Miracle-dz/UniFAR-FTUs huggingface dataset:
Modélisation des mécanismes de transport de la vapeur métallique dans les techniques de dépôt physique en phase vapeur

L'etude theorique et appliquee des mecanismes de transport des atomes metalliques mis en phase vapeur dans les methodes de depot physique en phase vapeur (p. V. D. ) fait l'objet de ce travail. Une premiere etude a ete realisee dans le cas de l'evaporation sous vide. Dans ce cas, les atomes emis suivent une trajectoire rectiligne sans subir de collision, et l'etude des phenomenes de transport porte principalement sur les conditions d'emission des atomes. Pour cela, l'influence, de la deformation de la source et de la fonction de distribution spatiale, sur les repartitions en epaisseur, a ete etudiee. L'hypothese de l'existence d'une zone de pression elevee au voisinage de la source permet d'expliquer la deformation des repartitions en epaisseurs experimentales. L'existence d'une telle zone semble etre confirmee par le calcul des pressions au-dessus de la source. La deuxieme partie de ce memoire porte sur la modelisation du transfert des atomes pulverises en pulverisation cathodique magnetron. Dans ce cas, les atomes metalliques subissent des collisions avec les atomes du gaz support de la decharge electrique. Les trajectoires des atomes sont alors simulees par les methodes de monte carlo et une comparaison entre des repartitions en epaisseur theoriques et experimentales permet de valider le modele dans le cas de la pulverisation des metaux purs. Ce modele est ensuite utilise pour determiner les fonctions de repartition en energie et les angles d'incidence des atomes metalliques lorsqu'ils arrivent sur le depot en croissance. Ce modele a egalement ete applique aux cas de depots d'alliages metalliques binaires (aluminium-titane) et de depots de nitrure de titane (tin). L'evolution des rapports atomiques al/ti d'une part et n/ti d'autre part a ete etudiee pour differentes conditions de depot
Viscosity solutions with shocks

A solution of single nonlinear first order equations may develop jump discontinuities even if initial data is smooth. Typical examples include a crude model equation describing some bunching phenomena observed in epitaxial growth of crystals as well as conservation laws where jump discontinuities are called shocks. Conventional theory of viscosity solutions does not apply.
Introduction to critical phenomena in fluids

Introduction to Critical Phenomena in Fluids encompasses the fundamentals of this relatively young field, as well as applications in the fields of chemical engineering, analytical chemistry, and environmental remediation processing. The exercises in the text have been developed in a way that makes the book suitable for graduate courses in chemical engineering thermodynamics and physical chemistry.
Caractérisation et quantification dans la basse atmosphère de composés organiques volatils biogéniques et anthropiques contribuant à la pollution de l'air

Les composes organiques volatils (COV) sont consideres avec les oxydes d'azote (NOX) comme les principaux precurseurs de la formation de l'ozone dans la troposphere. Ils ont des origines naturelles ou resultent des activites humaines. La connaissance qualitative et quantitative des principaux COV est indispensable a la comprehension de la physico-chimie de l'atmosphere. Le travail realise comporte une serie de resultats dont les plus marquants sont : - la realisation et la mise au point d'une chaine analytique permettant de determiner les concentrations atmospheriques des hydrocarbures anthropiques legers (C 4 - C 9); - la participation, apres validation du systeme analytique, a diverses campagnes de mesures sur site, principalement dans la region Midi-Pyrenees, afin de mettre en exergue la pollution atmospherique engendree par les hydrocarbures anthropiques; - la determination, lors de campagnes internationales, de taux et flux d'emission monoterpeniques (COV Biogeniques) de plusieurs ecosystemes differents, a partir de la methode des cuvettes instrumentees; - l'estimation annuelle des COV naturels de l'ecosysteme forestier francais, par application de modeles mathematiques.
Investigation on X-ray Shielding Property of PA6 Composite with High Tungsten Content

By using computer tomography(CT)instrument,the X-ray shielding property of nylon 6 composite with high tungsten concentration was investigated.The results showed that the X-ray shielding of the nylon 6 composite increased as the thickness density increased.Moreover,the test results observed the Lambert-Beer law.In addition,nylon 6 composite(density of 10.3 g/cm3)had similar X-ray shielding effect with lead.
Verres de confinement de déchets nucléaires de type SON68 et leurs produits d'altération : spectroscopie optique des terres rares et de l'uranium

Cette etude porte sur le comportement a long terme du verre SON68 et plus particulierement sur le comportement de l'uranium et des lanthanides au cours de l'alteration. Au sein du verre, coexistent les degres IV et VI d'oxydation de l'uranium. U(VI) se trouve sous entites UO22+ ainsi que dans un environnement de type UO3. L'environnement de U evolue avec l'alteration vers un melange uranyle et hydroxydes d'uranyle. Les especes bauranoite et uranophane cristallisent dans les gels. En ce qui concerne Eu3+, deux types de site ont pu etre mis en evidence. Dans le verre, le premier site a ete attribue a un environnement silicate conserve au cours de l'alteration tandis que le second est de nature boratee. La symetrie du site de la terre rare augmente dans les gels, ceci confirme qu'ils possedent une structure plus ordonnee que le verre. Le chapitre consacre aux effets d'irradiation s souligne principalement des differences de comportement entre un verre simple et le verre de type SON68.
Cognitive Radio Networking and Security: A Game-Theoretic View

With the rapid growth of new wireless devices and applications over the past decade, the demand for wireless radio spectrum is increasing relentlessly. The development of cognitive radio networking provides a framework for making the best possible use of limited spectrum resources, and it is revolutionising the telecommunications industry. This book presents the fundamentals of designing, implementing, and deploying cognitive radio communication and networking systems. Uniquely, it focuses on game theory and its applications to various aspects of cognitive networking. It covers in detail the core aspects of cognitive radio, including cooperation, situational awareness, learning, and security mechanisms and strategies. In addition, it provides novel, state-of-the-art concepts and recent results. This is an ideal reference for researchers, students and professionals in industry who need to learn the applications of game theory to cognitive networking.
Bacteremia in patients with liver cirrhosis

Las infecciones bacteriemicas son mas frecuentes en el paciente cirrotico que en la poblacion general. Se identificaron retrospectivamente 59 pacientes cirroticos con bacteriemia, hospitalizados entre los anos 2005 y 2008. La bacteriemia sin foco fue la mas frecuente (29%), seguida de aquellas de origen pulmonar (22%). Cincuenta y dos por ciento de los agentes aislados correspondieron a cocaceas grampositivas y 48% a bacilos gramnegativos, siendo estos ultimos los agentes predominantes en las bacteriemias nosocomiales. Los principales agentes aislados fueron Staphylococcns aureus (24%) y Escherichia col i (22%). La mortalidad de los pacientes cirroticos bacteriemicos fue mayor que la del total de cirroticos hospitalizados (37 vs 9,4%; p < 0,001) y la medicion del puntaje de MELD a las 72 horas se correlaciono significativamente con la mortalidad. Conclusion: La bacteriemia es una complicacion grave del paciente cirrotico y el MELD podria ser util en su categorizacion de riesgo.
ASSESSMENT AND CHARACTERIZATION OF STRESS INDUCED BY VIA-FIRST TSV TECHNOLOGY

Through Silicon Via (TSV) is a key enabling technology for 3D stacking. One of the main concerns regarding the TSV introduction inside the IC fabrication is the resulting stress build up in the silicon substrate that may induce warpage or expansion at the wafer level, strain and crystalline defects in the neighboring silicon of the TSV and finally can impact performances and reliability of the CMOS devices as well. Polysilicon, tungsten and copper are the three main conductors that are nowadays considered for the TSV fabrication. In a first part of this paper the different factors that contribute to the stress in these tree TSV types including the geometry, the materials and the process will be reviewed. After bonding on a temporary carrier and thinning of the substrate to expose the via the stress built up during the fabrication of the TSV can be also revealed by the expansion of the silicon membrane. Thermo-mechanical FEM simulations will be equally introduced and confronted to the experimental findings.
Rôle des caractéristiques membranaires dans l 'apoptose induite par le benzo[a]pyrène : implication du fer et des lysosomes

Nous avons etudie l'implication des caracteristiques membranaires et des organites intracellulaires au cours de l'apoptose induite par le benzo[a]pyrene (B[a]P) dans la lignee F258. Nous avons ainsi mis en evidence un effet protecteur du ganglioside GM1, stabilisant membranaire, sur l'apoptose induite par le B[a]P. Cette protection serait liee a une inhibition des dommages mitochondriaux, du stress oxydant et de l'entree de fer. Nous avons egalement montre que le B[a]P induisait une augmentation precoce de la fluidite membranaire. Une stabilisation des membranes par le cholesterol a permis d'inhiber l'augmentation de fluidite, l'entree de fer et l'apoptose. Nous avons de plus observe des modifications de la morphologie et du pH des lysosomes dans les cellules exposees au B[a]P. Ces modifications seraient en partie dues aux desordres mitochondriaux induits par cet hydrocarbure. Nous avons egalement mis en evidence une implication forte du fer lysosomal dans l'activation de la caspase-3.
Valoración comparativa de pruebas serodiagnósticas utilizadas para detectar enfermedad de Chagas en Venezuela

*Autor de correspondencia: nanes@ula.ve Se presenta la valoracion comparativa de 8 tecnicas de uso comun en el despistaje serologico de la enfermedad de Chagas utilizando muestras de pacientes de diversas procedencias del occidente de Venezuela. En el estudio fueron utilizados metodos serologicos convencionales (TAD, IFI, ELISA) y pruebas de diagnostico comercialmente expendidas en el pais (Pharmatest®, Chagatest ELISA®, Chagatest ELISA Recombinante V.3.0®, Test ELISA para Chagas III® y Chagas Stat PakTM Assay®). La comparacion de los resultados no revelo diferencias estadisticamente significativas entre los niveles de sensibilidad y especificidad de las tecnicas evaluadas (P>0.05). Se sugiere, para la obtencion de un diagnostico preciso, la implementacion de pruebas de rutina y pruebas confirmatorias. El analisis de la relacion costo-beneficio reflejo diferencias entre las tecnicas evaluadas, sugiriendo su uso de acuerdo a las condiciones de servicio presentes en cada centro diagnostico, para lo cual se proponen pruebas candidatas para la rutina y la confirmacion diagnostica. Se demuestra la disminucion progresiva de reactividad, con el consecuente incremento de resultados erroneos, en una prueba comercial sometida a sucesivos cambios de temperatura en el tiempo.
Lidar-based exploration and discretization for mobile robot planning

In robotic applications, the control, and actuation deal with a continuous description of the system and environment, while high-level planning usually works with a discrete description. This paper considers the problem of bridging the low-level control and high-level planning for robotic systems via sensor data. In particular, we propose a discretization algorithm that identifies free polytopes via lidar point cloud data. A transition graph is then constructed where each node corresponds to a free polytope and two nodes are connected with an edge if the two corresponding free polytopes intersect. Furthermore, a distance measure is associated with each edge, which allows for the assessment of quality (or cost) of the transition for high-level planning. For the low-level control, the free polytopes act as a convenient encoding of the environment and allow for the planning of collision-free trajectories that realizes the high-level plan. The results are demonstrated in high-fidelity ROS simulations and experiments with a drone and a Segway.
An Efficient End-to-End Deep Learning Training Framework via Fine-Grained Pattern-Based Pruning

Convolutional neural networks (CNNs) are becoming increasingly deeper, wider, and non-linear because of the growing demand on prediction accuracy and analysis quality. The wide and deep CNNs, however, require a large amount of computing resources and processing time. Many previous works have studied model pruning to improve inference performance, but little work has been done for effectively reducing training cost. In this paper, we propose ClickTrain: an efficient and accurate end-to-end training and pruning framework for CNNs. Different from the existing pruning-during-training work, ClickTrain provides higher model accuracy and compression ratio via fine-grained architecture-preserving pruning. By leveraging pattern-based pruning with our proposed novel accurate weight importance estimation, dynamic pattern generation and selection, and compiler-assisted computation optimizations, ClickTrain generates highly accurate and fast pruned CNN models for direct deployment without any time overhead, compared with the baseline training. ClickTrain also reduces the end-to-end time cost of the state-of-the-art pruning-after-training methods by up to about 67% with comparable accuracy and compression ratio. Moreover, compared with the state-of-the-art pruning-during-training approach, ClickTrain reduces the accuracy drop by up to 2.1% and improves the compression ratio by up to 2.2X on the tested datasets, under similar limited training time.
LAGNet: Logic-Aware Graph Network for Human Interaction Understanding

Compared with the progress made on human activity classification, much less success has been achieved on human interaction understanding (HIU). Apart from the latter task is much more challenging, the main cause is that recent approaches learn human interactive relations via shallow graphical representations, which is inadequate to model complicated human interactions. In this paper, we propose a deep logic-aware graph network, which combines the representative ability of graph attention and the rigorousness of logical reasoning to facilitate human interaction understanding. Our network consists of three components, a backbone CNN to extract image features, a graph network to learn interactive relations among participants, and a logic-aware reasoning module. Our key observation is that the first-order logic for HIU can be embedded into higher-order energy functions, minimizing which delivers logic-aware predictions. An efficient mean-field inference algorithm is proposed, such that all modules of our network could be trained jointly in an end-to-end way. Experimental results show that our approach achieves leading performance on three existing benchmarks and a new challenging dataset crafted by ourselves. Code will be publicly available.
Simulation of the orbit and spin period evolution of the double pulsars PSR J0737-3039 from their birth to coalescence induced by gravitational wave radiation

The complete orbital and spin period evolutions of the double neutron star (NS) system PSR J0737–3039 are simulated from birth to coalescence, which include the two observed radio pulsars classified as primary NS PSR J0737–3039A and companion NS PSR J0737–3039B. By employing the characteristic age of PSR J0737–3039B to constrain the true age of the double pulsar system, the initial orbital period and initial binary separation are obtained as 2.89 h and 1.44 × 106 km, respectively, and the coalescence age or the lifetime from the birth to merger of PSR J0737–3039 is obtained to be 1.38 × 108 yr. At the last minute of coalescence, corresponding to the gravitational wave frequency changing from 20 Hz to 1180 Hz, we present the binary separation of PSR J0737–3039 to be from 442 km to 30 km, while the spin periods of PSR J0737–3039A and PSR J0737–3039B are 27.10 ms and 4.63 s, respectively. From the standard radio pulsar emission model, before the system merged, the primary NS could still be observed by a radio telescope, but the companion NS had crossed the death line in the pulsar magnetic-field versus period (B – P) diagram at which point it is usually considered to cease life as a pulsar. This is the first time that the whole life evolutionary simulation of the orbit and spin periods for a double NS system is presented, which provides useful information for observing a primary NS at the coalescence stage.
Interpretable and Transferable Models to Understand the Impact of Lockdown Measures on Local Air Quality

The COVID-19 related lockdown measures offer a unique opportunity to understand how changes in economic activity and traffic affect ambient air quality and how much pollution reduction potential can the society offer through digitalization and mobilitylimiting policies. In this work, we estimate pollution reduction over the lockdown period by using the measurements from ground air pollution monitoring stations, training a long-term prediction model and comparing its predictions to measured values over the lockdown month.We show that our models achieve state-of-the-art performance on the data from air pollution measurement stations in Switzerland and in China: evaluate up to -15.8% / +34.4% change in NO2 / PM10 in Zurich; -35.3 % / -3.5 % and -42.4 % / -34.7 % in NO2 / PM2.5 in Beijing and Wuhan respectively. Our reduction estimates are consistent with recent publications, yet in contrast to prior works, our method takes local weather into account. What can we learn from pollution emissions during lockdown? The lockdown period was too short to train meaningful models from scratch. To tackle this problem, we use transfer learning to newly fit only traffic-dependent variables. We show that the resulting models are accurate, suitable for an analysis of the post-lockdown period and capable of estimating the future air pollution reduction potential.
ac susceptibility study of magnetic relaxation phenomena in the antiskyrmion-hosting tetragonal Mn-Pt(Pd)-Sn system

Here, we report an exhaustive study of the frequency-dependent ac magnetic susceptibility of the ${D}_{2d}$-symmetric Heusler system Mn-Pt(Pd)-Sn that hosts antiskyrmions over a wide temperature range. Magnetic relaxation studies using Cole-Cole formalism reveal a Debye-type relaxation with a nearly negligible distribution in relaxation times. In contrast to the archetypical skyrmion hosts, the high Curie temperature ${T}_{C}$ of the present system ensures shorter switching times, and correspondingly, higher frequencies are required to probe the relaxation dynamics. We find a nonmonotonic variation in the characteristic relaxation time with distinct maxima at the phase boundaries via helical $\ensuremath{\longrightarrow}$ antiskyrmion $\ensuremath{\longrightarrow}$ field-polarized states, indicating slower magnetization dynamics over the region of phase coexistence. The temperature-dependent relaxation time across different phases is of the order of ${10}^{\ensuremath{-}5}--{10}^{\ensuremath{-}4}$ s and follows the well-known Arrhenius law with reasonable values of the energy barriers. The present study concerning the magnetization dynamics in the antiskyrmion host tetragonal Heusler system is an important contribution towards the basic understanding of the dynamical aspects of antiskyrmions for their potential applications.
Segmentation overlapping wear particles with few labelled data and imbalance sample

Ferrograph image segmentation is of significance for obtaining features of wear particles. However, wear particles are usually overlapped in the form of debris chains, which makes challenges to segment wear debris. An overlapping wear particle segmentation network (OWPSNet) is proposed in this study to segment the overlapped debris chains. The proposed deep learning model includes three parts: a region segmentation network, an edge detection network and a feature refine module. The region segmentation network is an improved U shape network, and it is applied to separate the wear debris form background of ferrograph image. The edge detection network is used to detect the edges of wear particles. Then, the feature refine module combines low-level features and high-level semantic features to obtain the final results. In order to solve the problem of sample imbalance, we proposed a square dice loss function to optimize the model. Finally, extensive experiments have been carried out on a ferrograph image dataset. Results show that the proposed model is capable of separating overlapping wear particles. Moreover, the proposed square dice loss function can improve the segmentation results, especially for the segmentation results of wear particle edge.
Energy Supply for Heating the Slow Solar Wind Observed by Parker Solar Probe between 0.17 and 0.7 au

Energy supply sources for the heating process in the slow solar wind remain unknown. The Parker Solar Probe (PSP) mission provides a good opportunity to study this issue. Recently, PSP observations have found that the slow solar wind experiences stronger heating inside 0.24 au. Here for the first time we measure in the slow solar wind the radial gradient of the low-frequency breaks on the magnetic trace power spectra and evaluate the associated energy supply rate. We find that the energy supply rate is consistent with the observed perpendicular heating rate calculated based on the gradient of the magnetic moment. Based on this finding, one could explain why the slow solar wind is strongly heated inside 0.25 au but expands nearly adiabatically outside 0.25 au. This finding supports the concept that the energy added from the energy-containing range is transferred by an energy cascade process to the dissipation range, and then dissipates to heat the slow solar wind. The related issues for further study are discussed.
SalSum: Saliency-based Video Summarization using Generative Adversarial Networks

The huge amount of video data produced daily by camera-based systems, such as surveilance, medical and telecommunication systems, emerges the need for effective video summarization (VS) methods. These methods should be capable of creating an overview of the video content. In this paper, we propose a novel VS method based on a Generative Adversarial Network (GAN) model pre-trained with human eye fixations. The main contribution of the proposed method is that it can provide perceptually compatible video summaries by combining both perceived color and spatiotemporal visual attention cues in a unsupervised scheme. Several fusion approaches are considered for robustness under uncertainty, and personalization. The proposed method is evaluated in comparison to state-of-the-art VS approaches on the benchmark dataset VSUMM. The experimental results conclude that SalSum outperforms the state-of-the-art approaches by providing the highest f-measure score on the VSUMM benchmark.