Topological descriptors for 3D surface analysis

We investigate topological descriptors for 3D surface analysis, i.e. the classification of surfaces according to their geometric fine structure. On a dataset of high-resolution 3D surface reconstructions we compute persistence diagrams for a 2D cubical filtration. In the next step we investigate different topological descriptors and measure their ability to discriminate structurally different 3D surface patches. We evaluate their sensitivity to different parameters and compare the performance of the resulting topological descriptors to alternative (non-topological) descriptors. We present a comprehensive evaluation that shows that topological descriptors are (i) robust, (ii) yield state-of-the-art performance for the task of 3D surface analysis and (iii) improve classification performance when combined with non-topological descriptors.Comment: 12 pages, 3 figures, CTIC 201

Poussée de maladie de Kaposi et élévation du CA 19-9: Penser à la tuberculose!

La maladie de Kaposi (MK) est une entité pathologique qui peut survenir chez les patients VIH positifs et dans le cadre d'une immunodépression, d'origine tuberculeuse très rarement. On décrit le cas d'une MK chez un patient VIH négatif au décours d'une tuberculose. Nous rapportons le cas d'un patient âgé de 81 ans, VIH négatif, ayant présenté deux nodules angiomateux de l'avant bras gauche dont la biopsie cutanée était en faveur d'une MK. L'évolution était marquée 2 mois plus tard, par  l'apparition de placards angiomateux extensifs des deux membres supérieurs et d'adénopathies cervicales jugulo-carotidiennes bilatérales. La biopsie ganglionnaire était en faveur d'une  tuberculose ganglionnaire. Par ailleurs, il avait un taux sérique élevé des CA 19-9. La régression de l'étendue des lésions au niveau des membres  supérieurs et la  normalisation du taux sérique des CA 19-9 ont été obtenues sous traitement anti-tuberculeux. Chez les patients atteints d'une MK avec une élévation des CA 19-9, il faut penser à la tuberculose

Neurocognitive outcome after preterm birth: Interest of the follow-up and the systematic evaluation

ObjectivePreterm children can experience cognitive and behavioral difficulties being able to be responsible for school difficulties going to the academic failure. The aim of this study was to assess the cognitive process while insisting on the early screening from the preschool age.MethodsThe data arise from the study of files and from the neuropsychological evaluations realized with the premature children followed in a regular way to the service. The premature children with or without motor disabilities more 4 and a half-years, old deficit integrated pre-school and ordinary school were included. The children with severe disabilities in upper limbs and the children having a mental deficiency were excluded.Results30 middle-aged children 7 years 5 months have been included. The prematurity is between 27–34. The born term has an effect on the performances in particular on attention and visuo-spatial capacities.ConclusionThe prematurity is a risk factor of the school future of the child. There is specially a negative impact on visuo-spatial and visuo-motor processes and those children present social and behavioral difficulties. It is mandatory to include the neuropsychological evaluation in any follow-up of premature child thanks to tests validated in the Tunisian context. It remains of great importance to identify effective interventions to improve the long-term neurocognitive outcomes

Artificially decreasing cortical tension generates aneuploidy in mouse oocytes

Human and mouse oocytes’ developmental potential can be predicted by their mechanical properties. Their development into blastocysts requires a specific stiffness window. In this study, we combine live-cell and computational imaging, laser ablation, and biophysical measurements to investigate how deregulation of cortex tension in the oocyte contributes to early developmental failure. We focus on extra-soft cells, the most common defect in a natural population. Using two independent tools to artificially decrease cortical tension, we show that chromosome alignment is impaired in extra-soft mouse oocytes, despite normal spindle morphogenesis and dynamics, inducing aneuploidy. The main cause is a cytoplasmic increase in myosin-II activity that could sterically hinder chromosome capture. We describe here an original mode of generation of aneuploidies that could be very common in oocytes and could contribute to the high aneuploidy rate observed during female meiosis, a leading cause of infertility and congenital disorders

A New Zn(II) Metal Hybrid Material of 5-Nitrobenzimidazolium Organic Cation (C7H6N3O2)2[ZnCl4]: Elaboration, Structure, Hirshfeld Surface, Spectroscopic, Molecular Docking Analysis, Electric and Dielectric Properties

The slow solvent evaporation approach was used to create a single crystal of (CHNO)[ZnCl] at room temperature. Our compound has been investigated by single-crystal XRD which declares that the complex crystallizes in the monoclinic crystallographic system with the P2/c as a space group. The molecular arrangement of the compound can be described by slightly distorted tetrahedral ZnCl anionic entities and 5-nitrobenzimidazolium as cations, linked together by different non-covalent interaction types (H-bonds, Cl…Cl, π…π and C–H…π). Hirshfeld’s surface study allows us to identify that the dominant contacts in the crystal building are H…Cl/Cl…H contacts (37.3%). FT-IR method was used to identify the different groups in (CHNO)[ZnCl]. Furthermore, impedance spectroscopy analysis in 393 ≤ T ≤ 438 K shows that the temperature dependence of DC conductivity follows Arrhenius’ law. The frequency–temperature dependence of AC conductivity for the studied sample shows one region (E = 2.75 eV). In order to determine modes of interactions of compound with double stranded DNA, molecular docking simulations were performed at molecular level

Empirical Analysis for Stock Price Prediction Using NARX Model with Exogenous Technical Indicators

The file attached to this record is the Publisher's final version. Open access article.Stock price prediction is one of the major challenges for investors who participate in the stock markets. Therefore, different methods have been explored by practitioners and academicians to predict stock price movement. Artificial intelligence models are one of the methods that attracted many researchers in the field of financial prediction in the stock market. This study investigates the prediction of the daily stock prices for Commerce International Merchant Bankers (CIMB) using technical indicators in a NARX neural network model. The methodology employs comprehensive parameter trails for different combinations of input variables and different neural network designs. The study seeks to investigate the optimal artificial neural networks (ANN) parameters and settings that enhance the performance of the NARX model. Therefore, extensive parameter trails were studied for various combinations of input variables and NARX neural network configurations. The proposed model is further enhanced by preprocessing and optimising the NARX model’s input and output parameters. The prediction performance is assessed based on the mean squared error (MSE), R-squared, and hit rate. The performance of the proposed model is compared with other models, and it is shown that the utilisation of technical indicators with the NARX neural network improves the accuracy of one-step-ahead prediction for CIMB stock in Malaysia. The performance of the proposed model is further improved by optimising the input data and neural network parameters. The improved prediction of stock prices could help investors increase their returns from investment in stock markets

Age estimation from faces using deep learning:a comparative analysis

Abstract Automatic Age Estimation (AAE) has attracted attention due to the wide variety of possible applications. However, it is a challenging task because of the large variation of facial appearance and several other extrinsic and intrinsic factors. Most of the proposed approaches in the literature use hand-crafted features to encode ageing patterns. Deeply learned features extracted by Convolutional Neural Networks (CNNs) algorithms usually perform better than hand-crafted features. The main contribution of this paper is an extensive comparative analysis of several frameworks for real AAE based on deep learning architectures. Different well-known CNN architectures are considered and their performances are compared. MORPH, FG-NET, FACES, PubFig and CASIA-web Face datasets are used in our experiments. The robustness of the best deep estimator is evaluated under noise, expression changes, “crossing” ethnicity and “crossing” gender. The experimental results demonstrate the high performances of the popular CNNs frameworks against the state-of-art methods of automatic age estimation. A Layer-wise transfer learning evaluation is done to study the optimal number of layers to fine-tune on AAE task. An evaluation framework of Knowledge transfer from face recognition task across AAE is performed. We have made our best-performing CNNs models publicly available that would allow one to duplicate the results and for further research on the use of CNNs for AAE from face images

Transparent Er3+ doped Ag2O containing tellurite glass-ceramics

Transparent Er3+ doped Ag2O containing tellurite glass-ceramics were fabricated by melting process followed by a heat treatment at 20 °C above the glass transition temperature of the glass for 2 to 17 h. The effects of the crystallization on the optical and luminescence properties of the glasses are presented and discussed. The precipitation of Bi4TeO8 crystal was confirmed in all the glasses, independently of their composition. From the spectroscopic properties, the heat treatment was found to have no impact on the site of the Er3+ ions indicating that the Er3+ ions remain in the amorphous part of the glass-ceramic. Although Ag nanoparticles could be evidenced using transmission electron microscopy and nonlinear optical imaging, no surface plasmon resonance band of Ag nanoparticles appeared in the absorption spectrum of the heat treated glasses. No enhancement of the NIR emission centered at 1.5 μm was observed probably due to the low concentration of Ag nanoparticles precipitating in the glasses. However, an increase in the intensity of the upconversion and mid-infrared emissions was observed from the glass-ceramics prepared with the low amount of Ag2O (<1 mol%). As evidenced using Raman spectroscopy, the addition of Ag2O was found to depolymerize the tellurite network. The precipitation of the Bi4TeO8 crystal in the most polymerized glasses is suspected to reduce the Er–Er distances whereas it has no significant impact on the Er–Er distances in glasses with a depolymerized network.publishedVersionPeer reviewe