Large structures and tethers working group

The Large Structures and Tethers Working Group sought to clarify the meaning of large structures and tethers as they related to space systems. Large was assumed to mean that the characteristic length of the structure was greater than one of such relevant plasma characteristics as ion gyroradius or debey length. Typically, anything greater than or equal to the Shuttle dimensions was considered large. It was agreed that most large space systems that the tether could be better categorized as extended length, area, or volume structures. The key environmental interactions were then identified in terms of these three categories. In the following Working Group summary, these categories and the related interactions are defined in detail. The emphasis is on how increases in each of the three spatial dimensions uniquely determine the interactions with the near-Earth space environment. Interactions with the environments around the other planets and the solar wind were assumed to be similar or capable of being extrapolated from the near-Earth results. It should be remembered in the following that the effects on large systems do not just affect specific technologies but will quite likely impact whole missions. Finally, the possible effects of large systems on the plasma environment, although only briefly discussed, were felt to be of potentially great concern

A Cognitive Robotic Imitation Learning System Based On Cause-Effect Reasoning

As autonomous systems become more intelligent and ubiquitous, it is increasingly important that their behavior can be easily controlled and understood by human end users. Robotic imitation learning has emerged as a useful paradigm for meeting this challenge. However, much of the research in this area focuses on mimicking the precise low-level motor control of a demonstrator, rather than interpreting the intentions of a demonstrator at a cognitive level, which limits the ability of these systems to generalize. In particular, cause-effect reasoning is an important component of human cognition that is under-represented in these systems. This dissertation contributes a novel framework for cognitive-level imitation learning that uses parsimonious cause-effect reasoning to generalize demonstrated skills, and to justify its own actions to end users. The contributions include new causal inference algorithms, which are shown formally to be correct and have reasonable computational complexity characteristics. Additionally, empirical validations both in simulation and on board a physical robot show that this approach can efficiently and often successfully infer a demonstrator’s intentions on the basis of a single demonstration, and can generalize learned skills to a variety of new situations. Lastly, computer experiments are used to compare several formal criteria of parsimony in the context of causal intention inference, and a new criterion proposed in this work is shown to compare favorably with more traditional ones. In addition, this dissertation takes strides towards a purely neurocomputational implementation of this causally-driven imitation learning framework. In particular, it contributes a novel method for systematically locating fixed points in recurrent neural networks. Fixed points are relevant to recent work on neural networks that can be “programmed” to exhibit cognitive-level behaviors, like those involved in the imitation learning system developed here. As such, the fixed point solver developed in this work is a tool that can be used to improve our engineering and understanding of neurocomputational cognitive control in the next generation of autonomous systems, ultimately resulting in systems that are more pliable and transparent

Identifying Fixed Points in Recurrent Neural Networks using Directional Fibers: Supplemental Material on Theoretical Results and Practical Aspects of Numerical Traversal

Fixed points of recurrent neural networks can represent many things, including stored memories, solutions to optimization problems, and waypoints along non-fixed attractors. As such, they are relevant to a number of neurocomputational phenomena, ranging from low-level motor control and tool use to high-level problem solving and decision making. Therefore, global solution of the fixed point equations can improve our understanding and engineering of recurrent neural networks. While local solvers and statistical characterizations abound, we do not know of any method for efficiently and precisely locating all fixed points of an arbitrary network. To solve this problem we have proposed a novel strategy for global fixed point location, based on numerical traversal of mathematical objects we defined called directional fibers [2]. This report supplements our results in [2] by presenting certain technical aspects of our method in more depth

Government Partisanship, Labor Organization, and Macroeconomic Performance: A Corrigendum

Alvarez, Garrett and Lange (1991) used cross-national data panel data on the Organization for Economic Coordination and Development nations to show that countries with left governments and encompassing labor movements enjoyed superior economic performance. Here we show that the standard errors reported in that article are incorrect. Reestimation of the model using ordinary least squares and robust standard errors upholds the major finding of Alvarez, Garrett and Lange, regarding the political and institutional causes of economic growth but leaves the findings for unemployment and inflation open to question. We show that the model used by Alvarez, Garrett and Lange, feasible generalized least squares, cannot produce standard errors when the number of countries analyzed exceeds the length of the time period under analysis. Also, we argue that ordinary least squares with robust standard errors is superior to feasible generalized least square for typical cross-national panel studies

Morphology of Influenza B/Lee/40 Determined by Cryo-Electron Microscopy

Cryo-electron microscopy projection image analysis and tomography is used to describe the overall architecture of influenza B/Lee/40. Algebraic reconstruction techniques with utilization of volume elements (blobs) are employed to reconstruct tomograms of this pleomorphic virus and distinguish viral surface spikes. The purpose of this research is to examine the architecture of influenza type B virions by cryo-electron tomography and projection image analysis. The aims are to explore the degree of ribonucleoprotein disorder in irregular shaped virions; and to quantify the number and distribution of glycoprotein surface spikes (hemagglutinin and neuraminidase) on influenza B. Projection image analysis of virion morphology shows that the majority (∼83%) of virions are spherical with an average diameter of 134±19 nm. The aspherical virions are larger (average diameter = 155±47 nm), exhibit disruption of the ribonucleoproteins, and show a partial loss of surface protein spikes. A count of glycoprotein spikes indicates that a typical 130 nm diameter type B virion contains ∼460 surface spikes. Configuration of the ribonucleoproteins and surface glycoprotein spikes are visualized in tomogram reconstructions and EM densities visualize extensions of the spikes into the matrix. The importance of the viral matrix in organization of virus structure through interaction with the ribonucleoproteins and the anchoring of the glycoprotein spikes to the matrix is demonstrated

Voting in the bicameral Congress: large majorities as a signal of quality

publication-status: Acceptedtypes: ArticleWe estimate a model of voting in Congress that allows for dispersed information about the quality of proposals in an equilibrium context. In equilibrium, the Senate only approves House bills that receive the support of a supermajority of members of the lower chamber. We estimate this endogenous supermajority rule to be about four-fifths on average across policy areas. Our results indicate that the value of information dispersed among legislators is significant, and that in equilibrium a large fraction of House members' (40–50%) votes following their private information. Finally, we show that the probability of a type I error in Congress (not passing a good bill) is on average about twice as high as the probability of a type II error (passing a low-quality bill)

Consistency Relations for Internal Waves

A complete set of linearly independent relationships among the different cross spectral components obtained from pairs of moored instruments is derived which can be utilized to test whether or not the observed fluctuations within the internal wave frequency band represent a field of propagating internal waves. A further complete set of relationships is derived which enables to test whether or not the internal wave field is horizontally isotropic and (or) vertically symmetric. These relations are compared with corresponding relations for alternative models (standing internal wave modes, three-dimensional isotropic turbulence) and their capability to discriminate between the various models is investigated. The tests are applied to a set of data for which it is found that the observed fluctuations are consistent with both propagating and standing internal waves whereas isotropic turbulence must be rejected for the most part of the internal wave frequency band

Protein P7 of the Cystovirus φ6 Is Located at the Three-Fold Axis of the Unexpanded Procapsid

The objective of this study was to determine the location of protein P7, the RNA packaging factor, in the procapsid of the φ6 cystovirus. A comparison of cryo-electron microscopy high-resolution single particle reconstructions of the φ6 complete unexpanded procapsid, the protein P2-minus procapsid (P2 is the RNA directed RNA-polymerase), and the P7-minus procapsid, show that prior to RNA packaging the P7 protein is located near the three-fold axis of symmetry. Difference maps highlight the precise position of P7 and demonstrate that in P7-minus particles the P2 proteins are less localized with reduced densities at the three-fold axes. We propose that P7 performs the mechanical function of stabilizing P2 on the inner protein P1 shell which ensures that entering viral single-stranded RNA is replicated

Magnetour: Surfing Planetary Systems on Electromagnetic and Multi-Body Gravity Fields

In this NIAC Phase One study, we propose a new mission concept, named Magnetour, to facilitate the exploration of outer planet systems and address both power and propulsion challenges. Our approach would enable a single spacecraft to orbit and travel between multiple moons of an outer planet, with no propellant required. Our approach would enable a single spacecraft to orbit and travel between multiple moons of an outer planet, with no propellant nor onboard power source required. To achieve this free-lunch _Grand Tour', we exploit the unexplored combination of magnetic and multi-body gravitational fields of planetary systems, with a unique focus on using a bare tether for power and propulsion. The main objective of the study is to develop this conceptually novel mission architecture, explore its design space, and investigate its feasibility and applicability to enhance the exploration of planetary systems within a 10-year timeframe. Propellantless propulsion technology offers enormous potential to transform the way NASA conducts outer planet missions. We hope to demonstrate that our free-lunch tour concept can replace heavy, costly, traditional chemical-based missions and can open up a new variety of trajectories around outer planets. Leveraging the powerful magnetic and multi-body gravity fields of planetary systems to travel freely among planetary moons would allow for long-term missions and provide unique scientific capabilities and flagship-class science for a fraction of the mass and cost of traditional concepts. New mission design techniques are needed to fully exploit the potential of this new concept.This final report contains the results and findings of the Phase One study, and is organized as follows. First, an overview of the Magnetour mission concept is presented. Then, the research methodology adopted for this Phase One study is described, followed by a brief outline of the main findings and their correspondence with the original Phase One task plan. Next, an overview of the environment of outer planets is provided, including magnetosphere, radiation belt and planetary moons. Then performance of electrodynamic tethers is assessed, as well as other electromagnetic systems. A method to exploit multi-body dynamics is given next. These analyses allow us to carry out a Jovian mission design to gain insight in the benefits of Magnetour. In addition, a spacecraft configuration is presented that fully incorporates the tether in the design. Finally technology roadmap considerations are discussed

Electronic clinical decision support algorithms incorporating point-of-care diagnostic tests in low-resource settings: a target product profile

Health workers in low-resource settings often lack the support and tools to follow evidence-based clinical recommendations for diagnosing, treating and managing sick patients. Digital technologies, by combining patient health information and point-of-care diagnostics with evidence-based clinical protocols, can help improve the quality of care and the rational use of resources, and save patient lives. A growing number of electronic clinical decision support algorithms (CDSAs) on mobile devices are being developed and piloted without evidence of safety or impact. Here, we present a target product profile (TPP) for CDSAs aimed at guiding preventive or curative consultations in low-resource settings. This document will help align developer and implementer processes and product specifications with the needs of end users, in terms of quality, safety, performance and operational functionality. To identify the characteristics of CDSAs, a multidisciplinary group of experts (academia, industry and policy makers) with expertise in diagnostic and CDSA development and implementation in low-income and middle-income countries were convened to discuss a draft TPP. The TPP was finalised through a Delphi process to facilitate consensus building. An agreement greater than 75% was reached for all 40 TPP characteristics. In general, experts were in overwhelming agreement that, given that CDSAs provide patient management recommendations, the underlying clinical algorithms should be human-interpretable and evidence-based. Whenever possible, the algorithm's patient management output should take into account pretest disease probabilities and likelihood ratios of clinical and diagnostic predictors. In addition, validation processes should at a minimum show that CDSAs are implementing faithfully the evidence they are based on, and ideally the impact on patient health outcomes. In terms of operational needs, CDSAs should be designed to fit within clinic workflows and function in connectivity-challenged and high-volume settings. Data collected through the tool should conform to local patient privacy regulations and international data standards