University of California

About: University of California is a education organization based out in Oakland, California, United States. It is known for research contribution in the topics: Population & Layer (electronics). The organization has 55175 authors who have published 52933 publications receiving 1491169 citations. The organization is also known as: UC & University of California System.

Non-invasive gene targeting to the brain

Abstract: Liposomes containing therapeutic genes are conjugated to multiple blood-brain barrier and brain cell membrane targeting agents to provide transport of the encapsulated gene across the blood-brain barrier and brain cell membrane. Once across the blood-brain barrier and brain cell membrane, the encapsulated gene expresses the encoded therapeutic agent within the brain to provide treatment and diagnosis of disease.

IC-processed microneedles

Abstract: A method of fabricating a microstructure is disclosed. The method includes providing a substrate for forming an interface region and an elongated portion extending away from the interface region. A patterned, non-planar etchable structure is formed on one side of the elongated portion of the substrate. An unetchable membrane layer is deposited atop the etchable structure. At least one etching hole is formed in the membrane layer. The etchable structure is etched by placing an etchant into the etching hole to form a cavity underneath the membrane layer, thereby producing a shaft.

DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills

Abstract: A longstanding goal in character animation is to combine data-driven specification of behavior with a system that can execute a similar behavior in a physical simulation, thus enabling realistic responses to perturbations and environmental variation. We show that well-known reinforcement learning (RL) methods can be adapted to learn robust control policies capable of imitating a broad range of example motion clips, while also learning complex recoveries, adapting to changes in morphology, and accomplishing user-specified goals. Our method handles keyframed motions, highly-dynamic actions such as motion-captured flips and spins, and retargeted motions. By combining a motion-imitation objective with a task objective, we can train characters that react intelligently in interactive settings, e.g., by walking in a desired direction or throwing a ball at a user-specified target. This approach thus combines the convenience and motion quality of using motion clips to define the desired style and appearance, with the flexibility and generality afforded by RL methods and physics-based animation. We further explore a number of methods for integrating multiple clips into the learning process to develop multi-skilled agents capable of performing a rich repertoire of diverse skills. We demonstrate results using multiple characters (human, Atlas robot, bipedal dinosaur, dragon) and a large variety of skills, including locomotion, acrobatics, and martial arts.

Photocurrent spectroscopy of optical absorption enhancement in silicon photodiodes via scattering from surface plasmon polaritons in gold nanoparticles

Abstract: Experimental characterization and finite-element numerical simulations of the electromagnetic interaction between Au nanoparticles positioned atop a Si pn junction photodiode and incident electromagnetic plane waves have been performed as a function of wavelength. The presence of the Au nanoparticles is found to lead to increased electromagnetic field amplitude within the semiconductor, and consequently increased photocurrent response, over a broad range of wavelengths extending upward from the nanoparticle surface plasmon polariton resonance wavelength. At shorter wavelengths, a reduction in electromagnetic field amplitude and a corresponding decrease in photocurrent response in the semiconductor are observed. Numerical simulations reveal that these different behaviors are a consequence of a shift in the phase of the nanoparticle polarizability near the surface plasmon polariton wavelength, leading to interference effects within the semiconductor that vary strongly with wavelength. These observations hav...

Occupy the cloud: distributed computing for the 99%

Abstract: Distributed computing remains inaccessible to a large number of users, in spite of many open source platforms and extensive commercial offerings. While distributed computation frameworks have moved beyond a simple map-reduce model, many users are still left to struggle with complex cluster management and configuration tools, even for running simple embarrassingly parallel jobs. We argue that stateless functions represent a viable platform for these users, eliminating cluster management overhead, fulfilling the promise of elasticity. Furthermore, using our prototype implementation, PyWren, we show that this model is general enough to implement a number of distributed computing models, such as BSP, efficiently. Extrapolating from recent trends in network bandwidth and the advent of disaggregated storage, we suggest that stateless functions are a natural fit for data processing in future computing environments.