Great enhancement of mechanical features in PLA based composites containing aligned few layer graphene (FLG), the effect of FLG loading,size, and dispersion on mechanical and thermal properties

Four series of polylactide (PLA) based composite films containing horizontally aligned few layer graphene (FLG) flakes of high aspect ratio and adsorbed albumin are prepared. The mechanical and thermal properties varies with percentage, dispersion degree and size of FLG flakes. Great improvement up to 290% and 360% of tensile modulus and strength respectively were obtained for the composite containing high lateral size of FLG at 0.17% wt, and up to 60% and 80% for the composite with very well dispersed 0.02% wt FLG. The composites of PLA and PEG-PLLA containing very well dispersed FLG flakes at 0.07% wt are ductile showing enhancement of elongation at break up to respectively 80% and 88%. Relatively high electrical conductivity, 5 × 10⁻³ S/cm, is measured for PLA film charged with 3% of FLG.     

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.     

非整数阶系统的频率辨识

使用频响数据对非整数阶系统作频域模拟和辨识.首先,定义了非整数阶微分器的频率特性,进而给出了非整数阶系统的余奎斯特曲线的绘制方法.然后,运用方程式误差的辅助变量法,根据实部和虚部频率数据进行非整数阶系统的频率辨识.最后,通过两个数字仿真来验证这种辨识方法.     

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.     

Motion of points and lines in the uncalibrated case

In the present paper we address the problem of computing structure and motion, given a set point and/or line correspondences, in a monocular image sequence, when the camera is not calibrated.Considering point correspondences first, we analyse how to parameterize the retinal correspondences, in function of the chosen geometry: Euclidean, affine or projective geometry. The simplest of these parameterizations is called the FQs-representation and is a composite projective representation. The main result is that considering N+1 views in such a monocular image sequence, the retinal correspondences are parameterized by 11 N–4 parameters in the general projective case. Moreover, 3 other parameters are required to work in the affine case and 5 additional parameters in the Euclidean case. These 8 parameters are calibration parameters and must be calculated considering at least 8 external informations or constraints. The method being constructive, all these representations are made explicit.Then, considering line correspondences, we show how the the same parameterizations can be used when we analyse the motion of lines, in the uncalibrated case. The case of three views is extensively studied and a geometrical interpretation is proposed, introducing the notion of trifocal geometry which generalizes the well known epipolar geometry. It is also discussed how to introduce line correspondences, in a framework based on point correspondences, using the same equations.Finally, considering the F Qs-representation, one implementation is proposed as a motion module, taking retinal correspondences as input, and providing and estimation of the 11 N–4 retinal motion parameters. As discussed in this paper, this module can also estimate the 3D depth of the points up to an affine and projective transformation, defined by the 8 parameters identified in the first section. Experimental results are provided.     

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.