Texas Christian University

About: Texas Christian University is a education organization based out in Fort Worth, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 3245 authors who have published 8258 publications receiving 282216 citations. The organization is also known as: TCU & Texas Christian University, TCU.

Modeling interactions between lignocellulose and ionic liquids using DFT-D

Abstract: Dissolution of lignocellulose in ionic liquids is a promising route to synthesizing fuels and chemical feedstocks from woody plant materials. While cellulose dissolution is well-understood, less is known about the differences between ionic liquids' interactions with cellulose vs.lignin. This work uses dispersion-corrected density functional theory (DFT-D) to model the interactions of imidazolium chloride ionic liquid anions and cations with (1,4)-dimethoxy-β-D-glucopyranose and 1-(4-methoxyphenyl)-2-methoxyethanol as models for cellulose and the lignin polyphenol, respectively. The cellulose model preferentially interacts with Cl−, confirming previous experimental and theoretical studies. However, the lignin model has significant π-stacking and hydrogen bonding interactions with imidazolium cation. These results are robust to changes in the computational details, and suggest that the ionic liquid cations play important roles in tuning the relative solubilities of lignin and cellulose. Calculations predict that the extended π-systems of benzimidazolium ionic liquids yield stronger interactions with lignin, showing potential for improved lignocellulose solvents.

Toward a Research Agenda on the Informal Economy

Abstract: Executive Overview Informal firms operate in a shadowy zone where they produce legal goods and services but do not follow legal requirements to register with government authorities. The collective economic activity involving informal firms, their suppliers, and their customers constitutes the informal economy. Although the informal economy accounts for a significant percentage of total commerce in many countries, there has been little management research about it. We outline some key issues and questions involving the informal economy that management researchers could help to answer, forming a potential research agenda in the process.

Designing systems for adaptability by means of architecture options

Abstract: The value of a system usually diminishes over its lifetime, but some systems depreciate more slowly than others. Diminished value is due partly to the increasing needs and wants of the system's stakeholders and partly to its decreasing capabilities relative to emerging alternatives. Thus, systems are replaced or upgraded at substantial cost and disruption. If a system is designed to be changed and upgraded easily, however, this adaptability may increase its lifetime value. How can adaptability be designed into a system so that it will provide increased value over its lifetime? This paper describes the problem and an approach to its mitigation, adopting the concept of real options from the field of economics, extending it to the field of systems architecture, and coining the term architecture options for this next-generation method and the associated tools for design for adaptability. Architecture options provide a quantitative means of optimizing a system architecture to maximize its lifetime value. This paper provides two quantitative models to assess the value of architecture adaptability. First, we define three metrics—component adaptability factors, component option values, and interface cost factors—which are used in a static model to evaluate architecture adaptability during the design of new systems. Second, we enhance a dynamic model to evaluate architecture adaptability over the maintenance and upgrade lifetime of a system, formulating a Design for Dynamic Value (DDV) optimization model. We illustrate both models with quantitative examples and also discuss how to obtain the socio-economic data required for each model. © 2008 Wiley Periodicals, Inc. Syst Eng

From the bulge to the outer disc: StarHorse stellar parameters, distances, and extinctions for stars in APOGEE DR16 and other spectroscopic surveys

Abstract: The StarHorse code is written in python 3.6 and makes use of several community-developed python packages, among them astropy (Astropy Collaboration 2013), ezpadova (https://github.com/ mfouesneau/ezpadova), numpy and scipy (Virtanen et al. 2020), and matplotlib (Hunter 2007). The code also makes use of the photometric filter database of VOSA (Bayo et al. 2008), developed under the Spanish Virtual Observatory project supported from the Spanish MICINN through grant AyA2011-24052. Funding for the SDSS Brazilian Participation Group has been provided by the Ministerio de Ciencia e Tecnologia (MCT), Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERJ), Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq), and Financiadora de Estudos e Projetos (FINEP). Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the US Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS web site is www.sdss. org. SDSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, the French Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofisica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU)/University of Tokyo, Lawrence Berkeley National Laboratory, Leibniz-Institut fur Astrophysik Potsdam (AIP), Max-Planck-Institut fur Astronomie (MPIA Heidelberg), Max-Planck-Institut fur Astrophysik (MPA Garching), Max-Planck-Institut fur Extraterrestrische Physik (MPE), National Astronomical Observatory of China, New Mexico State University, New York University, University of Notre Dame, Observatario Nacional/MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Uni-versidad Nacional Autonoma de Mexico, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University. Guoshoujing Telescope (the Large Sky Area Multi-Object Fiber Spectroscopic Telescope LAMOST) is a National Major Scientific Project built by the Chinese Academy of Sciences. Funding for the project has been provided by the National Development and Reform Commission. LAMOST is operated and managed by the National Astronomical Observatories, Chinese Academy of Sciences. Funding for RAVE has been provided by: the Australian Astronomical Observatory; the Leibniz-Institut fur Astrophysik Potsdam (AIP); the Australian National University; the Australian Research Council; the French National Research Agency; the German Research Foundation (SPP 1177 and SFB 881); the European Research Council (ERC-StG 240271 Galactica); the Istituto Nazionale di Astrofisica at Padova; The Johns Hopkins University; the National Science Foundation of the USA (AST-0908326); the W. M. Keck foundation; the Macquarie University; the Netherlands Research School for Astronomy; the Natural Sciences and Engineering Research Council of Canada; the Slovenian Research Agency; the Swiss National Science Foundation; the Science & Technology Facilities Council of the UK; Opticon; Strasbourg Observatory; and the Universities of Groningen, Heidelberg and Sydney. The RAVE web site is at https://www.rave-survey. org. This work has made use of data from the European Space Agency (ESA) mission Gaia (http://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, http://www.cosmos.esa. int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. This work has also made use of data from Gaia-ESO based on data products from observations made with ESO Telescopes at the La Silla Paranal Observatory under programme ID 188.B-3002. FA is grateful for funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 800502 H2020-MSCA-IF-EF-2017. CC acknowledges support from DFG Grant CH1188/2-1 and from the ChETEC COST Action (CA16117)