Advanced Scientific Concepts (United States)

Late Pleistocene Clovis fluted points and stone flake tools have been found in association with bison at several archaeological sites in western North America. To gain insight into how these tools may have functioned in bison butchery, as well as to assess the assumptions or interpretations of these implements by archaeologists, we conducted a bison-processing experiment. We examined the relative efficacy in the butchering process of hafted fluted points versus handheld flakes and of different Clovis point forms; the types of tool breakage that might occur during butchering; cut-marks that might occur on bones; and, the effects of edge resharpening, both in terms of cutting efficiency and in the before/after form of the points and flake tools used in the process. We also recorded several unanticipated observations on, but not limited to, field-processor injury, the function of fluted point proximal-lateral edge grinding, and tool loss during the butchery event. Overall, our experiment emphasizes the prevalence of equifinality in archaeological interpretation, as it shows that numerous aspects of the Clovis archaeological record – as it is currently understood – can be equally explained by several distinct processes.

In the recent decade, computational tools have become central in material design, allowing rapid development cycles at reduced costs. Machine learning tools are especially on the rise in photonics. However, the inversion of the Maxwell equations needed for the design is particularly challenging from an optimization standpoint, requiring sophisticated software. We present an innovative, open-source software tool called Neural Inverse Design of Nanostructures (NIDN) that allows designing complex, stacked material nanostructures using a physics-based deep learning approach. Instead of a derivative-free or data-driven optimization or learning method, we perform a gradient-based neural network training where we directly optimize the material and its structure based on its spectral characteristics. NIDN supports two different solvers, rigorous coupled-wave analysis and a finite-difference time-domain method. The utility and validity of NIDN are demonstrated on several synthetic examples as well as the design of a 1550 nm filter and anti-reflection coating. Results match experimental baselines, other simulation tools, and the desired spectral characteristics. Given its full modularity in regard to network architectures and Maxwell solvers as well as open-source, permissive availability, NIDN will be able to support computational material design processes in a broad range of applications.

The adaptation of LIDAR sensing for space-based applications has grown dramatically over the past decade. Global shutter flash LIDAR has emerged as the LIDAR sensor modality of choice for space craft operations.

During eclipses, the spacecraft cannot rely on solar energy and must exploit the power coming from the on-board batteries. Critical for the payload is to maintain its temperature inside a specific predetermined range to avoid degradation and malfunctioning. For XMM-Newton, this is done through the Temperature Closed Loop (TCL) unit, which automatically turns on and off the heaters when the instruments reach the minimum and maximum temperatures, respectively. A possible scenario is the case when more than a single instrument reaches the minimum temperature simultaneously, thus causing a peak in the demand of power from the batteries and threatening their integrity. Such a circumstance may impact the overall mission and a better battery management is therefore required. Here we propose a solution that uses machine learning to optimize the battery consumption during eclipses. We show that after training the algorithm with past data, we are able to predict the temperature profiles of the instruments with good accuracy. These predictions provide the relevant insight to determine the optimal times at which the heaters should be turned on and off, thus improving and optimizing the current eclipse operations. The approach presented here helps overcome the issue of excessively stressing the batteries and, despite being tailored for XMM-Newton, can be extended and applied to other missions as well.

The problem description for the 9th edition of the Global Trajectory Optimization Competition

A technology reference study for a multiple near-Earth object (NEO) rendezvous mission with solar sailcraft is currently carried out by the authors of this paper. The investigated mission builds on previous concepts, but adopts a strong micro-spacecraft philosophy based on the DLR/ESA Gossamer technology. The main scientific objective of the mission is to explore the diversity of NEOs. After direct interplanetary insertion, the solar sailcraft should—within less than 10 years—rendezvous three NEOs that are not only scientifically interesting, but also from the point of human spaceight and planetary defense. In this paper, the objectives of the study are outlined and a preliminary potential mission profile is presented.

Successful leadership depends on the confidence to rally support, win allies, and deter competitors. However, overconfident leaders have led their companies into disaster. This article identifies the circumstances in which leaders are most prone to overconfidence and its concomitant risks. On the flip side, it explores those circumstances under which confidence is most conducive to success. Using insights from recent research, the article provides recommendations on how managers can avoid the pitfalls of overconfidence while benefiting from the advantages of confidence.

Autonomous aerial refueling (AAR) is an important capability for an unmanned aerial vehicle (UAV) to increase its flying range and endurance without increasing its size. This paper presents a novel tracking method that utilizes both 2D intensity and 3D point-cloud data acquired with a 3D Flash LIDAR sensor to establish relative position and orientation between the receiver vehicle and drogue during an aerial refueling process. Unlike classic, vision-based sensors, a 3D Flash LIDAR sensor can provide 3D point-cloud data in real time without motion blur, in the day or night, and is capable of imaging through fog and clouds. The proposed method segments out the drogue through 2D analysis and estimates the center of the drogue from 3D point-cloud data for flight trajectory determination. A level-set front propagation routine is first employed to identify the target of interest and establish its silhouette information. Sufficient domain knowledge, such as the size of the drogue and the expected operable distance, is integrated into our approach to quickly eliminate unlikely target candidates. A statistical analysis along with a random sample consensus (RANSAC) is performed on the target to reduce noise and estimate the center of the drogue after all 3D points on the drogue are identified. The estimated center and drogue silhouette serve as the seed points to efficiently locate the target in the next frame.

Abstract This article discusses some new developments in medical thermography, including the new‐generation infrared technologies, the smart image processing algorithms, and the pathophysiological‐based understanding of infrared images. These developments have largely advanced the role of thermography in health monitoring and examination, as well as in assisting diagnosis.

The primary technical challenge for optical backplanes involve the alignment and optical isolation of multiple data channels. Since most backplanes require data transfer rates greater than a single optical channel can costeffectively provide, multiple data channels is the common solution for higher aggregate transfer rates. Established optical alignment and isolation techniques include spatial separation of optical channels, use of lensing elements to focus specific transmitter outputs to specific receiver areas, use of differing wavelengths for adjacent channels with appropriate frequency filtering on receivers, and the use of "light guide tubes" for each channel. This presentation will examine another promising option, the use of "matched" Holographic Optical Elements (HOEs) to provide both cross channel optical isolation and to significantly relax traditional optical alignment requirements. Matched HOEs can both induce upon a transmitted optical stream, and then filter upon a received optical stream, a number of distinguishing characteristics such as wavelength, polarization, phase, and amplitude. Thus the use of a unique "matched HOE" pair with each transmitterreceiver pair of multiple optical data channels can provide an efficient mechanism to isolate individual data streams even when they may be physically coincident, such as in a length of fibre optic or when multiple free space data transmitters illuminate several channel's receiver elements. Thus, the alignment issue is relaxed from the usual constraint of attempting to physically separate channels to one where, as long as the receiver is within the optical cone of it's matched transmitting element, cross channel interference can be effectively eliminated.