Airborne ultrasonic vortex generation using flexible ferroelectrets

Cellular ferroelectrets exhibit interesting electromechanical- acoustical characteristics. Their recent appearance and remarkable properties open up new possibilities for the design and development of ultrasonic transducers. In particular, the feasibility of fabricating ultrasonic vortex generators using ferroelectret films is demonstrated in this work. To this end, a transducer prototype was built by gluing the material onto a tangential-helical surface (outer diameter: 40 mm, pitch: 3.45 mm). Experimental results agree well with the theoretical estimation of the pressure and phase of the acoustic field in the near field and far field, which corroborates the potential of ferroelectrets to customize special acoustic fields. Furthermore, the proposed fabrication procedure is inexpensive and represents a new alternative for exploring and analyzing the special characteristics of acoustical helical wavefront

Seismic Response of Embankment Dams

This study is intended as a contribution towards a better understanding of the seismic response of embankment dams. Laboratory tests for the determination of static and dynamic mechanical properties of the material are described. A parametric study is performed varying the main source of earthquakes, the height of the dam, the type of the materials and the core position (central and upstream sloping core). The dynamic analyses have made possible the identification of hazard scenarios and particularly the evaluation of stability and residual deformation of the dams

A robotized dumper for debris removal in tunnels under construction

Tunnels in construction exhibit many challenges for automation. In this work we address the robotization of a conventional dumper for debris removal during the construction of tunnels, in the framework of a technological transfer project. The goal is to convert a dumper into an autonomous vehicle capable of planning, navigate and localize itself. Planning and navigation techniques have been adapted to the special kinodynamic characteristics of the vehicle. The difficulties for having a precise continuous localization in this kind of scenarios, due to the irregularities of the terrain, the changing illumination and the own scenario, have driven to develop hybrid localization techniques to integrate continuous and discrete information, coming from the navigation sensors, some semantic geometric features, and the signal strength propagation in tunnel scenarios. Simulation and real-world experiments are described, and some preliminary results are discussed

From Collapse to Freezing in Random Heteropolymers

We consider a two-letter self-avoiding (square) lattice heteropolymer model of N_H (out ofN) attracting sites. At zero temperature, permanent links are formed leading to collapse structures for any fraction rho_H=N_H/N. The average chain size scales as R = N^{1/d}F(rho_H) (d is space dimension). As rho_H --> 0, F(rho_H) ~ rho_H^z with z={1/d-nu}=-1/4 for d=2. Moreover, for 0 < rho_H < 1, entropy approaches zero as N --> infty (being finite for a homopolymer). An abrupt decrease in entropy occurs at the phase boundary between the swollen (R ~ N^nu) and collapsed region. Scaling arguments predict different regimes depending on the ensemble of crosslinks. Some implications to the protein folding problem are discussed.Comment: 4 pages, Revtex, figs upon request. New interpretation and emphasis. Submitted to Europhys.Let

Overview of ImageCLEFcoral 2019 task

Understanding the composition of species in ecosystems on a large scale is key to developing effective solutions for marine conservation, hence there is a need to classify imagery automatically and rapidly. In 2019, ImageCLEF proposed for the first time the ImageCLEFcoral task. The task requires participants to automatically annotate and localize benthic substrate (such as hard coral, soft coral, algae and sponge) in a collection of images originating from a growing, large-scale dataset from coral reefs around the world as part of monitoring programmes. In its first edition, five groups participated submitting 20 runs using a variety of machine learning and deep learning approaches. Best runs achieved 0.24 in the annotation and localisation subtask and 0.04 on the pixel-wise parsing subtask in terms of MAP 0.5 IoU scores which measures the Mean Average Precision (MAP) when using the performance measure of Intersection over Union (IoU) bigger to 0.5 of the ground truth

SlideImages: A Dataset for Educational Image Classification

In the past few years, convolutional neural networks (CNNs) have achieved impressive results in computer vision tasks, which however mainly focus on photos with natural scene content. Besides, non-sensor derived images such as illustrations, data visualizations, figures, etc. are typically used to convey complex information or to explore large datasets. However, this kind of images has received little attention in computer vision. CNNs and similar techniques use large volumes of training data. Currently, many document analysis systems are trained in part on scene images due to the lack of large datasets of educational image data. In this paper, we address this issue and present SlideImages, a dataset for the task of classifying educational illustrations. SlideImages contains training data collected from various sources, e.g., Wikimedia Commons and the AI2D dataset, and test data collected from educational slides. We have reserved all the actual educational images as a test dataset in order to ensure that the approaches using this dataset generalize well to new educational images, and potentially other domains. Furthermore, we present a baseline system using a standard deep neural architecture and discuss dealing with the challenge of limited training data.Comment: 8 pages, 2 figures, to be presented at ECIR 202

EGS4 and MCNP4b MC Simulation of a Siemens KD2 Accelerator in 6 MV Photon Mode

The geometry of a Siemens Mevatron KD2 linear accelerator in 6 MV photon mode was modeled with EGS4 and MCNP4b. Energy spectra and other phase space distributions have been extensively compared in different plans along the beam line. The differences found have been evaluated both qualitative and quantitatively. The final aim was that both codes, running in different operating systems and with a common set of simulation conditions, met the requirement of fitting the experimental depth dose curves and dose profiles, measured in water for different field sizes. Whereas depth dose calculations are in a certain extent insensible to some simulation parameters like electron nominal energy, dose profiles have revealed to be a much better indicator to appreciate that feature. Fine energy tuning has been tried and the best fit was obtained for a nominal electron energy of 6.15 MeV

Placenta accreta spectrum - variations in clinical practice and maternal morbidity between UK and France : a population-based comparative study

SM’s DPhil was funded by the Medical Research Council. PACCRETA was funded by PACCRETA was funded by the French Health Ministry under its Clinical Research Hospital Program (grant number: AOR12156) and by the Angers University Hospital.Peer reviewedPublisher PD

An Overview of Lipid Droplets in Cancer and Cancer Stem Cells

For decades, lipid droplets have been considered as the main cellular organelles involved in the fat storage, because of their lipid composition. However, in recent years, some new and totally unexpected roles have been discovered for them: (i) they are active sites for synthesis and storage of inflammatory mediators, and (ii) they are key players in cancer cells and tissues, especially in cancer stem cells. In this review, we summarize the main concepts related to the lipid droplet structure and function and their involvement in inflammatory and cancer processes