Learning to Infer Graphics Programs from Hand-Drawn Images

We introduce a model that learns to convert simple hand drawings into graphics programs written in a subset of \LaTeX. The model combines techniques from deep learning and program synthesis. We learn a convolutional neural network that proposes plausible drawing primitives that explain an image. These drawing primitives are like a trace of the set of primitive commands issued by a graphics program. We learn a model that uses program synthesis techniques to recover a graphics program from that trace. These programs have constructs like variable bindings, iterative loops, or simple kinds of conditionals. With a graphics program in hand, we can correct errors made by the deep network, measure similarity between drawings by use of similar high-level geometric structures, and extrapolate drawings. Taken together these results are a step towards agents that induce useful, human-readable programs from perceptual input

Methods and considerations for the analysis and standardization of assessing muscle sympathetic nerve activity in humans.

The technique of microneurography and the assessment of muscle sympathetic nerve activity (MSNA) are used in laboratories throughout the world. The variables used to describe MSNA, and the criteria by which these variables are quantified from the integrated neurogram, vary among studies and laboratories and, therefore, can become confusing to those starting to learn the technique. Therefore, the purpose of this educational review is to discuss guidelines and standards for the assessment of sympathetic nervous activity through the collection and analysis of MSNA. This review will reiterate common practices in the collection of MSNA, but will also introduce considerations for the evaluation and physiological inference using MSNA

Methods and considerations for the analysis and standardization of assessing muscle sympathetic nerve activity in humans

© 2015 Elsevier B.V.. The technique of microneurography and the assessment of muscle sympathetic nerve activity (MSNA) are used in laboratories throughout the world. The variables used to describe MSNA, and the criteria by which these variables are quantified from the integrated neurogram, vary among studies and laboratories and, therefore, can become confusing to those starting to learn the technique. Therefore, the purpose of this educational review is to discuss guidelines and standards for the assessment of sympathetic nervous activity through the collection and analysis of MSNA. This review will reiterate common practices in the collection of MSNA, but will also introduce considerations for the evaluation and physiological inference using MSNA

The Soft Landing Problem: Minimizing Energy Loss by a Legged Robot Impacting Yielding Terrain

Enabling robots to walk and run on yielding terrain is increasingly vital to endeavors ranging from disaster response to extraterrestrial exploration. While dynamic legged locomotion on rigid ground is challenging enough, yielding terrain presents additional challenges such as permanent ground deformation which dissipates energy. In this paper, we examine the soft landing problem: given some impact momentum, bring the robot to rest while minimizing foot penetration depth. To gain insight into properties of penetration depth-minimizing control policies, we formulate a constrained optimal control problem and obtain a bang-bang open-loop force profile. Motivated by examples from biology and recent advances in legged robotics, we also examine impedance-control solutions to the dimensionless soft landing problem. Through simulations, we find that optimal impedance reduces penetration depth nearly as much as the open-loop force profile, while remaining robust to model uncertainty. Through simulations and experiments, we find that the solution space is rich, exhibiting qualitatively different relationships between impact velocity and the optimal impedance for small and large dimensionless impact velocities. Lastly, we discuss the relevance of this work to minimum-cost-of-transport locomotion for several actuator design choices

Solid Microneedles for Transdermal Delivery of Amantadine Hydrochloride and Pramipexole Dihydrochloride

The aim of this project was to study the influence of microneedles on transdermal delivery of amantadine hydrochloride and pramipexole dihydrochloride across porcine ear skin in vitro. Microchannel visualization studies were carried out and characterization of the microchannel depth was performed using confocal laser scanning microscopy (CLSM) to demonstrate microchannel formation following microneedle roller application. We also report, for the first time, the use of TA.XT Plus Texture Analyzer to characterize burst force in pig skin for transdermal drug delivery experiments. This is the force required to rupture pig skin. The mean passive flux of amantadine hydrochloride, determined using a developed LC–MS/MS technique, was 22.38 ± 4.73 μg/cm2/h, while the mean flux following the use of a stainless steel microneedle roller was 49.04 ± 19.77 μg/cm2/h. The mean passive flux of pramipexole dihydrochloride was 134.83 ± 13.66 μg/cm2/h, while the flux following the use of a stainless steel microneedle roller was 134.04 ± 0.98 μg/cm2/h. For both drugs, the difference in flux values following the use of solid stainless steel microneedle roller was not statistically significantly (p \u3e 0.05). Statistical analysis was carried out using the Mann–Whitney Rank sum test

Population-based Laboratory Surveillance for AmpC β-Lactamase–producing Escherichia coli, Calgary

AmpC β-lactamase–producing E. coli are commonly isolated from the urinary tract of older women