Nonlinear disturbance attenuation control of hydraulic robotics

This paper presents a novel nonlinear disturbance rejection control for hydraulic robots. This method requires two third-order filters as well as inverse dynamics in order to estimate the disturbances. All the parameters for the third-order filters are pre-defined. The proposed method is nonlinear, which does not require the linearization of the rigid body dynamics. The estimated disturbances are used by the nonlinear controller in order to achieve disturbance attenuation. The performance of the proposed approach is compared with existing approaches. Finally, the tracking performance and robustness of the proposed approach is validated extensively on real hardware by performing different tasks under either internal or both internal and external disturbances. The experimental results demonstrate the robustness and superior tracking performance of the proposed approach

Borrowing from Yourself: The Determinants of 401(k) Loan Patterns

This paper explores the determinants of people’s decisions to take 401(k) loans. We argue that 401(k) plans do not simply represent retirement saving, but they also provide a means of saving for precautionary purposes. We model factors that rationally would induce people to borrow from their pension plans, and we explain why people do not often use 401(k) loans to replace their more expensive credit card debt. Next we test our hypotheses using a rich dataset and show that people who are liquidity-constrained are more likely to have plan loans, while the better-off take larger loans when they do borrow. Plan characteristics such as the number of loans allowed also influence borrowing and loan size in interesting ways, while loan interest rates have only a small impact.

Precision Synthesis of Silicon Nanowires with Crystalline Core and Amorphous Shell

A synthetic route to crystalline silicon (Si) nanowires with an amorphous Si shell is reported. Trisilane (Si3H8) and Sn(HMDS)(2) are decomposed in supercritical toluene at 450 degrees C. Sn(HMDS)(2) creates Sn nanoparticles that seed Si nanowire growth by the supercritical fluid-liquid-solid (SFLS) mechanism. The Si : Sn ratio in the reaction determines the growth of amorphous Si shell. No amorphous shell forms at relatively low Si : Sn ratios of 20 : 1, whereas higher Si : Sn ratio of 40 : 1 leads to significant amorphous shell. We propose that hydrogen evolved from trisilane decomposition etches away the Sn seed particles as nanowires grow, which promotes the amorphous Si shell deposition when the higher Si : Sn ratios are used.Robert A. Welch Foundation F-1464U.S. Department of Energy Office of Science, Office of Basic Energy Sciences DE-SC0001091National Defense Science and Engineering Graduate FellowshipChemistr

GEOSIM: A numerical model for geophysical fluid flow simulation

A numerical model which simulates geophysical fluid flow in a wide range of problems is described in detail, and comparisons of some of the model's results are made with previous experimental and numerical studies. The model is based upon the Boussinesq Navier-Stokes equations in spherical coordinates, which can be reduced to a cylindrical system when latitudinal walls are used near the pole and the ratio of latitudinal length to the radius of the sphere is small. The equations are approximated by finite differences in the meridional plane and spectral decomposition in the azimuthal direction. The user can specify a variety of boundary and initial conditions, and there are five different spectral truncation options. The results of five validation cases are presented: (1) the transition between axisymmetric flow and baroclinic wave flow in the side heated annulus; (2) the steady baroclinic wave of the side heated annulus; (3) the wave amplitude vacillation of the side heated annulus; (4) transition to baroclinic wave flow in a bottom heated annulus; and (5) the Spacelab Geophysical Fluid Flow Cell (spherical) experiment

Flexible Neural Electrode Array Based-on Porous Graphene for Cortical Microstimulation and Sensing.

Neural sensing and stimulation have been the backbone of neuroscience research, brain-machine interfaces and clinical neuromodulation therapies for decades. To-date, most of the neural stimulation systems have relied on sharp metal microelectrodes with poor electrochemical properties that induce extensive damage to the tissue and significantly degrade the long-term stability of implantable systems. Here, we demonstrate a flexible cortical microelectrode array based on porous graphene, which is capable of efficient electrophysiological sensing and stimulation from the brain surface, without penetrating into the tissue. Porous graphene electrodes show superior impedance and charge injection characteristics making them ideal for high efficiency cortical sensing and stimulation. They exhibit no physical delamination or degradation even after 1 million biphasic stimulation cycles, confirming high endurance. In in vivo experiments with rodents, same array is used to sense brain activity patterns with high spatio-temporal resolution and to control leg muscles with high-precision electrical stimulation from the cortical surface. Flexible porous graphene array offers a minimally invasive but high efficiency neuromodulation scheme with potential applications in cortical mapping, brain-computer interfaces, treatment of neurological disorders, where high resolution and simultaneous recording and stimulation of neural activity are crucial

An interactive model accounts for both ultra-rapid superordinate classificationand basic-level advantage in object recognition

While people are faster to categorize objects at an intermediate or basic level of specificity (e.g. “bird”), severalrecent studies have shown them to have much earlier access to more general category information (e.g. “animal”). Ultra-rapidsuperordinate classification has been taken as evidence that recognition processes are largely feed-forward. In simulations witha deep neural network model, we show that this conclusion does not follow: even a model that is fully recurrent and interactiveshows ultra-rapid superordinate classification patterns when tested with analogs of behavioral tasks such as rapid serial visualpresentation or deadline classification. Moreover, this recurrent model explains recently-observed similarities and differencesin the time-course of classification as estimated by electro-encephlography (EEG) versus human electro-corticography (ECoG),and also account for the well-known basic-level advantage in non-speeded classification. These results provide evidence thatultra-rapid and unconstrained visual object recognition is supported by interactive processes in the brain

DNA nanotechnology: new adventures for an old warhorse

As the blueprint of life, the natural exploits of DNA are admirable. However, DNA should not only be viewed within a biological context. It is an elegantly simple yet functionally complex chemical polymer with properties that make it an ideal platform for engineering new nanotechnologies. Rapidly advancing synthesis and sequencing technologies are enabling novel unnatural applications for DNA beyond the realm of genetics. Here we explore the chemical biology of DNA nanotechnology for emerging applications in communication and digital data storage. Early studies of DNA as an alternative to magnetic and optical storage mediums have not only been promising, but have demonstrated the potential of DNA to revolutionize the way we interact with digital data in the future.United States. Defense Advanced Research Projects Agency (Contract FA8721-05-C-0002)National Institutes of Health (U.S.) (Grant 1R01EB017755)National Institutes of Health (U.S.) (Grant 1DP2OD008435)National Institutes of Health (U.S.) (Grant 1P50GM098792

Social Interaction Effects and Individual Portfolio Choice: Evidence from 401(k) Pension Plan Investors

We show that participants are influenced by their coworkers when they make equity investment decisions. Using a rich dataset of 401(k) plans, we find that individuals are likely to increase (decrease) their risky share when they have lower (higher) equity exposure than their coworkers in the last period. The effect is especially strong when the difference in equity exposure is substantial. Furthermore, individuals are likely to increase their equity exposure if they earn lower equity returns than their coworkers did in the last period. However, when their returns on equity are higher than their peers’, they tend not to decrease their risky share. The interaction of peer behavior and peer outcome influences investment decisions, inducing individuals with substantially lower equity exposure than their coworkers to increase their risky share when coworkers also earned higher returns. Finally, we find that there exists heterogeneity in short-term excess returns following social interaction

The Schr\"odinger Functional for Improved Gluon and Quark Actions

The Schr\"odinger Functional (quantum/lattice field theory with Dirichlet boundary conditions) is a powerful tool in the non-perturbative improvement and for the study of other aspects of lattice QCD. Here we adapt it to improved gluon and quark actions, on isotropic as well as anisotropic lattices. Specifically, we describe the structure of the boundary layers, obtain the exact form of the classically improved gauge action, and outline the modifications necessary on the quantum level. The projector structure of Wilson-type quark actions determines which field components can be specified at the boundaries. We derive the form of O(a) improved quark actions and describe how the coefficients can be tuned non-perturbatively. There is one coefficient to be tuned for an isotropic lattice, three in the anisotropic case. Our ultimate aim is the construction of actions that allow accurate simulations of all aspects of QCD on coarse lattices.Comment: 39 pages, LaTeX, 11 embedded eps file