscale.
Vulnérabilité, exposition et adaptation aux crues rapides Les recherches dans cette thématique visent à mieux documenter et comprendre la vulnérabilité des populations et territoires méditerranéens et les stratégies d'adaptation développées pour faire face aux évènements météorologiques intenses. Un premier axe consiste à collecter des données sur les évènements extrêmes hydrométéorologiques et les impacts et perturbations socio-économiques à l'échelle des régions ou pays méditerranéens à partir de diverses sources (bases de données nationales et internationales, presse écrite, services opérationnels. ), ainsi que des informations sur les comportements individuels à l'échelle d'un évènement au moyen d'entretiens semi-directifs sur le terrain réalisées dans le cadre de la LOP, de questionnaires en ligne, ou plus récemment, de l'analyse des réseaux sociaux (Twitter).
Une base de données géoréférencée a également été constituée sur le sud de la France pour les principaux évènements survenus depuis 2011 afin de collecter des données de validation sur les impacts liés aux crues rapide  (Saint-Martin et al. , 2018a). À partir de ces premiers résultats, le projet ANR PICS a été lancé afin de concevoir et tester de façon plus large des chaînes de prévision immédiate intégrée des impacts des crues soudaines. Le premier maillon de la chaîne de prévision porte sur la prévision immédiate des pluies et des débits, où notamment il s'agira d'évaluer les prévisions opérationnelles de précipitation disponibles pour les échéances 0 h à 6 h, incluant notamment les prévisions du système de prévision immédiate AROME-PI de Météo-France  (Auger et al. , 2015)  (Tab. 1) et le produit de prévision de précipitation PIAF de Météo-France qui fusionne les prévisions d'AROME-PI aux prévisions de la méthode d'extrapolation 2PIR de la mosaïque de lame d'eau radar PANTHERE.