Growth and optical properties of In x Ga1−x P nanowires synthesized by selective-area epitaxy

Ternary Ⅲ-Ⅴ nanowires (NWs) cover a wide range of wavelengths in the solar spectrum and would greatly benefit from being synthesized as position-controlled arrays for improved vertical yield,reprodudbility,and tunable optical absorption.Here,we report on successful selective-area epitaxy of metal-particle-free vertical InxGa1-xP NW arrays using metal-organic vapor phase epitaxy and detail their optical properties.A systematic growth study establishes the range of suitable growth parameters to obtain uniform NW growth over a large array.The optical properties of the NWs were characterized by room-temperature cathodoluminescence spectroscopy.Tunability of the emission wavelength from 870 nm to approximately 800 nm was achieved.Transmission electron microscopy and energy dispersive X-ray measurements performed on crosssection samples revealed a pure wurtzite crystal structure with very few stacking faults and a slight composition gradient along the NW growth axis.     

Switched reluctance motor modeling with on-line parameteridentification

A nonlinear model with on-line parameter estimation using recursive identification for switched reluctance motors (SRMs) is presented. The model is robust toward parameter variations in the motor or any system disturbances. The parameters of the model are adjusted to account for errors in rotor position, which allows the use of crude inexpensive position sensors. The proposed modeling approach allows self-tuning of SRMs in a production unit. The simulations and experiments performed to test the model demonstrate the accuracy of estimation of the model     

Identification of pole-like structures from mobile lidar data of complex road environment

Pole-like structures (PLSs) located in road environment are important roadway assets. They play a vital role in road safety inspection and road planning. The use of light detection and ranging (lidar) based mobile mapping technology for mapping of PLSs is an important area of research as it holds the potential for automation. Point cloud data of rural, peri-urban, and urban road environment are used in this study, which pose special challenge in view of the complexity of terrain, unlike well-planned roads, which have been the subject of interest in existing literature for identification of PLSs. A new five-step method is proposed in this article. The first two steps, i.e. ground filtering and voxelization of filtered non-ground points, are used for data size reduction. Next three steps are used to extract PLSs from reduced data. The proposed method was tested on point cloud data of three test sites having different levels of complexities. PLSs including partially occluded pole, tilted pole, pole situated very close to other objects, and vertical pole attached to tilted pole were accurately identified. Average correctness and completeness, respectively of 92.6% and 94.9%, were achieved in three different complex test sites, i.e. urban, peri-urban, and rural sites, respectively. Computation complexity shows that our proposed method delivers fast and computationally efficient solution for identifying the PLSs from volumetric mobile lidar point cloud. Impact of PLSs on road safety and road planning is also addressed for these selected test sites.     

Reinforcement Learning Based Algorithms for Average Cost Markov Decision Processes

This article proposes several two-timescale simulation-based actor-critic algorithms for solution of infinite horizon Markov Decision Processes with finite state-space under the average cost criterion. Two of the algorithms are for the compact (non-discrete) action setting while the rest are for finite-action spaces. On the slower timescale, all the algorithms perform a gradient search over corresponding policy spaces using two different Simultaneous Perturbation Stochastic Approximation (SPSA) gradient estimates. On the faster timescale, the differential cost function corresponding to a given stationary policy is updated and an additional averaging is performed for enhanced performance. A proof of convergence to a locally optimal policy is presented. Next, we discuss a memory efficient implementation that uses a feature-based representation of the state-space and performs TD(0) learning along the faster timescale. The TD(0) algorithm does not follow an on-line sampling of states but is observed to do well on our setting. Numerical experiments on a problem of rate based flow control are presented using the proposed algorithms. We consider here the model of a single bottleneck node in the continuous time queueing framework. We show performance comparisons of our algorithms with the two-timescale actor-critic algorithms of Konda and Borkar (1999) and Bhatnagar and Kumar (2004). Our algorithms exhibit more than an order of magnitude better performance over those of Konda and Borkar (1999).

Modelling the activity of I in the primary coolant of a CANDU reactor

A mathematical treatment has been developed to describe the activity levels of ¹²⁹I as a function of time in the primary heat transport system during constant power operation and for a reactor shutdown situation. The model accounts for a release of fission-product iodine from defective fuel rods and tramp uranium contamination on in-core surfaces. The physical transport constants of the model are derived from a coolant activity analysis of the short-lived radioiodine species. An estimate of 3×10⁻⁹ has been determined for the coolant activity ratio of ¹²⁹I/¹³¹I in a CANDU Nuclear Generating Station (NGS), which is in reasonable agreement with that observed in the primary coolant and for plant test resin columns from pressurized and boiling water reactor plants. The model has been further applied to a CANDU NGS, by fitting it to the observed short-lived iodine and long-lived cesium data, to yield a coolant activity ratio of ∼2×10⁻⁸ for ¹²⁹I/¹³⁷Cs. This ratio can be used to estimate the levels of ¹²⁹I in reactor waste based on a measurement of the activity of ¹³⁷Cs.     

Decoding Speech Prosody: Do Music Lessons Help?

Three experiments revealed that music lessons promote sensitivity to emotions conveyed by speech prosody. After hearing semantically neutral utterances spoken with emotional (i.e., happy, sad, fearful, or angry) prosody, or tone sequences that mimicked the utterances' prosody, participants identified the emotion conveyed. In Experiment 1 (n=20), musically trained adults performed better than untrained adults. In Experiment 2 (n=56), musically trained adults outperformed untrained adults at identifying sadness, fear, or neutral emotion. In Experiment 3 (n=43), 6-year-olds were tested after being randomly assigned to 1 year of keyboard, vocal, drama, or no lessons. The keyboard group performed equivalently to the drama group and better than the no-lessons group at identifying anger or fear. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Failure Investigation of Boiler Water Wall Tubes of a Thermal Power Station

Failure investigation was carried out on boiler water wall tubes of a thermal power plant through visual inspection, chemical analysis, and metallurgical analysis. Failure was in the form of thin/micro cracks along the length of the tubes which were located at the girth welding joint of tubes. Experimental results revealed that the cracking was from inward to outward of the tube thickness. Discontinuities/cavities were observed in the welded region which might have occurred due to lack of fusion of base metal and the weld metal. Cracks were initiated from the sharp corner/crack tip of the cavities/discontinuities present at the welded region under the action of hoop/thermal stress existed during the operation. Nature of the crack propagation indicates the case of typical hydrogen-induced cracking. Moreover, the presence of the cavities/discontinuities reduced the cross-sectional area of tubes resulting increased stress intensity. Increased stress beyond the flow stress of the material assisted by hydrogen-induced effect resulted the cracking of the tubes. In order to mitigate the problem, proper welding of tubes joints should be carried out followed by proper inspection after weld. Secondly, hydrogen dissolution during welding should be prevented and treatment for its removal after welding should be carried out.     

Control of a robotic orthosis for gait rehabilitation

Robot assisted gait training may help in producing rapid improvements in functional gait parameters. This paper presents new experimental results with an intrinsically compliant robotic gait training orthosis. The newly developed robotic orthosis has 6 degrees of freedom (DOFs). A trajectory tracking controller based on the boundary layer augmented sliding control (BASMC) law was implemented to guide the subject’s limbs on physiological gait trajectories. The compliance of the robotic orthosis sagittal plane hip and knee joints was also controlled, independently of the trajectory tracking control. The robotic orthosis and the control scheme were evaluated on three neurologically intact subjects walking on a treadmill. A maximum trajectory tracking error of 10° was recorded at the hip and knee sagittal plane joints. The results showed that subjects can walk in the robotic orthosis with comfort and the BASMC law was able to guide the subject’s limbs on reference physiological trajectories.     

Copper substituted nickel ferrite nanoparticles anchored onto the graphene sheets as electrode materials for supercapacitors fabrication

Nickel ferrites with high theoretical capacitance value as compared to the other metal oxides have been applied as electrode material for energy storage devices i.e. batteries and supercapacitors. High tendency towards aggregation and less specific surface area make the metal oxides poor candidate for electrochemical applications. Therefore, the improvements in the electrochemical properties of nickel ferrites (NiFe₂O₄) are required. Here, we report the synthesis of graphene nano-sheets decorated with spherical copper substituted nickel ferrite nanoparticles for supercapacitors electrode fabrication. The copper substituted and unsubstituted NiFe₂O₄ nanoparticles were prepared via wet chemical co-precipitation route. Reduced graphene oxide (rGO) was prepared via well-known Hummer's method. After structural characterization of both ferrite (Ni_1-xCu_xFe₂O₄) nanoparticles and rGO, the ferrite particles were decorated onto the graphene sheets to obtain Ni_1-xCu_xFe₂O₄@rGO nanocomposites. The confirmation of preparation of these nanocomposites was confirmed by scanning electron microscopy (SEM). The electrochemical measurements of nanoparticles and their nanocomposites (Ni_0.9Cu_0.1Fe₂O₄@rGO) confirmed that the nanocomposites due to highly conductive nature and relatively high surface area showed better capacitive behavior as compared to bare nanoparticles. This enhanced electrochemical energy storage properties of nanocomposites were attributed to the graphene and also supported by electrical (I-V) measurements. The cyclic stability experiments results showed ~65% capacitance retention after 1000 cycles. However this retention was enhanced from 65% to 75% for the copper substituted nanoparticles (Ni_0.9Cu_0.1Fe₂O₄) and 65–85% for graphene based composites. All this data suggest that these nanoparticles and their composites can be utilized for supercapacitors electrodes fabrication.