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Author (up) openurl 
  Title Methanol Worked Examples for the TEA and LCA Guidelines for CO2 Utilization Type Report
  Year 2018 Publication Abbreviated Journal  
  Volume Issue Pages  
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  Corporate Author Thesis  
  Publisher Global CO2 Initiative@UM Place of Publication Editor  
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  Notes Approved no  
  Call Number refbase @ user @ MethanolWorkedExamples2018 Serial 17675  
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Author (up) openurl 
  Title Water-Gas Shift Reaction Type Journal Article
  Year 2018 Publication Wikipedia Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract The water-gas shift reaction (WGSR) describes the reaction of carbon monoxide and water vapor to form carbon dioxide and hydrogen (the mixture of carbon monoxide and hydrogen (not water) is known as water gas): CO + H2O $\rightleftharpoons$ CO2 + H2The water gas shift reaction was discovered by Italian physicist Felice Fontana in 1780. It was not until much later that the industrial value of this reaction was realized. Before the early 20th century, hydrogen was obtained by reacting steam under high pressure with iron to produce iron, iron oxide and hydrogen. With the development of industrial processes that required hydrogen, such as the Haber Bosch ammonia synthesis, a less expensive and more efficient method of hydrogen production was needed. As a resolution to this problem, the WGSR was combined with the gasification of coal to produce a pure hydrogen product. As the idea of hydrogen economy gains popularity, the focus on hydrogen as a replacement fuel source for hydrocarbons is increasing.  
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  Notes Approved no  
  Call Number refbase @ user @ WatergasShiftReaction2018 Serial 17728  
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Author (up) url  openurl
  Title Algorithmic Accountability Policy Toolkit Type Miscellaneous
  Year 2018 Publication Abbreviated Journal  
  Volume Issue Pages  
  Keywords algorithm, deep learning, artificial intelligence, AI, accountability, toolkit  
  Abstract Algorithms are widely used in society to make decisions that affect most aspects of our lives, including which school a child can attend, whether a person will be offered credit from a bank, what products are advertised to consumers, and whether someone will receive an interview for a job. Federal, state and local governments are increasingly using algorithms to conduct government services. Algorithmic systems are used to make decisions about government resource allocation (e.g. where fire stations are built or where police are dispatched), expedite government procedures (e.g. public benefits eligibility and compliance), and aid government officials in making important decisions like whether a person will receive bail or a family will receive a follow up visit from a child welfare agency. Despite the importance of these uses and decisions, government agencies frequently procure, develop, and implement algorithmic systems with minimal to no transparency, public notice, community input, oversight, or accountability measures. Procurement officers and agency staff often lack technical expertise to evaluate algorithmic systems, their capabilities, and potential consequences. This creates a knowledge imbalance in contracting, particularly because many algorithmic systems vendors almost exclusively sell to government agencies. Consequently, vendors are able to oversell the utility and value of a system or offer the system at reduced costs, which is difficult for resource constrained agencies to turn down. Algorithms are fallible human creations, so they are embedded with errors and bias like human processes. When algorithmic tools are adopted by government agencies without adequate transparency, accountability, and oversight, their use can threaten civil liberties and exacerbate existing issues within government agencies (e.g. bias, inefficiencies, opacity regarding decision making). We know that federal, state and local governments are increasingly implementing algorithmic systems in their daily practices, but we still do not know how widespread and integrated such algorithmic systems are used at any level of government. The following toolkit is intended to provide legal and policy advocates with a basic understanding of government use of algorithms including, a breakdown of key concepts and questions that may come up when engaging with this issue, an overview of existing research, and summaries of algorithmic systems currently used in government. This toolkit also includes resources for advocates interested in or currently engaged in work to uncover where algorithms are being used and to create transparency and accountability mechanisms.  
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  Notes Approved no  
  Call Number refbase @ admin @ ainow_althorithmic_2018 Serial 17423  
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Author (up) Aydemir, F.B.\csak; Dalpiaz, F.; Brinkkemper, S.; Giorgini, P.; Mylopoulos, J. openurl 
  Title The Next Release Problem Revisited: A New Avenue for Goal Models Type Conference Article
  Year 2018 Publication Proceedings of the 26th IEEE International Requirements Engineering Conference (RE18) Abbreviated Journal  
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  Publisher Ieee Place of Publication Editor  
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  Notes Invited for special issue \ding80 Approved no  
  Call Number refbase @ admin @ AydeDalpBrinGior2018 Serial 17579  
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Author (up) Bardies, M. openurl 
  Title [I182] Dosimetry in radiopharmaceutical therapy Type Journal Article
  Year 2018 Publication Physica Medica: European Journal of Medical Physics Abbreviated Journal  
  Volume 52 Issue Pages 70  
  Keywords nuclear1  
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  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1120-1797 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number refbase @ admin @ Serial 17557  
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