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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Researchers worldwide are seeking to repurpose existing drugs or discover new drugs to counter the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A promising source of candidates for such studies is molecules that have been reported in the scientific literature to be drug-like in the context of viral research. However, this literature is too large for human review and features unusual vocabularies for which existing named entity recognition (NER) models are ineffective. We report here on a project that leverages both human and artificial intelligence to detect references to such molecules in free text. We present 1) a iterative model-in-the-loop method that makes judicious use of scarce human expertise in generating training data for a NER model, and 2) the application and evaluation of this method to the problem of identifying drug-like molecules in the COVID-19 Open Research Dataset Challenge (CORD-19) corpus of 198,875 papers. We show that by repeatedly presenting human labelers only with samples for which an evolving NER model is uncertain, our human-machine hybrid pipeline requires only modest amounts of non-expert human labeling time (tens of hours to label 1778 samples) to generate an NER model with an F-1 score of 80.5%—on par with that of non-expert humans—and when applied to CORD’19, identifies 10,912 putative drug-like molecules. This enriched the computational screening team’s targets by 3,591 molecules, of which 18 ranked in the top 0.1% of all 6.6 million molecules screened for docking against the 3CLPro protein.
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Non-numeric digital computer program using coordinate transformation in deriving equations of motion for particles in general orthogonal curvilinear system
Computer program converts print image tape files into six dot Braille cells, enabling a blind computer programmer to monitor and evaluate data generated by his own programs. The Braille output is printed 8 lines per inch.
Bibliography on graph theory and its applications
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Straightforward algorithm for converting context free grammars into pushdown-store automata
Graph theory and its applications - bibliography, supplement 1
Computer software designed to perform interval arithmetic is described. An interval is defined as the set of all real numbers between two given numbers including or excluding one or both endpoints. Interval arithmetic consists of the various elementary arithmetic operations defined on the set of all intervals, such as interval addition, subtraction, union, etc. One of the main applications of interval arithmetic is in the area of error analysis of computer calculations. For example, it has been used sucessfully to compute bounds on sounding errors in the solution of linear algebraic systems, error bounds in numerical solutions of ordinary differential equations, as well as integral equations and boundary value problems. The described software enables users to implement algorithms of the type described in references efficiently on the IBM 360 system.
A compiler for recognizing statements of a FORTRAN program which are suited for fast execution on a parallel or pipeline machine such as Illiac-4, Star or ASC is described. The technique employs interval analysis to provide flow information to the vector/parallel recognizer. Where profitable the compiler changes scalar variables to subscripted variables. The output of the compiler is an extension to FORTRAN which shows parallel and vector operations explicitly.
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HAL accomplishes three significant objectives: (1) increased readability, through the use of a natural two-dimensional mathematical format; (2) increased reliability, by providing for selective recognition of common data and subroutines, and by incorporating specific data-protect features; (3) real-time control facility, by including a comprehensive set of real-time control commands and signal conditions. Although HAL is designed primarily for programming on-board computers, it is general enough to meet nearly all the needs in the production, verification and support of aerospace, and other real-time applications.
This specification identifies and describes the principal functions and elements of the Interpretive Code Translator which has been developed for use with the GOAL Compiler. This translator enables the user to convert a compliled GOAL program to a highly general binary format which is designed to enable interpretive execution. The translator program provides user controls which are designed to enable the selection of various output types and formats. These controls provide a means for accommodating many of the implementation options which are discussed in the Interpretive Code Guideline document. The technical design approach is given. The relationship between the translator and the GOAL compiler is explained and the principal functions performed by the Translator are described. Specific constraints regarding the use of the Translator are discussed. The control options are described. These options enable the user to select outputs to be generated by the translator and to control vrious aspects of the translation processing.
Data and analyses related to a variety of algorithms for solving typical large-scale scheduling and resource allocation problems are presented. The capabilities and deficiencies of various alternative problem solving strategies are discussed from the viewpoint of computer system design.