Developing and testing algorithms for autonomous vehicles in real world is an expensive and time consuming process. Also, in order to utilize recent advances in machine intelligence and deep learning we need to collect a large amount of annotated training data in a variety of conditions and environments. We present a new simulator built on Unreal Engine that offers physically and visually realistic simulations for both of these goals. Our simulator includes a physics engine that can operate at a high frequency for real-time hardware-in-the-loop (HITL) simulations with support for popular protocols (e.g. MavLink). The simulator is designed from the ground up to be extensible to accommodate new types of vehicles, hardware platforms and software protocols. In addition, the modular design enables various components to be easily usable independently in other projects. We demonstrate the simulator by first implementing a quadrotor as an autonomous vehicle and then experimentally comparing the software components with real-world flights.

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Baseline renal function is a powerful predictor of short- and long-term events in the CCU population. There is an early hazard for in-hospital and postdischarge mortality for those with a corrected creatinine clearance <46.2 ml/min per kg, but not on dialysis.

The field of DNA nanoscience has demonstrated many exquisite DNA nanostructures and intricate DNA nanodevices. However, the operation of each step of prior demonstrated DNA nanodevices requires the diffusion of DNA strands, and the speed of these devices is limited by diffusion kinetics. Here we demonstrate chains of localized DNA hybridization reactions on the surface of a self-assembled DNA origami rectangle. The localization design for our DNA nanodevices does not rely on the diffusion of DNA strands for each step, thus providing faster reaction kinetics. The locality also provides considerable increased scalability, since localized components of the devices can be reused in other locations. A variety of techniques, including atomic force microscopy, total internal reflection fluorescence, and ensemble fluorescence spectroscopy, are used to confirm the occurrence of localized DNA hybridization reactions on the surface of DNA origami. There are many potential biological applications for our localized DNA nanodevices, and the localization design is extensible to applications involving DNA nanodevices operating on other molecular surfaces, such as those of the cell.

Drones equipped with cameras are emerging as a powerful tool for large-scale aerial 3D scanning, but existing automatic flight planners do not exploit all available information about the scene, and can therefore produce inaccurate and incomplete 3D models. We present an automatic method to generate drone trajectories, such that the imagery acquired during the flight will later produce a highfidelity 3D model. Our method uses a coarse estimate of the scene geometry to plan camera trajectories that: (1) cover the scene as thoroughly as possible; (2) encourage observations of scene geometry from a diverse set of viewing angles; (3) avoid obstacles; and (4) respect a user-specified flight time budget. Our method relies on a mathematical model of scene coverage that exhibits an intuitive diminishing returns property known as submodularity. We leverage this property extensively to design a trajectory planning algorithm that reasons globally about the non-additive coverage reward obtained across a trajectory, jointly with the cost of traveling between views. We evaluate our method by using it to scan three large outdoor scenes, and we perform a quantitative evaluation using a photorealistic video game simulator.

Significant CKD was related to overall poor survival, arrhythmic death and high DFTs.

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