Modification of the trapped field in bulk high-temperature superconductors as a result of the drilling of a pattern of artificial columnar holes

The trapped magnetic field is examined in bulk high-temperature superconductors that are artificially drilled along their c-axis. The influence of the hole pattern on the magnetization is studied and compared by means of numerical models and Hall probe mapping techniques. To this aim, we consider two bulk YBCO samples with a rectangular cross-section that are drilled each by six holes arranged either on a rectangular lattice (sample I) or on a centered rectangular lattice (sample II). For the numerical analysis, three different models are considered for calculating the trapped flux: (i), a two-dimensional (2D) Bean model neglecting demagnetizing effects and flux creep, (ii), a 2D finite-element model neglecting demagnetizing effects but incorporating magnetic relaxation in the form of an E-J power law, and, (iii), a 3D finite element analysis that takes into account both the finite height of the sample and flux creep effects. For the experimental analysis, the trapped magnetic flux density is measured above the sample surface by Hall probe mapping performed before and after the drilling process. The maximum trapped flux density in the drilled samples is found to be smaller than that in the plain samples. The smallest magnetization drop is found for sample II, with the centered rectangular lattice. This result is confirmed by the numerical models. In each sample, the relative drops that are calculated independently with the three different models are in good agreement. As observed experimentally, the magnetization drop calculated in the sample II is the smallest one and its relative value is comparable to the measured one. By contrast, the measured magnetization drop in sample (1) is much larger than that predicted by the simulations, most likely because of a change of the microstructure during the drilling process.

Beyond dataset bias: Multi-task unaligned shared knowledge transfer

Many visual datasets are traditionally used to analyze the performance of different learning techniques. The evaluation is usually done within each dataset, therefore it is questionable if such results are a reliable indicator of true generalization ability. We propose here an algorithm to exploit the existing data resources when learning on a new multiclass problem. Our main idea is to identify an image representation that decomposes orthogonally into two subspaces: a part specific to each dataset, and a part generic to, and therefore shared between, all the considered source sets. This allows us to use the generic representation as un-biased reference knowledge for a novel classification task. By casting the method in the multi-view setting, we also make it possible to use different features for different databases. We call the algorithm MUST, Multitask Unaligned Shared knowledge Transfer. Through extensive experiments on five public datasets, we show that MUST consistently improves the cross-datasets generalization performance. © 2013 Springer-Verlag.

Study by Hall probe mapping of the trapped flux modification produced by local heating in YBCO HTS bulks for different surface/volume ratios

The aim of this report is to compare the trapped field distribution under a local heating created at the sample edge for different sample morphologies. Hall probe mappings of the magnetic induction trapped in YBCO bulk samples maintained out of thermal equilibrium were performed on YBCO bulk single domains, YBCO single domains with regularly spaced hole arrays, and YBCO superconducting foams. The capability of heat draining was quantified by two criteria: the average induction decay and the size of the thermally affected zone caused by a local heating of the sample. Among the three investigated sample shapes, the drilled single domain displays a trapped induction which is weakly affected by the local heating while displaying a high trapped field. Finally, a simple numerical modelling of the heat flux spreading into a drilled sample is used to suggest some design rules about the hole configuration and their size. © 2005 IOP Publishing Ltd.

Dopamine and performance in a reinforcement learning task: evidence from Parkinson's disease.

The role dopamine plays in decision-making has important theoretical, empirical and clinical implications. Here, we examined its precise contribution by exploiting the lesion deficit model afforded by Parkinson's disease. We studied patients in a two-stage reinforcement learning task, while they were ON and OFF dopamine replacement medication. Contrary to expectation, we found that dopaminergic drug state (ON or OFF) did not impact learning. Instead, the critical factor was drug state during the performance phase, with patients ON medication choosing correctly significantly more frequently than those OFF medication. This effect was independent of drug state during initial learning and appears to reflect a facilitation of generalization for learnt information. This inference is bolstered by our observation that neural activity in nucleus accumbens and ventromedial prefrontal cortex, measured during simultaneously acquired functional magnetic resonance imaging, represented learnt stimulus values during performance. This effect was expressed solely during the ON state with activity in these regions correlating with better performance. Our data indicate that dopamine modulation of nucleus accumbens and ventromedial prefrontal cortex exerts a specific effect on choice behaviour distinct from pure learning. The findings are in keeping with the substantial other evidence that certain aspects of learning are unaffected by dopamine lesions or depletion, and that dopamine plays a key role in performance that may be distinct from its role in learning.

Dopamine and performance in a reinforcement learning task: Evidence from Parkinson's disease

The role dopamine plays in decision-making has important theoretical, empirical and clinical implications. Here, we examined its precise contribution by exploiting the lesion deficit model afforded by Parkinson's disease. We studied patients in a two-stage reinforcement learning task, while they were ON and OFF dopamine replacement medication. Contrary to expectation, we found that dopaminergic drug state (ON or OFF) did not impact learning. Instead, the critical factor was drug state during the performance phase, with patients ON medication choosing correctly significantly more frequently than those OFF medication. This effect was independent of drug state during initial learning and appears to reflect a facilitation of generalization for learnt information. This inference is bolstered by our observation that neural activity in nucleus accumbens and ventromedial prefrontal cortex, measured during simultaneously acquired functional magnetic resonance imaging, represented learnt stimulus values during performance. This effect was expressed solely during the ON state with activity in these regions correlating with better performance. Our data indicate that dopamine modulation of nucleus accumbens and ventromedial prefrontal cortex exerts a specific effect on choice behaviour distinct from pure learning. The findings are in keeping with the substantial other evidence that certain aspects of learning are unaffected by dopamine lesions or depletion, and that dopamine plays a key role in performance that may be distinct from its role in learning. © 2012 The Author.

The temporal evolution of feedback gains rapidly update to task demands.

Recent theoretical frameworks such as optimal feedback control suggest that feedback gains should modulate throughout a movement and be tuned to task demands. Here we measured the visuomotor feedback gain throughout the course of movements made to "near" or "far" targets in human subjects. The visuomotor gain showed a systematic modulation over the time course of the reach, with the gain peaking at the middle of the movement and dropping rapidly as the target is approached. This modulation depends primarily on the proportion of the movement remaining, rather than hand position, suggesting that the modulation is sensitive to task demands. Model-predictive control suggests that the gains should be continuously recomputed throughout a movement. To test this, we investigated whether feedback gains update when the task goal is altered during a movement, that is when the target of the reach jumped. We measured the visuomotor gain either simultaneously with the jump or 100 ms after the jump. The visuomotor gain nonspecifically reduced for all target jumps when measured synchronously with the jump. However, the visuomotor gain 100 ms later showed an appropriate modulation for the revised task goal by increasing for jumps that increased the distance to the target and reducing for jumps that decreased the distance. We conclude that visuomotor feedback gain shows a temporal evolution related to task demands and that this evolution can be flexibly recomputed within 100 ms to accommodate online modifications to task goals.

Cognitive Tomography Reveals Complex, Task-Independent Mental Representations

Humans develop rich mental representations that guide their behavior in a variety of everyday tasks. However, it is unknown whether these representations, often formalized as priors in Bayesian inference, are specific for each task or subserve multiple tasks. Current approaches cannot distinguish between these two possibilities because they cannot extract comparable representations across different tasks [1-10]. Here, we develop a novel method, termed cognitive tomography, that can extract complex, multidimensional priors across tasks. We apply this method to human judgments in two qualitatively different tasks, "familiarity" and "odd one out," involving an ecologically relevant set of stimuli, human faces. We show that priors over faces are structurally complex and vary dramatically across subjects, but are invariant across the tasks within each subject. The priors we extract from each task allow us to predict with high precision the behavior of subjects for novel stimuli both in the same task as well as in the other task. Our results provide the first evidence for a single high-dimensional structured representation of a naturalistic stimulus set that guides behavior in multiple tasks. Moreover, the representations estimated by cognitive tomography can provide independent, behavior-based regressors for elucidating the neural correlates of complex naturalistic priors. © 2013 The Authors.

Exploiting passive dynamics for robot throwing task

Throwing is a complex and highly dynamic task. Humans usually exploit passive dynamics of their limbs to optimize their movement and muscle activation. In order to approach human throwing, we developed a double pendulum robotic platform. To introduce passivity into the actuated joints, clutches were included in the drive train. In this paper, we demonstrate the advantage of exploiting passive dynamics in reducing the mechanical work. However, engaging and disengaging the clutches are done in discrete fashions. Therefore, we propose an optimization approach which can deal with such discontinuities. It is shown that properly engaging/disengaging the clutches can reduce the mechanical work of a throwing task. The result is compared to the solution of fully actuated double pendulum, both in simulation and experiment. © 2012 IEEE.

Modification of two-photon excited fluorescence from quantum dots on SiN photonic crystals

We investigate two-photon excited fluorescence from CdSe quantum dots with a center-emitting wavelength of 655 nm on SiN photonic crystals. We find that two-photon excited fluorescence is enhanced by more than 1 order of magnitude in the vertical direction when a photonic crystal is used compared to the fluorescence spectra in the absence of photonic crystals. The spectrum of two-photon excited fluorescence from quantum dots on SiN photonic crystal is observed to shift to blue compared to that from quantum dots on SiN without photonic crystals. (C) 2010 Optical Society of America

Ferromagnetic modification of GaN film by Cu+ ions implantation

The structural and magnetic properties of Cu+ ions-implanted GaN films have been reported. Eighty kilo-electron-volt Cu+ ions were implanted into n-type GaN film at room temperature with fluences ranging from 1 x 10(16) to 8 x 10(16) cm(-2) and subsequently annealed at 800 degrees C for 1 h in N-2 ambient. PIXE was employed to determine the Cu-implanted content. The magnetic property was measured by the Quantum Design MPMS SQUID magnetometer. No secondary phases or clusters were detected within the sensitivity of XRD. Raman spectrum measurement showed that the Cu ions incorporated into the crystal lattice positions of GaN through substitution of Ga atoms. Apparent ferromagnetic hysteresis loops measured at 10 K were presented. The experimental result showed that the ferromagnetic signal strongly increased with Cu-implanted fluence from 1 x 10(16) to 8 x 10(16) cm(-2).

Modification of emission wavelength of self-assembled In(Ga)As/GaAs quantum dots covered by InxGa1-xAs(0 <= x <= 0.3) layer

Red shifts of emission wavelength of self-organized In(Cla)As/GaAs quantum dots (QDs) covered by 3 nm thick InxGa1-xAs layer with three different In mole fractions (x = 0.1, 0.2 and 0.3, respectively) have been observed. Transmission electron microscopy images demonstrate that the stress along growth direction in the InAs dots was reduced due to introducing the InxGa1-xAs (x = 0.1, 0.2 and 0.3) covering layer instead of GaAs layer. Atomic force microscopy pictures show a smoother surface of InAs islands covered by an In0.2Ga0.8As layer. It is explained by the calculations that the redshifts of the photoluminescence (PL) spectra from the QDs covered by the InxGa1-xAs (x greater than or equal to 0.1) layers were mainly due to the reducing of the strain other than the InAs/GaAs intermixing in the InAs QDs. The temperature dependent PL spectra further confirm that the InGaAs covering layer can effectively suppress the temperature sensitivity of PL emissions. 1.3 mum emission wavelength with a very narrow linewidth of 19.2 mcV at room temperature has been obtained successfully from In,In0.5Ga0.5As/GaAs self-assembled QDs covered by a 3-nm In0.2Ga0.2As strain reducing layer. (C) 2001 Elsevier Science B.V. All rights reserved.

Modification of InAs quantum dot structure by the growth of the capping layer

InAs quantum dots inserted at the middle of a GaAs quantum well structure have been investigated by transmission electron microscopy and scanning transmission electron microscopy. We find that the growth condition of the overlayer on the InAs dots can lead to drastic changes in the structure of the dots. We attribute the changes to a combination of factors such as preferential growth of the overlayer above the wetting layers because of the strained surfaces and to the thermal instability of the InAs dots at elevated temperature. The result suggests that controlled sublimation, through suitable manipulation of the overlayer growth conditions, can be an effective tool to improve the structure of the self-organized quantum dots and can help tailor their physical properties to any specific requirements of the device applications. (C) 1998 American Institute of Physics.