WorldWideScience

Sample records for enhance knowledge discovery

  1. Enhancing Big Data Value Using Knowledge Discovery Techniques

    OpenAIRE

    Mai Abdrabo; Mohammed Elmogy; Ghada Eltaweel; Sherif Barakat

    2016-01-01

    The world has been drowned by floods of data due to technological development. Consequently, the Big Data term has gotten the expression to portray the gigantic sum. Different sorts of quick data are doubling every second. We have to profit from this enormous surge of data to convert it to knowledge. Knowledge Discovery (KDD) can enhance detecting the value of Big Data based on some techniques and technologies like Hadoop, MapReduce, and NoSQL. The use of Big D...

  2. Enhancing knowledge discovery from cancer genomics data with Galaxy.

    Science.gov (United States)

    Albuquerque, Marco A; Grande, Bruno M; Ritch, Elie J; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K; Shah, Sohrab P; Boutros, Paul C; Morin, Ryan D

    2017-05-01

    The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. © The Author 2017. Published by Oxford University Press.

  3. RHSEG and Subdue: Background and Preliminary Approach for Combining these Technologies for Enhanced Image Data Analysis, Mining and Knowledge Discovery

    Science.gov (United States)

    Tilton, James C.; Cook, Diane J.

    2008-01-01

    Under a project recently selected for funding by NASA's Science Mission Directorate under the Applied Information Systems Research (AISR) program, Tilton and Cook will design and implement the integration of the Subdue graph based knowledge discovery system, developed at the University of Texas Arlington and Washington State University, with image segmentation hierarchies produced by the RHSEG software, developed at NASA GSFC, and perform pilot demonstration studies of data analysis, mining and knowledge discovery on NASA data. Subdue represents a method for discovering substructures in structural databases. Subdue is devised for general-purpose automated discovery, concept learning, and hierarchical clustering, with or without domain knowledge. Subdue was developed by Cook and her colleague, Lawrence B. Holder. For Subdue to be effective in finding patterns in imagery data, the data must be abstracted up from the pixel domain. An appropriate abstraction of imagery data is a segmentation hierarchy: a set of several segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. The RHSEG program, a recursive approximation to a Hierarchical Segmentation approach (HSEG), can produce segmentation hierarchies quickly and effectively for a wide variety of images. RHSEG and HSEG were developed at NASA GSFC by Tilton. In this presentation we provide background on the RHSEG and Subdue technologies and present a preliminary analysis on how RHSEG and Subdue may be combined to enhance image data analysis, mining and knowledge discovery.

  4. Enhancements to knowledge discovery framework of SOPHIA textual case-based reasoning

    Directory of Open Access Journals (Sweden)

    Islam Elhalwany

    2014-11-01

    This paper contributes to propose enhancements to SOPHIA approach that aims to enhance the retrieval efficiency and increase the precision degree. It also aimed to grantee that all results will have the same subject of the user query. The enhancements include performing an automatic classification to the case-base before the clustering step in the indexing stage, and include performing an automatic classification to the user query before the retrieval stage. Moreover, proofing that SOPHIA approach is a domain and language independent by applying it in the domain of Islamic jurisprudence in Arabic language.

  5. Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology.

    Science.gov (United States)

    Lovering, Ruth C; Roncaglia, Paola; Howe, Douglas G; Laulederkind, Stanley J F; Khodiyar, Varsha K; Berardini, Tanya Z; Tweedie, Susan; Foulger, Rebecca E; Osumi-Sutherland, David; Campbell, Nancy H; Huntley, Rachael P; Talmud, Philippa J; Blake, Judith A; Breckenridge, Ross; Riley, Paul R; Lambiase, Pier D; Elliott, Perry M; Clapp, Lucie; Tinker, Andrew; Hill, David P

    2018-02-01

    A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. © 2018 The Authors.

  6. Knowledge discovery from data streams

    CERN Document Server

    Gama, Joao

    2010-01-01

    Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents a coherent overview of state-of-the-art research in learning from data streams.The book covers the fundamentals that are imperative to understanding data streams and describes important applications, such as TCP/IP traffic, GPS data, sensor networks,

  7. Rough – Granular Computing knowledge discovery models

    Directory of Open Access Journals (Sweden)

    Mohammed M. Eissa

    2016-11-01

    Full Text Available Medical domain has become one of the most important areas of research in order to richness huge amounts of medical information about the symptoms of diseases and how to distinguish between them to diagnose it correctly. Knowledge discovery models play vital role in refinement and mining of medical indicators to help medical experts to settle treatment decisions. This paper introduces four hybrid Rough – Granular Computing knowledge discovery models based on Rough Sets Theory, Artificial Neural Networks, Genetic Algorithm and Rough Mereology Theory. A comparative analysis of various knowledge discovery models that use different knowledge discovery techniques for data pre-processing, reduction, and data mining supports medical experts to extract the main medical indicators, to reduce the misdiagnosis rates and to improve decision-making for medical diagnosis and treatment. The proposed models utilized two medical datasets: Coronary Heart Disease dataset and Hepatitis C Virus dataset. The main purpose of this paper was to explore and evaluate the proposed models based on Granular Computing methodology for knowledge extraction according to different evaluation criteria for classification of medical datasets. Another purpose is to make enhancement in the frame of KDD processes for supervised learning using Granular Computing methodology.

  8. Knowledge Discovery from Vibration Measurements

    Directory of Open Access Journals (Sweden)

    Jun Deng

    2014-01-01

    Full Text Available The framework as well as the particular algorithms of pattern recognition process is widely adopted in structural health monitoring (SHM. However, as a part of the overall process of knowledge discovery from data bases (KDD, the results of pattern recognition are only changes and patterns of changes of data features. In this paper, based on the similarity between KDD and SHM and considering the particularity of SHM problems, a four-step framework of SHM is proposed which extends the final goal of SHM from detecting damages to extracting knowledge to facilitate decision making. The purposes and proper methods of each step of this framework are discussed. To demonstrate the proposed SHM framework, a specific SHM method which is composed by the second order structural parameter identification, statistical control chart analysis, and system reliability analysis is then presented. To examine the performance of this SHM method, real sensor data measured from a lab size steel bridge model structure are used. The developed four-step framework of SHM has the potential to clarify the process of SHM to facilitate the further development of SHM techniques.

  9. Knowledge discovery in the prediction of bankruptcy

    NARCIS (Netherlands)

    Almeida, R.J.; Vieira, S.M.; Milea, D.V.; Kaymak, U.; Costa Sousa, da J.M.; Carvalho, J.P.; Dubois, D.; Kaymak, U.

    2009-01-01

    Knowledge discovery in databases (KDD) is the process of discovering interesting knowledge from large amounts of data. However, real-world datasets have problems such as incompleteness, redundancy, inconsistency, noise, etc. All these problems affect the performance of data mining algorithms. Thus,

  10. Knowledge management and Discovery for advanced Enterprise Knowledge Engineering

    OpenAIRE

    Novi, Daniele

    2014-01-01

    2012 - 2013 The research work addresses mainly issues related to the adoption of models, methodologies and knowledge management tools that implement a pervasive use of the latest technologies in the area of Semantic Web for the improvement of business processes and Enterprise 2.0 applications. The first phase of the research has focused on the study and analysis of the state of the art and the problems of Knowledge Discovery database, paying more attention to the data mining systems. Th...

  11. Bioenergy Knowledge Discovery Framework Fact Sheet

    Energy Technology Data Exchange (ETDEWEB)

    None

    2017-07-01

    The Bioenergy Knowledge Discovery Framework (KDF) supports the development of a sustainable bioenergy industry by providing access to a variety of data sets, publications, and collaboration and mapping tools that support bioenergy research, analysis, and decision making. In the KDF, users can search for information, contribute data, and use the tools and map interface to synthesize, analyze, and visualize information in a spatially integrated manner.

  12. Knowledge Discovery in Data in Construction Projects

    Directory of Open Access Journals (Sweden)

    Szelka J.

    2016-06-01

    Full Text Available Decision-making processes, including the ones related to ill-structured problems, are of considerable significance in the area of construction projects. Computer-aided inference under such conditions requires the employment of specific methods and tools (non-algorithmic ones, the best recognized and successfully used in practice represented by expert systems. The knowledge indispensable for such systems to perform inference is most frequently acquired directly from experts (through a dialogue: a domain expert - a knowledge engineer and from various source documents. Little is known, however, about the possibility of automating knowledge acquisition in this area and as a result, in practice it is scarcely ever used. It has to be noted that in numerous areas of management more and more attention is paid to the issue of acquiring knowledge from available data. What is known and successfully employed in the practice of aiding the decision-making is the different methods and tools. The paper attempts to select methods for knowledge discovery in data and presents possible ways of representing the acquired knowledge as well as sample tools (including programming ones, allowing for the use of this knowledge in the area under consideration.

  13. Advances in knowledge discovery in databases

    CERN Document Server

    Adhikari, Animesh

    2015-01-01

    This book presents recent advances in Knowledge discovery in databases (KDD) with a focus on the areas of market basket database, time-stamped databases and multiple related databases. Various interesting and intelligent algorithms are reported on data mining tasks. A large number of association measures are presented, which play significant roles in decision support applications. This book presents, discusses and contrasts new developments in mining time-stamped data, time-based data analyses, the identification of temporal patterns, the mining of multiple related databases, as well as local patterns analysis.  

  14. Enhancement and knowledge

    Directory of Open Access Journals (Sweden)

    Cinzia Talamo

    2012-04-01

    Full Text Available Many issues related to enhancement strategies emerge nowadays both from the scenario offered by public real estates and from the current processes of conveyance of public assets to local authorities. On one hand it is still difficult, from a strategic point of view, to approach in the medium-long term the chronic problems of the public estates due to deterioration, obsolescence and organizational inadequacy. On the other hand there is the risk that inadequate levels of knowledge lead on one side to a prevalence of the binomial enhancement-alienation and on the other side to a lack of full comprehension of the actual potentialities of the existing assets. In this direction it is possible to analyze the topic of enhancement through, among many, the key of knowledge during the lifecycle of a building.

  15. Asymmetric threat data mining and knowledge discovery

    Science.gov (United States)

    Gilmore, John F.; Pagels, Michael A.; Palk, Justin

    2001-03-01

    Asymmetric threats differ from the conventional force-on- force military encounters that the Defense Department has historically been trained to engage. Terrorism by its nature is now an operational activity that is neither easily detected or countered as its very existence depends on small covert attacks exploiting the element of surprise. But terrorism does have defined forms, motivations, tactics and organizational structure. Exploiting a terrorism taxonomy provides the opportunity to discover and assess knowledge of terrorist operations. This paper describes the Asymmetric Threat Terrorist Assessment, Countering, and Knowledge (ATTACK) system. ATTACK has been developed to (a) data mine open source intelligence (OSINT) information from web-based newspaper sources, video news web casts, and actual terrorist web sites, (b) evaluate this information against a terrorism taxonomy, (c) exploit country/region specific social, economic, political, and religious knowledge, and (d) discover and predict potential terrorist activities and association links. Details of the asymmetric threat structure and the ATTACK system architecture are presented with results of an actual terrorist data mining and knowledge discovery test case shown.

  16. Energy-Water Nexus Knowledge Discovery Framework

    Science.gov (United States)

    Bhaduri, B. L.; Foster, I.; Chandola, V.; Chen, B.; Sanyal, J.; Allen, M.; McManamay, R.

    2017-12-01

    As demand for energy grows, the energy sector is experiencing increasing competition for water. With increasing population and changing environmental, socioeconomic scenarios, new technology and investment decisions must be made for optimized and sustainable energy-water resource management. This requires novel scientific insights into the complex interdependencies of energy-water infrastructures across multiple space and time scales. An integrated data driven modeling, analysis, and visualization capability is needed to understand, design, and develop efficient local and regional practices for the energy-water infrastructure components that can be guided with strategic (federal) policy decisions to ensure national energy resilience. To meet this need of the energy-water nexus (EWN) community, an Energy-Water Knowledge Discovery Framework (EWN-KDF) is being proposed to accomplish two objectives: Development of a robust data management and geovisual analytics platform that provides access to disparate and distributed physiographic, critical infrastructure, and socioeconomic data, along with emergent ad-hoc sensor data to provide a powerful toolkit of analysis algorithms and compute resources to empower user-guided data analysis and inquiries; and Demonstration of knowledge generation with selected illustrative use cases for the implications of climate variability for coupled land-water-energy systems through the application of state-of-the art data integration, analysis, and synthesis. Oak Ridge National Laboratory (ORNL), in partnership with Argonne National Laboratory (ANL) and researchers affiliated with the Center for International Earth Science Information Partnership (CIESIN) at Columbia University and State University of New York-Buffalo (SUNY), propose to develop this Energy-Water Knowledge Discovery Framework to generate new, critical insights regarding the complex dynamics of the EWN and its interactions with climate variability and change. An overarching

  17. Developing integrated crop knowledge networks to advance candidate gene discovery.

    Science.gov (United States)

    Hassani-Pak, Keywan; Castellote, Martin; Esch, Maria; Hindle, Matthew; Lysenko, Artem; Taubert, Jan; Rawlings, Christopher

    2016-12-01

    The chances of raising crop productivity to enhance global food security would be greatly improved if we had a complete understanding of all the biological mechanisms that underpinned traits such as crop yield, disease resistance or nutrient and water use efficiency. With more crop genomes emerging all the time, we are nearer having the basic information, at the gene-level, to begin assembling crop gene catalogues and using data from other plant species to understand how the genes function and how their interactions govern crop development and physiology. Unfortunately, the task of creating such a complete knowledge base of gene functions, interaction networks and trait biology is technically challenging because the relevant data are dispersed in myriad databases in a variety of data formats with variable quality and coverage. In this paper we present a general approach for building genome-scale knowledge networks that provide a unified representation of heterogeneous but interconnected datasets to enable effective knowledge mining and gene discovery. We describe the datasets and outline the methods, workflows and tools that we have developed for creating and visualising these networks for the major crop species, wheat and barley. We present the global characteristics of such knowledge networks and with an example linking a seed size phenotype to a barley WRKY transcription factor orthologous to TTG2 from Arabidopsis, we illustrate the value of integrated data in biological knowledge discovery. The software we have developed (www.ondex.org) and the knowledge resources (http://knetminer.rothamsted.ac.uk) we have created are all open-source and provide a first step towards systematic and evidence-based gene discovery in order to facilitate crop improvement.

  18. Rule Induction-Based Knowledge Discovery for Energy Efficiency

    OpenAIRE

    Chen, Qipeng; Fan, Zhong; Kaleshi, Dritan; Armour, Simon M D

    2015-01-01

    Rule induction is a practical approach to knowledge discovery. Provided that a problem is developed, rule induction is able to return the knowledge that addresses the goal of this problem as if-then rules. The primary goals of knowledge discovery are for prediction and description. The rule format knowledge representation is easily understandable so as to enable users to make decisions. This paper presents the potential of rule induction for energy efficiency. In particular, three rule induct...

  19. Discovery simulations and the assessment of intuitive knowledge

    NARCIS (Netherlands)

    Swaak, Janine; de Jong, Anthonius J.M.

    2001-01-01

    The objective of the present work is to have a closer look at the relations between the features of discovery simulations, the learning processes elicited, the knowledge that results, and the methods used to measure this acquired knowledge. It is argued that discovery simulations are ‘rich’, have a

  20. Semantic Approaches for Knowledge Discovery and Retrieval in Biomedicine

    DEFF Research Database (Denmark)

    Wilkowski, Bartlomiej

    This thesis discusses potential applications of semantics to the recent literaturebased informatics systems to facilitate knowledge discovery, hypothesis generation, and literature retrieval in the domain of biomedicine. The approaches presented herein make use of semantic information extracted...

  1. 08471 Report -- Geographic Privacy-Aware Knowledge Discovery and Delivery

    OpenAIRE

    Kuijpers, Bart; Pedreschi, Dino; Saygin, Yucel; Spaccapietra, Stefano

    2009-01-01

    The Dagstuhl-Seminar on Geographic Privacy-Aware Knowledge Discovery and Delivery was held during 16 - 21 November, 2008, with 37 participants registered from various countries from Europe, as well as other parts of the world such as United States, Canada, Argentina, and Brazil. Issues in the newly emerging area of geographic knowledge discovery with a privacy perspective were discussed in a week to consolidate some of the research questions. The Dagstuhl program included...

  2. Data mining and knowledge discovery technologies

    National Research Council Canada - National Science Library

    Taniar, David

    2008-01-01

    "This book presents researchers and practitioners in fields such as knowledge management, information science, Web engineering, and medical informatics, with comprehensive, innovative research on data...

  3. Concept Formation in Scientific Knowledge Discovery from a Constructivist View

    Science.gov (United States)

    Peng, Wei; Gero, John S.

    The central goal of scientific knowledge discovery is to learn cause-effect relationships among natural phenomena presented as variables and the consequences their interactions. Scientific knowledge is normally expressed as scientific taxonomies and qualitative and quantitative laws [1]. This type of knowledge represents intrinsic regularities of the observed phenomena that can be used to explain and predict behaviors of the phenomena. It is a generalization that is abstracted and externalized from a set of contexts and applicable to a broader scope. Scientific knowledge is a type of third-person knowledge, i.e., knowledge that independent of a specific enquirer. Artificial intelligence approaches, particularly data mining algorithms that are used to identify meaningful patterns from large data sets, are approaches that aim to facilitate the knowledge discovery process [2]. A broad spectrum of algorithms has been developed in addressing classification, associative learning, and clustering problems. However, their linkages to people who use them have not been adequately explored. Issues in relation to supporting the interpretation of the patterns, the application of prior knowledge to the data mining process and addressing user interactions remain challenges for building knowledge discovery tools [3]. As a consequence, scientists rely on their experience to formulate problems, evaluate hypotheses, reason about untraceable factors and derive new problems. This type of knowledge which they have developed during their career is called "first-person" knowledge. The formation of scientific knowledge (third-person knowledge) is highly influenced by the enquirer's first-person knowledge construct, which is a result of his or her interactions with the environment. There have been attempts to craft automatic knowledge discovery tools but these systems are limited in their capabilities to handle the dynamics of personal experience. There are now trends in developing

  4. Biomarker Gene Signature Discovery Integrating Network Knowledge

    Directory of Open Access Journals (Sweden)

    Holger Fröhlich

    2012-02-01

    Full Text Available Discovery of prognostic and diagnostic biomarker gene signatures for diseases, such as cancer, is seen as a major step towards a better personalized medicine. During the last decade various methods, mainly coming from the machine learning or statistical domain, have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinical diagnosis is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Here we review the current state of research in this field by giving an overview about so-far proposed approaches.

  5. Knowledge discovery with classification rules in a cardiovascular dataset.

    Science.gov (United States)

    Podgorelec, Vili; Kokol, Peter; Stiglic, Milojka Molan; Hericko, Marjan; Rozman, Ivan

    2005-12-01

    In this paper we study an evolutionary machine learning approach to data mining and knowledge discovery based on the induction of classification rules. A method for automatic rules induction called AREX using evolutionary induction of decision trees and automatic programming is introduced. The proposed algorithm is applied to a cardiovascular dataset consisting of different groups of attributes which should possibly reveal the presence of some specific cardiovascular problems in young patients. A case study is presented that shows the use of AREX for the classification of patients and for discovering possible new medical knowledge from the dataset. The defined knowledge discovery loop comprises a medical expert's assessment of induced rules to drive the evolution of rule sets towards more appropriate solutions. The final result is the discovery of a possible new medical knowledge in the field of pediatric cardiology.

  6. Incremental Knowledge Discovery in Social Media

    Science.gov (United States)

    Tang, Xuning

    2013-01-01

    In light of the prosperity of online social media, Web users are shifting from data consumers to data producers. To catch the pulse of this rapidly changing world, it is critical to transform online social media data to information and to knowledge. This dissertation centers on the issue of modeling the dynamics of user communities, trending…

  7. A collaborative filtering-based approach to biomedical knowledge discovery.

    Science.gov (United States)

    Lever, Jake; Gakkhar, Sitanshu; Gottlieb, Michael; Rashnavadi, Tahereh; Lin, Santina; Siu, Celia; Smith, Maia; Jones, Martin R; Krzywinski, Martin; Jones, Steven J M; Wren, Jonathan

    2018-02-15

    The increase in publication rates makes it challenging for an individual researcher to stay abreast of all relevant research in order to find novel research hypotheses. Literature-based discovery methods make use of knowledge graphs built using text mining and can infer future associations between biomedical concepts that will likely occur in new publications. These predictions are a valuable resource for researchers to explore a research topic. Current methods for prediction are based on the local structure of the knowledge graph. A method that uses global knowledge from across the knowledge graph needs to be developed in order to make knowledge discovery a frequently used tool by researchers. We propose an approach based on the singular value decomposition (SVD) that is able to combine data from across the knowledge graph through a reduced representation. Using cooccurrence data extracted from published literature, we show that SVD performs better than the leading methods for scoring discoveries. We also show the diminishing predictive power of knowledge discovery as we compare our predictions with real associations that appear further into the future. Finally, we examine the strengths and weaknesses of the SVD approach against another well-performing system using several predicted associations. All code and results files for this analysis can be accessed at https://github.com/jakelever/knowledgediscovery. sjones@bcgsc.ca. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  8. 4th International conference on Knowledge Discovery and Data Mining

    CERN Document Server

    Knowledge Discovery and Data Mining

    2012-01-01

    The volume includes a set of selected papers extended and revised from the 4th International conference on Knowledge Discovery and Data Mining, March 1-2, 2011, Macau, Chin.   This Volume is to provide a forum for researchers, educators, engineers, and government officials involved in the general areas of knowledge discovery and data mining and learning to disseminate their latest research results and exchange views on the future research directions of these fields. 108 high-quality papers are included in the volume.

  9. Mandolin: A Knowledge Discovery Framework for the Web of Data

    OpenAIRE

    Soru, Tommaso; Esteves, Diego; Marx, Edgard; Ngomo, Axel-Cyrille Ngonga

    2017-01-01

    Markov Logic Networks join probabilistic modeling with first-order logic and have been shown to integrate well with the Semantic Web foundations. While several approaches have been devised to tackle the subproblems of rule mining, grounding, and inference, no comprehensive workflow has been proposed so far. In this paper, we fill this gap by introducing a framework called Mandolin, which implements a workflow for knowledge discovery specifically on RDF datasets. Our framework imports knowledg...

  10. Service-oriented discovery of knowledge : foundations, implementations and applications

    NARCIS (Netherlands)

    Bruin, Jeroen Sebastiaan de

    2010-01-01

    In this thesis we will investigate how a popular new way of distributed computing called service orientation can be used within the field of Knowledge Discovery. We critically investigate its principles and present models for developing withing this paradigm. We then apply this model to create a web

  11. Knowledge Discovery and Data Mining in Iran's Climatic Researches

    Science.gov (United States)

    Karimi, Mostafa

    2013-04-01

    Advances in measurement technology and data collection is the database gets larger. Large databases require powerful tools for analysis data. Iterative process of acquiring knowledge from information obtained from data processing is done in various forms in all scientific fields. However, when the data volume large, and many of the problems the Traditional methods cannot respond. in the recent years, use of databases in various scientific fields, especially atmospheric databases in climatology expanded. in addition, increases in the amount of data generated by the climate models is a challenge for analysis of it for extraction of hidden pattern and knowledge. The approach to this problem has been made in recent years uses the process of knowledge discovery and data mining techniques with the use of the concepts of machine learning, artificial intelligence and expert (professional) systems is overall performance. Data manning is analytically process for manning in massive volume data. The ultimate goal of data mining is access to information and finally knowledge. climatology is a part of science that uses variety and massive volume data. Goal of the climate data manning is Achieve to information from variety and massive atmospheric and non-atmospheric data. in fact, Knowledge Discovery performs these activities in a logical and predetermined and almost automatic process. The goal of this research is study of uses knowledge Discovery and data mining technique in Iranian climate research. For Achieve This goal, study content (descriptive) analysis and classify base method and issue. The result shown that in climatic research of Iran most clustering, k-means and wards applied and in terms of issues precipitation and atmospheric circulation patterns most introduced. Although several studies in geography and climate issues with statistical techniques such as clustering and pattern extraction is done, Due to the nature of statistics and data mining, but cannot say for

  12. Knowledge discovery in variant databases using inductive logic programming.

    Science.gov (United States)

    Nguyen, Hoan; Luu, Tien-Dao; Poch, Olivier; Thompson, Julie D

    2013-01-01

    Understanding the effects of genetic variation on the phenotype of an individual is a major goal of biomedical research, especially for the development of diagnostics and effective therapeutic solutions. In this work, we describe the use of a recent knowledge discovery from database (KDD) approach using inductive logic programming (ILP) to automatically extract knowledge about human monogenic diseases. We extracted background knowledge from MSV3d, a database of all human missense variants mapped to 3D protein structure. In this study, we identified 8,117 mutations in 805 proteins with known three-dimensional structures that were known to be involved in human monogenic disease. Our results help to improve our understanding of the relationships between structural, functional or evolutionary features and deleterious mutations. Our inferred rules can also be applied to predict the impact of any single amino acid replacement on the function of a protein. The interpretable rules are available at http://decrypthon.igbmc.fr/kd4v/.

  13. Scientific Knowledge Discovery in Complex Semantic Networks of Geophysical Systems

    Science.gov (United States)

    Fox, P.

    2012-04-01

    The vast majority of explorations of the Earth's systems are limited in their ability to effectively explore the most important (often most difficult) problems because they are forced to interconnect at the data-element, or syntactic, level rather than at a higher scientific, or semantic, level. Recent successes in the application of complex network theory and algorithms to climate data, raise expectations that more general graph-based approaches offer the opportunity for new discoveries. In the past ~ 5 years in the natural sciences there has substantial progress in providing both specialists and non-specialists the ability to describe in machine readable form, geophysical quantities and relations among them in meaningful and natural ways, effectively breaking the prior syntax barrier. The corresponding open-world semantics and reasoning provide higher-level interconnections. That is, semantics provided around the data structures, using semantically-equipped tools, and semantically aware interfaces between science application components allowing for discovery at the knowledge level. More recently, formal semantic approaches to continuous and aggregate physical processes are beginning to show promise and are soon likely to be ready to apply to geoscientific systems. To illustrate these opportunities, this presentation presents two application examples featuring domain vocabulary (ontology) and property relations (named and typed edges in the graphs). First, a climate knowledge discovery pilot encoding and exploration of CMIP5 catalog information with the eventual goal to encode and explore CMIP5 data. Second, a multi-stakeholder knowledge network for integrated assessments in marine ecosystems, where the data is highly inter-disciplinary.

  14. A knowledge discovery in databases approach for industrial microgrid planning

    DEFF Research Database (Denmark)

    Gamarra, Carlos; Guerrero, Josep M.; Montero, Eduardo

    2016-01-01

    The progressive application of Information and Communication Technologies to industrial processes has increased the amount of data gathered by manufacturing companies during last decades. Nowadays some standardized management systems, such as ISO 50.001 and ISO 14.001, exploit these data in order...... sustainable and proactive microgrid which allows identifying, designing and developing energy efficiency strategies at supply, management and energy use levels. In this context, the expansion of Internet of Things and Knowledge Discovery in Databases techniques will drive changes in current microgrid planning...

  15. A Metadata based Knowledge Discovery Methodology for Seeding Translational Research.

    Science.gov (United States)

    Kothari, Cartik R; Payne, Philip R O

    2015-01-01

    In this paper, we present a semantic, metadata based knowledge discovery methodology for identifying teams of researchers from diverse backgrounds who can collaborate on interdisciplinary research projects: projects in areas that have been identified as high-impact areas at The Ohio State University. This methodology involves the semantic annotation of keywords and the postulation of semantic metrics to improve the efficiency of the path exploration algorithm as well as to rank the results. Results indicate that our methodology can discover groups of experts from diverse areas who can collaborate on translational research projects.

  16. Data Mining and Knowledge Discovery via Logic-Based Methods

    CERN Document Server

    Triantaphyllou, Evangelos

    2010-01-01

    There are many approaches to data mining and knowledge discovery (DM&KD), including neural networks, closest neighbor methods, and various statistical methods. This monograph, however, focuses on the development and use of a novel approach, based on mathematical logic, that the author and his research associates have worked on over the last 20 years. The methods presented in the book deal with key DM&KD issues in an intuitive manner and in a natural sequence. Compared to other DM&KD methods, those based on mathematical logic offer a direct and often intuitive approach for extracting easily int

  17. Privacy-aware knowledge discovery novel applications and new techniques

    CERN Document Server

    Bonchi, Francesco

    2010-01-01

    Covering research at the frontier of this field, Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques presents state-of-the-art privacy-preserving data mining techniques for application domains, such as medicine and social networks, that face the increasing heterogeneity and complexity of new forms of data. Renowned authorities from prominent organizations not only cover well-established results-they also explore complex domains where privacy issues are generally clear and well defined, but the solutions are still preliminary and in continuous development. Divided into seve

  18. Knowledge discovery from structured mammography reports using inductive logic programming.

    Science.gov (United States)

    Burnside, Elizabeth S; Davis, Jesse; Costa, Victor Santos; Dutra, Inês de Castro; Kahn, Charles E; Fine, Jason; Page, David

    2005-01-01

    The development of large mammography databases provides an opportunity for knowledge discovery and data mining techniques to recognize patterns not previously appreciated. Using a database from a breast imaging practice containing patient risk factors, imaging findings, and biopsy results, we tested whether inductive logic programming (ILP) could discover interesting hypotheses that could subsequently be tested and validated. The ILP algorithm discovered two hypotheses from the data that were 1) judged as interesting by a subspecialty trained mammographer and 2) validated by analysis of the data itself.

  19. Network-based approaches to climate knowledge discovery

    Science.gov (United States)

    Budich, Reinhard; Nyberg, Per; Weigel, Tobias

    2011-11-01

    Climate Knowledge Discovery Workshop; Hamburg, Germany, 30 March to 1 April 2011 Do complex networks combined with semantic Web technologies offer the next generation of solutions in climate science? To address this question, a first Climate Knowledge Discovery (CKD) Workshop, hosted by the German Climate Computing Center (Deutsches Klimarechenzentrum (DKRZ)), brought together climate and computer scientists from major American and European laboratories, data centers, and universities, as well as representatives from industry, the broader academic community, and the semantic Web communities. The participants, representing six countries, were concerned with large-scale Earth system modeling and computational data analysis. The motivation for the meeting was the growing problem that climate scientists generate data faster than it can be interpreted and the need to prepare for further exponential data increases. Current analysis approaches are focused primarily on traditional methods, which are best suited for large-scale phenomena and coarse-resolution data sets. The workshop focused on the open discussion of ideas and technologies to provide the next generation of solutions to cope with the increasing data volumes in climate science.

  20. Semantically-enabled Knowledge Discovery in the Deep Carbon Observatory

    Science.gov (United States)

    Wang, H.; Chen, Y.; Ma, X.; Erickson, J. S.; West, P.; Fox, P. A.

    2013-12-01

    The Deep Carbon Observatory (DCO) is a decadal effort aimed at transforming scientific and public understanding of carbon in the complex deep earth system from the perspectives of Deep Energy, Deep Life, Extreme Physics and Chemistry, and Reservoirs and Fluxes. Over the course of the decade DCO scientific activities will generate a massive volume of data across a variety of disciplines, presenting significant challenges in terms of data integration, management, analysis and visualization, and ultimately limiting the ability of scientists across disciplines to make insights and unlock new knowledge. The DCO Data Science Team (DCO-DS) is applying Semantic Web methodologies to construct a knowledge representation focused on the DCO Earth science disciplines, and use it together with other technologies (e.g. natural language processing and data mining) to create a more expressive representation of the distributed corpus of DCO artifacts including datasets, metadata, instruments, sensors, platforms, deployments, researchers, organizations, funding agencies, grants and various awards. The embodiment of this knowledge representation is the DCO Data Science Infrastructure, in which unique entities within the DCO domain and the relations between them are recognized and explicitly identified. The DCO-DS Infrastructure will serve as a platform for more efficient and reliable searching, discovery, access, and publication of information and knowledge for the DCO scientific community and beyond.

  1. Knowledge Discovery and Pavement Performance : Intelligent Data Mining

    NARCIS (Netherlands)

    Miradi, M.

    2009-01-01

    The main goal of the study was to discover knowledge from data about asphalt road pavement problems to achieve a better understanding of the behavior of them and via this understanding improve pavement quality and enhance its lifespan. Four pavement problems were chosen to be investigated; raveling

  2. Plant Enhancers: A Call for Discovery

    NARCIS (Netherlands)

    Weber, B.; Zicola, J.; Oka, R.; Stam, M.

    2016-01-01

    Higher eukaryotes typically contain many different cell types, displaying different cellular functions that are influenced by biotic and abiotic cues. The different functions are characterized by specific gene expression patterns mediated by regulatory sequences such as transcriptional enhancers.

  3. Knowledge Discovery from Posts in Online Health Communities Using Unified Medical Language System

    Directory of Open Access Journals (Sweden)

    Donghua Chen

    2018-06-01

    Full Text Available Patient-reported posts in Online Health Communities (OHCs contain various valuable information that can help establish knowledge-based online support for online patients. However, utilizing these reports to improve online patient services in the absence of appropriate medical and healthcare expert knowledge is difficult. Thus, we propose a comprehensive knowledge discovery method that is based on the Unified Medical Language System for the analysis of narrative posts in OHCs. First, we propose a domain-knowledge support framework for OHCs to provide a basis for post analysis. Second, we develop a Knowledge-Involved Topic Modeling (KI-TM method to extract and expand explicit knowledge within the text. We propose four metrics, namely, explicit knowledge rate, latent knowledge rate, knowledge correlation rate, and perplexity, for the evaluation of the KI-TM method. Our experimental results indicate that our proposed method outperforms existing methods in terms of providing knowledge support. Our method enhances knowledge support for online patients and can help develop intelligent OHCs in the future.

  4. Text mining for traditional Chinese medical knowledge discovery: a survey.

    Science.gov (United States)

    Zhou, Xuezhong; Peng, Yonghong; Liu, Baoyan

    2010-08-01

    Extracting meaningful information and knowledge from free text is the subject of considerable research interest in the machine learning and data mining fields. Text data mining (or text mining) has become one of the most active research sub-fields in data mining. Significant developments in the area of biomedical text mining during the past years have demonstrated its great promise for supporting scientists in developing novel hypotheses and new knowledge from the biomedical literature. Traditional Chinese medicine (TCM) provides a distinct methodology with which to view human life. It is one of the most complete and distinguished traditional medicines with a history of several thousand years of studying and practicing the diagnosis and treatment of human disease. It has been shown that the TCM knowledge obtained from clinical practice has become a significant complementary source of information for modern biomedical sciences. TCM literature obtained from the historical period and from modern clinical studies has recently been transformed into digital data in the form of relational databases or text documents, which provide an effective platform for information sharing and retrieval. This motivates and facilitates research and development into knowledge discovery approaches and to modernize TCM. In order to contribute to this still growing field, this paper presents (1) a comparative introduction to TCM and modern biomedicine, (2) a survey of the related information sources of TCM, (3) a review and discussion of the state of the art and the development of text mining techniques with applications to TCM, (4) a discussion of the research issues around TCM text mining and its future directions. Copyright 2010 Elsevier Inc. All rights reserved.

  5. Accelerating knowledge discovery through community data sharing and integration.

    Science.gov (United States)

    Yip, Y L

    2009-01-01

    To summarize current excellent research in the field of bioinformatics. Synopsis of the articles selected for the IMIA Yearbook 2009. The selection process for this yearbook's section on Bioinformatics results in six excellent articles highlighting several important trends First, it can be noted that Semantic Web technology continues to play an important role in heterogeneous data integration. Novel applications also put more emphasis on its ability to make logical inferences leading to new insights and discoveries. Second, translational research, due to its complex nature, increasingly relies on collective intelligence made available through the adoption of community-defined protocols or software architectures for secure data annotation, sharing and analysis. Advances in systems biology, bio-ontologies and text-ming can also be noted. Current biomedical research gradually evolves towards an environment characterized by intensive collaboration and more sophisticated knowledge processing activities. Enabling technologies, either Semantic Web or other solutions, are expected to play an increasingly important role in generating new knowledge in the foreseeable future.

  6. Semi-automated knowledge discovery: identifying and profiling human trafficking

    Science.gov (United States)

    Poelmans, Jonas; Elzinga, Paul; Ignatov, Dmitry I.; Kuznetsov, Sergei O.

    2012-11-01

    We propose an iterative and human-centred knowledge discovery methodology based on formal concept analysis. The proposed approach recognizes the important role of the domain expert in mining real-world enterprise applications and makes use of specific domain knowledge, including human intelligence and domain-specific constraints. Our approach was empirically validated at the Amsterdam-Amstelland police to identify suspects and victims of human trafficking in 266,157 suspicious activity reports. Based on guidelines of the Attorney Generals of the Netherlands, we first defined multiple early warning indicators that were used to index the police reports. Using concept lattices, we revealed numerous unknown human trafficking and loverboy suspects. In-depth investigation by the police resulted in a confirmation of their involvement in illegal activities resulting in actual arrestments been made. Our human-centred approach was embedded into operational policing practice and is now successfully used on a daily basis to cope with the vastly growing amount of unstructured information.

  7. A knowledge discovery object model API for Java

    Directory of Open Access Journals (Sweden)

    Jones Steven JM

    2003-10-01

    Full Text Available Abstract Background Biological data resources have become heterogeneous and derive from multiple sources. This introduces challenges in the management and utilization of this data in software development. Although efforts are underway to create a standard format for the transmission and storage of biological data, this objective has yet to be fully realized. Results This work describes an application programming interface (API that provides a framework for developing an effective biological knowledge ontology for Java-based software projects. The API provides a robust framework for the data acquisition and management needs of an ontology implementation. In addition, the API contains classes to assist in creating GUIs to represent this data visually. Conclusions The Knowledge Discovery Object Model (KDOM API is particularly useful for medium to large applications, or for a number of smaller software projects with common characteristics or objectives. KDOM can be coupled effectively with other biologically relevant APIs and classes. Source code, libraries, documentation and examples are available at http://www.bcgsc.ca/bioinfo/software.

  8. Knowledge discovery: Extracting usable information from large amounts of data

    International Nuclear Information System (INIS)

    Whiteson, R.

    1998-01-01

    The threat of nuclear weapons proliferation is a problem of world wide concern. Safeguards are the key to nuclear nonproliferation and data is the key to safeguards. The safeguards community has access to a huge and steadily growing volume of data. The advantages of this data rich environment are obvious, there is a great deal of information which can be utilized. The challenge is to effectively apply proven and developing technologies to find and extract usable information from that data. That information must then be assessed and evaluated to produce the knowledge needed for crucial decision making. Efficient and effective analysis of safeguards data will depend on utilizing technologies to interpret the large, heterogeneous data sets that are available from diverse sources. With an order-of-magnitude increase in the amount of data from a wide variety of technical, textual, and historical sources there is a vital need to apply advanced computer technologies to support all-source analysis. There are techniques of data warehousing, data mining, and data analysis that can provide analysts with tools that will expedite their extracting useable information from the huge amounts of data to which they have access. Computerized tools can aid analysts by integrating heterogeneous data, evaluating diverse data streams, automating retrieval of database information, prioritizing inputs, reconciling conflicting data, doing preliminary interpretations, discovering patterns or trends in data, and automating some of the simpler prescreening tasks that are time consuming and tedious. Thus knowledge discovery technologies can provide a foundation of support for the analyst. Rather than spending time sifting through often irrelevant information, analysts could use their specialized skills in a focused, productive fashion. This would allow them to make their analytical judgments with more confidence and spend more of their time doing what they do best

  9. Knowledge Discovery and Data Mining (KDDM) survey report.

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, Laurence R.; Jordan, Danyelle N.; Bauer, Travis L.; Elmore, Mark T. (Oak Ridge National Laboratory, Oak Ridge, TN); Treadwell, Jim N. (Oak Ridge National Laboratory, Oak Ridge, TN); Homan, Rossitza A.; Chapman, Leon Darrel; Spires, Shannon V.

    2005-02-01

    The large number of government and industry activities supporting the Unit of Action (UA), with attendant documents, reports and briefings, can overwhelm decision-makers with an overabundance of information that hampers the ability to make quick decisions often resulting in a form of gridlock. In particular, the large and rapidly increasing amounts of data and data formats stored on UA Advanced Collaborative Environment (ACE) servers has led to the realization that it has become impractical and even impossible to perform manual analysis leading to timely decisions. UA Program Management (PM UA) has recognized the need to implement a Decision Support System (DSS) on UA ACE. The objective of this document is to research the commercial Knowledge Discovery and Data Mining (KDDM) market and publish the results in a survey. Furthermore, a ranking mechanism based on UA ACE-specific criteria has been developed and applied to a representative set of commercially available KDDM solutions. In addition, an overview of four R&D areas identified as critical to the implementation of DSS on ACE is provided. Finally, a comprehensive database containing detailed information on surveyed KDDM tools has been developed and is available upon customer request.

  10. Knowledge discovery for pancreatic cancer using inductive logic programming.

    Science.gov (United States)

    Qiu, Yushan; Shimada, Kazuaki; Hiraoka, Nobuyoshi; Maeshiro, Kensei; Ching, Wai-Ki; Aoki-Kinoshita, Kiyoko F; Furuta, Koh

    2014-08-01

    Pancreatic cancer is a devastating disease and predicting the status of the patients becomes an important and urgent issue. The authors explore the applicability of inductive logic programming (ILP) method in the disease and show that the accumulated clinical laboratory data can be used to predict disease characteristics, and this will contribute to the selection of therapeutic modalities of pancreatic cancer. The availability of a large amount of clinical laboratory data provides clues to aid in the knowledge discovery of diseases. In predicting the differentiation of tumour and the status of lymph node metastasis in pancreatic cancer, using the ILP model, three rules are developed that are consistent with descriptions in the literature. The rules that are identified are useful to detect the differentiation of tumour and the status of lymph node metastasis in pancreatic cancer and therefore contributed significantly to the decision of therapeutic strategies. In addition, the proposed method is compared with the other typical classification techniques and the results further confirm the superiority and merit of the proposed method.

  11. Working with Data: Discovering Knowledge through Mining and Analysis; Systematic Knowledge Management and Knowledge Discovery; Text Mining; Methodological Approach in Discovering User Search Patterns through Web Log Analysis; Knowledge Discovery in Databases Using Formal Concept Analysis; Knowledge Discovery with a Little Perspective.

    Science.gov (United States)

    Qin, Jian; Jurisica, Igor; Liddy, Elizabeth D.; Jansen, Bernard J; Spink, Amanda; Priss, Uta; Norton, Melanie J.

    2000-01-01

    These six articles discuss knowledge discovery in databases (KDD). Topics include data mining; knowledge management systems; applications of knowledge discovery; text and Web mining; text mining and information retrieval; user search patterns through Web log analysis; concept analysis; data collection; and data structure inconsistency. (LRW)

  12. The relation between prior knowledge and students' collaborative discovery learning processes.

    NARCIS (Netherlands)

    Gijlers, Aaltje H.; de Jong, Anthonius J.M.

    2005-01-01

    In this study we investigate how prior knowledge influences knowledge development during collaborative discovery learning. Fifteen dyads of students (pre-university education, 15-16 years old) worked on a discovery learning task in the physics field of kinematics. The (face-to-face) communication

  13. Teacher Design Knowledge for Technology Enhanced Learning

    NARCIS (Netherlands)

    McKenney, Susan

    2014-01-01

    This presentation shares a framework for investigating the knowledge teachers need to be able to design technology-enhanced learning. Specific activities are undertaken to consider elements within the framework

  14. Discovery of stimulation-responsive immune enhancers with CRISPR activation

    Science.gov (United States)

    Simeonov, Dimitre R.; Gowen, Benjamin G.; Boontanrart, Mandy; Roth, Theodore L.; Gagnon, John D.; Mumbach, Maxwell R.; Satpathy, Ansuman T.; Lee, Youjin; Bray, Nicolas L.; Chan, Alice Y.; Lituiev, Dmytro S.; Nguyen, Michelle L.; Gate, Rachel E.; Subramaniam, Meena; Li, Zhongmei; Woo, Jonathan M.; Mitros, Therese; Ray, Graham J.; Curie, Gemma L.; Naddaf, Nicki; Chu, Julia S.; Ma, Hong; Boyer, Eric; van Gool, Frederic; Huang, Hailiang; Liu, Ruize; Tobin, Victoria R.; Schumann, Kathrin; Daly, Mark J.; Farh, Kyle K.; Ansel, K. Mark; Ye, Chun J.; Greenleaf, William J.; Anderson, Mark S.; Bluestone, Jeffrey A.; Chang, Howard Y.; Corn, Jacob E.; Marson, Alexander

    2017-09-01

    The majority of genetic variants associated with common human diseases map to enhancers, non-coding elements that shape cell-type-specific transcriptional programs and responses to extracellular cues. Systematic mapping of functional enhancers and their biological contexts is required to understand the mechanisms by which variation in non-coding genetic sequences contributes to disease. Functional enhancers can be mapped by genomic sequence disruption, but this approach is limited to the subset of enhancers that are necessary in the particular cellular context being studied. We hypothesized that recruitment of a strong transcriptional activator to an enhancer would be sufficient to drive target gene expression, even if that enhancer was not currently active in the assayed cells. Here we describe a discovery platform that can identify stimulus-responsive enhancers for a target gene independent of stimulus exposure. We used tiled CRISPR activation (CRISPRa) to synthetically recruit a transcriptional activator to sites across large genomic regions (more than 100 kilobases) surrounding two key autoimmunity risk loci, CD69 and IL2RA. We identified several CRISPRa-responsive elements with chromatin features of stimulus-responsive enhancers, including an IL2RA enhancer that harbours an autoimmunity risk variant. Using engineered mouse models, we found that sequence perturbation of the disease-associated Il2ra enhancer did not entirely block Il2ra expression, but rather delayed the timing of gene activation in response to specific extracellular signals. Enhancer deletion skewed polarization of naive T cells towards a pro-inflammatory T helper (TH17) cell state and away from a regulatory T cell state. This integrated approach identifies functional enhancers and reveals how non-coding variation associated with human immune dysfunction alters context-specific gene programs.

  15. Discovery of stimulation-responsive immune enhancers with CRISPR activation

    Science.gov (United States)

    Simeonov, Dimitre R.; Gowen, Benjamin G.; Boontanrart, Mandy; Roth, Theodore L.; Gagnon, John D.; Mumbach, Maxwell R.; Satpathy, Ansuman T.; Lee, Youjin; Bray, Nicolas L.; Chan, Alice Y.; Lituiev, Dmytro S.; Nguyen, Michelle L.; Gate, Rachel E.; Subramaniam, Meena; Li, Zhongmei; Woo, Jonathan M.; Mitros, Therese; Ray, Graham J.; Curie, Gemma L.; Naddaf, Nicki; Chu, Julia S.; Ma, Hong; Boyer, Eric; Van Gool, Frederic; Huang, Hailiang; Liu, Ruize; Tobin, Victoria R.; Schumann, Kathrin; Daly, Mark J.; Farh, Kyle K; Ansel, K. Mark; Ye, Chun J.; Greenleaf, William J.; Anderson, Mark S.; Bluestone, Jeffrey A.; Chang, Howard Y.; Corn, Jacob E.; Marson, Alexander

    2017-01-01

    The majority of genetic variants associated with common human diseases map to enhancers, non-coding elements that shape cell-type-specific transcriptional programs and responses to extracellular cues1–3. Systematic mapping of functional enhancers and their biological contexts is required to understand the mechanisms by which variation in non-coding genetic sequences contributes to disease. Functional enhancers can be mapped by genomic sequence disruption4–6, but this approach is limited to the subset of enhancers that are necessary in the particular cellular context being studied. We hypothesized that recruitment of a strong transcriptional activator to an enhancer would be sufficient to drive target gene expression, even if that enhancer was not currently active in the assayed cells. Here we describe a discovery platform that can identify stimulus-responsive enhancers for a target gene independent of stimulus exposure. We used tiled CRISPR activation (CRISPRa)7 to synthetically recruit a transcriptional activator to sites across large genomic regions (more than 100 kilobases) surrounding two key autoimmunity risk loci, CD69 and IL2RA. We identified several CRISPRa-responsive elements with chromatin features of stimulus-responsive enhancers, including an IL2RA enhancer that harbours an autoimmunity risk variant. Using engineered mouse models, we found that sequence perturbation of the disease-associated Il2ra enhancer did not entirely block Il2ra expression, but rather delayed the timing of gene activation in response to specific extracellular signals. Enhancer deletion skewed polarization of naive T cells towards a pro-inflammatory T helper (TH17) cell state and away from a regulatory T cell state. This integrated approach identifies functional enhancers and reveals how non-coding variation associated with human immune dysfunction alters context-specific gene programs. PMID:28854172

  16. A Cognitive Adopted Framework for IoT Big-Data Management and Knowledge Discovery Prospective

    OpenAIRE

    Mishra, Nilamadhab; Lin, Chung-Chih; Chang, Hsien-Tsung

    2015-01-01

    In future IoT big-data management and knowledge discovery for large scale industrial automation application, the importance of industrial internet is increasing day by day. Several diversified technologies such as IoT (Internet of Things), computational intelligence, machine type communication, big-data, and sensor technology can be incorporated together to improve the data management and knowledge discovery efficiency of large scale automation applications. So in this work, we need to propos...

  17. Engineering Application Way of Faults Knowledge Discovery Based on Rough Set Theory

    International Nuclear Information System (INIS)

    Zhao Rongzhen; Deng Linfeng; Li Chao

    2011-01-01

    For the knowledge acquisition puzzle of intelligence decision-making technology in mechanical industry, to use the Rough Set Theory (RST) as a kind of tool to solve the puzzle was researched. And the way to realize the knowledge discovery in engineering application is explored. A case extracting out the knowledge rules from a concise data table shows out some important information. It is that the knowledge discovery similar to the mechanical faults diagnosis is an item of complicated system engineering project. In where, first of all-important tasks is to preserve the faults knowledge into a table with data mode. And the data must be derived from the plant site and should also be as concise as possible. On the basis of the faults knowledge data obtained so, the methods and algorithms to process the data and extract the knowledge rules from them by means of RST can be processed only. The conclusion is that the faults knowledge discovery by the way is a process of rising upward. But to develop the advanced faults diagnosis technology by the way is a large-scale knowledge engineering project for long time. Every step in which should be designed seriously according to the tool's demands firstly. This is the basic guarantees to make the knowledge rules obtained have the values of engineering application and the studies have scientific significance. So, a general framework is designed for engineering application to go along the route developing the faults knowledge discovery technology.

  18. Drive Cost Reduction, Increase Innovation and Mitigate Risk with Advanced Knowledge Discovery Tools Designed to Unlock and Leverage Prior Knowledge

    International Nuclear Information System (INIS)

    Mitchell, I.

    2016-01-01

    Full text: The nuclear industry is knowledge-intensive and includes a diverse number of stakeholders. Much of this knowledge is at risk as engineers, technicians and project professionals retire, leaving a widening skills and information gap. This knowledge is critical in an increasingly complex environment with information from past projects often buried in decades-old, non-integrated systems enterprise. Engineers can spend 40% or more of their time searching for answers across the enterprise instead of solving problems. The inability to access trusted industry knowledge results in increased risk and expense. Advanced knowledge discovery technologies slash research times by as much as 75% and accelerate innovation and problem solving by giving technical professionals access to the information they need, in the context of the problems they are trying to solve. Unlike traditional knowledge management approaches, knowledge discovery tools powered by semantic search technologies are adept at uncovering answers in unstructured data and require no tagging, organization or moving of data, meaning a smaller IT footprint and faster time-to-knowledge. This session will highlight best-in-class knowledge discovery technologies, content, and strategies to give nuclear industry organizations the ability to leverage the corpus of enterprise knowledge into the future. (author

  19. Advancing Drug Discovery through Enhanced Free Energy Calculations.

    Science.gov (United States)

    Abel, Robert; Wang, Lingle; Harder, Edward D; Berne, B J; Friesner, Richard A

    2017-07-18

    A principal goal of drug discovery project is to design molecules that can tightly and selectively bind to the target protein receptor. Accurate prediction of protein-ligand binding free energies is therefore of central importance in computational chemistry and computer aided drug design. Multiple recent improvements in computing power, classical force field accuracy, enhanced sampling methods, and simulation setup have enabled accurate and reliable calculations of protein-ligands binding free energies, and position free energy calculations to play a guiding role in small molecule drug discovery. In this Account, we outline the relevant methodological advances, including the REST2 (Replica Exchange with Solute Temperting) enhanced sampling, the incorporation of REST2 sampling with convential FEP (Free Energy Perturbation) through FEP/REST, the OPLS3 force field, and the advanced simulation setup that constitute our FEP+ approach, followed by the presentation of extensive comparisons with experiment, demonstrating sufficient accuracy in potency prediction (better than 1 kcal/mol) to substantially impact lead optimization campaigns. The limitations of the current FEP+ implementation and best practices in drug discovery applications are also discussed followed by the future methodology development plans to address those limitations. We then report results from a recent drug discovery project, in which several thousand FEP+ calculations were successfully deployed to simultaneously optimize potency, selectivity, and solubility, illustrating the power of the approach to solve challenging drug design problems. The capabilities of free energy calculations to accurately predict potency and selectivity have led to the advance of ongoing drug discovery projects, in challenging situations where alternative approaches would have great difficulties. The ability to effectively carry out projects evaluating tens of thousands, or hundreds of thousands, of proposed drug candidates

  20. SemaTyP: a knowledge graph based literature mining method for drug discovery.

    Science.gov (United States)

    Sang, Shengtian; Yang, Zhihao; Wang, Lei; Liu, Xiaoxia; Lin, Hongfei; Wang, Jian

    2018-05-30

    Drug discovery is the process through which potential new medicines are identified. High-throughput screening and computer-aided drug discovery/design are the two main drug discovery methods for now, which have successfully discovered a series of drugs. However, development of new drugs is still an extremely time-consuming and expensive process. Biomedical literature contains important clues for the identification of potential treatments. It could support experts in biomedicine on their way towards new discoveries. Here, we propose a biomedical knowledge graph-based drug discovery method called SemaTyP, which discovers candidate drugs for diseases by mining published biomedical literature. We first construct a biomedical knowledge graph with the relations extracted from biomedical abstracts, then a logistic regression model is trained by learning the semantic types of paths of known drug therapies' existing in the biomedical knowledge graph, finally the learned model is used to discover drug therapies for new diseases. The experimental results show that our method could not only effectively discover new drug therapies for new diseases, but also could provide the potential mechanism of action of the candidate drugs. In this paper we propose a novel knowledge graph based literature mining method for drug discovery. It could be a supplementary method for current drug discovery methods.

  1. An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework.

    Science.gov (United States)

    Chen, Yi-An; Tripathi, Lokesh P; Mizuguchi, Kenji

    2016-01-01

    Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org. © The Author(s) 2016. Published by Oxford University Press.

  2. A knowledge discovery approach to urban analysis: Beyoglu Preservation Area as a data mine

    Directory of Open Access Journals (Sweden)

    Ahu Sokmenoglu Sohtorik

    2017-11-01

    Full Text Available Enhancing our knowledge of the complexities of cities in order to empower ourselves to make more informed decisions has always been a challenge for urban research. Recent developments in large-scale computing, together with the new techniques and automated tools for data collection and analysis are opening up promising opportunities for addressing this problem. The main motivation that served as the driving force behind this research is how these developments may contribute to urban data analysis. On this basis, the thesis focuses on urban data analysis in order to search for findings that can enhance our knowledge of urban environments, using the generic process of knowledge discovery using data mining. A knowledge discovery process based on data mining is a fully automated or semi-automated process which involves the application of computational tools and techniques to explore the “previously unknown, and potentially useful information” (Witten & Frank, 2005 hidden in large and often complex and multi-dimensional databases. This information can be obtained in the form of correlations amongst variables, data groupings (classes and clusters or more complex hypotheses (probabilistic rules of co-occurrence, performance vectors of prediction models etc.. This research targets researchers and practitioners working in the field of urban studies who are interested in quantitative/ computational approaches to urban data analysis and specifically aims to engage the interest of architects, urban designers and planners who do not have a background in statistics or in using data mining methods in their work. Accordingly, the overall aim of the thesis is the development of a knowledge discovery approach to urban analysis; a domain-specific adaptation of the generic process of knowledge discovery using data mining enabling the analyst to discover ‘relational urban knowledge’. ‘Relational urban knowledge’ is a term employed in this thesis to refer

  3. Automated cell type discovery and classification through knowledge transfer

    Science.gov (United States)

    Lee, Hao-Chih; Kosoy, Roman; Becker, Christine E.

    2017-01-01

    Abstract Motivation: Recent advances in mass cytometry allow simultaneous measurements of up to 50 markers at single-cell resolution. However, the high dimensionality of mass cytometry data introduces computational challenges for automated data analysis and hinders translation of new biological understanding into clinical applications. Previous studies have applied machine learning to facilitate processing of mass cytometry data. However, manual inspection is still inevitable and becoming the barrier to reliable large-scale analysis. Results: We present a new algorithm called Automated Cell-type Discovery and Classification (ACDC) that fully automates the classification of canonical cell populations and highlights novel cell types in mass cytometry data. Evaluations on real-world data show ACDC provides accurate and reliable estimations compared to manual gating results. Additionally, ACDC automatically classifies previously ambiguous cell types to facilitate discovery. Our findings suggest that ACDC substantially improves both reliability and interpretability of results obtained from high-dimensional mass cytometry profiling data. Availability and Implementation: A Python package (Python 3) and analysis scripts for reproducing the results are availability on https://bitbucket.org/dudleylab/acdc. Contact: brian.kidd@mssm.edu or joel.dudley@mssm.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28158442

  4. Knowledge discovery based on experiential learning corporate culture management

    Science.gov (United States)

    Tu, Kai-Jan

    2014-10-01

    A good corporate culture based on humanistic theory can make the enterprise's management very effective, all enterprise's members have strong cohesion and centripetal force. With experiential learning model, the enterprise can establish an enthusiastic learning spirit corporate culture, have innovation ability to gain the positive knowledge growth effect, and to meet the fierce global marketing competition. A case study on Trend's corporate culture can offer the proof of industry knowledge growth rate equation as the contribution to experiential learning corporate culture management.

  5. The discovery and history of knowledge of natural atmospheric radioactivity

    International Nuclear Information System (INIS)

    Renoux, A.

    1996-01-01

    Everybody knows that the radioactivity was discovered, 100 years ago, by the Frenchman Henri Becquerel at Paris, in Feb. 1896, stemmed from the discovery of X-rays by Roentgen in the preceding year. In 1899, Rutherford was able to show the existence of α and β rays, and in 1900 Villard showed the presence of a third class of rays, the γ rays. The discovery of the rare radioactive gas radon is attributed to P. and M. Curie in 1898 and F. Dorn in 1900. Thoron ( 220 Rn) was discovered by Rutherford and Owens in 1899-1900 and Actinon ( 219 Rn) by Debierne and Geisel about the same time. The radon's radiotoxicity was studied in France since 1904 by Bouchard and Balthazard and in 1924 it was formulated the hypothesis that the great mortality observed in the uranium miners of Schneeberg in Germany and Joachimsthal in Czechoslovakia was maybe due to the radon. But, in fact, Elster and Geitel were the first to see that the radioactivity is present in the atmosphere in about 1901. After this date, many investigations were made (M. Curie, for example), but it is during the fifties and, of course, until today that the most numerous works were developed. In this paper, we speak about the researches of the after second war pioneers: Evans, Wilkening, Kawano, Israel, Junge, Schuman, Bricard... Renoux, Madelaine, Blanc, Fontan, Siksna, Chamberlain, Dyson, Nolan, etc. and the works developed later. Finally, we reach to the nineties, period where the works are particularly directed in the aim of radon and radon progeny indoor, with in particular, many works effectuated in France. (author). 78 refs., 17 figs., 2 tabs

  6. Formal concept analysis in knowledge discovery: A survey

    NARCIS (Netherlands)

    Poelmans, J.; Elzinga, P.; Viaene, S.; Dedene, G.; Croitoru, M.; Ferré, S.; Lukose, D.

    2010-01-01

    In this paper, we analyze the literature on Formal Concept Analysis (FCA) using FCA. We collected 702 papers published between 2003-2009 mentioning Formal Concept Analysis in the abstract. We developed a knowledge browsing environment to support our literature analysis process. The pdf-files

  7. A projection and density estimation method for knowledge discovery.

    Directory of Open Access Journals (Sweden)

    Adam Stanski

    Full Text Available A key ingredient to modern data analysis is probability density estimation. However, it is well known that the curse of dimensionality prevents a proper estimation of densities in high dimensions. The problem is typically circumvented by using a fixed set of assumptions about the data, e.g., by assuming partial independence of features, data on a manifold or a customized kernel. These fixed assumptions limit the applicability of a method. In this paper we propose a framework that uses a flexible set of assumptions instead. It allows to tailor a model to various problems by means of 1d-decompositions. The approach achieves a fast runtime and is not limited by the curse of dimensionality as all estimations are performed in 1d-space. The wide range of applications is demonstrated at two very different real world examples. The first is a data mining software that allows the fully automatic discovery of patterns. The software is publicly available for evaluation. As a second example an image segmentation method is realized. It achieves state of the art performance on a benchmark dataset although it uses only a fraction of the training data and very simple features.

  8. Data Mining in Education : A Review on the Knowledge Discovery Perspective

    OpenAIRE

    Pratiyush Guleria; Manu Sood

    2014-01-01

    Knowledge Discovery in Databases is the process of finding knowledge in massive amount of data where data mining is the core of this process. Data minin g can be used to mine understandable meaningful patterns from large databases and these patterns ma y then be converted into knowledge.Data mining is t he process of extracting the information and patterns derived by the KDD process which helps in crucial decision-making.Data mining works with data warehou se and...

  9. Process Knowledge Discovery Using Sparse Principal Component Analysis

    DEFF Research Database (Denmark)

    Gao, Huihui; Gajjar, Shriram; Kulahci, Murat

    2016-01-01

    As the goals of ensuring process safety and energy efficiency become ever more challenging, engineers increasingly rely on data collected from such processes for informed decision making. During recent decades, extracting and interpreting valuable process information from large historical data sets...... SPCA approach that helps uncover the underlying process knowledge regarding variable relations. This approach systematically determines the optimal sparse loadings for each sparse PC while improving interpretability and minimizing information loss. The salient features of the proposed approach...

  10. Advanced biological and chemical discovery (ABCD): centralizing discovery knowledge in an inherently decentralized world.

    Science.gov (United States)

    Agrafiotis, Dimitris K; Alex, Simson; Dai, Heng; Derkinderen, An; Farnum, Michael; Gates, Peter; Izrailev, Sergei; Jaeger, Edward P; Konstant, Paul; Leung, Albert; Lobanov, Victor S; Marichal, Patrick; Martin, Douglas; Rassokhin, Dmitrii N; Shemanarev, Maxim; Skalkin, Andrew; Stong, John; Tabruyn, Tom; Vermeiren, Marleen; Wan, Jackson; Xu, Xiang Yang; Yao, Xiang

    2007-01-01

    We present ABCD, an integrated drug discovery informatics platform developed at Johnson & Johnson Pharmaceutical Research & Development, L.L.C. ABCD is an attempt to bridge multiple continents, data systems, and cultures using modern information technology and to provide scientists with tools that allow them to analyze multifactorial SAR and make informed, data-driven decisions. The system consists of three major components: (1) a data warehouse, which combines data from multiple chemical and pharmacological transactional databases, designed for supreme query performance; (2) a state-of-the-art application suite, which facilitates data upload, retrieval, mining, and reporting, and (3) a workspace, which facilitates collaboration and data sharing by allowing users to share queries, templates, results, and reports across project teams, campuses, and other organizational units. Chemical intelligence, performance, and analytical sophistication lie at the heart of the new system, which was developed entirely in-house. ABCD is used routinely by more than 1000 scientists around the world and is rapidly expanding into other functional areas within the J&J organization.

  11. Coupling Visualization and Data Analysis for Knowledge Discovery from Multi-dimensional Scientific Data

    International Nuclear Information System (INIS)

    Rubel, Oliver; Ahern, Sean; Bethel, E. Wes; Biggin, Mark D.; Childs, Hank; Cormier-Michel, Estelle; DePace, Angela; Eisen, Michael B.; Fowlkes, Charless C.; Geddes, Cameron G.R.; Hagen, Hans; Hamann, Bernd; Huang, Min-Yu; Keranen, Soile V.E.; Knowles, David W.; Hendriks, Chris L. Luengo; Malik, Jitendra; Meredith, Jeremy; Messmer, Peter; Prabhat; Ushizima, Daniela; Weber, Gunther H.; Wu, Kesheng

    2010-01-01

    Knowledge discovery from large and complex scientific data is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the growing number of data dimensions and data objects presents tremendous challenges for effective data analysis and data exploration methods and tools. The combination and close integration of methods from scientific visualization, information visualization, automated data analysis, and other enabling technologies 'such as efficient data management' supports knowledge discovery from multi-dimensional scientific data. This paper surveys two distinct applications in developmental biology and accelerator physics, illustrating the effectiveness of the described approach.

  12. Methodologies of Knowledge Discovery from Data and Data Mining Methods in Mechanical Engineering

    Directory of Open Access Journals (Sweden)

    Rogalewicz Michał

    2016-12-01

    Full Text Available The paper contains a review of methodologies of a process of knowledge discovery from data and methods of data exploration (Data Mining, which are the most frequently used in mechanical engineering. The methodologies contain various scenarios of data exploring, while DM methods are used in their scope. The paper shows premises for use of DM methods in industry, as well as their advantages and disadvantages. Development of methodologies of knowledge discovery from data is also presented, along with a classification of the most widespread Data Mining methods, divided by type of realized tasks. The paper is summarized by presentation of selected Data Mining applications in mechanical engineering.

  13. Knowledge Discovery in Spectral Data by Means of Complex Networks

    Directory of Open Access Journals (Sweden)

    Stefano Boccaletti

    2013-03-01

    Full Text Available In the last decade, complex networks have widely been applied to the study of many natural and man-made systems, and to the extraction of meaningful information from the interaction structures created by genes and proteins. Nevertheless, less attention has been devoted to metabonomics, due to the lack of a natural network representation of spectral data. Here we define a technique for reconstructing networks from spectral data sets, where nodes represent spectral bins, and pairs of them are connected when their intensities follow a pattern associated with a disease. The structural analysis of the resulting network can then be used to feed standard data-mining algorithms, for instance for the classification of new (unlabeled subjects. Furthermore, we show how the structure of the network is resilient to the presence of external additive noise, and how it can be used to extract relevant knowledge about the development of the disease.

  14. Reconstructing Sessions from Data Discovery and Access Logs to Build a Semantic Knowledge Base for Improving Data Discovery

    Directory of Open Access Journals (Sweden)

    Yongyao Jiang

    2016-04-01

    Full Text Available Big geospatial data are archived and made available through online web discovery and access. However, finding the right data for scientific research and application development is still a challenge. This paper aims to improve the data discovery by mining the user knowledge from log files. Specifically, user web session reconstruction is focused upon in this paper as a critical step for extracting usage patterns. However, reconstructing user sessions from raw web logs has always been difficult, as a session identifier tends to be missing in most data portals. To address this problem, we propose two session identification methods, including time-clustering-based and time-referrer-based methods. We also present the workflow of session reconstruction and discuss the approach of selecting appropriate thresholds for relevant steps in the workflow. The proposed session identification methods and workflow are proven to be able to extract data access patterns for further pattern analyses of user behavior and improvement of data discovery for more relevancy data ranking, suggestion, and navigation.

  15. Knowledge discovery in cardiology: A systematic literature review.

    Science.gov (United States)

    Kadi, I; Idri, A; Fernandez-Aleman, J L

    2017-01-01

    Data mining (DM) provides the methodology and technology needed to transform huge amounts of data into useful information for decision making. It is a powerful process employed to extract knowledge and discover new patterns embedded in large data sets. Data mining has been increasingly used in medicine, particularly in cardiology. In fact, DM applications can greatly benefit all those involved in cardiology, such as patients, cardiologists and nurses. The purpose of this paper is to review papers concerning the application of DM techniques in cardiology so as to summarize and analyze evidence regarding: (1) the DM techniques most frequently used in cardiology; (2) the performance of DM models in cardiology; (3) comparisons of the performance of different DM models in cardiology. We performed a systematic literature review of empirical studies on the application of DM techniques in cardiology published in the period between 1 January 2000 and 31 December 2015. A total of 149 articles published between 2000 and 2015 were selected, studied and analyzed according to the following criteria: DM techniques and performance of the approaches developed. The results obtained showed that a significant number of the studies selected used classification and prediction techniques when developing DM models. Neural networks, decision trees and support vector machines were identified as being the techniques most frequently employed when developing DM models in cardiology. Moreover, neural networks and support vector machines achieved the highest accuracy rates and were proved to be more efficient than other techniques. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  16. Enhancing discovery in spatial data infrastructures using a search engine

    Directory of Open Access Journals (Sweden)

    Paolo Corti

    2018-05-01

    Full Text Available A spatial data infrastructure (SDI is a framework of geospatial data, metadata, users and tools intended to provide an efficient and flexible way to use spatial information. One of the key software components of an SDI is the catalogue service which is needed to discover, query and manage the metadata. Catalogue services in an SDI are typically based on the Open Geospatial Consortium (OGC Catalogue Service for the Web (CSW standard which defines common interfaces for accessing the metadata information. A search engine is a software system capable of supporting fast and reliable search, which may use ‘any means necessary’ to get users to the resources they need quickly and efficiently. These techniques may include full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting, recommendations and many others. In this paper we present an example of a search engine being added to an SDI to improve search against large collections of geospatial datasets. The Centre for Geographic Analysis (CGA at Harvard University re-engineered the search component of its public domain SDI (Harvard WorldMap which is based on the GeoNode platform. A search engine was added to the SDI stack to enhance the CSW catalogue discovery abilities. It is now possible to discover spatial datasets from metadata by using the standard search operations of the catalogue and to take advantage of the new abilities of the search engine, to return relevant and reliable content to SDI users.

  17. Data-Centric Knowledge Discovery Strategy for a Safety-Critical Sensor Application

    Directory of Open Access Journals (Sweden)

    Nilamadhab Mishra

    2014-01-01

    Full Text Available In an indoor safety-critical application, sensors and actuators are clustered together to accomplish critical actions within a limited time constraint. The cluster may be controlled by a dedicated programmed autonomous microcontroller device powered with electricity to perform in-network time critical functions, such as data collection, data processing, and knowledge production. In a data-centric sensor network, approximately 3–60% of the sensor data are faulty, and the data collected from the sensor environment are highly unstructured and ambiguous. Therefore, for safety-critical sensor applications, actuators must function intelligently within a hard time frame and have proper knowledge to perform their logical actions. This paper proposes a knowledge discovery strategy and an exploration algorithm for indoor safety-critical industrial applications. The application evidence and discussion validate that the proposed strategy and algorithm can be implemented for knowledge discovery within the operational framework.

  18. Knowledge-Based Topic Model for Unsupervised Object Discovery and Localization.

    Science.gov (United States)

    Niu, Zhenxing; Hua, Gang; Wang, Le; Gao, Xinbo

    Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object

  19. Visual Climate Knowledge Discovery within a Grid Environment

    Science.gov (United States)

    Heitzler, Magnus; Kiertscher, Simon; Lang, Ulrich; Nocke, Thomas; Wahnes, Jens; Winkelmann, Volker

    2013-04-01

    Grid for different purposes. The analysis products, such as images and videos, can then be exported and shared with the community, enhancing scientific communication and therefore accelerating scientific research.

  20. Knowledge discovery from models of soil properties developed through data mining

    NARCIS (Netherlands)

    Bui, E.N.; Henderson, B.L.; Viergever, K.

    2006-01-01

    We modelled the distribution of soil properties across the agricultural zone on the Australian continent using data mining and knowledge discovery from databases (DM&KDD) tools. Piecewise linear tree models were built choosing from 19 climate variables, digital elevation model (DEM) and derived

  1. KNODWAT: a scientific framework application for testing knowledge discovery methods for the biomedical domain.

    Science.gov (United States)

    Holzinger, Andreas; Zupan, Mario

    2013-06-13

    Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge challenge. However, there are so many diverse methods and methodologies available, that for biomedical researchers who are inexperienced in the use of even relatively popular knowledge discovery methods, it can be very difficult to select the most appropriate method for their particular research problem. A web application, called KNODWAT (KNOwledge Discovery With Advanced Techniques) has been developed, using Java on Spring framework 3.1. and following a user-centered approach. The software runs on Java 1.6 and above and requires a web server such as Apache Tomcat and a database server such as the MySQL Server. For frontend functionality and styling, Twitter Bootstrap was used as well as jQuery for interactive user interface operations. The framework presented is user-centric, highly extensible and flexible. Since it enables methods for testing using existing data to assess suitability and performance, it is especially suitable for inexperienced biomedical researchers, new to the field of knowledge discovery and data mining. For testing purposes two algorithms, CART and C4.5 were implemented using the WEKA data mining framework.

  2. Knowledge Discovery Process: Case Study of RNAV Adherence of Radar Track Data

    Science.gov (United States)

    Matthews, Bryan

    2018-01-01

    This talk is an introduction to the knowledge discovery process, beginning with: identifying the problem, choosing data sources, matching the appropriate machine learning tools, and reviewing the results. The overview will be given in the context of an ongoing study that is assessing RNAV adherence of commercial aircraft in the national airspace.

  3. Machine Learning Methods for Knowledge Discovery in Medical Data on Atherosclerosis

    Czech Academy of Sciences Publication Activity Database

    Serrano, J.I.; Tomečková, Marie; Zvárová, Jana

    2006-01-01

    Roč. 1, - (2006), s. 6-33 ISSN 1801-5603 Institutional research plan: CEZ:AV0Z10300504 Keywords : knowledge discovery * supervised machine learning * biomedical data mining * risk factors of atherosclerosis Subject RIV: BB - Applied Statistics, Operational Research

  4. Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

    Science.gov (United States)

    Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

    2010-01-18

    The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

  5. Flood AI: An Intelligent Systems for Discovery and Communication of Disaster Knowledge

    Science.gov (United States)

    Demir, I.; Sermet, M. Y.

    2017-12-01

    Communities are not immune from extreme events or natural disasters that can lead to large-scale consequences for the nation and public. Improving resilience to better prepare, plan, recover, and adapt to disasters is critical to reduce the impacts of extreme events. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This project presents an intelligent system, Flood AI, for flooding to improve societal preparedness by providing a knowledge engine using voice recognition, artificial intelligence, and natural language processing based on a generalized ontology for disasters with a primary focus on flooding. The knowledge engine utilizes the flood ontology and concepts to connect user input to relevant knowledge discovery channels on flooding by developing a data acquisition and processing framework utilizing environmental observations, forecast models, and knowledge bases. Communication channels of the framework includes web-based systems, agent-based chat bots, smartphone applications, automated web workflows, and smart home devices, opening the knowledge discovery for flooding to many unique use cases.

  6. Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes.

    Science.gov (United States)

    Hassani-Pak, Keywan; Rawlings, Christopher

    2017-06-13

    Genetics and "omics" studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future.

  7. Integrating traditional knowledge when it appears to conflict with conservation: lessons from the discovery and protection of sitatunga in Ghana

    Directory of Open Access Journals (Sweden)

    Jana M. McPherson

    2016-03-01

    Full Text Available Cultural traditions can conflict with modern conservation goals when they promote damage to fragile environments or the harvest of imperiled species. We explore whether and how traditional, culturally motivated species exploitation can nonetheless aid conservation by examining the recent "discovery" in Avu Lagoon, Ghana, of sitatunga (Tragelaphus spekii gratus, a species familiar to locals, but not previously scientifically recorded in Ghana and regionally assumed extinct. Specifically, we investigate what role traditional beliefs, allied hunting practices, and the associated traditional ecological knowledge have played in the species' discovery and subsequent community-based conservation; how they might influence future conservation outcomes; and how they may themselves be shaped by conservation efforts. Our study serves to exemplify the complexities, risks, and benefits associated with building conservation efforts around traditional ecological knowledge and beliefs. Complexities arise from localized variation in beliefs (with cultural significance of sitatunga much stronger in one village than others, progressive dilution of traditional worldviews by mainstream religions, and the context dependence, both culturally and geographically, of the reliability of traditional ecological knowledge. Among the benefits, we highlight (1 information on the distribution and habitat needs of species that can help to discover, rediscover, or manage imperiled taxa if appropriately paired with scientific data collection; and (2 enhanced sustainability of conservation efforts given the cultivation of mutual trust, respect, and understanding between researchers and local communities. In turn, conservation attention to traditional ecological knowledge and traditionally important species can help reinvigorate cultural diversity by promoting the persistence of traditional belief and knowledge systems alongside mainstream worldviews and religions.

  8. Protein crystallography and drug discovery: recollections of knowledge exchange between academia and industry

    Directory of Open Access Journals (Sweden)

    Tom L. Blundell

    2017-07-01

    Full Text Available The development of structure-guided drug discovery is a story of knowledge exchange where new ideas originate from all parts of the research ecosystem. Dorothy Crowfoot Hodgkin obtained insulin from Boots Pure Drug Company in the 1930s and insulin crystallization was optimized in the company Novo in the 1950s, allowing the structure to be determined at Oxford University. The structure of renin was developed in academia, on this occasion in London, in response to a need to develop antihypertensives in pharma. The idea of a dimeric aspartic protease came from an international academic team and was discovered in HIV; it eventually led to new HIV antivirals being developed in industry. Structure-guided fragment-based discovery was developed in large pharma and biotechs, but has been exploited in academia for the development of new inhibitors targeting protein–protein interactions and also antimicrobials to combat mycobacterial infections such as tuberculosis. These observations provide a strong argument against the so-called `linear model', where ideas flow only in one direction from academic institutions to industry. Structure-guided drug discovery is a story of applications of protein crystallography and knowledge exhange between academia and industry that has led to new drug approvals for cancer and other common medical conditions by the Food and Drug Administration in the USA, as well as hope for the treatment of rare genetic diseases and infectious diseases that are a particular challenge in the developing world.

  9. Protein crystallography and drug discovery: recollections of knowledge exchange between academia and industry.

    Science.gov (United States)

    Blundell, Tom L

    2017-07-01

    The development of structure-guided drug discovery is a story of knowledge exchange where new ideas originate from all parts of the research ecosystem. Dorothy Crowfoot Hodgkin obtained insulin from Boots Pure Drug Company in the 1930s and insulin crystallization was optimized in the company Novo in the 1950s, allowing the structure to be determined at Oxford University. The structure of renin was developed in academia, on this occasion in London, in response to a need to develop antihypertensives in pharma. The idea of a dimeric aspartic protease came from an international academic team and was discovered in HIV; it eventually led to new HIV antivirals being developed in industry. Structure-guided fragment-based discovery was developed in large pharma and biotechs, but has been exploited in academia for the development of new inhibitors targeting protein-protein interactions and also antimicrobials to combat mycobacterial infections such as tuberculosis. These observations provide a strong argument against the so-called 'linear model', where ideas flow only in one direction from academic institutions to industry. Structure-guided drug discovery is a story of applications of protein crystallography and knowledge exhange between academia and industry that has led to new drug approvals for cancer and other common medical conditions by the Food and Drug Administration in the USA, as well as hope for the treatment of rare genetic diseases and infectious diseases that are a particular challenge in the developing world.

  10. Enhancing SAT Based Planning with Landmark Knowledge

    NARCIS (Netherlands)

    Elffers, J.; Konijnenberg, D.; Walraven, E.M.P.; Spaan, M.T.J.

    2013-01-01

    Several approaches exist to solve Artificial Intelligence planning problems, but little attention has been given to the combination of using landmark knowledge and satisfiability (SAT). Landmark knowledge has been exploited successfully in the heuristics of classical planning. Recently it was also

  11. Knowledge management strategies: Enhancing knowledge transfer to clinicians and patients.

    Science.gov (United States)

    Roemer, Lorrie K; Rocha, Roberto A; Del Fiol, Guilherme; Bradshaw, Richard L; Hanna, Timothy P; Hulse, Nathan C

    2006-01-01

    At Intermountain Healthcare (Intermountain), executive clinical content experts are responsible for disseminating consistent evidence-based clinical content throughout the enterprise at the point-of-care. With a paper-based system it was difficult to ensure that current information was received and was being used in practice. With electronic information systems multiple applications were supplying similar, but different, vendor-licensed and locally-developed content. These issues influenced the consistency of clinical practice within the enterprise, jeopardized patient and clinician safety, and exposed the enterprise and its employees to potential financial penalties. In response to these issues Intermountain is developing a knowledge management infrastructure providing tools and services to support clinical content development, deployment, maintenance, and communication. The Intermountain knowledge management philosophy includes strategies guiding clinicians and consumers of health information to relevant best practice information with the intention of changing behaviors. This paper presents three case studies describing different information management problems identified within Intermountain, methods used to solve the problems, implementation challenges, and the current status of each project.

  12. Ontology Learning for Chinese Information Organization and Knowledge Discovery in Ethnology and Anthropology

    Directory of Open Access Journals (Sweden)

    Jing Kong

    2007-09-01

    Full Text Available This paper presents an ontology learning architecture that reflects the interaction between ontology learning and other applications such as ontology-engineering tools and information systems. Based on this architecture, we have developed a prototype system CHOL: a Chinese ontology learning tool. CHOL learns domain ontology from Chinese domain specific texts. On the one hand, it supports a semi-automatic domain ontology acquisition and dynamic maintenance, and on the other hand, it supports an auto-indexing and auto-classification of Chinese scholarly literature. CHOL has been applied in ethnology and anthropology for Chinese information organization and knowledge discovery.

  13. Human Resource Management in the Enhancement Processes of Knowledge Management

    Directory of Open Access Journals (Sweden)

    Didi Sundiman

    2017-11-01

    Full Text Available This research explored Human Resource Management (HRM in enhancement processes of knowledge management. This research explored how HRM practice enhanced the operational of knowledge management. Data were collected by a survey by interviewing 12 informants from Small and Medium Enterprise (SME. The results show that HRM practice gives initiative in the enhancement process of the knowledge management strategy applied to the company. It can be concluded that each sub-component of HRM affects the components of knowledge management, and HRM is highly influential and has a positive effect on quality management processes and vice versa in the work environment.

  14. Knowledge Management for Enhancing Regulatory Body Capabilities in Thailand

    International Nuclear Information System (INIS)

    Apichaibukol, A.; Pakdee, K.

    2016-01-01

    Full text: In order to be a learning organization, the Office of Atoms for Peace (OAP) has appointed a knowledge-management team in an attempt to manage internal knowledge, both tacit knowledge and explicit knowledge, systematically. In principle, the seven steps of knowledge management will be applied for OAP KM, namely; 1. Knowledge identification including the knowledge required of the Regulatory Body. 2. Knowledge creation and acquisition including knowledge sharing, transfer and how to maintain knowledge external factors such as a customers, stakeholder, etc. 3. Knowledge organization based on knowledge structure is needed for a systematic knowledge retention in the future. 4. Knowledge refinement with ISO standards in document storage. 5. Knowledge access for example, using information technology management through web board. 6. Knowledge sharing, OAP staff through numerous methods designed to transfer implicit and tacit knowledge such as formal classroom and on-the-job training, informal Communities of Practice, mentoring. 7. Learning is OAP group continually enhancing their capabilities and making decisions, solving problems and improving the organization. OAP staff could apply knowledge for organization development and planning for a supporting guideline. (author

  15. Application of data mining and artificial intelligence techniques to mass spectrometry data for knowledge discovery

    Directory of Open Access Journals (Sweden)

    Hugo López-Fernández

    2016-05-01

    Full Text Available Mass spectrometry using matrix assisted laser desorption ionization coupled to time of flight analyzers (MALDI-TOF MS has become popular during the last decade due to its high speed, sensitivity and robustness for detecting proteins and peptides. This allows quickly analyzing large sets of samples are in one single batch and doing high-throughput proteomics. In this scenario, bioinformatics methods and computational tools play a key role in MALDI-TOF data analysis, as they are able handle the large amounts of raw data generated in order to extract new knowledge and useful conclusions. A typical MALDI-TOF MS data analysis workflow has three main stages: data acquisition, preprocessing and analysis. Although the most popular use of this technology is to identify proteins through their peptides, analyses that make use of artificial intelligence (AI, machine learning (ML, and statistical methods can be also carried out in order to perform biomarker discovery, automatic diagnosis, and knowledge discovery. In this research work, this workflow is deeply explored and new solutions based on the application of AI, ML, and statistical methods are proposed. In addition, an integrated software platform that supports the full MALDI-TOF MS data analysis workflow that facilitate the work of proteomics researchers without advanced bioinformatics skills has been developed and released to the scientific community.

  16. ForEx++: A New Framework for Knowledge Discovery from Decision Forests

    Directory of Open Access Journals (Sweden)

    Md Nasim Adnan

    2017-11-01

    Full Text Available Decision trees are popularly used in a wide range of real world problems for both prediction and classification (logic rules discovery. A decision forest is an ensemble of decision trees and it is often built for achieving better predictive performance compared to a single decision tree. Besides improving predictive performance, a decision forest can be seen as a pool of logic rules (rules with great potential for knowledge discovery. However, a standard-sized decision forest usually generates a large number of rules that a user may not able to manage for effective knowledge analysis. In this paper, we propose a new, data set independent framework for extracting those rules that are comparatively more accurate, generalized and concise than others. We apply the proposed framework on rules generated by two different decision forest algorithms from some publicly available medical related data sets on dementia and heart disease. We then compare the quality of rules extracted by the proposed framework with rules generated from a single J48 decision tree and rules extracted by another recent method. The results reported in this paper demonstrate the effectiveness of the proposed framework.

  17. Enhancing Life Sciences Teachers' Biodiversity Knowledge

    African Journals Online (AJOL)

    This paper provides insights into how Life Sciences teachers in the Eastern Cape ..... Even simulations, in most cases they are quite artificial in the sense that the ... explain the concept of human impacts on biodiversity; and field activities were .... integrated and applied knowledge required for quality teaching (disciplinary, ...

  18. Development of traditional Chinese medicine clinical data warehouse for medical knowledge discovery and decision support.

    Science.gov (United States)

    Zhou, Xuezhong; Chen, Shibo; Liu, Baoyan; Zhang, Runsun; Wang, Yinghui; Li, Ping; Guo, Yufeng; Zhang, Hua; Gao, Zhuye; Yan, Xiufeng

    2010-01-01

    Traditional Chinese medicine (TCM) is a scientific discipline, which develops the related theories from the long-term clinical practices. The large-scale clinical data are the core empirical knowledge source for TCM research. This paper introduces a clinical data warehouse (CDW) system, which incorporates the structured electronic medical record (SEMR) data for medical knowledge discovery and TCM clinical decision support (CDS). We have developed the clinical reference information model (RIM) and physical data model to manage the various information entities and their relationships in TCM clinical data. An extraction-transformation-loading (ETL) tool is implemented to integrate and normalize the clinical data from different operational data sources. The CDW includes online analytical processing (OLAP) and complex network analysis (CNA) components to explore the various clinical relationships. Furthermore, the data mining and CNA methods are used to discover the valuable clinical knowledge from the data. The CDW has integrated 20,000 TCM inpatient data and 20,000 outpatient data, which contains manifestations (e.g. symptoms, physical examinations and laboratory test results), diagnoses and prescriptions as the main information components. We propose a practical solution to accomplish the large-scale clinical data integration and preprocessing tasks. Meanwhile, we have developed over 400 OLAP reports to enable the multidimensional analysis of clinical data and the case-based CDS. We have successfully conducted several interesting data mining applications. Particularly, we use various classification methods, namely support vector machine, decision tree and Bayesian network, to discover the knowledge of syndrome differentiation. Furthermore, we have applied association rule and CNA to extract the useful acupuncture point and herb combination patterns from the clinical prescriptions. A CDW system consisting of TCM clinical RIM, ETL, OLAP and data mining as the core

  19. Knowledge discovery in traditional Chinese medicine: state of the art and perspectives.

    Science.gov (United States)

    Feng, Yi; Wu, Zhaohui; Zhou, Xuezhong; Zhou, Zhongmei; Fan, Weiyu

    2006-11-01

    As a complementary medical system to Western medicine, traditional Chinese medicine (TCM) provides a unique theoretical and practical approach to the treatment of diseases over thousands of years. Confronted with the increasing popularity of TCM and the huge volume of TCM data, historically accumulated and recently obtained, there is an urgent need to explore these resources effectively by the techniques of knowledge discovery in database (KDD). This paper aims at providing an overview of recent KDD studies in TCM field. A literature search was conducted in both English and Chinese publications, and major studies of knowledge discovery in TCM (KDTCM) reported in these materials were identified. Based on an introduction to the state of the art of TCM data resources, a review of four subfields of KDTCM research was presented, including KDD for the research of Chinese medical formula, KDD for the research of Chinese herbal medicine, KDD for TCM syndrome research, and KDD for TCM clinical diagnosis. Furthermore, the current state and main problems in each subfield were summarized based on a discussion of existing studies, and future directions for each subfield were also proposed accordingly. A series of KDD methods are used in existing KDTCM researches, ranging from conventional frequent itemset mining to state of the art latent structure model. Considerable interesting discoveries are obtained by these methods, such as novel TCM paired drugs discovered by frequent itemset analysis, functional community of related genes discovered under syndrome perspective by text mining, the high proportion of toxic plants in the botanical family Ranunculaceae disclosed by statistical analysis, the association between M-cholinoceptor blocking drug and Solanaceae revealed by association rule mining, etc. It is particularly inspiring to see some studies connecting TCM with biomedicine, which provide a novel top-down view for functional genomics research. However, further developments

  20. Data Mining and Knowledge Discovery tools for exploiting big Earth-Observation data

    Science.gov (United States)

    Espinoza Molina, D.; Datcu, M.

    2015-04-01

    The continuous increase in the size of the archives and in the variety and complexity of Earth-Observation (EO) sensors require new methodologies and tools that allow the end-user to access a large image repository, to extract and to infer knowledge about the patterns hidden in the images, to retrieve dynamically a collection of relevant images, and to support the creation of emerging applications (e.g.: change detection, global monitoring, disaster and risk management, image time series, etc.). In this context, we are concerned with providing a platform for data mining and knowledge discovery content from EO archives. The platform's goal is to implement a communication channel between Payload Ground Segments and the end-user who receives the content of the data coded in an understandable format associated with semantics that is ready for immediate exploitation. It will provide the user with automated tools to explore and understand the content of highly complex images archives. The challenge lies in the extraction of meaningful information and understanding observations of large extended areas, over long periods of time, with a broad variety of EO imaging sensors in synergy with other related measurements and data. The platform is composed of several components such as 1.) ingestion of EO images and related data providing basic features for image analysis, 2.) query engine based on metadata, semantics and image content, 3.) data mining and knowledge discovery tools for supporting the interpretation and understanding of image content, 4.) semantic definition of the image content via machine learning methods. All these components are integrated and supported by a relational database management system, ensuring the integrity and consistency of Terabytes of Earth Observation data.

  1. Discovery of Selective Phosphodiesterase 1 Inhibitors with Memory Enhancing Properties.

    Science.gov (United States)

    Dyck, Brian; Branstetter, Bryan; Gharbaoui, Tawfik; Hudson, Andrew R; Breitenbucher, J Guy; Gomez, Laurent; Botrous, Iriny; Marrone, Tami; Barido, Richard; Allerston, Charles K; Cedervall, E Peder; Xu, Rui; Sridhar, Vandana; Barker, Ryan; Aertgeerts, Kathleen; Schmelzer, Kara; Neul, David; Lee, Dong; Massari, Mark Eben; Andersen, Carsten B; Sebring, Kristen; Zhou, Xianbo; Petroski, Robert; Limberis, James; Augustin, Martin; Chun, Lawrence E; Edwards, Thomas E; Peters, Marco; Tabatabaei, Ali

    2017-04-27

    A series of potent thienotriazolopyrimidinone-based PDE1 inhibitors was discovered. X-ray crystal structures of example compounds from this series in complex with the catalytic domain of PDE1B and PDE10A were determined, allowing optimization of PDE1B potency and PDE selectivity. Reduction of hERG affinity led to greater than a 3000-fold selectivity for PDE1B over hERG. 6-(4-Methoxybenzyl)-9-((tetrahydro-2H-pyran-4-yl)methyl)-8,9,10,11-tetrahydropyrido[4',3':4,5]thieno[3,2-e][1,2,4]triazolo[1,5-c]pyrimidin-5(6H)-one was identified as an orally bioavailable and brain penetrating PDE1B enzyme inhibitor with potent memory-enhancing effects in a rat model of object recognition memory.

  2. Enhancing Nurses Access for Care Quality and Knowledge through ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Enhancing Nurses Access for Care Quality and Knowledge through ... Special journal issue highlights IDRC-supported findings on women's paid work ... New website will help record vital life events to improve access to services for all.

  3. Enhanced digital library system that supports sustainable knowledge

    African Journals Online (AJOL)

    Enhanced digital library system that supports sustainable knowledge: A focus ... This research work provides a Web-Based University library, ability to access the ... and generates pins to authorize bonafide students and staff of the University.

  4. Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

    Science.gov (United States)

    Si, Qian

    Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

  5. The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

    Science.gov (United States)

    Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.

    2010-01-01

    The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624

  6. Integrating Genomic Data Sets for Knowledge Discovery: An Informed Approach to Management of Captive Endangered Species

    Directory of Open Access Journals (Sweden)

    Kristopher J. L. Irizarry

    2016-01-01

    Full Text Available Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management.

  7. Integrating Genomic Data Sets for Knowledge Discovery: An Informed Approach to Management of Captive Endangered Species.

    Science.gov (United States)

    Irizarry, Kristopher J L; Bryant, Doug; Kalish, Jordan; Eng, Curtis; Schmidt, Peggy L; Barrett, Gini; Barr, Margaret C

    2016-01-01

    Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs) that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management.

  8. Pattern recognition algorithms for data mining scalability, knowledge discovery and soft granular computing

    CERN Document Server

    Pal, Sankar K

    2004-01-01

    Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, methodologies, and algorithms, using both classical approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks.Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.

  9. The biological knowledge discovery by PCCF measure and PCA-F projection.

    Science.gov (United States)

    Jia, Xingang; Zhu, Guanqun; Han, Qiuhong; Lu, Zuhong

    2017-01-01

    In the process of biological knowledge discovery, PCA is commonly used to complement the clustering analysis, but PCA typically gives the poor visualizations for most gene expression data sets. Here, we propose a PCCF measure, and use PCA-F to display clusters of PCCF, where PCCF and PCA-F are modeled from the modified cumulative probabilities of genes. From the analysis of simulated and experimental data sets, we demonstrate that PCCF is more appropriate and reliable for analyzing gene expression data compared to other commonly used distances or similarity measures, and PCA-F is a good visualization technique for identifying clusters of PCCF, where we aim at such data sets that the expression values of genes are collected at different time points.

  10. From Data to Knowledge to Discoveries: Artificial Intelligence and Scientific Workflows

    Directory of Open Access Journals (Sweden)

    Yolanda Gil

    2009-01-01

    Full Text Available Scientific computing has entered a new era of scale and sharing with the arrival of cyberinfrastructure facilities for computational experimentation. A key emerging concept is scientific workflows, which provide a declarative representation of complex scientific applications that can be automatically managed and executed in distributed shared resources. In the coming decades, computational experimentation will push the boundaries of current cyberinfrastructure in terms of inter-disciplinary scope and integrative models of scientific phenomena under study. This paper argues that knowledge-rich workflow environments will provide necessary capabilities for that vision by assisting scientists to validate and vet complex analysis processes and by automating important aspects of scientific exploration and discovery.

  11. A Knowledge Discovery Approach to Diagnosing Intracranial Hematomas on Brain CT: Recognition, Measurement and Classification

    Science.gov (United States)

    Liao, Chun-Chih; Xiao, Furen; Wong, Jau-Min; Chiang, I.-Jen

    Computed tomography (CT) of the brain is preferred study on neurological emergencies. Physicians use CT to diagnose various types of intracranial hematomas, including epidural, subdural and intracerebral hematomas according to their locations and shapes. We propose a novel method that can automatically diagnose intracranial hematomas by combining machine vision and knowledge discovery techniques. The skull on the CT slice is located and the depth of each intracranial pixel is labeled. After normalization of the pixel intensities by their depth, the hyperdense area of intracranial hematoma is segmented with multi-resolution thresholding and region-growing. We then apply C4.5 algorithm to construct a decision tree using the features of the segmented hematoma and the diagnoses made by physicians. The algorithm was evaluated on 48 pathological images treated in a single institute. The two discovered rules closely resemble those used by human experts, and are able to make correct diagnoses in all cases.

  12. Integrating GIS components with knowledge discovery technology for environmental health decision support.

    Science.gov (United States)

    Bédard, Yvan; Gosselin, Pierre; Rivest, Sonia; Proulx, Marie-Josée; Nadeau, Martin; Lebel, Germain; Gagnon, Marie-France

    2003-04-01

    This paper presents a new category of decision-support tools that builds on today's Geographic Information Systems (GIS) and On-Line Analytical Processing (OLAP) technologies to facilitate Geographic Knowledge Discovery (GKD). This new category, named Spatial OLAP (SOLAP), has been an R&D topic for about 5 years in a few university labs and is now being implemented by early adopters in different fields, including public health where it provides numerous advantages. In this paper, we present an example of a SOLAP application in the field of environmental health: the ICEM-SE project. After having presented this example, we describe the design of this system and explain how it provides fast and easy access to the detailed and aggregated data that are needed for GKD and decision-making in public health. The SOLAP concept is also described and a comparison is made with traditional GIS applications.

  13. Enhancing Transfer of Knowledge in Physics through Effective Teaching Strategies

    Science.gov (United States)

    Akinbobola, Akinyemi Olufunminiyi

    2015-01-01

    The study assessed the enhancement of transfer of knowledge in physics through the use of effective teaching strategies in Nigerian senior secondary schools. Non-randomized pretest-posttest control group design was adopted for the study. A total of 278 physics students took part in the study. Transfer of Knowledge Test in Physics (TKTP) with the…

  14. An Ontology-supported Approach for Automatic Chaining of Web Services in Geospatial Knowledge Discovery

    Science.gov (United States)

    di, L.; Yue, P.; Yang, W.; Yu, G.

    2006-12-01

    Recent developments in geospatial semantic Web have shown promise for automatic discovery, access, and use of geospatial Web services to quickly and efficiently solve particular application problems. With the semantic Web technology, it is highly feasible to construct intelligent geospatial knowledge systems that can provide answers to many geospatial application questions. A key challenge in constructing such intelligent knowledge system is to automate the creation of a chain or process workflow that involves multiple services and highly diversified data and can generate the answer to a specific question of users. This presentation discusses an approach for automating composition of geospatial Web service chains by employing geospatial semantics described by geospatial ontologies. It shows how ontology-based geospatial semantics are used for enabling the automatic discovery, mediation, and chaining of geospatial Web services. OWL-S is used to represent the geospatial semantics of individual Web services and the type of the services it belongs to and the type of the data it can handle. The hierarchy and classification of service types are described in the service ontology. The hierarchy and classification of data types are presented in the data ontology. For answering users' geospatial questions, an Artificial Intelligent (AI) planning algorithm is used to construct the service chain by using the service and data logics expressed in the ontologies. The chain can be expressed as a graph with nodes representing services and connection weights representing degrees of semantic matching between nodes. The graph is a visual representation of logical geo-processing path for answering users' questions. The graph can be instantiated to a physical service workflow for execution to generate the answer to a user's question. A prototype system, which includes real world geospatial applications, is implemented to demonstrate the concept and approach.

  15. Enhancing Location-Related Hydrogeological Knowledge

    Directory of Open Access Journals (Sweden)

    Alexander Kmoch

    2018-03-01

    Full Text Available We analyzed the corpus of three geoscientific journals to investigate if there are enough locational references in research articles to apply a geographical search method, such as the example of New Zealand. Based on all available abstracts and all freely available papers of the “New Zealand Journal of Geology and Geophysics”, the “New Zealand Journal of Marine and Freshwater Research”, and the “Journal of Hydrology, New Zealand”, we searched title, abstracts, and full texts for place name occurrences that match records from the official Land Information New Zealand (LINZ gazetteer. We generated ISO standard compliant metadata records for each article including the spatial references and made them available in a public catalogue service. This catalogue can be queried for articles based on authors, titles, keywords, topics, and spatial reference. We visualize the results in a map to show which area the research articles are about, and how much and how densely geographic space is described through these geoscientific research articles by mapping mentioned place names by their geographic locations. We outlined the methodology and technical framework for the geo-referencing of the journal articles and the platform design for this knowledge inventory. The results indicate that the use of well-crafted abstracts for journal articles with carefully chosen place names of relevance for the article provides a guideline for geographically referencing unstructured information like journal articles and reports in order to make such resources discoverable through geographical queries. Lastly, this approach can actively support integrated holistic assessment of water resources and support decision making.

  16. A Hybrid Information Mining Approach for Knowledge Discovery in Cardiovascular Disease (CVD

    Directory of Open Access Journals (Sweden)

    Stefania Pasanisi

    2018-04-01

    Full Text Available The healthcare ambit is usually perceived as “information rich” yet “knowledge poor”. Nowadays, an unprecedented effort is underway to increase the use of business intelligence techniques to solve this problem. Heart disease (HD is a major cause of mortality in modern society. This paper analyzes the risk factors that have been identified in cardiovascular disease (CVD surveillance systems. The Heart Care study identifies attributes related to CVD risk (gender, age, smoking habit, etc. and other dependent variables that include a specific form of CVD (diabetes, hypertension, cardiac disease, etc.. In this paper, we combine Clustering, Association Rules, and Neural Networks for the assessment of heart-event-related risk factors, targeting the reduction of CVD risk. With the use of the K-means algorithm, significant groups of patients are found. Then, the Apriori algorithm is applied in order to understand the kinds of relations between the attributes within the dataset, first looking within the whole dataset and then refining the results through the subsets defined by the clusters. Finally, both results allow us to better define patients’ characteristics in order to make predictions about CVD risk with a Multilayer Perceptron Neural Network. The results obtained with the hybrid information mining approach indicate that it is an effective strategy for knowledge discovery concerning chronic diseases, particularly for CVD risk.

  17. Problem Formulation in Knowledge Discovery via Data Analytics (KDDA) for Environmental Risk Management.

    Science.gov (United States)

    Li, Yan; Thomas, Manoj; Osei-Bryson, Kweku-Muata; Levy, Jason

    2016-12-15

    With the growing popularity of data analytics and data science in the field of environmental risk management, a formalized Knowledge Discovery via Data Analytics (KDDA) process that incorporates all applicable analytical techniques for a specific environmental risk management problem is essential. In this emerging field, there is limited research dealing with the use of decision support to elicit environmental risk management (ERM) objectives and identify analytical goals from ERM decision makers. In this paper, we address problem formulation in the ERM understanding phase of the KDDA process. We build a DM³ ontology to capture ERM objectives and to inference analytical goals and associated analytical techniques. A framework to assist decision making in the problem formulation process is developed. It is shown how the ontology-based knowledge system can provide structured guidance to retrieve relevant knowledge during problem formulation. The importance of not only operationalizing the KDDA approach in a real-world environment but also evaluating the effectiveness of the proposed procedure is emphasized. We demonstrate how ontology inferencing may be used to discover analytical goals and techniques by conceptualizing Hazardous Air Pollutants (HAPs) exposure shifts based on a multilevel analysis of the level of urbanization (and related economic activity) and the degree of Socio-Economic Deprivation (SED) at the local neighborhood level. The HAPs case highlights not only the role of complexity in problem formulation but also the need for integrating data from multiple sources and the importance of employing appropriate KDDA modeling techniques. Challenges and opportunities for KDDA are summarized with an emphasis on environmental risk management and HAPs.

  18. Problem Formulation in Knowledge Discovery via Data Analytics (KDDA for Environmental Risk Management

    Directory of Open Access Journals (Sweden)

    Yan Li

    2016-12-01

    Full Text Available With the growing popularity of data analytics and data science in the field of environmental risk management, a formalized Knowledge Discovery via Data Analytics (KDDA process that incorporates all applicable analytical techniques for a specific environmental risk management problem is essential. In this emerging field, there is limited research dealing with the use of decision support to elicit environmental risk management (ERM objectives and identify analytical goals from ERM decision makers. In this paper, we address problem formulation in the ERM understanding phase of the KDDA process. We build a DM3 ontology to capture ERM objectives and to inference analytical goals and associated analytical techniques. A framework to assist decision making in the problem formulation process is developed. It is shown how the ontology-based knowledge system can provide structured guidance to retrieve relevant knowledge during problem formulation. The importance of not only operationalizing the KDDA approach in a real-world environment but also evaluating the effectiveness of the proposed procedure is emphasized. We demonstrate how ontology inferencing may be used to discover analytical goals and techniques by conceptualizing Hazardous Air Pollutants (HAPs exposure shifts based on a multilevel analysis of the level of urbanization (and related economic activity and the degree of Socio-Economic Deprivation (SED at the local neighborhood level. The HAPs case highlights not only the role of complexity in problem formulation but also the need for integrating data from multiple sources and the importance of employing appropriate KDDA modeling techniques. Challenges and opportunities for KDDA are summarized with an emphasis on environmental risk management and HAPs.

  19. Knowledge discovery in databases of biomechanical variables: application to the sit to stand motor task

    Directory of Open Access Journals (Sweden)

    Benvenuti Francesco

    2004-10-01

    Full Text Available Abstract Background The interpretation of data obtained in a movement analysis laboratory is a crucial issue in clinical contexts. Collection of such data in large databases might encourage the use of modern techniques of data mining to discover additional knowledge with automated methods. In order to maximise the size of the database, simple and low-cost experimental set-ups are preferable. The aim of this study was to extract knowledge inherent in the sit-to-stand task as performed by healthy adults, by searching relationships among measured and estimated biomechanical quantities. An automated method was applied to a large amount of data stored in a database. The sit-to-stand motor task was already shown to be adequate for determining the level of individual motor ability. Methods The technique of search for association rules was chosen to discover patterns as part of a Knowledge Discovery in Databases (KDD process applied to a sit-to-stand motor task observed with a simple experimental set-up and analysed by means of a minimum measured input model. Selected parameters and variables of a database containing data from 110 healthy adults, of both genders and of a large range of age, performing the task were considered in the analysis. Results A set of rules and definitions were found characterising the patterns shared by the investigated subjects. Time events of the task turned out to be highly interdependent at least in their average values, showing a high level of repeatability of the timing of the performance of the task. Conclusions The distinctive patterns of the sit-to-stand task found in this study, associated to those that could be found in similar studies focusing on subjects with pathologies, could be used as a reference for the functional evaluation of specific subjects performing the sit-to-stand motor task.

  20. Evolution of the clinical and epidemiological knowledge about Chagas disease 90 years after its discovery

    Directory of Open Access Journals (Sweden)

    Prata Aluízio

    1999-01-01

    Full Text Available Three different periods may be considered in the evolution of knowledge about the clinical and epidemiological aspects of Chagas disease since its discovery: (a early period concerning the studies carried out by Carlos Chagas in Lassance with the collaboration of other investigators of the Manguinhos School. At that time the disease was described and the parasite, transmitters and reservoirs were studied. The coexistence of endemic goiter in the same region generated some confusion about the clinical forms of the disease; (b second period involving uncertainty and the description of isolated cases, which lasted until the 1940 decade. Many acute cases were described during this period and the disease was recognized in many Latin American countries. Particularly important were the studies of the Argentine Mission of Regional Pathology Studies, which culminated with the description of the Romaña sign in the 1930 decade, facilitating the diagnosis of the early phase of the disease. However, the chronic phase, which was the most important, continued to be difficult to recognize; (c period of consolidation of knowledge and recognition of the importance of Chagas disease. Studies conducted by Laranja, Dias and Nóbrega in Bambuí updated the description of Chagas heart disease made by Carlos Chagas and Eurico Villela. From then on, the disease was more easily recognized, especially with the emphasis on the use of a serologic diagnosis; (d period of enlargement of knowledges on the disease. The studies on denervation conducted in Ribeirão Preto by Fritz Köberle starting in the 1950 decade led to a better understanding of the relations between Chagas disease and megaesophagus and other visceral megas detected in endemic areas.

  1. Problem Formulation in Knowledge Discovery via Data Analytics (KDDA) for Environmental Risk Management

    Science.gov (United States)

    Li, Yan; Thomas, Manoj; Osei-Bryson, Kweku-Muata; Levy, Jason

    2016-01-01

    With the growing popularity of data analytics and data science in the field of environmental risk management, a formalized Knowledge Discovery via Data Analytics (KDDA) process that incorporates all applicable analytical techniques for a specific environmental risk management problem is essential. In this emerging field, there is limited research dealing with the use of decision support to elicit environmental risk management (ERM) objectives and identify analytical goals from ERM decision makers. In this paper, we address problem formulation in the ERM understanding phase of the KDDA process. We build a DM3 ontology to capture ERM objectives and to inference analytical goals and associated analytical techniques. A framework to assist decision making in the problem formulation process is developed. It is shown how the ontology-based knowledge system can provide structured guidance to retrieve relevant knowledge during problem formulation. The importance of not only operationalizing the KDDA approach in a real-world environment but also evaluating the effectiveness of the proposed procedure is emphasized. We demonstrate how ontology inferencing may be used to discover analytical goals and techniques by conceptualizing Hazardous Air Pollutants (HAPs) exposure shifts based on a multilevel analysis of the level of urbanization (and related economic activity) and the degree of Socio-Economic Deprivation (SED) at the local neighborhood level. The HAPs case highlights not only the role of complexity in problem formulation but also the need for integrating data from multiple sources and the importance of employing appropriate KDDA modeling techniques. Challenges and opportunities for KDDA are summarized with an emphasis on environmental risk management and HAPs. PMID:27983713

  2. Geo-Enrichment and Semantic Enhancement of Metadata Sets to Augment Discovery in Geoportals

    Directory of Open Access Journals (Sweden)

    Bernhard Vockner

    2014-03-01

    Full Text Available Geoportals are established to function as main gateways to find, evaluate, and start “using” geographic information. Still, current geoportal implementations face problems in optimizing the discovery process due to semantic heterogeneity issues, which leads to low recall and low precision in performing text-based searches. Therefore, we propose an enhanced semantic discovery approach that supports multilingualism and information domain context. Thus, we present workflow that enriches existing structured metadata with synonyms, toponyms, and translated terms derived from user-defined keywords based on multilingual thesauri and ontologies. To make the results easier and understandable, we also provide automated translation capabilities for the resource metadata to support the user in conceiving the thematic content of the descriptive metadata, even if it has been documented using a language the user is not familiar with. In addition, to text-enable spatial filtering capabilities, we add additional location name keywords to metadata sets. These are based on the existing bounding box and shall tweak discovery scores when performing single text line queries. In order to improve the user’s search experience, we tailor faceted search strategies presenting an enhanced query interface for geo-metadata discovery that are transparently leveraging the underlying thesauri and ontologies.

  3. Knowledge base verification based on enhanced colored petri net

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jong Hyun; Seong, Poong Hyun [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

    1997-12-31

    Verification is a process aimed at demonstrating whether a system meets it`s specified requirements. As expert systems are used in various applications, the knowledge base verification of systems takes an important position. The conventional Petri net approach that has been studied recently in order to verify the knowledge base is found that it is inadequate to verify the knowledge base of large and complex system, such as alarm processing system of nuclear power plant. Thus, we propose an improved method that models the knowledge base as enhanced colored Petri net. In this study, we analyze the reachability and the error characteristics of the knowledge base and apply the method to verification of simple knowledge base. 8 refs., 4 figs. (Author)

  4. Knowledge base verification based on enhanced colored petri net

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jong Hyun; Seong, Poong Hyun [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

    1998-12-31

    Verification is a process aimed at demonstrating whether a system meets it`s specified requirements. As expert systems are used in various applications, the knowledge base verification of systems takes an important position. The conventional Petri net approach that has been studied recently in order to verify the knowledge base is found that it is inadequate to verify the knowledge base of large and complex system, such as alarm processing system of nuclear power plant. Thus, we propose an improved method that models the knowledge base as enhanced colored Petri net. In this study, we analyze the reachability and the error characteristics of the knowledge base and apply the method to verification of simple knowledge base. 8 refs., 4 figs. (Author)

  5. Knowledge discovery about quality of life changes of spinal cord injury patients: clustering based on rules by states.

    Science.gov (United States)

    Gibert, Karina; García-Rudolph, Alejandro; Curcoll, Lluïsa; Soler, Dolors; Pla, Laura; Tormos, José María

    2009-01-01

    In this paper, an integral Knowledge Discovery Methodology, named Clustering based on rules by States, which incorporates artificial intelligence (AI) and statistical methods as well as interpretation-oriented tools, is used for extracting knowledge patterns about the evolution over time of the Quality of Life (QoL) of patients with Spinal Cord Injury. The methodology incorporates the interaction with experts as a crucial element with the clustering methodology to guarantee usefulness of the results. Four typical patterns are discovered by taking into account prior expert knowledge. Several hypotheses are elaborated about the reasons for psychological distress or decreases in QoL of patients over time. The knowledge discovery from data (KDD) approach turns out, once again, to be a suitable formal framework for handling multidimensional complexity of the health domains.

  6. FluKB: A Knowledge-Based System for Influenza Vaccine Target Discovery and Analysis of the Immunological Properties of Influenza Viruses

    DEFF Research Database (Denmark)

    Simon, Christian; Kudahl, Ulrich Johan; Sun, Jing

    2015-01-01

    FluKB is a knowledge-based system focusing on data and analytical tools for influenza vaccine discovery. The main goal of FluKB is to provide access to curated influenza sequence and epitope data and enhance the analysis of influenza sequence diversity and the analysis of targets of immune...... responses. FluKB consists of more than 400,000 influenza protein sequences, known epitope data (357 verified T-cell epitopes, 685 HLA binders, and 16 naturally processed MHC ligands), and a collection of 28 influenza antibodies and their structurally defined B-cell epitopes. FluKB was built using amodular...

  7. Enhancing students’ vocabulary knowledge using the Facebook environment

    OpenAIRE

    Muhammad Kamarul Kabilan; Tuti Zalina Mohamed Ernes Zahar

    2016-01-01

    This study investigates the effectiveness of using Facebook in enhancing vocabulary knowledge among Community College students. Thirty-three (33) Community College students are exposed to the use of Facebook as an environment of learning and enhancing their English vocabulary. They are given a pre-test and a post-test and the findings indicate that students perform significantly better in the post-test compared to the pre-test. It appears that Facebook could be considered as a supplementary l...

  8. Evaluation of gene association methods for coexpression network construction and biological knowledge discovery.

    Directory of Open Access Journals (Sweden)

    Sapna Kumari

    Full Text Available BACKGROUND: Constructing coexpression networks and performing network analysis using large-scale gene expression data sets is an effective way to uncover new biological knowledge; however, the methods used for gene association in constructing these coexpression networks have not been thoroughly evaluated. Since different methods lead to structurally different coexpression networks and provide different information, selecting the optimal gene association method is critical. METHODS AND RESULTS: In this study, we compared eight gene association methods - Spearman rank correlation, Weighted Rank Correlation, Kendall, Hoeffding's D measure, Theil-Sen, Rank Theil-Sen, Distance Covariance, and Pearson - and focused on their true knowledge discovery rates in associating pathway genes and construction coordination networks of regulatory genes. We also examined the behaviors of different methods to microarray data with different properties, and whether the biological processes affect the efficiency of different methods. CONCLUSIONS: We found that the Spearman, Hoeffding and Kendall methods are effective in identifying coexpressed pathway genes, whereas the Theil-sen, Rank Theil-Sen, Spearman, and Weighted Rank methods perform well in identifying coordinated transcription factors that control the same biological processes and traits. Surprisingly, the widely used Pearson method is generally less efficient, and so is the Distance Covariance method that can find gene pairs of multiple relationships. Some analyses we did clearly show Pearson and Distance Covariance methods have distinct behaviors as compared to all other six methods. The efficiencies of different methods vary with the data properties to some degree and are largely contingent upon the biological processes, which necessitates the pre-analysis to identify the best performing method for gene association and coexpression network construction.

  9. PKDE4J: Entity and relation extraction for public knowledge discovery.

    Science.gov (United States)

    Song, Min; Kim, Won Chul; Lee, Dahee; Heo, Go Eun; Kang, Keun Young

    2015-10-01

    Due to an enormous number of scientific publications that cannot be handled manually, there is a rising interest in text-mining techniques for automated information extraction, especially in the biomedical field. Such techniques provide effective means of information search, knowledge discovery, and hypothesis generation. Most previous studies have primarily focused on the design and performance improvement of either named entity recognition or relation extraction. In this paper, we present PKDE4J, a comprehensive text-mining system that integrates dictionary-based entity extraction and rule-based relation extraction in a highly flexible and extensible framework. Starting with the Stanford CoreNLP, we developed the system to cope with multiple types of entities and relations. The system also has fairly good performance in terms of accuracy as well as the ability to configure text-processing components. We demonstrate its competitive performance by evaluating it on many corpora and found that it surpasses existing systems with average F-measures of 85% for entity extraction and 81% for relation extraction. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. Mining the Quantified Self: Personal Knowledge Discovery as a Challenge for Data Science.

    Science.gov (United States)

    Fawcett, Tom

    2015-12-01

    The last several years have seen an explosion of interest in wearable computing, personal tracking devices, and the so-called quantified self (QS) movement. Quantified self involves ordinary people recording and analyzing numerous aspects of their lives to understand and improve themselves. This is now a mainstream phenomenon, attracting a great deal of attention, participation, and funding. As more people are attracted to the movement, companies are offering various new platforms (hardware and software) that allow ever more aspects of daily life to be tracked. Nearly every aspect of the QS ecosystem is advancing rapidly, except for analytic capabilities, which remain surprisingly primitive. With increasing numbers of qualified self participants collecting ever greater amounts and types of data, many people literally have more data than they know what to do with. This article reviews the opportunities and challenges posed by the QS movement. Data science provides well-tested techniques for knowledge discovery. But making these useful for the QS domain poses unique challenges that derive from the characteristics of the data collected as well as the specific types of actionable insights that people want from the data. Using a small sample of QS time series data containing information about personal health we provide a formulation of the QS problem that connects data to the decisions of interest to the user.

  11. Informing child welfare policy and practice: using knowledge discovery and data mining technology via a dynamic Web site.

    Science.gov (United States)

    Duncan, Dean F; Kum, Hye-Chung; Weigensberg, Elizabeth Caplick; Flair, Kimberly A; Stewart, C Joy

    2008-11-01

    Proper management and implementation of an effective child welfare agency requires the constant use of information about the experiences and outcomes of children involved in the system, emphasizing the need for comprehensive, timely, and accurate data. In the past 20 years, there have been many advances in technology that can maximize the potential of administrative data to promote better evaluation and management in the field of child welfare. Specifically, this article discusses the use of knowledge discovery and data mining (KDD), which makes it possible to create longitudinal data files from administrative data sources, extract valuable knowledge, and make the information available via a user-friendly public Web site. This article demonstrates a successful project in North Carolina where knowledge discovery and data mining technology was used to develop a comprehensive set of child welfare outcomes available through a public Web site to facilitate information sharing of child welfare data to improve policy and practice.

  12. Role Of Indigenous Knowledge In Enhancing Household Food ...

    African Journals Online (AJOL)

    The data were collected using semi-structured questionnaires, personal interviews and group discussions. The finding showed that many people depend on the use of indigenous knowledge practices in sustaining subsistence farming and enhancing household food security. Majority of farmers mulch their crops using local ...

  13. Enhancing Canadian Civil Society Research and Knowledge-Based ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Enhancing Canadian Civil Society Research and Knowledge-Based Practice in a Rapidly Changing Landscape for International Development ... Women in the developing world continue to face obstacles that limit their ability to establish careers and become leaders in the fields of science, technology, engineering, and ...

  14. Knowledge Generation in Technology-Enhanced Health Exhibitions

    DEFF Research Database (Denmark)

    Magnussen, Rikke; Kharlamov, Nikita; Zachariasssen, Maria

    2016-01-01

    This paper presents results from eye-tracking studies of audience interaction and knowledge generation in the technology-enhanced health promotion exhibition PULSE at a science centre in Copenhagen, Denmark. The main purpose of the study was to understand what types of knowledge audiences build...... in health promotion exhibitions designed to include direct physical interaction. The current study is part of the larger PULSE project, which aims to develop innovative health promotion activities that include a science museum exhibition as a key setting. The primary target group is families with children...

  15. ESIP's Earth Science Knowledge Graph (ESKG) Testbed Project: An Automatic Approach to Building Interdisciplinary Earth Science Knowledge Graphs to Improve Data Discovery

    Science.gov (United States)

    McGibbney, L. J.; Jiang, Y.; Burgess, A. B.

    2017-12-01

    Big Earth observation data have been produced, archived and made available online, but discovering the right data in a manner that precisely and efficiently satisfies user needs presents a significant challenge to the Earth Science (ES) community. An emerging trend in information retrieval community is to utilize knowledge graphs to assist users in quickly finding desired information from across knowledge sources. This is particularly prevalent within the fields of social media and complex multimodal information processing to name but a few, however building a domain-specific knowledge graph is labour-intensive and hard to keep up-to-date. In this work, we update our progress on the Earth Science Knowledge Graph (ESKG) project; an ESIP-funded testbed project which provides an automatic approach to building a dynamic knowledge graph for ES to improve interdisciplinary data discovery by leveraging implicit, latent existing knowledge present within across several U.S Federal Agencies e.g. NASA, NOAA and USGS. ESKG strengthens ties between observations and user communities by: 1) developing a knowledge graph derived from various sources e.g. Web pages, Web Services, etc. via natural language processing and knowledge extraction techniques; 2) allowing users to traverse, explore, query, reason and navigate ES data via knowledge graph interaction. ESKG has the potential to revolutionize the way in which ES communities interact with ES data in the open world through the entity, spatial and temporal linkages and characteristics that make it up. This project enables the advancement of ESIP collaboration areas including both Discovery and Semantic Technologies by putting graph information right at our fingertips in an interactive, modern manner and reducing the efforts to constructing ontology. To demonstrate the ESKG concept, we will demonstrate use of our framework across NASA JPL's PO.DAAC, NOAA's Earth Observation Requirements Evaluation System (EORES) and various USGS

  16. Enhancing Students’ Local Knowledge Through Themed Garden Project

    Directory of Open Access Journals (Sweden)

    Esa Norizan

    2015-01-01

    Full Text Available Traditional or local knowledge is a major issue to be focused on, particularly since the implementation of the Strategic Plan for Biodiversity 2011–2020 and the Aichi Targets “Living in Harmony with Nature”. According to the strategic goals, by 2020, conservation of biodiversity and its sustainable use incorporate what local and indigenous communities have within their traditional knowledge, innovation and practice and their customary use of biological resources are respected at all relevant levels. The older generation among the local people usually use medicinal herbs for various ailments, health care and other cultural purposes. However, encroaching industrialization and the changes in today’s life styles are responsible for the decreasing practice in the local use of herbs especially for healing purposes. It is, therefore, felt worthwhile to encourage young generations such as school children to gain knowledge about these local herbs and record the native uses of these herbs before the information is lost. One biodiversity education program was conducted to facilitate secondary school students to set up a themed garden and find out the local knowledge of the plants they grew in their garden from their family members or communities. The findings revealed that students’ local knowledge on healing improved after they joined the program. Therefore, it is proposed that the themed garden project can enhance students’ local knowledge.

  17. How does non-formal marine education affect student attitude and knowledge? A case study using SCDNR's Discovery program

    Science.gov (United States)

    McGovern, Mary Francis

    Non-formal environmental education provides students the opportunity to learn in ways that would not be possible in a traditional classroom setting. Outdoor learning allows students to make connections to their environment and helps to foster an appreciation for nature. This type of education can be interdisciplinary---students not only develop skills in science, but also in mathematics, social studies, technology, and critical thinking. This case study focuses on a non-formal marine education program, the South Carolina Department of Natural Resources' (SCDNR) Discovery vessel based program. The Discovery curriculum was evaluated to determine impact on student knowledge about and attitude toward the estuary. Students from two South Carolina coastal counties who attended the boat program during fall 2014 were asked to complete a brief survey before, immediately after, and two weeks following the program. The results of this study indicate that both student knowledge about and attitude significantly improved after completion of the Discovery vessel based program. Knowledge and attitude scores demonstrated a positive correlation.

  18. The new world of discovery, invention, and innovation: convergence of knowledge, technology, and society

    Science.gov (United States)

    Roco, Mihail C.; Bainbridge, William S.

    2013-09-01

    Convergence of knowledge and technology for the benefit of society (CKTS) is the core opportunity for progress in the twenty-first century. CKTS is defined as the escalating and transformative interactions among seemingly different disciplines, technologies, communities, and domains of human activity to achieve mutual compatibility, synergism, and integration, and through this process to create added value and branch out to meet shared goals. Convergence has been progressing by stages over the past several decades, beginning with nanotechnology for the material world, followed by convergence of nanotechnology, biotechnology, information, and cognitive science (NBIC) for emerging technologies. CKTS is the third level of convergence. It suggests a general process to advance creativity, innovation, and societal progress based on five general purpose principles: (1) the interdependence of all components of nature and society, (2) decision analysis for research, development, and applications based on dynamic system-logic deduction, (3) enhancement of creativity and innovation through evolutionary processes of convergence that combines existing principles and divergence that generates new ones, (4) the utility of higher-level cross-domain languages to generate new solutions and support transfer of new knowledge, and (5) the value of vision-inspired basic research embodied in grand challenges. CKTS is a general purpose approach in knowledge society. It allows society to answer questions and resolve problems that isolated capabilities cannot, as well as to create new competencies, knowledge, and technologies on this basis. Possible solutions are outlined for key societal challenges in the next decade, including support for foundational emerging technologies NBIC to penetrate essential platforms of human activity and create new industries and jobs, improve lifelong wellness and human potential, achieve personalized and integrated healthcare and education, and secure a

  19. The new world of discovery, invention, and innovation: convergence of knowledge, technology, and society

    International Nuclear Information System (INIS)

    Roco, Mihail C.; Bainbridge, William S.

    2013-01-01

    Convergence of knowledge and technology for the benefit of society (CKTS) is the core opportunity for progress in the twenty-first century. CKTS is defined as the escalating and transformative interactions among seemingly different disciplines, technologies, communities, and domains of human activity to achieve mutual compatibility, synergism, and integration, and through this process to create added value and branch out to meet shared goals. Convergence has been progressing by stages over the past several decades, beginning with nanotechnology for the material world, followed by convergence of nanotechnology, biotechnology, information, and cognitive science (NBIC) for emerging technologies. CKTS is the third level of convergence. It suggests a general process to advance creativity, innovation, and societal progress based on five general purpose principles: (1) the interdependence of all components of nature and society, (2) decision analysis for research, development, and applications based on dynamic system-logic deduction, (3) enhancement of creativity and innovation through evolutionary processes of convergence that combines existing principles and divergence that generates new ones, (4) the utility of higher-level cross-domain languages to generate new solutions and support transfer of new knowledge, and (5) the value of vision-inspired basic research embodied in grand challenges. CKTS is a general purpose approach in knowledge society. It allows society to answer questions and resolve problems that isolated capabilities cannot, as well as to create new competencies, knowledge, and technologies on this basis. Possible solutions are outlined for key societal challenges in the next decade, including support for foundational emerging technologies NBIC to penetrate essential platforms of human activity and create new industries and jobs, improve lifelong wellness and human potential, achieve personalized and integrated healthcare and education, and secure a

  20. The new world of discovery, invention, and innovation: convergence of knowledge, technology, and society

    Energy Technology Data Exchange (ETDEWEB)

    Roco, Mihail C., E-mail: mroco@nsf.gov; Bainbridge, William S. [National Science Foundation (United States)

    2013-09-15

    Convergence of knowledge and technology for the benefit of society (CKTS) is the core opportunity for progress in the twenty-first century. CKTS is defined as the escalating and transformative interactions among seemingly different disciplines, technologies, communities, and domains of human activity to achieve mutual compatibility, synergism, and integration, and through this process to create added value and branch out to meet shared goals. Convergence has been progressing by stages over the past several decades, beginning with nanotechnology for the material world, followed by convergence of nanotechnology, biotechnology, information, and cognitive science (NBIC) for emerging technologies. CKTS is the third level of convergence. It suggests a general process to advance creativity, innovation, and societal progress based on five general purpose principles: (1) the interdependence of all components of nature and society, (2) decision analysis for research, development, and applications based on dynamic system-logic deduction, (3) enhancement of creativity and innovation through evolutionary processes of convergence that combines existing principles and divergence that generates new ones, (4) the utility of higher-level cross-domain languages to generate new solutions and support transfer of new knowledge, and (5) the value of vision-inspired basic research embodied in grand challenges. CKTS is a general purpose approach in knowledge society. It allows society to answer questions and resolve problems that isolated capabilities cannot, as well as to create new competencies, knowledge, and technologies on this basis. Possible solutions are outlined for key societal challenges in the next decade, including support for foundational emerging technologies NBIC to penetrate essential platforms of human activity and create new industries and jobs, improve lifelong wellness and human potential, achieve personalized and integrated healthcare and education, and secure a

  1. New Trends in E-Science: Machine Learning and Knowledge Discovery in Databases

    Science.gov (United States)

    Brescia, Massimo

    2012-11-01

    Data mining, or Knowledge Discovery in Databases (KDD), while being the main methodology to extract the scientific information contained in Massive Data Sets (MDS), needs to tackle crucial problems since it has to orchestrate complex challenges posed by transparent access to different computing environments, scalability of algorithms, reusability of resources. To achieve a leap forward for the progress of e-science in the data avalanche era, the community needs to implement an infrastructure capable of performing data access, processing and mining in a distributed but integrated context. The increasing complexity of modern technologies carried out a huge production of data, whose related warehouse management and the need to optimize analysis and mining procedures lead to a change in concept on modern science. Classical data exploration, based on local user own data storage and limited computing infrastructures, is no more efficient in the case of MDS, worldwide spread over inhomogeneous data centres and requiring teraflop processing power. In this context modern experimental and observational science requires a good understanding of computer science, network infrastructures, Data Mining, etc. i.e. of all those techniques which fall into the domain of the so called e-science (recently assessed also by the Fourth Paradigm of Science). Such understanding is almost completely absent in the older generations of scientists and this reflects in the inadequacy of most academic and research programs. A paradigm shift is needed: statistical pattern recognition, object oriented programming, distributed computing, parallel programming need to become an essential part of scientific background. A possible practical solution is to provide the research community with easy-to understand, easy-to-use tools, based on the Web 2.0 technologies and Machine Learning methodology. Tools where almost all the complexity is hidden to the final user, but which are still flexible and able to

  2. Improve Data Mining and Knowledge Discovery through the use of MatLab

    Science.gov (United States)

    Shaykahian, Gholan Ali; Martin, Dawn Elliott; Beil, Robert

    2011-01-01

    Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and

  3. EarthCube Data Discovery Hub: Enhancing, Curating and Finding Data across Multiple Geoscience Data Sources.

    Science.gov (United States)

    Zaslavsky, I.; Valentine, D.; Richard, S. M.; Gupta, A.; Meier, O.; Peucker-Ehrenbrink, B.; Hudman, G.; Stocks, K. I.; Hsu, L.; Whitenack, T.; Grethe, J. S.; Ozyurt, I. B.

    2017-12-01

    EarthCube Data Discovery Hub (DDH) is an EarthCube Building Block project using technologies developed in CINERGI (Community Inventory of EarthCube Resources for Geoscience Interoperability) to enable geoscience users to explore a growing portfolio of EarthCube-created and other geoscience-related resources. Over 1 million metadata records are available for discovery through the project portal (cinergi.sdsc.edu). These records are retrieved from data facilities, including federal, state and academic sources, or contributed by geoscientists through workshops, surveys, or other channels. CINERGI metadata augmentation pipeline components 1) provide semantic enhancement based on a large ontology of geoscience terms, using text analytics to generate keywords with references to ontology classes, 2) add spatial extents based on place names found in the metadata record, and 3) add organization identifiers to the metadata. The records are indexed and can be searched via a web portal and standard search APIs. The added metadata content improves discoverability and interoperability of the registered resources. Specifically, the addition of ontology-anchored keywords enables faceted browsing and lets users navigate to datasets related by variables measured, equipment used, science domain, processes described, geospatial features studied, and other dataset characteristics that are generated by the pipeline. DDH also lets data curators access and edit the automatically generated metadata records using the CINERGI metadata editor, accept or reject the enhanced metadata content, and consider it in updating their metadata descriptions. We consider several complex data discovery workflows, in environmental seismology (quantifying sediment and water fluxes using seismic data), marine biology (determining available temperature, location, weather and bleaching characteristics of coral reefs related to measurements in a given coral reef survey), and river geochemistry (discovering

  4. Augmenting collider searches and enhancing discovery potentials through stochastic jet grooming

    Science.gov (United States)

    Roy, Tuhin S.; Thalapillil, Arun M.

    2017-04-01

    The jet trimming procedure has been demonstrated to greatly improve event reconstruction in hadron collisions by mitigating contamination due initial state radiation, multiple interactions, and event pileup. Meanwhile, Qjets—a nondeterministic approach to tree-based jet substructure—has been shown to be a powerful technique in decreasing random statistical fluctuations, yielding significant effective luminosity improvements. This manifests through an improvement in the significance S /δ B , relative to conventional methods. Qjets also provides novel observables in many cases, like mass-volatility, that could be used to further discriminate between signal and background events. The statistical robustness and volatility observables, for tagging, are obtained simultaneously. We explore here a combination of the two techniques, and demonstrate that significant enhancements in discovery potentials may be obtained in nontrivial ways. We will illustrate this by considering a diboson resonance analysis as a case study, enabling us to interpolate between scenarios where the gains are purely due to statistical robustness and scenarios where the gains are also reinforced by volatility variable discriminants. The former, for instance, is applicable to digluon/diquark resonances, while the latter will be of relevance to di -W±/di -Z0 resonances, where the boosted vector bosons are decaying hadronically and have an intrinsic mass scale attached to them. We argue that one can enhance signal significance and discovery potentials markedly through stochastic grooming, and help augment studies at the Large Hadron Collider and future hadron colliders.

  5. Supporting students' knowledge integration with technology-enhanced inquiry curricula

    Science.gov (United States)

    Chiu, Jennifer Lopseen

    Dynamic visualizations of scientific phenomena have the potential to transform how students learn and understand science. Dynamic visualizations enable interaction and experimentation with unobservable atomic-level phenomena. A series of studies clarify the conditions under which embedding dynamic visualizations in technology-enhanced inquiry instruction can help students develop robust and durable chemistry knowledge. Using the knowledge integration perspective, I designed Chemical Reactions, a technology-enhanced curriculum unit, with a partnership of teachers, educational researchers, and chemists. This unit guides students in an exploration of how energy and chemical reactions relate to climate change. It uses powerful dynamic visualizations to connect atomic level interactions to the accumulation of greenhouse gases. The series of studies were conducted in typical classrooms in eleven high schools across the country. This dissertation describes four studies that contribute to understanding of how visualizations can be used to transform chemistry learning. The efficacy study investigated the impact of the Chemical Reactions unit compared to traditional instruction using pre-, post- and delayed posttest assessments. The self-monitoring study used self-ratings in combination with embedded assessments to explore how explanation prompts help students learn from dynamic visualizations. The self-regulation study used log files of students' interactions with the learning environment to investigate how external feedback and explanation prompts influence students' exploration of dynamic visualizations. The explanation study compared specific and general explanation prompts to explore the processes by which explanations benefit learning with dynamic visualizations. These studies delineate the conditions under which dynamic visualizations embedded in inquiry instruction can enhance student outcomes. The studies reveal that visualizations can be deceptively clear

  6. Hackathons as a means of accelerating scientific discoveries and knowledge transfer.

    Science.gov (United States)

    Ghouila, Amel; Siwo, Geoffrey Henry; Entfellner, Jean-Baka Domelevo; Panji, Sumir; Button-Simons, Katrina A; Davis, Sage Zenon; Fadlelmola, Faisal M; Ferdig, Michael T; Mulder, Nicola

    2018-05-01

    Scientific research plays a key role in the advancement of human knowledge and pursuit of solutions to important societal challenges. Typically, research occurs within specific institutions where data are generated and subsequently analyzed. Although collaborative science bringing together multiple institutions is now common, in such collaborations the analytical processing of the data is often performed by individual researchers within the team, with only limited internal oversight and critical analysis of the workflow prior to publication. Here, we show how hackathons can be a means of enhancing collaborative science by enabling peer review before results of analyses are published by cross-validating the design of studies or underlying data sets and by driving reproducibility of scientific analyses. Traditionally, in data analysis processes, data generators and bioinformaticians are divided and do not collaborate on analyzing the data. Hackathons are a good strategy to build bridges over the traditional divide and are potentially a great agile extension to the more structured collaborations between multiple investigators and institutions. © 2018 Ghouila et al.; Published by Cold Spring Harbor Laboratory Press.

  7. 41. DISCOVERY, SEARCH, AND COMMUNICATION OF TEXTUAL KNOWLEDGE RESOURCES IN DISTRIBUTED SYSTEMS a. Discovering and Utilizing Knowledge Sources for Metasearch Knowledge Systems

    Energy Technology Data Exchange (ETDEWEB)

    Zamora, Antonio

    2008-03-18

    Advanced Natural Language Processing Tools for Web Information Retrieval, Content Analysis, and Synthesis. The goal of this SBIR was to implement and evaluate several advanced Natural Language Processing (NLP) tools and techniques to enhance the precision and relevance of search results by analyzing and augmenting search queries and by helping to organize the search output obtained from heterogeneous databases and web pages containing textual information of interest to DOE and the scientific-technical user communities in general. The SBIR investigated 1) the incorporation of spelling checkers in search applications, 2) identification of significant phrases and concepts using a combination of linguistic and statistical techniques, and 3) enhancement of the query interface and search retrieval results through the use of semantic resources, such as thesauri. A search program with a flexible query interface was developed to search reference databases with the objective of enhancing search results from web queries or queries of specialized search systems such as DOE's Information Bridge. The DOE ETDE/INIS Joint Thesaurus was processed to create a searchable database. Term frequencies and term co-occurrences were used to enhance the web information retrieval by providing algorithmically-derived objective criteria to organize relevant documents into clusters containing significant terms. A thesaurus provides an authoritative overview and classification of a field of knowledge. By organizing the results of a search using the thesaurus terminology, the output is more meaningful than when the results are just organized based on the terms that co-occur in the retrieved documents, some of which may not be significant. An attempt was made to take advantage of the hierarchy provided by broader and narrower terms, as well as other field-specific information in the thesauri. The search program uses linguistic morphological routines to find relevant entries regardless of

  8. Knowledge management and networking for enhancing nuclear safety

    International Nuclear Information System (INIS)

    Taniguchi, T.; Lederman, L.

    2004-01-01

    Striving for innovative solutions to enhance efficiency of programme delivery and a wider outreach of its nuclear safety activities, the International Atomic Energy Agency (IAEA) has developed an Integrated Safety Approach as a platform for linking its safety related statutory functions and its many associated activities. The approach recognizes the vital importance of effective management of the knowledge base and builds on the integration between the IAEA's safety standards and all aspects of the provision for their application, including peer reviews and technical meetings to share lessons learned. The IAEA is using knowledge management techniques to develop process flows, map safety knowledge and to promote knowledge sharing. The first practical application was the establishment of a knowledge base related to safety aspects of ageing and long-term operation of nuclear power plants. The IAEA is also promoting and facilitating the establishment of regional nuclear and radiation safety networks to preserve existing knowledge and expertise as well as to strengthen sharing and creation of new knowledge in these fields. Prominent examples are the Asian Nuclear Safety Network established in the frame of the IAEA's Programme on the Safety of Nuclear Installations in South East Asia, Pacific and Far East Countries, and the Ibero-American Radiation Safety Network in the frame of the Ibero-American Forum of Nuclear Regulators. Results to date are most encouraging and suggest that this pioneer work should be extended to other regions and eventually to a global nuclear safety network. Responsive to the need of Member States, the IAEA Secretariat has prepared and made available a large number of up-to-date training packages in nuclear, radiation, transport and waste safety, using IAEA safety standards as a basis. It is also providing instruction to trainers in Member States on the use of these modules. This ensures that the material is properly used and that the IAEA

  9. Enhancing students’ vocabulary knowledge using the Facebook environment

    Directory of Open Access Journals (Sweden)

    Muhammad Kamarul Kabilan

    2016-01-01

    Full Text Available This study investigates the effectiveness of using Facebook in enhancing vocabulary knowledge among Community College students. Thirty-three (33 Community College students are exposed to the use of Facebook as an environment of learning and enhancing their English vocabulary. They are given a pre-test and a post-test and the findings indicate that students perform significantly better in the post-test compared to the pre-test. It appears that Facebook could be considered as a supplementary learning environment or learning platform or a learning tool; with meaningful and engaging activities that require students to collaborate, network and functions as a community of practice, particularly for introverted students with low proficiency levels and have low self-esteem.

  10. A KNOWLEDGE DISCOVERY STRATEGY FOR RELATING SEA SURFACE TEMPERATURES TO FREQUENCIES OF TROPICAL STORMS AND GENERATING PREDICTIONS OF HURRICANES UNDER 21ST-CENTURY GLOBAL WARMING SCENARIOS

    Data.gov (United States)

    National Aeronautics and Space Administration — A KNOWLEDGE DISCOVERY STRATEGY FOR RELATING SEA SURFACE TEMPERATURES TO FREQUENCIES OF TROPICAL STORMS AND GENERATING PREDICTIONS OF HURRICANES UNDER 21ST-CENTURY...

  11. Advances in Knowledge Discovery and Data Mining 21st Pacific Asia Conference, PAKDD 2017 Held in Jeju, South Korea, May 23 26, 2017. Proceedings Part I, Part II.

    Science.gov (United States)

    2017-06-27

    Data Mining 21’’ Pacific-Asia Conference, PAKDD 2017Jeju, South Korea, May 23-26, Sb. GRANT NUMBER 2017 Proceedings, Part I, Part II Sc. PROGRAM...Springer; Switzerland. 14. ABSTRACT The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) is a leading international conference...in the areas of knowledge discovery and data mining (KDD). We had three keynote speeches, delivered by Sang Cha from Seoul National University

  12. Knowledge Discovery, Integration and Communication for Extreme Weather and Flood Resilience Using Artificial Intelligence: Flood AI Alpha

    Science.gov (United States)

    Demir, I.; Sermet, M. Y.

    2016-12-01

    Nobody is immune from extreme events or natural hazards that can lead to large-scale consequences for the nation and public. One of the solutions to reduce the impacts of extreme events is to invest in improving resilience with the ability to better prepare, plan, recover, and adapt to disasters. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This abstracts presents our project on developing a resilience framework for flooding to improve societal preparedness with objectives; (a) develop a generalized ontology for extreme events with primary focus on flooding; (b) develop a knowledge engine with voice recognition, artificial intelligence, natural language processing, and inference engine. The knowledge engine will utilize the flood ontology and concepts to connect user input to relevant knowledge discovery outputs on flooding; (c) develop a data acquisition and processing framework from existing environmental observations, forecast models, and social networks. The system will utilize the framework, capabilities and user base of the Iowa Flood Information System (IFIS) to populate and test the system; (d) develop a communication framework to support user interaction and delivery of information to users. The interaction and delivery channels will include voice and text input via web-based system (e.g. IFIS), agent-based bots (e.g. Microsoft Skype, Facebook Messenger), smartphone and augmented reality applications (e.g. smart assistant), and automated web workflows (e.g. IFTTT, CloudWork) to open the knowledge discovery for flooding to thousands of community extensible web workflows.

  13. ALMA Discovery of Solar Umbral Brightness Enhancement at λ = 3 mm

    Energy Technology Data Exchange (ETDEWEB)

    Iwai, Kazumasa [Institute for Space-Earth Environmental Research, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8601 (Japan); Loukitcheva, Maria [Center for Solar-Terrestrial Research, New Jersey Institute of Technology, 323 Martin Luther King Boulevard, Newark, NJ 07102 (United States); Shimojo, Masumi [Chile Observatory, National Astronomical Observatory of Japan, Mitaka, Tokyo 181-8588 (Japan); Solanki, Sami K. [Max Planck Institute for Solar System Research, Justus-von-Liebig-Weg 3, D-37073 Göttingen (Germany); White, Stephen M., E-mail: k.iwai@isee.nagoya-u.ac.jp [Space Vehicles Directorate, Air Force Research Laboratory, Albuquerque, NM (United States)

    2017-06-01

    We report the discovery of a brightness enhancement in the center of a large sunspot umbra at a wavelength of 3 mm using the Atacama Large Millimeter/sub-millimeter Array (ALMA). Sunspots are among the most prominent features on the solar surface, but many of their aspects are surprisingly poorly understood. We analyzed a λ = 3 mm (100 GHz) mosaic image obtained by ALMA that includes a large sunspot within the active region AR12470, on 2015 December 16. The 3 mm map has a 300″ × 300″ field of view and 4.″9 × 2.″2 spatial resolution, which is the highest spatial resolution map of an entire sunspot in this frequency range. We find a gradient of 3 mm brightness from a high value in the outer penumbra to a low value in the inner penumbra/outer umbra. Within the inner umbra, there is a marked increase in 3 mm brightness temperature, which we call an umbral brightness enhancement. This enhanced emission corresponds to a temperature excess of 800 K relative to the surrounding inner penumbral region and coincides with excess brightness in the 1330 and 1400 Å slit-jaw images of the Interface Region Imaging Spectrograph ( IRIS ), adjacent to a partial lightbridge. This λ = 3 mm brightness enhancement may be an intrinsic feature of the sunspot umbra at chromospheric heights, such as a manifestation of umbral flashes, or it could be related to a coronal plume, since the brightness enhancement was coincident with the footpoint of a coronal loop observed at 171 Å.

  14. Data Linkage Graph: computation, querying and knowledge discovery of life science database networks

    Directory of Open Access Journals (Sweden)

    Lange Matthias

    2007-12-01

    Full Text Available To support the interpretation of measured molecular facts, like gene expression experiments or EST sequencing, the functional or the system biological context has to be considered. Doing so, the relationship to existing biological knowledge has to be discovered. In general, biological knowledge is worldwide represented in a network of databases. In this paper we present a method for knowledge extraction in life science databases, which prevents the scientists from screen scraping and web clicking approaches.

  15. Architectural Knowledge Discovery with Latent Semantic Analysis: Constructing a Reading Guide for Software Product Audits

    NARCIS (Netherlands)

    de Boer, R.C.; van Vliet, H.

    2008-01-01

    Architectural knowledge is reflected in various artifacts of a software product. In a software product audit this architectural knowledge needs to be uncovered and its effects assessed in order to evaluate the quality of the software product. A particular problem is to find and comprehend the

  16. Segmented and Detailed Visualization of Anatomical Structures based on Augmented Reality for Health Education and Knowledge Discovery

    Directory of Open Access Journals (Sweden)

    Isabel Cristina Siqueira da Silva

    2017-05-01

    Full Text Available The evolution of technology has changed the face of education, especially when combined with appropriate pedagogical bases. This combination has created innovation opportunities in order to add quality to teaching through new perspectives for traditional methods applied in the classroom. In the Health field, particularly, augmented reality and interaction design techniques can assist the teacher in the exposition of theoretical concepts and/or concepts that need of training at specific medical procedures. Besides, visualization and interaction with Health data, from different sources and in different formats, helps to identify hidden patterns or anomalies, increases the flexibility in the search for certain values, allows the comparison of different units to obtain relative difference in quantities, provides human interaction in real time, etc. At this point, it is noted that the use of interactive visualization techniques such as augmented reality and virtual can collaborate with the process of knowledge discovery in medical and biomedical databases. This work discuss aspects related to the use of augmented reality and interaction design as a tool for teaching anatomy and knowledge discovery, with the proposition of an case study based on mobile application that can display targeted anatomical parts in high resolution and with detail of its parts.

  17. Increased bioassay sensitivity of bioactive molecule discovery using metal-enhanced bioluminescence

    International Nuclear Information System (INIS)

    Golberg, Karina; Elbaz, Amit; McNeil, Ronald; Kushmaro, Ariel; Geddes, Chris D.; Marks, Robert S.

    2014-01-01

    We report the use of bioluminescence signal enhancement via proximity to deposited silver nanoparticles for bioactive compound discovery. This approach employs a whole-cell bioreporter harboring a plasmid-borne fusion of a specific promoter incorporated with a bioluminescence reporter gene. The silver deposition process was first optimized to provide optimal nanoparticle size in the reaction time dependence with fluorescein. The use of silver deposition of 350 nm particles enabled the doubling of the bioluminescent signal amplitude by the bacterial bioreporter when compared to an untouched non-silver-deposited microtiter plate surface. This recording is carried out in the less optimal but necessary far-field distance. SEM micrographs provided a visualization of the proximity of the bioreporter to the silver nanoparticles. The electromagnetic field distributions around the nanoparticles were simulated using Finite Difference Time Domain, further suggesting a re-excitation of non-chemically excited bioluminescence in addition to metal-enhanced bioluminescence. The possibility of an antiseptic silver effect caused by such a close proximity was eliminated disregarded by the dynamic growth curves of the bioreporter strains as seen using viability staining. As a highly attractive biotechnology tool, this silver deposition technique, coupled with whole-cell sensing, enables increased bioluminescence sensitivity, making it especially useful for cases in which reporter luminescence signals are very weak

  18. Increased bioassay sensitivity of bioactive molecule discovery using metal-enhanced bioluminescence

    Energy Technology Data Exchange (ETDEWEB)

    Golberg, Karina, E-mail: karingo@bgu.ac.il; Elbaz, Amit [Ben-Gurion University of the Negev, Avram and Stella Goldstein-Goren Department of Biotechnology Engineering (Israel); McNeil, Ronald [The Institute of Fluorescence, University of Maryland Baltimore County (United States); Kushmaro, Ariel [Ben-Gurion University of the Negev, Avram and Stella Goldstein-Goren Department of Biotechnology Engineering (Israel); Geddes, Chris D. [The Institute of Fluorescence, University of Maryland Baltimore County (United States); Marks, Robert S., E-mail: rsmarks@bgu.ac.il [Ben-Gurion University of the Negev, Avram and Stella Goldstein-Goren Department of Biotechnology Engineering (Israel)

    2014-12-15

    We report the use of bioluminescence signal enhancement via proximity to deposited silver nanoparticles for bioactive compound discovery. This approach employs a whole-cell bioreporter harboring a plasmid-borne fusion of a specific promoter incorporated with a bioluminescence reporter gene. The silver deposition process was first optimized to provide optimal nanoparticle size in the reaction time dependence with fluorescein. The use of silver deposition of 350 nm particles enabled the doubling of the bioluminescent signal amplitude by the bacterial bioreporter when compared to an untouched non-silver-deposited microtiter plate surface. This recording is carried out in the less optimal but necessary far-field distance. SEM micrographs provided a visualization of the proximity of the bioreporter to the silver nanoparticles. The electromagnetic field distributions around the nanoparticles were simulated using Finite Difference Time Domain, further suggesting a re-excitation of non-chemically excited bioluminescence in addition to metal-enhanced bioluminescence. The possibility of an antiseptic silver effect caused by such a close proximity was eliminated disregarded by the dynamic growth curves of the bioreporter strains as seen using viability staining. As a highly attractive biotechnology tool, this silver deposition technique, coupled with whole-cell sensing, enables increased bioluminescence sensitivity, making it especially useful for cases in which reporter luminescence signals are very weak.

  19. Computational Evolutionary Methodology for Knowledge Discovery and Forecasting in Epidemiology and Medicine

    International Nuclear Information System (INIS)

    Rao, Dhananjai M.; Chernyakhovsky, Alexander; Rao, Victoria

    2008-01-01

    Humanity is facing an increasing number of highly virulent and communicable diseases such as avian influenza. Researchers believe that avian influenza has potential to evolve into one of the deadliest pandemics. Combating these diseases requires in-depth knowledge of their epidemiology. An effective methodology for discovering epidemiological knowledge is to utilize a descriptive, evolutionary, ecological model and use bio-simulations to study and analyze it. These types of bio-simulations fall under the category of computational evolutionary methods because the individual entities participating in the simulation are permitted to evolve in a natural manner by reacting to changes in the simulated ecosystem. This work describes the application of the aforementioned methodology to discover epidemiological knowledge about avian influenza using a novel eco-modeling and bio-simulation environment called SEARUMS. The mathematical principles underlying SEARUMS, its design, and the procedure for using SEARUMS are discussed. The bio-simulations and multi-faceted case studies conducted using SEARUMS elucidate its ability to pinpoint timelines, epicenters, and socio-economic impacts of avian influenza. This knowledge is invaluable for proactive deployment of countermeasures in order to minimize negative socioeconomic impacts, combat the disease, and avert a pandemic

  20. Acts of Discovery: Using Collaborative Research to Mobilize and Generate Knowledge about Visual Arts Teaching Practice

    Science.gov (United States)

    Mitchell, Donna Mathewson

    2014-01-01

    Visual arts teachers engage in complex work on a daily basis. This work is informed by practical knowledge that is rarely examined or drawn on in research or in the development of policy. Focusing on the work of secondary visual arts teachers, this article reports on a research program conducted in a regional area of New South Wales, Australia.…

  1. Knowledge Discovery for Smart Grid Operation, Control, and Situation Awareness -- A Big Data Visualization Platform

    Energy Technology Data Exchange (ETDEWEB)

    Gu, Yi; Jiang, Huaiguang; Zhang, Yingchen; Zhang, Jun Jason; Gao, Tianlu; Muljadi, Eduard

    2016-11-21

    In this paper, a big data visualization platform is designed to discover the hidden useful knowledge for smart grid (SG) operation, control and situation awareness. The spawn of smart sensors at both grid side and customer side can provide large volume of heterogeneous data that collect information in all time spectrums. Extracting useful knowledge from this big-data poll is still challenging. In this paper, the Apache Spark, an open source cluster computing framework, is used to process the big-data to effectively discover the hidden knowledge. A high-speed communication architecture utilizing the Open System Interconnection (OSI) model is designed to transmit the data to a visualization platform. This visualization platform uses Google Earth, a global geographic information system (GIS) to link the geological information with the SG knowledge and visualize the information in user defined fashion. The University of Denver's campus grid is used as a SG test bench and several demonstrations are presented for the proposed platform.

  2. Text mining for literature review and knowledge discovery in cancer risk assessment and research.

    Directory of Open Access Journals (Sweden)

    Anna Korhonen

    Full Text Available Research in biomedical text mining is starting to produce technology which can make information in biomedical literature more accessible for bio-scientists. One of the current challenges is to integrate and refine this technology to support real-life scientific tasks in biomedicine, and to evaluate its usefulness in the context of such tasks. We describe CRAB - a fully integrated text mining tool designed to support chemical health risk assessment. This task is complex and time-consuming, requiring a thorough review of existing scientific data on a particular chemical. Covering human, animal, cellular and other mechanistic data from various fields of biomedicine, this is highly varied and therefore difficult to harvest from literature databases via manual means. Our tool automates the process by extracting relevant scientific data in published literature and classifying it according to multiple qualitative dimensions. Developed in close collaboration with risk assessors, the tool allows navigating the classified dataset in various ways and sharing the data with other users. We present a direct and user-based evaluation which shows that the technology integrated in the tool is highly accurate, and report a number of case studies which demonstrate how the tool can be used to support scientific discovery in cancer risk assessment and research. Our work demonstrates the usefulness of a text mining pipeline in facilitating complex research tasks in biomedicine. We discuss further development and application of our technology to other types of chemical risk assessment in the future.

  3. In Silico Mining for Antimalarial Structure-Activity Knowledge and Discovery of Novel Antimalarial Curcuminoids

    Directory of Open Access Journals (Sweden)

    Birgit Viira

    2016-06-01

    Full Text Available Malaria is a parasitic tropical disease that kills around 600,000 patients every year. The emergence of resistant Plasmodium falciparum parasites to artemisinin-based combination therapies (ACTs represents a significant public health threat, indicating the urgent need for new effective compounds to reverse ACT resistance and cure the disease. For this, extensive curation and homogenization of experimental anti-Plasmodium screening data from both in-house and ChEMBL sources were conducted. As a result, a coherent strategy was established that allowed compiling coherent training sets that associate compound structures to the respective antimalarial activity measurements. Seventeen of these training sets led to the successful generation of classification models discriminating whether a compound has a significant probability to be active under the specific conditions of the antimalarial test associated with each set. These models were used in consensus prediction of the most likely active from a series of curcuminoids available in-house. Positive predictions together with a few predicted as inactive were then submitted to experimental in vitro antimalarial testing. A large majority from predicted compounds showed antimalarial activity, but not those predicted as inactive, thus experimentally validating the in silico screening approach. The herein proposed consensus machine learning approach showed its potential to reduce the cost and duration of antimalarial drug discovery.

  4. In Silico Mining for Antimalarial Structure-Activity Knowledge and Discovery of Novel Antimalarial Curcuminoids.

    Science.gov (United States)

    Viira, Birgit; Gendron, Thibault; Lanfranchi, Don Antoine; Cojean, Sandrine; Horvath, Dragos; Marcou, Gilles; Varnek, Alexandre; Maes, Louis; Maran, Uko; Loiseau, Philippe M; Davioud-Charvet, Elisabeth

    2016-06-29

    Malaria is a parasitic tropical disease that kills around 600,000 patients every year. The emergence of resistant Plasmodium falciparum parasites to artemisinin-based combination therapies (ACTs) represents a significant public health threat, indicating the urgent need for new effective compounds to reverse ACT resistance and cure the disease. For this, extensive curation and homogenization of experimental anti-Plasmodium screening data from both in-house and ChEMBL sources were conducted. As a result, a coherent strategy was established that allowed compiling coherent training sets that associate compound structures to the respective antimalarial activity measurements. Seventeen of these training sets led to the successful generation of classification models discriminating whether a compound has a significant probability to be active under the specific conditions of the antimalarial test associated with each set. These models were used in consensus prediction of the most likely active from a series of curcuminoids available in-house. Positive predictions together with a few predicted as inactive were then submitted to experimental in vitro antimalarial testing. A large majority from predicted compounds showed antimalarial activity, but not those predicted as inactive, thus experimentally validating the in silico screening approach. The herein proposed consensus machine learning approach showed its potential to reduce the cost and duration of antimalarial drug discovery.

  5. Microbial Dark Matter Investigations: How Microbial Studies Transform Biological Knowledge and Empirically Sketch a Logic of Scientific Discovery

    Science.gov (United States)

    Bernard, Guillaume; Pathmanathan, Jananan S; Lannes, Romain; Lopez, Philippe; Bapteste, Eric

    2018-01-01

    Abstract Microbes are the oldest and most widespread, phylogenetically and metabolically diverse life forms on Earth. However, they have been discovered only 334 years ago, and their diversity started to become seriously investigated even later. For these reasons, microbial studies that unveil novel microbial lineages and processes affecting or involving microbes deeply (and repeatedly) transform knowledge in biology. Considering the quantitative prevalence of taxonomically and functionally unassigned sequences in environmental genomics data sets, and that of uncultured microbes on the planet, we propose that unraveling the microbial dark matter should be identified as a central priority for biologists. Based on former empirical findings of microbial studies, we sketch a logic of discovery with the potential to further highlight the microbial unknowns. PMID:29420719

  6. The data bonanza improving knowledge discovery in science, engineering, and business

    CERN Document Server

    Atkinson, Malcolm; Brezany, Peter; Corcho, Oscar; Galea, Michelle; Parsons, Mark; Snelling, David; van Hemert, Jano

    2013-01-01

    Complete guidance for mastering the tools and techniques of the digital revolution With the digital revolution opening up tremendous opportunities in many fields, there is a growing need for skilled professionals who can develop data-intensive systems and extract information and knowledge from them. This book frames for the first time a new systematic approach for tackling the challenges of data-intensive computing, providing decision makers and technical experts alike with practical tools for dealing with our exploding data collections. Emphasizing data-intensive thinking an

  7. Final report for Palestine knowledge-sharing network enhancing ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Naser Qadous

    2013-08-27

    Aug 27, 2013 ... needs a Chief Knowledge Officer, a position designed for someone who can connect the loose ends between ... included, "the role of technology in knowledge sharing/management," "the resources of tacit ... Financial Report:.

  8. Selection of entropy-measure parameters for knowledge discovery in heart rate variability data.

    Science.gov (United States)

    Mayer, Christopher C; Bachler, Martin; Hörtenhuber, Matthias; Stocker, Christof; Holzinger, Andreas; Wassertheurer, Siegfried

    2014-01-01

    Heart rate variability is the variation of the time interval between consecutive heartbeats. Entropy is a commonly used tool to describe the regularity of data sets. Entropy functions are defined using multiple parameters, the selection of which is controversial and depends on the intended purpose. This study describes the results of tests conducted to support parameter selection, towards the goal of enabling further biomarker discovery. This study deals with approximate, sample, fuzzy, and fuzzy measure entropies. All data were obtained from PhysioNet, a free-access, on-line archive of physiological signals, and represent various medical conditions. Five tests were defined and conducted to examine the influence of: varying the threshold value r (as multiples of the sample standard deviation σ, or the entropy-maximizing rChon), the data length N, the weighting factors n for fuzzy and fuzzy measure entropies, and the thresholds rF and rL for fuzzy measure entropy. The results were tested for normality using Lilliefors' composite goodness-of-fit test. Consequently, the p-value was calculated with either a two sample t-test or a Wilcoxon rank sum test. The first test shows a cross-over of entropy values with regard to a change of r. Thus, a clear statement that a higher entropy corresponds to a high irregularity is not possible, but is rather an indicator of differences in regularity. N should be at least 200 data points for r = 0.2 σ and should even exceed a length of 1000 for r = rChon. The results for the weighting parameters n for the fuzzy membership function show different behavior when coupled with different r values, therefore the weighting parameters have been chosen independently for the different threshold values. The tests concerning rF and rL showed that there is no optimal choice, but r = rF = rL is reasonable with r = rChon or r = 0.2σ. Some of the tests showed a dependency of the test significance on the data at hand. Nevertheless, as the medical

  9. The Adam and Eve Robot Scientists for the Automated Discovery of Scientific Knowledge

    Science.gov (United States)

    King, Ross

    A Robot Scientist is a physically implemented robotic system that applies techniques from artificial intelligence to execute cycles of automated scientific experimentation. A Robot Scientist can automatically execute cycles of hypothesis formation, selection of efficient experiments to discriminate between hypotheses, execution of experiments using laboratory automation equipment, and analysis of results. The motivation for developing Robot Scientists is to better understand science, and to make scientific research more efficient. The Robot Scientist `Adam' was the first machine to autonomously discover scientific knowledge: both form and experimentally confirm novel hypotheses. Adam worked in the domain of yeast functional genomics. The Robot Scientist `Eve' was originally developed to automate early-stage drug development, with specific application to neglected tropical disease such as malaria, African sleeping sickness, etc. We are now adapting Eve to work with on cancer. We are also teaching Eve to autonomously extract information from the scientific literature.

  10. Data mining and knowledge discovery for big data methodologies, challenge and opportunities

    CERN Document Server

    2014-01-01

    The field of data mining has made significant and far-reaching advances over the past three decades.  Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for patterns in complex structural information. In biomedicine for example, modeling complex biological systems requires linking knowledge across many levels of science, from genes to disease.  Further, the data characteristics of the problems have also grown from static to dynamic and spatiotemporal, complete to incomplete, and centralized to distributed, and grow in their scope and size (this is known as big data). The effective integration of big data for decision-making also requires privacy preservation. The contributions to this monograph summarize the advances of data mining in the respective fields. This volume consists of nine chapters that address subjects ranging from mining da...

  11. Knowledge productivity : designing and testing a method to diagnose knowledge productivity and plan for enhancement

    NARCIS (Netherlands)

    Stam, C.D.

    2007-01-01

    Our economy has changed from an industrial into a knowledge economy in which knowledge productivity has become the main challenge. The lack of appropriate techniques to reveal knowledge productivity hinders organizations to design effective policies aiming at improving knowledge-based performance.

  12. Knowledge discovery from seismic data using neural networks; Descoberta de conhecimento a partir de dados sismicos utilizando redes neurais

    Energy Technology Data Exchange (ETDEWEB)

    Paula, Wesley R. de; Costa, Bruno A.D.; Gomes, Herman M. [Universidade Federal de Campina Grande (UFCG), PB (Brazil)

    2004-07-01

    The analysis and interpretation of seismic data is of fundamental importance to the Oil Industry, since it helps discover geologic formations that are conducive to hydrocarbon accumulation. The use of seismic data in reservoir characterization may be performed through localized data inspections and clustering based on features of common seismic responses. This clustering or classification can be performed in two basic ways: visually, with the help of graphical tools; or using automatic classification techniques, such as statistical models and artificial neural networks. Neural network based methods are generally superior to rule- or knowledge-based systems, since they have a better generalization capability and are fault tolerant. Within this context, the main objective of this work is to describe methods that employ the two main neural network based approaches (supervised and unsupervised) in knowledge discovery from seismic data. Initially, the implementation and experiments were focused on the problem of seismic facies recognition using the unsupervised approach, but in future works, the implementation of the supervised approach, an application to fault detection and a parallel implementation of the proposed methods are planned. (author)

  13. BEST: Next-Generation Biomedical Entity Search Tool for Knowledge Discovery from Biomedical Literature.

    Directory of Open Access Journals (Sweden)

    Sunwon Lee

    Full Text Available As the volume of publications rapidly increases, searching for relevant information from the literature becomes more challenging. To complement standard search engines such as PubMed, it is desirable to have an advanced search tool that directly returns relevant biomedical entities such as targets, drugs, and mutations rather than a long list of articles. Some existing tools submit a query to PubMed and process retrieved abstracts to extract information at query time, resulting in a slow response time and limited coverage of only a fraction of the PubMed corpus. Other tools preprocess the PubMed corpus to speed up the response time; however, they are not constantly updated, and thus produce outdated results. Further, most existing tools cannot process sophisticated queries such as searches for mutations that co-occur with query terms in the literature. To address these problems, we introduce BEST, a biomedical entity search tool. BEST returns, as a result, a list of 10 different types of biomedical entities including genes, diseases, drugs, targets, transcription factors, miRNAs, and mutations that are relevant to a user's query. To the best of our knowledge, BEST is the only system that processes free text queries and returns up-to-date results in real time including mutation information in the results. BEST is freely accessible at http://best.korea.ac.kr.

  14. Knowledge Management: A Model to Enhance Combatant Command Effectiveness

    Science.gov (United States)

    2011-02-15

    implementing the change that is required to achieve the knowledge management vision.43 The Chief Knowledge Management Officer ( KMO ) is overall responsible for...the processes, people/culture and technology in the organization. The Chief KMO develops policy and leads the organization’s knowledge management...integrates team. Reporting directly to the Chief KMO is the Chief Process Manager, Chief Learning Manager and Chief Technology Officer

  15. The MY NASA DATA Project: Tools and a Collaboration Space for Knowledge Discovery

    Science.gov (United States)

    Chambers, L. H.; Alston, E. J.; Diones, D. D.; Moore, S. W.; Oots, P. C.; Phelps, C. S.

    2006-05-01

    The Atmospheric Science Data Center (ASDC) at NASA Langley Research Center is charged with serving a wide user community that is interested in its large data holdings in the areas of Aerosols, Clouds, Radiation Budget, and Tropospheric Chemistry. Most of the data holdings, however, are in large files with specialized data formats. The MY NASA DATA (mynasadata.larc.nasa.gov) project began in 2004, as part of the NASA Research, Education, and Applications Solutions Network (REASoN), in order to open this important resource to a broader community including K-12 education and citizen scientists. MY NASA DATA (short for Mentoring and inquirY using NASA Data on Atmospheric and earth science for Teachers and Amateurs) consists of a web space that collects tools, lesson plans, and specially developed documentation to help the target audience more easily use the vast collection of NASA data about the Earth System. The core piece of the MY NASA DATA project is the creation of microsets (both static and custom) that make data easily accessible. The installation of a Live Access Server (LAS) greatly enhanced the ability for teachers, students, and citizen scientists to create and explore custom microsets of Earth System Science data. The LAS, which is an open source software tool using emerging data standards, also allows the MY NASA DATA team to make available data on other aspects of the Earth System from collaborating data centers. We are currently working with the Physical Oceanography DAAC at the Jet Propulsion Laboratory to bring in several parameters describing the ocean. In addition, MY NASA DATA serves as a central space for the K-12 community to share resources. The site already includes a dozen User-contributed lesson plans. This year we will be focusing on the Citizen Science portion of the site, and will be welcoming user-contributed project ideas, as well as reports of completed projects. An e-mentor network has also been created to involve a wider community in

  16. Enhancing knowledge sharing management using BIM technology in construction.

    Science.gov (United States)

    Ho, Shih-Ping; Tserng, Hui-Ping; Jan, Shu-Hui

    2013-01-01

    Construction knowledge can be communicated and reused among project managers and jobsite engineers to alleviate problems on a construction jobsite and reduce the time and cost of solving problems related to constructability. This paper proposes a new methodology for the sharing of construction knowledge by using Building Information Modeling (BIM) technology. The main characteristics of BIM include illustrating 3D CAD-based presentations and keeping information in a digital format and facilitation of easy updating and transfer of information in the BIM environment. Using the BIM technology, project managers and engineers can gain knowledge related to BIM and obtain feedback provided by jobsite engineers for future reference. This study addresses the application of knowledge sharing management using BIM technology and proposes a BIM-based Knowledge Sharing Management (BIMKSM) system for project managers and engineers. The BIMKSM system is then applied in a selected case study of a construction project in Taiwan to demonstrate the effectiveness of sharing knowledge in the BIM environment. The results demonstrate that the BIMKSM system can be used as a visual BIM-based knowledge sharing management platform by utilizing the BIM technology.

  17. A semantically rich and standardised approach enhancing discovery of sensor data and metadata

    Science.gov (United States)

    Kokkinaki, Alexandra; Buck, Justin; Darroch, Louise

    2016-04-01

    The marine environment plays an essential role in the earth's climate. To enhance the ability to monitor the health of this important system, innovative sensors are being produced and combined with state of the art sensor technology. As the number of sensors deployed is continually increasing,, it is a challenge for data users to find the data that meet their specific needs. Furthermore, users need to integrate diverse ocean datasets originating from the same or even different systems. Standards provide a solution to the above mentioned challenges. The Open Geospatial Consortium (OGC) has created Sensor Web Enablement (SWE) standards that enable different sensor networks to establish syntactic interoperability. When combined with widely accepted controlled vocabularies, they become semantically rich and semantic interoperability is achievable. In addition, Linked Data is the recommended best practice for exposing, sharing and connecting information on the Semantic Web using Uniform Resource Identifiers (URIs), Resource Description Framework (RDF) and RDF Query Language (SPARQL). As part of the EU-funded SenseOCEAN project, the British Oceanographic Data Centre (BODC) is working on the standardisation of sensor metadata enabling 'plug and play' sensor integration. Our approach combines standards, controlled vocabularies and persistent URIs to publish sensor descriptions, their data and associated metadata as 5 star Linked Data and OGC SWE (SensorML, Observations & Measurements) standard. Thus sensors become readily discoverable, accessible and useable via the web. Content and context based searching is also enabled since sensors descriptions are understood by machines. Additionally, sensor data can be combined with other sensor or Linked Data datasets to form knowledge. This presentation will describe the work done in BODC to achieve syntactic and semantic interoperability in the sensor domain. It will illustrate the reuse and extension of the Semantic Sensor

  18. Enhancing acronym/abbreviation knowledge bases with semantic information.

    Science.gov (United States)

    Torii, Manabu; Liu, Hongfang

    2007-10-11

    In the biomedical domain, a terminology knowledge base that associates acronyms/abbreviations (denoted as SFs) with the definitions (denoted as LFs) is highly needed. For the construction such terminology knowledge base, we investigate the feasibility to build a system automatically assigning semantic categories to LFs extracted from text. Given a collection of pairs (SF,LF) derived from text, we i) assess the coverage of LFs and pairs (SF,LF) in the UMLS and justify the need of a semantic category assignment system; and ii) automatically derive name phrases annotated with semantic category and construct a system using machine learning. Utilizing ADAM, an existing collection of (SF,LF) pairs extracted from MEDLINE, our system achieved an f-measure of 87% when assigning eight UMLS-based semantic groups to LFs. The system has been incorporated into a web interface which integrates SF knowledge from multiple SF knowledge bases. Web site: http://gauss.dbb.georgetown.edu/liblab/SFThesurus.

  19. Constrained Combinatorial Libraries of Gp2 Proteins Enhance Discovery of PD-L1 Binders.

    Science.gov (United States)

    Kruziki, Max A; Sarma, Vidur; Hackel, Benjamin J

    2018-06-05

    Engineered protein ligands are used for molecular therapy, diagnostics, and industrial biotechnology. The Gp2 domain is a 45-amino acid scaffold that has been evolved for specific, high-affinity binding to multiple targets by diversification of two solvent-exposed loops. Inspired by sitewise enrichment of select amino acids, including cysteine pairs, in earlier Gp2 discovery campaigns, we hypothesized that the breadth and efficiency of de novo Gp2 discovery will be aided by sitewise amino acid constraint within combinatorial library design. We systematically constructed eight libraries and comparatively evaluated their efficacy for binder discovery via yeast display against a panel of targets. Conservation of a cysteine pair at the termini of the first diversified paratope loop increased binder discovery 16-fold ( p libraries with conserved cysteine pairs, within the second loop or an interloop pair, did not aid discovery thereby indicating site-specific impact. Via a yeast display protease resistance assay, Gp2 variants from the loop one cysteine pair library were 3.3 ± 2.1-fold ( p = 0.005) more stable than nonconstrained variants. Sitewise constraint of noncysteine residues-guided by previously evolved binders, natural Gp2 homology, computed stability, and structural analysis-did not aid discovery. A panel of binders to programmed death ligand 1 (PD-L1), a key target in cancer immunotherapy, were discovered from the loop 1 cysteine constraint library. Affinity maturation via loop walking resulted in strong, specific cellular PD-L1 affinity ( K d = 6-9 nM).

  20. Rough Sets as a Knowledge Discovery and Classification Tool for the Diagnosis of Students with Learning Disabilities

    Directory of Open Access Journals (Sweden)

    Yu-Chi Lin

    2011-02-01

    Full Text Available Due to the implicit characteristics of learning disabilities (LDs, the diagnosis of students with learning disabilities has long been a difficult issue. Artificial intelligence techniques like artificial neural network (ANN and support vector machine (SVM have been applied to the LD diagnosis problem with satisfactory outcomes. However, special education teachers or professionals tend to be skeptical to these kinds of black-box predictors. In this study, we adopt the rough set theory (RST, which can not only perform as a classifier, but may also produce meaningful explanations or rules, to the LD diagnosis application. Our experiments indicate that the RST approach is competitive as a tool for feature selection, and it performs better in term of prediction accuracy than other rulebased algorithms such as decision tree and ripper algorithms. We also propose to mix samples collected from sources with different LD diagnosis procedure and criteria. By pre-processing these mixed samples with simple and readily available clustering algorithms, we are able to improve the quality and support of rules generated by the RST. Overall, our study shows that the rough set approach, as a classification and knowledge discovery tool, may have great potential in playing an essential role in LD diagnosis.

  1. The fragile x mental retardation syndrome 20 years after the FMR1 gene discovery: an expanding universe of knowledge.

    Science.gov (United States)

    Rousseau, François; Labelle, Yves; Bussières, Johanne; Lindsay, Carmen

    2011-08-01

    The fragile X mental retardation (FXMR) syndrome is one of the most frequent causes of mental retardation. Affected individuals display a wide range of additional characteristic features including behavioural and physical phenotypes, and the extent to which individuals are affected is highly variable. For these reasons, elucidation of the pathophysiology of this disease has been an important challenge to the scientific community. 1991 marks the year of the discovery of both the FMR1 gene mutations involved in this disease, and of their dynamic nature. Although a mouse model for the disease has been available for 16 years and extensive research has been performed on the FMR1 protein (FMRP), we still understand little about how the disease develops, and no treatment has yet been shown to be effective. In this review, we summarise current knowledge on FXMR with an emphasis on the technical challenges of molecular diagnostics, on its prevalence and dynamics among populations, and on the potential of screening for FMR1 mutations.

  2. The Fragile X Mental Retardation Syndrome 20 Years After the FMR1 Gene Discovery: an Expanding Universe of Knowledge

    Science.gov (United States)

    Rousseau, François; Labelle, Yves; Bussières, Johanne; Lindsay, Carmen

    2011-01-01

    The fragile X mental retardation (FXMR) syndrome is one of the most frequent causes of mental retardation. Affected individuals display a wide range of additional characteristic features including behavioural and physical phenotypes, and the extent to which individuals are affected is highly variable. For these reasons, elucidation of the pathophysiology of this disease has been an important challenge to the scientific community. 1991 marks the year of the discovery of both the FMR1 gene mutations involved in this disease, and of their dynamic nature. Although a mouse model for the disease has been available for 16 years and extensive research has been performed on the FMR1 protein (FMRP), we still understand little about how the disease develops, and no treatment has yet been shown to be effective. In this review, we summarise current knowledge on FXMR with an emphasis on the technical challenges of molecular diagnostics, on its prevalence and dynamics among populations, and on the potential of screening for FMR1 mutations. PMID:21912443

  3. Exploring the Malaysian Rural School Teachers' Professional Local Knowledge in Enhancing Students' Thinking Skills

    Science.gov (United States)

    Jamil, Hazri; Arbaa, Rohani; Ahmad, Mohamad Zohir

    2017-01-01

    This paper discussed a qualitative research findings on the case of Malaysian teachers employed their professional local knowledge for enhancing students' thinking skills in classroom practices. In this paper, a teacher's professional local knowledge is viewed as a teacher's professional knowledge and skills developed through the combination of…

  4. The future of drug discovery: enabling technologies for enhancing lead characterization and profiling therapeutic potential.

    Science.gov (United States)

    Janero, David R

    2014-08-01

    Technology often serves as a handmaiden and catalyst of invention. The discovery of safe, effective medications depends critically upon experimental approaches capable of providing high-impact information on the biological effects of drug candidates early in the discovery pipeline. This information can enable reliable lead identification, pharmacological compound differentiation and successful translation of research output into clinically useful therapeutics. The shallow preclinical profiling of candidate compounds promulgates a minimalistic understanding of their biological effects and undermines the level of value creation necessary for finding quality leads worth moving forward within the development pipeline with efficiency and prognostic reliability sufficient to help remediate the current pharma-industry productivity drought. Three specific technologies discussed herein, in addition to experimental areas intimately associated with contemporary drug discovery, appear to hold particular promise for strengthening the preclinical valuation of drug candidates by deepening lead characterization. These are: i) hydrogen-deuterium exchange mass spectrometry for characterizing structural and ligand-interaction dynamics of disease-relevant proteins; ii) activity-based chemoproteomics for profiling the functional diversity of mammalian proteomes; and iii) nuclease-mediated precision gene editing for developing more translatable cellular and in vivo models of human diseases. When applied in an informed manner congruent with the clinical understanding of disease processes, technologies such as these that span levels of biological organization can serve as valuable enablers of drug discovery and potentially contribute to reducing the current, unacceptably high rates of compound clinical failure.

  5. Enhancing Knowledge Sharing and Research Collaboration among Academics: The Role of Knowledge Management

    Science.gov (United States)

    Tan, Christine Nya-Ling

    2016-01-01

    Although knowledge sharing (KS) has been acknowledged as important, universities face issues that may hinder active sharing among its faculty members such as the absence of trust among its members or insufficient incentives rewarded to those who deserved it. The aim of this research is to focus on the impact of knowledge management (KM) factors in…

  6. Rethinking Knowledge Management: Strategies for Enhancing District-Level Teacher and Leader Tacit Knowledge Sharing

    Science.gov (United States)

    Edge, Karen

    2013-01-01

    Grounded within knowledge management (KM) theory and conceptions of tacit and explicit knowledge, this article draws on historical evidence from the Early Years Literacy Project (EYLP), a four-year instructional renewal strategy implemented across 100 schools in a large Canadian school district. The EYLP management approach included a series of…

  7. Enhancing Conceptual Knowledge of Energy in Biology with Incorrect Representations

    Science.gov (United States)

    Wernecke, Ulrike; Schütte, Kerstin; Schwanewedel, Julia; Harms, Ute

    2018-01-01

    Energy is an important concept in all natural sciences, and a challenging one for school science education. Students' conceptual knowledge of energy is often low, and they entertain misconceptions. Educational research in science and mathematics suggests that learning through depictive representations and learning from errors, based on the theory…

  8. Enhancing the Teaching-Learning Process: A Knowledge Management Approach

    Science.gov (United States)

    Bhusry, Mamta; Ranjan, Jayanthi

    2012-01-01

    Purpose: The purpose of this paper is to emphasize the need for knowledge management (KM) in the teaching-learning process in technical educational institutions (TEIs) in India, and to assert the impact of information technology (IT) based KM intervention in the teaching-learning process. Design/methodology/approach: The approach of the paper is…

  9. Enhancing Media Personalization by Extracting Similarity Knowledge from Metadata

    DEFF Research Database (Denmark)

    Butkus, Andrius

    be seen as a cognitive foundation for modeling concepts. Conceptual Spaces is applied in this thesis to analyze media in terms of its dimensions and knowledge domains, which in return defines properties and concepts. One of the most important domains in terms of describing media is the emotional one...... only “more of the same” type of content which does not necessarily lead to the meaningful personalization. Another way to approach similarity is to find a similar underlying meaning in the content. Aspects of meaning in media can be represented using Gardenfors Conceptual Spaces theory, which can......) using Latent Semantic Analysis (one of the unsupervised machine learning techniques). It presents three separate cases to illustrate the similarity knowledge extraction from the metadata, where the emotional components in each case represents different abstraction levels – genres, synopsis and lyrics...

  10. Experiential Learning and Research Ethics: Enhancing Knowledge through Action

    Science.gov (United States)

    Teixeira-Poit, Stephanie M.; Cameron, Abigail E.; Schulman, Michael D.

    2011-01-01

    How can instructors use experiential learning strategies to enhance student understanding of research ethics and responsible research conduct? In this article, the authors review literature on using experiential learning to teach research ethics and responsible research conduct. They present a three-step exercise for teaching research ethics and…

  11. Semantic Document Model to Enhance Data and Knowledge Interoperability

    Science.gov (United States)

    Nešić, Saša

    To enable document data and knowledge to be efficiently shared and reused across application, enterprise, and community boundaries, desktop documents should be completely open and queryable resources, whose data and knowledge are represented in a form understandable to both humans and machines. At the same time, these are the requirements that desktop documents need to satisfy in order to contribute to the visions of the Semantic Web. With the aim of achieving this goal, we have developed the Semantic Document Model (SDM), which turns desktop documents into Semantic Documents as uniquely identified and semantically annotated composite resources, that can be instantiated into human-readable (HR) and machine-processable (MP) forms. In this paper, we present the SDM along with an RDF and ontology-based solution for the MP document instance. Moreover, on top of the proposed model, we have built the Semantic Document Management System (SDMS), which provides a set of services that exploit the model. As an application example that takes advantage of SDMS services, we have extended MS Office with a set of tools that enables users to transform MS Office documents (e.g., MS Word and MS PowerPoint) into Semantic Documents, and to search local and distant semantic document repositories for document content units (CUs) over Semantic Web protocols.

  12. Collaborative Professional Development in Higher Education: Developing Knowledge of Technology Enhanced Teaching

    Science.gov (United States)

    Jaipal-Jamani, Kamini; Figg, Candace; Gallagher, Tiffany; Scott, Ruth McQuirter; Ciampa, Katia

    2015-01-01

    This paper describes a professional development initiative for teacher educators, called the "Digital Pedagogies Collaboration," in which the goal was to build faculty knowledge about technology enhanced teaching (TPACK knowledge), develop a collaborative learning and research community of faculty members around technology enhanced…

  13. Online system for knowledge assessment enhances students' results on school knowledge test.

    Science.gov (United States)

    Kralj, Benjamin; Glazar, Sasa Aleksej

    2013-01-01

    Variety of online tools were built to help assessing students' performance in school. Many teachers changed their methods of assessment from paper-and-pencil (P&P) to online systems. In this study we analyse the influence that using an online system for knowledge assessment has on students' knowledge. Based on both a literature study and our own research we designed and built an online system for knowledge assessment. The system is evaluated using two groups of primary school teachers and students (N = 686) in Slovenia: an experimental and a control group. Students solved P&P exams on several occasions. The experimental group was allowed to access the system either at school or at home for a limited period during the presentation of a selected school topic. Students in the experimental group were able to solve tasks and compare their own achievements with those of their coevals. A comparison of the P&P school exams results achieved by both groups revealed a positive effect on subject topic comprehension for those with access to the online self-assessment system.

  14. Enhancing climate governance through indigenous knowledge: Case in sustainability science

    Directory of Open Access Journals (Sweden)

    Nelson Chanza

    2016-03-01

    Full Text Available The current tempo of climate change strategies puts the notion of sustainability in question. In this philosophy, mitigation and adaptation strategies ought to be appropriate to the sectors and communities that are targeted. There is a growing realisation that the effectiveness of both strategies hinges on climate governance, which also informs their sustainability. The application of the climate governance concept by the technocratic divide (policymakers and climate practitioners to communities facing climate change impacts, however, is still a poorly developed field, despite extensive treatment by academia. By drawing heavily from conceptual and analytical review of scholarship on the utility of indigenous knowledge (IK in climate science, these authors argue that IK can be deployed in the practice of climate governance. It reveals that the merits of such a deployment lie in the understanding that the tenets of IK and climate governance overlap and are complementary. This is exhibited by examining the conceptual, empirical and sustainability strands of the climate governance-IK nexus. In the milieu of climate change problems, it is argued that the basic elements of climate governance, where actions are informed by the principles of decentralisation and autonomy; accountability and transparency; responsiveness and flexibility; and participation and inclusion, can be pragmatic particularly to communities who have been religiously observing changes in their environment. Therefore, it becomes necessary to invigorate the participation of communities, with their IK, in designing climate change interventions, which in this view can be a means to attain the objectives of climate governance.

  15. UCLA's Molecular Screening Shared Resource: enhancing small molecule discovery with functional genomics and new technology.

    Science.gov (United States)

    Damoiseaux, Robert

    2014-05-01

    The Molecular Screening Shared Resource (MSSR) offers a comprehensive range of leading-edge high throughput screening (HTS) services including drug discovery, chemical and functional genomics, and novel methods for nano and environmental toxicology. The MSSR is an open access environment with investigators from UCLA as well as from the entire globe. Industrial clients are equally welcome as are non-profit entities. The MSSR is a fee-for-service entity and does not retain intellectual property. In conjunction with the Center for Environmental Implications of Nanotechnology, the MSSR is unique in its dedicated and ongoing efforts towards high throughput toxicity testing of nanomaterials. In addition, the MSSR engages in technology development eliminating bottlenecks from the HTS workflow and enabling novel assays and readouts currently not available.

  16. Knowledge discovery for Deep Phenotyping serious mental illness from Electronic Mental Health records [version 2; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Richard Jackson

    2018-05-01

    Full Text Available Background: Deep Phenotyping is the precise and comprehensive analysis of phenotypic features in which the individual components of the phenotype are observed and described. In UK mental health clinical practice, most clinically relevant information is recorded as free text in the Electronic Health Record, and offers a granularity of information beyond what is expressed in most medical knowledge bases. The SNOMED CT nomenclature potentially offers the means to model such information at scale, yet given a sufficiently large body of clinical text collected over many years, it is difficult to identify the language that clinicians favour to express concepts. Methods: By utilising a large corpus of healthcare data, we sought to make use of semantic modelling and clustering techniques to represent the relationship between the clinical vocabulary of internationally recognised SMI symptoms and the preferred language used by clinicians within a care setting. We explore how such models can be used for discovering novel vocabulary relevant to the task of phenotyping Serious Mental Illness (SMI with only a small amount of prior knowledge.  Results: 20 403 terms were derived and curated via a two stage methodology. The list was reduced to 557 putative concepts based on eliminating redundant information content. These were then organised into 9 distinct categories pertaining to different aspects of psychiatric assessment. 235 concepts were found to be expressions of putative clinical significance. Of these, 53 were identified having novel synonymy with existing SNOMED CT concepts. 106 had no mapping to SNOMED CT. Conclusions: We demonstrate a scalable approach to discovering new concepts of SMI symptomatology based on real-world clinical observation. Such approaches may offer the opportunity to consider broader manifestations of SMI symptomatology than is typically assessed via current diagnostic frameworks, and create the potential for enhancing

  17. Strategies for enhancing the effectiveness of metagenomic-based enzyme discovery in lignocellulytic microbial communities

    Energy Technology Data Exchange (ETDEWEB)

    DeAngelis, K.M.; Gladden, J.G.; Allgaier, M.; D' haeseleer, P.; Fortney, J.L.; Reddy, A.; Hugenholtz, P.; Singer, S.W.; Vander Gheynst, J.; Silver, W.L.; Simmons, B.; Hazen, T.C.

    2010-03-01

    Producing cellulosic biofuels from plant material has recently emerged as a key U.S. Department of Energy goal. For this technology to be commercially viable on a large scale, it is critical to make production cost efficient by streamlining both the deconstruction of lignocellulosic biomass and fuel production. Many natural ecosystems efficiently degrade lignocellulosic biomass and harbor enzymes that, when identified, could be used to increase the efficiency of commercial biomass deconstruction. However, ecosystems most likely to yield relevant enzymes, such as tropical rain forest soil in Puerto Rico, are often too complex for enzyme discovery using current metagenomic sequencing technologies. One potential strategy to overcome this problem is to selectively cultivate the microbial communities from these complex ecosystems on biomass under defined conditions, generating less complex biomass-degrading microbial populations. To test this premise, we cultivated microbes from Puerto Rican soil or green waste compost under precisely defined conditions in the presence dried ground switchgrass (Panicum virgatum L.) or lignin, respectively, as the sole carbon source. Phylogenetic profiling of the two feedstock-adapted communities using SSU rRNA gene amplicon pyrosequencing or phylogenetic microarray analysis revealed that the adapted communities were significantly simplified compared to the natural communities from which they were derived. Several members of the lignin-adapted and switchgrass-adapted consortia are related to organisms previously characterized as biomass degraders, while others were from less well-characterized phyla. The decrease in complexity of these communities make them good candidates for metagenomic sequencing and will likely enable the reconstruction of a greater number of full length genes, leading to the discovery of novel lignocellulose-degrading enzymes adapted to feedstocks and conditions of interest.

  18. Usability of Discovery Portals

    OpenAIRE

    Bulens, J.D.; Vullings, L.A.E.; Houtkamp, J.M.; Vanmeulebrouk, B.

    2013-01-01

    As INSPIRE progresses to be implemented in the EU, many new discovery portals are built to facilitate finding spatial data. Currently the structure of the discovery portals is determined by the way spatial data experts like to work. However, we argue that the main target group for discovery portals are not spatial data experts but professionals with limited spatial knowledge, and a focus outside the spatial domain. An exploratory usability experiment was carried out in which three discovery p...

  19. Does External Knowledge Sourcing Enhance Market Performance? Evidence from the Korean Manufacturing Industry.

    Science.gov (United States)

    Lee, Kibaek; Yoo, Jaeheung; Choi, Munkee; Zo, Hangjung; Ciganek, Andrew P

    2016-01-01

    Firms continuously search for external knowledge that can contribute to product innovation, which may ultimately increase market performance. The relationship between external knowledge sourcing and market performance is not well-documented. The extant literature primarily examines the causal relationship between external knowledge sources and product innovation performance or to identify factors which moderates the relationship between external knowledge sourcing and product innovation. Non-technological innovations, such as organization and marketing innovations, intervene in the process of external knowledge sourcing to product innovation to market performance but has not been extensively examined. This study addresses two research questions: does external knowledge sourcing lead to market performance and how does external knowledge sourcing interact with a firm's different innovation activities to enhance market performance. This study proposes a comprehensive model to capture the causal mechanism from external knowledge sourcing to market performance. The research model was tested using survey data from manufacturing firms in South Korea and the results demonstrate a strong statistical relationship in the path of external knowledge sourcing (EKS) to product innovation performance (PIP) to market performance (MP). Organizational innovation is an antecedent to EKS while marketing innovation is a consequence of EKS, which significantly influences PIP and MP. The results imply that any potential EKS effort should also consider organizational innovations which may ultimately enhance market performance. Theoretical and practical implications are discussed as well as concluding remarks.

  20. Does External Knowledge Sourcing Enhance Market Performance? Evidence from the Korean Manufacturing Industry

    Science.gov (United States)

    Lee, Kibaek; Yoo, Jaeheung; Choi, Munkee; Zo, Hangjung; Ciganek, Andrew P.

    2016-01-01

    Firms continuously search for external knowledge that can contribute to product innovation, which may ultimately increase market performance. The relationship between external knowledge sourcing and market performance is not well-documented. The extant literature primarily examines the causal relationship between external knowledge sources and product innovation performance or to identify factors which moderates the relationship between external knowledge sourcing and product innovation. Non-technological innovations, such as organization and marketing innovations, intervene in the process of external knowledge sourcing to product innovation to market performance but has not been extensively examined. This study addresses two research questions: does external knowledge sourcing lead to market performance and how does external knowledge sourcing interact with a firm’s different innovation activities to enhance market performance. This study proposes a comprehensive model to capture the causal mechanism from external knowledge sourcing to market performance. The research model was tested using survey data from manufacturing firms in South Korea and the results demonstrate a strong statistical relationship in the path of external knowledge sourcing (EKS) to product innovation performance (PIP) to market performance (MP). Organizational innovation is an antecedent to EKS while marketing innovation is a consequence of EKS, which significantly influences PIP and MP. The results imply that any potential EKS effort should also consider organizational innovations which may ultimately enhance market performance. Theoretical and practical implications are discussed as well as concluding remarks. PMID:28006022

  1. Enhancing hit identification in Mycobacterium tuberculosis drug discovery using validated dual-event Bayesian models.

    Directory of Open Access Journals (Sweden)

    Sean Ekins

    Full Text Available High-throughput screening (HTS in whole cells is widely pursued to find compounds active against Mycobacterium tuberculosis (Mtb for further development towards new tuberculosis (TB drugs. Hit rates from these screens, usually conducted at 10 to 25 µM concentrations, typically range from less than 1% to the low single digits. New approaches to increase the efficiency of hit identification are urgently needed to learn from past screening data. The pharmaceutical industry has for many years taken advantage of computational approaches to optimize compound libraries for in vitro testing, a practice not fully embraced by academic laboratories in the search for new TB drugs. Adapting these proven approaches, we have recently built and validated Bayesian machine learning models for predicting compounds with activity against Mtb based on publicly available large-scale HTS data from the Tuberculosis Antimicrobial Acquisition Coordinating Facility. We now demonstrate the largest prospective validation to date in which we computationally screened 82,403 molecules with these Bayesian models, assayed a total of 550 molecules in vitro, and identified 124 actives against Mtb. Individual hit rates for the different datasets varied from 15-28%. We have identified several FDA approved and late stage clinical candidate kinase inhibitors with activity against Mtb which may represent starting points for further optimization. The computational models developed herein and the commercially available molecules derived from them are now available to any group pursuing Mtb drug discovery.

  2. Characterization of Greater Middle Eastern genetic variation for enhanced disease gene discovery.

    Science.gov (United States)

    Scott, Eric M; Halees, Anason; Itan, Yuval; Spencer, Emily G; He, Yupeng; Azab, Mostafa Abdellateef; Gabriel, Stacey B; Belkadi, Aziz; Boisson, Bertrand; Abel, Laurent; Clark, Andrew G; Alkuraya, Fowzan S; Casanova, Jean-Laurent; Gleeson, Joseph G

    2016-09-01

    The Greater Middle East (GME) has been a central hub of human migration and population admixture. The tradition of consanguinity, variably practiced in the Persian Gulf region, North Africa, and Central Asia, has resulted in an elevated burden of recessive disease. Here we generated a whole-exome GME variome from 1,111 unrelated subjects. We detected substantial diversity and admixture in continental and subregional populations, corresponding to several ancient founder populations with little evidence of bottlenecks. Measured consanguinity rates were an order of magnitude above those in other sampled populations, and the GME population exhibited an increased burden of runs of homozygosity (ROHs) but showed no evidence for reduced burden of deleterious variation due to classically theorized 'genetic purging'. Applying this database to unsolved recessive conditions in the GME population reduced the number of potential disease-causing variants by four- to sevenfold. These results show variegated genetic architecture in GME populations and support future human genetic discoveries in Mendelian and population genetics.

  3. A Linked Science Investigation: Enhancing Climate Change Data Discovery with Semantic Technologies.

    Science.gov (United States)

    Pouchard, Line C; Branstetter, Marcia L; Cook, Robert B; Devarakonda, Ranjeet; Green, Jim; Palanisamy, Giri; Alexander, Paul; Noy, Natalya F

    2013-09-01

    Linked Science is the practice of inter-connecting scientific assets by publishing, sharing and linking scientific data and processes in end-to-end loosely coupled workflows that allow the sharing and re-use of scientific data. Much of this data does not live in the cloud or on the Web, but rather in multi-institutional data centers that provide tools and add value through quality assurance, validation, curation, dissemination, and analysis of the data. In this paper, we make the case for the use of scientific scenarios in Linked Science. We propose a scenario in river-channel transport that requires biogeochemical experimental data and global climate-simulation model data from many sources. We focus on the use of ontologies-formal machine-readable descriptions of the domain-to facilitate search and discovery of this data. Mercury, developed at Oak Ridge National Laboratory, is a tool for distributed metadata harvesting, search and retrieval. Mercury currently provides uniform access to more than 100,000 metadata records; 30,000 scientists use it each month. We augmented search in Mercury with ontologies, such as the ontologies in the Semantic Web for Earth and Environmental Terminology (SWEET) collection by prototyping a component that provides access to the ontology terms from Mercury. We evaluate the coverage of SWEET for the ORNL Distributed Active Archive Center (ORNL DAAC).

  4. The Emergence of New Successful Export Activities in Argentina: Self-Discovery, Knowledge Niches, or Barriers to Riches?

    OpenAIRE

    Gabriel Sánchez; Ricardo Rozemberg; Inés Butler; Hernán Rufo

    2008-01-01

    This paper examines the emergence of three new successful export activities in Argentina: biotechnology applied to human health, blueberries and chocolate confections. The main interest lies in ascertaining why these sectors/products were targeted, on which previously accumulated capabilities they were built upon, and what type of hurdles they faced and how they were overcome. In the absence of government support for discovery, these new exports emerged because the pioneers could introduce pe...

  5. Leveraging cloud based big data analytics in knowledge management for enhanced decision making in organizations

    OpenAIRE

    Shorfuzzaman, Mohammad

    2017-01-01

    In recent past, big data opportunities have gained much momentum to enhance knowledge management in organizations. However, big data due to its various properties like high volume, variety, and velocity can no longer be effectively stored and analyzed with traditional data management techniques to generate values for knowledge development. Hence, new technologies and architectures are required to store and analyze this big data through advanced data analytics and in turn generate vital real-t...

  6. Towards Ubiquitous Peer Review Strategies to Sustain and Enhance a Clinical Knowledge Management Framework

    Science.gov (United States)

    Rocha, Roberto A.; Bradshaw, Richard L.; Bigelow, Sharon M.; Hanna, Timothy P.; Fiol, Guilherme Del; Hulse, Nathan C.; Roemer, Lorrie K.; Wilkinson, Steven G.

    2006-01-01

    Widespread cooperation between domain experts and front-line clinicians is a key component of any successful clinical knowledge management framework. Peer review is an established form of cooperation that promotes the dissemination of new knowledge. The authors describe three peer collaboration scenarios that have been implemented using the knowledge management infrastructure available at Intermountain Healthcare. Utilization results illustrating the early adoption patterns of the proposed scenarios are presented and discussed, along with succinct descriptions of planned enhancements and future implementation efforts. PMID:17238422

  7. Enhancing knowledge retention in higher education: A case of the University of Zambia

    Directory of Open Access Journals (Sweden)

    Sitali Wamundila

    2011-08-01

    Full Text Available The purpose of this study was to investigate how knowledge retention may be enhanced at the University of Zambia (UNZA. A quantitative case study design employing a triangulation of data collection methods was used. Data were collected using interviews and questionnaires. Purposive sampling was used to determine participants for the interviews whilst stratified random sampling was employed to select the respondents for the questionnaire. The quantitative and qualitative data that was analysed using SPSS® indicates that UNZA lacked certain knowledge retention practices that might enable it to retain operational relevant knowledge. In view of the findings, the study recommends the adoption of a knowledge retention framework that could be embedded in UNZA’s knowledge management policy.

  8. Discovery of a new function of curcumin which enhances its anticancer therapeutic potency

    Science.gov (United States)

    Nagahama, Koji; Utsumi, Tomoya; Kumano, Takayuki; Maekawa, Saeko; Oyama, Naho; Kawakami, Junji

    2016-08-01

    Curcumin has received immense attention over the past decades because of its diverse biological activities and recognized as a promising drug candidate in a large number of diseases. However, its clinical application has been hindered due to extremely low aqueous solubility, chemical stability, and cellular uptake. In this study, we discovered quite a new function of curcumin, i.e. pH-responsive endosomal disrupting activity, derived from curcumin’s self-assembly. We selected anticancer activity as an example of biological activities of curcumin, and investigated the contribution of pH-responsive property to its anticancer activity. As a result, we demonstrated that the pH-responsive property significantly enhances the anticancer activity of curcumin. Furthermore, we demonstrated a utility of the pH-responsive property of curcumin as delivery nanocarriers for doxorubicin toward combination cancer therapy. These results clearly indicate that the smart curcumin assemblies act as promising nanoplatform for development of curcumin-based therapeutics.

  9. Discovery of Several Novel Targets that Enhance β-Carotene Production in Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Jia Li

    2017-06-01

    Full Text Available β-Carotene is the precursor of vitamin A, and also exhibits multiple pharmaceutical functions by itself. In comparison to chemical synthesis, the production of β-carotene in microbes by metabolic engineering strategy is relatively inexpensive. Identifying genes enhancing β-carotene production in microbes is important for engineering a strain of producing higher yields of β-carotene. Most of previous efforts in identifying the gene targets have focused on the isoprenoid pathway where the β-carotene biosynthesis belongs. However, due to the complex interactions between metabolic fluxes, seemingly irrelevant genes that are outside the isoprenoid pathway might also affect β-carotene biosynthesis. To this end, here we provided an example that several novel gene targets, which are outside the isoprenoid pathway, have improving effects on β-carotene synthesis in yeast cells, when they were over-expressed. Among these targets, the class E protein of the vacuolar protein-sorting pathway (Did2 led to the highest improvement in β-carotene yields, which was 2.1-fold to that of the corresponding control. This improvement was further explained by the observation that the overexpression of the DID2 gene generally boosted the transcriptions of β-carotene pathway genes. The mechanism by which the other targets improve the production of β-carotene is discussed.

  10. Subject Knowledge Enhancement Courses for Creating New Chemistry and Physics Teachers: The Students' Perceptions

    Science.gov (United States)

    Tynan, Richard; Jones, Robert Bryn; Mallaburn, Andrea; Clays, Ken

    2016-01-01

    Subject knowledge enhancement (SKE) courses are one option open in England to graduates with a science background whose first degree content is judged to be insufficient to train to become chemistry or physics teachers. Previous articles in "School Science Review" have discussed the structure of one type of extended SKE course offered at…

  11. Using Film and Intergenerational Colearning to Enhance Knowledge and Attitudes toward Older Adults

    Science.gov (United States)

    McCleary, Roseanna

    2014-01-01

    This study evaluated whether two evidence-based methods used collaboratively, intergenerational colearning and use of films/documentaries in an educational context, enhanced knowledge levels and attitudes toward older adults in nursing, social work, and other allied profession students. Students participated in a gerontology film festival where…

  12. Supporting Knowledge Integration in Chemistry with a Visualization-Enhanced Inquiry Unit

    Science.gov (United States)

    Chiu, Jennifer L.; Linn, Marcia C.

    2014-01-01

    This paper describes the design and impact of an inquiry-oriented online curriculum that takes advantage of dynamic molecular visualizations to improve students' understanding of chemical reactions. The visualization-enhanced unit uses research-based guidelines following the knowledge integration framework to help students develop coherent…

  13. Development of Education Programs in Mountainous Regions to Enhance the Culture and Knowledge of Minority Nationalities.

    Science.gov (United States)

    Wei, Shiyuan; Zhou, Guangda

    1989-01-01

    Describes the historical development of educational programs which could enhance the culture and knowledge of minorities in the mountainous regions of China. Identifies current major problems in minority education and lists statistical information for the school population. Provides guidelines for developing a minority education program. (KO)

  14. Enhancing knowledge and attitudes in pain management: a pain management education program for nursing home staff.

    Science.gov (United States)

    Tse, Mimi Mun Yee; Ho, Suki S K

    2014-03-01

    The aim of the study was to examine the effectiveness of a pain management program (PMP) in enhancing the knowledge and attitudes of health care workers in pain management. Many nursing home residents suffer from pain, and treatment of pain is often inadequate. Failure of health care workers to assess pain and their insufficient knowledge of pain management are barriers to adequate treatment. It was a quasiexperimental pretest and posttest study. Four nursing homes were approached, and 88 staff joined the 8-week PMP. Demographics and the knowledge and attitudes regarding pain were collected with the use of the Nurse's Knowledge and Attitudes Survey Regarding Pain-Chinese version (NKASRP-C) before and after the PMP. A deficit in knowledge and attitudes related to pain management was prominent before the PMP, and there was a significant increase in pain knowledge and attitudes from 7.9 ± SD 3.52 to 19.2 ± SD4.4 (p nursing staff and enable them to provide adequate and appropriate care to older persons in pain. PMPs for nurses and all health care professionals are important in enhancing care for older adults and to inform policy on the provision of pain management. Copyright © 2014 American Society for Pain Management Nursing. Published by Elsevier Inc. All rights reserved.

  15. IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites.

    Science.gov (United States)

    Hadjithomas, Michalis; Chen, I-Min Amy; Chu, Ken; Ratner, Anna; Palaniappan, Krishna; Szeto, Ernest; Huang, Jinghua; Reddy, T B K; Cimermančič, Peter; Fischbach, Michael A; Ivanova, Natalia N; Markowitz, Victor M; Kyrpides, Nikos C; Pati, Amrita

    2015-07-14

    In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of "big" genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in Alphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to

  16. High throughput screening for small molecule enhancers of the interferon signaling pathway to drive next-generation antiviral drug discovery.

    Directory of Open Access Journals (Sweden)

    Dhara A Patel

    Full Text Available Most of current strategies for antiviral therapeutics target the virus specifically and directly, but an alternative approach to drug discovery might be to enhance the immune response to a broad range of viruses. Based on clinical observation in humans and successful genetic strategies in experimental models, we reasoned that an improved interferon (IFN signaling system might better protect against viral infection. Here we aimed to identify small molecular weight compounds that might mimic this beneficial effect and improve antiviral defense. Accordingly, we developed a cell-based high-throughput screening (HTS assay to identify small molecules that enhance the IFN signaling pathway components. The assay is based on a phenotypic screen for increased IFN-stimulated response element (ISRE activity in a fully automated and robust format (Z'>0.7. Application of this assay system to a library of 2240 compounds (including 2160 already approved or approvable drugs led to the identification of 64 compounds with significant ISRE activity. From these, we chose the anthracycline antibiotic, idarubicin, for further validation and mechanism based on activity in the sub-µM range. We found that idarubicin action to increase ISRE activity was manifest by other members of this drug class and was independent of cytotoxic or topoisomerase inhibitory effects as well as endogenous IFN signaling or production. We also observed that this compound conferred a consequent increase in IFN-stimulated gene (ISG expression and a significant antiviral effect using a similar dose-range in a cell-culture system inoculated with encephalomyocarditis virus (EMCV. The antiviral effect was also found at compound concentrations below the ones observed for cytotoxicity. Taken together, our results provide proof of concept for using activators of components of the IFN signaling pathway to improve IFN efficacy and antiviral immune defense as well as a validated HTS approach to identify

  17. Enhancing innovation between scientific and indigenous knowledge: pioneer NGOs in India

    Directory of Open Access Journals (Sweden)

    Laplante Julie

    2009-10-01

    Full Text Available Abstract Background Until recently, little attention has been paid to local innovation capacity as well as management practices and institutions developed by communities and other local actors based on their traditional knowledge. This paper doesn't focus on the results of scientific research into innovation systems, but rather on how local communities, in a network of supportive partnerships, draw knowledge for others, combine it with their own knowledge and then innovate in their local practices. Innovation, as discussed in this article, is the capacity of local stakeholders to play an active role in innovative knowledge creation in order to enhance local health practices and further environmental conservation. In this article, the innovative processes through which this capacity is created and reinforced will be defined as a process of "ethnomedicine capacity". Methods The field study undertaken by the first author took place in India, in the State of Tamil Nadu, over a period of four months in 2007. The data was collected through individual interviews and focus groups and was complemented by participant observations. Results The research highlights the innovation capacity related to ethnomedical knowledge. As seen, the integration of local and scientific knowledge is crucial to ensure the practices anchor themselves in daily practices. The networks created are clearly instrumental to enhancing the innovation capacity that allows the creation, dissemination and utilization of 'traditional' knowledge. However, these networks have evolved in very different forms and have become entities that can fit into global networks. The ways in which the social capital is enhanced at the village and network levels are thus important to understand how traditional knowledge can be used as an instrument for development and innovation. Conclusion The case study analyzed highlights examples of innovation systems in a developmental context. They demonstrate that

  18. Technology-Enhanced Discovery

    Science.gov (United States)

    Harrow, Chris; Chin, Lillian

    2014-01-01

    Exploration, innovation, proof: For students, teachers, and others who are curious, keeping an open mind and being ready to investigate unusual or unexpected properties will always lead to learning something new. Technology can further this process, allowing various behaviors to be analyzed that were previously memorized or poorly understood. This…

  19. 4th ASEM Seminar on Knowledge Management to Enhance Nuclear Safety

    International Nuclear Information System (INIS)

    Castello, F.; Reyes, A. de los; Sobari, M. P. Mohd; Istiyanto, J. E.; Faross, P.; Delarosa, A.

    2016-01-01

    Full text: The 4th Asia-Europe Meeting (ASEM) Seminar on Nuclear Safety was convened in Madrid, Spain on 29th–30th October 2015, hosted by the Spanish Nuclear Safety Council. The seminar’s theme was “Knowledge management to enhance nuclear safety”, which aimed to continue discussing on nuclear safety to foster Asia-Europe capacity-building and cooperation in nuclear safety. The seminar was attended by representatives from national governments, nuclear regulators, energy companies, radiation protection and nuclear safety authorities, research institutes and universities. According to such model, proposed by the IAEA, the national capacity building requires an integrated approach based on four pillars: human resources development, education and training, knowledge management and knowledge networking. In this context, Nuclear Knowledge Management (KM) has become a high priority in many countries and international organizations and it has been taken into account to develop and implement specific strategies in ensuring safe and sustainable operation of nuclear facilities. At national level, a sustainable approach should include the necessary Nuclear Knowledge Management actions to ensure that every actor having a significant role in the national nuclear programmes infrastructure acquires, preserves and improves its corporate and individual knowledge. (author

  20. Semantics in support of biodiversity knowledge discovery: an introduction to the biological collections ontology and related ontologies.

    Science.gov (United States)

    Walls, Ramona L; Deck, John; Guralnick, Robert; Baskauf, Steve; Beaman, Reed; Blum, Stanley; Bowers, Shawn; Buttigieg, Pier Luigi; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Morrison, Norman; Ó Tuama, Éamonn; Schildhauer, Mark; Smith, Barry; Stucky, Brian J; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers.

  1. Semantics in Support of Biodiversity Knowledge Discovery: An Introduction to the Biological Collections Ontology and Related Ontologies

    Science.gov (United States)

    Baskauf, Steve; Blum, Stanley; Bowers, Shawn; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Tuama, Éamonn Ó.; Schildhauer, Mark; Smith, Barry; Stucky, Brian J.; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers

  2. Seeking a potential system in managing organizational knowledge flow towards enhancing individual learning and intellectual capital

    Directory of Open Access Journals (Sweden)

    Intan Soraya Rosdi

    2013-12-01

    Full Text Available The knowledge-based economy of today heralds an era where the business environment is characterized by complex and ever-changing conditions, driven by rapid technological advancements. With knowledge regarded as the main competitive resource, continuous learning becomes critical to firms as they try to keep up with the latest technology and business practices. Moreover, knowledge resides within individual employees, and the challenge is to ensure that knowledge is acquired, applied, and shared to benefit the firm. The situation becomes more complex when it is established that there exists different human capital in firms at any one time, differentiated based on the types of knowledge they contribute to the firm. Further, scant literature exists on the relationship dynamics between the different human capital groups and their influences on individual learning. This paper aims to propose a potential system to manage interaction between the different human capital groups within firms, and its link to enhancing different types of individual learning and intellectual capital.

  3. Knowledge translation strategies for enhancing nurses' evidence-informed decision making: a scoping review.

    Science.gov (United States)

    Yost, Jennifer; Thompson, David; Ganann, Rebecca; Aloweni, Fazila; Newman, Kristine; McKibbon, Ann; Dobbins, Maureen; Ciliska, Donna

    2014-06-01

    Nurses are increasingly expected to engage in evidence-informed decision making (EIDM); the use of research evidence with information about patient preferences, clinical context and resources, and their clinical expertise in decision making. Strategies for enhancing EIDM have been synthesized in high-quality systematic reviews, yet most relate to physicians or mixed disciplines. Existing reviews, specific to nursing, have not captured a broad range of strategies for promoting the knowledge and skills for EIDM, patient outcomes as a result of EIDM, or contextual information for why these strategies "work." To conduct a scoping review to identify and map the literature related to strategies implemented among nurses in tertiary care for promoting EIDM knowledge, skills, and behaviours, as well as patient outcomes and contextual implementation details. A search strategy was developed and executed to identify relevant research evidence. Participants included registered nurses, clinical nurse specialists, nurse practitioners, and advanced practice nurses. Strategies were those enhancing nurses' EIDM knowledge, skills, or behaviours, as well as patient outcomes. Relevant studies included systematic reviews, randomized controlled trials, cluster randomized controlled trials, non-randomized trials (including controlled before and after studies), cluster non-randomized trials, interrupted time series designs, prospective cohort studies, mixed-method studies, and qualitative studies. Two reviewers performed study selection and data extraction using standardized forms. Disagreements were resolved through discussion or third party adjudication. Using a narrative synthesis, the body of research was mapped by design, clinical areas, strategies, and provider and patient outcomes to determine areas appropriate for a systematic review. There are a sufficiently high number of studies to conduct a more focused systematic review by care settings, study design, implementation strategies

  4. Response to traumatic brain injury neurorehabilitation through an artificial intelligence and statistics hybrid knowledge discovery from databases methodology.

    Science.gov (United States)

    Gibert, Karina; García-Rudolph, Alejandro; García-Molina, Alberto; Roig-Rovira, Teresa; Bernabeu, Montse; Tormos, José María

    2008-01-01

    Develop a classificatory tool to identify different populations of patients with Traumatic Brain Injury based on the characteristics of deficit and response to treatment. A KDD framework where first, descriptive statistics of every variable was done, data cleaning and selection of relevant variables. Then data was mined using a generalization of Clustering based on rules (CIBR), an hybrid AI and Statistics technique which combines inductive learning (AI) and clustering (Statistics). A prior Knowledge Base (KB) is considered to properly bias the clustering; semantic constraints implied by the KB hold in final clusters, guaranteeing interpretability of the resultis. A generalization (Exogenous Clustering based on rules, ECIBR) is presented, allowing to define the KB in terms of variables which will not be considered in the clustering process itself, to get more flexibility. Several tools as Class panel graph are introduced in the methodology to assist final interpretation. A set of 5 classes was recommended by the system and interpretation permitted profiles labeling. From the medical point of view, composition of classes is well corresponding with different patterns of increasing level of response to rehabilitation treatments. All the patients initially assessable conform a single group. Severe impaired patients are subdivided in four profiles which clearly distinct response patterns. Particularly interesting the partial response profile, where patients could not improve executive functions. Meaningful classes were obtained and, from a semantics point of view, the results were sensibly improved regarding classical clustering, according to our opinion that hybrid AI & Stats techniques are more powerful for KDD than pure ones.

  5. How music training enhances working memory: a cerebrocerebellar blending mechanism that can lead equally to scientific discovery and therapeutic efficacy in neurological disorders.

    Science.gov (United States)

    Vandervert, Larry

    2015-01-01

    Following in the vein of studies that concluded that music training resulted in plastic changes in Einstein's cerebral cortex, controlled research has shown that music training (1) enhances central executive attentional processes in working memory, and (2) has also been shown to be of significant therapeutic value in neurological disorders. Within this framework of music training-induced enhancement of central executive attentional processes, the purpose of this article is to argue that: (1) The foundational basis of the central executive begins in infancy as attentional control during the establishment of working memory, (2) In accordance with Akshoomoff, Courchesne and Townsend's and Leggio and Molinari's cerebellar sequence detection and prediction models, the rigors of volitional control demands of music training can enhance voluntary manipulation of information in thought and movement, (3) The music training-enhanced blending of cerebellar internal models in working memory as can be experienced as intuition in scientific discovery (as Einstein often indicated) or, equally, as moments of therapeutic advancement toward goals in the development of voluntary control in neurological disorders, and (4) The blending of internal models as in (3) thus provides a mechanism by which music training enhances central executive processes in working memory that can lead to scientific discovery and improved therapeutic outcomes in neurological disorders. Within the framework of Leggio and Molinari's cerebellar sequence detection model, it is determined that intuitive steps forward that occur in both scientific discovery and during therapy in those with neurological disorders operate according to the same mechanism of adaptive error-driven blending of cerebellar internal models. It is concluded that the entire framework of the central executive structure of working memory is a product of the cerebrocerebellar system which can, through the learning of internal models

  6. Enhancement of knowledge construction activities utilizing 21st century learning design rubric

    Science.gov (United States)

    Pedoche, Margarette Anne U.; Taladua, Janica Mae M.; Panal, Geicky Pearl C.; Magsayo, Joy R.; Guarin, Rica Mae B.; Myrna, H. Lahoylahoy

    2018-01-01

    The main objective of the study was to enhance knowledge construction activities on its design particularly the objectives, support materials, student activities and assessment tools. Activities from the 2nd Quarter of Science Learners Material were the basis in the adaptation of activities. The adapted activities were evaluated by the In-service Science teachers and undergone modification by the researchers based on the teacher's comments and suggestions. It was then evaluated, revised, and validated, tried-out using the 21st CLD Rubric. Subjects of the study were 110 students from Grade 7-B, Grade 7-D, Grade 7-F in Geronima Cabrera National High School, Kolambugan, Lanao del Norte during the academic year 2016-2017, the study to determine their learning capabilities investigated by the use of Knowledge Construction Activities in the 21st Century Classroom, to investigate how the lessons were understood and appreciated by students, to stimulate interpretation, analysis, synthesizing, or evaluating ideas and develop critical thinking. Both quantitative and qualitative data were obtained from the students' scores in three activities. Results showed that there was a significant difference between the pretest and posttest scores of students. Mean scores between the pretest and posttest showed a mean difference of 3.35, thus the null hypothesis was rejected. It could be concluded with sufficient evidence to show that the students had basically low prior knowledge about the topic ecosystem. A significant difference was seen in the pretest and posttest, scores of the activities and Ecosystem model results after the implementation phase that a knowledge construction type of activity was better than the traditional one for it promoted meaningful learning and active engagement of students. Based on the results, it was clear that the use of knowledge construction activities had an effect on student's achievement in comparison to traditional teaching method. Thus, it was

  7. An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

    Energy Technology Data Exchange (ETDEWEB)

    Khawli, Toufik Al; Eppelt, Urs; Hermanns, Torsten [RWTH Aachen University, Chair for Nonlinear Dynamics, Steinbachstr. 15, 52047 Aachen (Germany); Gebhardt, Sascha [RWTH Aachen University, Virtual Reality Group, IT Center, Seffenter Weg 23, 52074 Aachen (Germany); Kuhlen, Torsten [Forschungszentrum Jülich GmbH, Institute for Advanced Simulation (IAS), Jülich Supercomputing Centre (JSC), Wilhelm-Johnen-Straße, 52425 Jülich (Germany); Schulz, Wolfgang [Fraunhofer, ILT Laser Technology, Steinbachstr. 15, 52047 Aachen (Germany)

    2016-06-08

    In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.

  8. Australian athletes' knowledge of the WADA Prohibited Substances List and performance enhancing substances.

    Science.gov (United States)

    Orr, Rhonda; Grassmayr, Matthew; Macniven, Rona; Grunseit, Anne; Halaki, Mark; Bauman, Adrian

    2018-03-15

    This study investigated athlete knowledge of the World Anti-doping Agency (WADA) Prohibited Substances List and the effects of four well-known performance enhancing substances (PES). A sample of 1925 elite and sub-elite athletes (mean age 20.6 years) completed a questionnaire about the banned status of 30 substances/methods and their knowledge of the effects of amphetamines, anabolic steroids, growth hormone and erythropoietin. Athletes showed limited understanding of the WADA Prohibited Substances List, scoring 32.2% correct, 36.3% incorrect, and 31.4% indicated they did not know the status of 30 substances. Responses of >50% correct were given for only eight substances/method: anabolic steroids, amphetamines, blood doping, erythropoietin, caffeine, vitamins/minerals, protein powders and iron. Athletes demonstrated moderate knowledge of the desired effects of the four PES (49% correct), but poor knowledge of their adverse effects (29% correct). Age, sex, ethnicity, professional/amateur status, and current competition level were significant predictors of the number of correct responses (r 2  = 0.16, p wide range of substances and PES. Better targeted drug education towards younger and non-professional athletes and evaluation of current anti-doping programs are warranted. Copyright © 2018 Elsevier B.V. All rights reserved.

  9. One Usage of Geogebra in Enhancing Pre-service Mathematics Teachers’ Content Knowledge

    Directory of Open Access Journals (Sweden)

    Karmelita Pjanic

    2015-04-01

    Full Text Available A wide range of mathematical ideas could be used to develop and justify a formula for calculating the area of trapezoid. Those ideas lead to different strategies for finding out area of trapezoid that we classify in three groups: decomposing, enclosing and transforming strategies. Those strategies should be part of mathematics content knowledge for teaching. In this study we trace a change in structure of mathematics content knowledge of nine pre-service mathematics teachers as a result of using GeoGebra applets that visualize different approaches in finding out the area of trapezoid. We argue that engaging pre-service mathematics teachers to develop and justify formula for calculating the area of trapezoid using GeoGebra applets is a worth task that enhances pre-service mathematics teachers’ content knowledge for teaching. Our experiment confirmed that the use of Geogebra encourage pre-service mathematics teachers to uncover new ideas that lead them towards clearer justifications and easier way of proving formula for area of trapezoid. Keywords: Area of trapezoid, GeoGebra, content knowledge for teaching

  10. Enhancing the metalinguistic abilities of pre-service teachers via coursework targeting language structure knowledge.

    Science.gov (United States)

    Purvis, Caralyn J; McNeill, Brigid C; Everatt, John

    2016-04-01

    Low metalinguistic knowledge of pre-service and in-service teachers is likely to restrict the provision of evidence-based literacy instruction in the classroom. Despite such concerns, relatively few studies have examined the effects of teacher preparation coursework in building pre-service teachers' language structure knowledge. This study examined the effects of 7 h of language structure coursework, delivered over 7 weeks, on 121 New Zealand pre-service teachers in their initial year of study. Changes in participants' phonological awareness, morphological awareness, and orthographic knowledge were tracked across the teaching period. The impact of the coursework for participants who presented with strong spelling (n = 24) and poor spelling (n = 24) ability was also compared. The cohort demonstrated significant gains across all measures. Strong spellers responded more favourably to the teaching than poor spellers, even when accounting for initial levels of meta-linguistic knowledge. Implications for the development of teacher preparation programmes that enhance the provision of effective literacy instruction are discussed.

  11. Discovery Mondays

    CERN Multimedia

    2003-01-01

    Many people don't realise quite how much is going on at CERN. Would you like to gain first-hand knowledge of CERN's scientific and technological activities and their many applications? Try out some experiments for yourself, or pick the brains of the people in charge? If so, then the «Lundis Découverte» or Discovery Mondays, will be right up your street. Starting on May 5th, on every first Monday of the month you will be introduced to a different facet of the Laboratory. CERN staff, non-scientists, and members of the general public, everyone is welcome. So tell your friends and neighbours and make sure you don't miss this opportunity to satisfy your curiosity and enjoy yourself at the same time. You won't have to listen to a lecture, as the idea is to have open exchange with the expert in question and for each subject to be illustrated with experiments and demonstrations. There's no need to book, as Microcosm, CERN's interactive museum, will be open non-stop from 7.30 p.m. to 9 p.m. On the first Discovery M...

  12. Knowledges

    DEFF Research Database (Denmark)

    Berling, Trine Villumsen

    2012-01-01

    Scientific knowledge in international relations has generally focused on an epistemological distinction between rationalism and reflectivism over the last 25 years. This chapter argues that this distinction has created a double distinction between theory/reality and theory/practice, which works...... and reflectivism. Bourdieu, on the contrary, lets the challenge to the theory/reality distinction spill over into a challenge to the theory/practice distinction by thrusting the scientist in the foreground as not just a factor (discourse/genre) but as an actor. In this way, studies of IR need to include a focus...... as a ghost distinction structuring IR research. While reflectivist studies have emphasised the impossibility of detached, objective knowledge production through a dissolution of the theory/reality distinction, the theory/practice distinction has been left largely untouched by both rationalism...

  13. Non-linear learning in online tutorial to enhance students’ knowledge on normal distribution application topic

    Science.gov (United States)

    Kartono; Suryadi, D.; Herman, T.

    2018-01-01

    This study aimed to analyze the enhancement of non-linear learning (NLL) in the online tutorial (OT) content to students’ knowledge of normal distribution application (KONDA). KONDA is a competence expected to be achieved after students studied the topic of normal distribution application in the course named Education Statistics. The analysis was performed by quasi-experiment study design. The subject of the study was divided into an experimental class that was given OT content in NLL model and a control class which was given OT content in conventional learning (CL) model. Data used in this study were the results of online objective tests to measure students’ statistical prior knowledge (SPK) and students’ pre- and post-test of KONDA. The statistical analysis test of a gain score of KONDA of students who had low and moderate SPK’s scores showed students’ KONDA who learn OT content with NLL model was better than students’ KONDA who learn OT content with CL model. Meanwhile, for students who had high SPK’s scores, the gain score of students who learn OT content with NLL model had relatively similar with the gain score of students who learn OT content with CL model. Based on those findings it could be concluded that the NLL model applied to OT content could enhance KONDA of students in low and moderate SPK’s levels. Extra and more challenging didactical situation was needed for students in high SPK’s level to achieve the significant gain score.

  14. A didactic and hands-on module enhances resident microsurgical knowledge and technical skill.

    Science.gov (United States)

    El Ahmadieh, Tarek Y; Aoun, Salah G; El Tecle, Najib E; Nanney, Allan D; Daou, Marc R; Harrop, James; Batjer, Hunt H; Bendok, Bernard R

    2013-10-01

    Simulation has been adopted as a powerful training tool in many areas of health care. However, it has not yet been systematically embraced in neurosurgery because of the absence of validated tools, assessment scales, and curricula. To use our validated microanastomosis module and scale to evaluate the effects of an educational intervention on the performance of neurosurgery residents at the 2012 Congress of Neurological Surgeons Annual Meeting. The module consisted of an end-to-end microanastomosis of a 3-mm vessel and was divided into 3 phases: (1) a cognitive and microsuture prelecture testing phase, (2) a didactic lecture, and (3) a cognitive and microsuture postlecture testing phase. We compared resident knowledge and technical proficiency from the pretesting and posttesting phases. One neurosurgeon and 7 neurosurgery residents participated in the study. None had previous experience in microsurgery. The average score on the microsuture prelecture and postlecture tests, as measured by our assessment scale, was 32.50 and 39.75, respectively (P = .001). The number of completed sutures at the end of each procedure was higher for 75% of participants in the postlecture testing phase (P = .03). The average score on the cognitive postlecture test (12.75) was significantly better than that of the cognitive prelecture test (8.38; P = .001). Simulation has the potential to enhance resident education and to elevate proficiency levels. Our data suggest that a focused microsurgical module that incorporates a didactic component and a technical component can enhance resident knowledge and technical proficiency in microsurgical anastomosis.

  15. Enhancing Content Knowledge in Essay Writing Classes: A Multimedia Package for Iranian EFL Learners

    Directory of Open Access Journals (Sweden)

    Marziyeh Tahmouresi Majelan

    2014-04-01

    Full Text Available The main objective of this study was to investigate empirically if promoting a multimedia package enhances content knowledge in essay writing of 80 junior English translation students at a University in Karaj, Iran; plus, whether the learners’ writing content improve due to the presence of the multimedia package or not. The multimedia was considered to be a CD, containing recordings both in first language (L1=Farsi and in second language (L2=English along with manipulative and task-based activities. A homogenizing test, the pre-posttests, and the material in a form of a CD (treatment including forty of the most common TOEFL essays both in L1 and L2 plus manipulative tasks to fulfill provided by the researcher, were the instruments in the study.  After 14 weeks, both the experimental and control groups sat for the posttest with exactly the same characteristics of pretest except for the topics. When the collected data was analyzed, a mean difference of t-test along with a paired t-test showed a significant difference between the performance of the control and the experimental groups, regarding the content. Consequently, the statistics proved that enhancing content knowledge by means of a multimedia package containing recordings plus manipulative and task-based activities would improve students’ writing ability while the control group in which a current traditional rhetoric approach was used, the placebo, did not show any statistically significant improvement regarding content.

  16. A Revenue Analysis on Taiwan’s Publishing Industries from the Prospective of Knowledge Discovery Using Government’s Financial Database

    Directory of Open Access Journals (Sweden)

    Ming-Ju Hsu

    2017-07-01

    Full Text Available This research focused on retrieving and analyzing data and information from the “Financial Database” established by the Ministry of Finance of Republic of China (Taiwan, carrying out a Knowledge Discovery from the Financial Database (KDFD 2013~2015, primarily on Taiwan’s Nine(9-subclass Publishing Industries. The results of the research showed that: a. the sales revenues of Taiwan’s Publishing Industries have declined year after year from 2013 to 2015; b. within the year there was a wave of steep drop in sales from May to June, then the sales revenues gradually recovered and reached the peak in November to December and c. Newspapers, magazines and books publishing were still the dominate part of the sales for the Publishing Industries (82.1%. While the Digital Publishing Industries accounted for an average of 16% of total sales revenues from 2013 to 2015, the growth spurs from 11% in 2013 to 16% in 2014, then to 20% in 2015 were quite impressive, indicating a potential growth for Digital Publishing Industries. The definition of the publishing industries categorized by the government of Taiwan included nine subclasses in the whole division, further study could be conducted for each subclass of the publishing division to obtain its actual sales revenues for a more realistic comparison with surveyed data.

  17. Telehealth Applications to Enhance CKD Knowledge and Awareness Among Patients and Providers.

    Science.gov (United States)

    Tuot, Delphine S; Boulware, L Ebony

    2017-01-01

    CKD affects 13% of the US adult population, causes excess mortality, and is associated with significant sociodemographic disparities. Optimal CKD management slows progression of disease and reduces cardiovascular-related outcomes. Resources for patients and primary care providers, major stakeholders in preventive CKD care, are critically needed to enhance understanding of the disease and to optimize CKD health, particularly because of the asymptomatic nature of kidney disease. Telehealth is defined as the use of electronic communication and telecommunications technology to support long-distance clinical health care, patient and professional health-related education, and public health and health administration. It provides new opportunities to enhance awareness and understanding among these important stakeholders. This review will examine the role of telehealth within existing educational theories, identify telehealth applications that can enhance CKD knowledge and behavior change among patients and primary care providers, and examine the advantages and disadvantages of telehealth vs usual modalities for education. Copyright © 2016 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

  18. Enhancing Pediatric Trainees' and Students' Knowledge in Providing Care to Transgender Youth.

    Science.gov (United States)

    Vance, Stanley R; Deutsch, Madeline B; Rosenthal, Stephen M; Buckelew, Sara M

    2017-04-01

    To enhance pediatric trainees' and students' knowledge of the psychosocial and medical issues facing transgender youth through a comprehensive curriculum. During the 2015-2016 academic year, we administered a transgender youth curriculum to fourth-year medical students, pediatric interns, psychiatry interns, and nurse practitioner students on their 1-month adolescent and young adult medicine rotation. The curriculum included six interactive, online modules and an observational experience in a multidisciplinary pediatric gender clinic. The online modules had a primary care focus with topics of general transgender terminology, taking a gender history, taking a psychosocial history, performing a sensitive physical examination, and formulating an assessment, psychosocial plan, and medical plan. At the completion of the curriculum, learners completed an evaluation that assessed change in perceived awareness and knowledge of transgender-related issues and learner satisfaction with the curriculum. Twenty learners participated in the curriculum with 100% completing the curriculum evaluations, 100% reporting completing all six online modules, and 90% attending the gender clinic. Learners demonstrated a statistically significant improvement in all pre-post knowledge/awareness measures. On a Likert scale where 5 indicated very satisfied, learners' mean rating of the quality of the curriculum was 4.5 ± .7; quality of the modules was 4.4 ± .7; and satisfaction with the observational experience was 4.5 ± .8. A comprehensive curriculum comprised interactive online modules and an observational experience in a pediatric gender clinic was effective at improving pediatric learners' perceived knowledge of the medical and psychosocial issues facing transgender youth. Learners also highly valued the curriculum. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  19. Visual Input Enhancement via Essay Coding Results in Deaf Learners' Long-Term Retention of Improved English Grammatical Knowledge

    Science.gov (United States)

    Berent, Gerald P.; Kelly, Ronald R.; Schmitz, Kathryn L.; Kenney, Patricia

    2009-01-01

    This study explored the efficacy of visual input enhancement, specifically "essay enhancement", for facilitating deaf college students' improvement in English grammatical knowledge. Results documented students' significant improvement immediately after a 10-week instructional intervention, a replication of recent research. Additionally, the…

  20. Using collaborative technology to enhance pre-service teachers' pedagogical content knowledge in Science

    Science.gov (United States)

    Donnelly, Dermot Francis; Hume, Anne

    2015-01-01

    Background:Supporting pre-service teacher (PT) collaboration as a means of professional learning is a challenging but essential task for effective practice. However, teacher placements or practicums in schools, which is common practice within teacher education programmes, can often isolate PTs from sharing their experiences with each other. Further, the articulation of effective pedagogical practices by high-quality teachers is limited, restricting PTs' ability to access such professional knowledge. Purpose:This study investigates how the introduction of a collaborative technology, a wiki, may enhance existing and new opportunities for pre-service teachers' (PTs) to develop pedagogical content knowledge (PCK). Sample:Seven PT chemistry teachers of varied backgrounds participated in this study. Design and method:The PTs were learning to collaboratively formulate and document their early topic-specific teaching knowledge using a pedagogical tool known as Content Representation (CoRe) design. Once scaffolded into this process, the PTs continued and extended this collaborative work online through the introduction of a wiki. Data were collected for qualitative analysis through the CoRe artefacts, a semi-structured focus group interview, and PTs' reflective essays about their collaborative experiences representing their teaching knowledge in CoRes through the wiki. Results:Data analysis highlighted that while wiki use showed some potential for collaborative representation when participants were not face-to-face, the PTs were hesitant in critiquing each other's work. As such, the online representations remained relatively static without face-to-face interaction. However, developing artefacts online was favoured over established practice and the access to artefacts of their peers on the wiki enhanced PTs' consideration for their own PCK. Conclusion:Wikis show some potential in the hosting of CoRes, but issues in simultaneous posting and lack of chat functionality may

  1. Knowledge-enhanced network simulation modeling of the nuclear power plant operator

    International Nuclear Information System (INIS)

    Schryver, J.C.; Palko, L.E.

    1988-01-01

    Simulation models of the human operator of advanced control systems must provide an adequate account of the cognitive processes required to control these systems. The Integrated Reactor Operator/System (INTEROPS) prototype model was developed at Oak Ridge National Laboratory (ORNL) to demonstrate the feasibility of dynamically integrating a cognitive operator model and a continuous plant process model (ARIES-P) to provide predictions of the total response of a nuclear power plant during upset/emergency conditions. The model consists of a SAINT network of cognitive tasks enhanced with expertise provided by a knowledge-based fault diagnosis model. The INTEROPS prototype has been implemented in both closed and open loop modes. The prototype model is shown to be cognitively relevant by accounting for cognitive tunneling, confirmation bias, evidence chunking, intentional error, and forgetting

  2. Professional Development Strategies to Enhance Nurses' Knowledge and Maintain Safe Practice.

    Science.gov (United States)

    Bindon, Susan L

    2017-08-01

    Maintaining competence is a professional responsibility for nurses. Individual nurses are accountable for their practice, as outlined in the American Nurses Association's Nursing: Scope and Standards of Practice. Nurses across clinical settings face the sometimes daunting challenge of staying abreast of regulatory mandates, practice changes, equipment updates, and other workplace expectations. In the complex, evolving perioperative setting, professional development is a priority, and the need for ongoing education is critical. However, nurses' efforts to engage in their own development can be hampered by a lack of time, limited access to educational resources, or cost concerns. This article provides an overview of nursing professional development and offers some resources to help individual nurses maintain or enhance their knowledge, skills, and attitudes. Copyright © 2017 AORN, Inc. Published by Elsevier Inc. All rights reserved.

  3. Knowledge and tools to enhance resilience of beef grazing systems for sustainable animal protein production.

    Science.gov (United States)

    Steiner, Jean L; Engle, David M; Xiao, Xiangming; Saleh, Ali; Tomlinson, Peter; Rice, Charles W; Cole, N Andy; Coleman, Samuel W; Osei, Edward; Basara, Jeffrey; Middendorf, Gerad; Gowda, Prasanna; Todd, Richard; Moffet, Corey; Anandhi, Aavudai; Starks, Patrick J; Ocshner, Tyson; Reuter, Ryan; Devlin, Daniel

    2014-11-01

    Ruminant livestock provides meat and dairy products that sustain health and livelihood for much of the world's population. Grazing lands that support ruminant livestock provide numerous ecosystem services, including provision of food, water, and genetic resources; climate and water regulation; support of soil formation; nutrient cycling; and cultural services. In the U.S. southern Great Plains, beef production on pastures, rangelands, and hay is a major economic activity. The region's climate is characterized by extremes of heat and cold and extremes of drought and flooding. Grazing lands occupy a large portion of the region's land, significantly affecting carbon, nitrogen, and water budgets. To understand vulnerabilities and enhance resilience of beef production, a multi-institutional Coordinated Agricultural Project (CAP), the "grazing CAP," was established. Integrative research and extension spanning biophysical, socioeconomic, and agricultural disciplines address management effects on productivity and environmental footprints of production systems. Knowledge and tools being developed will allow farmers and ranchers to evaluate risks and increase resilience to dynamic conditions. The knowledge and tools developed will also have relevance to grazing lands in semiarid and subhumid regions of the world. © 2014 New York Academy of Sciences.

  4. Volatility Discovery

    DEFF Research Database (Denmark)

    Dias, Gustavo Fruet; Scherrer, Cristina; Papailias, Fotis

    The price discovery literature investigates how homogenous securities traded on different markets incorporate information into prices. We take this literature one step further and investigate how these markets contribute to stochastic volatility (volatility discovery). We formally show...... that the realized measures from homogenous securities share a fractional stochastic trend, which is a combination of the price and volatility discovery measures. Furthermore, we show that volatility discovery is associated with the way that market participants process information arrival (market sensitivity......). Finally, we compute volatility discovery for 30 actively traded stocks in the U.S. and report that Nyse and Arca dominate Nasdaq....

  5. Technology Focus: Enhancing Conceptual Knowledge of Linear Programming with a Flash Tool

    Science.gov (United States)

    Garofalo, Joe; Cory, Beth

    2007-01-01

    Mathematical knowledge can be categorized in different ways. One commonly used way is to distinguish between procedural mathematical knowledge and conceptual mathematical knowledge. Procedural knowledge of mathematics refers to formal language, symbols, algorithms, and rules. Conceptual knowledge is essential for meaningful understanding of…

  6. Enhancing the Value of Sensor-based Observations by Capturing the Knowledge of How An Observation Came to Be

    Science.gov (United States)

    Fredericks, J.; Rueda-Velasquez, C. A.

    2016-12-01

    As we move from keeping data on our disks to sharing it with the world, often in real-time, we are obligated to also tell an unknown user about how our observations were made. Data that are shared must not only have ownership metadata, unit descriptions and content formatting information. The provider must also share information that is needed to assess the data as it relates to potential re-use. A user must be able to assess the limitations and capabilities of the sensor, as it is configured, to understand its value. For example, when an instrument is configured, it typically affects the data accuracy and operational limits of the sensor. An operator may sacrifice data accuracy to achieve a broader operational range and visa versa. If you are looking at newly discovered data, it is important to be able to find all of the information that relates to assessing the data quality for your particular application. Traditionally, metadata are captured by data managers who usually do not know how the data are collected. By the time data are distributed, this knowledge is often gone, buried within notebooks or hidden in documents that are not machine-harvestable and often not human-readable. In a recently funded NSF EarthCube Integrative Activity called X-DOMES (Cross-Domain Observational Metadata in EnviroSensing), mechanisms are underway to enable the capture of sensor and deployment metadata by sensor manufacturers and field operators. The support has enabled the development of a community ontology repository (COR) within the Earth Science Information Partnership (ESIP) community, fostering easy creation of resolvable terms for the broader community. This tool enables non-experts to easily develop W3C standards-based content, promoting the implementation of Semantic Web technologies for enhanced discovery of content and interoperability in workflows. The X-DOMES project is also developing a SensorML Viewer/Editor to provide an easy interface for sensor manufacturers and

  7. Prostate segmentation by feature enhancement using domain knowledge and adaptive region based operations

    International Nuclear Information System (INIS)

    Nanayakkara, Nuwan D; Samarabandu, Jagath; Fenster, Aaron

    2006-01-01

    Estimation of prostate location and volume is essential in determining a dose plan for ultrasound-guided brachytherapy, a common prostate cancer treatment. However, manual segmentation is difficult, time consuming and prone to variability. In this paper, we present a semi-automatic discrete dynamic contour (DDC) model based image segmentation algorithm, which effectively combines a multi-resolution model refinement procedure together with the domain knowledge of the image class. The segmentation begins on a low-resolution image by defining a closed DDC model by the user. This contour model is then deformed progressively towards higher resolution images. We use a combination of a domain knowledge based fuzzy inference system (FIS) and a set of adaptive region based operators to enhance the edges of interest and to govern the model refinement using a DDC model. The automatic vertex relocation process, embedded into the algorithm, relocates deviated contour points back onto the actual prostate boundary, eliminating the need of user interaction after initialization. The accuracy of the prostate boundary produced by the proposed algorithm was evaluated by comparing it with a manually outlined contour by an expert observer. We used this algorithm to segment the prostate boundary in 114 2D transrectal ultrasound (TRUS) images of six patients scheduled for brachytherapy. The mean distance between the contours produced by the proposed algorithm and the manual outlines was 2.70 ± 0.51 pixels (0.54 ± 0.10 mm). We also showed that the algorithm is insensitive to variations of the initial model and parameter values, thus increasing the accuracy and reproducibility of the resulting boundaries in the presence of noise and artefacts

  8. The Integrated Knowledge Space - the Foundation for Enhancing the Effectiveness of the University’s Innovative Activity

    Directory of Open Access Journals (Sweden)

    Yury TELNOV

    2009-01-01

    Full Text Available The paper examines the implementation of Integrated Knowledge Space as an effective method for knowledge management in a global university network which will integrate all interested parties of the educational space: the faculty, scholars and business people within the framework of distributed departments on the basis of Information Centre of Disciplines (ICD. ICD enables higher education institutions to accumulate and make on-line renewal of knowledge for teaching and learning processes and for enhancing innovation potential. ICD facilitates the development of human and relational capital of integrated and interconnected educational, research and business communities.

  9. Beyond Discovery

    DEFF Research Database (Denmark)

    Korsgaard, Steffen; Sassmannshausen, Sean Patrick

    2017-01-01

    In this chapter we explore four alternatives to the dominant discovery view of entrepreneurship; the development view, the construction view, the evolutionary view, and the Neo-Austrian view. We outline the main critique points of the discovery presented in these four alternatives, as well...

  10. Chemical Discovery

    Science.gov (United States)

    Brown, Herbert C.

    1974-01-01

    The role of discovery in the advance of the science of chemistry and the factors that are currently operating to handicap that function are considered. Examples are drawn from the author's work with boranes. The thesis that exploratory research and discovery should be encouraged is stressed. (DT)

  11. The Effect of Vocabulary Self-Selection Strategy and Input Enhancement Strategy on the Vocabulary Knowledge of Iranian EFL Learners

    Science.gov (United States)

    Masoudi, Golfam

    2017-01-01

    The present study was designed to investigate empirically the effect of Vocabulary Self-Selection strategy and Input Enhancement strategy on the vocabulary knowledge of Iranian EFL Learners. After taking a diagnostic pretest, both experimental groups enrolled in two classes. Learners who practiced Vocabulary Self-Selection were allowed to…

  12. A Case for Enhancing Environmental Education Programs in Schools: Reflecting on Primary School Students' Knowledge and Attitudes

    Science.gov (United States)

    Treagust, David F.; Amarant, Arlene; Chandrasegaran, A. L.; Won, Mihye

    2016-01-01

    Environmental education in schools is of increasing importance as the world population increases with the subsequent demand on resources and the potential for increased pollution. In an effort to enhance the standing of environmental education in the school curriculum, this study was designed to determine primary students' knowledge about the…

  13. Pacific Research Platform - Creation of a West Coast Big Data Freeway System Applied to the CONNected objECT (CONNECT) Data Mining Framework for Earth Science Knowledge Discovery

    Science.gov (United States)

    Sellars, S. L.; Nguyen, P.; Tatar, J.; Graham, J.; Kawsenuk, B.; DeFanti, T.; Smarr, L.; Sorooshian, S.; Ralph, M.

    2017-12-01

    A new era in computational earth sciences is within our grasps with the availability of ever-increasing earth observational data, enhanced computational capabilities, and innovative computation approaches that allow for the assimilation, analysis and ability to model the complex earth science phenomena. The Pacific Research Platform (PRP), CENIC and associated technologies such as the Flash I/O Network Appliance (FIONA) provide scientists a unique capability for advancing towards this new era. This presentation reports on the development of multi-institutional rapid data access capabilities and data pipeline for applying a novel image characterization and segmentation approach, CONNected objECT (CONNECT) algorithm to study Atmospheric River (AR) events impacting the Western United States. ARs are often associated with torrential rains, swollen rivers, flash flooding, and mudslides. CONNECT is computationally intensive, reliant on very large data transfers, storage and data mining techniques. The ability to apply the method to multiple variables and datasets located at different University of California campuses has previously been challenged by inadequate network bandwidth and computational constraints. The presentation will highlight how the inter-campus CONNECT data mining framework improved from our prior download speeds of 10MB/s to 500MB/s using the PRP and the FIONAs. We present a worked example using the NASA MERRA data to describe how the PRP and FIONA have provided researchers with the capability for advancing knowledge about ARs. Finally, we will discuss future efforts to expand the scope to additional variables in earth sciences.

  14. Discovery of TUG-770

    DEFF Research Database (Denmark)

    Christiansen, Elisabeth; Hansen, Steffen V F; Urban, Christian

    2013-01-01

    Free fatty acid receptor 1 (FFA1 or GPR40) enhances glucose-stimulated insulin secretion from pancreatic β-cells and currently attracts high interest as a new target for the treatment of type 2 diabetes. We here report the discovery of a highly potent FFA1 agonist with favorable physicochemical...

  15. Discovery of Enhanced Magnetoelectric Coupling through Electric Field Control of Two-Magnon Scattering within Distorted Nanostructures.

    Science.gov (United States)

    Xue, Xu; Zhou, Ziyao; Dong, Guohua; Feng, Mengmeng; Zhang, Yijun; Zhao, Shishun; Hu, Zhongqiang; Ren, Wei; Ye, Zuo-Guang; Liu, Yaohua; Liu, Ming

    2017-09-26

    Electric field control of dynamic spin interactions is promising to break through the limitation of the magnetostatic interaction based magnetoelectric (ME) effect. In this work, electric field control of the two-magnon scattering (TMS) effect excited by in-plane lattice rotation has been demonstrated in a La 0.7 Sr 0.3 MnO 3 (LSMO)/Pb(Mn 2/3 Nb 1/3 )-PbTiO 3 (PMN-PT) (011) multiferroic heterostructure. Compared with the conventional strain-mediated ME effect, a giant enhancement of ME effect up to 950% at the TMS critical angle is precisely determined by angular resolution of the ferromagnetic resonance (FMR) measurement. Particularly, a large electric field modulation of magnetic anisotropy (464 Oe) and FMR line width (401 Oe) is achieved at 173 K. The electric-field-controllable TMS effect and its correlated ME effect have been explained by electric field modulation of the planar spin interactions triggered by spin-lattice coupling. The enhancement of the ME effect at various temperatures and spin dynamics control are promising paradigms for next-generation voltage-tunable spintronic devices.

  16. Higgs Discovery

    DEFF Research Database (Denmark)

    Sannino, Francesco

    2013-01-01

    has been challenged by the discovery of a not-so-heavy Higgs-like state. I will therefore review the recent discovery \\cite{Foadi:2012bb} that the standard model top-induced radiative corrections naturally reduce the intrinsic non-perturbative mass of the composite Higgs state towards the desired...... via first principle lattice simulations with encouraging results. The new findings show that the recent naive claims made about new strong dynamics at the electroweak scale being disfavoured by the discovery of a not-so-heavy composite Higgs are unwarranted. I will then introduce the more speculative......I discuss the impact of the discovery of a Higgs-like state on composite dynamics starting by critically examining the reasons in favour of either an elementary or composite nature of this state. Accepting the standard model interpretation I re-address the standard model vacuum stability within...

  17. Toward rapid analysis, forecast and discovery of bioactive compounds from herbs by jointly using thin layer chromatography and ratiometric surface-enhanced Raman spectroscopy technique.

    Science.gov (United States)

    Gu, Xiaoling; Jin, Yang; Dong, Fang; Cai, Yueqing; You, Zhengyi; You, Junhui; Zhang, Liying; Du, Shuhu

    2018-05-10

    Conventional isolation and identification of active compounds from herbs have been extensively reported by using various chromatographic and spectroscopic techniques. However, how to quickly discover new bioactive ingredients from natural sources still remains a challenging task due to the interference of their similar structures or matrices. Here, we present a grand approach for rapid analysis, forecast and discovery of bioactive compounds from herbs based on a hyphenated strategy of thin layer chromatography and ratiometric surface-enhanced Raman spectroscopy. The performance of the hyphenated strategy is first evaluated by analyzing four protoberberine alkaloids, berberine (BER), coptisine (COP), palmatine (PAT) and jatrorrhizine (JAT), from a typical herb Coptidis Rhizoma as an example. It has been demonstrated that this coupling method can identify the four compounds by characteristic peaks at 728, 708, 736 and 732 cm -1 , and especially discriminate BER and COP (with similar migration distances) by ratiometric Raman intensity (I 708 /I 728 ). The corresponding limits of detection are 0.1, 0.05, 0.1 and 0.5 μM, respectively, which are about 1-2 orders of magnitude lower than those of direct observation method under 254 nm UV lamp. Based on these findings, the proposed method further guides forecast and discovery of unknown compounds from traditional Chinese herb Typhonii Rhizoma. Results infer that two trace alkaloids (BER and COP) from the n-butanol extract of Typhonii Rhizoma are found for the first time. Moreover, in vitro experiments manifest that BER can effectively decrease the viability of human glioma U87 cells by inducing cell cycle arrest in a concentration-dependent manner. Copyright © 2018 Elsevier B.V. All rights reserved.

  18. Perceived outcomes of web-based modules designed to enhance athletic trainers' knowledge of evidence-based practice.

    Science.gov (United States)

    Welch, Cailee E; Van Lunen, Bonnie L; Hankemeier, Dorice A; Wyant, Aimee L; Mutchler, Jessica M; Pitney, William A; Hays, Danica G

    2014-01-01

    The release of evidence-based practice (EBP) Web-based learning modules to the membership of the National Athletic Trainers' Association has provided athletic trainers (ATs) the opportunity to enhance their knowledge of the various EBP concepts. Whereas increasing the knowledge of EBP among ATs is important, assessing whether this newfound knowledge is being translated into clinical practice and didactic education is crucial. To explore the effectiveness of an educational intervention regarding EBP on the didactic instruction patterns of athletic training educators and the clinical practice behaviors of clinicians. Qualitative study. Individual telephone interviews. A total of 25 ATs (12 educators, 13 clinicians; experience as an AT = 16.00 ± 9.41 years) were interviewed. We conducted 1 individual telephone interview with each participant. After transcription, the data were analyzed and coded into common themes and categories. Triangulation of the data occurred via the use of multiple researchers and member checking to confirm the accuracy of the data. Participants perceived the EBP Web-based modules to produce numerous outcomes regarding education and clinical practice. These outcomes included perceived knowledge gain among participants, an increase in the importance and scope of EBP, a positive effect on educators' didactic instruction patterns and on instilling value and practice of EBP among students, and an enhanced ability among clinicians to implement EBP within clinical practice. However, some clinicians reported the Web-based modules had no current effect on clinical practice. Although the EBP Web-based modules were successful at enhancing knowledge among ATs, translation of knowledge into the classroom and clinical practice remains limited. Researchers should aim to identify effective strategies to help ATs implement EBP concepts into didactic education and clinical practice.

  19. Facilitating Cohort Discovery by Enhancing Ontology Exploration, Query Management and Query Sharing for Large Clinical Data Repositories

    Science.gov (United States)

    Tao, Shiqiang; Cui, Licong; Wu, Xi; Zhang, Guo-Qiang

    2017-01-01

    To help researchers better access clinical data, we developed a prototype query engine called DataSphere for exploring large-scale integrated clinical data repositories. DataSphere expedites data importing using a NoSQL data management system and dynamically renders its user interface for concept-based querying tasks. DataSphere provides an interactive query-building interface together with query translation and optimization strategies, which enable users to build and execute queries effectively and efficiently. We successfully loaded a dataset of one million patients for University of Kentucky (UK) Healthcare into DataSphere with more than 300 million clinical data records. We evaluated DataSphere by comparing it with an instance of i2b2 deployed at UK Healthcare, demonstrating that DataSphere provides enhanced user experience for both query building and execution. PMID:29854239

  20. Facilitating Cohort Discovery by Enhancing Ontology Exploration, Query Management and Query Sharing for Large Clinical Data Repositories.

    Science.gov (United States)

    Tao, Shiqiang; Cui, Licong; Wu, Xi; Zhang, Guo-Qiang

    2017-01-01

    To help researchers better access clinical data, we developed a prototype query engine called DataSphere for exploring large-scale integrated clinical data repositories. DataSphere expedites data importing using a NoSQL data management system and dynamically renders its user interface for concept-based querying tasks. DataSphere provides an interactive query-building interface together with query translation and optimization strategies, which enable users to build and execute queries effectively and efficiently. We successfully loaded a dataset of one million patients for University of Kentucky (UK) Healthcare into DataSphere with more than 300 million clinical data records. We evaluated DataSphere by comparing it with an instance of i2b2 deployed at UK Healthcare, demonstrating that DataSphere provides enhanced user experience for both query building and execution.

  1. Effectiveness of an intergenerational approach for enhancing knowledge and improving attitudes toward the environment

    Science.gov (United States)

    Liu, Shih-Tsen

    One area in which many environmental education programs are deficient is in reaching and involving the adult population. For senior adults in particular, the disconnect from environmental centers and other settings represents a missed opportunity for strengthening relationships, utilizing community resources and promoting civic engagement. In this sense, "intergenerational programming" could serve as an effective strategy for broadening the public's awareness and participation in environmental activities. Although the concept of involving older adults and young people in joint environmental education experiences is compelling on several fronts, there is no body of evidence to draw upon; nor is there a blueprint to guide efforts to translate this general goal into practice. This research was therefore designed to: (1) assess the effectiveness of an intergeneration outdoor education program in enhancing participants' environmental knowledge and positive attitudes, (2) explore other program impacts on the participants and the environmental centers, and (3) learn about environmental educators' experiences and opinions in regard to utilizing senior adults in their programs. This study was conducted in two phases in order to address the research purposes: (1) a nonequivalent-control-group quasi-experimental research incorporated with the Outdoor School program at the Shaver's Creek Environmental Center, and (2) a statewide mail-in survey with environmental educators in Pennsylvania. According to the quantitative data, both intergenerational groups obtained higher mean scores for environmental attitudes than the monogenerational groups, although the difference in scores was not statistically significant than one of the two monogenerational groups. The qualitative data showed that senior adults have certain characteristics that allowed them to make a substantial contribution toward enriching children's awareness and appreciation of the natural environment. Although the

  2. United States Program for Technical assistance to IAEA Standards. Concept Paper: Knowledge Acquisition, Skills training for enhanced IAEA safeguards inspections

    Energy Technology Data Exchange (ETDEWEB)

    Morris, F.A.; Toquam, J.L.

    1993-11-01

    This concept paper explores the potential contribution of ``Knowledge Acquisition Skills`` in enhancing the effectiveness of international safeguards inspections by the International Atomic energy Agency (IAEA, or Agency) and identifies types of training that could be provided to develop or improve such skills. For purposes of this concept paper, Knowledge Acquisition Skills are defined broadly to include all appropriate techniques that IAEA safeguards inspectors can use to acquire and analyze information relevant to the performance of successful safeguards inspections. These techniques include a range of cognitive, analytic, judgmental, interpersonal, and communications skills that have the potential to help IAEA safeguards inspectors function more effectively.

  3. Making sense of knowledge productivity: beta testing the KP-enhancer

    NARCIS (Netherlands)

    Christiaan Stam

    2007-01-01

    Purpose – purpose of this article is to report about the progress of the development of a method that makes sense of knowledge productivity, in order to be able to give direction to knowledge management initiatives. Methodology/approach – the development and testing of the method is based on the

  4. Test and Evaluation for Enhanced Security: A Quantitative Method to Incorporate Expert Knowledge into Test Planning Decisions.

    Energy Technology Data Exchange (ETDEWEB)

    Rizzo, Davinia [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Blackburn, Mark [Stevens Inst. of Technology, Hoboken, NJ (United States)

    2017-03-01

    Complex systems are comprised of technical, social, political and environmental factors as well as the programmatic factors of cost, schedule and risk. Testing these systems for enhanced security requires expert knowledge in many different fields. It is important to test these systems to ensure effectiveness, but testing is limited to due cost, schedule, safety, feasibility and a myriad of other reasons. Without an effective decision framework for Test and Evaluation (T&E) planning that can take into consideration technical as well as programmatic factors and leverage expert knowledge, security in complex systems may not be assessed effectively. Therefore, this paper covers the identification of the current T&E planning problem and an approach to include the full variety of factors and leverage expert knowledge in T&E planning through the use of Bayesian Networks (BN).

  5. Using Social Media Tools to Enhance Tacit Knowledge Sharing Within the USMC

    Science.gov (United States)

    2013-09-01

    Organizational KM Success According to Davenport, De Long, and Beers, “If the cultural soil isn’t fertile for a knowledge project, no amount of...1998). The USMC is always ready to provide forcible entry or ship-to- objective maneuver (STOM) on foreign soil for a wide range of operations from... enviro nment has called f o r gre ater attention o n how the Marine Corps captures, shares, and transfers info rmation and knowledge assets within

  6. Continuous Enhancement of Science Teachers' Knowledge and Skills through Scientific Lecturing.

    Science.gov (United States)

    Azevedo, Maria-Manuel; Duarte, Sofia

    2018-01-01

    Due to their importance in transmitting knowledge, teachers can play a crucial role in students' scientific literacy acquisition and motivation to respond to ongoing and future economic and societal challenges. However, to conduct this task effectively, teachers need to continuously improve their knowledge, and for that, a periodic update is mandatory for actualization of scientific knowledge and skills. This work is based on the outcomes of an educational study implemented with science teachers from Portuguese Basic and Secondary schools. We evaluated the effectiveness of a training activity consisting of lectures covering environmental and health sciences conducted by scientists/academic teachers. The outcomes of this educational study were evaluated using a survey with several questions about environmental and health scientific topics. Responses to the survey were analyzed before and after the implementation of the scientific lectures. Our results showed that Basic and Secondary schools teachers' knowledge was greatly improved after the lectures. The teachers under training felt that these scientific lectures have positively impacted their current knowledge and awareness on several up-to-date scientific topics, as well as their teaching methods. This study emphasizes the importance of continuing teacher education concerning knowledge and awareness about health and environmental education.

  7. The Effects of Enhancing Prospective EFL Teachers' Knowledge Management Strategies in Virtual Learning Environments on Their Ideational Flexibility and Engagement

    Directory of Open Access Journals (Sweden)

    Ammar Abdullah Mahmoud Ismail

    2017-01-01

    Full Text Available The last few years have witnessed an increased interest in moving away from traditional language instruction settings towards more hybrid and virtual learning environments. Face-to-face interaction, guided practice, and uniformity of knowledge sources and skills are all replaced by settings where multiplicity of views from different learning communities, interconnectedness, self-directedness, and self-management of knowledge and learning are increasingly emphasized. This shift from walled-classroom instruction with its limited scope and resources to hybrid and virtual learning environments with their limitless provisions requires that learners be equipped with requisite skills and strategies to manage knowledge and handle language learning in ways commensurate with the nature and limitless possibilities of these new environments. The current study aimed at enhancing knowledge management strategies of EFL teachers in virtual learning environments and examine the impact on their ideational flexibility and engagement in language learning settings. A knowledge management model was proposed and field-test on a cohort of prospective EFL teachers in the Emirati context. Participants were prospective EFL teachers enrolled in the Methods of Teaching Courses and doing their practicum in the Emirati EFL context. Participants' ideational flexibility was tapped via a bi-methodical approach including a contextualized task and a decontextualized one. Their engagement in virtual language learning settings was tapped via an engagement scale. Results of the study indicated that enhancing prospective EFL teachers' knowledge management strategies in virtual learning environments had a significant impact on their ideational flexibility and engagement in foreign language learning settings. Details of the instructional intervention, instruments for tapping students’ ideational flexibility and engagement, and results of the study are discussed. Implications for

  8. Enhancing health policymakers' information literacy knowledge and skill for policymaking on control of infectious diseases of poverty in Nigeria.

    Science.gov (United States)

    Uneke, Chigozie Jesse; Ezeoha, Abel Ebeh; Uro-Chukwu, Henry; Ezeonu, Chinonyelum Thecla; Ogbu, Ogbonnaya; Onwe, Friday; Edoga, Chima

    2015-01-01

    In Nigeria, one of the major challenges associated with evidence-to-policy link in the control of infectious diseases of poverty (IDP), is deficient information literacy knowledge and skill among policymakers. There is need for policymakers to acquire the skill to discover relevant information, accurately evaluate retrieved information and to apply it correctly. To use information literacy tool of International Network for Availability of Scientific Publications (INASP) to enhance policymakers' knowledge and skill for policymaking on control of IDP in Nigeria. Modified "before and after" intervention study design was used in which outcomes were measured on target participants both before the intervention is implemented and after. This study was conducted in Ebonyi State, south-eastern Nigeria and participants were career health policy makers. A two-day health-policy information literacy training workshop was organized to enhance participants" information literacy capacity. Topics covered included: introduction to information literacy; defining information problem; searching for information online; evaluating information; science information; knowledge sharing interviews; and training skills. A total of 52 policymakers attended the workshop. The pre-workshop mean rating (MNR) of knowledge and capacity for information literacy ranged from 2.15-2.97, while the post-workshop MNR ranged from 3.34-3.64 on 4-point scale. The percentage increase in MNR of knowledge and capacity at the end of the workshop ranged from 22.6%-55.3%. The results of this study suggest that through information literacy training workshop policy makers can acquire the knowledge and skill to identify, capture and share the right kind of information in the right contexts to influence relevant action or a policy decision.

  9. Can Children Enhance Their Family's Health Knowledge? An Infectious Disease Prevention Program.

    Science.gov (United States)

    Sedighi, Iraj; Nouri, Shahla; Sadrosadat, Taravat; Nemati, Reza; Shahbazi, Mojgan

    2012-12-01

    The purpose of this study is to propose an innovative method of knowledge transfer that aims to improve health literacy about pediatric infectious diseases prevention in families. Children have an appreciable role in this scheme. This study is a before and after trial that has been conducted in Hamedan in 2009. After changing seven infectious disease topics into childish poems, we selected five kindergartens randomly and taught these poetries to the children. Teaching process held after a pretest containing 24 questions that examined 103 of parents about mentioned topics. The same post-test was given after 4 months of teaching process. The mean of correct answers to the pretest was 59.22% comparable with 81.00% for post-test (P<0.00). Gender and knowledge degree could not change the results significantly. Assuming one's correct answers to the questions as his/her Knowledge Mark, the mean of this variable increased to 5.32 by this method. This cost-effective and joyful method had successful results in promoting health knowledge. Children are able to play an active role in family's health situation. Learning within family atmosphere without any obligations makes our scheme a solution for paving the knowledge transferring way.

  10. Technology-enhanced storytelling stimulating parent–child interaction and preschool children's vocabulary knowledge

    NARCIS (Netherlands)

    Teepe, R.C.; Molenaar, I.; Verhoeven, L.

    2016-01-01

    Preschool children's vocabulary mainly develops verbal through interaction. Therefore, the technology-enhanced storytelling (TES) activity Jeffy's Journey is developed to support parent–child interaction and vocabulary in preschool children. TES entails shared verbal storytelling supported by a

  11. Technology-enhanced storytelling stimulating parent-child interaction and preschool children's vocabulary knowledge

    NARCIS (Netherlands)

    Teepe, R.C.; Molenaar, I.; Verhoeven, L.T.W.

    2017-01-01

    Preschool children's vocabulary mainly develops verbal through interaction. Therefore, the technology-enhanced storytelling (TES) activity Jeffy's Journey is developed to support parent-child interaction and vocabulary in preschool children. TES entails shared verbal storytelling supported by a

  12. Augmented Reality-Based Simulators as Discovery Learning Tools: An Empirical Study

    Science.gov (United States)

    Ibáñez, María-Blanca; Di-Serio, Ángela; Villarán-Molina, Diego; Delgado-Kloos, Carlos

    2015-01-01

    This paper reports empirical evidence on having students use AR-SaBEr, a simulation tool based on augmented reality (AR), to discover the basic principles of electricity through a series of experiments. AR-SaBEr was enhanced with knowledge-based support and inquiry-based scaffolding mechanisms, which proved useful for discovery learning in…

  13. Problem based learning: enhancing constructivist activities and engagement by fostering online knowledge sharing

    OpenAIRE

    Malik, Manish

    2009-01-01

    PBL was first introduced in medical education as a pure constructivist activity. This was popularly known as the McMaster approach [1]. Later, as can be seen in the literature [2], [4]-[10], there were several different implementations of PBL. There is no single definition of what is classed as a PBL activity. Similarly, there is no one approach reported to be the only successful approach. Sharing of knowledge and discussions based on this knowledge are the hall mark of any successful PBL bas...

  14. Developing the STS sound pollution unit for enhancing students' applying knowledge among science technology engineering and mathematics

    Science.gov (United States)

    Jumpatong, Sutthaya; Yuenyong, Chokchai

    2018-01-01

    STEM education suggested that students should be enhanced to learn science with integration between Science, Technology, Engineering and Mathematics. To help Thai students make sense of relationship between Science, Technology, Engineering and Mathematics, this paper presents learning activities of STS Sound Pollution. The developing of STS Sound Pollution is a part of research that aimed to enhance students' perception of the relationship between Science Technology Engineering and Mathematics. This paper will discuss how to develop Sound Pollution through STS approach in framework of Yuenyong (2006) where learning activities were provided based on 5 stages. These included (1) identification of social issues, (2) identification of potential solutions, (3) need for knowledge, (4) decisionmaking, and (5) socialization stage. The learning activities could be highlighted as following. First stage, we use video clip of `Problem of people about Sound Pollution'. Second stage, students will need to identification of potential solutions by design Home/Factory without noisy. The need of scientific and other knowledge will be proposed for various alternative solutions. Third stage, students will gain their scientific knowledge through laboratory and demonstration of sound wave. Fourth stage, students have to make decision for the best solution of designing safety Home/Factory based on their scientific knowledge and others (e.g. mathematics, economics, art, value, and so on). Finally, students will present and share their Design Safety Home/Factory in society (e.g. social media or exhibition) in order to validate their ideas and redesigning. The paper, then, will discuss how those activities would allow students' applying knowledge of science technology engineering, mathematics and others (art, culture and value) for their possible solution of the STS issues.

  15. Resource Discovery in Activity-Based Sensor Networks

    DEFF Research Database (Denmark)

    Bucur, Doina; Bardram, Jakob

    This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networ....... ABSN enhances the generic Extended Zone Routing Protocol with logical sensor grouping and greatly lowers network overhead during the process of discovery, while keeping discovery latency close to optimal.......This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networks...... (ABSNs) knowledge about their usage even at the network layer. ABSN redesigns classical network-level service discovery protocols to include and use this logical structuring of the network for a more practically applicable service discovery scheme. Noting that in practical settings activity-based sensor...

  16. Were Knowledge Management Abilities of University Students Enhanced after Creating Personal Blog-Based Portfolios?

    Science.gov (United States)

    Chang, Chi-Cheng; Liang, Chaoyun; Tseng, Kuo-Hung; Tseng, Ju-Shih; Chen, To-Yu

    2013-01-01

    The effect of creating blog-based portfolios on knowledge management (KM) abilities among university students was examined in the present study. Participants included 43 students majoring in Multimedia and Game Science at a University in Taiwan. Students spent nine weeks creating their personal portfolios by using a blog. The "t"-test…

  17. Enhancing Students' NOS Views and Science Knowledge Using Facebook-Based Scientific News

    Science.gov (United States)

    Huang, Hsi-Yu; Wu, Hui-Ling; She, Hsiao-Ching; Lin, Yu-Ren

    2014-01-01

    This study investigated how the different discussion approaches in Facebook influenced students' scientific knowledge acquisition and the nature of science (NOS) views. Two eighth- and two ninth-grade classes in a Taiwanese junior high school participated in the study. In two of the classes students engaged in synchronous discussion, and in the…

  18. Knowledge of Results after Good Trials Enhances Learning in Older Adults

    Science.gov (United States)

    Chiviacowsky, Suzete; Wulf, Gabriele; Wally, Raquel; Borges, Thiago

    2009-01-01

    In recent years, some researchers have examined motor learning in older adults. Some of these studies have specifically looked at the effectiveness of different manipulations of extrinsic feedback, or knowledge of results (KR). Given that many motor tasks may already be more challenging for older adults compared to younger adults, making KR more…

  19. Teacher design knowledge and beliefs for technology enhanced learning materials in early literacy: Four portraits

    NARCIS (Netherlands)

    Boschman, Ferry; McKenney, Susan; Pieters, Jules; Voogt, Joke

    2016-01-01

    Teacher engagement in the design of technology-rich learning material is beneficial to teacher learning and may create a sense of ownership, both of which are conducive to bringing about innovation with technology. During collaborative design, teachers draw on various types of knowledge and

  20. Teacher design knowledge and beliefs for technology enhanced learning materials in early literacy: Four portraits

    NARCIS (Netherlands)

    Boschman, F.; McKenney, S.; Pieters, J.M.; Voogt, J.

    2015-01-01

    Teacher engagement in the design of technology-rich learning material is beneficial to teacher learning and may create a sense of ownership, both of which are conducive to bringing about innovation with technology. During collaborative design, teachers draw on various types of knowledge and beliefs:

  1. A Creative Way to Utilize Social Media to Enhance Fitness and Health Knowledge

    Science.gov (United States)

    Polsgrove, Myles Jay; Frimming, Renee Elizabeth

    2013-01-01

    The social media format can be used to create a physical education community of experienced and new student members. In this setting, opportunities for novel and meaningful student interactions can be made possible. Through access to the insights of experienced members, new or incoming members can more quickly become knowledgeable members.…

  2. Enhancing Mathematics Teachers' Knowledge of Students' Thinking from Assessing and Analyzing Misconceptions in Homework

    Science.gov (United States)

    An, Shuhua; Wu, Zhonghe

    2012-01-01

    This study focuses on teacher learning of student thinking through grading homework, assessing and analyzing misconceptions. The data were collected from 10 teachers at fifth-eighth grade levels in the USA. The results show that assessing and analyzing misconceptions from grading homework is an important approach to acquiring knowledge of…

  3. Enhancing the prospective biology teachers’ Pedagogical Content Knowledge (PCK) through a peer coaching based model

    Science.gov (United States)

    Anwar, Yenny

    2018-05-01

    This paper presents the results of implementation Peer Coaching Based Model that was implemented in development and Packaging Learning Tool program aimed at developing a Pedagogical Content Knowledge prospective teachers’ capabilities. Development and Packaging Learning Tool is a training program that applies various knowledge, attitude, and skill of students in order to form professional teacher. A need assessment was conducted to identify prospective teachers’ professional needs, especially PCK ability. Tests, questionnaires, interviews, field notes and video recordings were used in this research. The result indicated that the ability of Prospective teachers’ PCK has increased. This can be shown from the N-Gain that included in the medium category. This increase shows that there is integration of pedagogy and content; they have used varied strategies and can explain the reasons for its used. This means that the pattern belongs to the lower limit of the growing- PCK category. It is recommended to use peer coaching model during peer teaching.

  4. Paving New Roads to Knowledge: An Experiment to Enhance Construction Education

    Science.gov (United States)

    Sattineni, Anoop; Williams, Steve

    2008-01-01

    As a result of their own sometimes frustrating educational experiences, and a growing discontent with their current teaching methods, the authors, in conjunction with another instructor, decided to try an experiment. With the goal of enhancing visualization and understanding, the instructors created several multi-path educational paths for the…

  5. To Enhance Collaborative Learning and Practice Network Knowledge with a Virtualization Laboratory and Online Synchronous Discussion

    Science.gov (United States)

    Hwang, Wu-Yuin; Kongcharoen, Chaknarin; Ghinea, Gheorghita

    2014-01-01

    Recently, various computer networking courses have included additional laboratory classes in order to enhance students' learning achievement. However, these classes need to establish a suitable laboratory where each student can connect network devices to configure and test functions within different network topologies. In this case, the Linux…

  6. Technology-Enhanced Storytelling Stimulating Parent-Child Interaction and Preschool Children's Vocabulary Knowledge

    Science.gov (United States)

    Teepe, R. C.; Molenaar, I.; Verhoeven, L.

    2017-01-01

    Preschool children's vocabulary mainly develops verbal through interaction. Therefore, the technology-enhanced storytelling (TES) activity Jeffy's Journey is developed to support parent-child interaction and vocabulary in preschool children. TES entails shared verbal storytelling supported by a story structure and real-time visual, auditory and…

  7. Teacher design knowledge for technology enhanced learning: a framework for investigating assets and needs

    NARCIS (Netherlands)

    McKenney, Susan; Kali, Y.; Mauiskaite, L.; Voogt, Joke

    2014-01-01

    Design of (technology-enhanced) learning activities and materials is one fruitful process through which teachers learn and become professionals. To facilitate this process, research is needed to understand how teachers learn through design, how this process may be supported, and how teacher

  8. Knowledge Discovery and Intensive Management of Manufacturing enterprise Based on Data Mining Technology%基于数据挖掘技术的制造企业工艺知识发现和集约化管理

    Institute of Scientific and Technical Information of China (English)

    王茨; 彭静; 刘雁; 杨素明

    2016-01-01

    A great deal of useful knowledge and law were hidden in lots of experience,case data in the process of design and production everyday. These knowledge would be wasted if these data were just stored in computers or work packages. In this paper,one knowledge discovery based rough set theory on was proposed. Combined with a case,three pieces of knowledge were dug from 25 production data. the result showed that the way was valid. The data digging technology could help enterprises to realize the knowledge fully dug up and intensive management to avoid that the enterprise had a great volume of data but no useful knowledge,and improved the core competitiveness of the company.%制造型企业在日常设计、生产过程中,积累了大量的经验、案例和设计生产数据。为挖掘这些数据中的有用知识和规律,实现知识的充分挖掘和集约化管理,提升企业的核心竞争力,提出一种基于粗糙集的工艺知识发现技术,并通过具体算例从25条生产数据中挖掘出3条知识,结果显示:该方法是有效的。

  9. Introduction of Virtual Patient Software to Enhance Physician Assistant Student Knowledge in Palliative Medicine.

    Science.gov (United States)

    Prazak, Kristine A

    2017-01-01

    The purpose of this project was to infuse palliative medicine and end-of-life care creatively into physician assistant (PA) education. Nine second-year PA students volunteered to participate in this quasi-experimental, pretest-posttest pilot study. Students initially completed an anonymous survey evaluating seven domains of knowledge in palliative medicine coupled with a self-assessment in competence. Virtual patient software was then used to simulate clinical encounters that addressed major palliative care domains. Upon completion of these cases, the same survey, with the addition of three questions about their own personal feelings, was administered. Overall response was positive in regard to improved knowledge and the virtual patient experience. After completion of the cases, students rated their self-assessed skills higher in all domains than prior to completing the cases. Factual knowledge scores showed a slight but not significant improvement, with an average pre-survey score of 4.56 and post-survey score of 4.67. Using virtual patient software can be a way of infusing palliative medicine and end-of-life care into PA education. These encounters can then be modified to include interprofessional encounters within the health professions.

  10. Radioactivity. Centenary of radioactivity discovery

    International Nuclear Information System (INIS)

    Charpak, G.; Tubiana, M.; Bimbot, R.

    1997-01-01

    This small booklet was edited for the occasion of the exhibitions of the celebration of the centenary of radioactivity discovery which took place in various locations in France from 1996 to 1998. It recalls some basic knowledge concerning radioactivity and its applications: history of discovery, atoms and isotopes, radiations, measurement of ionizing radiations, natural and artificial radioactivity, isotope dating and labelling, radiotherapy, nuclear power and reactors, fission and fusion, nuclear wastes, dosimetry, effects and radioprotection. (J.S.)

  11. A knowledge translation intervention to enhance clinical application of a virtual reality system in stroke rehabilitation.

    Science.gov (United States)

    Levac, Danielle; Glegg, Stephanie M N; Sveistrup, Heidi; Colquhoun, Heather; Miller, Patricia A; Finestone, Hillel; DePaul, Vincent; Harris, Jocelyn E; Velikonja, Diana

    2016-10-06

    Despite increasing evidence for the effectiveness of virtual reality (VR)-based therapy in stroke rehabilitation, few knowledge translation (KT) resources exist to support clinical integration. KT interventions addressing known barriers and facilitators to VR use are required. When environmental barriers to VR integration are less amenable to change, KT interventions can target modifiable barriers related to therapist knowledge and skills. A multi-faceted KT intervention was designed and implemented to support physical and occupational therapists in two stroke rehabilitation units in acquiring proficiency with use of the Interactive Exercise Rehabilitation System (IREX; GestureTek). The KT intervention consisted of interactive e-learning modules, hands-on workshops and experiential practice. Evaluation included the Assessing Determinants of Prospective Take Up of Virtual Reality (ADOPT-VR) Instrument and self-report confidence ratings of knowledge and skills pre- and post-study. Usability of the IREX was measured with the System Usability Scale (SUS). A focus group gathered therapist experiences. Frequency of IREX use was recorded for 6 months post-study. Eleven therapists delivered a total of 107 sessions of VR-based therapy to 34 clients with stroke. On the ADOPT-VR, significant pre-post improvements in therapist perceived behavioral control (p = 0.003), self-efficacy (p = 0.005) and facilitating conditions (p =0.019) related to VR use were observed. Therapist intention to use VR did not change. Knowledge and skills improved significantly following e-learning completion (p = 0.001) and was sustained 6 months post-study. Below average perceived usability of the IREX (19 th percentile) was reported. Lack of time was the most frequently reported barrier to VR use. A decrease in frequency of perceived barriers to VR use was not significant (p = 0.159). Two therapists used the IREX sparingly in the 6 months following the study. Therapists reported

  12. A FAIR-Based Approach to Enhancing the Discovery and Re-Use of Transcriptomic Data Assets for Nuclear Receptor Signaling Pathways

    Directory of Open Access Journals (Sweden)

    Scott A. Ochsner

    2017-03-01

    Full Text Available Public transcriptomic assets in the nuclear receptor (NR signaling field hold considerable collective potential for exposing underappreciated aspects of NR regulation of gene expression. This potential is undermined however by a series of enduring informatic pain points that retard the routine re-use of these datasets. Here we describe a coordinated biocuration and web development approach to redress this situation that is closely aligned with ideals articulated in the FAIR (findable, accessible, interoperable, re-usable principles on data stewardship. To improve findability, biocurators engage authors of studies in collaborating journals to secure datasets for deposition in public archives. Annotated derivatives of the archived datasets are assigned digital object identifiers and regulatory molecule identifiers that support persistent linkages between datasets and their associated research articles, integration in relevant records in gene and small molecule knowledgebases, and indexing by dataset search engines. To enhance their accessibility and interoperability, datasets are visualizable in responsively designed web pages, retrievable in machine-readable spreadsheets, or through an application programming interface. Re-use of the datasets is supported by their interrogation as a universe of data points through the Transcriptomine search engine, highlighting transcriptional intersections between NR signaling pathways, physiological processes and disease states. We illustrate the value of our approach in connecting disparate research communities using a use case of persistent interoperability between the Nuclear Receptor Signaling Atlas and the Pharmacogenomics Knowledgebase. Our FAIR-aligned model demonstrates the enduring value of discovery-scale datasets that accrues from their systematic compilation, biocuration and distribution across the digital biomedical research enterprise.

  13. Knowledge Translation Strategies for Enhancing Nurses’ Evidence-Informed Decision Making: A Scoping Review

    OpenAIRE

    Yost, Jennifer; Thompson, David; Ganann, Rebecca; Aloweni, Fazila; Newman, Kristine; McKibbon, Ann; Dobbins, Maureen; Ciliska, Donna

    2014-01-01

    Background Nurses are increasingly expected to engage in evidence-informed decision making (EIDM); the use of research evidence with information about patient preferences, clinical context and resources, and their clinical expertise in decision making. Strategies for enhancing EIDM have been synthesized in high-quality systematic reviews, yet most relate to physicians or mixed disciplines. Existing reviews, specific to nursing, have not captured a broad range of strategies for promoting the k...

  14. Educational outreach and collaborative care enhances physician's perceived knowledge about Developmental Coordination Disorder.

    Science.gov (United States)

    Gaines, Robin; Missiuna, Cheryl; Egan, Mary; McLean, Jennifer

    2008-01-24

    Developmental Coordination Disorder (DCD) is a chronic neurodevelopmental condition that affects 5-6% of children. When not recognized and properly managed during the child's development, DCD can lead to academic failure, mental health problems and poor physical fitness. Physicians, working in collaboration with rehabilitation professionals, are in an excellent position to recognize and manage DCD. This study was designed to determine the feasibility and impact of an educational outreach and collaborative care model to improve chronic disease management of children with DCD. The intervention included educational outreach and collaborative care for children with suspected DCD. Physicians were educated by and worked with rehabilitation professionals from February 2005 to April 2006. Mixed methods evaluation approach documented the process and impact of the intervention. Physicians: 750 primary care physicians from one major urban area and outlying regions were invited to participate; 147 physicians enrolled in the project. Children: 125 children were identified and referred with suspected DCD. The main outcome was improvement in knowledge and perceived skill of physicians concerning their ability to screen, diagnose and manage DCD. At baseline 91.1% of physicians were unaware of the diagnosis of DCD, and only 1.6% could diagnose condition. Post-intervention, 91% of participating physicians reported greater knowledge about DCD and 29.2% were able to diagnose DCD compared to 0.5% of non-participating physicians. 100% of physicians who participated in collaborative care indicated they would continue to use the project materials and resources and 59.4% reported they would recommend or share the materials with medical colleagues. In addition, 17.6% of physicians not formally enrolled in the project reported an increase in knowledge of DCD. Physicians receiving educational outreach visits significantly improved their knowledge about DCD and their ability to identify and

  15. Exploiting Expert Knowledge to Enhance Simulation-based Optimization of Environmental Remediation Systems

    Science.gov (United States)

    Reslink, C. F.; Matott, L. S.

    2012-12-01

    Designing cost-effective systems to safeguard national water supplies from contaminated sites is often aided by simulation-based optimization - where a flow or transport model is linked with an "off-the-shelf" global optimization search algorithm. However, achieving good performance from these types of optimizers within a reasonable computational budget has proven to be difficult. Therefore, this research seeks to boost optimization efficiency by augmenting search procedures with non-traditional information, such as site-specific knowledge and practitioner rules-of-thumb. An example application involving pump-and-treat optimization is presented in which a series of extraction wells are to be installed to intercept pollutants at a contaminated site in Billings, Montana. Selected heuristic algorithms (e.g. Genetic Algorithm) are interfaced with a rules engine that makes inline adjustments to the well locations of candidate pump-and-treat designs. If necessary, the rules engine modifies a given pump-and-treat design so that: (1) wells are placed within plume boundaries; and (2) well placement is biased toward areas where, if left untreated, the plume is predicted to spread most rapidly. Results suggest that incorporating this kind of expert knowledge can significantly increase the search efficiency of many popular global optimizers.

  16. Security Enhancement of Knowledge-based User Authentication through Keystroke Dynamics

    Directory of Open Access Journals (Sweden)

    Roy Soumen

    2016-01-01

    Full Text Available Keystroke Dynamics is a behavioural biometrics characteristic in Biometric science, which solve the issues in user identification or verification. In Knowledge-based user authentication technique, we compromise with PIN or password which is unsafe due to different type of attacks. It is good to choose password with the combination of upper and lower case letter with some digits and symbols, but which is very hard to remember or generally we forget to distinguish those passwords for different access control systems. Our system not only takes the users’ entered texts but their typing style is also account for. In our experiment, we have not taken hard password type texts, we have chosen some daily used words where users are habituated and comfortable at typing and we obtained the consisting typing pattern. Different distance-based and data mining algorithms we have applied on collected typing pattern and obtained impressive results. As per our experiment, if we use keystroke dynamics in existing knowledge based user authentication system with minimum of five daily used common texts then it increases the security level up to 97.6% to 98.2% (if we remove some of the irrelevant feature sets.

  17. Translational Research 2.0: a framework for accelerating collaborative discovery.

    Science.gov (United States)

    Asakiewicz, Chris

    2014-05-01

    The world wide web has revolutionized the conduct of global, cross-disciplinary research. In the life sciences, interdisciplinary approaches to problem solving and collaboration are becoming increasingly important in facilitating knowledge discovery and integration. Web 2.0 technologies promise to have a profound impact - enabling reproducibility, aiding in discovery, and accelerating and transforming medical and healthcare research across the healthcare ecosystem. However, knowledge integration and discovery require a consistent foundation upon which to operate. A foundation should be capable of addressing some of the critical issues associated with how research is conducted within the ecosystem today and how it should be conducted for the future. This article will discuss a framework for enhancing collaborative knowledge discovery across the medical and healthcare research ecosystem. A framework that could serve as a foundation upon which ecosystem stakeholders can enhance the way data, information and knowledge is created, shared and used to accelerate the translation of knowledge from one area of the ecosystem to another.

  18. Enhancing creativity for individuals, groups and organizations: Creativity as the Unlimited Application of Knowledge

    DEFF Research Database (Denmark)

    Byrge, Christian; Hansen, Søren

    How do we become creative individuals, by ourselves and with others? How do we increase innovation in our work or study environments? How do we learn to think in unlimited ways? The answers to these questions can be found in this book, which presents new methods for enhancing our own and others......, cultural or professional backgrounds. Using a newly developed scientific theory combined with three practical and thoroughly tested methods, scholars Christian Byrge and Søren Hansen demonstrate how to increase our possibilities for creative thinking in both our academic, professional and private lives...

  19. Enhanced parenting knowledge and skills in mothers of preschool children with sickle cell disease.

    Science.gov (United States)

    Schuman, W B; Armstrong, F D; Pegelow, C H; Routh, D K

    1993-10-01

    Compared 25 preschool children with sickle cell disease (SCD) to demographically matched healthy comparison children on maternal reports of child-rearing beliefs and practices and maternal and child behaviors related to social adjustment. Mothers of children with SCD possessed significantly more knowledge of appropriate discipline techniques. The groups did not differ on maternal reports of socially relevant child behavior. However, when mother-child interactions were observed in free play and structured play settings, mothers of children with SCD treated their children as competent significantly more, and treated their children as incompetent significantly less, than comparison mothers. Mothers of children with SCD also used significantly more reinforcement during the final toy pick-up condition. There were no observed differences between groups in the children's behavior.

  20. Frequent Immediate Knowledge of Results Enhances the Increase of Throwing Velocity in Overarm Handball Performance.

    Science.gov (United States)

    Štirn, Igor; Carruthers, Jamie; Šibila, Marko; Pori, Primož

    2017-02-01

    In the present study, the effect of frequent, immediate, augmented feedback on the increase of throwing velocity was investigated. An increase of throwing velocity of a handball set shot when knowledge of results was provided or not provided during training was compared. Fifty female and seventy-three male physical education students were assigned randomly to the experimental or control group. All participants performed two series of ten set shots with maximal effort twice a week for six weeks. The experimental group received information regarding throwing velocity measured by a radar gun immediately after every shot, whereas the control group did not receive any feedback. Measurements of maximal throwing velocity of an ordinary handball and a heavy ball were performed, before and after the training period and compared. Participants who received feedback on results attained almost a four times greater relative increase of the velocity of the normal ball (size 2) as compared to the same intervention when feedback was not provided (8.1 ± 3.6 vs. 2.7 ± 2.9%). The velocity increases were smaller, but still significant between the groups for throws using the heavy ball (5.1 ± 4.2 and 2.5 ± 5.8 for the experimental and control group, respectively). Apart from the experimental group throwing the normal ball, no differences in velocity change for gender were obtained. The results confirmed that training oriented towards an increase in throwing velocity became significantly more effective when frequent knowledge of results was provided.

  1. Can role-play with interactive simulations enhance climate change knowledge, affect and intent to act?

    Science.gov (United States)

    Rooney-varga, J. N.; Sterman, J.; Fracassi, E. P.; Franck, T.; Kapmeier, F.; Kurker, V.; Jones, A.; Rath, K.

    2017-12-01

    The strong scientific consensus about the reality and risks of anthropogenic climate change stands in stark contrast to widespread confusion and complacency among the public. Many efforts to close that gap, grounded in the information deficit model of risk communication, provide scientific information on climate change through reports and presentations. However, research shows that showing people research does not work: the gap between scientific and public understanding of climate change remains wide. Tools that are rigorously grounded in the science and motivate action on climate change are urgently needed. Here we assess the impact of one such tool, an interactive, role-play simulation, World Climate. Participants take the roles of delegates to the UN climate negotiations and are challenged to create an agreement limiting warming to no more than 2°C. The C-ROADS climate simulation model then provides participants with immediate feedback about the expected impacts of their decisions. Participants use C-ROADS to explore the climate system and use the results to refine their negotiating positions, learning about climate change while experiencing the social dynamics of negotiations and decision-making. Pre- and post-survey results from 21 sessions in eight nations showed significant gains in participants' climate change knowledge, affective engagement, intent to take action, and desire to learn. Contrary to the deficit model, gains in participants' desire to learn more and intention to act were associated with gains in affective engagement, particularly feelings of urgency and hope, but not climate knowledge. Gains were just as strong among participants who oppose government regulation, suggesting the simulation's potential to reach across political divides. Results indicate that simulations like World Climate offer a climate change communication tool that enables people to learn and feel for themselves, which together have the potential to motivate action informed

  2. Use of an Online Education Platform to Enhance Patients' Knowledge About Radiation in Diagnostic Imaging.

    Science.gov (United States)

    Steele, Joseph R; Jones, A Kyle; Clarke, Ryan K; Shiao, Sue J; Wei, Wei; Shoemaker, Stowe; Parmar, Simrit

    2017-03-01

    The aim of this study was to compare the impact of a digital interactive education platform and standard paper-based education on patients' knowledge regarding ionizing radiation. Beginning in January 2015, patients at a tertiary cancer center scheduled for diagnostic imaging procedures were randomized to receive information about ionizing radiation delivered through a web-based interactive education platform (interactive education group), the same information in document format (document education group), or no specialized education (control group). Patients who completed at least some education and control group patients were invited to complete a knowledge assessment; interactive education patients were invited to provide feedback about satisfaction with their experience. A total of 2,226 patients participated. Surveys were completed by 302 of 745 patients (40.5%) participating in interactive education, 488 of 993 (49.1%) participating in document education, and 363 of 488 (74.4%) in the control group. Patients in the interactive education group were significantly more likely to say that they knew the definition of ionizing radiation, outperformed the other groups in identifying which imaging examinations used ionizing radiation, were significantly more likely to identify from a list which imaging modality had the highest radiation dose, and tended to perform better when asked about the tissue effects of radiation in diagnostic imaging, although this difference was not significant. In the interactive education group, 84% of patients were satisfied with the experience, and 79% said that they would recommend the program. Complex information on a highly technical subject with personal implications for patients may be conveyed more effectively using electronic platforms, and this approach is well accepted. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  3. Enhancing Evacuation Plans with a Situation Awareness System Based on End-User Knowledge Provision

    Directory of Open Access Journals (Sweden)

    Augusto Morales

    2014-06-01

    Full Text Available Recent disasters have shown that having clearly defined preventive procedures and decisions is a critical component that minimizes evacuation hazards and ensures a rapid and successful evolution of evacuation plans. In this context, we present our Situation-Aware System for enhancing Evacuation Plans (SASEP system, which allows creating end-user business rules that technically support the specific events, conditions and actions related to evacuation plans. An experimental validation was carried out where 32 people faced a simulated emergency situation, 16 of them using SASEP and the other 16 using a legacy system based on static signs. From the results obtained, we compare both techniques and discuss in which situations SASEP offers a better evacuation route option, confirming that it is highly valuable when there is a threat in the evacuation route. In addition, a study about user satisfaction using both systems is presented showing in which cases the systems are assessed as satisfactory, relevant and not frustrating.

  4. Learning and Relevance in Information Retrieval: A Study in the Application of Exploration and User Knowledge to Enhance Performance

    Science.gov (United States)

    Hyman, Harvey

    2012-01-01

    This dissertation examines the impact of exploration and learning upon eDiscovery information retrieval; it is written in three parts. Part I contains foundational concepts and background on the topics of information retrieval and eDiscovery. This part informs the reader about the research frameworks, methodologies, data collection, and…

  5. External Control of Knowledge of Results: Learner Involvement Enhances Motor Skill Transfer.

    Science.gov (United States)

    Figueiredo, L S; Ugrinowitsch, H; Freire, A B; Shea, J B; Benda, R N

    2018-04-01

    Providing the learner control over aspects of practice has improved the process of motor skill acquisition, and self-controlled knowledge of results (KR) schedules have shown specific advantages over externally controlled ones. A possible explanation is that self-controlled KR schedules lead learners to more active task involvement, permitting deeper information processing. This study tested this explanatory hypothesis. Thirty undergraduate volunteers of both sexes, aged 18 to 35, all novices in the task, practiced transporting a tennis ball in a specified sequence within a time goal. We compared a high-involvement group (involvement yoked, IY), notified in advance about upcoming KR trials, to self-controlled KR (SC) and yoked KR (YK) groups. The experiment consisted of three phases: acquisition, retention, and transfer. We found both IY and SC groups to be superior to YK for transfer of learning. Postexperiment participant questionnaires confirmed a preference for receiving KR after learner-perceived good trials, even though performance on those trials did not differ from performance on trials without KR. Equivalent IY and SC performances provide support for the benefits of task involvement and deeper information processing when KR is self-controlled in motor skill acquisition.

  6. Adding temporally localized noise can enhance the contribution of target knowledge on contrast detection.

    Science.gov (United States)

    Silvestre, Daphné; Cavanagh, Patrick; Arleo, Angelo; Allard, Rémy

    2017-02-01

    External noise paradigms are widely used to characterize sensitivity by comparing the effect of a variable on contrast threshold when it is limited by internal versus external noise. A basic assumption of external noise paradigms is that the processing properties are the same in low and high noise. However, recent studies (e.g., Allard & Cavanagh, 2011; Allard & Faubert, 2014b) suggest that this assumption could be violated when using spatiotemporally localized noise (i.e., appearing simultaneously and at the same location as the target) but not when using spatiotemporally extended noise (i.e., continuously displayed, full-screen, dynamic noise). These previous findings may have been specific to the crowding and 0D noise paradigms that were used, so the purpose of the current study is to test if this violation of noise-invariant processing also occurs in a standard contrast detection task in white noise. The rationale of the current study is that local external noise triggers the use of recognition rather than detection and that a recognition process should be more affected by uncertainty about the shape of the target than one involving detection. To investigate the contribution of target knowledge on contrast detection, the effect of orientation uncertainty was evaluated for a contrast detection task in the absence of noise and in the presence of spatiotemporally localized or extended noise. A larger orientation uncertainty effect was observed with temporally localized noise than with temporally extended noise or with no external noise, indicating a change in the nature of the processing for temporally localized noise. We conclude that the use of temporally localized noise in external noise paradigms risks triggering a shift in process, invalidating the noise-invariant processing required for the paradigm. If, instead, temporally extended external noise is used to match the properties of internal noise, no such processing change occurs.

  7. The discovery of radioactivity: the centenary

    International Nuclear Information System (INIS)

    Patil, S.K.

    1995-01-01

    In the last decade of the nineteenth century, a number of fundamental discoveries of outstanding importance were made unexpectedly which marked the beginning of a new era in physics. A cascade of spectacular discoveries began with the announcement of the discovery of x-rays by Roentgen followed by the discoveries, in quick succession, of radioactivity by Becquerel, of Zeeman effect, of electron by J.J. Thomson, and of polonium and radium by the Curies. Both x-rays and radioactivity have wide applications in scientific, medical and industrial fields and have made outstanding contribution to the advancement of human knowledge and welfare. Radioactivity is well known and no other discovery in the field of physics or chemistry has had a more profound effect on our fundamental knowledge of nature. Present article, on the occasion of the centenary of the discovery of radioactivity, makes an attempt to describe some glimpses of the history of radioactivity. (author). 59 refs

  8. To Enhance Collaborative Learning and Practice Network Knowledge with a Virtualization Laboratory and Online Synchronous Discussion

    Directory of Open Access Journals (Sweden)

    Wu-Yuin Hwang

    2014-09-01

    Full Text Available Recently, various computer networking courses have included additional laboratory classes in order to enhance students’ learning achievement. However, these classes need to establish a suitable laboratory where each student can connect network devices to configure and test functions within different network topologies. In this case, the Linux operating system can be used to operate network devices and the virtualization technique can include multiple OSs for supporting a significant number of students. In previous research, the virtualization application was successfully applied in a laboratory, but focused only on individual assignments. The present study extends previous research by designing the Networking Virtualization-Based Laboratory (NVBLab, which requires collaborative learning among the experimental students. The students were divided into an experimental group and a control group for the experiment. The experimental group performed their laboratory assignments using NVBLab, whereas the control group completed them on virtual machines (VMs that were installed on their personal computers. Moreover, students using NVBLab were provided with an online synchronous discussion (OSD feature that enabled them to communicate with others. The laboratory assignments were divided into two parts: Basic Labs and Advanced Labs. The results show that the experimental group significantly outperformed the control group in two Advanced Labs and the post-test after Advanced Labs. Furthermore, the experimental group’s activities were better than those of the control group based on the total average of the command count per laboratory. Finally, the findings of the interviews and questionnaires with the experimental group reveal that NVBLab was helpful during and after laboratory class.

  9. Systematic Integration of Innovation in Process Improvement Projects Using the Enhanced Sigma-TRIZ Algorithm and Its Effective Use by Means of a Knowledge Management Software Platform

    Directory of Open Access Journals (Sweden)

    Mircea FULEA

    2009-01-01

    Full Text Available In an evolving, highly turbulent and uncertain socio-economic environment, organizations must consider strategies of systematic and continuous integration of innovation within their business systems, as a fundamental condition for sustainable development. Adequate methodologies are required in this respect. A mature framework for integrating innovative problem solving approaches within business process improvement methodologies is proposed in this paper. It considers a TRIZ-centred algorithm in the improvement phase of the DMAIC methodology. The new tool is called enhanced sigma-TRIZ. A case study reveals the practical application of the proposed methodology. The integration of enhanced sigma-TRIZ within a knowledge management software platform (KMSP is further described. Specific developments to support processes of knowledge creation, knowledge storage and retrieval, knowledge transfer and knowledge application in a friendly and effective way within the KMSP are also highlighted.

  10. Knowledge discovery from patients' behavior via clustering-classification algorithms based on weighted eRFM and CLV model: An empirical study in public health care services.

    Science.gov (United States)

    Zare Hosseini, Zeinab; Mohammadzadeh, Mahdi

    2016-01-01

    The rapid growing of information technology (IT) motivates and makes competitive advantages in health care industry. Nowadays, many hospitals try to build a successful customer relationship management (CRM) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. Many hospitals have large data warehouses containing customer demographic and transactions information. Data mining techniques can be used to analyze this data and discover hidden knowledge of customers. This research develops an extended RFM model, namely RFML (added parameter: Length) based on health care services for a public sector hospital in Iran with the idea that there is contrast between patient and customer loyalty, to estimate customer life time value (CLV) for each patient. We used Two-step and K-means algorithms as clustering methods and Decision tree (CHAID) as classification technique to segment the patients to find out target, potential and loyal customers in order to implement strengthen CRM. Two approaches are used for classification: first, the result of clustering is considered as Decision attribute in classification process and second, the result of segmentation based on CLV value of patients (estimated by RFML) is considered as Decision attribute. Finally the results of CHAID algorithm show the significant hidden rules and identify existing patterns of hospital consumers.

  11. Knowledge discovery from patients’ behavior via clustering-classification algorithms based on weighted eRFM and CLV model: An empirical study in public health care services

    Science.gov (United States)

    Zare Hosseini, Zeinab; Mohammadzadeh, Mahdi

    2016-01-01

    The rapid growing of information technology (IT) motivates and makes competitive advantages in health care industry. Nowadays, many hospitals try to build a successful customer relationship management (CRM) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. Many hospitals have large data warehouses containing customer demographic and transactions information. Data mining techniques can be used to analyze this data and discover hidden knowledge of customers. This research develops an extended RFM model, namely RFML (added parameter: Length) based on health care services for a public sector hospital in Iran with the idea that there is contrast between patient and customer loyalty, to estimate customer life time value (CLV) for each patient. We used Two-step and K-means algorithms as clustering methods and Decision tree (CHAID) as classification technique to segment the patients to find out target, potential and loyal customers in order to implement strengthen CRM. Two approaches are used for classification: first, the result of clustering is considered as Decision attribute in classification process and second, the result of segmentation based on CLV value of patients (estimated by RFML) is considered as Decision attribute. Finally the results of CHAID algorithm show the significant hidden rules and identify existing patterns of hospital consumers. PMID:27610177

  12. Knowledge-based identification of the ERK2/STAT3 signal pathway as a therapeutic target for type 2 diabetes and drug discovery.

    Science.gov (United States)

    Kinoshita, Takayoshi; Doi, Kentaro; Sugiyama, Hajime; Kinoshita, Shuhei; Wada, Mutsuyo; Naruto, Shuji; Tomonaga, Atsushi

    2011-09-01

    Many existing agents for diabetes therapy are unable to restore or maintain normal glucose homeostasis or prevent the eventual emergence of hyperglycemia-related complication. Therefore, agents based on novel mechanisms are sought to complement and extend the current therapeutic approaches. Based on the initial paper research, we focused on active STAT3 as an attractive pharmacological target for type 2 diabetes. The subsequent text mining with a unique query to identify suppressors but not activators of STAT3 revealed the ERK2/STAT3 pathway as a novel diabetes target. The description of ERK2 inhibitors as diabetes target had not been found in our text mining research at present. The mechanism-based peptide inhibitor for ERK2 was identified using the knowledge of the KIM sequence, which has an important role in the recognition of cognate kinases, phosphatases, scaffold proteins, and substrates. The peptide inhibitor was confirmed to exert effects in vitro and in vivo. The peptide inhibitor conferred a significant decrease in HOMA-IR levels on Day 28 compared with that in the vehicle group. Besides lowering the fasting blood glucose level, the peptide inhibitor also attenuated the blood glucose increment in the fed state, as compared with the vehicle group. © 2011 John Wiley & Sons A/S.

  13. Curricular initiatives that enhance student knowledge and perceptions of sexual and gender minority groups: a critical interpretive synthesis.

    Science.gov (United States)

    Desrosiers, Jennifer; Wilkinson, Tim; Abel, Gillian; Pitama, Suzanne

    2016-10-01

    There is no accepted best practice for optimizing tertiary student knowledge, perceptions, and skills to care for sexual and gender diverse groups. The objective of this research was to synthesize the relevant literature regarding effective curricular initiatives designed to enhance tertiary level student knowledge, perceptions, and skills to care for sexual and gender diverse populations. A modified Critical Interpretive Synthesis using a systematic search strategy was conducted in 2015. This method was chosen to synthesize the relevant qualitative and quantitative literature as it allows for the depth and breadth of information to be captured and new constructs to be illuminated. Databases searched include AMED, CINAHL EBM Reviews, ERIC, Ovid MEDLINE, Ovid Nursing Database, PsychInfo, and Google Scholar. Thirty-one articles were included in this review. Curricular initiatives ranging from discrete to multimodal approaches have been implemented. Successful initiatives included discrete sessions with time for processing, and multi-modal strategies. Multi-modal approaches that encouraged awareness of one's lens and privilege in conjunction with facilitated communication seemed the most effective. The literature is limited to the evaluation of explicit curricula. The wider cultural competence literature offers further insight by highlighting the importance of broad and embedded forces including social influences, the institutional climate, and the implicit, or hidden, curriculum. A combined interpretation of the complementary cultural competence and sexual and gender diversity literature provides a novel understanding of the optimal content and context for the delivery of a successful curricular initiative.

  14. Beyond trend analysis: How a modified breakpoint analysis enhances knowledge of agricultural production after Zimbabwe's fast track land reform

    Science.gov (United States)

    Hentze, Konrad; Thonfeld, Frank; Menz, Gunter

    2017-10-01

    MODIS based trend analysis and enhancing knowledge of Zimbabwe's FTLRP.

  15. Computational methods in drug discovery

    Directory of Open Access Journals (Sweden)

    Sumudu P. Leelananda

    2016-12-01

    Full Text Available The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein–ligand docking, pharmacophore modeling and QSAR techniques are reviewed.

  16. Development of an Enhanced Recovery After Surgery Guideline and Implementation Strategy Based on the Knowledge-to-action Cycle.

    Science.gov (United States)

    McLeod, Robin S; Aarts, Mary-Anne; Chung, Frances; Eskicioglu, Cagla; Forbes, Shawn S; Conn, Lesley Gotlib; McCluskey, Stuart; McKenzie, Marg; Morningstar, Beverly; Nadler, Ashley; Okrainec, Allan; Pearsall, Emily A; Sawyer, Jason; Siddique, Naveed; Wood, Trevor

    2015-12-01

    Enhanced Recovery After Surgery (ERAS) protocols have been shown to increase recovery, decrease complications, and reduce length of stay. However, they are difficult to implement. To develop and implement an ERAS clinical practice guideline (CPG) at multiple hospitals. A tailored strategy based on the Knowledge-to-action (KTA) cycle was used to develop and implement an ERAS CPG at 15 academic hospitals in Canada. This included an initial audit to identify gaps and interviews to assess barriers and enablers to implementation. Implementation included development of an ERAS guideline by a multidisciplinary group, communities of practice led by multidiscipline champions (surgeons, anesthesiologists, and nurses) both provincially and locally, educational tools, and clinical pathways as well as audit and feedback. The initial audit revealed there was greater than 75% compliance in only 2 of 18 CPG recommendations. Main themes identified by stakeholders were that the CPG must be based on best evidence, there must be increased communication and collaboration among perioperative team members, and patient education is essential. ERAS and Pain Management CPGs were developed by a multidisciplinary team and have been adopted at all hospitals. Preliminary data from more than 1000 patients show that the uptake of recommended interventions varies but despite this, mean length of stay has decreased with low readmission rates and adverse events. On the basis of short-term findings, our results suggest that a tailored implementation strategy based on the KTA cycle can be used to successfully implement an ERAS program at multiple sites.

  17. Application of Data Mining and Knowledge Discovery Techniques to Enhance Binary Target Detection and Decision-Making for Compromised Visual Images

    National Research Council Canada - National Science Library

    Repperger, D. W; Phillips, C. A; Schrider, C. D; Smith, E. A

    2004-01-01

    In an effort to improve decision-making on the identity of unknown objects appearing in visual images when the surrounding environment may be noisy and cluttered, a highly sensitive target detection...

  18. Interactive data exploration and knowledge discovery

    NARCIS (Netherlands)

    Zudilova-Seinstra, E.; Martens, J.B.O.S.; Adriaansen, T.

    2010-01-01

    People have always relied on visual tools such as maps, charts and diagrams to better understand problems and solve them in less time. Continuous improvements in computer processing power and graphics capabilities have made it possible to incorporate a wide range of advanced visualization techniques

  19. Process mining: making knowledge discovery process centric

    NARCIS (Netherlands)

    Aalst, van der W.M.P.

    2011-01-01

    Recently, the Task Force on Process Mining released the Process Mining Manifesto. The manifesto is supported by 53 organizations and 77 process mining experts contributed to it. The active contributions from end-users, tool vendors, consultants, analysts, and researchers illustrate the growing

  20. Knowledge Discovery from Growing Social Networks

    Science.gov (United States)

    2009-12-24

    a trackback. We exploited the blog “Theme salon of blogs” in the site “goo” 2, where a blogger can recruit trackbacks of other bloggers by registering...using trackbacks. Thus, a piece of information can propagate from one blogger to another blogger through a trackback. We exploited the blog “Theme salon ...interesting propagation properties. The circle is a URL that corresponds to the musical baton which is a kind of telephone game on the Internet. It has the

  1. Socratic Questioning-Guided Discovery

    Directory of Open Access Journals (Sweden)

    M. Hakan Türkçapar

    2012-04-01

    Full Text Available “Socratic Method” is a way of teaching philosophical thinking and knowledge by asking questions which was used by antique period greek philosopher Socrates. Socrates was teaching knowledge to his followers by asking questions and the conversation between them was named “Socratic Dialogues”. In this meaning, no novel knowledge is taught to the individual but only what is formerly known is reminded and rediscovered. The form of socratic questioning which is used during the process of cognitive behavioral therapy is known as Guided Discovery. In this method it is aimed to make the client notice the piece of knowledge which he could notice but is not aware with a series of questions. Socratic method or guided discovery consists of several steps which are: Identifying the problem by listening to the client and making reflections, finding alternatives by examining and evaluating, reidentification by using the newly found information and questioning the old distorted belief and reaching to a conclusion and applying it. Question types used during these procedures are, questions for gaining information, questions revealing the meanings, questions revealing the beliefs, questions about behaviours during the similar past experiences, analyse questions and analytic synthesis questions. In order to make the patient feel understood it is important to be empathetic and summarising the problem during the interview. In this text, steps of Socratic Questioning-Guided Discovery will be reviewed with sample dialogues after eachstep. [JCBPR 2012; 1(1.000: 15-20

  2. Pre-Service Teachers' Knowledge of Phonemic Awareness: Relationship to Perceived Knowledge, Self-Efficacy Beliefs, and Exposure to a Multimedia-Enhanced Lecture

    Science.gov (United States)

    Martinussen, Rhonda; Ferrari, Julia; Aitken, Madison; Willows, Dale

    2015-01-01

    This study examined the relations among perceived and actual knowledge of phonemic awareness (PA), exposure to PA instruction during practicum, and self-efficacy for teaching PA in a sample of 54 teacher candidates (TCs) enrolled in a 1-year Bachelor of Education program in a Canadian university. It also assessed the effects of a brief…

  3. A Teacher Action Research Study: Enhancing Student Critical Thinking Knowledge, Skills, Dispositions, Application and Transfer in a Higher Education Technology Course

    Science.gov (United States)

    Phelan, Jack Gordon

    2012-01-01

    This study examined the effects of a critical thinking instructional intervention in a higher education technology course with the purpose of determining the extent to which the intervention enhanced student critical thinking knowledge, skills, dispositions, application and transfer abilities. Historically, critical thinking has been considered…

  4. Causality discovery technology

    Science.gov (United States)

    Chen, M.; Ertl, T.; Jirotka, M.; Trefethen, A.; Schmidt, A.; Coecke, B.; Bañares-Alcántara, R.

    2012-11-01

    Causality is the fabric of our dynamic world. We all make frequent attempts to reason causation relationships of everyday events (e.g., what was the cause of my headache, or what has upset Alice?). We attempt to manage causality all the time through planning and scheduling. The greatest scientific discoveries are usually about causality (e.g., Newton found the cause for an apple to fall, and Darwin discovered natural selection). Meanwhile, we continue to seek a comprehensive understanding about the causes of numerous complex phenomena, such as social divisions, economic crisis, global warming, home-grown terrorism, etc. Humans analyse and reason causality based on observation, experimentation and acquired a priori knowledge. Today's technologies enable us to make observations and carry out experiments in an unprecedented scale that has created data mountains everywhere. Whereas there are exciting opportunities to discover new causation relationships, there are also unparalleled challenges to benefit from such data mountains. In this article, we present a case for developing a new piece of ICT, called Causality Discovery Technology. We reason about the necessity, feasibility and potential impact of such a technology.

  5. A Study of Teacher-Mediated Enhancement of Students' Organization of Earth Science Knowledge Using Web Diagrams as a Teaching Device

    Science.gov (United States)

    Anderson, O. Roger; Contino, Julie

    2010-10-01

    Current research indicates that students with enhanced knowledge networks are more effective in learning science content and applying higher order thinking skills in open-ended inquiry learning. This research examined teacher implementation of a novel teaching strategy called “web diagramming,” a form of network mapping, in a secondary school earth science class. We report evidence for student improvement in knowledge networking, questionnaire-based reports by the students on the merits of web diagramming in terms of interest and usefulness, and information on the collaborating teacher’s perceptions of the process of implementation, including implications for teacher education. This is among the first reports that teachers can be provided with strategies to enhance student knowledge networking capacity, especially for those students whose initial networking scores are among the lowest.

  6. Enhancing health care professionals' and trainees' knowledge of physical activity guidelines for adults with and without SCI.

    Science.gov (United States)

    Shirazipour, Celina H; Tomasone, Jennifer R; Martin Ginis, Kathleen A

    2018-01-11

    Health care providers (HCPs) are preferred sources of physical activity (PA) information; however, minimal research has explored HCPs' knowledge of spinal cord injury (SCI) PA guidelines, and no research has examined HCP trainees' PA guideline knowledge. The current study explored HCPs' and trainees' initial knowledge of PA guidelines for both adults with SCI and the general population, and the utility of an event-based intervention for improving this knowledge. Participants (HCPs n = 129; trainees n = 573) reported guideline knowledge for both sets of guidelines (SCI and general population) immediately after, one-month, and six-months following the intervention. Frequencies determined guideline knowledge at each timepoint, while chi-squared tests examined differences in knowledge of both guidelines, as well as knowledge differences in the short- and long-term. Results demonstrated that HCPs and trainees lack knowledge of PA guidelines, particularly guidelines for adults with SCI. The results further suggest that a single event-based intervention is not effective for improving long-term guideline knowledge. Suggestions are made for future research with the aim of improving interventions that target HCP and HCP trainees' long-term guideline knowledge for adults with SCI and the general population.

  7. Enhance knowledge on sustainable use of plant protection products within the framework of the sustainable use directive.

    Science.gov (United States)

    Calliera, Maura; Berta, Fabio; Galassi, Tiziano; Mazzini, Floriano; Rossi, Rossana; Bassi, Roberto; Meriggi, Pierluigi; Bernard, Alfredo; Marchis, Alex; Di Guardo, Andrea; Capri, Ettore

    2013-08-01

    In 2008-2009, a survey in the Emilia Romagna region of Italy collected information on the farm use of plant protection products (PPPs) and evaluated whether the provisions of the Directive for the Sustainable Use of Pesticides are applicable. It was concluded that the provisions can be implemented, even if some gaps need to be filled and also the behaviour of farmers needs to be improved. Moreover, it was observed that all stages in the use of PPPs on farms could generate risks for the operator and/or the environment. One of the recommendations is to promote training for operators and to adopt good agronomic practices in order to improve sustainable use of PPPs. The findings were used, in the following years, to develop a Guideline for Sustainable Use of PPPs to help the user in identifying the flaws in current practices at farm level as well as their corresponding corrective actions. The Guidelines are accompanied by free online software to be used as a diagnostic tool as well as to provide recommendations for improvements. The approach adopted, taking into account the variability in farm structure, cropping pattern, risk attitude and economic availability, is not an instrument to identify the most suitable protection strategy for a given crop in a given period, but to help professional users to improve their practices in managing PPPs on farms and to make the most appropriate choices leading to reduced environmental and human risk, without compromising the profitability of agricultural production and food standards. This work has, as an underlying principle, a holistic approach to link the different elements of the three pillars of sustainability (environment, economy and society) and to enhance knowledge, which represents one of the main aspects of the Directive. © 2013 Society of Chemical Industry.

  8. “Time for Some Traffic Problems": Enhancing E-Discovery and Big Data Processing Tools with Linguistic Methods for Deception Detection

    Directory of Open Access Journals (Sweden)

    Erin Smith Crabb

    2014-09-01

    Full Text Available Linguistic deception theory provides methods to discover potentially deceptive texts to make them accessible to clerical review. This paper proposes the integration of these linguistic methods with traditional e-discovery techniques to identify deceptive texts within a given author’s larger body of written work, such as their sent email box. First, a set of linguistic features associated with deception are identified and a prototype classifier is constructed to analyze texts and describe the features’ distributions, while avoiding topic-specific features to improve recall of relevant documents. The tool is then applied to a portion of the Enron Email Dataset to illustrate how these strategies identify records, providing an example of its advantages and capability to stratify the large data set at hand.

  9. Resource Discovery within the Networked "Hybrid" Library.

    Science.gov (United States)

    Leigh, Sally-Anne

    This paper focuses on the development, adoption, and integration of resource discovery, knowledge management, and/or knowledge sharing interfaces such as interactive portals, and the use of the library's World Wide Web presence to increase the availability and usability of information services. The introduction addresses changes in library…

  10. Knowledge Management as an Indication of Organizational Maturity in Project Management: An Enhancement of the OPM3(c) Model

    Science.gov (United States)

    Smith, Dedrick A.

    2010-01-01

    This dissertation reviews the knowledge management's role in organizational maturity in project management. It draws a direct linked between organizational maturity knowledge channels both informal and then formal and organizational project management maturity. The study uses a mixed method approach through online and telephone surveys that draws…

  11. Indigenous knowledge management to enhance community resilience to tsunami risk: lessons learned from Smong traditions in Simeulue island, Indonesia

    Science.gov (United States)

    Rahman, A.; Sakurai, A.; Munadi, K.

    2017-02-01

    Knowledge accumulation and production embedded in communities through social interactions meant that the Smong tradition of indigenous knowledge of tsunami risk successfully alerted people to the 2004 tsunami, on the island of Simeulue, in Aceh, Indonesia. Based on this practical example, an indigenous management model was developed for Smong information. This knowledge management method involves the transformation of indigenous knowledge into applicable ways to increase community resilience, including making appropriate decisions and taking action in three disaster phases. First, in the pre-disaster stage, the community needs to be willing to mainstream and integrate indigenous knowledge of disaster risk reduction issues into related activities. Second, during disasters, the Smong tradition should make the community able to think clearly, act based on informed decisions, and protect themselves and others by using their indigenous knowledge. Last, in the post-disaster phase, the community needs to be strong enough to face challenges and support each other and “building back better” efforts, using local resources. The findings for the Smong tradition provide valuable knowledge about community resilience. Primary community resilience to disasters is strongly related to existing knowledge that triggers appropriate decisions and actions during pre-disaster, disaster, and post-disaster phases.

  12. The Development Model of Knowledge Management via Web-Based Learning to Enhance Pre-Service Teacher's Competency

    Science.gov (United States)

    Rampai, Nattaphon; Sopeerak, Saroch

    2011-01-01

    This research explores that the model of knowledge management and web technology for teachers' professional development as well as its impact in the classroom on learning and teaching, especially in pre-service teacher's competency and practices that refer to knowledge creating, analyzing, nurturing, disseminating, and optimizing process as part…

  13. Towards a Framework of Using Knowledge Tools for Teaching by Solving Problems in Technology-Enhanced Learning Environment

    Science.gov (United States)

    Kostousov, Sergei; Kudryavtsev, Dmitry

    2017-01-01

    Problem solving is a critical competency for modern world and also an effective way of learning. Education should not only transfer domain-specific knowledge to students, but also prepare them to solve real-life problems--to apply knowledge from one or several domains within specific situation. Problem solving as teaching tool is known for a long…

  14. Contrast-Enhanced Proton Radiography for Patient Set-up by Using X-Ray CT Prior Knowledge

    Energy Technology Data Exchange (ETDEWEB)

    Spadea, Maria Francesca, E-mail: mfspadea@unicz.it [Department of Experimental and Clinical Medicine, Magna Graecia University, Catanzaro (Italy); Fassi, Aurora [Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano (Italy); Zaffino, Paolo [Department of Experimental and Clinical Medicine, Magna Graecia University, Catanzaro (Italy); Riboldi, Marco; Baroni, Guido [Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano (Italy); Bioengineering Unit—CNAO Foundation, Pavia (Italy); Depauw, Nicolas [Department of Radiation Oncology, Harvard Medical School and Massachusetts General Hospital, Boston, Massachusetts (United States); Centre for Medical Radiation Physics, University of Wollongong, Wollongong (Australia); Seco, Joao [Department of Radiation Oncology, Harvard Medical School and Massachusetts General Hospital, Boston, Massachusetts (United States)

    2014-11-01

    Purpose: To obtain a contrasted image of the tumor region during the setup for proton therapy in lung patients, by using proton radiography and x-ray computed tomography (CT) prior knowledge. Methods and Materials: Six lung cancer patients' CT scans were preprocessed by masking out the gross tumor volume (GTV), and digitally reconstructed radiographs along the planned beam's eye view (BEV) were generated, for a total of 27 projections. Proton radiographies (PR) were also computed for the same BEV through Monte Carlo simulations. The digitally reconstructed radiograph was subtracted from the corresponding proton image, resulting in a contrast-enhanced proton radiography (CEPR). Michelson contrast analysis was performed both on PR and CEPR. The tumor region was then automatically segmented on CEPR and compared to the ground truth (GT) provided by physicians in terms of Dice coefficient, accuracy, precision, sensitivity, and specificity. Results: Contrast on CEPR was, on average, 4 times better than on PR. For 10 lateral projections (±45° off of 90° or 270°), although it was not possible to distinguish the tumor region in the PR, CEPR offers excellent GTV visibility. The median ± quartile values of Dice, precision, and accuracy indexes were 0.86 ± 0.03, 0.86 ± 0.06, and 0.88 ± 0.02, respectively, thus confirming the reliability of the method in highlighting tumor boundaries. Sensitivity and specificity analysis demonstrated that there is no systematic over- or underestimation of the tumor region. Identification of the tumor boundaries using CEPR resulted in a more accurate and precise definition of GTV compared to that obtained from pretreatment CT. Conclusions: In most proton centers, the current clinical protocol is to align the patient using kV imaging with bony anatomy as a reference. We demonstrated that CEPR can significantly improve tumor visualization, allowing better patient set-up and permitting image guided proton therapy (IGPT)

  15. The knowledge-learning-instruction framework: bridging the science-practice chasm to enhance robust student learning.

    Science.gov (United States)

    Koedinger, Kenneth R; Corbett, Albert T; Perfetti, Charles

    2012-07-01

    Despite the accumulation of substantial cognitive science research relevant to education, there remains confusion and controversy in the application of research to educational practice. In support of a more systematic approach, we describe the Knowledge-Learning-Instruction (KLI) framework. KLI promotes the emergence of instructional principles of high potential for generality, while explicitly identifying constraints of and opportunities for detailed analysis of the knowledge students may acquire in courses. Drawing on research across domains of science, math, and language learning, we illustrate the analyses of knowledge, learning, and instructional events that the KLI framework affords. We present a set of three coordinated taxonomies of knowledge, learning, and instruction. For example, we identify three broad classes of learning events (LEs): (a) memory and fluency processes, (b) induction and refinement processes, and (c) understanding and sense-making processes, and we show how these can lead to different knowledge changes and constraints on optimal instructional choices. Copyright © 2012 Cognitive Science Society, Inc.

  16. The limits of de novo DNA motif discovery.

    Directory of Open Access Journals (Sweden)

    David Simcha

    Full Text Available A major challenge in molecular biology is reverse-engineering the cis-regulatory logic that plays a major role in the control of gene expression. This program includes searching through DNA sequences to identify "motifs" that serve as the binding sites for transcription factors or, more generally, are predictive of gene expression across cellular conditions. Several approaches have been proposed for de novo motif discovery-searching sequences without prior knowledge of binding sites or nucleotide patterns. However, unbiased validation is not straightforward. We consider two approaches to unbiased validation of discovered motifs: testing the statistical significance of a motif using a DNA "background" sequence model to represent the null hypothesis and measuring performance in predicting membership in gene clusters. We demonstrate that the background models typically used are "too null," resulting in overly optimistic assessments of significance, and argue that performance in predicting TF binding or expression patterns from DNA motifs should be assessed by held-out data, as in predictive learning. Applying this criterion to common motif discovery methods resulted in universally poor performance, although there is a marked improvement when motifs are statistically significant against real background sequences. Moreover, on synthetic data where "ground truth" is known, discriminative performance of all algorithms is far below the theoretical upper bound, with pronounced "over-fitting" in training. A key conclusion from this work is that the failure of de novo discovery approaches to accurately identify motifs is basically due to statistical intractability resulting from the fixed size of co-regulated gene clusters, and thus such failures do not necessarily provide evidence that unfound motifs are not active biologically. Consequently, the use of prior knowledge to enhance motif discovery is not just advantageous but necessary. An implementation of

  17. Usability of Discovery Portals

    NARCIS (Netherlands)

    Bulens, J.D.; Vullings, L.A.E.; Houtkamp, J.M.; Vanmeulebrouk, B.

    2013-01-01

    As INSPIRE progresses to be implemented in the EU, many new discovery portals are built to facilitate finding spatial data. Currently the structure of the discovery portals is determined by the way spatial data experts like to work. However, we argue that the main target group for discovery portals

  18. Discovery and the atom

    International Nuclear Information System (INIS)

    1989-01-01

    ''Discovery and the Atom'' tells the story of the founding of nuclear physics. This programme looks at nuclear physics up to the discovery of the neutron in 1932. Animation explains the science of the classic experiments, such as the scattering of alpha particles by Rutherford and the discovery of the nucleus. Archive film shows the people: Lord Rutherford, James Chadwick, Marie Curie. (author)

  19. On the threshold of discovery

    International Nuclear Information System (INIS)

    Cherenkov, P.A.

    1986-01-01

    The author, the discoverer of the Cherenkov radiation, recalls some interesting circumstances of his discoery 50 years ago and puts it into the context of the knowledge of the period. The discovery of Cherenkov radiation which today is in practice used especially for the detection of charged particles, was correctly understood and appreciated somewhat belatedly. At first the discovery was met with distrust and the original article announcing it was rejected by the magazine Nature. In effect, the discovery was not the result of any planned experiment but was the by-product of another research. It was, of course, allowed by previous achievements in various fields of physics, namely progress reached in the study of luminescence by S.I. Vavilov and his pupils. The discovery was made during an experimental study of luminescence induced in liquids by the β and γ radiations of uranyl salts. During his attempts to suppress the background radiation from vessel walls the autor found a ''background'' from pure solvent which differed from luminescence by being independent of the concentration, temperature and viscosity of the liquid. A closer examination of the phenomenon more or less by accident revealed its marked spatial asymmetry which had major importance for the development of the theory of the new phenomenon by I.V. Tamm and I.M. Frank. (A.K.)

  20. Identificación de los requisitos del usuario en el sector de la construcción bajo mecanismos de descubrimiento del conocimiento A knowledge discovery mechanism to user requirement identification in building design

    Directory of Open Access Journals (Sweden)

    Fernanda Flach

    2012-08-01

    project well adjusted to the user requirements increase value and causes minors changes during its life cycle. As a consequence, renewal, refurbishments, and demolition are less present, reducing waste generation, reworking and material consumption. It is especially important in housing customization markets. However, one of the challenges faced by designers is frequently concerned about how properly to identify user requirements, wishes and needs, which are on the essence of the briefing phase. In this context, real estate data can be useful to designers, since it reflects the users' evaluation of the building attributes. The research strategy uses a knowledge discovery mechanism, composed by five steps: (1 formulation of a general database; (2 specific data selection using Case-Based Reasoning; (3 enrichment of data-sample; (4 development of hedonic price models using regression analysis; and (5 simulation of the value of design alternatives. Based on an application of an hedonic price model, using data from the medium-class housing market of Porto Alegre, Brazil, the main results indicate that adjusted price models have sufficient detailing and statistical precision to support decisions in the initial stage of design.

  1. Topology Discovery Using Cisco Discovery Protocol

    OpenAIRE

    Rodriguez, Sergio R.

    2009-01-01

    In this paper we address the problem of discovering network topology in proprietary networks. Namely, we investigate topology discovery in Cisco-based networks. Cisco devices run Cisco Discovery Protocol (CDP) which holds information about these devices. We first compare properties of topologies that can be obtained from networks deploying CDP versus Spanning Tree Protocol (STP) and Management Information Base (MIB) Forwarding Database (FDB). Then we describe a method of discovering topology ...

  2. Enhanced knowledge of spontaneous reporting with structured educational programs in Korean community pharmacists: a cross-sectional study.

    Science.gov (United States)

    Yu, Yun Mi; Lee, Euni

    2017-05-30

    While spontaneous reporting (SR) is one of the important public health activities for community pharmacists to guard patients' safety, very few studies examined educational activities and its effects on knowledge about the SR system in Korea. This study described the association between knowledge of SR and educational activities targeting community pharmacists in Korea. Self-administered questionnaires were collected between September 1, 2014 and November 25, 2014. The questionnaires addressed sources of SR knowledge (structured educational programs, personal access to educational resources, and information by social network services) and knowledge about the Regional Pharmacovigilance Center designated for community pharmacists, the legal responsibility clause on the serious event reporting, and the reportable items. The association between the knowledge of SR and the educational activities was evaluated using analysis of variance or chi-squared tests. Overall, 766 questionnaires demonstrated that mean age and length of career in community pharmacies was 45.7 years and 15.9 years, respectively. A structured educational program was used in 63.1% of the participants followed by a personal access to educational resources (56.3%). An educational program offered by the Korean Pharmaceutical Association was the most frequently mentioned program (56.8%), and no regional disparity in the program between the metropolitan and rural areas was observed. Pharmacists who had personal access to educational resources identified SR knowledge contents less correctly than those who used a structured educational program or both (p education (p educational program was used alone or in combination with other educational methods. Knowledge on reportable items should be reinforced during the continuing education process.

  3. Applied metabolomics in drug discovery.

    Science.gov (United States)

    Cuperlovic-Culf, M; Culf, A S

    2016-08-01

    The metabolic profile is a direct signature of phenotype and biochemical activity following any perturbation. Metabolites are small molecules present in a biological system including natural products as well as drugs and their metabolism by-products depending on the biological system studied. Metabolomics can provide activity information about possible novel drugs and drug scaffolds, indicate interesting targets for drug development and suggest binding partners of compounds. Furthermore, metabolomics can be used for the discovery of novel natural products and in drug development. Metabolomics can enhance the discovery and testing of new drugs and provide insight into the on- and off-target effects of drugs. This review focuses primarily on the application of metabolomics in the discovery of active drugs from natural products and the analysis of chemical libraries and the computational analysis of metabolic networks. Metabolomics methodology, both experimental and analytical is fast developing. At the same time, databases of compounds are ever growing with the inclusion of more molecular and spectral information. An increasing number of systems are being represented by very detailed metabolic network models. Combining these experimental and computational tools with high throughput drug testing and drug discovery techniques can provide new promising compounds and leads.

  4. What Do We Need to Know to Enhance the Environmental Sustainability of Agricultural Production? A Prioritisation of Knowledge Needs for the UK Food System

    Directory of Open Access Journals (Sweden)

    William J. Sutherland

    2013-07-01

    Full Text Available Increasing concerns about global environmental change and food security have focused attention on the need for environmentally sustainable agriculture. This is agriculture that makes efficient use of natural resources and does not degrade the environmental systems that underpin it, or deplete natural capital stocks. We convened a group of 29 ‘practitioners’ and 17 environmental scientists with direct involvement or expertise in the environmental sustainability of agriculture. The practitioners included representatives from UK industry, non-government organizations and government agencies. We collaboratively developed a long list of 264 knowledge needs to help enhance the environmental sustainability of agriculture within the UK or for the UK market. We refined and selected the most important knowledge needs through a three-stage process of voting, discussion and scoring. Scientists and practitioners identified similar priorities. We present the 26 highest priority knowledge needs. Many of them demand integration of knowledge from different disciplines to inform policy and practice. The top five are about sustainability of livestock feed, trade-offs between ecosystem services at farm or landscape scale, phosphorus recycling and metrics to measure sustainability. The outcomes will be used to guide on-going knowledge exchange work, future science policy and funding.

  5. Enhancing the quality of oral nutrition support for hospitalized patients: a mixed methods knowledge translation study (The EQONS study).

    Science.gov (United States)

    Gerrish, Kate; Laker, Sara; Taylor, Carolyn; Kennedy, Fiona; McDonnell, Ann

    2016-12-01

    The aim of this study was to report a multifaceted knowledge translation intervention to facilitate use of the Malnutrition Universal Screening Tool and innovation in nutritional care for patients at risk of malnutrition. Malnutrition among hospitalized patients is a widespread problem leading to adverse health outcomes. Despite evidence of the benefits of malnutrition screening and recommendations for achieving good nutrition, shortfalls in practice continue. A mixed method integrated knowledge translation study. The knowledge translation intervention comprised nutrition champions supported by knowledge translation facilitators and an action planning process. Data collection was undertaken over 18 months between 2011-2012 in a hospital in England. Data comprised observation of mealtimes, audit of patient records, survey of nurses and semi-structured interviews with nutrition champions, knowledge translation facilitators, senior ward nurses and nurse managers. Statistically significant relationships (Chi Square) were observed between self-reported confidence of nurses (a) to assess patients using the Malnutrition Universal Screening Tool, (b) to teach colleagues how to use the Malnutrition Universal Screening Tool and (c) to ensure that patients were assessed within 24 hours of admission. Ward-based nutrition champions facilitated successful innovation in nutrition support. Contextual factors operating at micro (ward), meso (organization) and macro (healthcare system) levels acted as barriers and enablers for change. Nutrition champions were successful in increasing the timely assessment of patients at risk of malnutrition and promoting innovation in nutritional care. Support from knowledge translation facilitators helped nutrition champions develop their role and work collaboratively with senior ward nurses to implement action plans for improving nutrition. © 2016 John Wiley & Sons Ltd.

  6. The Role of Research Coordination in Enhancing Integrative Research: the Co-production of Knowledge Agenda of the Global Land Programme

    Science.gov (United States)

    Scarpa, F. M.; Boillat, S. P.; Grove, J. M.

    2015-12-01

    The search for sustainability and resilience requires the integration of natural science with social science, as well as the joint production of knowledge and solutions by science and society. In this context, international science coordination initiatives, like Future Earth, have increasingly stressed the need to perform more integrated and more socially relevant research. This contribution has the objective to highlight the potential role of a research coordination initiative, the Global Land Programme (GLP), to provide guidance for more integrative research. The need to perform integrative research is particularly true for land systems, which include dynamic interactions among social and natural drivers that are often multifunctional. Thus, their governance and management is particularity complex and involve highly diverse stakeholders. A key aspect of integrative research is co-production of knowledge, understood as the interactive production of knowledge by both academics and non-academics, that leads to new forms of solutions-oriented knowledge. We relied on experiences of co-production of knowledge on land systems from the GLP network, and drove seven lessons learnt: 1) the importance of including several learning loops in the process, 2) the importance of long-term relationships, 3) the need to overcome the distinction between basic and applied science, 4) the opportunities offered by new communication technologies, 5) the need to train professionals in both breadth and depth, 6) the access to knowledge, and 7) the need to understand better the roles of scientists and decision-makers. These lessons were used to define action-research priorities for enhancing co-production of knowledge on land systems in GLP projects and working groups. As a conclusion, we argue that research coordination initiatives have the potential to provide analysis and guidance for more integrative research. This can be done by performing synthesis and self-reflection activities that

  7. Structure-based discovery of NANOG variant with enhanced properties to promote self-renewal and reprogramming of pluripotent stem cells.

    Science.gov (United States)

    Hayashi, Yohei; Caboni, Laura; Das, Debanu; Yumoto, Fumiaki; Clayton, Thomas; Deller, Marc C; Nguyen, Phuong; Farr, Carol L; Chiu, Hsiu-Ju; Miller, Mitchell D; Elsliger, Marc-André; Deacon, Ashley M; Godzik, Adam; Lesley, Scott A; Tomoda, Kiichiro; Conklin, Bruce R; Wilson, Ian A; Yamanaka, Shinya; Fletterick, Robert J

    2015-04-14

    NANOG (from Irish mythology Tír na nÓg) transcription factor plays a central role in maintaining pluripotency, cooperating with OCT4 (also known as POU5F1 or OCT3/4), SOX2, and other pluripotency factors. Although the physiological roles of the NANOG protein have been extensively explored, biochemical and biophysical properties in relation to its structural analysis are poorly understood. Here we determined the crystal structure of the human NANOG homeodomain (hNANOG HD) bound to an OCT4 promoter DNA, which revealed amino acid residues involved in DNA recognition that are likely to be functionally important. We generated a series of hNANOG HD alanine substitution mutants based on the protein-DNA interaction and evolutionary conservation and determined their biological activities. Some mutant proteins were less stable, resulting in loss or decreased affinity for DNA binding. Overexpression of the orthologous mouse NANOG (mNANOG) mutants failed to maintain self-renewal of mouse embryonic stem cells without leukemia inhibitory factor. These results suggest that these residues are critical for NANOG transcriptional activity. Interestingly, one mutant, hNANOG L122A, conversely enhanced protein stability and DNA-binding affinity. The mNANOG L122A, when overexpressed in mouse embryonic stem cells, maintained their expression of self-renewal markers even when retinoic acid was added to forcibly drive differentiation. When overexpressed in epiblast stem cells or human induced pluripotent stem cells, the L122A mutants enhanced reprogramming into ground-state pluripotency. These findings demonstrate that structural and biophysical information on key transcriptional factors provides insights into the manipulation of stem cell behaviors and a framework for rational protein engineering.

  8. The Role of Knowledge Sharing in Enhancing Innovation: A Comparative Study of Public and Private Higher Education Institutions in Iraq

    Science.gov (United States)

    Al-Husseini, Sawasn; Elbeltagi, Ibrahim

    2018-01-01

    This paper reports on an examination of the impact of knowledge sharing on product and process innovation. In it we try to identify the similarities and differences between these impacts in public and private Higher Education (HE) Institutions in Iraq. A mixed methods approach was conducted using 486 valid responses to test the causal…

  9. Use of e-learning to enhance medical students' understanding and knowledge of healthcare-associated infection prevention and control.

    LENUS (Irish Health Repository)

    O'Neill, E

    2011-12-01

    An online infection prevention and control programme for medical students was developed and assessed. There was a statistically significant improvement (P<0.0001) in the knowledge base among 517 students after completing two modules. The majority of students who completed the evaluation were positive about the learning experience.

  10. Enhancing Student Learning in Knowledge-Based Courses: Integrating Team-Based Learning in Mass Communication Theory Classes

    Science.gov (United States)

    Han, Gang; Newell, Jay

    2014-01-01

    This study explores the adoption of the team-based learning (TBL) method in knowledge-based and theory-oriented journalism and mass communication (J&MC) courses. It first reviews the origin and concept of TBL, the relevant theories, and then introduces the TBL method and implementation, including procedures and assessments, employed in an…

  11. Automated discovery systems and the inductivist controversy

    Science.gov (United States)

    Giza, Piotr

    2017-09-01

    The paper explores possible influences that some developments in the field of branches of AI, called automated discovery and machine learning systems, might have upon some aspects of the old debate between Francis Bacon's inductivism and Karl Popper's falsificationism. Donald Gillies facetiously calls this controversy 'the duel of two English knights', and claims, after some analysis of historical cases of discovery, that Baconian induction had been used in science very rarely, or not at all, although he argues that the situation has changed with the advent of machine learning systems. (Some clarification of terms machine learning and automated discovery is required here. The key idea of machine learning is that, given data with associated outcomes, software can be trained to make those associations in future cases which typically amounts to inducing some rules from individual cases classified by the experts. Automated discovery (also called machine discovery) deals with uncovering new knowledge that is valuable for human beings, and its key idea is that discovery is like other intellectual tasks and that the general idea of heuristic search in problem spaces applies also to discovery tasks. However, since machine learning systems discover (very low-level) regularities in data, throughout this paper I use the generic term automated discovery for both kinds of systems. I will elaborate on this later on). Gillies's line of argument can be generalised: thanks to automated discovery systems, philosophers of science have at their disposal a new tool for empirically testing their philosophical hypotheses. Accordingly, in the paper, I will address the question, which of the two philosophical conceptions of scientific method is better vindicated in view of the successes and failures of systems developed within three major research programmes in the field: machine learning systems in the Turing tradition, normative theory of scientific discovery formulated by Herbert Simon

  12. SETIA Health Education Set Enhances Knowledge, Attitude, and Parenting Self-Efficacy Score in Postpartum Adolescent Mothers.

    Science.gov (United States)

    Setiawati, Nina; Setyowati; Budiati, Tri

    The lack of readiness in assuming the role of a mother causes many adolescent mothers to decide not to breastfeed their babies. This study was conducted to assess the effect of the SETIA health education set on adolescent mothers' knowledge, attitude, and parenting self-efficacy score. This quasi-experimental pre-test-post-test with control group study was conducted on 66 adolescent mothers, 33 participants in each group. Data collecting used knowledge and attitude questionnaires and the Parenting Self-Efficacy Scale (PSES). This study revealed that there was a significant difference before and after intervention in knowledge, attitude, and PSE score on postpartum adolescent mothers (p = .045; p = .013; p = .001 respectively). There was an increase in knowledge ≥ 20%, attitude ≥10%, parental self-efficacy ≥ 10%, and a difference between control and intervention group (p = .001 with 95% CI: 3.587-44.876, p = .001 with 95% CI: 4.954-56.397, p = .001 respectively). Logistic regression analysis found that postpartum adolescent mothers who receive SETIA are 12.687 times more likely to have better knowledge after being controlled for mother's age and education and 0.248 times more likely to have a higher PSES score after being controlled for mother's age, education, and husband's work status than their counterpart. This study recommends the use of the SETIA health education set to provide postpartum education to adolescent mothers.

  13. Personal discovery in diabetes self-management: Discovering cause and effect using self-monitoring data.

    Science.gov (United States)

    Mamykina, Lena; Heitkemper, Elizabeth M; Smaldone, Arlene M; Kukafka, Rita; Cole-Lewis, Heather J; Davidson, Patricia G; Mynatt, Elizabeth D; Cassells, Andrea; Tobin, Jonathan N; Hripcsak, George

    2017-12-01

    To outline new design directions for informatics solutions that facilitate personal discovery with self-monitoring data. We investigate this question in the context of chronic disease self-management with the focus on type 2 diabetes. We conducted an observational qualitative study of discovery with personal data among adults attending a diabetes self-management education (DSME) program that utilized a discovery-based curriculum. The study included observations of class sessions, and interviews and focus groups with the educator and attendees of the program (n = 14). The main discovery in diabetes self-management evolved around discovering patterns of association between characteristics of individuals' activities and changes in their blood glucose levels that the participants referred to as "cause and effect". This discovery empowered individuals to actively engage in self-management and provided a desired flexibility in selection of personalized self-management strategies. We show that discovery of cause and effect involves four essential phases: (1) feature selection, (2) hypothesis generation, (3) feature evaluation, and (4) goal specification. Further, we identify opportunities to support discovery at each stage with informatics and data visualization solutions by providing assistance with: (1) active manipulation of collected data (e.g., grouping, filtering and side-by-side inspection), (2) hypotheses formulation (e.g., using natural language statements or constructing visual queries), (3) inference evaluation (e.g., through aggregation and visual comparison, and statistical analysis of associations), and (4) translation of discoveries into actionable goals (e.g., tailored selection from computable knowledge sources of effective diabetes self-management behaviors). The study suggests that discovery of cause and effect in diabetes can be a powerful approach to helping individuals to improve their self-management strategies, and that self-monitoring data can

  14. Guided Discovery with Socratic Questioning

    Directory of Open Access Journals (Sweden)

    M. Hakan Türkçapar

    2015-04-01

    Full Text Available “The Socratic method” is a way of teaching philosophical thinking and knowledge by asking questions. It was first used by in ancient times by the Greek philosopher Socrates who taught his followers by asking questions; these conversations between them are known as “Socratic dialogues”. In this methodology, no new knowledge is taught to the individual; rather, the individual is guided to remember and rediscover what was formerly known through this process. The main method used in cognitive therapy is guided discovery. There are various methods of guided discovery in cognitive therapy. The form of verbal exchange between the therapist and client which is used during the process of cognitive behavioral therapy is known as “socratic questioning”. In this method the goal is to make the client rediscover, with a series of questions, a piece of knowledge which he could otherwise know but is not presently conscious of. The Socratic Questioning consists of several steps, including: identifying the problem by listening to the client and making reflections, finding alternatives by examining and evaluating, reidentification by using the newly rediscovered information and questioning the old distorted belief, and reaching a new conclusion and applying it. Question types used during these procedures are: questions for collecting information, questions revealing meanings, questions revealing beliefs, questions about behaviours during similar past experiences, analytic questions and analytic synthesis questions. In order to make the patient feel understood, it is important to be empathetic and summarize the problem during the interview. In this text, steps of Socratic Questioning-Guided Discovery will be reviewed with sample dialogues provided for each step. [JCBPR 2015; 4(1.000: 47-53

  15. Impact of educational outreach intervention on enhancing health care providers' knowledge about statin therapy prescribing in Malaysian patients with type 2 diabetes mellitus.

    Science.gov (United States)

    Elnaem, Mohamed Hassan; Nik Mohamed, Mohamad Haniki; Zaman Huri, Hasniza; Azarisman, Shah M

    2018-03-06

    Previous research reported underutilization of statin therapy among patients with type 2 diabetes mellitus. Improving health care providers' awareness and understanding of the benefits and risks of statin treatment could be of assistance in optimizing the statin prescribing process. This study aimed to assess health care providers' knowledge related to statin therapy and the impact of educational outreach intervention based on the perceived knowledge. This was a cross-sectional study based on educational outreach intervention targeting physicians and pharmacists in 1 major tertiary hospital in the state of Pahang, Malaysia. Participants responded to a 12-item, validated questionnaire both prior to and after the outreach educational program. Two sessions were conducted separately for 2 cohorts of pharmacists and physicians. The knowledge scores prior to and after the educational intervention were calculated and compared using a paired-samples t-test. The response rate to both pre-and post-educational outreach questionnaires was 91% (40/44). Prior to the intervention, around 84% (n37) of the participants decided to initiate statin therapy for both pre-assessment clinical case scenarios; however, only 27% (n12) could state the clinical benefits of statin therapy. Forty-five percent (n20) could state the drug to drug interactions, and 52.3% (n23) could identify the statin therapy that can be given at any time day/evening. The educational outreach program increased participants' knowledge scores of 1.450 (95% CI, 0.918 to 1.982) point, P health care providers' knowledge and beliefs about statin therapy. This type of intervention is considered effective for short-term knowledge enhancement. Further research is needed to test the long-term efficacy of such intervention. © 2018 John Wiley & Sons, Ltd.

  16. Scaring Them into Learning!? Using a Snake Screen to Enhance the Knowledge Transfer Effectiveness of a Web Interface

    Science.gov (United States)

    Kock, Ned; Chatelain-Jardón, Ruth; Carmona, Jesus

    2009-01-01

    It seems that surprise events have the potential to turn short-term memories into long-term memories, an unusual phenomenon that may have limited but interesting applications in learning tasks. This surprise-enhanced cognition phenomenon is theoretically modeled based on the notion that many human mental traits have evolved through natural…

  17. Motivational interviewing-based training enhances clinicians' skills and knowledge in psoriasis: findings from the Pso Well® study.

    Science.gov (United States)

    Chisholm, A; Nelson, P A; Pearce, C J; Littlewood, A J; Kane, K; Henry, A L; Thorneloe, R; Hamilton, M P; Lavallee, J; Lunt, M; Griffiths, C E M; Cordingley, L; Bundy, C

    2017-03-01

    Psoriasis is a common long-term, immune-mediated skin condition associated with behavioural factors (e.g. smoking, excess alcohol, obesity), which increase the risk of psoriasis onset, flares and comorbidities. Motivational interviewing (MI) is an evidence-based approach to health-related behaviour change that has been used successfully for patients with long-term conditions. This study assessed change in clinicians' MI skills and psoriasis knowledge following Psoriasis and Wellbeing (Pso Well ® ) training. To investigate whether the Pso Well training intervention improves clinicians' MI skills and knowledge about psoriasis-related comorbidities and risk factors; and to explore the acceptability and feasibility of the Pso Well training content, delivery and evaluation. Clinicians attended the 1-day training programme focused on MI skills development in the context of psoriasis. MI skills were assessed pre- and post-training using the Behaviour Change Counselling Index. Knowledge about psoriasis-related comorbidity and risk factors was assessed with a novel 22-point measure developed for the study. Interviews with clinicians were analysed qualitatively to identify perceptions about the feasibility and acceptability of the training. Sixty-one clinicians completed the training (35 dermatology nurses, 23 dermatologists and three primary-care clinicians). Clinicians' MI skills (P skills to manage psoriasis holistically. Clinicians deemed the training itself and the assessment procedures used both feasible and acceptable. Future research should investigate how this training may influence patient outcomes. © 2016 British Association of Dermatologists.

  18. Enhanced

    Directory of Open Access Journals (Sweden)

    Martin I. Bayala

    2014-06-01

    Full Text Available Land Surface Temperature (LST is a key parameter in the energy balance model. However, the spatial resolution of the retrieved LST from sensors with high temporal resolution is not accurate enough to be used in local-scale studies. To explore the LST–Normalised Difference Vegetation Index relationship potential and obtain thermal images with high spatial resolution, six enhanced image sharpening techniques were assessed: the disaggregation procedure for radiometric surface temperatures (TsHARP, the Dry Edge Quadratic Function, the Difference of Edges (Ts∗DL and three models supported by the relationship of surface temperature and water stress of vegetation (Normalised Difference Water Index, Normalised Difference Infrared Index and Soil wetness index. Energy Balance Station data and in situ measurements were used to validate the enhanced LST images over a mixed agricultural landscape in the sub-humid Pampean Region of Argentina (PRA, during 2006–2010. Landsat Thematic Mapper (TM and Moderate Resolution Imaging Spectroradiometer (EOS-MODIS thermal datasets were assessed for different spatial resolutions (e.g., 960, 720 and 240 m and the performances were compared with global and local TsHARP procedures. Results suggest that the Ts∗DL technique is the most adequate for simulating LST to high spatial resolution over the heterogeneous landscape of a sub-humid region, showing an average root mean square error of less than 1 K.

  19. Driver education: Enhancing knowledge of sleep, fatigue and risky behaviour to improve decision making in young drivers.

    Science.gov (United States)

    Alvaro, Pasquale K; Burnett, Nicole M; Kennedy, Gerard A; Min, William Yu Xun; McMahon, Marcus; Barnes, Maree; Jackson, Melinda; Howard, Mark E

    2018-03-01

    This study assessed the impact of an education program on knowledge of sleepiness and driving behaviour in young adult drivers and their performance and behaviour during simulated night driving. Thirty-four participants (18-26 years old) were randomized to receive either a four-week education program about sleep and driving or a control condition. A series of questionnaires were administered to assess knowledge of factors affecting sleep and driving before and after the four-week education program. Participants also completed a two hour driving simulator task at 1am after 17 h of extended wakefulness to assess the impact on driving behaviour. There was an increase in circadian rhythm knowledge in the intervention group following the education program. Self-reported risky behaviour increased in the control group with no changes in other aspects of sleep knowledge. There were no significant differences in proportion of intervention and control participants who had microsleeps (p ≤ .096), stopped driving due to sleepiness (p = .107), recorded objective episodes of drowsiness (p = .455), and crashed (p = .761), although there was a trend towards more control participants having microsleeps and stopping driving. Those in the intervention group reported higher subjective sleepiness at the end of the drive [M = 6.25, SD = 3.83, t(31) = 2.15, p = .05] and were more likely to indicate that they would stop driving [M = 3.08, SD = 1.16, t(31) = 2.24, p = .04]. The education program improved some aspects of driver knowledge about sleep and safety. The results also suggested that the education program lead to an increased awareness of sleepiness. Education about sleep and driving could reduce the risk of drowsy driving and associated road trauma in young drivers, but requires evaluation in a broader sample with assessment of real world driving outcomes. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Knowledge Exchange and Discovery in the Age of Social Media: The Journey From Inception to Establishment of a Parent-Led Web-Based Research Advisory Community for Childhood Disability.

    Science.gov (United States)

    Russell, Dianne J; Sprung, Jennifer; McCauley, Dayle; Kraus de Camargo, Olaf; Buchanan, Francine; Gulko, Roman; Martens, Rachel; Gorter, Jan Willem

    2016-11-11

    Efforts to involve parents and families in all aspects of research, from initiating the question through to dissemination and knowledge exchange, are increasing. While social media as a method for health communication has shown numerous benefits, including increasing accessibility, interactions with others, and access to health care information, little work has been published on the use of social media to enhance research partnerships. Our objective was to describe the development and evaluation of a Web-based research advisory community, hosted on Facebook and connecting a diverse group of parents of special needs children with researchers at CanChild Centre for Childhood Disability Research. The goal of this community is to work together and exchange knowledge in order to improve research and the lives of children and their families. The Web-based Parents Participating in Research (PPR) advisory community was a secret Facebook group launched in June 2014 and run by 2 parent moderators who worked in consultation with CanChild. We evaluated its success using Facebook statistics of engagement and activity (eg, number of posts, number of comments) between June 2014 and April 2015, and a Web-based survey of members. The PPR community had 96 participants (2 parent moderators, 13 researchers, and 81 family members) as of April 1, 2015. Over 9 months, 432 original posts were made: 155 (35.9%) by moderators, 197 (45.6%) by parents, and 80 (18.5%) by researchers. Posts had a median of 3 likes (range 0-24) and 4 comments (range 0-113). Members, rather than moderators, generated 64% (277/432) of posts. The survey had a 51% response rate (49/96 members), with 40 (82%) being parent members and 9 (18%) being researchers. The initial purpose of the group was to be an advisory to CanChild, and 76% (28/37) of parents and all the researchers (9/9) identified having an impact on childhood disability research as their reason for participating. A total of 58% (23/40) of parents and 56

  1. A New Universe of Discoveries

    Science.gov (United States)

    Córdova, France A.

    2016-01-01

    The convergence of emerging advances in astronomical instruments, computational capabilities and talented practitioners (both professional and civilian) is creating an extraordinary new environment for making numerous fundamental discoveries in astronomy, ranging from the nature of exoplanets to understanding the evolution of solar systems and galaxies. The National Science Foundation is playing a critical role in supporting, stimulating, and shaping these advances. NSF is more than an agency of government or a funding mechanism for the infrastructure of science. The work of NSF is a sacred trust that every generation of Americans makes to those of the next generation, that we will build on the body of knowledge we inherit and continue to push forward the frontiers of science. We never lose sight of NSF's obligation to "explore the unexplored" and inspire all of humanity with the wonders of discovery. As the only Federal agency dedicated to the support of basic research and education in all fields of science and engineering, NSF has empowered discoveries across a broad spectrum of scientific inquiry for more than six decades. The result is fundamental scientific research that has had a profound impact on our nation's innovation ecosystem and kept our nation at the very forefront of the world's science-and-engineering enterprise.

  2. Competency-based residency training and the web log: modeling practice-based learning and enhancing medical knowledge

    Directory of Open Access Journals (Sweden)

    Matthew F. Hollon

    2015-12-01

    Full Text Available Background: By using web-based tools in medical education, there are opportunities to innovatively teach important principles from the general competencies of graduate medical education. Objectives: Postulating that faculty transparency in learning from uncertainties in clinical work could help residents to incorporate the principles of practice-based learning and improvement (PBLI in their professional development, faculty in this community-based residency program modeled the steps of PBLI on a weekly basis through the use of a web log. Method: The program confidentially surveyed residents before and after this project about actions consistent with PBLI and knowledge acquired through reading the web log. Results: The frequency that residents encountered clinical situations where they felt uncertain declined over the course of the 24 weeks of the project from a mean frequency of uncertainty of 36% to 28% (Wilcoxon signed rank test, p=0.008; however, the frequency with which residents sought answers when faced with uncertainty did not change (Wilcoxon signed rank test, p=0.39, remaining high at approximately 80%. Residents answered a mean of 52% of knowledge questions correct when tested prior to faculty posts to the blog, rising to a mean of 65% of questions correct when tested at the end of the project (paired t-test, p=0.001. Conclusions: Faculty role modeling of PBLI behaviors and posting clinical questions and answers to a web log led to modest improvements in medical knowledge but did not alter behavior that was already taking place frequently among residents.

  3. Household attitudes and knowledge on drinking water enhance water hazards in peri-urban communities in Western Kenya

    Directory of Open Access Journals (Sweden)

    Kimongu J. Kioko

    2012-12-01

    Full Text Available Ensuring safe drinking water remains a big challenge in developing countries where waterborne diseases cause havoc in many communities. A major challenge is limited knowledge, misinformation and attitudes that work against ensuring that drinking water is safe. This study investigated the knowledge, attitudes and practices of peri-urban households in Kakamega Town of Western Kenya, concerning the collection, treatment and storage of drinking water. Alongside this we examined the role of solid waste disposal in water safety. Three hundred and seventy eight households from four residential regions of varying economic levels were randomly sampled in Kakamega Town. Data was collected via questionnaire interviews that incorporated attitude questions based on a Likert scale of 1−5, and administered to the households and key informants. The results showed most respondents were knowledgeable about ideal methods of water collection, treatment and storage. However, they did not practise them appropriately. Some attitudes among the respondents worked against the ideals of achieving safe drinking water. For instance, many households perceived their drinking water source as safe and did not treat it, even when obtained from open sources like rivers. Further, they preferred to store drinking water in clay pots, because the pots kept the water cold, rather than use the narrow-necked containers that limit exposure to contaminants. Also, hand washing with soap was not practised enough in their daily lives to avoid contact with waterborne hazards. We recommend that the government undertake training programmes on drinking water safety that advocate appropriate water use, hygiene and sanitation strategies.

  4. Service Discovery At Home

    NARCIS (Netherlands)

    Sundramoorthy, V.; Scholten, Johan; Jansen, P.G.; Hartel, Pieter H.

    Service discovery is a fady new field that kicked off since the advent of ubiquitous computing and has been found essential in the making of intelligent networks by implementing automated discovery and remote control between deviies. This paper provides an ovewiew and comparison of several prominent

  5. Academic Drug Discovery Centres

    DEFF Research Database (Denmark)

    Kirkegaard, Henriette Schultz; Valentin, Finn

    2014-01-01

    Academic drug discovery centres (ADDCs) are seen as one of the solutions to fill the innovation gap in early drug discovery, which has proven challenging for previous organisational models. Prior studies of ADDCs have identified the need to analyse them from the angle of their economic...

  6. Decades of Discovery

    Science.gov (United States)

    2011-06-01

    For the past two-and-a-half decades, the Office of Science at the U.S. Department of Energy has been at the forefront of scientific discovery. Over 100 important discoveries supported by the Office of Science are represented in this document.

  7. Service discovery at home

    NARCIS (Netherlands)

    Sundramoorthy, V.; Scholten, Johan; Jansen, P.G.; Hartel, Pieter H.

    2003-01-01

    Service discovery is a fairly new field that kicked off since the advent of ubiquitous computing and has been found essential in the making of intelligent networks by implementing automated discovery and remote control between devices. This paper provides an overview and comparison of several

  8. Research on an Agricultural Knowledge Fusion Method for Big Data

    Directory of Open Access Journals (Sweden)

    Nengfu Xie

    2015-05-01

    Full Text Available The object of our research is to develop an ontology-based agricultural knowledge fusion method that can be used as a comprehensive basis on which to solve agricultural information inconsistencies, analyze data, and discover new knowledge. A recent survey has provided a detailed comparison of various fusion methods used with Deep Web data (Li, 2013. In this paper, we propose an effective agricultural ontology-based knowledge fusion method by leveraging recent advances in data fusion, such as the semantic web and big data technologies, that will enhance the identification and fusion of new and existing data sets to make big data analytics more possible. We provide a detailed fusion method that includes agricultural ontology building, fusion rule construction, an evaluation module, etc. Empirical results show that this knowledge fusion method is useful for knowledge discovery.

  9. Enhancing community knowledge and health behaviors to eliminate blinding trachoma in Mali using radio messaging as a strategy.

    Science.gov (United States)

    Bamani, Sanoussi; Toubali, Emily; Diarra, Sadio; Goita, Seydou; Berté, Zana; Coulibaly, Famolo; Sangaré, Hama; Tuinsma, Marjon; Zhang, Yaobi; Dembelé, Benoit; Melvin, Palesa; MacArthur, Chad

    2013-04-01

    The National Blindness Prevention Program in Mali has broadcast messages on the radio about trachoma as part of the country's trachoma elimination strategy since 2008. In 2011, a radio impact survey using multi-stage cluster sampling was conducted in the regions of Kayes and Segou to assess radio listening habits, coverage of the broadcasts, community knowledge and behavior specific to trachoma and facial cleanliness of children. Radio access and listening were high, with 60% of respondents having heard a message on the radio about trachoma. The majority of respondents knew about trachoma, its root causes, its impact on health and prevention measures. Additionally, 66% reported washing their children's faces more than or equal to twice/day and 94% reported latrine disposal of feces. A high percentage of persons who gave a positive response to knowledge and behavior questions reported hearing the trachoma messages on the radio with 60% reporting that the radio is where they learned about trachoma. There was no significant difference in facial cleanliness when comparing children whose primary caregiver had/had not heard the trachoma messages. Next steps include revising the current messages to include more focused behavior change messaging and to engage in a more robust use of community radios.

  10. Building Scalable Knowledge Graphs for Earth Science

    Science.gov (United States)

    Ramachandran, Rahul; Maskey, Manil; Gatlin, Patrick; Zhang, Jia; Duan, Xiaoyi; Miller, J. J.; Bugbee, Kaylin; Christopher, Sundar; Freitag, Brian

    2017-01-01

    Knowledge Graphs link key entities in a specific domain with other entities via relationships. From these relationships, researchers can query knowledge graphs for probabilistic recommendations to infer new knowledge. Scientific papers are an untapped resource which knowledge graphs could leverage to accelerate research discovery. Goal: Develop an end-to-end (semi) automated methodology for constructing Knowledge Graphs for Earth Science.

  11. "Eureka, Eureka!" Discoveries in Science

    Science.gov (United States)

    Agarwal, Pankaj

    2011-01-01

    Accidental discoveries have been of significant value in the progress of science. Although accidental discoveries are more common in pharmacology and chemistry, other branches of science have also benefited from such discoveries. While most discoveries are the result of persistent research, famous accidental discoveries provide a fascinating…

  12. How Use of knowledge, Skills and Cognition Enhance Board Performance in Nigerian market: A SEM-Approach

    Directory of Open Access Journals (Sweden)

    Bashir Mande

    2013-09-01

    Full Text Available This research aims to take steps towards explaining behavioral principle-based board process as factors for effective board performance. Dominant rule-based board structure approach could not transform effective corporate functioning, thus inconclusive. Based on a survey perception of 154 respondents from Nigerian capital market participants, the study employs confirmatory factor analysis (CFA in a structural equation modeling (SEM approach. Other studies used EFA and in developed nations. Replicates and builds upon board process constructs - cognitive conflict, effort norms, use of knowledge and skills, and groupthink. The study concludes that the items are valid measures of the latent constructs and significantly relate to board performance. The paper links corporate governance debates to broader behavioral choices in agency perspective and employs CFA and SEM as alternative approach for the measurement and structural models, in place of the usual exploratory factor analysis (EFA.

  13. Using concepts in literature-based discovery : Simulating Swanson's Raynaud-fish oil and migraine-magnesium discoveries

    NARCIS (Netherlands)

    Weeber, M; Klein, Henny; de Jong-van den Berg, LTW; Vos, R

    Literature-based discovery has resulted in new knowledge. In the biomedical context, Don R. Swanson has generated several literature-based hypotheses that have been corroborated experimentally and clinically. In this paper, we propose a two-step model of the discovery process in which hypotheses are

  14. Birds in the playground: Evaluating the effectiveness of an urban environmental education project in enhancing school children’s awareness, knowledge and attitudes towards local wildlife

    Science.gov (United States)

    Eberstein, Katie; Scott, Dawn M.

    2018-01-01

    Children nowadays, particularly in urban areas, are more disconnected from nature than ever before, leading to a large-scale “extinction of experience” with the natural world. Yet there are many potential benefits from children interacting with nature first-hand, including via outdoor learning opportunities. Urban environmental education programmes typically aim to increase awareness and knowledge of local biodiversity and to promote positive attitudes and behaviour towards the environment. However, limited research has been conducted evaluating to what extent these interventions achieve their goals. Here, we explore and assess the influence of a six-week bird-feeding and monitoring project conducted within school grounds (“Bird Buddies”) on individual awareness, knowledge and attitudes towards birds by primary school children. This initiative was conducted across eight (sub-)urban primary schools within Brighton and Hove (UK), with 220 participating children (aged 7 to 10). Via pre- and post-project questionnaires, we found evidence for enhanced awareness of local biodiversity, alongside significant gains in both bird identification knowledge and attitudes, which were greatest for children with little prior exposure to nature. Many children expressed a keenness to continue improving the environmental value of their school grounds and to apply elements of the project at home. Student project evaluation scores were consistently positive. Mirroring this, participating teachers endorsed the project as a positive learning experience for their students. One year after the project, several schools were continuing to feed and watch birds. Collectively, the findings from this study highlight the multiple benefits that can be derived from engagement with a relatively short outdoor environmental activity. We therefore believe that such interventions, if repeated locally/longer term, could enhance children’s experience with nature in urban settings with combined

  15. Birds in the playground: Evaluating the effectiveness of an urban environmental education project in enhancing school children's awareness, knowledge and attitudes towards local wildlife.

    Science.gov (United States)

    White, Rachel L; Eberstein, Katie; Scott, Dawn M

    2018-01-01

    Children nowadays, particularly in urban areas, are more disconnected from nature than ever before, leading to a large-scale "extinction of experience" with the natural world. Yet there are many potential benefits from children interacting with nature first-hand, including via outdoor learning opportunities. Urban environmental education programmes typically aim to increase awareness and knowledge of local biodiversity and to promote positive attitudes and behaviour towards the environment. However, limited research has been conducted evaluating to what extent these interventions achieve their goals. Here, we explore and assess the influence of a six-week bird-feeding and monitoring project conducted within school grounds ("Bird Buddies") on individual awareness, knowledge and attitudes towards birds by primary school children. This initiative was conducted across eight (sub-)urban primary schools within Brighton and Hove (UK), with 220 participating children (aged 7 to 10). Via pre- and post-project questionnaires, we found evidence for enhanced awareness of local biodiversity, alongside significant gains in both bird identification knowledge and attitudes, which were greatest for children with little prior exposure to nature. Many children expressed a keenness to continue improving the environmental value of their school grounds and to apply elements of the project at home. Student project evaluation scores were consistently positive. Mirroring this, participating teachers endorsed the project as a positive learning experience for their students. One year after the project, several schools were continuing to feed and watch birds. Collectively, the findings from this study highlight the multiple benefits that can be derived from engagement with a relatively short outdoor environmental activity. We therefore believe that such interventions, if repeated locally/longer term, could enhance children's experience with nature in urban settings with combined positive

  16. Predicting future discoveries from current scientific literature.

    Science.gov (United States)

    Petrič, Ingrid; Cestnik, Bojan

    2014-01-01

    Knowledge discovery in biomedicine is a time-consuming process starting from the basic research, through preclinical testing, towards possible clinical applications. Crossing of conceptual boundaries is often needed for groundbreaking biomedical research that generates highly inventive discoveries. We demonstrate the ability of a creative literature mining method to advance valuable new discoveries based on rare ideas from existing literature. When emerging ideas from scientific literature are put together as fragments of knowledge in a systematic way, they may lead to original, sometimes surprising, research findings. If enough scientific evidence is already published for the association of such findings, they can be considered as scientific hypotheses. In this chapter, we describe a method for the computer-aided generation of such hypotheses based on the existing scientific literature. Our literature-based discovery of NF-kappaB with its possible connections to autism was recently approved by scientific community, which confirms the ability of our literature mining methodology to accelerate future discoveries based on rare ideas from existing literature.

  17. The hydroelectric power plant of the Widemann cotton mill (San Germano Chisone, Turin: perspectives of knowledge, conservation and enhancement.

    Directory of Open Access Journals (Sweden)

    Riccardo Rudiero

    2017-12-01

    Full Text Available Alpine valleys Pellice, Chisone and Germanasca, at whose feet lies the town of Pinerolo (TO, were among the first most industrialized areas of the Savoy state, vocation still spotted in the wide network of material evidences, such as production complexes, social facilities built for the working class, water channeling, electrification system. About the latter, there are still many active structures in the production of electricity. Some of them are dismantling, others are in operation, others are in the process of being transformed. This contribution will be focused on the case of the hydroelectric power plant of Widemann cotton mill in San Germano Chisone (TO, where the analysis of the existing structures and a diachronic reading of the archive documents has allowed to reconstruct its history and has provided the basis for some suggestions related to its conservation and enhancement.

  18. The Greatest Mathematical Discovery?

    Energy Technology Data Exchange (ETDEWEB)

    Bailey, David H.; Borwein, Jonathan M.

    2010-05-12

    What mathematical discovery more than 1500 years ago: (1) Is one of the greatest, if not the greatest, single discovery in the field of mathematics? (2) Involved three subtle ideas that eluded the greatest minds of antiquity, even geniuses such as Archimedes? (3) Was fiercely resisted in Europe for hundreds of years after its discovery? (4) Even today, in historical treatments of mathematics, is often dismissed with scant mention, or else is ascribed to the wrong source? Answer: Our modern system of positional decimal notation with zero, together with the basic arithmetic computational schemes, which were discovered in India about 500 CE.

  19. Preservation and enhancement of nuclear knowledge towards Indonesia's plan to operate first nuclear power plant by 2016

    International Nuclear Information System (INIS)

    Ardisasmita, M.S.

    2004-01-01

    non-governmental organizations that have their own agenda. Therefore the public information has to be intensified in line with the dissemination of proven nuclear technology application activities already carried out for couple years in various provinces together with various research and development institutes and local governments, universities, private companies, and non-governmental organizations. The Batan nuclear workforce is aging - that is, more and more nuclear workers are approaching retirement age, without a corresponding influx of appropriately qualified younger personnel to replace them. This situation happens due to zero growth policy in government employment or more precisely negative growth policy on Batan employment. Between years 2000 and 2004, from 3704 Batan employees there are 280 retired or quitting Batan, but only 108 recruitments of newer employees have been accepted. The statistic shows a significant brain-drain flow from government research institutes to the private sectors and industrial countries. The establishment and maintenance of a formal human resources policy and nuclear knowledge management strategies are important to ensure that an organization maintains adequate numbers of competent and motivated personnel, and the availability of essential technical information (explicit knowledge) in the form of scientific research, engineering analysis, design documentation, operational data, maintenance records, regulatory reviews, and other documents and data to achieve the organization's mission. Human resources development for the design, construction, installation and safe operation of the NPP's should be inseparable from the package in the procurement of the NPP's. Polytechnic Institute of Nuclear Technology, as an educational institute under Batan, was inaugurated in August 2001. The main objective of the institute is to provide education and training facilities to support human resource development program in nuclear science and

  20. Scientific Discoveries the Year I Was Born

    Science.gov (United States)

    Cherif, Abour

    2012-01-01

    The author has successfully used a learning activity titled "The Year I Was Born" to motivate students to conduct historical research and present key scientific discoveries from their birth year. The activity promotes writing, helps students enhance their scientific literacy, and also improves their attitude toward the learning of science. As one…

  1. Enhancing discovery and saving money with MERIT.

    Science.gov (United States)

    Epstein, Jonathan A

    2011-04-01

    The National Institutes of Health and many of our biomedical institutions face significant budgetary challenges that are likely to persist for the foreseeable future. The paylines for Research Project Grant (RO1) applications to the NIH will be near or below the tenth percentile, and many investigators are growing increasingly concerned about maintaining their research programs. One of the most concerning potential results of limited grant dollars is the natural tendency for researchers to propose conservative projects that are more likely to succeed, to do well in peer review, and to be funded, but that may not dramatically advance the field, and a concurrent tendency among study sections to reward proposals that are seen as safe, if uninspiring. Established and well-respected investigators may be (perhaps appropriately) given the benefit of the doubt when compared with less-established colleagues and may therefore command a growing percentage of the total available grant dollars, while simultaneously avoiding bold and potentially groundbreaking approaches. At the same time, fewer dollars are available for new investigators with unproven track records and for the expansion of newly successful programs.

  2. Methods of Academic Course Planning for Cancer Biology PhD Students to Enhance Knowledge of Clinical Oncology.

    Science.gov (United States)

    Mattes, Malcolm D; Swart, Elizabeth; Markwell, Steven M; Wen, Sijin; Vona-Davis, Linda C

    2017-09-15

    Little is known about how clinical oncology concepts are taught to PhD students or the most effective methods of doing so. In this study, electronic surveys were sent to faculty and students at PhD training programs, assessing their institution's methods of clinical oncology education and their perspective on optimal approaches to clinical oncology education. Only 40.0% of students reported any clinical oncology component to their institution's training, and only 26.5% had a clinician on their graduate advisory committee. Forty-three percent of students believed that they had a good understanding for translating basic science research into clinical practice, and 77.2% of all participants believed dual degree MD/PhD students were superior to PhD students in this regard. Lectures on clinical oncology research topics were the most valuable type of experience for all participants and were also the most common type of experience utilized. Working with a clinician to develop a clinical trial with correlative endpoints was also highly valued, but was only utilized by approximately 10% of programs. Faculty rated the value of nearly all types of clinical oncology exposure significantly lower than did students. Inclusion of the approaches identified in this study is likely to enhance PhD training in oncology-related disciplines. Cancer Res; 77(18); 4741-4. ©2017 AACR . ©2017 American Association for Cancer Research.

  3. Multidimensional process discovery

    NARCIS (Netherlands)

    Ribeiro, J.T.S.

    2013-01-01

    Typically represented in event logs, business process data describe the execution of process events over time. Business process intelligence (BPI) techniques such as process mining can be applied to get strategic insight into business processes. Process discovery, conformance checking and

  4. Fateful discovery almost forgotten

    CERN Multimedia

    1989-01-01

    "The discovery of the fission of uranium exactly half a century ago is at risk of passing unremarked because of the general ambivalence towards the consequences of this development. Can that be wise?" (4 pages)

  5. Toxins and drug discovery.

    Science.gov (United States)

    Harvey, Alan L

    2014-12-15

    Components from venoms have stimulated many drug discovery projects, with some notable successes. These are briefly reviewed, from captopril to ziconotide. However, there have been many more disappointments on the road from toxin discovery to approval of a new medicine. Drug discovery and development is an inherently risky business, and the main causes of failure during development programmes are outlined in order to highlight steps that might be taken to increase the chances of success with toxin-based drug discovery. These include having a clear focus on unmet therapeutic needs, concentrating on targets that are well-validated in terms of their relevance to the disease in question, making use of phenotypic screening rather than molecular-based assays, and working with development partners with the resources required for the long and expensive development process. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.

  6. Defining Creativity with Discovery

    OpenAIRE

    Wilson, Nicholas Charles; Martin, Lee

    2017-01-01

    The standard definition of creativity has enabled significant empirical and theoretical advances, yet contains philosophical conundrums concerning the nature of novelty and the role of recognition and values. In this work we offer an act of conceptual valeting that addresses these issues and in doing so, argue that creativity definitions can be extended through the use of discovery. Drawing on dispositional realist philosophy we outline why adding the discovery and bringing into being of new ...

  7. On the antiproton discovery

    International Nuclear Information System (INIS)

    Piccioni, O.

    1989-01-01

    The author of this article describes his own role in the discovery of the antiproton. Although Segre and Chamberlain received the Nobel Prize in 1959 for its discovery, the author claims that their experimental method was his idea which he communicated to them informally in December 1954. He describes how his application for citizenship (he was Italian), and other scientists' manipulation, prevented him from being at Berkeley to work on the experiment himself. (UK)

  8. Discovery Driven Growth

    DEFF Research Database (Denmark)

    Bukh, Per Nikolaj

    2009-01-01

    Anmeldelse af Discovery Driven Growh : A breakthrough process to reduce risk and seize opportunity, af Rita G. McGrath & Ian C. MacMillan, Boston: Harvard Business Press. Udgivelsesdato: 14 august......Anmeldelse af Discovery Driven Growh : A breakthrough process to reduce risk and seize opportunity, af Rita G. McGrath & Ian C. MacMillan, Boston: Harvard Business Press. Udgivelsesdato: 14 august...

  9. The π discovery

    International Nuclear Information System (INIS)

    Fowler, P.H.

    1988-01-01

    The paper traces the discovery of the Π meson. The discovery was made by exposure of nuclear emulsions to cosmic radiation at high altitudes, with subsequent scanning of the emulsions for meson tracks. Disintegration of nuclei by a negative meson, and the decay of a Π meson were both observed. Further measurements revealed the mass of the meson. The studies carried out on the origin of the Π-mesons, and their mode of decay, are both described. (U.K.)

  10. Knowledge about knowledge

    International Nuclear Information System (INIS)

    Ramm, Hans Henrik

    2006-01-01

    Technology and knowledge make up the knowledge capital that has been so essential to the oil and gas industry's value creation, competitiveness and internationalization. Report prepared for the Norwegian Oil Industry Association (OLF) and The Norwegian Society of Chartered Technical and Scientific Professionals (Tekna), on the Norwegian petroleum cluster as an environment for creating knowledge capital from human capital, how fiscal and other framework conditions may influence the building of knowledge capital, the long-term perspectives for the petroleum cluster, what Norwegian society can learn from the experiences in the petroleum cluster, and the importance of gaining more knowledge about the functionality of knowledge for increased value creation (author) (ml)

  11. Combinatorial thin film materials science: From alloy discovery and optimization to alloy design

    Energy Technology Data Exchange (ETDEWEB)

    Gebhardt, Thomas, E-mail: gebhardt@mch.rwth-aachen.de; Music, Denis; Takahashi, Tetsuya; Schneider, Jochen M.

    2012-06-30

    This paper provides an overview of modern alloy development, from discovery and optimization towards alloy design, based on combinatorial thin film materials science. The combinatorial approach, combining combinatorial materials synthesis of thin film composition-spreads with high-throughput property characterization has proven to be a powerful tool to delineate composition-structure-property relationships, and hence to efficiently identify composition windows with enhanced properties. Furthermore, and most importantly for alloy design, theoretical models and hypotheses can be critically appraised. Examples for alloy discovery, optimization, and alloy design of functional as well as structural materials are presented. Using Fe-Mn based alloys as an example, we show that the combination of modern electronic-structure calculations with the highly efficient combinatorial thin film composition-spread method constitutes an effective tool for knowledge-based alloy design.

  12. Combinatorial thin film materials science: From alloy discovery and optimization to alloy design

    International Nuclear Information System (INIS)

    Gebhardt, Thomas; Music, Denis; Takahashi, Tetsuya; Schneider, Jochen M.

    2012-01-01

    This paper provides an overview of modern alloy development, from discovery and optimization towards alloy design, based on combinatorial thin film materials science. The combinatorial approach, combining combinatorial materials synthesis of thin film composition-spreads with high-throughput property characterization has proven to be a powerful tool to delineate composition–structure–property relationships, and hence to efficiently identify composition windows with enhanced properties. Furthermore, and most importantly for alloy design, theoretical models and hypotheses can be critically appraised. Examples for alloy discovery, optimization, and alloy design of functional as well as structural materials are presented. Using Fe-Mn based alloys as an example, we show that the combination of modern electronic-structure calculations with the highly efficient combinatorial thin film composition-spread method constitutes an effective tool for knowledge-based alloy design.

  13. Care Coordination for Children with Complex Special Health Care Needs: The Value of the Advanced Practice Nurse’s Enhanced Scope of Knowledge and Practice

    Science.gov (United States)

    Looman, Wendy S.; Presler, Elizabeth; Erickson, Mary M.; Garwick, Ann E.; Cady, Rhonda G.; Kelly, Anne M.; Finkelstein, Stanley M.

    2012-01-01

    Efficiency and effectiveness of care coordination depends on a match between the needs of the population and the skills, scope of practice, and intensity of services provided by the care coordinator. There is limited existing literature that addresses the relevance of the APN role as a fit for coordination of care for children with SHCN. The objective of this paper is to describe the value of the advanced practice nurse’s (APN’s) enhanced scope of knowledge and practice for relationship-based care coordination in healthcare homes that serve children with complex special health care needs (SHCN). The TeleFamilies project is provided as an example of the integration of an APN care coordinator in a healthcare home for children with SHCN. PMID:22560803

  14. Analysis student self efficacy in terms of using Discovery Learning model with SAVI approach

    Science.gov (United States)

    Sahara, Rifki; Mardiyana, S., Dewi Retno Sari

    2017-12-01

    Often students are unable to prove their academic achievement optimally according to their abilities. One reason is that they often feel unsure that they are capable of completing the tasks assigned to them. For students, such beliefs are necessary. The term belief has called self efficacy. Self efficacy is not something that has brought about by birth or something with permanent quality of an individual, but is the result of cognitive processes, the meaning one's self efficacy will be stimulated through learning activities. Self efficacy has developed and enhanced by a learning model that can stimulate students to foster confidence in their capabilities. One of them is by using Discovery Learning model with SAVI approach. Discovery Learning model with SAVI approach is one of learning models that involves the active participation of students in exploring and discovering their own knowledge and using it in problem solving by utilizing all the sensory devices they have. This naturalistic qualitative research aims to analyze student self efficacy in terms of use the Discovery Learning model with SAVI approach. The subjects of this study are 30 students focused on eight students who have high, medium, and low self efficacy obtained through purposive sampling technique. The data analysis of this research used three stages, that were reducing, displaying, and getting conclusion of the data. Based on the results of data analysis, it was concluded that the self efficacy appeared dominantly on the learning by using Discovery Learning model with SAVI approach is magnitude dimension.

  15. Polar Domain Discovery with Sparkler

    Science.gov (United States)

    Duerr, R.; Khalsa, S. J. S.; Mattmann, C. A.; Ottilingam, N. K.; Singh, K.; Lopez, L. A.

    2017-12-01

    The scientific web is vast and ever growing. It encompasses millions of textual, scientific and multimedia documents describing research in a multitude of scientific streams. Most of these documents are hidden behind forms which require user action to retrieve and thus can't be directly accessed by content crawlers. These documents are hosted on web servers across the world, most often on outdated hardware and network infrastructure. Hence it is difficult and time-consuming to aggregate documents from the scientific web, especially those relevant to a specific domain. Thus generating meaningful domain-specific insights is currently difficult. We present an automated discovery system (Figure 1) using Sparkler, an open-source, extensible, horizontally scalable crawler which facilitates high throughput and focused crawling of documents pertinent to a particular domain such as information about polar regions. With this set of highly domain relevant documents, we show that it is possible to answer analytical questions about that domain. Our domain discovery algorithm leverages prior domain knowledge to reach out to commercial/scientific search engines to generate seed URLs. Subject matter experts then annotate these seed URLs manually on a scale from highly relevant to irrelevant. We leverage this annotated dataset to train a machine learning model which predicts the `domain relevance' of a given document. We extend Sparkler with this model to focus crawling on documents relevant to that domain. Sparkler avoids disruption of service by 1) partitioning URLs by hostname such that every node gets a different host to crawl and by 2) inserting delays between subsequent requests. With an NSF-funded supercomputer Wrangler, we scaled our domain discovery pipeline to crawl about 200k polar specific documents from the scientific web, within a day.

  16. A Technique Socratic Questioning-Guided Discovery

    Directory of Open Access Journals (Sweden)

    M. Hakan Türkçapar

    2012-03-01

    Full Text Available “Socratic Method” is a way of teaching philosophical thinking and knowledge by asking questions which was used by antique period greek philosopher Socrates. Socrates was teaching knowledge to his followers by asking questions and the conversation between them was named “Socratic Dialogues”. In this meaning, no novel knowledge is taught to the individual but only what is formerly known is reminded and rediscovered. The form of socratic questioning which is used during the process of cognitive behavioral therapy is known as Guided Discovery. In this method it is aimed to make the client notice the piece of knowledge which he could notice but is not aware with a series of questions. Socratic method or guided discovery consists of several steps which are: Identifying the problem by listening to the client and making reflections, finding alternatives by examining and evaluating, reidentification by using the newly found information and questioning the old distorted belief and reaching to a conclusion and applying it. Question types used during these procedures are, questions for gaining information, questions revealing the meanings, questions revealing the beliefs, questions about behaviours during the similar past experiences, analyse questions and analytic synthesis questions. In order to make the patient feel understood it is important to be empathetic and summarising the problem during the interview. In this text, steps of Socratic Questioning-Guided Discovery will be reviewed with sample dialogues after each step

  17. Geodiversity and geohazards of the Susa Valley (W-Alps, Italy): combining scientific research and new technologies for enhanced knowledge and proactive management of geoheritage in mountain regions

    Science.gov (United States)

    Giardino, Marco; Bacenetti, Marco; Perotti, Luigi; Giordano, Enrico; Ghiraldi, Luca; Palomba, Mauro

    2013-04-01

    Mountain regions have a range of geological and geomorphological features that make them very attractive for tourism activities. As a consequence, increased human "pressure" causes impacts on geoheritage sites and higher geomorphological risks. These effects are magnified by active geomorphic processes characterizing mountains areas, highly sensitive to climate change. In term of "human sensitivity", several sociological surveys have shown that "perceived risk", not "real risk", influences people's behavior towards natural hazards. The same approach can be applied to geodiversity and geoheritage. Based on these assumptions, we considered the possible strategic roles played by diffusion of scientific research and application of new technologies: 1) to enhance awareness, either of geodiversity or environmental dynamics and 2) to improve knowledge, both on geoheritage management and natural risk reduction. Within the activities of the "ProGEO-Piemonte Project" (Progetti d'Ateneo 2011, cofunded by Universita? degli Studi di Torino and Compagnia di San Paolo Bank Foundation), we performed a systematic review of geodiversity and natural hazards information in the Piemonte Region (NW-Italy). Then we focused our attention on the Susa Valley, an area of the Western Alps where the geoheritage is affected by very active morphodynamics, as well as by a growing tourism, after the 2006 winter Olympics. The Susa Valley became one of the 9 strategic geothematic areas have been selected to represent the geodiversity of the Piemonte region, each characterized by high potential for enhancement of public understanding of science, and recreation activities supported by local communities. Then we contributed to the awareness-raising communication strategy of the "RiskNat project" (Interreg Alcotra 2007-2013, Action A.4.3) by synthesizing geoscience knowledge on the Susa Valley and information on slope instabilities and models/prevention measures/warning systems. Visual representations

  18. From Geoportals to Geographic Knowledge Portals

    Directory of Open Access Journals (Sweden)

    Manfred Mittlböck

    2013-03-01

    Full Text Available We present the application of Latent Semantic Analysis (LSA in combination with recommender systems, in order to enhance discovery in geoportals. As a basis for discovery, metadata of spatial data and services, as well as of non-spatial resources, such as documents and scientific papers, is created and registered in the catalogue of the geoportal (semi-automatically. Links that are not inherent in the data itself are established based on the semantic similarity of its textual content using LSA. This leads to the transition from unstructured data to structured (metadata information, serving as a basis for the generation of knowledge. The metadata information is integrated into a recommendation system that provides a ranked list showing (1 what other users viewed and (2 the related resources discovered by the LSA workflow as a result. Based on the assumptions that similar texts have something in common and that users are likely to be interested in what other users viewed, recommendations provide a broader, but also more precise, search result; on the one hand, the recommender engine considers additional information; on the other hand, it ranks resources based on the discovery experience of other users and the likeliness of the documents being related to each other.

  19. Discovery of charm

    International Nuclear Information System (INIS)

    Goldhaber, G.

    1984-11-01

    In my talk I will cover the period 1973 to 1976 which saw the discoveries of the J/psi and psi' resonances and most of the Psion spectroscopy, the tau lepton and the D 0 ,D + charmed meson doublet. Occasionally I will refer briefly to more recent results. Since this conference is on the history of the weak-interactions I will deal primarily with the properties of naked charm and in particular the weakly decaying doublet of charmed mesons. Most of the discoveries I will mention were made with the SLAC-LBL Magnetic Detector or MARK I which we operated at SPEAR from 1973 to 1976. 27 references

  20. Big Data in Drug Discovery.

    Science.gov (United States)

    Brown, Nathan; Cambruzzi, Jean; Cox, Peter J; Davies, Mark; Dunbar, James; Plumbley, Dean; Sellwood, Matthew A; Sim, Aaron; Williams-Jones, Bryn I; Zwierzyna, Magdalena; Sheppard, David W

    2018-01-01

    Interpretation of Big Data in the drug discovery community should enhance project timelines and reduce clinical attrition through improved early decision making. The issues we encounter start with the sheer volume of data and how we first ingest it before building an infrastructure to house it to make use of the data in an efficient and productive way. There are many problems associated with the data itself including general reproducibility, but often, it is the context surrounding an experiment that is critical to success. Help, in the form of artificial intelligence (AI), is required to understand and translate the context. On the back of natural language processing pipelines, AI is also used to prospectively generate new hypotheses by linking data together. We explain Big Data from the context of biology, chemistry and clinical trials, showcasing some of the impressive public domain sources and initiatives now available for interrogation. © 2018 Elsevier B.V. All rights reserved.

  1. Stoma management: enhancing patient knowledge.

    Science.gov (United States)

    Burch, Jennie

    2011-04-01

    Community nurses are likely to encounter people with a stoma, most commonly a colostomy. An appliance is used to collect and contain the stomal output. There are various appliances available, each designed to specifically care for a particular type of stoma. Ostomates (people with a stoma) are trained to care for their stoma while they are in hospital by the stoma specialist nurse. However, it is possible that complications can occur, such as sore peristomal skin, and in this instance a stoma accessory can be used to good effect. There are many accessories available, which can make choice difficult. However, an understanding of why accessories are used can assist in the assessment and treatment choice. It may be necessary to request the assistance of the stoma specialist nurse.

  2. Discovery: Pile Patterns

    Science.gov (United States)

    de Mestre, Neville

    2017-01-01

    Earlier "Discovery" articles (de Mestre, 1999, 2003, 2006, 2010, 2011) considered patterns from many mathematical situations. This article presents a group of patterns used in 19th century mathematical textbooks. In the days of earlier warfare, cannon balls were stacked in various arrangements depending on the shape of the pile base…

  3. Discovery and Innovation

    African Journals Online (AJOL)

    Discovery and Innovation is a journal of the African Academy of Sciences (AAS) ... World (TWAS) meant to focus attention on science and technology in Africa and the ... of Non-wood Forest Products: Potential Impacts and Challenges in Africa ...

  4. The discovery of fission

    International Nuclear Information System (INIS)

    McKay, H.A.C.

    1978-01-01

    In this article by the retired head of the Separation Processes Group of the Chemistry Division, Atomic Energy Research Establishment, Harwell, U.K., the author recalls what he terms 'an exciting drama, the unravelling of the nature of the atomic nucleus' in the years before the Second World War, including the discovery of fission. 12 references. (author)

  5. The Discovery of America

    Science.gov (United States)

    Martin, Paul S.

    1973-01-01

    Discusses a model for explaining the spread of human population explosion on North American continent since its discovery 12,000 years ago. The model may help to map the spread of Homo sapiens throughout the New World by using the extinction chronology of the Pleistocene megafauna. (Author/PS)

  6. Impact of knowledge-based iterative model reconstruction on myocardial late iodine enhancement in computed tomography and comparison with cardiac magnetic resonance.

    Science.gov (United States)

    Tanabe, Yuki; Kido, Teruhito; Kurata, Akira; Fukuyama, Naoki; Yokoi, Takahiro; Kido, Tomoyuki; Uetani, Teruyoshi; Vembar, Mani; Dhanantwari, Amar; Tokuyasu, Shinichi; Yamashita, Natsumi; Mochizuki, Teruhito

    2017-10-01

    We evaluated the image quality and diagnostic performance of late iodine enhancement computed tomography (LIE-CT) with knowledge-based iterative model reconstruction (IMR) for the detection of myocardial infarction (MI) in comparison with late gadolinium enhancement magnetic resonance imaging (LGE-MRI). The study investigated 35 patients who underwent a comprehensive cardiac CT protocol and LGE-MRI for the assessment of coronary artery disease. The CT protocol consisted of stress dynamic myocardial CT perfusion, coronary CT angiography (CTA) and LIE-CT using 256-slice CT. LIE-CT scans were acquired 5 min after CTA without additional contrast medium and reconstructed with filtered back projection (FBP), a hybrid iterative reconstruction (HIR), and IMR. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed. Sensitivity and specificity of LIE-CT for detecting MI were assessed according to the 16-segment model. Image quality scores, and diagnostic performance were compared among LIE-CT with FBP, HIR and IMR. Among the 35 patients, 139 of 560 segments showed MI in LGE-MRI. On LIE-CT with FBP, HIR, and IMR, the median SNRs were 2.1, 2.9, and 6.1; and the median CNRs were 1.7, 2.2, and 4.7, respectively. Sensitivity and specificity were 56 and 93% for FBP, 62 and 91% for HIR, and 80 and 91% for IMR. LIE-CT with IMR showed the highest image quality and sensitivity (p quality and diagnostic performance of LIE-CT for detecting MI in comparison with FBP and HIR.

  7. A knowledge-based operator advisor system for integration of fault detection, control, and diagnosis to enhance the safe and reliable operation of nuclear power plants

    International Nuclear Information System (INIS)

    Bhatnagar, R.

    1989-01-01

    A Knowledged-Based Operator Advisor System has been developed for enhancing the complex task of maintaining safe and reliable operation of nuclear power plants. The operator's activities have been organized into the four tasks of data interpretation for abstracting high level information from sensor data, plant state monitoring for identification of faults, plan execution for controlling the faults, and diagnosis for determination of root causes of faults. The Operator Advisor System is capable of identifying the abnormal functioning of the plant in terms of: (1) deviations from normality, (2) pre-enumerated abnormal events, and (3) safety threats. The classification of abnormal functioning into the three categories of deviations from normality, abnormal events, and safety threats allows the detection of faults at three levels of: (1) developing faults, (2) developed faults, and (3) safety threatening faults. After the identification of abnormal functioning the system will identify the procedures to be executed to mitigate the consequences of abnormal functioning and will help the operator by displaying the procedure steps and monitoring the success of actions taken. The system also is capable of diagnosing the root causes of abnormal functioning. The identification, and diagnosis of root causes of abnormal functioning are done in parallel to the task of procedure execution, allowing the detection of more critical safety threats while executing procedures to control abnormal events

  8. Chirality - The forthcoming 160th Anniversary of Pasteur's Discovery

    OpenAIRE

    Molčanov, K.; Kojić-Prodić., B.

    2007-01-01

    The presented review on chirality is dedicated to the centennial birth anniversary of Nobel laureate Vladimir Prelog and 160 years of Pasteur's discovery of chirality on tartrates. Chirality has been recognized in nature by artists and architects, who have used it for decorations and basic constructions, as shown in the Introduction. The progress of science through history has enabled the gathering of knowledge on chirality and its many ways of application. The key historical discoveries abou...

  9. Improved accuracy of supervised CRM discovery with interpolated Markov models and cross-species comparison.

    Science.gov (United States)

    Kazemian, Majid; Zhu, Qiyun; Halfon, Marc S; Sinha, Saurabh

    2011-12-01

    Despite recent advances in experimental approaches for identifying transcriptional cis-regulatory modules (CRMs, 'enhancers'), direct empirical discovery of CRMs for all genes in all cell types and environmental conditions is likely to remain an elusive goal. Effective methods for computational CRM discovery are thus a critically needed complement to empirical approaches. However, existing computational methods that search for clusters of putative binding sites are ineffective if the relevant TFs and/or their binding specificities are unknown. Here, we provide a significantly improved method for 'motif-blind' CRM discovery that does not depend on knowledge or accurate prediction of TF-binding motifs and is effective when limited knowledge of functional CRMs is available to 'supervise' the search. We propose a new statistical method, based on 'Interpolated Markov Models', for motif-blind, genome-wide CRM discovery. It captures the statistical profile of variable length words in known CRMs of a regulatory network and finds candidate CRMs that match this profile. The method also uses orthologs of the known CRMs from closely related genomes. We perform in silico evaluation of predicted CRMs by assessing whether their neighboring genes are enriched for the expected expression patterns. This assessment uses a novel statistical test that extends the widely used Hypergeometric test of gene set enrichment to account for variability in intergenic lengths. We find that the new CRM prediction method is superior to existing methods. Finally, we experimentally validate 12 new CRM predictions by examining their regulatory activity in vivo in Drosophila; 10 of the tested CRMs were found to be functional, while 6 of the top 7 predictions showed the expected activity patterns. We make our program available as downloadable source code, and as a plugin for a genome browser installed on our servers. © The Author(s) 2011. Published by Oxford University Press.

  10. The neutron discovery

    International Nuclear Information System (INIS)

    Six, J.

    1987-01-01

    The neutron: who had first the idea, who discovered it, who established its main properties. To these apparently simple questions, multiple answers exist. The progressive discovery of the neutron is a marvellous illustration of some characteristics of the scientific research, where the unforeseen may be combined with the expected. This discovery is replaced in the context of the 1930's scientific effervescence that succeeded the revolutionary introduction of quantum mechanics. This book describes the works of Bothe, the Joliot-Curie and Chadwick which led to the neutron in an unexpected way. A historical analysis allows to give a new interpretation on the hypothesis suggested by the Joliot-Curie. Some texts of these days will help the reader to revive this fascinating story [fr

  11. Atlas of Astronomical Discoveries

    CERN Document Server

    Schilling, Govert

    2011-01-01

    Four hundred years ago in Middelburg, in the Netherlands, the telescope was invented. The invention unleashed a revolution in the exploration of the universe. Galileo Galilei discovered mountains on the Moon, spots on the Sun, and moons around Jupiter. Christiaan Huygens saw details on Mars and rings around Saturn. William Herschel discovered a new planet and mapped binary stars and nebulae. Other astronomers determined the distances to stars, unraveled the structure of the Milky Way, and discovered the expansion of the universe. And, as telescopes became bigger and more powerful, astronomers delved deeper into the mysteries of the cosmos. In his Atlas of Astronomical Discoveries, astronomy journalist Govert Schilling tells the story of 400 years of telescopic astronomy. He looks at the 100 most important discoveries since the invention of the telescope. In his direct and accessible style, the author takes his readers on an exciting journey encompassing the highlights of four centuries of astronomy. Spectacul...

  12. Viral pathogen discovery

    Science.gov (United States)

    Chiu, Charles Y

    2015-01-01

    Viral pathogen discovery is of critical importance to clinical microbiology, infectious diseases, and public health. Genomic approaches for pathogen discovery, including consensus polymerase chain reaction (PCR), microarrays, and unbiased next-generation sequencing (NGS), have the capacity to comprehensively identify novel microbes present in clinical samples. Although numerous challenges remain to be addressed, including the bioinformatics analysis and interpretation of large datasets, these technologies have been successful in rapidly identifying emerging outbreak threats, screening vaccines and other biological products for microbial contamination, and discovering novel viruses associated with both acute and chronic illnesses. Downstream studies such as genome assembly, epidemiologic screening, and a culture system or animal model of infection are necessary to establish an association of a candidate pathogen with disease. PMID:23725672

  13. Resource Discovery in Activity-Based Sensor Networks

    DEFF Research Database (Denmark)

    Bucur, Doina; Bardram, Jakob

    This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networks...... (ABSNs) knowledge about their usage even at the network layer. ABSN redesigns classical network-level service discovery protocols to include and use this logical structuring of the network for a more practically applicable service discovery scheme. Noting that in practical settings activity-based sensor...

  14. Fateful discovery almost forgotten

    International Nuclear Information System (INIS)

    Anon.

    1989-01-01

    The paper reviews the discovery of the fission of uranium, which took place fifty years ago. A description is given of the work of Meitner and Frisch in interpreting the Fermi data on the bombardment of uranium nuclei with neutrons, i.e. proposing fission. The historical events associated with the development and exploitation of uranium fission are described, including the Manhattan Project, Hiroshima and Nagasaki, Shippingport, and Chernobyl. (U.K.)

  15. Discovery as a process

    Energy Technology Data Exchange (ETDEWEB)

    Loehle, C.

    1994-05-01

    The three great myths, which form a sort of triumvirate of misunderstanding, are the Eureka! myth, the hypothesis myth, and the measurement myth. These myths are prevalent among scientists as well as among observers of science. The Eureka! myth asserts that discovery occurs as a flash of insight, and as such is not subject to investigation. This leads to the perception that discovery or deriving a hypothesis is a moment or event rather than a process. Events are singular and not subject to description. The hypothesis myth asserts that proper science is motivated by testing hypotheses, and that if something is not experimentally testable then it is not scientific. This myth leads to absurd posturing by some workers conducting empirical descriptive studies, who dress up their study with a ``hypothesis`` to obtain funding or get it published. Methods papers are often rejected because they do not address a specific scientific problem. The fact is that many of the great breakthroughs in silence involve methods and not hypotheses or arise from largely descriptive studies. Those captured by this myth also try to block funding for those developing methods. The third myth is the measurement myth, which holds that determining what to measure is straightforward, so one doesn`t need a lot of introspection to do science. As one ecologist put it to me ``Don`t give me any of that philosophy junk, just let me out in the field. I know what to measure.`` These myths lead to difficulties for scientists who must face peer review to obtain funding and to get published. These myths also inhibit the study of science as a process. Finally, these myths inhibit creativity and suppress innovation. In this paper I first explore these myths in more detail and then propose a new model of discovery that opens the supposedly miraculous process of discovery to doser scrutiny.

  16. Introduction to fragment-based drug discovery.

    Science.gov (United States)

    Erlanson, Daniel A

    2012-01-01

    Fragment-based drug discovery (FBDD) has emerged in the past decade as a powerful tool for discovering drug leads. The approach first identifies starting points: very small molecules (fragments) that are about half the size of typical drugs. These fragments are then expanded or linked together to generate drug leads. Although the origins of the technique date back some 30 years, it was only in the mid-1990s that experimental techniques became sufficiently sensitive and rapid for the concept to be become practical. Since that time, the field has exploded: FBDD has played a role in discovery of at least 18 drugs that have entered the clinic, and practitioners of FBDD can be found throughout the world in both academia and industry. Literally dozens of reviews have been published on various aspects of FBDD or on the field as a whole, as have three books (Jahnke and Erlanson, Fragment-based approaches in drug discovery, 2006; Zartler and Shapiro, Fragment-based drug discovery: a practical approach, 2008; Kuo, Fragment based drug design: tools, practical approaches, and examples, 2011). However, this chapter will assume that the reader is approaching the field with little prior knowledge. It will introduce some of the key concepts, set the stage for the chapters to follow, and demonstrate how X-ray crystallography plays a central role in fragment identification and advancement.

  17. Discovery stories in the science classroom

    Science.gov (United States)

    Arya, Diana Jaleh

    when the readers have little prior knowledge of a given topic. Further, ethnic minority groups of lower socio-economic level (i.e., Latin and African-American origins) demonstrated an even greater benefit from the SDN texts, suggesting that a scientist's story of discovery can help to close the gap in academic performance in science.

  18. Nuclear knowledge management

    International Nuclear Information System (INIS)

    2007-01-01

    The management of nuclear knowledge has emerged as a growing challenge in recent years. The need to preserve and transfer nuclear knowledge is compounded by recent trends such as ageing of the nuclear workforce, declining student numbers in nuclear-related fields, and the threat of losing accumulated nuclear knowledge. Addressing these challenges, the IAEA promotes a 'knowledge management culture' through: - Providing guidance for policy formulation and implementation of nuclear knowledge management; - Strengthening the contribution of nuclear knowledge in solving development problems, based on needs and priorities of Member States; - Pooling, analysing and sharing nuclear information to facilitate knowledge creation and its utilization; - Implementing effective knowledge management systems; - Preserving and maintaining nuclear knowledge; - Securing sustainable human resources for the nuclear sector; and - Enhancing nuclear education and training

  19. Swift: 10 Years of Discovery

    Science.gov (United States)

    2014-12-01

    The conference Swift: 10 years of discovery was held in Roma at La Sapienza University on Dec. 2-5 2014 to celebrate 10 years of Swift successes. Thanks to a large attendance and a lively program, it provided the opportunity to review recent advances of our knowledge of the high-energy transient Universe both from the observational and theoretical sides. When Swift was launched on November 20, 2004, its prime objective was to chase Gamma-Ray Bursts and deepen our knowledge of these cosmic explosions. And so it did, unveiling the secrets of long and short GRBs. However, its multi-wavelength instrumentation and fast scheduling capabilities made it the most versatile mission ever flown. Besides GRBs, Swift has observed, and contributed to our understanding of, an impressive variety of targets including AGNs, supernovae, pulsars, microquasars, novae, variable stars, comets, and much more. Swift is continuously discovering rare and surprising events distributed over a wide range of redshifts, out to the most distant transient objects in the Universe. Such a trove of discoveries has been addressed during the conference with sessions dedicated to each class of events. Indeed, the conference in Rome was a spectacular celebration of the Swift 10th anniversary. It included sessions on all types of transient and steady sources. Top scientists from around the world gave invited and contributed talks. There was a large poster session, sumptuous lunches, news interviews and a glorious banquet with officials attending from INAF and ASI. All the presentations, as well as several conference pictures, can be found in the conference website (http://www.brera.inaf.it/Swift10/Welcome.html). These proceedings have been collected owing to the efforts of Paolo D’Avanzo who has followed each paper from submission to final acceptance. Our warmest thanks to Paolo for all his work. The Conference has been made possible by the support from La Sapienza University as well as from the ARAP

  20. Investigations into Library Web-Scale Discovery Services

    Directory of Open Access Journals (Sweden)

    Jason Vaughan

    2008-03-01

    Full Text Available Web-scale discovery services for libraries provide deep discovery to a library’s local and licensed content, and represent an evolution, perhaps a revolution, for end user information discovery as pertains to library collections.  This article frames the topic of web-scale discovery, and begins by illuminating web-scale discovery from an academic library’s perspective – that is, the internal perspective seeking widespread staff participation in the discovery conversation.  This included the creation of a discovery task force, a group which educated library staff, conducted internal staff surveys, and gathered observations from early adopters.  The article next addresses the substantial research conducted with library vendors which have developed these services.  Such work included drafting of multiple comprehensive question lists distributed to the vendors, onsite vendor visits, and continual tracking of service enhancements.  Together, feedback gained from library staff, insights arrived at by the Discovery Task Force, and information gathered from vendors collectively informed the recommendation of a service for the UNLV Libraries.

  1. Panorama 2014 - New oil and gas discoveries

    International Nuclear Information System (INIS)

    Vially, Roland; Hureau, Geoffroy

    2013-12-01

    Spending on exploration increased significantly in 2012, and this growth should continue into 2013. Over a period of ten years, exploration budgets have increased five-fold, leading to major discoveries in regions as yet unexplored. In 2012, 25 billion barrels of oil equivalent (Gboe) were revealed. This is more than the average for the whole decade, but less than the amount for the previous year. Although knowledge of the volumes that have been discovered is still very fragmented, they should continue to fall into 2013. The main reason lies in the fact that spending on exploration is being shifted towards assessing discoveries made in previous years in the particularly prolific basins of Brazil and East Africa, while the exploration of border regions - such as the West African pre-salt formation - is still only in its early stages. (authors)

  2. 14 CFR 406.143 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Discovery. 406.143 Section 406.143... Transportation Adjudications § 406.143 Discovery. (a) Initiation of discovery. Any party may initiate discovery... after a complaint has been filed. (b) Methods of discovery. The following methods of discovery are...

  3. BayesMD: flexible biological modeling for motif discovery

    DEFF Research Database (Denmark)

    Tang, Man-Hung Eric; Krogh, Anders; Winther, Ole

    2008-01-01

    We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fashion. A mixture of Dirichlets is used as prior over nucleotide probabilities in binding sites. It is trained on trans......We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fashion. A mixture of Dirichlets is used as prior over nucleotide probabilities in binding sites. It is trained...

  4. Foreword to the Special Focus on Mathematics, Data and Knowledge

    KAUST Repository

    Chen, Xiaoyu

    2013-12-01

    There is a growing interest in applying mathematical theories and methods from topology, computational geometry, differential equations, fluid dynamics, quantum statistics, etc. to describe and to analyze scientific regularities of diverse, massive, complex, nonlinear, and fast changing data accumulated continuously around the world and in discovering and revealing valid, insightful, and valuable knowledge that data imply. With increasingly solid mathematical foundations, various methods and techniques have been studied and developed for data mining, modeling, and processing, and knowledge representation, organization, and verification; different systems and mechanisms have been designed to perform data-intensive tasks in many application fields for classification, predication, recommendation, ranking, filtering, etc. This special focus of Mathematics in Computer Science is organized to stimulate original research on the interaction of mathematics with data and knowledge, in particular the exploration of new mathematical theories and methodologies for data modeling and analysis and knowledge discovery and management, the study of mathematical models of big data and complex knowledge, and the development of novel solutions and strategies to enhance the performance of existing systems and mechanisms for data and knowledge processing. The present foreword provides a short review of some key ideas and techniques on how mathematics interacts with data and knowledge, together with a few selected research directions and problems and a brief introduction to the four papers published in the focus. © 2013 Springer Basel.

  5. Investigating the Knowledge Management Culture

    Science.gov (United States)

    Stylianou, Vasso; Savva, Andreas

    2016-01-01

    Knowledge Management (KM) efforts aim at leveraging an organization into a knowledge organization thereby presenting knowledge employees with a very powerful tool; organized valuable knowledge accessible when and where needed in flexible, technologically-enhanced modes. The attainment of this aim, i.e., the transformation into a knowledge…

  6. "Tacit Knowledge" versus "Explicit Knowledge"

    DEFF Research Database (Denmark)

    Sanchez, Ron

    creators and carriers. By contrast, the explicit knowledge approach emphasizes processes for articulating knowledge held by individuals, the design of organizational approaches for creating new knowledge, and the development of systems (including information systems) to disseminate articulated knowledge...

  7. Automated Supernova Discovery (Abstract)

    Science.gov (United States)

    Post, R. S.

    2015-12-01

    (Abstract only) We are developing a system of robotic telescopes for automatic recognition of Supernovas as well as other transient events in collaboration with the Puckett Supernova Search Team. At the SAS2014 meeting, the discovery program, SNARE, was first described. Since then, it has been continuously improved to handle searches under a wide variety of atmospheric conditions. Currently, two telescopes are used to build a reference library while searching for PSN with a partial library. Since data is taken every night without clouds, we must deal with varying atmospheric and high background illumination from the moon. Software is configured to identify a PSN, reshoot for verification with options to change the run plan to acquire photometric or spectrographic data. The telescopes are 24-inch CDK24, with Alta U230 cameras, one in CA and one in NM. Images and run plans are sent between sites so the CA telescope can search while photometry is done in NM. Our goal is to find bright PSNs with magnitude 17.5 or less which is the limit of our planned spectroscopy. We present results from our first automated PSN discoveries and plans for PSN data acquisition.

  8. West Nile Virus Drug Discovery

    Directory of Open Access Journals (Sweden)

    Siew Pheng Lim

    2013-12-01

    Full Text Available The outbreak of West Nile virus (WNV in 1999 in the USA, and its continued spread throughout the Americas, parts of Europe, the Middle East and Africa, underscored the need for WNV antiviral development. Here, we review the current status of WNV drug discovery. A number of approaches have been used to search for inhibitors of WNV, including viral infection-based screening, enzyme-based screening, structure-based virtual screening, structure-based rationale design, and antibody-based therapy. These efforts have yielded inhibitors of viral or cellular factors that are critical for viral replication. For small molecule inhibitors, no promising preclinical candidate has been developed; most of the inhibitors could not even be advanced to the stage of hit-to-lead optimization due to their poor drug-like properties. However, several inhibitors developed for related members of the family Flaviviridae, such as dengue virus and hepatitis C virus, exhibited cross-inhibition of WNV, suggesting the possibility to re-purpose these antivirals for WNV treatment. Most promisingly, therapeutic antibodies have shown excellent efficacy in mouse model; one of such antibodies has been advanced into clinical trial. The knowledge accumulated during the past fifteen years has provided better rationale for the ongoing WNV and other flavivirus antiviral development.

  9. What contributes to the enhanced use of customer, competition and technology knowledge for product innovation performance? : a survey of multinational companies' subsidiaries operating in China

    NARCIS (Netherlands)

    Zhang, Junfeng; Hoenig, S.; Benedetto, Di A.C.; Lancioni, R.A.; Phatak, A.

    2009-01-01

    This study extends an emerging research area in knowledge management to new product development by empirically examining the factors associated with the use of different types of knowledge flows from various sources and product innovation performance (i.e., market success of new products) in the

  10. The need to enhance the employability competences (knowledge, skills, autonomy, and attitudes of undergraduates in Agriculture. Evidence from students’ perceptions and employers’ expectations

    Directory of Open Access Journals (Sweden)

    Nigel Yoven Armoogum

    2016-11-01

    Full Text Available The Faculty of Agriculture (FoA (University of Mauritius is the only tertiary Education Institution in the country providing graduate training in Agriculture with an annual enrolment of about 100-125 students. Although the relative contribution of the Agricultural sector to the economy has declined over the past decade — share to GDP: 3.0% in 2014 as compared to 6.4% in 2004[1] the introduction of new schemes in support of Bio- Farming, food processing and value-addition will attract new entrepreneurs to Agriculture. This transformation in the Agriculture sector will create new job opportunities, but has to leverage on skilled human capital. Graduates with good employability skills are of strategic importance to the FoA, in line with the government’s vision to develop a knowledge-based economy. This study aimed at mapping out the set of skills, understandings and personal attributes that will increase the job prospects of the fresh graduate from FoA in Agriculture. The main research question centred on the perceptions of employers, alumni and students of the FoA, concerning the most relevant competences for the Subject Area (key general and key subject specific competences, understandings and personal attributes, which enhance the employability of graduates in Agriculture. Using semi-structured interviews, the study explored and triangulated the perceptions from four key stakeholders’ perspectives, namely: a range of employers, Industry Placement Supervisors, alumni of the FoA and current students. Both quantitative and qualitative insights of the perceptions on the employability skills of FoA undergraduates were obtained from a wide range of employers from the private and public sector. An analysis of data from the interviews and responses was carried out using SPSS. The key attributes that were valued by the key stakeholders have been used to inform the ‘Employability Skills Subject Area Framework’, and the ‘Curriculum Mapping

  11. Using hydrochemical data and modelling to enhance the knowledge of groundwater flow and quality in an alluvial aquifer of Zagreb, Croatia

    Energy Technology Data Exchange (ETDEWEB)

    Marković, Tamara, E-mail: tmarkovic@hgi-cgs.hr; Brkić, Željka; Larva, Ozren

    2013-08-01

    The Zagreb alluvial aquifer system is located in the southwest of the Pannonian Basin in the Sava Valley in Croatia. It is composed of Quaternary unconsolidated deposits and is highly utilised, primarily as a water supply for the more than one million inhabitants of the capital city of Croatia. To determine the origin and dynamics of the groundwater and to enhance the knowledge of groundwater flow and the interactions between the groundwater and surface water, extensive hydrogeological and hydrochemical investigations have been completed. The groundwater levels monitored in nested observation wells and the lithological profile indicate that the aquifer is a single hydrogeologic unit, but the geochemical characteristics of the aquifer indicate stratification. The weathering of carbonate and silicate minerals has an important role in groundwater chemistry, especially in the area where old meanders of the Sava River existed. Groundwater quality was observed to be better in the deeper parts of the aquifer than in the shallower parts. Furthermore, deterioration of the groundwater quality was observed in the area under the influence of the landfill. The stable isotopic composition of all sampled waters indicates meteoric origin. NETPATH-WIN was used to calculate the mixing proportions between initial waters (water from the Sava River and groundwater from “regional” flow) in the final water (groundwater sampled from observation wells). According to the results, the mixing proportions of “regional” flow and the river water depend on hydrological conditions, the duration of certain hydrological conditions and the vicinity of the Sava River. Moreover, although the aquifer system behaves as a single hydrogeologic unit from a hydraulic point of view, it still clearly demonstrates geochemical stratification, which could be a decisive factor in future utilisation strategies for the aquifer system. - Highlights: • The Zagreb aquifer is the largest utilised source of

  12. Computational methods in drug discovery

    OpenAIRE

    Sumudu P. Leelananda; Steffen Lindert

    2016-01-01

    The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery project...

  13. Representation Discovery using Harmonic Analysis

    CERN Document Server

    Mahadevan, Sridhar

    2008-01-01

    Representations are at the heart of artificial intelligence (AI). This book is devoted to the problem of representation discovery: how can an intelligent system construct representations from its experience? Representation discovery re-parameterizes the state space - prior to the application of information retrieval, machine learning, or optimization techniques - facilitating later inference processes by constructing new task-specific bases adapted to the state space geometry. This book presents a general approach to representation discovery using the framework of harmonic analysis, in particu

  14. Hippocampus discovery First steps

    Directory of Open Access Journals (Sweden)

    Eliasz Engelhardt

    Full Text Available The first steps of the discovery, and the main discoverers, of the hippocampus are outlined. Arantius was the first to describe a structure he named "hippocampus" or "white silkworm". Despite numerous controversies and alternate designations, the term hippocampus has prevailed until this day as the most widely used term. Duvernoy provided an illustration of the hippocampus and surrounding structures, considered the first by most authors, which appeared more than one and a half century after Arantius' description. Some authors have identified other drawings and texts which they claim predate Duvernoy's depiction, in studies by Vesalius, Varolio, Willis, and Eustachio, albeit unconvincingly. Considering the definition of the hippocampal formation as comprising the hippocampus proper, dentate gyrus and subiculum, Arantius and Duvernoy apparently described the gross anatomy of this complex. The pioneering studies of Arantius and Duvernoy revealed a relatively small hidden formation that would become one of the most valued brain structures.

  15. Participative knowledge management to empower manufacturing workers

    DEFF Research Database (Denmark)

    Campatelli, Gianni; Richter, Alexander; Stocker, Alexander

    2016-01-01

    skills. In this paper, the authors suggest a participative knowledge management approach to empower manufacturing workers. Starting from a comprehensive empirical analysis of the existing work practices in a manufacturing company, the authors have developed and validated a knowledge management system...... prototype. The prototype is aimed for training, problem solving, and facilitating the discovery, acquisition, and sharing of manufacturing knowledge. The conducted evaluation of the prototype indicates that workers' skills and level of work satisfaction will increase since the knowledge management system...

  16. Effective knowledge management in translational medicine.

    Science.gov (United States)

    Szalma, Sándor; Koka, Venkata; Khasanova, Tatiana; Perakslis, Eric D

    2010-07-19

    The growing consensus that most valuable data source for biomedical discoveries is derived from human samples is clearly reflected in the growing number of translational medicine and translational sciences departments across pharma as well as academic and government supported initiatives such as Clinical and Translational Science Awards (CTSA) in the US and the Seventh Framework Programme (FP7) of EU with emphasis on translating research for human health. The pharmaceutical companies of Johnson and Johnson have established translational and biomarker departments and implemented an effective knowledge management framework including building a data warehouse and the associated data mining applications. The implemented resource is built from open source systems such as i2b2 and GenePattern. The system has been deployed across multiple therapeutic areas within the pharmaceutical companies of Johnson and Johnsons and being used actively to integrate and mine internal and public data to support drug discovery and development decisions such as indication selection and trial design in a translational medicine setting. Our results show that the established system allows scientist to quickly re-validate hypotheses or generate new ones with the use of an intuitive graphical interface. The implemented resource can serve as the basis of precompetitive sharing and mining of studies involving samples from human subjects thus enhancing our understanding of human biology and pathophysiology and ultimately leading to more effective treatment of diseases which represent unmet medical needs.

  17. Effective knowledge management in translational medicine

    Directory of Open Access Journals (Sweden)

    Khasanova Tatiana

    2010-07-01

    Full Text Available Abstract Background The growing consensus that most valuable data source for biomedical discoveries is derived from human samples is clearly reflected in the growing number of translational medicine and translational sciences departments across pharma as well as academic and government supported initiatives such as Clinical and Translational Science Awards (CTSA in the US and the Seventh Framework Programme (FP7 of EU with emphasis on translating research for human health. Methods The pharmaceutical companies of Johnson and Johnson have established translational and biomarker departments and implemented an effective knowledge management framework including building a data warehouse and the associated data mining applications. The implemented resource is built from open source systems such as i2b2 and GenePattern. Results The system has been deployed across multiple therapeutic areas within the pharmaceutical companies of Johnson and Johnsons and being used actively to integrate and mine internal and public data to support drug discovery and development decisions such as indication selection and trial design in a translational medicine setting. Our results show that the established system allows scientist to quickly re-validate hypotheses or generate new ones with the use of an intuitive graphical interface. Conclusions The implemented resource can serve as the basis of precompetitive sharing and mining of studies involving samples from human subjects thus enhancing our understanding of human biology and pathophysiology and ultimately leading to more effective treatment of diseases which represent unmet medical needs.

  18. Biomimicry as a basis for drug discovery.

    Science.gov (United States)

    Kolb, V M

    1998-01-01

    Selected works are discussed which clearly demonstrate that mimicking various aspects of the process by which natural products evolved is becoming a powerful tool in contemporary drug discovery. Natural products are an established and rich source of drugs. The term "natural product" is often used synonymously with "secondary metabolite." Knowledge of genetics and molecular evolution helps us understand how biosynthesis of many classes of secondary metabolites evolved. One proposed hypothesis is termed "inventive evolution." It invokes duplication of genes, and mutation of the gene copies, among other genetic events. The modified duplicate genes, per se or in conjunction with other genetic events, may give rise to new enzymes, which, in turn, may generate new products, some of which may be selected for. Steps of the inventive evolution can be mimicked in several ways for purpose of drug discovery. For example, libraries of chemical compounds of any imaginable structure may be produced by combinatorial synthesis. Out of these libraries new active compounds can be selected. In another example, genetic system can be manipulated to produce modified natural products ("unnatural natural products"), from which new drugs can be selected. In some instances, similar natural products turn up in species that are not direct descendants of each other. This is presumably due to a horizontal gene transfer. The mechanism of this inter-species gene transfer can be mimicked in therapeutic gene delivery. Mimicking specifics or principles of chemical evolution including experimental and test-tube evolution also provides leads for new drug discovery.

  19. Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery

    Directory of Open Access Journals (Sweden)

    Nicholas Ekow Thomford

    2018-05-01

    Full Text Available The therapeutic properties of plants have been recognised since time immemorial. Many pathological conditions have been treated using plant-derived medicines. These medicines are used as concoctions or concentrated plant extracts without isolation of active compounds. Modern medicine however, requires the isolation and purification of one or two active compounds. There are however a lot of global health challenges with diseases such as cancer, degenerative diseases, HIV/AIDS and diabetes, of which modern medicine is struggling to provide cures. Many times the isolation of “active compound” has made the compound ineffective. Drug discovery is a multidimensional problem requiring several parameters of both natural and synthetic compounds such as safety, pharmacokinetics and efficacy to be evaluated during drug candidate selection. The advent of latest technologies that enhance drug design hypotheses such as Artificial Intelligence, the use of ‘organ-on chip’ and microfluidics technologies, means that automation has become part of drug discovery. This has resulted in increased speed in drug discovery and evaluation of the safety, pharmacokinetics and efficacy of candidate compounds whilst allowing novel ways of drug design and synthesis based on natural compounds. Recent advances in analytical and computational techniques have opened new avenues to process complex natural products and to use their structures to derive new and innovative drugs. Indeed, we are in the era of computational molecular design, as applied to natural products. Predictive computational softwares have contributed to the discovery of molecular targets of natural products and their derivatives. In future the use of quantum computing, computational softwares and databases in modelling molecular interactions and predicting features and parameters needed for drug development, such as pharmacokinetic and pharmacodynamics, will result in few false positive leads in drug

  20. Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery.

    Science.gov (United States)

    Thomford, Nicholas Ekow; Senthebane, Dimakatso Alice; Rowe, Arielle; Munro, Daniella; Seele, Palesa; Maroyi, Alfred; Dzobo, Kevin

    2018-05-25

    The therapeutic properties of plants have been recognised since time immemorial. Many pathological conditions have been treated using plant-derived medicines. These medicines are used as concoctions or concentrated plant extracts without isolation of active compounds. Modern medicine however, requires the isolation and purification of one or two active compounds. There are however a lot of global health challenges with diseases such as cancer, degenerative diseases, HIV/AIDS and diabetes, of which modern medicine is struggling to provide cures. Many times the isolation of "active compound" has made the compound ineffective. Drug discovery is a multidimensional problem requiring several parameters of both natural and synthetic compounds such as safety, pharmacokinetics and efficacy to be evaluated during drug candidate selection. The advent of latest technologies that enhance drug design hypotheses such as Artificial Intelligence, the use of 'organ-on chip' and microfluidics technologies, means that automation has become part of drug discovery. This has resulted in increased speed in drug discovery and evaluation of the safety, pharmacokinetics and efficacy of candidate compounds whilst allowing novel ways of drug design and synthesis based on natural compounds. Recent advances in analytical and computational techniques have opened new avenues to process complex natural products and to use their structures to derive new and innovative drugs. Indeed, we are in the era of computational molecular design, as applied to natural products. Predictive computational softwares have contributed to the discovery of molecular targets of natural products and their derivatives. In future the use of quantum computing, computational softwares and databases in modelling molecular interactions and predicting features and parameters needed for drug development, such as pharmacokinetic and pharmacodynamics, will result in few false positive leads in drug development. This review

  1. Materials Discovery | Materials Science | NREL

    Science.gov (United States)

    Discovery Materials Discovery Images of red and yellow particles NREL's research in materials characterization of sample by incoming beam and measuring outgoing particles, with data being stored and analyzed Staff Scientist Dr. Zakutayev specializes in design of novel semiconductor materials for energy

  2. Service discovery using Bloom filters

    NARCIS (Netherlands)

    Goering, P.T.H.; Heijenk, Geert; Lelieveldt, B.P.F.; Haverkort, Boudewijn R.H.M.; de Laat, C.T.A.M.; Heijnsdijk, J.W.J.

    A protocol to perform service discovery in adhoc networks is introduced in this paper. Attenuated Bloom filters are used to distribute services to nodes in the neighborhood and thus enable local service discovery. The protocol has been implemented in a discrete event simulator to investigate the

  3. On the pulse of discovery

    Science.gov (United States)

    2017-12-01

    What started 50 years ago as a `smudge' on paper has flourished into a fundamental field of astrophysics replete with unexpected applications and exciting discoveries. To celebrate the discovery of pulsars, we look at the past, present and future of pulsar astrophysics.

  4. Concept relation discovery and innovation enabling technology (CORDIET)

    NARCIS (Netherlands)

    Poelmans, J.; Elzinga, P.; Neznanov, A.; Viaene, S.; Kuznetsov, S.O.; Ignatov, D.; Dedene, G.

    2011-01-01

    Concept Relation Discovery and Innovation Enabling Technology (CORDIET), is a toolbox for gaining new knowledge from unstructured text data. At the core of CORDIET is the C-K theory which captures the essential elements of innovation. The tool uses Formal Concept Analysis (FCA), Emergent Self

  5. A Knowledge Discovery from POS Data using State Space Models

    Science.gov (United States)

    Sato, Tadahiko; Higuchi, Tomoyuki

    The number of competing-brands changes by new product's entry. The new product introduction is endemic among consumer packaged goods firm and is an integral component of their marketing strategy. As a new product's entry affects markets, there is a pressing need to develop market response model that can adapt to such changes. In this paper, we develop a dynamic model that capture the underlying evolution of the buying behavior associated with the new product. This extends an application of a dynamic linear model, which is used by a number of time series analyses, by allowing the observed dimension to change at some point in time. Our model copes with a problem that dynamic environments entail: changes in parameter over time and changes in the observed dimension. We formulate the model with framework of a state space model. We realize an estimation of the model using modified Kalman filter/fixed interval smoother. We find that new product's entry (1) decreases brand differentiation for existing brands, as indicated by decreasing difference between cross-price elasticities; (2) decreases commodity power for existing brands, as indicated by decreasing trend; and (3) decreases the effect of discount for existing brands, as indicated by a decrease in the magnitude of own-brand price elasticities. The proposed framework is directly applicable to other fields in which the observed dimension might be change, such as economic, bioinformatics, and so forth.

  6. Knowledge Discovery in Chess Using an Aesthetics Approach

    Science.gov (United States)

    Iqbal, Azlan

    2012-01-01

    Computational aesthetics is a relatively new subfield of artificial intelligence (AI). It includes research that enables computers to "recognize" (and evaluate) beauty in various domains such as visual art, music, and games. Aside from the benefit this gives to humans in terms of creating and appreciating art in these domains, there are perhaps…

  7. Knowledge driven discovery for opportunistic IoT networking.

    OpenAIRE

    Pozza, Riccardo

    2015-01-01

    So far, the Internet of Things (IoT) has been concerned with the objective of connecting every-thing, or any object to the Internet world. By collaborating towards the creation of new services, the IoT has introduced the opportunity to add smartness to our cities, homes, buildings and healthcare systems, as well as businesses and products. In many scenarios, objects or IoT devices are not always statically deployed, but they may be free to move around being carried by people or vehicles, whil...

  8. The Modeling and Simulation Catalog for Discovery, Knowledge and Reuse

    Science.gov (United States)

    Stone, George F. III; Greenberg, Brandi; Daehler-Wilking, Richard; Hunt, Steven

    2011-01-01

    The DoD M&S Steering Committee has noted that the current DoD and Service's modeling and simulation resource repository (MSRR) services are not up-to-date limiting their value to the using communities. However, M&S leaders and managers also determined that the Department needs a functional M&S registry card catalog to facilitate M&S tool and data visibility to support M&S activities across the DoD. The M&S Catalog will discover and access M&S metadata maintained at nodes distributed across DoD networks in a centrally managed, decentralized process that employs metadata collection and management. The intent is to link information stores, precluding redundant location updating. The M&S Catalog uses a standard metadata schemas based on the DoD's Net-Centric Data Strategy Community of Interest metadata specification. The Air Force, Navy and OSD (CAPE) have provided initial information to participating DoD nodes, but plans on the horizon are being made to bring in hundreds of source providers.

  9. Data mining, knowledge discovery and data-driven modelling

    NARCIS (Netherlands)

    Solomatine, D.P.; Velickov, S.; Bhattacharya, B.; Van der Wal, B.

    2003-01-01

    The project was aimed at exploring the possibilities of a new paradigm in modelling - data-driven modelling, often referred as "data mining". Several application areas were considered: sedimentation problems in the Port of Rotterdam, automatic soil classification on the basis of cone penetration

  10. Collaborative Cyberinfrastructure: Crowdsourcing of Knowledge and Discoveries (Invited)

    Science.gov (United States)

    Gay, P.

    2013-12-01

    The design and implementation of programs to crowdsource science presents a unique set of challenges to system architects, programmers, and designers. In this presentation, one solution, CosmoQuest's Citizen Science Builder (CSB), will be discussed. CSB combines a clean user interface with a powerful back end to allow the quick design and deployment of citizen science sites that meet the needs of both the random Joe Public, and the detail driven Albert Professional. In this talk, the software will be overviewed, and the results of usability testing and accuracy testing with both citizen and professional scientists will be discussed. The software is designed to run on one or more LINUX systems running Apache webserver with MySQL and PHP. The interface is HTML5 and relies on javascript and AJAX to provide a dynamic interactive experience. CosmoQuest currently runs on Amazon Web Services and uses VBulletin for logins. The public-facing aspects of CSB provide a uniform experience that allows citizen scientists to use a simple set of tools to achieve a diversity of tasks. This interface presents users with a large view window for data, a toolbar reminiscent of MS Word or Adobe Photoshop with tools from drawing circles or segmented lines, flagging features from a dropdown menu, or marking specific objects with a set marker. The toolbar also allows users to select checkboxes describing the image as a whole. In addition to the viewer and toolbar, volunteers can also access tooltips, examples, and a video tutorial. The scientist interface for CSB gives the science team the ability to prioritize images, download results, create comparison data to validate volunteer data, and also provides access to downloadable tools for doing data analysis. Both these interfaces are controlled through a simple set of config files, although some tasks require customization of the controlling javascript. These are used to point the software at YouTube tutorials, graphics, and the correct toolsets. The only part of the interface requiring direct CSB administrator attention is the uploading of new images/movies onto the server and uploading of meta-data about the data into the database. This step must be customized for each unique data set. Initial research shows that professionals using the software to annotate images - marking craters on the moon to be specific - are as accurate with CSB as they are with their favourite professional software. It also shows that the results of members of the public are within error of the results of the professionals, with roughly the same level of error in each group and across many crater scales. Results of interviews with volunteers about their ease moving between interfaces for different projects, and response to the aesthetics of the site will also be discussed during this presentation

  11. Teaching APA Style Documentation: Discovery Learning, Scaffolding and Procedural Knowledge

    Science.gov (United States)

    Skeen, Thomas; Zafonte, Maria

    2015-01-01

    Students struggle with learning correct documentation style as found in the Publication Manual of the American Psychological Association and teachers are often at a loss for how to best instruct students in correct usage of APA style. As such, the first part of this paper discusses the current research on teaching documentation styles as well as…

  12. Energy-Water Nexus Knowledge Discovery Framework, Experts’ Meeting Report

    Energy Technology Data Exchange (ETDEWEB)

    Bhaduri, Budhendra L. [ORNL; Simon, AJ [Lawrence Livermore National Laboratory (LLNL); Allen, Melissa R. [ORNL; Sanyal, Jibonananda [ORNL; Stewart, Robert N. [ORNL; McManamay, Ryan A. [ORNL

    2018-01-01

    Energy and water generation and delivery systems are inherently interconnected. With worldwide demandfor energy growing, the energy sector is experiencing increasing competition for water. With increasingpopulation and changing environmental, socioeconomic, and demographic scenarios, new technology andinvestment decisions must be made for optimized and sustainable energy-water resource management. These decisions require novel scientific insights into the complex interdependencies of energy-water infrastructures across multiple space and time scales.

  13. 29 CFR 2700.56 - Discovery; general.

    Science.gov (United States)

    2010-07-01

    ...(c) or 111 of the Act has been filed. 30 U.S.C. 815(c) and 821. (e) Completion of discovery... 29 Labor 9 2010-07-01 2010-07-01 false Discovery; general. 2700.56 Section 2700.56 Labor... Hearings § 2700.56 Discovery; general. (a) Discovery methods. Parties may obtain discovery by one or more...

  14. 19 CFR 207.109 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 3 2010-04-01 2010-04-01 false Discovery. 207.109 Section 207.109 Customs Duties... and Committee Proceedings § 207.109 Discovery. (a) Discovery methods. All parties may obtain discovery under such terms and limitations as the administrative law judge may order. Discovery may be by one or...

  15. 30 CFR 44.24 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Discovery. 44.24 Section 44.24 Mineral... Discovery. Parties shall be governed in their conduct of discovery by appropriate provisions of the Federal... discovery. Alternative periods of time for discovery may be prescribed by the presiding administrative law...

  16. 19 CFR 356.20 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 3 2010-04-01 2010-04-01 false Discovery. 356.20 Section 356.20 Customs Duties... § 356.20 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery... sanctions proceeding. (b) Limitations on discovery. The administrative law judge shall place such limits...

  17. 24 CFR 180.500 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Discovery. 180.500 Section 180.500... OPPORTUNITY CONSOLIDATED HUD HEARING PROCEDURES FOR CIVIL RIGHTS MATTERS Discovery § 180.500 Discovery. (a) In general. This subpart governs discovery in aid of administrative proceedings under this part. Discovery in...

  18. 15 CFR 25.21 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Discovery. 25.21 Section 25.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery. (d...

  19. 39 CFR 963.14 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 39 Postal Service 1 2010-07-01 2010-07-01 false Discovery. 963.14 Section 963.14 Postal Service... PANDERING ADVERTISEMENTS STATUTE, 39 U.S.C. 3008 § 963.14 Discovery. Discovery is to be conducted on a... such discovery as he or she deems reasonable and necessary. Discovery may include one or more of the...

  20. 22 CFR 224.21 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Discovery. 224.21 Section 224.21 Foreign....21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of... parties, discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery...

  1. 75 FR 66766 - NIAID Blue Ribbon Panel Meeting on Adjuvant Discovery and Development

    Science.gov (United States)

    2010-10-29

    ..., identifies gaps in knowledge and capabilities, and defines NIAID's goals for the continued discovery...), will convene a Blue Ribbon Panel to provide expertise in developing a strategic plan and research... vaccines. NIAID has developed a draft Strategic Plan and Research Agenda for Adjuvant Discovery and...

  2. Drawbacks and benefits associated with inter-organizational collaboration along the discovery-development-delivery continuum: a cancer research network case study.

    Science.gov (United States)

    Harris, Jenine K; Provan, Keith G; Johnson, Kimberly J; Leischow, Scott J

    2012-07-25

    The scientific process around cancer research begins with scientific discovery, followed by development of interventions, and finally delivery of needed interventions to people with cancer. Numerous studies have identified substantial gaps between discovery and delivery in health research. Team science has been identified as a possible solution for closing the discovery to delivery gap; however, little is known about effective ways of collaborating within teams and across organizations. The purpose of this study was to determine benefits and drawbacks associated with organizational collaboration across the discovery-development-delivery research continuum. Representatives of organizations working on cancer research across a state answered a survey about how they collaborated with other cancer research organizations in the state and what benefits and drawbacks they experienced while collaborating. We used exponential random graph modeling to determine the association between these benefits and drawbacks and the presence of a collaboration tie between any two network members. Different drawbacks and benefits were associated with discovery, development, and delivery collaborations. The only consistent association across all three was with the drawback of difficulty due to geographic differences, which was negatively associated with collaboration, indicating that those organizations that had collaborated were less likely to perceive a barrier related to geography. The benefit, enhanced access to other knowledge, was positive and significant in the development and delivery networks, indicating that collaborating organizations viewed improved knowledge exchange as a benefit of collaboration. 'Acquisition of additional funding or other resources' and 'development of new tools and methods' were negatively significantly related to collaboration in these networks. So, although improved knowledge access was an outcome of collaboration, more tangible outcomes were not being

  3. Emerging concepts in biomarker discovery; The US-Japan workshop on immunological molecular markers in oncology

    Science.gov (United States)

    Tahara, Hideaki; Sato, Marimo; Thurin, Magdalena; Wang, Ena; Butterfield, Lisa H; Disis, Mary L; Fox, Bernard A; Lee, Peter P; Khleif, Samir N; Wigginton, Jon M; Ambs, Stefan; Akutsu, Yasunori; Chaussabel, Damien; Doki, Yuichiro; Eremin, Oleg; Fridman, Wolf Hervé; Hirohashi, Yoshihiko; Imai, Kohzoh; Jacobson, James; Jinushi, Masahisa; Kanamoto, Akira; Kashani-Sabet, Mohammed; Kato, Kazunori; Kawakami, Yutaka; Kirkwood, John M; Kleen, Thomas O; Lehmann, Paul V; Liotta, Lance; Lotze, Michael T; Maio, Michele; Malyguine, Anatoli; Masucci, Giuseppe; Matsubara, Hisahiro; Mayrand-Chung, Shawmarie; Nakamura, Kiminori; Nishikawa, Hiroyoshi; Palucka, A Karolina; Petricoin, Emanuel F; Pos, Zoltan; Ribas, Antoni; Rivoltini, Licia; Sato, Noriyuki; Shiku, Hiroshi; Slingluff, Craig L; Streicher, Howard; Stroncek, David F; Takeuchi, Hiroya; Toyota, Minoru; Wada, Hisashi; Wu, Xifeng; Wulfkuhle, Julia; Yaguchi, Tomonori; Zeskind, Benjamin; Zhao, Yingdong; Zocca, Mai-Britt; Marincola, Francesco M

    2009-01-01

    Supported by the Office of International Affairs, National Cancer Institute (NCI), the "US-Japan Workshop on Immunological Biomarkers in Oncology" was held in March 2009. The workshop was related to a task force launched by the International Society for the Biological Therapy of Cancer (iSBTc) and the United States Food and Drug Administration (FDA) to identify strategies for biomarker discovery and validation in the field of biotherapy. The effort will culminate on October 28th 2009 in the "iSBTc-FDA-NCI Workshop on Prognostic and Predictive Immunologic Biomarkers in Cancer", which will be held in Washington DC in association with the Annual Meeting. The purposes of the US-Japan workshop were a) to discuss novel approaches to enhance the discovery of predictive and/or prognostic markers in cancer immunotherapy; b) to define the state of the science in biomarker discovery and validation. The participation of Japanese and US scientists provided the opportunity to identify shared or discordant themes across the distinct immune genetic background and the diverse prevalence of disease between the two Nations. Converging concepts were identified: enhanced knowledge of interferon-related pathways was found to be central to the understanding of immune-mediated tissue-specific destruction (TSD) of which tumor rejection is a representative facet. Although the expression of interferon-stimulated genes (ISGs) likely mediates the inflammatory process leading to tumor rejection, it is insufficient by itself and the associated mechanisms need to be identified. It is likely that adaptive immune responses play a broader role in tumor rejection than those strictly related to their antigen-specificity; likely, their primary role is to trigger an acute and tissue-specific inflammatory response at the tumor site that leads to rejection upon recruitment of additional innate and adaptive immune mechanisms. Other candidate systemic and/or tissue-specific biomarkers were recognized that

  4. Emerging concepts in biomarker discovery; The US-Japan workshop on immunological molecular markers in oncology

    Directory of Open Access Journals (Sweden)

    Rivoltini Licia

    2009-06-01

    Full Text Available Abstract Supported by the Office of International Affairs, National Cancer Institute (NCI, the "US-Japan Workshop on Immunological Biomarkers in Oncology" was held in March 2009. The workshop was related to a task force launched by the International Society for the Biological Therapy of Cancer (iSBTc and the United States Food and Drug Administration (FDA to identify strategies for biomarker discovery and validation in the field of biotherapy. The effort will culminate on October 28th 2009 in the "iSBTc-FDA-NCI Workshop on Prognostic and Predictive Immunologic Biomarkers in Cancer", which will be held in Washington DC in association with the Annual Meeting. The purposes of the US-Japan workshop were a to discuss novel approaches to enhance the discovery of predictive and/or prognostic markers in cancer immunotherapy; b to define the state of the science in biomarker discovery and validation. The participation of Japanese and US scientists provided the opportunity to identify shared or discordant themes across the distinct immune genetic background and the diverse prevalence of disease between the two Nations. Converging concepts were identified: enhanced knowledge of interferon-related pathways was found to be central to the understanding of immune-mediated tissue-specific destruction (TSD of which tumor rejection is a representative facet. Although the expression of interferon-stimulated genes (ISGs likely mediates the inflammatory process leading to tumor rejection, it is insufficient by itself and the associated mechanisms need to be identified. It is likely that adaptive immune responses play a broader role in tumor rejection than those strictly related to their antigen-specificity; likely, their primary role is to trigger an acute and tissue-specific inflammatory response at the tumor site that leads to rejection upon recruitment of additional innate and adaptive immune mechanisms. Other candidate systemic and/or tissue-specific biomarkers

  5. Mining manufacturing data for discovery of high productivity process characteristics.

    Science.gov (United States)

    Charaniya, Salim; Le, Huong; Rangwala, Huzefa; Mills, Keri; Johnson, Kevin; Karypis, George; Hu, Wei-Shou

    2010-06-01

    Modern manufacturing facilities for bioproducts are highly automated with advanced process monitoring and data archiving systems. The time dynamics of hundreds of process parameters and outcome variables over a large number of production runs are archived in the data warehouse. This vast amount of data is a vital resource to comprehend the complex characteristics of bioprocesses and enhance production robustness. Cell culture process data from 108 'trains' comprising production as well as inoculum bioreactors from Genentech's manufacturing facility were investigated. Each run constitutes over one-hundred on-line and off-line temporal parameters. A kernel-based approach combined with a maximum margin-based support vector regression algorithm was used to integrate all the process parameters and develop predictive models for a key cell culture performance parameter. The model was also used to identify and rank process parameters according to their relevance in predicting process outcome. Evaluation of cell culture stage-specific models indicates that production performance can be reliably predicted days prior to harvest. Strong associations between several temporal parameters at various manufacturing stages and final process outcome were uncovered. This model-based data mining represents an important step forward in establishing a process data-driven knowledge discovery in bioprocesses. Implementation of this methodology on the manufacturing floor can facilitate a real-time decision making process and thereby improve the robustness of large scale bioprocesses. 2010 Elsevier B.V. All rights reserved.

  6. Sugar Transporters in Plants: New Insights and Discoveries.

    Science.gov (United States)

    Julius, Benjamin T; Leach, Kristen A; Tran, Thu M; Mertz, Rachel A; Braun, David M

    2017-09-01

    Carbohydrate partitioning is the process of carbon assimilation and distribution from source tissues, such as leaves, to sink tissues, such as stems, roots and seeds. Sucrose, the primary carbohydrate transported long distance in many plant species, is loaded into the phloem and unloaded into distal sink tissues. However, many factors, both genetic and environmental, influence sucrose metabolism and transport. Therefore, understanding the function and regulation of sugar transporters and sucrose metabolic enzymes is key to improving agriculture. In this review, we highlight recent findings that (i) address the path of phloem loading of sucrose in rice and maize leaves; (ii) discuss the phloem unloading pathways in stems and roots and the sugar transporters putatively involved; (iii) describe how heat and drought stress impact carbohydrate partitioning and phloem transport; (iv) shed light on how plant pathogens hijack sugar transporters to obtain carbohydrates for pathogen survival, and how the plant employs sugar transporters to defend against pathogens; and (v) discuss novel roles for sugar transporters in plant biology. These exciting discoveries and insights provide valuable knowledge that will ultimately help mitigate the impending societal challenges due to global climate change and a growing population by improving crop yield and enhancing renewable energy production. © The Author 2017. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  7. Knowledge Sharing is Knowledge Creation

    DEFF Research Database (Denmark)

    Greve, Linda

    2015-01-01

    Knowledge sharing and knowledge transfer are important to knowledge communication. However when groups of knowledge workers engage in knowledge communication activities, it easily turns into mere mechanical information processing despite other ambitions. This article relates literature of knowledge...... communication and knowledge creation to an intervention study in a large Danish food production company. For some time a specific group of employees uttered a wish for knowledge sharing, but it never really happened. The group was observed and submitted to metaphor analysis as well as analysis of co...

  8. Discovery Mondays: Surveyors' Tools

    CERN Multimedia

    2003-01-01

    Surveyors of all ages, have your rulers and compasses at the ready! This sixth edition of Discovery Monday is your chance to learn about the surveyor's tools - the state of the art in measuring instruments - and see for yourself how they work. With their usual daunting precision, the members of CERN's Surveying Group have prepared some demonstrations and exercises for you to try. Find out the techniques for ensuring accelerator alignment and learn about high-tech metrology systems such as deviation indicators, tracking lasers and total stations. The surveyors will show you how they precisely measure magnet positioning, with accuracy of a few thousandths of a millimetre. You can try your hand at precision measurement using different types of sensor and a modern-day version of the Romans' bubble level, accurate to within a thousandth of a millimetre. You will learn that photogrammetry techniques can transform even a simple digital camera into a remarkable measuring instrument. Finally, you will have a chance t...

  9. Knowledge Management.

    Science.gov (United States)

    1999

    The first of the four papers in this symposium, "Knowledge Management and Knowledge Dissemination" (Wim J. Nijhof), presents two case studies exploring the strategies companies use in sharing and disseminating knowledge and expertise among employees. "A Theory of Knowledge Management" (Richard J. Torraco), develops a conceptual…

  10. Discovery of Paradigm Dependencies

    OpenAIRE

    Sun, Jizhou; Li, Jianzhong; Gao, Hong

    2017-01-01

    Missing and incorrect values often cause serious consequences. To deal with these data quality problems, a class of common employed tools are dependency rules, such as Functional Dependencies (FDs), Conditional Functional Dependencies (CFDs) and Edition Rules (ERs), etc. The stronger expressing ability a dependency has, data with the better quality can be obtained. To the best of our knowledge, all previous dependencies treat each attribute value as a non-splittable whole. Actually however, i...

  11. Managing Knowledge

    OpenAIRE

    Connolly, Niall

    2013-01-01

    This paper provides a perspective on what knowledge is, why knowledge is important, and how we might encourage good knowledge behaviours. A knowledge management framework is described, and although the framework is project management-centric the basic principles are transferrable to other contexts. From a strategic perspective, knowledge can be considered an asset that has the potential to provide a competitive advantage provided that it has intrinsic value, it is not easily accessible by ...

  12. 'The Lusiads', poem of discovery

    Directory of Open Access Journals (Sweden)

    Natasha Furlan Felizi

    2016-07-01

    Full Text Available The article proposes reading Os Lusíadas as a discovery journey. Discovery here read as aletheia or “revelation”, as proposed by Sophia de Mello Brey­ner Andresen in 1980. Using Martin Heidegger’s notion of aletheia in the book Parmenides along with Jorge de Sena and Sophia de Mello Breyner Andresen reflections on Camões, I’ll seek to point out alternative readings for Os Lusíadas as a “discovery journey”.

  13. Weaving Indigenous Agricultural Knowledge with Formal Education to Enhance Community Food Security: School Competition as a Pedagogical Space in Rural Anchetty, India

    Science.gov (United States)

    Shukla, Shailesh; Barkman, Janna; Patel, Kirit

    2017-01-01

    Like many socially and economically disadvantaged farming communities around the world, the Anchetty region of Tamil Nadu, India, has been experiencing serious food security challenges mainly due to the loss of traditional foods such as small millets and associated crops (SMAC) and associated indigenous agricultural knowledge (IAK). Drawing on…

  14. Discovery of natural resources

    Science.gov (United States)

    Guild, P.W.

    1976-01-01

    Mankind will continue to need ores of more or less the types and grades used today to supply its needs for new mineral raw materials, at least until fusion or some other relatively cheap, inexhaustible energy source is developed. Most deposits being mined today were exposed at the surface or found by relatively simple geophysical or other prospecting techniques, but many of these will be depleted in the foreseeable future. The discovery of deeper or less obvious deposits to replace them will require the conjunction of science and technology to deduce the laws that governed the concentration of elements into ores and to detect and evaluate the evidence of their whereabouts. Great theoretical advances are being made to explain the origins of ore deposits and understand the general reasons for their localization. These advances have unquestionable value for exploration. Even a large deposit is, however, very small, and, with few exceptions, it was formed under conditions that have long since ceased to exist. The explorationist must suppress a great deal of "noise" to read and interpret correctly the "signals" that can define targets and guide the drilling required to find it. Is enough being done to ensure the long-term availability of mineral raw materials? The answer is probably no, in view of the expanding consumption and the difficulty of finding new deposits, but ingenuity, persistence, and continued development of new methods and tools to add to those already at hand should put off the day of "doing without" for many years. The possibility of resource exhaustion, especially in view of the long and increasing lead time needed to carry out basic field and laboratory studies in geology, geophysics, and geochemistry and to synthesize and analyze the information gained from them counsels against any letting down of our guard, however (17). Research and exploration by government, academia, and industry must be supported and encouraged; we cannot wait until an eleventh

  15. Supernovae Discovery Efficiency

    Science.gov (United States)

    John, Colin

    2018-01-01

    Abstract:We present supernovae (SN) search efficiency measurements for recent Hubble Space Telescope (HST) surveys. Efficiency is a key component to any search, and is important parameter as a correction factor for SN rates. To achieve an accurate value for efficiency, many supernovae need to be discoverable in surveys. This cannot be achieved from real SN only, due to their scarcity, so fake SN are planted. These fake supernovae—with a goal of realism in mind—yield an understanding of efficiency based on position related to other celestial objects, and brightness. To improve realism, we built a more accurate model of supernovae using a point-spread function. The next improvement to realism is planting these objects close to galaxies and of various parameters of brightness, magnitude, local galactic brightness and redshift. Once these are planted, a very accurate SN is visible and discoverable by the searcher. It is very important to find factors that affect this discovery efficiency. Exploring the factors that effect detection yields a more accurate correction factor. Further inquires into efficiency give us a better understanding of image processing, searching techniques and survey strategies, and result in an overall higher likelihood to find these events in future surveys with Hubble, James Webb, and WFIRST telescopes. After efficiency is discovered and refined with many unique surveys, it factors into measurements of SN rates versus redshift. By comparing SN rates vs redshift against the star formation rate we can test models to determine how long star systems take from the point of inception to explosion (delay time distribution). This delay time distribution is compared to SN progenitors models to get an accurate idea of what these stars were like before their deaths.

  16. EDITORIAL: Enhancing nanolithography Enhancing nanolithography

    Science.gov (United States)

    Demming, Anna

    2012-01-01

    Lithography was invented in late 18th century Bavaria by an ambitious young playwright named Alois Senefelder. Senefelder experimented with stone, wax, water and ink in the hope of finding a way of reproducing text so that he might financially gain from a wider distribution of his already successful scripts. His discovery not only facilitated the profitability of his plays, but also provided the world with an affordable printing press that would ultimately democratize the dissemination of art, knowledge and literature. Since Senefelder, experiments in lithography have continued with a range of innovations including the use of electron beams and UV that allow increasingly higher-resolution features [1, 2]. Applications for this have now breached the limits of paper printing into the realms of semiconductor and microelectronic mechanical systems technology. In this issue, researchers demonstrate a technique for fabricating periodic features in poly(3,4-ethylene dioxythiophene)-poly(styrenesulfonate) (PEDOT-PSS) [3]. Their method combines field enhancements from silica nanospheres with laser-interference lithography to provide a means of patterning a polymer that has the potential to open the market of low-end, high-volume microelectronics. Laser-interference lithography has already been used successfully in patterning. Researchers in Korea used laser-interference lithography to generate stamps for imprinting a two-dimensional photonic crystal structure into green light emitting diodes (LEDs) [4]. The imprinted patterns comprised depressions 100 nm deep and 180 nm wide with a periodicity of 295 nm. In comparison with unpatterned LEDs, the intensity of photoluminescence was enhanced by a factor of seven in the LEDs that had the photonic crystal structures imprinted in them. The potential of exploiting field enhancements around nanostructures for new technologies has also attracted a great deal of attention. Researchers in the USA and Australia have used the field

  17. Knowledge Sharing

    DEFF Research Database (Denmark)

    Holdt Christensen, Peter

    The concept of knowledge management has, indeed, become a buzzword that every single organization is expected to practice and live by. Knowledge management is about managing the organization's knowledge for the common good of the organization -but practicing knowledge management is not as simple...... as that. This article focuses on knowledge sharing as the process seeking to reduce the resources spent on reinventing the wheel.The article introduces the concept of time sensitiveness; i.e. that knowledge is either urgently needed, or not that urgently needed. Furthermore, knowledge sharing...... is considered as either a push or pull system. Four strategies for sharing knowledge - help, post-it, manuals and meeting, and advice are introduced. Each strategy requires different channels for sharing knowledge. An empirical analysis in a production facility highlights how the strategies can be practiced....

  18. Knowledge management

    DEFF Research Database (Denmark)

    Foss, Nicolai Juul; Mahnke, Volker

    2003-01-01

    Knowledge management has emerged as a very successful organization practice and has beenextensively treated in a large body of academic work. Surprisingly, however, organizationaleconomics (i.e., transaction cost economics, agency theory, team theory and property rightstheory) has played no role...... in the development of knowledge management. We argue thatorganizational economics insights can further the theory and practice of knowledge managementin several ways. Specifically, we apply notions of contracting, team production,complementaries, hold-up, etc. to knowledge management issues (i.e., creating...... and integrationknowledge, rewarding knowledge workers, etc.) , and derive refutable implications that are novelto the knowledge management field from our discussion....

  19. mySearch changed my life – a resource discovery journey

    OpenAIRE

    Crowley, Emma J.

    2013-01-01

    mySearch: the federated years mySearch: choosing a new platform mySearch: EBSCO Discovery Service (EDS) Implementing a new system Technical challenges Has resource discovery enhanced experiences at BU? Ongoing challenges Implications for library management systems Implications for information literacy Questions

  20. 78 FR 69363 - Lake Tahoe Basin Management Unit, California, Heavenly Mountain Resort Epic Discovery Project

    Science.gov (United States)

    2013-11-19

    ... DEPARTMENT OF AGRICULTURE Forest Service Lake Tahoe Basin Management Unit, California, Heavenly Mountain Resort Epic Discovery Project AGENCY: Lake Tahoe Basin Management Unit, Forest Service, USDA...: The Epic Discovery Project is intended to enhance summer activities in response to the USDA Forest...

  1. State of the Art in Tumor Antigen and Biomarker Discovery

    International Nuclear Information System (INIS)

    Even-Desrumeaux, Klervi; Baty, Daniel; Chames, Patrick

    2011-01-01

    Our knowledge of tumor immunology has resulted in multiple approaches for the treatment of cancer. However, a gap between research of new tumors markers and development of immunotherapy has been established and very few markers exist that can be used for treatment. The challenge is now to discover new targets for active and passive immunotherapy. This review aims at describing recent advances in biomarkers and tumor antigen discovery in terms of antigen nature and localization, and is highlighting the most recent approaches used for their discovery including “omics” technology

  2. RAS - Screens & Assays - Drug Discovery

    Science.gov (United States)

    The RAS Drug Discovery group aims to develop assays that will reveal aspects of RAS biology upon which cancer cells depend. Successful assay formats are made available for high-throughput screening programs to yield potentially effective drug compounds.

  3. Antibody informatics for drug discovery

    DEFF Research Database (Denmark)

    Shirai, Hiroki; Prades, Catherine; Vita, Randi

    2014-01-01

    to the antibody science in every project in antibody drug discovery. Recent experimental technologies allow for the rapid generation of large-scale data on antibody sequences, affinity, potency, structures, and biological functions; this should accelerate drug discovery research. Therefore, a robust bioinformatic...... infrastructure for these large data sets has become necessary. In this article, we first identify and discuss the typical obstacles faced during the antibody drug discovery process. We then summarize the current status of three sub-fields of antibody informatics as follows: (i) recent progress in technologies...... for antibody rational design using computational approaches to affinity and stability improvement, as well as ab-initio and homology-based antibody modeling; (ii) resources for antibody sequences, structures, and immune epitopes and open drug discovery resources for development of antibody drugs; and (iii...

  4. Discovery of the iron isotopes

    International Nuclear Information System (INIS)

    Schuh, A.; Fritsch, A.; Heim, M.; Shore, A.; Thoennessen, M.

    2010-01-01

    Twenty-eight iron isotopes have been observed so far and the discovery of these isotopes is discussed here. For each isotope a brief summary of the first refereed publication, including the production and identification method, is presented.

  5. Discovery of the silver isotopes

    International Nuclear Information System (INIS)

    Schuh, A.; Fritsch, A.; Ginepro, J.Q.; Heim, M.; Shore, A.; Thoennessen, M.

    2010-01-01

    Thirty-eight silver isotopes have been observed so far and the discovery of these isotopes is discussed here. For each isotope a brief summary of the first refereed publication, including the production and identification method, is presented.

  6. Synthetic biology of antimicrobial discovery

    Science.gov (United States)

    Zakeri, Bijan; Lu, Timothy K.

    2012-01-01

    Antibiotic discovery has a storied history. From the discovery of penicillin by Sir Alexander Fleming to the relentless quest for antibiotics by Selman Waksman, the stories have become like folklore, used to inspire future generations of scientists. However, recent discovery pipelines have run dry at a time when multidrug resistant pathogens are on the rise. Nature has proven to be a valuable reservoir of antimicrobial agents, which are primarily produced by modularized biochemical pathways. Such modularization is well suited to remodeling by an interdisciplinary approach that spans science and engineering. Herein, we discuss the biological engineering of small molecules, peptides, and non-traditional antimicrobials and provide an overview of the growing applicability of synthetic biology to antimicrobials discovery. PMID:23654251

  7. Discovery of the cadmium isotopes

    International Nuclear Information System (INIS)

    Amos, S.; Thoennessen, M.

    2010-01-01

    Thirty-seven cadmium isotopes have been observed so far and the discovery of these isotopes is discussed here. For each isotope a brief summary of the first refereed publication, including the production and identification method, is presented.

  8. Discoveries of isotopes by fission

    Indian Academy of Sciences (India)

    country of discovery as well as the production mechanism used to produce the isotopes. ... the disintegration products of bombarded uranium, as a consequence of a ..... advanced accelerator and newly developed separation and detection ...

  9. Synthetic biology of antimicrobial discovery.

    Science.gov (United States)

    Zakeri, Bijan; Lu, Timothy K

    2013-07-19

    Antibiotic discovery has a storied history. From the discovery of penicillin by Sir Alexander Fleming to the relentless quest for antibiotics by Selman Waksman, the stories have become like folklore used to inspire future generations of scientists. However, recent discovery pipelines have run dry at a time when multidrug-resistant pathogens are on the rise. Nature has proven to be a valuable reservoir of antimicrobial agents, which are primarily produced by modularized biochemical pathways. Such modularization is well suited to remodeling by an interdisciplinary approach that spans science and engineering. Herein, we discuss the biological engineering of small molecules, peptides, and non-traditional antimicrobials and provide an overview of the growing applicability of synthetic biology to antimicrobials discovery.

  10. The discovery of 'heavy light'

    International Nuclear Information System (INIS)

    Anon.

    1983-01-01

    The history of the discoveries of fundamental quanta is described starting from Maxwell's theory of electromagnetism up to the development of a theory of weak interaction and the detection of the W and Z bosons. (HSI).

  11. Discovery – Development of Rituximab

    Science.gov (United States)

    NCI funded the development of rituximab, one of the first monoclonal antibody cancer treatments. With the discovery of rituximab, more than 70 percent of patients diagnosed with non-hodgkin lymphoma now live five years past their initial diagnosis.

  12. Does the 'Teddy Bear Hospital' enhance preschool children's knowledge? A pilot study with a pre/post-case control design in Germany.

    Science.gov (United States)

    Leonhardt, Corinna; Margraf-Stiksrud, Jutta; Badners, Larissa; Szerencsi, Andrea; Maier, Rolf F

    2014-10-01

    The 'Teddy Bear Hospital' is a medical students' project, which has been increasingly established in many countries. To evaluate this concept, we examined the effects of a German Teddy Bear Hospital on children's knowledge relating to their body, health and disease. Using a quasi-experimental pre/post design, we examined 131 preschool children from 14 German kindergartens with pictorial interview-based scales. The analysis of covariance revealed that the children who visited the Teddy Bear Hospital had a significantly better knowledge concerning their body, health and disease than the children from the control group. This German Teddy Bear Hospital is a good health education vehicle for preschool children. © The Author(s) 2013.

  13. Can Web 2.0 Enhance Community Participation in an Institutional Repository? The Case of PocketKnowledge at Teachers College, Columbia University

    Science.gov (United States)

    Cocciolo, Anthony

    2010-01-01

    This project investigates if a Web 2.0 approach to designing an institutional repository can positively impact community participation. To study this, two institutional repositories (one Web 2.0, the other not) are used within the same institution. Results indicate that the use of a Web 2.0 approach significantly enhances community participation.…

  14. The development and evaluation of a computer-based resource to enhance the education of pre-registration nursing students regarding knowledge and attitudes towards pain management

    OpenAIRE

    Keefe, Gemma

    2011-01-01

    The study is the first in its field to quantitatively explore the effects of e-learning to improve knowledge and attitudes towards pain management. Pain is a fundamental reason for patients seeking healthcare, yet in recent years it has been acknowledged that the importance of pain management is often overlooked or misunderstood, with poor pain education frequently blamed. In fact, the extent of pain education is severely limited in current nursing curricula, primarily due to a lack of priori...

  15. Integrated approach to e-learning enhanced both subjective and objective knowledge of aEEG in a neonatal intensive care unit.

    Science.gov (United States)

    Poon, W B; Tagamolila, V; Toh, Y P; Cheng, Z R

    2015-03-01

    Various meta-analyses have shown that e-learning is as effective as traditional methods of continuing professional education. However, there are some disadvantages to e-learning, such as possible technical problems, the need for greater self-discipline, cost involved in developing programmes and limited direct interaction. Currently, most strategies for teaching amplitude-integrated electroencephalography (aEEG) in neonatal intensive care units (NICUs) worldwide depend on traditional teaching methods. We implemented a programme that utilised an integrated approach to e-learning. The programme consisted of three sessions of supervised protected time e-learning in an NICU. The objective and subjective effectiveness of the approach was assessed through surveys administered to participants before and after the programme. A total of 37 NICU staff (32 nurses and 5 doctors) participated in the study. 93.1% of the participants appreciated the need to acquire knowledge of aEEG. We also saw a statistically significant improvement in the subjective knowledge score (p = 0.041) of the participants. The passing rates for identifying abnormal aEEG tracings (defined as ≥ 3 correct answers out of 5) also showed a statistically significant improvement (from 13.6% to 81.8%, p e-learning can help improve subjective and objective knowledge of aEEG.

  16. Students Excited by Stellar Discovery

    Science.gov (United States)

    2011-02-01

    ," confessed Thompson. "I'm going to study astrophysics." Snider is pleased with the idea of contributing to scientific knowledge. "I hope that astronomers at Green Bank and around the world can learn something from the discovery," he said. Mabry is simply awed. "We've actually been able to experience something," she said. The PSC will continue through 2011. Teachers interested in participating in the program can learn more at this link, http://www.gb.nrao.edu/epo/psc.shtml.

  17. Get Involved in Planetary Discoveries through New Worlds, New Discoveries

    Science.gov (United States)

    Shupla, Christine; Shipp, S. S.; Halligan, E.; Dalton, H.; Boonstra, D.; Buxner, S.; SMD Planetary Forum, NASA

    2013-01-01

    "New Worlds, New Discoveries" is a synthesis of NASA’s 50-year exploration history which provides an integrated picture of our new understanding of our solar system. As NASA spacecraft head to and arrive at key locations in our solar system, "New Worlds, New Discoveries" provides an integrated picture of our new understanding of the solar system to educators and the general public! The site combines the amazing discoveries of past NASA planetary missions with the most recent findings of ongoing missions, and connects them to the related planetary science topics. "New Worlds, New Discoveries," which includes the "Year of the Solar System" and the ongoing celebration of the "50 Years of Exploration," includes 20 topics that share thematic solar system educational resources and activities, tied to the national science standards. This online site and ongoing event offers numerous opportunities for the science community - including researchers and education and public outreach professionals - to raise awareness, build excitement, and make connections with educators, students, and the public about planetary science. Visitors to the site will find valuable hands-on science activities, resources and educational materials, as well as the latest news, to engage audiences in planetary science topics and their related mission discoveries. The topics are tied to the big questions of planetary science: how did the Sun’s family of planets and bodies originate and how have they evolved? How did life begin and evolve on Earth, and has it evolved elsewhere in our solar system? Scientists and educators are encouraged to get involved either directly or by sharing "New Worlds, New Discoveries" and its resources with educators, by conducting presentations and events, sharing their resources and events to add to the site, and adding their own public events to the site’s event calendar! Visit to find quality resources and ideas. Connect with educators, students and the public to

  18. Accessible Knowledge - Knowledge on Accessibility

    DEFF Research Database (Denmark)

    Kirkeby, Inge Mette

    2015-01-01

    Although serious efforts are made internationally and nationally, it is a slow process to make our physical environment accessible. In the actual design process, architects play a major role. But what kinds of knowledge, including research-based knowledge, do practicing architects make use of when...... designing accessible environments? The answer to the question is crucially important since it affects how knowledge is distributed and how accessibility can be ensured. In order to get first-hand knowledge about the design process and the sources from which they gain knowledge, 11 qualitative interviews...... were conducted with architects with experience of designing for accessibility. The analysis draws on two theoretical distinctions. The first is research-based knowledge versus knowledge used by architects. The second is context-independent knowledge versus context-dependent knowledge. The practitioners...

  19. Interprofessional Simulations Promote Knowledge Retention and Enhance Perceptions of Teamwork Skills in a Surgical-Trauma-Burn Intensive Care Unit Setting.

    Science.gov (United States)

    George, Katie L; Quatrara, Beth

    The current state of health care encompasses highly acute, complex patients, managed with ever-changing technology. The ability to function proficiently in critical care relies on knowledge, technical skills, and interprofessional teamwork. Integration of these factors can improve patient outcomes. Simulation provides "hands-on" practice and allows for the integration of teamwork into knowledge/skill training. However, simulation can require a significant investment of time, effort, and financial resources. The Institute of Medicine recommendations from 2015 include "strengthening the evidence base for interprofessional education (IPE)" and "linking IPE with changes in collaborative behavior." In one surgical-trauma-burn intensive care unit (STBICU), no IPE existed. The highly acute and diverse nature of the patients served by the unit highlights the importance of appropriate training. This is heightened during critical event situations where patients deteriorate rapidly and the team intervenes swiftly. The aims of this study were to (1) evaluate knowledge retention and analyze changes in perceptions of teamwork among nurses and resident physicians in a STBICU setting after completion of an interprofessional critical event simulation and (2) provide insight for future interprofessional simulations (IPSs), including the ideal frequency of such training, associated cost, and potential effect on nursing turnover. A comparison-cohort pilot study was developed to evaluate knowledge retention and analyze changes in perceptions of teamwork. A 1-hour critical event IPS was held for nurses and resident physicians in a STBICU setting. A traumatic brain injury patient with elevated intracranial pressure, rapid deterioration, and cardiac arrest was utilized for the simulation scenario. The simulation required the team to use interventions to reduce elevated intracranial pressure and then perform cardiac resuscitation according to Advanced Cardiac Life Support guidelines. A

  20. Skin too thin? The developing utility of zebrafish skin (neuro)pharmacology for CNS drug discovery research.

    Science.gov (United States)

    Nguyen, Michael; Poudel, Manoj K; Stewart, Adam Michael; Kalueff, Allan V

    2013-09-01

    Skin coloration can be affected by many genetic, environmental and pharmacological factors. Zebrafish (Danio rerio) are a useful and versatile model organism in biomedical research due to their genetic tractability, physiological homology to mammals, low cost, reproducibility and high throughput. Zebrafish coloration is mediated by chromatophores - the skin color pigment cells largely controlled by endocrine and neural mechanisms. The characteristic darkening of zebrafish skin is caused by the dispersion (and paling - by aggregation) of melanosomes (pigment-containing organelles), which show high homology to mammalian structures. Various pharmacological agents potently affect zebrafish coloration - the phenotype that often accompanies behavioral effects of the drugs, and may be used for drug discovery. Although zebrafish behavior and skin responses are usually not directly related, they share common regulatory (neural, endocrine) mechanisms, and therefore may be assessed in parallel during psychotropic drug screening. For example, some psychoactive drugs can potently affect zebrafish skin coloration. Can we use this knowledge to refine phenotype-driven psychotropic drug discovery? Here, we present current models using zebrafish skin coloration assays, and discuss how these models may be applied to enhance in vivo CNS drug discovery. Copyright © 2013 Elsevier Inc. All rights reserved.