Tribological behavior of NiTi alloy against 52100 steel and WC at elevated temperatures

The dry tribological behavior of a Ti–50.3 at.% Ni alloy at temperatures of 25 °C, 50 °C and 200 °C was studied. The wear tests were performed on a high temperature pin-on-disk tribometer using 52100 steel and tungsten carbide pins. The worn surfaces of the NiTi alloy were examined by scanning electron microscope. The results showed that in the wear tests involving steel pins, the wear rate of the NiTi decreased as the wear testing temperature was increased. However, for the NiTi/WC contact, a reverse trend was observed. There was also a large decrease in the coefficient of friction for the NiTi/steel contact with increasing wear testing temperature. The formation of compact tribological layers could be the main reason for the reduction of the wear rate and coefficient of friction of the NiTi/steel contact at higher wear testing temperatures.     

p＋-InP/n-InGaAs/n-InP双异质结结构的微波反射光电导衰减法表征及机理分析

采用微波反射光电导衰减法测量了P -InP/n-InGaAs/n-InP双异质结材料的非平衡载流子寿命分布,通过对非平衡载流子浓度在P n结中衰减过程的分析,建立了在此结构材料中微波反射光电导衰退法测试少子寿命与器件参数之间的联系,并且解释了寿命测试值随温度降低而减小的反常行为.     

An Ultrasensitive Silicon Photonic Ion Sensor Enabled by 2D Plasmonic Molybdenum Oxide

Silicon photonics has demonstrated great potential in ultrasensitive biochemical sensing. However, it is challenging for such sensors to detect small ions which are also of great importance in many biochemical processes. A silicon photonic ion sensor enabled by an ionic dopant–driven plasmonic material is introduced here. The sensor consists of a microring resonator (MRR) coupled with a 2D restacked layer of near‐infrared plasmonic molybdenum oxide. When the 2D plasmonic layer interacts with ions from the environment, a strong change in the refractive index results in a shift in the MRR resonance wavelength and simultaneously the alteration of plasmonic absorption leads to the modulation of MRR transmission power, hence generating dual sensing outputs which is unique to other optical ion sensors. Proof‐of‐concept via a pH sensing model is demonstrated, showing up to 7 orders improvement in sensitivity per unit area across the range from 1 to 13 compared to those of other optical pH sensors. This platform offers the unique potential for ultrasensitive and robust measurement of changes in ionic environment, generating new modalities for on‐chip chemical sensors in the micro/nanoscale.     

深度卷积神经网络在多工况下刀具磨损状态监测中的应用

为了解决复杂多工况下刀具磨损状态的监测问题,提出一种基于深度学习的刀具磨损状态监测方法,并构建敏感特征值提取函数.基于刀具磨损数据集,建立多种工况下刀具磨损状态的监测模型,进行多工况下刀具磨损状态监测研究.研究结果表明:当敏感值界限设置为0.3时,从声发射、振动和电流信号的特征值中可以提取出56个敏感特征值;以均方根误...     

Genetic diversity of the human pathogen Vibrio vulnificus: a new phylogroup

The biotype 3 group of the human pathogen Vibrio vulnificus emerged in Israel probably as a result of genome hybridization of two bacterial populations. We performed a genomic and phylogenetic study of V. vulnificus strains isolated from the environmental niche from which this group emerged — fish aquaculture in Israel. The genetic relationships and evolutionary aspects of 188 environmental and clinical isolates of the bacterium were studied by genomic typing. Genetic relations were determined based on variation at 12 variable number tandem repeat (VNTR, also termed SSR) loci. Analysis revealed a new cluster, in addition to the main groups of biotype 1& 2 and biotype 3. Similar grouping results were obtained with three different statistical approaches. Isolates forming this new cluster presented unclear biochemical profile nevertheless were not identified as biotype 1 or biotype 3. Further examination of representative strains by multilocus sequence typing (MLST) of 10 housekeeping genes and 5 conserved hypothetical genes supported the identification of this as yet undiscovered phylogroup (phenotypically diverse), termed clade A herein. This new clonal subgroup includes environmental as well as clinical isolates. The results highlight the fish aquaculture environment, and possibly man-made ecological niches as a whole, as a source for the emergence of new pathogenic strains.     

Fabrication and characterization of an AlGaN/PZT detector

Design,fabrication and characterization of a novel two-color detector for ultraviolet and infrared applications are reported.The detector has a simple multilayer structure composed of n-Al_(0.3)Ga_(0.7)N/i-GaN/p-GaN /SiO_2/LaNiO_3/PZT/Pt fabricated on a sapphire substrate.Ultraviolet and infrared properties are measured.For the ultraviolet region,a flat band spectral response is achieved in the 302-363 nm band.The detector displays an unbiased responsivity of 0.064 AAV at 355 nm.The current-voltage curve...     

Piecewise linear spine for speed–energy efficiency trade-off in quadruped robots

We compare the effects of linear and piecewise linear compliant spines on locomotion performance of quadruped robots in terms of energy efficiency and locomotion speed through a set of simulations and experiments. We first present a simple locomotion system that behaviorally resembles a bounding quadruped with flexible spine. Then, we show that robots with linear compliant spines have higher locomotion speed and lower cost of transportation in comparison with those with rigid spine. However, in linear case, optimal speed and minimum cost of transportation are attained at very different spine compliance values. Moreover, it is verified that fast and energy efficient locomotion can be achieved together when the spine flexibility is piecewise linear. Furthermore, it is shown that the robot with piecewise linear spine is more robust against changes in the load it carries. Superiority of piecewise linear spines over linear and rigid ones is additionally confirmed by simulating a quadruped robot in Webots and experiments on a crawling two-parts robot with flexible connection.     

Attention control learning in the decision space using state estimation

The main goal of this paper is modelling attention while using it in efficient path planning of mobile robots. The key challenge in concurrently aiming these two goals is how to make an optimal, or near-optimal, decision in spite of time and processing power limitations, which inherently exist in a typical multi-sensor real-world robotic application. To efficiently recognise the environment under these two limitations, attention of an intelligent agent is controlled by employing the reinforcement learning framework. We propose an estimation method using estimated mixture-of-experts task and attention learning in perceptual space. An agent learns how to employ its sensory resources, and when to stop observing, by estimating its perceptual space. In this paper, static estimation of the state space in a learning task problem, which is examined in the Webots^TM simulator, is performed. Simulation results show that a robot learns how to achieve an optimal policy with a controlled cost by estimating the state space instead of continually updating sensory information.