Parabolic Flights @ Home

We developed an unmanned air vehicle (UAV) suitable for small parabolic-flight experiments. The flight speed of 100 m s^− 1 is sufficient for zero-gravity parabolas of 16 s duration. The flight path’s length of slightly more than 1 km and 400 m difference in altitude is suitable for ground controlled or supervised flights. Since this fits within the limits set for model aircraft, no additional clearance is required for operation. Our UAV provides a cost-effective platform readily available for low-g experiments, which can be performed locally without major preparation. A payload with a size of up to 0.9 ×0.3 ×0.3 m³ and a mass of ∼5 kg can be exposed to 0 g ₀–5 g ₀, with g ₀ being the gravitational acceleration of the Earth. Flight-duration depends on the desired acceleration level, e.g. 17 s at 0.17 g ₀ (lunar surface level) or 21 s at 0.38 g ₀ (Martian surface level). The aircraft has a mass of 25 kg (including payload) and a wingspan of 2 m. It is powered by a jet engine with an exhaust speed of 450 m s^− 1 providing a thrust of 180 N. The parabolic-flight curves are automated by exploiting the advantages of sophisticated micro-electronics to minimize acceleration errors.     

Thermal stability of CeO<Subscript>2</Subscript>/ZrO<Subscript>2</Subscript> multilayer thin films prepared by pulsed laser deposition

Multilayers of CeO₂/ZrO₂ thin films were deposited on Si (100) substrates using pulsed laser deposition at an optimized oxygen partial pressure of 3×10⁻² mbar and at room temperature. The CeO₂ layer thickness was 10 nm, while the ZrO₂ layer thickness was varied as 10, 20 and 30 nm. CeO₂ and ZrO₂ layers were deposited alternately to obtain 25 bilayers. High temperature x-ray diffraction (HTXRD) results showed that the multilayer films had cubic ceria and tetragonal ZrO₂. Thermal expansion coefficients were calculated for CeO₂ and t-ZrO₂ and found to increase with the decrease of ZrO₂ layer thickness. The cross sectional transmission electron microscopy (XTEM) of CeO₂/ZrO₂ multilayer also indicated that ceria was found to be in cubic phase while zirconia contained predominantly tetragonal phase along with cubic phase in thermally annealed specimen.     

Statistical analysis and modeling of the temperature-dependent sleep behavior of drosophila

The sleep behavior of drosophila is analyzed under different temperatures. The activity per minute of the flies is recorded automatically. Sleep for a fruit fly is defined as the periods without any activity and longer than 5 minutes. Several parameters such as total sleep time, circadian sleep profile, quality of sleep are analyzed. The sleep behaviors are significantly different for flies at different temperature. Interestingly, the durations of daytime sleep periods show a common scale-free power law distribution. We propose a stochastic model to simulate the activities of the population of neurons which regulate the dynamics of sleep–wake process to explain the distribution of daytime sleep.     

Effects of High Magnetic Fields on the Distribution and Alignment of Primary Phases in an Al-12Si-11.8Mg-6.5Ti Alloy

Al-12Si-11.8Mg-6.5Ti alloy samples were solidified in high magnetic fields with various magnetic field gradients. The effects of high magnetic fields on the distribution and alignment of primary phases in the alloys were investigated. It was found that the uniform magnetic field could improve the homogeneity of the primary Mg₂Si, whereas the magnetic field gradient caused the two-layer core grains ((Al,Si)₃Ti and Ti₅Si₄) to segregate at certain regions of the samples depending on the magnetic field gradient direction. The primary (Al,Si)₃Ti strips were oriented with their c axes perpendicular to the magnetic field direction and aligned with their long axes along the magnetic field direction. The changes in the distribution of the primary Mg₂Si and two-layer core grains were caused by the Lorentz force and magnetic force, which could counteract and cause the migration of these phases, respectively. The alignment of the primary (Al,Si)₃Ti could be attributed to the combination of the magnetic orientation and solute redistribution.     

On Homogeneous Nucleation of Dislocation Loops in Nanocrystalline Materials

In this article, we readdress the question of homogeneous nucleation of dislocation loops in the context of nanocrystalline materials. In this case, the commonly adopted assumption of an infinite medium is no longer valid, and image forces on dislocations must be accounted for in the analysis. An additional energy term associated with the presence of finite boundaries may act to promote homogeneous nucleation and growth of dislocation loops. Based on a simplified consideration of a circular dislocation loop in a spherical nanoparticle or nanosized grain in a polycrystal, energy calculations are carried out to estimate the activation energy for homogeneous nucleation of a dislocation loop in such a system. Two different cases are considered: (1) a single nanoparticle and (2) a grain in a polycrystalline nanomaterial. Based on simulations for aluminum, it is shown that this mechanism may be plausible in both cases, albeit only for small particles and grains in the nanometer range.     

Optimality and convergence of adaptive optimal control by reinforcement synthesis

Adaptive Optimal Control (AOC) by reinforcement synthesis is proposed to facilitate the application of optimal control theory in feedback controls. Reinforcement synthesis uses the critic–actor architecture of reinforcement learning to carry out sequential optimization. Optimality conditions for AOC are formulated using the discrete minimum principle. A proof of the convergence conditions for the reinforcement synthesis algorithm is presented. As the final time extends to infinity, the reinforcement synthesis algorithm is equivalent to the Dual Heuristic dynamic Programming (DHP) algorithm, a version of approximate dynamic programming. Thus, formulating DHP with the AOC approach has rigorous proofs of optimality and convergence. The efficacy of AOC by reinforcement synthesis is demonstrated by solving a linear quadratic regulator problem.     

Opacity of discrete event systems and its applications

In this paper, we investigate opacity of discrete event systems. We define two types of opacities: strong opacity and weak opacity. Given a general observation mapping, a language is strongly opaque if all strings in the language are confused with some strings in another language and it is weakly opaque if some strings in the language are confused with some strings in another language. We show that security and privacy of computer systems and communication protocols can be investigated in terms of opacity. In particular, two important properties in security and privacy, namely anonymity and secrecy, can be studied as special cases of opacity. We also show that by properly specifying the languages and the observation mapping, three important properties of discrete event systems, namely observability, diagnosability, and detectability, can all be reformulated as opacity. Thus, opacity has a wide range of applications. Also in this paper we provide algorithms for checking strong opacity and weak opacity for systems described by regular languages and having a generalized projection as the observation mapping.     

Degenerate problems of optimal control. II

The paper is the second part of the review of the results obtained by the special theory of the degenerate problems of optimal control and its applications, including the newest ones. Consideration was given to the methods based on the rearrangement of the degenerate problems in the smaller-order regular derivative problems, the main types of solutions of the derivative problems, and the issues of their realization as the generalized solutions of the original problems. The generalized conditions for their optimality were derived. Examples, both methodological and applied, were presented to demonstrate the efficiency of these methods.     

基于深度学习的采摘机器人目标识别定位算法

为了提升采摘机器人对果实的识别准确率以及定位定精度,提出一种基于深度学习Faster-RCNN框架的采摘机器人目标识别和定位算法.首先采用卷积神经网络VGG16模型提取输入图像的特性信息,并利用区域提议网络RPN生成含有目标的候选框,通过引入自适应候选框数的方法有效提升了算法性能,然后利用多任务损失函数对目标进行分类识...