Cognitive Information Processing

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

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

Information retrieval and text mining technologies for chemistry

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

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

Paleotemperature Proxies from Leaf Fossils Reinterpreted in Light of Evolutionary History

Present-day correlations between leaf physiognomic traits (shape and size) and climate are widely used to estimate paleoclimate using fossil floras. For example, leaf-margin analysis estimates paleotemperature using the modern relation of mean annual temperature (MAT) and the site-proportion of untoothed-leaf species (NT). This uniformitarian approach should provide accurate paleoclimate reconstructions under the core assumption that leaf-trait variation principally results from adaptive environmental convergence, and because variation is thus largely independent of phylogeny it should be constant through geologic time. Although much research acknowledges and investigates possible pitfalls in paleoclimate estimation based on leaf physiognomy, the core assumption has never been explicitly tested in a phylogenetic comparative framework. Combining an extant dataset of 21 leaf traits and temperature with a phylogenetic hypothesis for 569 species-site pairs at 17 sites, we found varying amounts of non-random phylogenetic signal in all traits. Phylogenetic vs. standard regressions generally support prevailing ideas that leaf-traits are adaptively responding to temperature, but wider confidence intervals, and shifts in slope and intercept, indicate an overall reduced ability to predict climate precisely due to the non-random phylogenetic signal. Notably, the modern-day relation of proportion of untoothed taxa with mean annual temperature (NT-MAT), central in paleotemperature inference, was greatly modified and reduced, indicating that the modern correlation primarily results from biogeographic history. Importantly, some tooth traits, such as number of teeth, had similar or steeper slopes after taking phylogeny into account, suggesting that leaf teeth display a pattern of exaptive evolution in higher latitudes. This study shows that the assumption of convergence required for precise, quantitative temperature estimates using present-day leaf traits is not supported by empirical evidence, and thus we have very low confidence in previously published, numerical paleotemperature estimates. However, interpreting qualitative changes in paleotemperature remains warranted, given certain conditions such as stratigraphically closely-spaced samples with floristic continuity

Environmental benefits of implementing alternative energy technologies in developing countries

During the early stages of industrialization, developed nations such as the United States did not foresee the extensive damage that would be done to the global environment by continued reliance on fossil fuels. As environmentally-friendly technologies become more feasible, efforts are being made to find ways to replace fossil fuels with more environmentally-friendly alternatives. However, industrialized countries have faced difficulties in converting their already-established infrastructures due to the time, effort, and cost involved. Implementing renewable-energy technologies in developing countries in the early stages of industrialization will avoid these obstacles. China and India are among the most populous and rapidly-developing countries. Therefore, employing renewable energy resources in these regions will have significant environmental and economic benefits and provide a model for other countries to follow.Pollution Developing countries Alternative energy