Mechanisms of nanostructure and metastable phase formations in the surface melted layers of a HCPEB-treated D2 steel

This work investigates the mechanism of surface modification associated with the high-current pulsed electron beam (HCPEB) treatment of a D2 steel with increasing numbers of pulses. The surface layers were melted and resolidified but the treated surfaces showed very different features. This variation is essentially due to the different levels of homogeneity and carbide dissolution. It is demonstrated that the presence of carbides served as nucleation sites for the surface eruption phenomenon that creates craters on the surface. After a sufficient number of pulses, most of the carbides in the surface layer were dissolved and an almost crater-free homogeneous melted layer consisting of a very stable nano-austenite structure was formed. The HCPEB technique is thus demonstrated to be a versatile technique for surface microstructure modification involving, in the case of steels, austenite stabilization and ultrafine grain formation.     

Nonparametric Traversability Estimation in Partially Occluded and Deformable Terrain

Terrain traversability estimation is a fundamental requirement to ensure the safety of autonomous planetary rovers and their ability to conduct long‐term missions. This paper addresses two fundamental challenges for terrain traversability estimation techniques. First, representations of terrain data, which are typically built by the rover's onboard exteroceptive sensors, are often incomplete due to occlusions and sensor limitations. Second, during terrain traversal, the rover‐terrain interaction can cause terrain deformation, which may significantly alter the difficulty of traversal. We propose a novel approach built on Gaussian process (GP) regression to learn, and consequently to predict, the rover's attitude and chassis configuration on unstructured terrain using terrain geometry information only. First, given incomplete terrain data, we make an initial prediction under the assumption that the terrain is rigid, using a learnt kernel function. Then, we refine this initial estimate to account for the effects of potential terrain deformation, using a near‐to‐far learning approach based on multitask GP regression. We present an extensive experimental validation of the proposed approach on terrain that is mostly rocky and whose geometry changes as a result of loads from rover traversals. This demonstrates the ability of the proposed approach to accurately predict the rover's attitude and configuration in partially occluded and deformable terrain.     

Flow profile measurement in microchannel using the optical feedback interferometry sensing technique

The need to accurately measure flow profiles in microfluidic channels is well recognised. In this work, we present a new optical feedback interferometry (OFI) flow sensor that accurately measures local velocity in fluids and enables reconstruction of a velocity profile inside a microchannel. OFI is a self-aligned interferometric technique that uses the laser as both the transmitter and the receiver thus offering high sensitivity, fast response, and a simple and compact optical design. The system described here is based on a commercial semiconductor laser and has been designed to achieve a micrometer-range spatial resolution. The sensor performance was validated by reconstructing the velocity profile inside a circular cross-section flow-channel with 320  $\upmu $ m internal diameter, with a relative error smaller than 1.8 %. The local flow velocity is directly measured, thus avoiding the need for model based profile calculation and uncertainties inherent to this approach. The system was validated by successfully extracting the flow profiles in both Newtonian and shear-thinning liquids.     

High-Resolution and Stable Ruddlesden–Popper Quasi-2D Perovskite Flexible Photodetectors Arrays for Potential Applications as Optical Image Sensor

The development of an efficient fabrication route to achieve high-resolution perovskite pixel array is key for large-scale flexible image sensor devices. Herein, a high-resolution and stable 10 × 10 flexible PDs array based on formamidinium(FA⁺) and phenylmethylammonium (PMA⁺) quasi-2D (PMA)₂FAPb₂I₇ (n = 2) perovskite is demonstrated by developing SiO₂-assisted hydrophobic and hydrophilic treatment process on polyethylene terephthalate substrate. By introducing Au nanoparticles (Au NPs),  the perovskite film quality is improved and grain boundaries are reduced. The mechanism by which Au NPs upgrade the photoelectric quality of perovskite is mainly revealed by glow discharge-optical emission spectroscopy (GD-OES) and grazing-incidence wide-angle X-ray scattering (GIWAXS). To further improve the photoelectric performance of the devices, a post-treatment strategy with formamidinium chloride (FACl) is used . The optimized flexible PDs arrays show excellent optoelectronic properties with a high responsivity of 4.7 A W⁻¹, a detectivity of 6.3 × 10¹² Jones, and a broad spectral sensitivity. The device also exhibits excellent electrical stability even under severe bending and excellent flexural strength, as well as excellent environmental stability. Finally, the integrated flexible PDs arrays are used as sensor pixels in an imaging system to obtain high-resolution imaging patterns, demonstrating the imaging capability of the PDs arrays.     

Learning state machine-based string edit kernels

During the past few years, several works have been done to derive string kernels from probability distributions. For instance, the Fisher kernel uses a generative model M (e.g. a hidden Markov model) and compares two strings according to how they are generated by M. On the other hand, the marginalized kernels allow the computation of the joint similarity between two instances by summing conditional probabilities. In this paper, we adapt this approach to edit distance-based conditional distributions and we present a way to learn a new string edit kernel. We show that the practical computation of such a kernel between two strings x and x^′ built from an alphabet Σ requires (i) to learn edit probabilities in the form of the parameters of a stochastic state machine and (ii) to calculate an infinite sum over Σ^* by resorting to the intersection of probabilistic automata as done for rational kernels. We show on a handwritten character recognition task that our new kernel outperforms not only the state of the art string kernels and string edit kernels but also the standard edit distance used by a neighborhood-based classifier.     

Action Recognition Using a Bio-Inspired Feedforward Spiking Network

We propose a bio-inspired feedforward spiking network modeling two brain areas dedicated to motion (V1 and MT), and we show how the spiking output can be exploited in a computer vision application: action recognition. In order to analyze spike trains, we consider two characteristics of the neural code: mean firing rate of each neuron and synchrony between neurons. Interestingly, we show that they carry some relevant information for the action recognition application. We compare our results to Jhuang et al. (Proceedings of the 11th international conference on computer vision, pp. 1–8, 2007) on the Weizmann database. As a conclusion, we are convinced that spiking networks represent a powerful alternative framework for real vision applications that will benefit from recent advances in computational neuroscience.     

Towards a continuous microfluidic rheometer

In a previous paper we presented a way to measure the rheological properties of complex fluids on a microfluidic chip (Guillot et al., Langmuir 22:6438, 2006). The principle of our method is to use parallel flows between two immiscible fluids as a pressure sensor. In fact, in a such flow, both fluids flow side by side and the size occupied by each fluid stream depends only on both flow rates and on both viscosities. We use this property to measure the viscosity of one fluid knowing the viscosity of the other one, both flow rates and the relative size of both streams in a cross-section. We showed that using a less viscous fluid as a reference fluid allows to define a mean shear rate with a low standard deviation in the other fluid. This method allows us to measure the flow curve of a fluid with less than 250 μL of fluid. In this paper we implement this principle in a fully automated set up which controls the flow rate, analyzes the picture and calculates the mean shear rate and the viscosity of the studied fluid. We present results obtained for Newtonian fluids and complex fluids using this set up and we compare our data with cone and plate rheometer measurements. By adding a mixing stage in the fluidic network we show how this set up can be used to characterize in a continuous way the evolution of the rheological properties as a function of the formulation composition. We illustrate this by measuring the rheological curve of four formulations of polyethylene oxide solution with only 1.3 mL of concentrated polyethylene oxide solution. This method could be very useful in screening processes where the viscosity range and the behavior of the fluid to an applied stress must be evaluated.     

Comparative morphology of leaf epidermis in eight populations of Atlas Pistachio (Pistacia atlantica Desf., Anacardiaceae)

A comparative analysis was undertaken to conduct a micromorphological study of Pistacia atlantica leaves by comparing different populations grown under different climatic conditions. Leaf epidermis of eight wild populations was investigated under scanning electron microscope. Micromorphological characteristics (epidermis ornament, stomata type, waxes as well as trichomes) of the adaxial and abaxial leaf surfaces were examined. The epidermis ornament varied among populations and leaf surface, the abaxial leaf surface is reticulate with a striate surface. Messaad site shows a smooth uneven surface. The adaxial leaf surface is smooth but several ornamentations can be seen. The leaflet is amphistomatic; the stomata appeared to be slightly sunken. A variety of stomatal types were recorded; actinocytic and anomocytic types are the most frequent. The indumentum consisted of glandular and nonglandular trichomes. Unicellular glandular trichomes are recorded for P. atlantica leaves in this study. Their density is higher in Oued safene site, located at the highest altitude in comparison with the other populations. The wax occurred in all the sites and its pattern varied according to the populations studied, particularly between Berriane and Messaad. The morphological variability exhibited by the eight populations of P. atlantica may be interpreted as relevant to the ecological plasticity and the physiological mechanisms involved are discussed in this report.