Influence of a Single Grain Boundary on Domain Wall Motion in Ferroelectrics

Epitaxial tetragonal 425 and 611 nm thick Pb(ZrTi)O (PZT) films are deposited by pulsed laser deposition on SrRuO-coated (100) SrTiO 24° tilt angle bicrystal substrates to create a single PZT grain boundary with a well-defined orientation. On either side of the bicrystal boundary, the films show square hysteresis loops and have dielectric permittivities of 456 and 576, with loss tangents of 0.010 and 0.015, respectively. Using piezoresponse force microscopy (PFM), a decrease in the nonlinear piezoelectric response is observed in the vicinity (720-820 nm) of the grain boundary. This region represents the width over which the extrinsic contributions to the piezoelectric response (e.g., those associated with the domain density/configuration and/or the domain wall mobility) are influenced by the presence of the grain boundary. Transmission electron microscope (TEM) images collected near and far from the grain boundary indicate a strong preference for (101)/(1-01) type domain walls at the grain boundary, whereas (011)/(01-1) and (101)/(1-01) are observed away from this region. It is proposed that the elastic strain field at the grain boundary interacts with the ferro-electric/elastic domain structure, stabilizing (101)/(1-01) rather than (011)/(01-1) type domain walls, which inhibits domain wall motion under applied field and decreases non-linearity. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Motion Management for Radical Radiotherapy in Non-small Cell Lung Cancer

Intrafraction tumour motion is an issue that is of increased interest in the era of image-guided radiotherapy. It is particularly relevant for non-small cell lung cancer, for which a number of recent developments are in use to aid with motion management in the delivery of radical radiotherapy. The ability to deliver hypofractionated ablative doses, such as in stereotactic radiotherapy, has been aided by improvements in the ability to analyse tumour motion and amend treatment delivery. In addition, accounting for tumour motion can enable dose escalation to occur by reducing the normal tissue being irradiated by virtue of a reduction in target volumes. Motion management for lung tumours incorporates five key components: imaging, breath-hold techniques, abdominal compression, respiratory tracking and respiratory gating. These will be described, together with the relevant benefits and associated complexities. Many studies have described improved dosimetric coverage and reduced normal tissue complication probability rates when using motion management techniques. Despite the widespread uptake of many of these techniques, there is a paucity of literature reporting improved outcome in overall survival and local control for patients whenever motion management techniques are used. This overview will review the extent of lung tumour motion, ways in which motion is detected and summarise the key methods used in motion management.

Interferometer for Co-operating Target Motion Detection

A correlation interferometer working with a cooperation target operating at 2.2GHz center frequency is presented. This simplified interferometer presented here uses a
lock-in amplifier to significantly increase system sensitivity when used in conjunction with a co-operating target signaling using amplitude modulation. The system is verified by detecting the angular velocity of passing tagged target. Experimental results show detectable range up over 110 meters in a multipath environment using a 10dBm EIRP tag.

Adaptive Fusion Of Particle Filtering And Spatio-Temporal Motion Energy For Human Tracking

Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.

Self-Feedback Motion Control for Cable-Driven Parallel Manipulators

This article proposes a closed-loop control scheme based on joint-angle feedback for cable-driven parallel manipulators (CDPMs), which is able to overcome various difficulties resulting from the flexible nature of the driven cables to achieve higher control accuracy. By introducing a unique structure design that accommodates built-in encoders in passive joints, the seven degrees of freedom (7-DOF) CDPM can obtain joint angle values without external sensing devices, and it is used for feedback control together with a proper closed-loop control algorithm. The control algorithm has been derived from the time differential of the kinematic formulation, which relates the joint angular velocities to the time derivative of cable lengths. In addition, the Lyapunov stability theory and Monte Carlo method have been used to mathematically verify the self-feedback control law that has tolerance for parameter errors. With the aid of co-simulation technique, the self-feedback closed-loop control is applied on a 7-DOF CDPM and it shows higher motion accuracy than the one with an open-loop control. The trajectory tracking experiment on the motion control of the 7-DOF CDPM demonstrated a good performance of the self-feedback control method.

Improved APF strategies for dual-arm local motion planning

Manipulator motion planning is a classic problem in robotics, with a number of complete solutions available for their motion in controlled (industrial) environments. Owing to recent technological advances in the field of robotics, there has been a significant development of more complex robots with high-fidelity sensors and more computational power. One such example has been a rise in the production of humanoid robots equipped with dual-arm manipulators which require complex motion planning algorithms. Also, the technological advances have resulted in a shift from using manipulators in strictly controlled environments, to investigating the deployment of manipulators in dynamic or unknown environments. As a result, a greater emphasis has been put on the development of local motion planners, which can provide real-time solutions to these problems. Artificial Potential Fields (APFs) is one such popular local motion planning technique, which can be applied to manipulator motion planning, however, the basic algorithm is severely prone to local minima problems. Here, two modified APF-based strategies for solving the dual-arm motion planning task in unknown environments are proposed. Both techniques make use of configuration sampling and subgoal selection to assist the APFs in avoiding these local minima scenarios. Extensive simulation results are presented to validate the efficacy of the proposed methodology.

Significance Driven Computation: A Voltage-Scalable, Variation-Aware, Quality-Tuning Motion Estimator

In this paper we present a design methodology for algorithm/architecture co-design of a voltage-scalable, process variation aware motion estimator based on significance driven computation. The fundamental premise of our approach lies in the fact that all computations are not equally significant in shaping the output response of video systems. We use a statistical technique to intelligently identify these significant/not-so-significant computations at the algorithmic level and subsequently change the underlying architecture such that the significant computations are computed in an error free manner under voltage over-scaling. Furthermore, our design includes an adaptive quality compensation (AQC) block which "tunes" the algorithm and architecture depending on the magnitude of voltage over-scaling and severity of process variations. Simulation results show average power savings of similar to 33% for the proposed architecture when compared to conventional implementation in the 90 nm CMOS technology. The maximum output quality loss in terms of Peak Signal to Noise Ratio (PSNR) was similar to 1 dB without incurring any throughput penalty.

The influence of water motion on the growth rate of the kelp Laminaria hyperborea

The kelp Laminaria hyperborea is a dominant component of the subtidal nearshore ecosystem and is subjected to a heterogeneous wave and current climate. Water motion is known to influence physiological processes in macroalgae such as photosynthesis and nutrient uptake attributed to mass-transfer limitation. The study attempts to establish the effect of water motion on the growth rates of blades and elongation rates of the stipes of L. hyperborea at adjacent wave-exposed and wave-sheltered locations over a 12month period from field observations. The observations were supported by detailed physical and chemical measurements (light, temperature, seawater nutrient concentrations and hydrodynamics) and of tissue carbon and nitrogen concentrations together with δ¹³carbon. Despite a 30% difference in the root mean square of the velocity (Vel_rms) between the two survey locations, there was no evidence to suggest that water motion had any direct influence on the growth rates of either the blades or elongation of stipes of L. hyperborea. No significant differences were observed between either environmental or plant physiological variables between the sheltered and exposed locations. Using an integral velocity parameter (Vel_rms) the present study also highlighted the importance of the tidally induced current component of water flow in the subtidal zone. 

Laughter Type Recognition from Whole Body Motion

Despite the importance of laughter in social interactions it remains little studied in affective computing. Respiratory, auditory, and facial laughter signals have been investigated but laughter-related body movements have received almost no attention. The aim of this study is twofold: first an investigation into observers' perception of laughter states (hilarious, social, awkward, fake, and non-laughter) based on body movements alone, through their categorization of avatars animated with natural and acted motion capture data. Significant differences in torso and limb movements were found between animations perceived as containing laughter and those perceived as nonlaughter. Hilarious laughter also differed from social laughter in the amount of bending of the spine, the amount of shoulder rotation and the amount of hand movement. The body movement features indicative of laughter differed between sitting and standing avatar postures. Based on the positive findings in this perceptual study, the second aim is to investigate the possibility of automatically predicting the distributions of observer's ratings for the laughter states. The findings show that the automated laughter recognition rates approach human rating levels, with the Random Forest method yielding the best performance.