Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation de la vulnérabilité sismique de bâtiments à partir de mesures in situ

L'objectif de cette these est d'analyser et de caracteriser le lien entre les mouvements du sol et la reponse des bâtiments. En particulier, on s'interesse a reduire les incertitudes qui entrent en jeu dans les methodes de vulnerabilite, afin d'estimer plus precisement la vulnerabilite des structures au risque sismique. Pour ce faire, cette these est basee sur l'utilisation de donnees enregistrees au sein de bâtiments. Les enregistrements de vibrations ambiantes et de seismes de faibles amplitudes au sein de bâtiments permettent de caracteriser le comportement elastique de ces structures. Des modeles peuvent ensuite etre definis afin d'etudier les differentes composantes de la variabilite presente au sein des courbes de fragilite. On s'interesse dans un premier temps au premier niveau de dommage, au-dela duquel les caracteristiques elastiques des bâtiments sont modifiees et les modeles definis ne sont plus valables. Des enregistrements de seismes ayant eu lieu depuis le debut des annees 1970 dans des bâtiments californiens sont ensuite utilises. A partir de ces donnees, on a pu mettre en evidence des relations entre le deplacement au sein des structures et des parametres decrivant la nocivite des signaux sismiques. Suivant l'indicateur utilise pour representer la nocivite des seismes, la reponse des bâtiments peut etre estimee plus ou moins precisement. Notamment, les indicateurs faisant intervenir les parametres dynamiques des bâtiments sont davantage lies avec la reponse des structures, representee par son deplacement inter-etage moyen. La variabilite de la reponse des bâtiments peut etre amelioree en regroupant les bâtiments par typologies (definies suivant leur materiau principal de construction et leur hauteur). En apportant davantage d'informations sur les structures, on peut ainsi diminuer la composante epistemique de la variabilite. De plus, en combinant des indicateurs de nocivite, on peut ameliorer la precision pour la prediction de la reponse de la structure. Une forme fonctionnelle est ainsi proposee afin d'estimer le deplacement inter-etage moyen au sein des structures, pour plusieurs typologies de bâtiments, a partir de quatre indicateurs de nocivite. Cette forme fonctionnelle est utilisee pour etablir des courbes de fragilite et peut egalement etre utilisee afin de donner une premiere estimation des dommages a la suite d'un seisme, en comparant les valeurs de deformations inter-etages avec des valeurs de reference (FEMA, 2003). Enfin, une methode hybride est proposee pour la construction de courbes de fragilite, faisant intervenir un modele de comportement non lineaire. Les parametres de ce modele sont definis de telle sorte que la reponse du modele s'ajuste aux enregistrements de seismes effectues dans les bâtiments. Ce modele est ensuite utilise pour evaluer les composantes d'incertitudes et pour construire des courbes de fragilite pour tous les niveaux de dommages.
Chemical dry etching of silicon nitride and silicon dioxide using CF4/O2/N2 gas mixtures

The chemical dry etching of silicon nitride (Si3N4)and silicon nitride (SiO2) in a downstream plasma reactor using CF4, O2, and N2 has been investigated. A comparison of the Si3N4 and SiO2 etch rates with that of polycrystalline silicon shows that the etch rates of Si3N4 and SiO2 are not limited by the amount of fluorine arriving on the surface only. Adding N2 in small amounts to a CF4/O2 microwave discharge increases the Si3N4 etch rate by a factor of 7, but leaves the SiO2 etch rate unchanged. This enables etch rate ratios of Si3N4 over SiO2 of 10 and greater. The Si3N4 etch rate was investigated with respect to dependence of tube length, tube geometry, and lining materials. Argon actinometry has shown that the production of F atoms in the plasma is not influenced by the addition of N2 to the discharge. Mass spectrometry shows a strong correlation between the Si3N4 etch rate and the NO concentration. X‐ray photoelectron spectra of the silicon nitride samples obtained immediately after the etching proces.
Stress Assessment Based on Decision Fusion of EEG and fNIRS Signals

Fusion of electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) is an emerging approach in the field of psychological and neurological studies. We developed a decision fusion technique to combine the output probabilities of the EEG and fNIRS classifiers. The fusion explored support vector machine as classifier for each modality, and optimized the classifiers based on their receiver operating characteristic curve values. EEG and fNIRS signal were acquired simultaneously while performing mental arithmetic task under control and stress conditions. Experiment results from 20 subjects demonstrated significant improvement in the detection rate of mental stress by +7.76% (<inline-formula> <tex-math notation="LaTeX">$p<0.001$ </tex-math></inline-formula>) and +10.57% (<inline-formula> <tex-math notation="LaTeX">$p<0.0005$ </tex-math></inline-formula>), compared with sole modality of EEG and fNIRS, respectively.
Second-line therapy for small cell lung cancer: exploring the potential role of circulating tumor cells.

BACKGROUND Small cell lung cancer (SCLC) is an aggressive and invasive variant of lung tumors. SCLC, especially in advanced stages, is distinguished by extremely high numbers of circulating tumor cells (CTCs) in comparison to other malignancies. CTCs are operative in tumor spread and are currently enumerated to assess prognosis and response to cytotoxic therapy. Chemosensitivity of SCLC CTCs compared to primary tumors and metastases is not known. METHODS Establishment of two SCLC CTC cell lines, namely BHGc7 and BHGc10, allowed the in vitro characterization of their chemosensitivity to the second-line chemotherapeutics topotecan and epirubicin in comparison to a range of SCLC cell lines. RESULTS The SCLC CTC cell lines exhibited an approximately 7- and 12-fold increased chemosensitivity to epirubicin compared to topotecan, respectively, in in vitro cytotoxicity assays. In comparison to a panel of six SCLC cell lines, the two CTC lines showed a significantly higher chemosensitivity to epirubicin (range, 3- to 16-fold) and topotecan (range, 2.2- to 14.4-fold), respectively. CONCLUSIONS CTC cell lines derived from SCLC patients with recurrent disease exhibit high chemosensitivity to epirubicin vs. topotecan and show considerable more cytotoxicity in response to both compounds in comparison to a panel of SCLC cell lines. Thus, a decrease in the number of CTCs in response to second-line chemotherapy in SCLC patients may overestimate the effect on resident SCLC lesions and metastases.
Connecting the learners: improving uptake of a nursing home educational program by focusing on staff interactions.

PURPOSE OF THE STUDY The CONNECT intervention is designed to improve staff connections, communication, and use of multiple perspectives for problem solving. This analysis compared staff descriptions of the learning climate, use of social constructivist learning processes, and outcomes in nursing facilities receiving CONNECT with facilities receiving a falls education program alone. DESIGN AND METHODS Qualitative evaluation of a randomized controlled trial was done using a focus group design. Facilities (n = 8) were randomized to a falls education program alone (control) or CONNECT followed by FALLS (intervention). A total of 77 staff participated in 16 focus groups using a structured interview protocol. Transcripts were analyzed using framework analysis, and summaries for each domain were compared between intervention and control facilities. RESULTS Notable differences in descriptions of the learning climate included greater learner empowerment, appreciation of the role of all disciplines, and seeking diverse viewpoints in the intervention group. Greater use of social constructivist learning processes was evidenced by the intervention group as they described greater identification of communication weaknesses, improvement in communication frequency and quality, and use of sense-making by seeking out multiple perspectives to better understand and act on information. Intervention group participants reported outcomes including more creative fall prevention plans, a more respectful work environment, and improved relationships with coworkers. No substantial difference between groups was identified in safety culture, shared responsibility, and self-reported knowledge about falls. IMPLICATIONS CONNECT appears to enhance the use of social constructivist learning processes among nursing home staff. The impact of CONNECT on clinical outcomes requires further study.
Cognitive impairment in motor neuron disease

ABSTRACT – A systematic investigation of the cognitive functions of 22 patients affected with motor neuron disease (MND) compared to 36 controls matched for age and education was performed. The MND group showed cognitive performances slightly but significantly lower than the control group; 6 MND patients, however, had decidedly pathological values. Cognitive impairment was stereotyped and global, with sparing of memory. There was no significant difference between patients with isolated involvement of the lower motor neuron and those with associated pyramidal involvement. Our neuropsychological findings are in agreement with previous clinical, neuroradiological and pathological reports indicating extra‐motor cerebral involvement in MND.
Estimation of external quantum efficiency for multi-junction solar cells under influence of charged particles using artificial neural networks

External quantum efficiency (EQE) of a solar cell is an important parameter as it determines the design efficiency and overall conversion efficiency. The EQE of solar cells for space applications is adversely affected due to bombardment of charged particles in space. Numerical model based softwares, e.g., PC1D, can be used to estimate the EQE under such situation. By varying the cell parameters to fit the measured EQE one can obtain degradation performance of space solar cells. However, due to complex phenomena and interactions occurring between the junctions of the solar cells and the nonlinear influence of charged particles, the accuracy of these models may be limited. In this paper we propose an artificial neural network (ANN)-based model to estimate the EQE performance of triple junction InGaP/GaAs/Ge solar cells under the influence of wide range of charged particles. With extensive simulation results we have shown that the ANN-based models provide better estimate of the EQE in terms of mean square error and correlation coefficient than the results reported by Sato et al.
Research on rotor excitation neural network PID control of variable speed constant frequency wind turbine

The key of variable speed constant frequency wind turbine operating control is the rotor excitation control, This article state the double-fed generator stator magnetic field direction detection control principle, discussed the stator magnetic field localization and the rotor position definite method, The rotor excitation uses neural network PID control which realizes easily in DSP, and has developed the DSP rotor excitation control device, has conducted the double-fed generator rotor excitation neural network PID control experimental study. The test result indicated that, the double-fed generator uses the neural network PID control strategy The test result indicated that, the double-fed generator uses the neural network PID control strategy is effective, not only it can realize the active power and the reactive power independent control, but also has the good static adjustment characteristic and the dynamic characteristic.
Top down scene context based visual attention model for natural images

Top down image semantics play a major role in predicting where people more attend in images. In the state of computational models of human visual attention incorporate high level object detections signifying top down image semantics in a separate channel along with other bottom up saliency channels. The different occurrences of objects in a scene also to attract our attention and this interaction is ignored in recent computational models. This paper deals with the attention model which uses low, high, scene features to understand how their joint presence affects visual attention. The context based features of the scene are extracted using cause effect mechanism. The MIT bench mark data base is used in this paper. The saliency map is compared with some existing models using the performance metric of ROC and area under ROC. It seems that the scene context based saliency map gives promising results compare to the state of art models.
Herschel / HIFI : first science highlights Special feature L etter to the E ditor Herschel / HIFI spectroscopy of the intermediate mass protostar NGC 7129 FIRS 2

Herschel/HIFI observations of water from the intermediate mass protostar NGC 7129 FIRS 2 provide a powerful diagnostic of the physical conditions in this star formation environment. Six spectral settings, covering four H2O and two H2O lines, were observed and all but one H2O line were detected. The four H2O lines discussed here share a similar morphology: a narrower, ≈6 km s−1, component centered slightly redward of the systemic velocity of NGC 7129 FIRS 2 and a much broader, ≈25 km s−1 component centered blueward and likely associated with powerful outflows. The narrower components are consistent with emission from water arising in the envelope around the intermediate mass protostar, and the abundance of H2O is constrained to ≈10−7 for the outer envelope. Additionally, the presence of a narrow self-absorption component for the lowest energy lines is likely due to self-absorption from colder water in the outer envelope. The broader component, where the H2O/CO relative abundance is found to be ≈0.2, appears to be tracing the same energetic region that produces strong CO emission at high J.
Automated modeling of custom processors for DCT algorithm

The needs for automated digital system design rise with constant technology improvements and time-to-market shortening. High-level synthesis tools cope with this problem by raising the design specification to a higher level. We have implemented the methodology of custom processor automated modeling for DCT algorithm. This algorithm is often used in signal and image processing applications. At front end, the methodology assumes C code input specification as it is the case of many high-level synthesis tools. C programming language popularity offers the applicability for a broader spectrum of users. At back end, logic synthesis tools produce the FPGA implementation of the algorithm. The results are evaluated in terms of execution cycles required for completing the algorithm and processor's datapath components allocations, and compared to previous work.
Knowledge, uncertainty and physical geography: towards the development of methodologies for questioning belief

Although it is widely acknowledged that our understanding of environmental systems cannot be reduced to single predictions and unique explanations, determinism remains a common strategy in physical geography. This paper argues for explicit assessments of uncertainty in environmental data and models as a necessary, although not a sufficient, condition for balancing uncertain scientific arguments against uncertain social, ethical, moral and legal arguments in managing environmental systems. In particular, this paper aims to: (1) demonstrate the importance of assessing uncertainty within a realist research framework; (2) consider the nature of scientific uncertainty as the basis for developing methodologies that question belief; and (3) explore some important aspects of a methodology for evaluating uncertainties in environmental research.
Performance Analysis of Quality-Based Channel State Feedback Scheme for Wireless Multicast Systems With Greedy Scheduling

Multi-group multicasting has recently attracted substantial attention. In this letter, we propose quality-based channel state information feedback (QCF) in multicast systems with greedy scheduling of multiple multicast groups, and present exact expressions for outage probability and average capacity of the multicast systems using QCF over independent Rayleigh fading channels. Further, we provide a method to determine the appropriate QCF threshold, and describe the relative feedback load of QCF with respect to full channel state information feedback. Our QCF scheme can significantly reduce the feedback load, simultaneously accomplishing negligible system performance loss.
Affine-Invariant Geometric Constraints-Based High Accuracy Simultaneous Localization and Mapping

In this study we describe a new appearance-based loop-closure detection method for online incremental simultaneous localization and mapping (SLAM) using affine-invariant-based geometric constraints. Unlike other pure bag-of-words-based approaches, our proposed method uses geometric constraints as a supplement to improve accuracy. By establishing an affine-invariant hypothesis, the proposed method excludes incorrect visual words and calculates the dispersion of correctly matched visual words to improve the accuracy of the likelihood calculation. In addition, camera’s intrinsic parameters and distortion coefficients are adequate for this method. 3D measuring is not necessary. We use the mechanism of Long-Term Memory and Working Memory (WM) to manage the memory. Only a limited size of the WM is used for loop-closure detection; therefore the proposed method is suitable for large-scale real-time SLAM. We tested our method using the CityCenter and Lip6Indoor datasets. Our proposed method results can effectively correct the typical false-positive localization of previous methods, thus gaining better recall ratios and better precision.
Neural Post-Editing Based on Quality Estimation

Automatic post-editing (APE) is a challenging task on WMT evaluation campaign. We find that only a small number of edit operations are required for most machine translation outputs, through analysis of the training set of WMT17 APE en-de task. Based on this statistics analysis, two neural post-editing (NPE) models are trained depended on the edit numbers: single edit and minor edits. The improved quality estimation (QE) approach is exploited to rank models, and select the best translation as the post-edited output from the n -best list translation hypotheses generated by the best APE model and the raw translation system. Experimental results on the datasets of WMT16 APE test set show that the proposed approach significantly outperformed the baseline. Our approach can bring considerable relief from the overcorrection problem in APE.
Theoretical considerations in the optimization of surface waves on a planar structure

The problem of optimum excitation of surface waves on a grounded dielectric slab by means of slots in the ground plane is considered. By adopting a two-dimensional (2-D) model, analysis lead to closed forms for the power launched as surface waves and power leaked as radiation. Input admittance of a single slot source and mutual admittance between two slots are derived and utilized to design a three element Yagi array of slots to achieve a prescribed ratio of forward to backward surface wave power. As a development of the 2-D model, we allow finite extent of slot excitation by assuming a Gaussian E-field distribution across the slot. The effect of the Gaussian width on the excited surface wave power is studied. The analysis is relevant to the study of surface waves on printed circuits. Specifically, it applies to the implementation of power combiners based on quasioptical slab beam that have been recently introduced in the literature for use in the millimeter wave band.
Exploring Functional Connectivity Networks with Multichannel Brain Array Coils

The use of multichannel array head coils in functional and structural magnetic resonance imaging (MRI) provides increased signal-to-noise ratio (SNR), higher sensitivity, and parallel imaging capabilities. However, their benefits remain to be systematically explored in the context of resting-state functional connectivity MRI (fcMRI). In this study, we compare signal detectability within and between commercially available multichannel brain coils, a 32-Channel (32Ch), and a 12-Channel (12Ch) at 3T, in a high-resolution regime to accurately map resting-state networks. We investigate whether the 32Ch coil can extract and map fcMRI more efficiently and robustly than the 12Ch coil using seed-based and graph-theory-based analyses. Our findings demonstrate that although the 12Ch coil can be used to reveal resting-state connectivity maps, the 32Ch coil provides increased detailed functional connectivity maps (using seed-based analysis) as well as increased global and local efficiency, and cost (using graph-theory-based analysis), in a number of widely reported resting-state networks. The exploration of subcortical networks, which are scarcely reported due to limitations in spatial-resolution and coil sensitivity, also proved beneficial with the 32Ch coil. Further, comparisons regarding the data acquisition time required to successfully map these networks indicated that scan time can be significantly reduced by 50% when a coil with increased number of channels (i.e., 32Ch) is used. Switching to multichannel arrays in resting-state fcMRI could, therefore, provide both detailed functional connectivity maps and acquisition time reductions, which could further benefit imaging special subject populations, such as patients or pediatrics who have less tolerance in lengthy imaging sessions.
Uniform Binding of Aminoacyl-tRNAs to Elongation Factor Tu by Thermodynamic Compensation

Elongation factor Tu (EF-Tu) binds all elongator aminoacyl–transfer RNAs (aa-tRNAs) for delivery to the ribosome during protein synthesis. Here, we show that EF-Tu binds misacylated tRNAs over a much wider range of affinities than it binds the corresponding correctly acylated tRNAs, suggesting that the protein exhibits considerable specificity for both the amino acid side chain and the tRNA body. The thermodynamic contributions of the amino acid and the tRNA body to the overall binding affinity are independent of each other and compensate for one another when the tRNAs are correctly acylated. Because certain misacylated tRNAs bind EF-Tu significantly more strongly or weakly than cognate aa-tRNAs, EF-Tu may contribute to translational accuracy.
Real-time Gender Recognition for Uncontrolled Environment of Real-life Images

Gender recognition is a challenging task in real life images and surveillance videos due to their relatively low-resolution, under uncontrolled environment and variant viewing angles of human subject. Therefore, in this paper, a system of real-time gender recognition for real life images is proposed. The contribution of this work is fourfold. A skin-color filter is first developed to filter out non-face noises. In order to make the system robust, a mechanism of decision making based on the combination of surrounding face detection, context-regions enhancement and confidence-based weighting assignment is designed. Experimental results obtained by using extensive dataset show that our system is effective and efficient in recognizing genders for uncontrolled environment of real life images.