177 research outputs found

    Heat Flux-Based Emissivity Measurement

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    A method for measuring the emissivity of a surface using heat flux sensors is described. The emissivity is calculated by directly measuring the heat flux passing through the surface using a heat flux sensor. Unlike calorimetric techniques, it does not require accounting for parasitic heat losses or knowing the temperature history of the sample. This technique allows emissivity measurements of newly developed variable emissivity surfaces, including electrostatic devices which cannot be directly measured using optical techniques. It can measure both passive and active thermal control coatings, and can evaluate many surfaces on the same substrate simultaneously. An experimental setup is detailed and results are presented for emissivity measurements of both active and passive surfaces using commercially available heat flux sensors. Errors are estimated for these measurements. A space-based experiment is also described and results of pre-flight testing are presented

    Storing the wisdom: chemical concepts and chemoinformatics

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    The purpose of the paper is to examine the nature of chemical concepts, and the ways in which they are applied in chemoinformatics systems. An account of concepts in philosophy and in the information sciences leads to an analysis of chemical concepts, and their representation. The way in which concepts are applied in systems for information retrieval and for structure–property correlation are reviewed, and some issues noted. Attention is focused on the basic concepts or substance, reaction and property, on the organising concepts of chemical structure, structural similarity, periodicity, and on more specific concepts, including two- and three-dimensional structural patterns, reaction types, and property concepts. It is concluded that chemical concepts, despite (or perhaps because of) their vague and mutable nature, have considerable and continuing value in chemoinformatics, and that an increased formal treatment of concepts may have value in the future

    Cognitive Information Processing

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    Contains reports on three research projects.National Science Foundation (Grant GP-2495)National Institutes of Health (Grant MH-04737-04)National Aeronautics and Space Administration (Grant NsG-496

    Integration of EndNote Online in information literacy instruction designed for small and large chemistry courses

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    The blended model for information literacy instruction described in this article introduces students not only to efficient techniques for finding scientific literature and properties of chemical compounds, but also to managing this information with a bibliographic management program (EndNote Online). The model blends face-to-face instruction with online tutorials posted on a LibGuide page prepared for each course. A graded online assignment designed in SurveyMonkey was used to assess student learning. During the instruction, students learned to find literature in Google Scholar, PubMed, Scopus, SciFinder, and Web of Science. They also searched for properties of chemical compounds in ChemSpider, PubChem, Reaxys, and SciFinder using a chemical name, molecular formula, CAS Registry Number, or by drawing a molecular structure. The results from the assignments showed that students learned how to find literature and chemical property information efficiently and use a bibliographic management program to store, organize, share, and cite references. This article presents the implementation of the model in two small (40–60 students) and one large (380–460 students) undergraduate chemistry courses. The information literacy instruction described in this article was carried out in more than 20 undergraduate and graduate courses at the University of Maryland College Park. It provided more than 5000 students with versatile skills that they can use throughout their college education and even later in their professional life. The design of the model and its implementation was a result of a close collaboration between the chemistry librarian and the course instructors

    Comparing Novice and Expert User Inputs in Early Stage Product Design

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    Abstract: This research examines similarities and differences between expert and novice user inputs during early stage concept design and ideation. Using a mixed-methods approach, we obtained and analyzed user inputs from 18 nurses (9 novices and 9 experts) for the design of an intramuscular drug delivery system. Users completed semi-structured interviews and two questionnaires to document design inputs through written and oral descriptions, and to rank their top five design requirements. We coded design inputs per the categories of nurse safety, patient safety, usability, and functionality, and used Pearson's Chi-squared analysis to test for independence between the novice and expert groups. The data illustrate a significant difference in the frequency of usability and functionality requirements between the two user groups. Novice users cited requirements associated with product usability over two times as often as did expert users (39.4% vs. 17.1%); and experts cited requirements associated with product functionality over two times as often as did novices (35.4% vs. 16.7%). For the design of complex systems, this research captures the unique contributions that novice and expert users make to the design process, and highlights the importance of considering potential user input biases during early stage design

    Information retrieval and text mining technologies for chemistry

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    Efficient access to chemical information contained in scientific literature, patents, technical reports, or the web is a pressing need shared by researchers and patent attorneys from different chemical disciplines. Retrieval of important chemical information in most cases starts with finding relevant documents for a particular chemical compound or family. Targeted retrieval of chemical documents is closely connected to the automatic recognition of chemical entities in the text, which commonly involves the extraction of the entire list of chemicals mentioned in a document, including any associated information. In this Review, we provide a comprehensive and in-depth description of fundamental concepts, technical implementations, and current technologies for meeting these information demands. A strong focus is placed on community challenges addressing systems performance, more particularly CHEMDNER and CHEMDNER patents tasks of BioCreative IV and V, respectively. Considering the growing interest in the construction of automatically annotated chemical knowledge bases that integrate chemical information and biological data, cheminformatics approaches for mapping the extracted chemical names into chemical structures and their subsequent annotation together with text mining applications for linking chemistry with biological information are also presented. Finally, future trends and current challenges are highlighted as a roadmap proposal for research in this emerging field.A.V. and M.K. acknowledge funding from the European Community’s Horizon 2020 Program (project reference: 654021 - OpenMinted). M.K. additionally acknowledges the Encomienda MINETAD-CNIO as part of the Plan for the Advancement of Language Technology. O.R. and J.O. thank the Foundation for Applied Medical Research (FIMA), University of Navarra (Pamplona, Spain). This work was partially funded by Consellería de Cultura, Educación e Ordenación Universitaria (Xunta de Galicia), and FEDER (European Union), and the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684). We thank Iñigo Garciá -Yoldi for useful feedback and discussions during the preparation of the manuscript.info:eu-repo/semantics/publishedVersio

    Thermal Conductivity of Ordered Mesoporous Nanocrystalline Silicon Thin Films Made from Magnesium Reduction of Polymer-Templated Silica

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    This paper reports the cross-plane thermal conductivity of ordered mesoporous nanocrystalline silicon thin films between 25 and 315 K. The films were produced by evaporation induced self-assembly of mesoporous silica followed by magnesium reduction. The periodic ordering of pores in mesoporous silicon was characterized by X-ray diffraction and direct SEM imaging. The average crystallite size, porosity, and film thickness were about 13 nm, 25-35%, and 140-340 nm, respectively. The pores were arranged in a face-centered cubic lattice. The cross-plane thermal conductivity of the mesoporous silicon thin films was measured using the 3ω method. It was between 3 and 5 orders of magnitude smaller than that of bulk single crystal silicon in the temperature range considered. The effects of temperature, film thickness, and copolymer template on the thermal conductivity were investigated. A model based on kinetic theory was used to accurately predict the measured thermal conductivity for all temperatures. On the one hand, both the measured thermal conductivity and the model predictions showed a temperature dependence of k proportional to T2 at low temperatures, typical of amorphous and strongly disordered materials. On the other hand, at high temperatures the thermal conductivity of mesoporous silicon films reached a maximum, indicating a crystalline-like behavior. These results will be useful in designing mesoporous silicon with desired thermal conductivity by tuning its morphology for various applications
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