Space transportation systems, launch systems, and propulsion for the Space Exploration Initiative: Results from Project Outreach

A number of transportation and propulsion options for Mars exploration missions are analyzed. As part of Project Outreach, RAND received and evaluated 350 submissions in the launch vehicle, space transportation, and propulsion areas. After screening submissions, aggregating those that proposed identical or nearly identical concepts, and eliminating from further consideration those that violated known physical princples, we had reduced the total number of viable submissions to 213. In order to avoid comparing such disparate things as launch vehicles and electric propulsion systems, six broad technical areas were selected to categorize the submissions: space transportation systems; earth-to-orbit (ETO) launch systems; chemical propulsion; nuclear propulsion; low-thrust propulsion; and other. To provide an appropriate background for analyzing the submissions, an extensive survey was made of the various technologies relevant to the six broad areas listed above. We discuss these technologies with the intent of providing the reader with an indication of the current state of the art, as well as the advances that might be expected within the next 10 to 20 years

Faithfulness Tests for Natural Language Explanations

Explanations of neural models aim to reveal a model’s decision-making process for its predictions. However, recent work shows that current methods giving explanations such as saliency maps or counterfactuals can be misleading, as they are prone to present reasons that are unfaithful to the model’s inner workings. This work explores the challenging question of evaluating the faithfulness of natural language explanations (NLEs). To this end, we present two tests. First, we propose a counterfactual input editor for inserting reasons that lead to counterfactual predictions but are not reflected by the NLEs. Second, we reconstruct inputs from the reasons stated in the generated NLEs and check how often they lead to the same predictions. Our tests can evaluate emerging NLE models, proving a fundamental tool in the development of faithful NLEs

Stance detection with bidirectional conditional encoding

Stance detection is the task of classifying the attitude expressed in a text towards a target such as Hillary Clinton to be "positive", negative" or "neutral". Previous work has assumed that either the target is mentioned in the text or that training data for every target is given. This paper considers the more challenging version of this task, where targets are not always mentioned and no training data is available for the test targets. We experiment with conditional LSTM encoding, which builds a representation of the tweet that is dependent on the target, and demonstrate that it outperforms encoding the tweet and the target independently. Performance is improved further when the conditional model is augmented with bidirectional encoding. We evaluate our approach on the SemEval 2016 Task 6 Twitter Stance Detection corpus achieving performance second best only to a system trained on semi-automatically labelled tweets for the test target. When such weak supervision is added, our approach achieves state-of-the-art results.Comment: 10 page

emoji2vec: Learning Emoji Representations from their Description

Many current natural language processing applications for social media rely on representation learning and utilize pre-trained word embeddings. There currently exist several publicly-available, pre-trained sets of word embeddings, but they contain few or no emoji representations even as emoji usage in social media has increased. In this paper we release emoji2vec, pre-trained embeddings for all Unicode emoji which are learned from their description in the Unicode emoji standard. The resulting emoji embeddings can be readily used in downstream social natural language processing applications alongside word2vec. We demonstrate, for the downstream task of sentiment analysis, that emoji embeddings learned from short descriptions outperforms a skip-gram model trained on a large collection of tweets, while avoiding the need for contexts in which emoji need to appear frequently in order to estimate a representation

Dense Antihydrogen: Its Production and Storage to Envision Antimatter Propulsion

We discuss the possibility that dense antihydrogen could provide a path towards a mechanism for a deep space propulsion system. We concentrate at first, as an example, on Bose-Einstein Condensate (BEC) antihydrogen. In a Bose-Einstein Condensate, matter (or antimatter) is in a coherent state analogous to photons in a laser beam, and individual atoms lose their independent identity. This allows many atoms to be stored in a small volume. In the context of recent advances in producing and controlling BECs, as well as in making antihydrogen, this could potentially provide a revolutionary path towards the efficient storage of large quantities of antimatter, perhaps eventually as a cluster or solid.Comment: 12 pages, 3 figure

K⊂{[FeII^{II}(Tp)(CN)3_{3}]4_{4}[CoIII^{III}(pz^{pz}Tp)]3_{3}[CoII^{II}(pz^{pz}Tp)]}: a neutral soluble model complex of photomagnetic Prussian blue analogues

Straightforward access to a new cyanide-bridged {Fe$_{4}$Co$_{4}$} “molecular box” containing a potassium ion, namely K⊂{[Fe$^{II}$(Tp)(CN)$_{3}$]$_{4}$[Co$^{III}$($^{pz}$Tp)]$_{3}$[Co$^{II}$($^{pz}$Tp)]} (1) (with Tp and $^{pz}$Tp = tris- and tetrakis(pyrazolyl)borate, respectively), is provided, alongside its full characterisation. A detailed analysis of the molecular structure (X-ray diffraction, mass spectrometry, NMR spectroscopy) and electronic properties (EPR spectroscopy, SQUID magnetometry, UV/Vis spectroscopy, cyclic voltammetry) reveals that 1 shows slow magnetic relaxation and a remarkable photomagnetic effect at low temperature which is reminiscent of some FeCo Prussian Blue Analogues (PBAs), and is ascribed to a photo-induced electron transfer. However, in contrast with these inorganic polymers, the overall neutral compound 1 is soluble and remarkably stable in organic solvents such as CH2Cl2. Moreover, 1 shows interesting redox versatility, with electrochemical experiments revealing the possible access to six stable redox states

Distant supervision from knowledge graphs

In this chapter, we discuss approaches leveraging distant supervision for relation extraction. We start by introducing the key ideas behind distant supervision as well as their main shortcomings. We then discuss approaches that improve over the basic method, including approaches based on the at-least-one-principle along with their extensions for handling false negative labels, and approaches leveraging topic models. We also describe embeddings-based methods including methods leveraging convolutional neural networks. Finally, we discuss how to take advantage of auxiliary information to improve relation extraction

Organic Reference Materials for Hydrogen, Carbon, and Nitrogen Stable Isotope-Ratio Measurements: Caffeines, n-Alkanes, Fatty Acid Methyl Esters, Glycines, L-Valines, Polyethylenes, and Oils

An international project developed, quality-tested, and determined isotope−δ values of 19 new organic reference materials (RMs) for hydrogen, carbon, and nitrogen stable isotope-ratio measurements, in addition to analyzing pre-existing RMs NBS 22 (oil), IAEA-CH-7 (polyethylene foil), and IAEA-600 (caffeine). These new RMs enable users to normalize measurements of samples to isotope−δ scales. The RMs span a range of δ^2H_(VSMOW-SLAP) values from −210.8 to +397.0 mUr or ‰, for δ^(13)C_(VPDB-LSVEC) from −40.81 to +0.49 mUr and for δ^(15)N_(Air) from −5.21 to +61.53 mUr. Many of the new RMs are amenable to gas and liquid chromatography. The RMs include triads of isotopically contrasting caffeines, C_(16) n-alkanes, n-C_(20)-fatty acid methyl esters (FAMEs), glycines, and L-valines, together with polyethylene powder and string, one n-C_(17)-FAME, a vacuum oil (NBS 22a) to replace NBS 22 oil, and a ^2H-enriched vacuum oil. A total of 11 laboratories from 7 countries used multiple analytical approaches and instrumentation for 2-point isotopic normalization against international primary measurement standards. The use of reference waters in silver tubes allowed direct normalization of δ2H values of organic materials against isotopic reference waters following the principle of identical treatment. Bayesian statistical analysis yielded the mean values reported here. New RMs are numbered from USGS61 through USGS78, in addition to NBS 22a. Because of exchangeable hydrogen, amino acid RMs currently are recommended only for carbon- and nitrogen-isotope measurements. Some amino acids contain ^(13)C and carbon-bound organic ^2H-enrichments at different molecular sites to provide RMs for potential site-specific isotopic analysis in future studies

Dual clumped isotope thermometry resolves kinetic biases in carbonate formation temperatures

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Bajnai, D., Guo, W., Spötl, C., Coplen, T. B., Methner, K., Löffler, N., Krsnik, E., Gischler, E., Hansen, M., Henkel, D., Price, G. D., Raddatz, J., Scholz, D., & Fiebig, J. Dual clumped isotope thermometry resolves kinetic biases in carbonate formation temperatures. Nature Communications, 11(1), (2020): 4005, doi:10.1038/s41467-020-17501-0.Surface temperature is a fundamental parameter of Earth’s climate. Its evolution through time is commonly reconstructed using the oxygen isotope and the clumped isotope compositions of carbonate archives. However, reaction kinetics involved in the precipitation of carbonates can introduce inaccuracies in the derived temperatures. Here, we show that dual clumped isotope analyses, i.e., simultaneous ∆47 and ∆48 measurements on the single carbonate phase, can identify the origin and quantify the extent of these kinetic biases. Our results verify theoretical predictions and evidence that the isotopic disequilibrium commonly observed in speleothems and scleractinian coral skeletons is inherited from the dissolved inorganic carbon pool of their parent solutions. Further, we show that dual clumped isotope thermometry can achieve reliable palaeotemperature reconstructions, devoid of kinetic bias. Analysis of a belemnite rostrum implies that it precipitated near isotopic equilibrium and confirms the warmer-than-present temperatures during the Early Cretaceous at southern high latitudes.This work became possible through DFG grant “INST 161/871-1” and the Investment in Science Fund at Woods Hole Oceanographic Institution. The authors would like to thank Sven Hofmann and Manuel Schumann for their assistance in the joint Goethe University – Senckenberg BiK-F Stable Isotope Facility at the Institute of Geosciences, Goethe University Frankfurt. K.M. acknowledges funding through “DFG ME 4955/1-1”, E.K. through “DFG MU 2845/6-1”, D.S. through “DFG SCHO 1274/8-1” and “DFG SCHO 1274/11-1”, and M.H. through “DFG HA 8694/1-1”. C.S. acknowledges funding from the University of Innsbruck. A review of the manuscript by David Evans on behalf of the USGS is acknowledged