Thermally-induced change in the relaxation behavior of skin tissue.

Skin biothermomechanics is highly interdisciplinary, involving bioheat transfer, burn damage, biomechanics, and physiology. Characterization of the thermomechanical behavior of skin tissue is of great importance and can contribute to a variety of medical applications. However, few quantitative studies have been conducted on the thermally-dependent mechanical properties of skin tissue. The aim of the present study is to experimentally examine the thermally-induced change in the relaxation behavior of skin tissue in both hyperthermal and hypothermic ranges. The results show that temperature has great influence on the stress-relaxation behavior of skin tissue under both hyperthermal and hypothermic temperatures; the quantitative relationship that has been found between temperature and the viscoelastic parameter (the elastic fraction or fractional energy dissipation) was temperature dependent, with greatest dissipation at high temperature levels.

Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.

Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller) or as an added value (risk-seeking controller) to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models.

Face recognition from video

In spite of over two decades of intense research, illumination and pose invariance remain prohibitively challenging aspects of face recognition for most practical applications. The objective of this work is to recognize faces using video sequences both for training and recognition input, in a realistic, unconstrained setup in which lighting, pose and user motion pattern have a wide variability and face images are of low resolution. In particular there are three areas of novelty: (i) we show how a photometric model of image formation can be combined with a statistical model of generic face appearance variation, learnt offline, to generalize in the presence of extreme illumination changes; (ii) we use the smoothness of geodesically local appearance manifold structure and a robust same-identity likelihood to achieve invariance to unseen head poses; and (iii) we introduce an accurate video sequence "reillumination" algorithm to achieve robustness to face motion patterns in video. We describe a fully automatic recognition system based on the proposed method and an extensive evaluation on 171 individuals and over 1300 video sequences with extreme illumination, pose and head motion variation. On this challenging data set our system consistently demonstrated a nearly perfect recognition rate (over 99.7%), significantly outperforming state-of-the-art commercial software and methods from the literature. © Springer-Verlag Berlin Heidelberg 2006.

Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty

Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller) or as an added value (risk-seeking controller) to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models. © 2010 Nagengast et al.

Slip flow and heat transfer in microbearings with fractal surface topographies

The effects of random surface roughness on slip flow and heat transfer in microbearings are investigated. A three-dimensional random surface roughness model characterized by fractal geometry is used to describe the multiscale self-affine roughness, which is represented by the modified two-variable Weierstrass- Mandelbrot (W-M) functions, at micro-scale. Based on this fractal characterization, the roles of rarefaction and roughness on the thermal and flow properties in microbearings are predicted and evaluated using numerical analyses and simulations. The results show that the boundary conditions of velocity slip and temperature jump depend not only on the Knudsen number but also on the surface roughness. It is found that the effects of the gas rarefaction and surface roughness on flow behavior and heat transfer in the microbearing are strongly coupled. The negative influence of roughness on heat transfer found to be the Nusselt number reduction. In addition, the effects of temperature difference and relative roughness on the heat transfer in the bearing are also analyzed and discussed. © 2012 Elsevier Ltd. All rights reserved.

Achieving robust face recognition from video by combining a weak photometric model and a learnt generic face invariant

In spite of over two decades of intense research, illumination and pose invariance remain prohibitively challenging aspects of face recognition for most practical applications. The objective of this work is to recognize faces using video sequences both for training and recognition input, in a realistic, unconstrained setup in which lighting, pose and user motion pattern have a wide variability and face images are of low resolution. The central contribution is an illumination invariant, which we show to be suitable for recognition from video of loosely constrained head motion. In particular there are three contributions: (i) we show how a photometric model of image formation can be combined with a statistical model of generic face appearance variation to exploit the proposed invariant and generalize in the presence of extreme illumination changes; (ii) we introduce a video sequence re-illumination algorithm to achieve fine alignment of two video sequences; and (iii) we use the smoothness of geodesically local appearance manifold structure and a robust same-identity likelihood to achieve robustness to unseen head poses. We describe a fully automatic recognition system based on the proposed method and an extensive evaluation on 323 individuals and 1474 video sequences with extreme illumination, pose and head motion variation. Our system consistently achieved a nearly perfect recognition rate (over 99.7% on all four databases). © 2012 Elsevier Ltd All rights reserved.

Subsurface transport behavior of micro-nano bubbles and potential applications for groundwater remediation.

Micro-nano bubbles (MNBs) are tiny bubbles with diameters on the order of micrometers and nanometers, showing great potential in environmental remediation. However, the application is only in the beginning stages and remains to be intensively studied. In order to explore the possible use of MNBs in groundwater contaminant removal, this study focuses on the transport of MNBs in porous media and dissolution processes. The bubble diameter distribution was obtained under different conditions by a laser particle analyzer. The permeability of MNB water through sand was compared with that of air-free water. Moreover, the mass transfer features of dissolved oxygen in water with MNBs were studied. The results show that the bubble diameter distribution is influenced by the surfactant concentration in the water. The existence of MNBs in pore water has no impact on the hydraulic conductivity of sand. Furthermore, the dissolved oxygen (DO) in water is greatly increased by the MNBs, which will predictably improve the aerobic bioremediation of groundwater. The results are meaningful and instructive in the further study of MNB research and applications in groundwater bioremediation.

Impact of donor traps on the 2DEG and electrical behavior of AlGaN/GaN MISFETs

As an important step in understanding trap-related mechanisms in AlGaN/GaN transistors, the physical properties of surface states have been analyzed through the study of the transfer characteristics of a MISFET. This letter focused initially on the relationship between donor parameters (concentration and energy level) and electron density in the channel in AlGaN/GaN heterostructures. This analysis was then correlated to dc and pulsed measurements of the transfer characteristics of a MISFET, where the gate bias was found to modulate either the channel density or the donor states. Traps-free and traps-frozen TCAD simulations were performed on an equivalent device to capture the donor behavior. A donor concentration of 1.14× 1013 ∼ cm-2 with an energy level located 0.2 eV below the conduction band edge gave the best fit to measurements. With the approach described here, we were able to analyze the region of the MISFET that corresponds to the drift region of a conventional HEMT. © 1980-2012 IEEE.