The Use of Supplementary Materials in English Foreign Language Classes in Ecuadorian Secondary Schools

ERIC Educational Resources Information Center

Dodd, Alexander R.; Camacho, Gina K.; Morocho, Elsa L.; Paredes, Fabián M.; Zúñiga, Alexandra; Pinza, Eliana I.; Toro, Lisset V.; Vargas, Alba B.; Benítez, Carmen D.; Rogers, Sylvia

2015-01-01

This mixed-methods study investigated the use of supplementary materials by EFL teachers in Ecuadorian secondary schools. Via the use of teacher interviews (n = 12) it was found that teachers believe the use of supplementary materials increases the motivation of the students, which in-turn improves the learning possibilities of the students. The…

E-learning in medical education in resource constrained low- and middle-income countries.

PubMed

Frehywot, Seble; Vovides, Yianna; Talib, Zohray; Mikhail, Nadia; Ross, Heather; Wohltjen, Hannah; Bedada, Selam; Korhumel, Kristine; Koumare, Abdel Karim; Scott, James

2013-02-04

In the face of severe faculty shortages in resource-constrained countries, medical schools look to e-learning for improved access to medical education. This paper summarizes the literature on e-learning in low- and middle-income countries (LMIC), and presents the spectrum of tools and strategies used. Researchers reviewed literature using terms related to e-learning and pre-service education of health professionals in LMIC. Search terms were connected using the Boolean Operators "AND" and "OR" to capture all relevant article suggestions. Using standard decision criteria, reviewers narrowed the article suggestions to a final 124 relevant articles. Of the relevant articles found, most referred to e-learning in Brazil (14 articles), India (14), Egypt (10) and South Africa (10). While e-learning has been used by a variety of health workers in LMICs, the majority (58%) reported on physician training, while 24% focused on nursing, pharmacy and dentistry training. Although reasons for investing in e-learning varied, expanded access to education was at the core of e-learning implementation which included providing supplementary tools to support faculty in their teaching, expanding the pool of faculty by connecting to partner and/or community teaching sites, and sharing of digital resources for use by students. E-learning in medical education takes many forms. Blended learning approaches were the most common methodology presented (49 articles) of which computer-assisted learning (CAL) comprised the majority (45 articles). Other approaches included simulations and the use of multimedia software (20 articles), web-based learning (14 articles), and eTutor/eMentor programs (3 articles). Of the 69 articles that evaluated the effectiveness of e-learning tools, 35 studies compared outcomes between e-learning and other approaches, while 34 studies qualitatively analyzed student and faculty attitudes toward e-learning modalities. E-learning in medical education is a means to an end, rather than the end in itself. Utilizing e-learning can result in greater educational opportunities for students while simultaneously enhancing faculty effectiveness and efficiency. However, this potential of e-learning assumes a certain level of institutional readiness in human and infrastructural resources that is not always present in LMICs. Institutional readiness for e-learning adoption ensures the alignment of new tools to the educational and economic context.

E-learning in medical education in resource constrained low- and middle-income countries

PubMed Central

2013-01-01

Background In the face of severe faculty shortages in resource-constrained countries, medical schools look to e-learning for improved access to medical education. This paper summarizes the literature on e-learning in low- and middle-income countries (LMIC), and presents the spectrum of tools and strategies used. Methods Researchers reviewed literature using terms related to e-learning and pre-service education of health professionals in LMIC. Search terms were connected using the Boolean Operators “AND” and “OR” to capture all relevant article suggestions. Using standard decision criteria, reviewers narrowed the article suggestions to a final 124 relevant articles. Results Of the relevant articles found, most referred to e-learning in Brazil (14 articles), India (14), Egypt (10) and South Africa (10). While e-learning has been used by a variety of health workers in LMICs, the majority (58%) reported on physician training, while 24% focused on nursing, pharmacy and dentistry training. Although reasons for investing in e-learning varied, expanded access to education was at the core of e-learning implementation which included providing supplementary tools to support faculty in their teaching, expanding the pool of faculty by connecting to partner and/or community teaching sites, and sharing of digital resources for use by students. E-learning in medical education takes many forms. Blended learning approaches were the most common methodology presented (49 articles) of which computer-assisted learning (CAL) comprised the majority (45 articles). Other approaches included simulations and the use of multimedia software (20 articles), web-based learning (14 articles), and eTutor/eMentor programs (3 articles). Of the 69 articles that evaluated the effectiveness of e-learning tools, 35 studies compared outcomes between e-learning and other approaches, while 34 studies qualitatively analyzed student and faculty attitudes toward e-learning modalities. Conclusions E-learning in medical education is a means to an end, rather than the end in itself. Utilizing e-learning can result in greater educational opportunities for students while simultaneously enhancing faculty effectiveness and efficiency. However, this potential of e-learning assumes a certain level of institutional readiness in human and infrastructural resources that is not always present in LMICs. Institutional readiness for e-learning adoption ensures the alignment of new tools to the educational and economic context. PMID:23379467

E-learning for medical imaging specialists: introducing blended learning in a nuclear medicine specialist course.

PubMed

Haslerud, Torjan; Tulipan, Andreas Julius; Gray, Robert M; Biermann, Martin

2017-07-01

While e-learning has become an important tool in teaching medical students, the training of specialists in medical imaging is still dominated by lecture-based courses. To assess the potential of e-learning in specialist education in medical imaging. An existing lecture-based five-day course in Clinical Nuclear Medicine (NM) was enhanced by e-learning resources and activities, including practical exercises. An anonymized survey was conducted after participants had completed and passed the multiple choice electronic course examination. Twelve out of 15 course participants (80%) responded. Overall satisfaction with the new course format was high, but 25% of the respondents wanted more interactive elements such as discussions and practical exercises. The importance of lecture handouts and supplementary online material such as selected original articles and professional guidelines was affirmed by all the respondents (92% fully, 8% partially), while 75% fully and 25% partially agreed that the lectures had been interesting and relevant. E-learning represents a hitherto unrealized potential in the education of medical specialists. It may expedite training of medical specialists while at the same time containing costs.

The OGCleaner: filtering false-positive homology clusters.

PubMed

Fujimoto, M Stanley; Suvorov, Anton; Jensen, Nicholas O; Clement, Mark J; Snell, Quinn; Bybee, Seth M

2017-01-01

Detecting homologous sequences in organisms is an essential step in protein structure and function prediction, gene annotation and phylogenetic tree construction. Heuristic methods are often employed for quality control of putative homology clusters. These heuristics, however, usually only apply to pairwise sequence comparison and do not examine clusters as a whole. We present the Orthology Group Cleaner (the OGCleaner), a tool designed for filtering putative orthology groups as homology or non-homology clusters by considering all sequences in a cluster. The OGCleaner relies on high-quality orthologous groups identified in OrthoDB to train machine learning algorithms that are able to distinguish between true-positive and false-positive homology groups. This package aims to improve the quality of phylogenetic tree construction especially in instances of lower-quality transcriptome assemblies. https://github.com/byucsl/ogcleaner CONTACT: sfujimoto@gmail.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Anatomical entity mention recognition at literature scale

PubMed Central

Pyysalo, Sampo; Ananiadou, Sophia

2014-01-01

Motivation: Anatomical entities ranging from subcellular structures to organ systems are central to biomedical science, and mentions of these entities are essential to understanding the scientific literature. Despite extensive efforts to automatically analyze various aspects of biomedical text, there have been only few studies focusing on anatomical entities, and no dedicated methods for learning to automatically recognize anatomical entity mentions in free-form text have been introduced. Results: We present AnatomyTagger, a machine learning-based system for anatomical entity mention recognition. The system incorporates a broad array of approaches proposed to benefit tagging, including the use of Unified Medical Language System (UMLS)- and Open Biomedical Ontologies (OBO)-based lexical resources, word representations induced from unlabeled text, statistical truecasing and non-local features. We train and evaluate the system on a newly introduced corpus that substantially extends on previously available resources, and apply the resulting tagger to automatically annotate the entire open access scientific domain literature. The resulting analyses have been applied to extend services provided by the Europe PubMed Central literature database. Availability and implementation: All tools and resources introduced in this work are available from http://nactem.ac.uk/anatomytagger. Contact: sophia.ananiadou@manchester.ac.uk Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:24162468

An introduction to deep learning on biological sequence data: examples and solutions.

PubMed

Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten; Almagro Armenteros, Jose Juan; Nielsen, Henrik; Sønderby, Casper Kaae; Winther, Ole; Sønderby, Søren Kaae

2017-11-15

Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use libraries for implementation and training of neural networks are the drivers of this development. The use of deep learning has been especially successful in image recognition; and the development of tools, applications and code examples are in most cases centered within this field rather than within biology. Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively easily be designed and trained to state-of-the-art performance on three biological sequence problems: prediction of subcellular localization, protein secondary structure and the binding of peptides to MHC Class II molecules. All implementations and datasets are available online to the scientific community at https://github.com/vanessajurtz/lasagne4bio. skaaesonderby@gmail.com. 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

Adding New Tools to the Black Bag—Introduction of Ultrasound into the Physical Diagnosis Course

PubMed Central

Amponsah, David; Yang, James; Mendez, Jennifer; Bridge, Patrick; Hays, Gregory; Baliga, Sudhir; Crist, Karen; Brennan, Simone; Jackson, Matt; Dulchavsky, Scott

2010-01-01

INTRODUCTION Ultrasound, a versatile diagnostic modality that permits real-time visualization at the patient’s bedside, can be used as an adjunct in teaching physical diagnosis (PD). Aims: (1) to study the feasibility of incorporating ultrasound into PD courses and (2) determine whether learners can demonstrate image recognition and acquisition skills. PROGRAM DESCRIPTION Three hundred seven second-year medical students were introduced to cardiovascular and abdominal ultrasound scanning after training in the physical examination. This consisted of a demonstration of the ultrasound examination, followed by practice on standardized patients (SPs). Pre-post tests were administered to evaluate students’ knowledge and understanding of ultrasound. Students performed an ultrasound examination during the PD final examination. PROGRAM EVALUATION Pre-post test data revealed significant improvements in image recognition. On the final exam, the highest scores (98.4%) were obtained for the internal jugular vein and lowest scores (74.6%) on the Focused Assessment with Sonography for Trauma images. Eighty-nine percent of students’ surveyed felt ultrasound was a valuable tool for physicians. DISCUSSION An introductory ultrasound course is effective in improving medical students' acquisition and recognition of basic cardiovascular and abdominal ultrasound images. This innovative program demonstrates the feasibility of incorporating portable ultrasound as a learning tool during medical school. Electronic supplementary material The online version of this article (doi:10.1007/s11606-010-1451-5) contains supplementary material, which is available to authorized users. PMID:20697974

WHIDE—a web tool for visual data mining colocation patterns in multivariate bioimages

PubMed Central

Kölling, Jan; Langenkämper, Daniel; Abouna, Sylvie; Khan, Michael; Nattkemper, Tim W.

2012-01-01

Motivation: Bioimaging techniques rapidly develop toward higher resolution and dimension. The increase in dimension is achieved by different techniques such as multitag fluorescence imaging, Matrix Assisted Laser Desorption / Ionization (MALDI) imaging or Raman imaging, which record for each pixel an N-dimensional intensity array, representing local abundances of molecules, residues or interaction patterns. The analysis of such multivariate bioimages (MBIs) calls for new approaches to support users in the analysis of both feature domains: space (i.e. sample morphology) and molecular colocation or interaction. In this article, we present our approach WHIDE (Web-based Hyperbolic Image Data Explorer) that combines principles from computational learning, dimension reduction and visualization in a free web application. Results: We applied WHIDE to a set of MBI recorded using the multitag fluorescence imaging Toponome Imaging System. The MBI show field of view in tissue sections from a colon cancer study and we compare tissue from normal/healthy colon with tissue classified as tumor. Our results show, that WHIDE efficiently reduces the complexity of the data by mapping each of the pixels to a cluster, referred to as Molecular Co-Expression Phenotypes and provides a structural basis for a sophisticated multimodal visualization, which combines topology preserving pseudocoloring with information visualization. The wide range of WHIDE's applicability is demonstrated with examples from toponome imaging, high content screens and MALDI imaging (shown in the Supplementary Material). Availability and implementation: The WHIDE tool can be accessed via the BioIMAX website http://ani.cebitec.uni-bielefeld.de/BioIMAX/; Login: whidetestuser; Password: whidetest. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: tim.nattkemper@uni-bielefeld.de PMID:22390938

Evaluating a learning management system for blended learning in Greek higher education.

PubMed

Kabassi, Katerina; Dragonas, Ioannis; Ntouzevits, Alexandra; Pomonis, Tzanetos; Papastathopoulos, Giorgos; Vozaitis, Yiannis

2016-01-01

This paper focuses on the usage of a learning management system in an educational institution for higher education in Greece. More specifically, the paper examines the literature on the use of different learning management systems for blended learning in higher education in Greek Universities and Technological Educational Institutions and reviews the advantages and disadvantages. Moreover, the paper describes the usage of the Open eClass platform in a Technological Educational Institution, TEI of Ionian Islands, and the effort to improve the educational material by organizing it and adding video-lectures. The platform has been evaluated by the students of the TEI of Ionian Islands based on six dimensions: namely student, teacher, course, technology, system design, and environmental dimension. The results of this evaluation revealed that Open eClass has been successfully used for blended learning in the TEI of Ionian Islands. Despite the instructors' initial worries about students' lack of participation in their courses if their educational material was made available online and especially in video lectures; blended learning did not reduce physical presence of the students in the classroom. Instead it was only used as a supplementary tool that helps students to study further, watch missed lectures, etc.

E-learning for medical imaging specialists: introducing blended learning in a nuclear medicine specialist course

PubMed Central

Haslerud, Torjan; Tulipan, Andreas Julius; Gray, Robert M

2017-01-01

Background While e-learning has become an important tool in teaching medical students, the training of specialists in medical imaging is still dominated by lecture-based courses. Purpose To assess the potential of e-learning in specialist education in medical imaging. Material and Methods An existing lecture-based five-day course in Clinical Nuclear Medicine (NM) was enhanced by e-learning resources and activities, including practical exercises. An anonymized survey was conducted after participants had completed and passed the multiple choice electronic course examination. Results Twelve out of 15 course participants (80%) responded. Overall satisfaction with the new course format was high, but 25% of the respondents wanted more interactive elements such as discussions and practical exercises. The importance of lecture handouts and supplementary online material such as selected original articles and professional guidelines was affirmed by all the respondents (92% fully, 8% partially), while 75% fully and 25% partially agreed that the lectures had been interesting and relevant. Conclusion E-learning represents a hitherto unrealized potential in the education of medical specialists. It may expedite training of medical specialists while at the same time containing costs. PMID:28804642

MoleculeNet: a benchmark for molecular machine learning† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc02664a

PubMed Central

Wu, Zhenqin; Ramsundar, Bharath; Feinberg, Evan N.; Gomes, Joseph; Geniesse, Caleb; Pappu, Aneesh S.; Leswing, Karl

2017-01-01

Molecular machine learning has been maturing rapidly over the last few years. Improved methods and the presence of larger datasets have enabled machine learning algorithms to make increasingly accurate predictions about molecular properties. However, algorithmic progress has been limited due to the lack of a standard benchmark to compare the efficacy of proposed methods; most new algorithms are benchmarked on different datasets making it challenging to gauge the quality of proposed methods. This work introduces MoleculeNet, a large scale benchmark for molecular machine learning. MoleculeNet curates multiple public datasets, establishes metrics for evaluation, and offers high quality open-source implementations of multiple previously proposed molecular featurization and learning algorithms (released as part of the DeepChem open source library). MoleculeNet benchmarks demonstrate that learnable representations are powerful tools for molecular machine learning and broadly offer the best performance. However, this result comes with caveats. Learnable representations still struggle to deal with complex tasks under data scarcity and highly imbalanced classification. For quantum mechanical and biophysical datasets, the use of physics-aware featurizations can be more important than choice of particular learning algorithm. PMID:29629118

Auto Body Repair. Supplementary Units. Instructor Key and Student Units.

ERIC Educational Resources Information Center

Daniel, Linda; Muench, James F., Ed.

These supplementary units are designed to help students with special needs learn and apply auto body repair skills. The material specifically supplements the Auto Body Repair Curriculum Guide (University of Missouri-Columbia 1988), and is intended for instructors serving the occupational needs of various categories of disadvantaged and handicapped…

Bayesian Network Webserver: a comprehensive tool for biological network modeling.

PubMed

Ziebarth, Jesse D; Bhattacharya, Anindya; Cui, Yan

2013-11-01

The Bayesian Network Webserver (BNW) is a platform for comprehensive network modeling of systems genetics and other biological datasets. It allows users to quickly and seamlessly upload a dataset, learn the structure of the network model that best explains the data and use the model to understand relationships between network variables. Many datasets, including those used to create genetic network models, contain both discrete (e.g. genotype) and continuous (e.g. gene expression traits) variables, and BNW allows for modeling hybrid datasets. Users of BNW can incorporate prior knowledge during structure learning through an easy-to-use structural constraint interface. After structure learning, users are immediately presented with an interactive network model, which can be used to make testable hypotheses about network relationships. BNW, including a downloadable structure learning package, is available at http://compbio.uthsc.edu/BNW. (The BNW interface for adding structural constraints uses HTML5 features that are not supported by current version of Internet Explorer. We suggest using other browsers (e.g. Google Chrome or Mozilla Firefox) when accessing BNW). ycui2@uthsc.edu. Supplementary data are available at Bioinformatics online.

Pharmacology podcasts: a qualitative study of non-medical prescribing students' use, perceptions and impact on learning.

PubMed

Meade, Oonagh; Bowskill, Dianne; Lymn, Joanne S

2011-01-11

There is growing research on student use of podcasts in academic settings. However, there is little in-depth research focusing on student experience of podcasts, in particular in terms of barriers to, and facilitators of, podcast use and students' perceptions of the usefulness of podcasts as learning tools. This study aimed to explore the experiences of non-medical prescribing students who had access to podcasts of key pharmacology lectures as supplementary learning tools to their existing course materials. Semi-structured interviews were carried out with seven non-medical prescribing students (average age = 43 years), all of whom were nurses, who had access to seven podcasts of key pharmacology lectures. These podcasts took the form of downloadable audio lecture recordings available through the virtual learning environment WebCT. Low, medium and high users of the podcasts took part in the interviews in order to access a variety of student experiences. Interview data was analysed using thematic template analysis to identify key themes surrounding student experience of podcast availability, particularly in relation to barriers to and facilitators of podcast use, and students' experiences of podcasts as a learning tool. Students used podcasts for a variety of reasons such as revisiting lectures, preparing for exams, to clarify or revise specific topics and, to a lesser extent, to catch up on a missed lecture. Barriers to podcast use centred mainly around technological issues. Lack of experience of the technology required to access podcasts proved a barrier for some students. A lack of access to suitable technology was also a reported barrier. Family assistance and I.T. assistance from the university helped facilitate students' use of the podcasts. Students found that using podcasts allowed them to have greater control over their learning and to gauge their learning needs, as well as helping them build their understanding of a complex topic. Students used podcasts for a variety of reasons. Barriers to podcasts use were generally related to technological issues. Students often found that once assistance had been gained regarding these technological issues, they accessed the podcasts more easily. Students felt that access to podcasts added value to their learning materials by allowing them to better manage their learning and build their understanding. Podcasts represent a valuable additional learning tool for this specific group of older students.

Pharmacology podcasts: a qualitative study of non-medical prescribing students' use, perceptions and impact on learning

PubMed Central

2011-01-01

Background There is growing research on student use of podcasts in academic settings. However, there is little in-depth research focusing on student experience of podcasts, in particular in terms of barriers to, and facilitators of, podcast use and students' perceptions of the usefulness of podcasts as learning tools. This study aimed to explore the experiences of non-medical prescribing students who had access to podcasts of key pharmacology lectures as supplementary learning tools to their existing course materials. Methods Semi-structured interviews were carried out with seven non-medical prescribing students (average age = 43 years), all of whom were nurses, who had access to seven podcasts of key pharmacology lectures. These podcasts took the form of downloadable audio lecture recordings available through the virtual learning environment WebCT. Low, medium and high users of the podcasts took part in the interviews in order to access a variety of student experiences. Interview data was analysed using thematic template analysis to identify key themes surrounding student experience of podcast availability, particularly in relation to barriers to and facilitators of podcast use, and students' experiences of podcasts as a learning tool. Results Students used podcasts for a variety of reasons such as revisiting lectures, preparing for exams, to clarify or revise specific topics and, to a lesser extent, to catch up on a missed lecture. Barriers to podcast use centred mainly around technological issues. Lack of experience of the technology required to access podcasts proved a barrier for some students. A lack of access to suitable technology was also a reported barrier. Family assistance and I.T. assistance from the university helped facilitate students' use of the podcasts. Students found that using podcasts allowed them to have greater control over their learning and to gauge their learning needs, as well as helping them build their understanding of a complex topic. Conclusions Students used podcasts for a variety of reasons. Barriers to podcasts use were generally related to technological issues. Students often found that once assistance had been gained regarding these technological issues, they accessed the podcasts more easily. Students felt that access to podcasts added value to their learning materials by allowing them to better manage their learning and build their understanding. Podcasts represent a valuable additional learning tool for this specific group of older students. PMID:21223547

bwtool: a tool for bigWig files

PubMed Central

Pohl, Andy; Beato, Miguel

2014-01-01

BigWig files are a compressed, indexed, binary format for genome-wide signal data for calculations (e.g. GC percent) or experiments (e.g. ChIP-seq/RNA-seq read depth). bwtool is a tool designed to read bigWig files rapidly and efficiently, providing functionality for extracting data and summarizing it in several ways, globally or at specific regions. Additionally, the tool enables the conversion of the positions of signal data from one genome assembly to another, also known as ‘lifting’. We believe bwtool can be useful for the analyst frequently working with bigWig data, which is becoming a standard format to represent functional signals along genomes. The article includes supplementary examples of running the software. Availability and implementation: The C source code is freely available under the GNU public license v3 at http://cromatina.crg.eu/bwtool. Contact: andrew.pohl@crg.eu, andypohl@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24489365

Machine Shop. Instructor Key. Supplementary Units.

ERIC Educational Resources Information Center

Walden, Charles; Cole, Phyllis

These supplementary units are designed to help students with special needs learn and apply machine shop skills. Nine competencies that are difficult for special needs students to grasp or that would help them get a future job in the field were chosen from the regular machine shop curriculum. Specific objectives for these competencies are listed at…

Using Lesson Study to Align Elementary Literacy Instruction within the RTI Framework

ERIC Educational Resources Information Center

Benedict, Amber E.; Park, Yujeong; Brownell, Mary T.; Lauterbach, Alexandra A.; Kiely, Mary Theresa

2013-01-01

The purpose of this article is to inform teachers about the dangers of misalignment between core (Tier 1) instruction and Tiers 2 and 3 supplementary instruction for struggling readers and students with learning disabilities. Misalignment between core and supplementary instruction is problematic for students at risk of academic failure because it…

Virtual Learning Simulations in High School: Effects on Cognitive and Non-cognitive Outcomes and Implications on the Development of STEM Academic and Career Choice.

PubMed

Thisgaard, Malene; Makransky, Guido

2017-01-01

The present study compared the value of using a virtual learning simulation compared to traditional lessons on the topic of evolution, and investigated if the virtual learning simulation could serve as a catalyst for STEM academic and career development, based on social cognitive career theory. The investigation was conducted using a crossover repeated measures design based on a sample of 128 high school biology/biotech students. The results showed that the virtual learning simulation increased knowledge of evolution significantly, compared to the traditional lesson. No significant differences between the simulation and lesson were found in their ability to increase the non-cognitive measures. Both interventions increased self-efficacy significantly, and none of them had a significant effect on motivation. In addition, the results showed that the simulation increased interest in biology related tasks, but not outcome expectations. The findings suggest that virtual learning simulations are at least as efficient in enhancing learning and self-efficacy as traditional lessons, and high schools can thus use them as supplementary educational methods. In addition, the findings indicate that virtual learning simulations may be a useful tool in enhancing student's interest in and goals toward STEM related careers.

Virtual Learning Simulations in High School: Effects on Cognitive and Non-cognitive Outcomes and Implications on the Development of STEM Academic and Career Choice

PubMed Central

Thisgaard, Malene; Makransky, Guido

2017-01-01

The present study compared the value of using a virtual learning simulation compared to traditional lessons on the topic of evolution, and investigated if the virtual learning simulation could serve as a catalyst for STEM academic and career development, based on social cognitive career theory. The investigation was conducted using a crossover repeated measures design based on a sample of 128 high school biology/biotech students. The results showed that the virtual learning simulation increased knowledge of evolution significantly, compared to the traditional lesson. No significant differences between the simulation and lesson were found in their ability to increase the non-cognitive measures. Both interventions increased self-efficacy significantly, and none of them had a significant effect on motivation. In addition, the results showed that the simulation increased interest in biology related tasks, but not outcome expectations. The findings suggest that virtual learning simulations are at least as efficient in enhancing learning and self-efficacy as traditional lessons, and high schools can thus use them as supplementary educational methods. In addition, the findings indicate that virtual learning simulations may be a useful tool in enhancing student’s interest in and goals toward STEM related careers. PMID:28611701

Transfer learning for biomedical named entity recognition with neural networks.

PubMed

Giorgi, John M; Bader, Gary D

2018-06-01

The explosive increase of biomedical literature has made information extraction an increasingly important tool for biomedical research. A fundamental task is the recognition of biomedical named entities in text (BNER) such as genes/proteins, diseases, and species. Recently, a domain-independent method based on deep learning and statistical word embeddings, called long short-term memory network-conditional random field (LSTM-CRF), has been shown to outperform state-of-the-art entity-specific BNER tools. However, this method is dependent on gold-standard corpora (GSCs) consisting of hand-labeled entities, which tend to be small but highly reliable. An alternative to GSCs are silver-standard corpora (SSCs), which are generated by harmonizing the annotations made by several automatic annotation systems. SSCs typically contain more noise than GSCs but have the advantage of containing many more training examples. Ideally, these corpora could be combined to achieve the benefits of both, which is an opportunity for transfer learning. In this work, we analyze to what extent transfer learning improves upon state-of-the-art results for BNER. We demonstrate that transferring a deep neural network (DNN) trained on a large, noisy SSC to a smaller, but more reliable GSC significantly improves upon state-of-the-art results for BNER. Compared to a state-of-the-art baseline evaluated on 23 GSCs covering four different entity classes, transfer learning results in an average reduction in error of approximately 11%. We found transfer learning to be especially beneficial for target data sets with a small number of labels (approximately 6000 or less). Source code for the LSTM-CRF is available athttps://github.com/Franck-Dernoncourt/NeuroNER/ and links to the corpora are available athttps://github.com/BaderLab/Transfer-Learning-BNER-Bioinformatics-2018/. john.giorgi@utoronto.ca. Supplementary data are available at Bioinformatics online.

Tools for visually exploring biological networks.

PubMed

Suderman, Matthew; Hallett, Michael

2007-10-15

Many tools exist for visually exploring biological networks including well-known examples such as Cytoscape, VisANT, Pathway Studio and Patika. These systems play a key role in the development of integrative biology, systems biology and integrative bioinformatics. The trend in the development of these tools is to go beyond 'static' representations of cellular state, towards a more dynamic model of cellular processes through the incorporation of gene expression data, subcellular localization information and time-dependent behavior. We provide a comprehensive review of the relative advantages and disadvantages of existing systems with two goals in mind: to aid researchers in efficiently identifying the appropriate existing tools for data visualization; to describe the necessary and realistic goals for the next generation of visualization tools. In view of the first goal, we provide in the Supplementary Material a systematic comparison of more than 35 existing tools in terms of over 25 different features. Supplementary data are available at Bioinformatics online.

Non-Formal Learning: Clarification of the Concept and Its Application in Music Learning

ERIC Educational Resources Information Center

Mok, On Nei Annie

2011-01-01

The concept of non-formal learning, which falls outside the categories of informal and formal learning, has not been as widely discussed, especially in the music education literature. In order to bridge this gap and to provide supplementary framework to the discussion of informal and formal learning, therefore, this paper will first summarize…

How Do I Manage? An Introduction to Management. Supplementary Material and Workbook.

ERIC Educational Resources Information Center

North West Regional Management Centre, Chorley (England).

This book contains supplementary material for a British self-study course in management designed as an introduction to the course for the Certificate in Management Studies. The materials in this book are learning activities referenced to various topics in the course materials. The nine activities include a case study of a production supervision…

Novel features and enhancements in BioBin, a tool for the biologically inspired binning and association analysis of rare variants

PubMed Central

Byrska-Bishop, Marta; Wallace, John; Frase, Alexander T; Ritchie, Marylyn D

2018-01-01

Abstract Motivation BioBin is an automated bioinformatics tool for the multi-level biological binning of sequence variants. Herein, we present a significant update to BioBin which expands the software to facilitate a comprehensive rare variant analysis and incorporates novel features and analysis enhancements. Results In BioBin 2.3, we extend our software tool by implementing statistical association testing, updating the binning algorithm, as well as incorporating novel analysis features providing for a robust, highly customizable, and unified rare variant analysis tool. Availability and implementation The BioBin software package is open source and freely available to users at http://www.ritchielab.com/software/biobin-download Contact mdritchie@geisinger.edu Supplementary information Supplementary data are available at Bioinformatics online. PMID:28968757

BIBLIOGRAPHY ON LEARNING PROCESS. SUPPLEMENT II.

ERIC Educational Resources Information Center

Harvard Univ., Cambridge, MA. Graduate School of Education.

THIS SUPPLEMENTARY BIBLIOGRAPHY LISTS MATERIALS ON VARIOUS FACETS OF HUMAN LEARNING. APPROXIMATELY 60 UNANNOTATED REFERENCES ARE PROVIDED FOR DOCUMENTS DATING FROM 1954 TO 1966. JOURNAL ARTICLES, BOOKS, RESEARCH REPORTS, AND CONFERENCE PAPERS ARE LISTED. SOME SUBJECT AREAS INCLUDED ARE (1) LEARNING PARAMETERS AND ABILITY, (2) RETENTION AND…

Towards a Better Distributed Framework for Learning Big Data

DTIC Science & Technology

2017-06-14

UNLIMITED: PB Public Release 13. SUPPLEMENTARY NOTES 14. ABSTRACT This work aimed at solving issues in distributed machine learning. The PI’s team proposed...communication load. Finally, the team proposed the parallel least-squares policy iteration (parallel LSPI) to parallelize a reinforcement policy learning. 15

QUAST: quality assessment tool for genome assemblies

PubMed Central

Gurevich, Alexey; Saveliev, Vladislav; Vyahhi, Nikolay; Tesler, Glenn

2013-01-01

Summary: Limitations of genome sequencing techniques have led to dozens of assembly algorithms, none of which is perfect. A number of methods for comparing assemblers have been developed, but none is yet a recognized benchmark. Further, most existing methods for comparing assemblies are only applicable to new assemblies of finished genomes; the problem of evaluating assemblies of previously unsequenced species has not been adequately considered. Here, we present QUAST—a quality assessment tool for evaluating and comparing genome assemblies. This tool improves on leading assembly comparison software with new ideas and quality metrics. QUAST can evaluate assemblies both with a reference genome, as well as without a reference. QUAST produces many reports, summary tables and plots to help scientists in their research and in their publications. In this study, we used QUAST to compare several genome assemblers on three datasets. QUAST tables and plots for all of them are available in the Supplementary Material, and interactive versions of these reports are on the QUAST website. Availability: http://bioinf.spbau.ru/quast Contact: gurevich@bioinf.spbau.ru Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23422339

DeepSynergy: predicting anti-cancer drug synergy with Deep Learning

PubMed Central

Preuer, Kristina; Lewis, Richard P I; Hochreiter, Sepp; Bender, Andreas; Bulusu, Krishna C; Klambauer, Günter

2018-01-01

Abstract Motivation While drug combination therapies are a well-established concept in cancer treatment, identifying novel synergistic combinations is challenging due to the size of combinatorial space. However, computational approaches have emerged as a time- and cost-efficient way to prioritize combinations to test, based on recently available large-scale combination screening data. Recently, Deep Learning has had an impact in many research areas by achieving new state-of-the-art model performance. However, Deep Learning has not yet been applied to drug synergy prediction, which is the approach we present here, termed DeepSynergy. DeepSynergy uses chemical and genomic information as input information, a normalization strategy to account for input data heterogeneity, and conical layers to model drug synergies. Results DeepSynergy was compared to other machine learning methods such as Gradient Boosting Machines, Random Forests, Support Vector Machines and Elastic Nets on the largest publicly available synergy dataset with respect to mean squared error. DeepSynergy significantly outperformed the other methods with an improvement of 7.2% over the second best method at the prediction of novel drug combinations within the space of explored drugs and cell lines. At this task, the mean Pearson correlation coefficient between the measured and the predicted values of DeepSynergy was 0.73. Applying DeepSynergy for classification of these novel drug combinations resulted in a high predictive performance of an AUC of 0.90. Furthermore, we found that all compared methods exhibit low predictive performance when extrapolating to unexplored drugs or cell lines, which we suggest is due to limitations in the size and diversity of the dataset. We envision that DeepSynergy could be a valuable tool for selecting novel synergistic drug combinations. Availability and implementation DeepSynergy is available via www.bioinf.jku.at/software/DeepSynergy. Contact klambauer@bioinf.jku.at Supplementary information Supplementary data are available at Bioinformatics online. PMID:29253077

Multiple Intelligences, Motivations and Learning Experience Regarding Video-Assisted Subjects in a Rural University

ERIC Educational Resources Information Center

Hajhashemi, Karim; Caltabiano, Nerina; Anderson, Neil; Tabibzadeh, Seyed Asadollah

2018-01-01

This study investigates multiple intelligences in relation to online video experiences, age, gender, and mode of learning from a rural Australian university. The inter-relationships between learners' different intelligences and their motivations and learning experience with the supplementary online videos utilised in their subjects are…

Basic and supplementary sensory feedback in handwriting

PubMed Central

Danna, Jérémy; Velay, Jean-Luc

2015-01-01

The mastering of handwriting is so essential in our society that it is important to try to find new methods for facilitating its learning and rehabilitation. The ability to control the graphic movements clearly impacts on the quality of the writing. This control allows both the programming of letter formation before movement execution and the online adjustments during execution, thanks to diverse sensory feedback (FB). New technologies improve existing techniques or enable new methods to supply the writer with real-time computer-assisted FB. The possibilities are numerous and various. Therefore, two main questions arise: (1) What aspect of the movement is concerned and (2) How can we best inform the writer to help them correct their handwriting? In a first step, we report studies on FB naturally used by the writer. The purpose is to determine which information is carried by each sensory modality, how it is used in handwriting control and how this control changes with practice and learning. In a second step, we report studies on supplementary FB provided to the writer to help them to better control and learn how to write. We suggest that, depending on their contents, certain sensory modalities will be more appropriate than others to assist handwriting motor control. We emphasize particularly the relevance of auditory modality as online supplementary FB on handwriting movements. Using real-time supplementary FB to assist in the handwriting process is probably destined for a brilliant future with the growing availability and rapid development of tablets. PMID:25750633

Developing an Entrepreneurship Module by Using Product-Based Learning Approach in Vocational Education

ERIC Educational Resources Information Center

Yulastri, Asmar; Hidayat, Hendra; Ganefri; Islami, Syaiful; Edya, Fuji

2017-01-01

Boring lecturers and irrelevant learning materials needed by students caused the students are less motivated to learn entrepreneurship course in vocational education. It is caused by the learning materials that will be delivered by the lectures can be predicted by the students. Thus, a relevant and supplementary support is much needed which can be…

Tachyon search speeds up retrieval of similar sequences by several orders of magnitude

PubMed Central

Tan, Joshua; Kuchibhatla, Durga; Sirota, Fernanda L.; Sherman, Westley A.; Gattermayer, Tobias; Kwoh, Chia Yee; Eisenhaber, Frank; Schneider, Georg; Maurer-Stroh, Sebastian

2012-01-01

Summary: The usage of current sequence search tools becomes increasingly slower as databases of protein sequences continue to grow exponentially. Tachyon, a new algorithm that identifies closely related protein sequences ~200 times faster than standard BLAST, circumvents this limitation with a reduced database and oligopeptide matching heuristic. Availability and implementation: The tool is publicly accessible as a webserver at http://tachyon.bii.a-star.edu.sg and can also be accessed programmatically through SOAP. Contact: sebastianms@bii.a-star.edu.sg Supplementary information: Supplementary data are available at the Bioinformatics online. PMID:22531216

Children's Discourse in Cooperative and Didactic Interaction: Developmental Patterns in Effective Learning.

ERIC Educational Resources Information Center

Cooper, Catherine R.; And Others

Experimental and supplementary observational studies of how children help one another learn are reported. In the experiment, developmental patterns in children's discourse in two common peer-learning situations were investigated. Sixty-four pairs of children, drawn equally from kindergarten and second grade, participated in the study. Dyads,…

The E-Learning Component of a Blended Learning Course

ERIC Educational Resources Information Center

Olejarczuk, Edyta

2014-01-01

Using new technologies in the academic field has become more and more visible in Poland in the recent years. In the past, digital learning resources were used as supplementary materials helping to support face-to-face instruction. Nowadays, we have the opportunity not only to apply "traditional" methods but also to use more sophisticated…

75 FR 26345 - Agency Information Collection (Ethics Consultation Feedback Tool (ECFT)) New Enrollee Survey...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-11

... Collection (Ethics Consultation Feedback Tool (ECFT)) New Enrollee Survey) Activity Under OMB Review AGENCY...).'' SUPPLEMENTARY INFORMATION: Title: Ethics Consultation Feedback Tool (ECFT), VA Form 10-0502. OMB Control Number... collect data from patients and family members about their experience during the Ethics Consultation...

75 FR 8388 - Agency Information Collection Activities: Submission for OMB Review; Comment Request, OMB No...

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Sparsity and Nullity: Paradigm for Analysis Dictionary Learning

DTIC Science & Technology

2016-08-09

16. SECURITY CLASSIFICATION OF: Sparse models in dictionary learning have been successfully applied in a wide variety of machine learning and...we investigate the relation between the SNS problem and the analysis dictionary learning problem, and show that the SNS problem plays a central role...and may be utilized to solve dictionary learning problems. 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13. SUPPLEMENTARY NOTES 12

Deep learning-based subdivision approach for large scale macromolecules structure recovery from electron cryo tomograms

PubMed Central

Xu, Min; Chai, Xiaoqi; Muthakana, Hariank; Liang, Xiaodan; Yang, Ge; Zeev-Ben-Mordehai, Tzviya; Xing, Eric P.

2017-01-01

Abstract Motivation: Cellular Electron CryoTomography (CECT) enables 3D visualization of cellular organization at near-native state and in sub-molecular resolution, making it a powerful tool for analyzing structures of macromolecular complexes and their spatial organizations inside single cells. However, high degree of structural complexity together with practical imaging limitations makes the systematic de novo discovery of structures within cells challenging. It would likely require averaging and classifying millions of subtomograms potentially containing hundreds of highly heterogeneous structural classes. Although it is no longer difficult to acquire CECT data containing such amount of subtomograms due to advances in data acquisition automation, existing computational approaches have very limited scalability or discrimination ability, making them incapable of processing such amount of data. Results: To complement existing approaches, in this article we propose a new approach for subdividing subtomograms into smaller but relatively homogeneous subsets. The structures in these subsets can then be separately recovered using existing computation intensive methods. Our approach is based on supervised structural feature extraction using deep learning, in combination with unsupervised clustering and reference-free classification. Our experiments show that, compared with existing unsupervised rotation invariant feature and pose-normalization based approaches, our new approach achieves significant improvements in both discrimination ability and scalability. More importantly, our new approach is able to discover new structural classes and recover structures that do not exist in training data. Availability and Implementation: Source code freely available at http://www.cs.cmu.edu/∼mxu1/software. Contact: mxu1@cs.cmu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28881965

Design Framework for an Adaptive MOOC Enhanced by Blended Learning: Supplementary Training and Personalized Learning for Teacher Professional Development

ERIC Educational Resources Information Center

Gynther, Karsten

2016-01-01

The research project has developed a design framework for an adaptive MOOC that complements the MOOC format with blended learning. The design framework consists of a design model and a series of learning design principles which can be used to design in-service courses for teacher professional development. The framework has been evaluated by…

Colonoscopy tutorial software made with a cadaver's sectioned images.

PubMed

Chung, Beom Sun; Chung, Min Suk; Park, Hyung Seon; Shin, Byeong-Seok; Kwon, Koojoo

2016-11-01

Novice doctors may watch tutorial videos in training for actual or computed tomographic (CT) colonoscopy. The conventional learning videos can be complemented by virtual colonoscopy software made with a cadaver's sectioned images (SIs). The objective of this study was to assist colonoscopy trainees with the new interactive software. Submucosal segmentation on the SIs was carried out through the whole length of the large intestine. With the SIs and segmented images, a three dimensional model was reconstructed. Six-hundred seventy-one proximal colonoscopic views (conventional views) and corresponding distal colonoscopic views (simulating the retroflexion of a colonoscope) were produced. Not only navigation views showing the current location of the colonoscope tip and its course, but also, supplementary description views were elaborated. The four corresponding views were put into convenient browsing software to be downloaded free from the homepage (anatomy.co.kr). The SI colonoscopy software with the realistic images and supportive tools was available to anybody. Users could readily notice the position and direction of the virtual colonoscope tip and recognize meaningful structures in colonoscopic views. The software is expected to be an auxiliary learning tool to improve technique and related knowledge in actual and CT colonoscopies. Hopefully, the software will be updated using raw images from the Visible Korean project. Copyright © 2016 Elsevier GmbH. All rights reserved.

Problem-Centered Supplemental Instruction in Biology: Influence on Content Recall, Content Understanding, and Problem Solving Ability

ERIC Educational Resources Information Center

Gardner, Joel; Belland, Brian R.

2017-01-01

To address the need for effective, efficient ways to apply active learning in undergraduate biology courses, in this paper, we propose a problem-centered approach that utilizes supplemental web-based instructional materials based on principles of active learning. We compared two supplementary web-based modules using active learning strategies: the…

Tools4miRs – one place to gather all the tools for miRNA analysis

PubMed Central

Lukasik, Anna; Wójcikowski, Maciej; Zielenkiewicz, Piotr

2016-01-01

Summary: MiRNAs are short, non-coding molecules that negatively regulate gene expression and thereby play several important roles in living organisms. Dozens of computational methods for miRNA-related research have been developed, which greatly differ in various aspects. The substantial availability of difficult-to-compare approaches makes it challenging for the user to select a proper tool and prompts the need for a solution that will collect and categorize all the methods. Here, we present tools4miRs, the first platform that gathers currently more than 160 methods for broadly defined miRNA analysis. The collected tools are classified into several general and more detailed categories in which the users can additionally filter the available methods according to their specific research needs, capabilities and preferences. Tools4miRs is also a web-based target prediction meta-server that incorporates user-designated target prediction methods into the analysis of user-provided data. Availability and Implementation: Tools4miRs is implemented in Python using Django and is freely available at tools4mirs.org. Contact: piotr@ibb.waw.pl Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153626

Tools and Their Uses. Rate Training Manual.

ERIC Educational Resources Information Center

Naval Personnel Program Support Activity, Washington, DC.

One of a series of training manuals prepared for enlisted personnel in the Navy and Naval Reserve, this supplementary manual contains data pertinent to a variety of tools necessary to the satisfactory performance of modern technical equipment used by the Navy. It is designed to help the learner identify tools and fastening devices by their correct…

MaGnET: Malaria Genome Exploration Tool

PubMed Central

Sharman, Joanna L.; Gerloff, Dietlind L.

2013-01-01

Summary: The Malaria Genome Exploration Tool (MaGnET) is a software tool enabling intuitive ‘exploration-style’ visualization of functional genomics data relating to the malaria parasite, Plasmodium falciparum. MaGnET provides innovative integrated graphic displays for different datasets, including genomic location of genes, mRNA expression data, protein–protein interactions and more. Any selection of genes to explore made by the user is easily carried over between the different viewers for different datasets, and can be changed interactively at any point (without returning to a search). Availability and Implementation: Free online use (Java Web Start) or download (Java application archive and MySQL database; requires local MySQL installation) at http://malariagenomeexplorer.org Contact: joanna.sharman@ed.ac.uk or dgerloff@ffame.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23894142

Developing Multimedia Supplementary Materials to Support Learning Beginning Level Chinese Characters

ERIC Educational Resources Information Center

Xu, Lisha

2017-01-01

Studies investigating beginner Chinese learners' character learning strategies found that learners considered orthographic knowledge the most useful factor (Ke, 1998; Shen, 2005). Orthographic recognition correlates with character identification and production and can be used by advanced learners to solve word identification problems (Everson,…

Implementation of formal learning objectives during a physical medicine and rehabilitation sports medicine rotation.

PubMed

Smith, Jay; Laskowski, Edward R; Newcomer-Aney, Karen L; Thompson, Jeffrey M; Schaefer, Michael P; Morfe, Erasmus G

2005-04-01

To develop and implement formal learning objectives during a physical medicine and rehabilitation sports medicine rotation and characterize resident experiences with the objectives over a 16-mo period. Prospective, including learning objective development, implementation, and postrotation survey. A total of 69 learning objectives were developed by physical medicine and rehabilitation staff physician consensus, including 39 core objectives. Eighteen residents completed 4-wk sports medicine rotations from January 2003 through April 2004. Residents completed an average of 31 total objectives (45%; range, 3-52), of which 24 (62%; range, 3-35) were core. Residents completed the highest percentage of knee (60%), shoulder (57%), and ankle-foot (57%) objectives and reported that objectives related to these areas were most effective to facilitate learning. In general, residents reported that objective content was good and that the objectives delineated important concepts to learn during the rotation. Seventeen of 18 residents indicated that the objectives should be permanently implemented into the sports rotation and that similar objectives should be developed for other rotations. Based on our experience and the recommendations of residents, the average resident should be able to complete approximately 30 objectives during a typical 4-wk rotation. Successful implementation of specific, consensus-derived learning objectives is possible within the context of a busy clinical practice. Our initial physician staff and resident experience with the objectives suggests that this model may be useful as a supplementary educational tool in physical medicine and rehabilitation residency programs.

An Action Research Approach to the Design, Development and Evaluation of an Interactive E-Learning Tutorial in a Cognitive Domain

ERIC Educational Resources Information Center

de Villiers, M. Ruth

2007-01-01

The teaching and learning of a complex section in "Theoretical Computer Science 1" in a distance-education context at the University of South Africa (UNISA) has been enhanced by a supplementary e-learning application called "Relations," which interactively teaches mathematical skills in a cognitive domain. It has tutorial and…

GARFIELD-NGS: Genomic vARiants FIltering by dEep Learning moDels in NGS.

PubMed

Ravasio, Viola; Ritelli, Marco; Legati, Andrea; Giacopuzzi, Edoardo

2018-04-14

Exome sequencing approach is extensively used in research and diagnostic laboratories to discover pathological variants and study genetic architecture of human diseases. However, a significant proportion of identified genetic variants are actually false positive calls, and this pose serious challenges for variants interpretation. Here, we propose a new tool named GARFIELD-NGS (Genomic vARiants FIltering by dEep Learning moDels in NGS), which rely on deep learning models to dissect false and true variants in exome sequencing experiments performed with Illumina or ION platforms. GARFIELD-NGS showed strong performances for both SNP and INDEL variants (AUC 0.71 - 0.98) and outperformed established hard filters. The method is robust also at low coverage down to 30X and can be applied on data generated with the recent Illumina two-colour chemistry. GARFIELD-NGS processes standard VCF file and produces a regular VCF output. Thus, it can be easily integrated in existing analysis pipeline, allowing application of different thresholds based on desired level of sensitivity and specificity. GARFIELD-NGS available at https://github.com/gedoardo83/GARFIELD-NGS. edoardo.giacopuzzi@unibs.it. Supplementary data are available at Bioinformatics online.

Nobody Reads Billboards!

ERIC Educational Resources Information Center

Walker, Joseph J.; Lotz, Condit

1982-01-01

The authors describe an incidental learning approach using supplementary reading sources such as bumper stickers, t-shirts, and novelty buttons to encourage gifted students' analysis and synthesis skills. (CL)

Supervised Learning for Detection of Duplicates in Genomic Sequence Databases.

PubMed

Chen, Qingyu; Zobel, Justin; Zhang, Xiuzhen; Verspoor, Karin

2016-01-01

First identified as an issue in 1996, duplication in biological databases introduces redundancy and even leads to inconsistency when contradictory information appears. The amount of data makes purely manual de-duplication impractical, and existing automatic systems cannot detect duplicates as precisely as can experts. Supervised learning has the potential to address such problems by building automatic systems that learn from expert curation to detect duplicates precisely and efficiently. While machine learning is a mature approach in other duplicate detection contexts, it has seen only preliminary application in genomic sequence databases. We developed and evaluated a supervised duplicate detection method based on an expert curated dataset of duplicates, containing over one million pairs across five organisms derived from genomic sequence databases. We selected 22 features to represent distinct attributes of the database records, and developed a binary model and a multi-class model. Both models achieve promising performance; under cross-validation, the binary model had over 90% accuracy in each of the five organisms, while the multi-class model maintains high accuracy and is more robust in generalisation. We performed an ablation study to quantify the impact of different sequence record features, finding that features derived from meta-data, sequence identity, and alignment quality impact performance most strongly. The study demonstrates machine learning can be an effective additional tool for de-duplication of genomic sequence databases. All Data are available as described in the supplementary material.

Small Business Management Training Tools Directory.

ERIC Educational Resources Information Center

American Association of Community and Junior Colleges, Washington, DC. National Small Business Training Network.

This directory is designed to assist in the identification of supplementary materials to support program development for small businesses. Following introductory comments and an overview of small business management training, section I lists training tools available from the Small Business Administration (SBA). Section II provides descriptions and…

Pharmacology as a foreign language: a preliminary evaluation of podcasting as a supplementary learning tool for non-medical prescribing students.

PubMed

Meade, Oonagh; Bowskill, Dianne; Lymn, Joanne S

2009-12-18

Nurses and other health professionals in the U.K. can gain similar prescribing rights to doctors by undertaking a non-medical prescribing course. Non-medical prescribing students must have a thorough understanding of the pharmacology of prescribing to ensure safe practice. Pharmacology education at this level is complicated by the variation in students' prior subject knowledge of, and anxiety about, the subject. The recent advances in technology, particularly the potential for mobile learning, provide increased opportunities for students to familiarise themselves with lecture materials and hence promote understanding. The objective of this study was therefore to evaluate both the subjective (student perception) and objective (student use and exam results) usefulness of podcasts of pharmacology lectures which were provided as an extra learning tool to two cohorts (n = 69) of non-medical prescribing students. The podcasts were made available to students through the virtual learning environment WebCT. Use of podcasts by two successive cohorts of nurse prescribing students (n = 69) was tracked through WebCT. Survey data, which was collected from 44 of these students, investigated patterns of/reasons for podcast use and perceived usefulness of podcasts as a learning tool. Of these 69 students, 64 completed the pharmacology exam. In order to examine any impact of podcasts on student knowledge, their exam results were compared with those of two historical cohorts who did not have access to podcasts (n = 70). WebCT tracking showed that 91% of students accessed at least one podcast. 93% of students used the podcasts to revisit a lecture, 85% used podcasts for revision, and 61% used the podcasts when they had a specific question. Only 22% used the podcasts because they had missed a pharmacology session. Most students (81%) generally listened to the entire podcast rather than specific sections and most (73%) used them while referring to their lecture handouts. The majority of students found the podcasts helpful as a learning tool, as a revision aid and in promoting their understanding of the subject. Evaluation of the range of marks obtained, mode mark and mean mark suggested improved knowledge in students with access to podcasts compared to historical cohorts of students who did not have access to pharmacology podcasts. The results of this study suggest that non-medical prescribing students utilised podcasts of pharmacology lectures, and have found the availability of these podcasts helpful for their learning. Exam results indicate that the availability of podcasts was also associated with improved exam performance.

‘Gamma Anna’: a classroom demonstration for teaching the concepts of gamma imaging

NASA Astrophysics Data System (ADS)

Wolff, Nicola; Griffiths, Jennifer; Yerworth, Rebecca

2017-01-01

Gamma imaging is at the interface of medicine and physics and thus its teaching is important in both fields. Pedagogic literature highlights the benefits of interactive demonstrations in teaching: an increase in enjoyment and interest, as well as improvement in academic achievement. However gamma imaging uses radioactive sources, which are potentially dangerous and thus their use is tightly controlled. We have developed a demonstration which uses a localised exothermic reaction within a rag doll as an analogue of radioactivity. This can be safely used in classrooms to demonstrate the principles of gamma imaging. The tool is easy to make, cheap, robust and portable. The supplementary material in this paper gives teacher notes and a description of how to make the rag doll demonstrator. We have tested the tool using six participants, acting as ‘teachers’, who carried out the demonstration and described the doll as easy to use, and the ‘tumour’ clearly identifiable. The teaching tool was separately demonstrated to a group of 12 GCSE physics students and a group of 12 medical students. Feedback showed increased student engagement, enjoyment and understanding of gamma imaging. Previous research has shown that these benefits have an impact on learning and academic outcomes.

Icarus: visualizer for de novo assembly evaluation.

PubMed

Mikheenko, Alla; Valin, Gleb; Prjibelski, Andrey; Saveliev, Vladislav; Gurevich, Alexey

2016-11-01

: Data visualization plays an increasingly important role in NGS data analysis. With advances in both sequencing and computational technologies, it has become a new bottleneck in genomics studies. Indeed, evaluation of de novo genome assemblies is one of the areas that can benefit from the visualization. However, even though multiple quality assessment methods are now available, existing visualization tools are hardly suitable for this purpose. Here, we present Icarus-a novel genome visualizer for accurate assessment and analysis of genomic draft assemblies, which is based on the tool QUAST. Icarus can be used in studies where a related reference genome is available, as well as for non-model organisms. The tool is available online and as a standalone application. http://cab.spbu.ru/software/icarus CONTACT: aleksey.gurevich@spbu.ruSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Effects of additional team-based learning on students' clinical reasoning skills: a pilot study.

PubMed

Jost, Meike; Brüstle, Peter; Giesler, Marianne; Rijntjes, Michel; Brich, Jochen

2017-07-14

In the field of Neurology good clinical reasoning skills are essential for successful diagnosing and treatment. Team-based learning (TBL), an active learning and small group instructional strategy, is a promising method for fostering these skills. The aim of this pilot study was to examine the effects of a supplementary TBL-class on students' clinical decision-making skills. Fourth- and fifth-year medical students participated in this pilot study (static-group comparison design). The non-treatment group (n = 15) did not receive any additional training beyond regular teaching in the neurology course. The treatment group (n = 11) took part in a supplementary TBL-class optimized for teaching clinical reasoning in addition to the regular teaching in the neurology course. Clinical decision making skills were assessed using a key-feature problem examination. Factual and conceptual knowledge was assessed by a multiple-choice question examination. The TBL-group performed significantly better than the non-TBL-group (p = 0.026) in the key-feature problem examination. No significant differences between the results of the multiple-choice question examination of both groups were found. In this pilot study participants of a supplementary TBL-class significantly improved clinical decision-making skills, indicating that TBL may be an appropriate method for teaching clinical decision making in neurology. Further research is needed for replication in larger groups and other clinical fields.

FRED 2: an immunoinformatics framework for Python

PubMed Central

Schubert, Benjamin; Walzer, Mathias; Brachvogel, Hans-Philipp; Szolek, András; Mohr, Christopher; Kohlbacher, Oliver

2016-01-01

Summary: Immunoinformatics approaches are widely used in a variety of applications from basic immunological to applied biomedical research. Complex data integration is inevitable in immunological research and usually requires comprehensive pipelines including multiple tools and data sources. Non-standard input and output formats of immunoinformatics tools make the development of such applications difficult. Here we present FRED 2, an open-source immunoinformatics framework offering easy and unified access to methods for epitope prediction and other immunoinformatics applications. FRED 2 is implemented in Python and designed to be extendable and flexible to allow rapid prototyping of complex applications. Availability and implementation: FRED 2 is available at http://fred-2.github.io Contact: schubert@informatik.uni-tuebingen.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153717

Alaska Is Our Home--Book 2: A Natural Science Handbook for Alaskan Students.

ERIC Educational Resources Information Center

Bury, John; Bury, Susan

A natural science resource booklet for teachers and students contains detailed materials for teaching and learning about Alaskan wildlife. Each of nine chapters provides background subject information, suggested learning activities, tear-out pages of review questions for students to answer, and supplementary notes for teachers which include…

Meaning-Making as Dialogic Process: Official and Carnival Lives in the Language Classroom

ERIC Educational Resources Information Center

Blackledge, Adrian; Creese, Angela

2009-01-01

This article adopts a Bakhtinian analysis to understand the complexities of discourse in language-learning classrooms. Drawing on empirical data from two of four linked case studies in a larger, ESRC-funded project, we argue that students learning in complementary (also known as community language, supplementary, or heritage language) schools…

Research Handbook on Children's Language Learning. Preliminary Edition. Final Report.

ERIC Educational Resources Information Center

Dato, Daniel P.

This handbook serves as an introduction to the study of children's language development and as a supplementary aid in the training of research workers in the field of children's language learning. As a teaching aid, it is suggested this work be used with a film entitled "Psycholinquistic Research Techniques: Children's Language." Major chapters…

78 FR 49335 - Agency Information Collection (Ethics Consultation Feedback Tool (ECFT)) Activity Under OMB Review

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-13

... DEPARTMENT OF VETERANS AFFAIRS [OMB Control No. 2900-0750] Agency Information Collection (Ethics...-0750''. SUPPLEMENTARY INFORMATION: Title: Ethics Consultation Feedback Tool (ECFT), VA Form 10-10065... experience during the Ethics Consultation Service. VA will be used the data to improve the process of ethics...

78 FR 37521 - Proposed Establishment of a Federally Funded Research and Development Center-Second Notice

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-21

... collaboration for accelerating the widespread adoption of integrated cybersecurity tools and technologies. This..., Gaithersburg, MD 20899-1640. SUPPLEMENTARY INFORMATION: The National Cybersecurity Center of Excellence (NCCoE... cybersecurity tools and technologies. The NCCoE will bring together experts from industry, government and...

76 FR 33365 - Solicitation for a Cooperative Agreement: Document-Tools for Implementing Inmate Behavior...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-08

...: Document--Tools for Implementing Inmate Behavior Management; Setting Measurable Goals AGENCY: National... elements of inmate behavior management (IBM), as defined by NIC. This document will be written in the context of inmate behavior management, which is described under SUPPLEMENTARY INFORMATION below. This...

Learning by Reading for Robust Reasoning in Intelligent Agents

DTIC Science & Technology

2018-04-24

SUPPLEMENTARY NOTES 14. ABSTRACT Our hypotheses are that analogical processing plays multiple roles in enabling machines to learn by reading, and that...systems). Our overall hypotheses are that analogical processing plays multiple roles in learning by reading, and that qualitative representations provide...from reading this text? Narrative function can be seen as a kind of communication act, but the idea goes a bit beyond that. Communication acts are

Parallel Alterations of Functional Connectivity during Execution and Imagination after Motor Imagery Learning

PubMed Central

Zhang, Rushao; Hui, Mingqi; Long, Zhiying; Zhao, Xiaojie; Yao, Li

2012-01-01

Background Neural substrates underlying motor learning have been widely investigated with neuroimaging technologies. Investigations have illustrated the critical regions of motor learning and further revealed parallel alterations of functional activation during imagination and execution after learning. However, little is known about the functional connectivity associated with motor learning, especially motor imagery learning, although benefits from functional connectivity analysis attract more attention to the related explorations. We explored whether motor imagery (MI) and motor execution (ME) shared parallel alterations of functional connectivity after MI learning. Methodology/Principal Findings Graph theory analysis, which is widely used in functional connectivity exploration, was performed on the functional magnetic resonance imaging (fMRI) data of MI and ME tasks before and after 14 days of consecutive MI learning. The control group had no learning. Two measures, connectivity degree and interregional connectivity, were calculated and further assessed at a statistical level. Two interesting results were obtained: (1) The connectivity degree of the right posterior parietal lobe decreased in both MI and ME tasks after MI learning in the experimental group; (2) The parallel alterations of interregional connectivity related to the right posterior parietal lobe occurred in the supplementary motor area for both tasks. Conclusions/Significance These computational results may provide the following insights: (1) The establishment of motor schema through MI learning may induce the significant decrease of connectivity degree in the posterior parietal lobe; (2) The decreased interregional connectivity between the supplementary motor area and the right posterior parietal lobe in post-test implicates the dissociation between motor learning and task performing. These findings and explanations further revealed the neural substrates underpinning MI learning and supported that the potential value of MI learning in motor function rehabilitation and motor skill learning deserves more attention and further investigation. PMID:22629308

A Study of Supplementing Conventional Business Education with Digital Games

ERIC Educational Resources Information Center

Ellahi, Abida; Zaka, Bilal; Sultan, Fahd

2017-01-01

This paper documents how the adoption of digital games by academia reshapes the current worldview by bringing the potential answers for all learning issues. The central objective of this study is to investigate the extent to which digital games can impact learning effectiveness, and to what extent these games can be used as supplementary elements…

Movie Effects on EFL Learners at Iraqi School in Kuala Lumpur

ERIC Educational Resources Information Center

Yaseen, Bilal Huri; Shakir, Hani

2015-01-01

Previously, one of the vital tasks of English learning is to find new methods and resources to make the EFL students more stimulating and productive. Recently, the usage of movies (in DVD format) in courses became popular or supplementary resources to learn English among EFL learners. Many researchers stated that authentic video is an advantage…

Technology Is the Answer, But What Was the Question? Audiotape vs. Videotape for Individualized Instruction.

ERIC Educational Resources Information Center

Tabachnick, Barbara Gerson; And Others

1978-01-01

In an evaluation of supplementary learning aids students were assigned to one of four learning conditions: (1) videotape plus worksheet, (2) audiotape plus worksheet, (3) combination of audio- and videotape plus worksheet, and (4) worksheet only. Results reported include test scores and ratings of helpfulness, as well as student preferences and…

Evaluation of Online Video Usage and Learning Satisfaction: An Extension of the Technology Acceptance Model

ERIC Educational Resources Information Center

Nagy, Judit T.

2018-01-01

The aim of the study was to examine the determining factors of students' video usage and their learning satisfaction relating to the supplementary application of educational videos, accessible in a Moodle environment in a Business Mathematics Course. The research model is based on the extension of "Technology Acceptance Model" (TAM), in…

A Near-Reality Approach to Improve the e-Learning Open Courseware

ERIC Educational Resources Information Center

Yu, Pao-Ta; Liao, Yuan-Hsun; Su, Ming-Hsiang

2013-01-01

The open courseware proposed by MIT with single streaming video has been widely accepted by most of the universities as their supplementary learning contents. In this streaming video, a digital video camera is used to capture the speaker's gesture and his/her PowerPoint presentation at the same time. However, the blurry content of PowerPoint…

Usefulness and accuracy of MALDI-TOF mass spectrometry as a supplementary tool to identify mosquito vector species and to invest in development of international database.

PubMed

Raharimalala, F N; Andrianinarivomanana, T M; Rakotondrasoa, A; Collard, J M; Boyer, S

2017-09-01

Arthropod-borne diseases are important causes of morbidity and mortality. The identification of vector species relies mainly on morphological features and/or molecular biology tools. The first method requires specific technical skills and may result in misidentifications, and the second method is time-consuming and expensive. The aim of the present study is to assess the usefulness and accuracy of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) as a supplementary tool with which to identify mosquito vector species and to invest in the creation of an international database. A total of 89 specimens belonging to 10 mosquito species were selected for the extraction of proteins from legs and for the establishment of a reference database. A blind test with 123 mosquitoes was performed to validate the MS method. Results showed that: (a) the spectra obtained in the study with a given species differed from the spectra of the same species collected in another country, which highlights the need for an international database; (b) MALDI-TOF MS is an accurate method for the rapid identification of mosquito species that are referenced in a database; (c) MALDI-TOF MS allows the separation of groups or complex species, and (d) laboratory specimens undergo a loss of proteins compared with those isolated in the field. In conclusion, MALDI-TOF MS is a useful supplementary tool for mosquito identification and can help inform vector control. © 2017 The Royal Entomological Society.

Integrating Six Sigma Concepts in an MBA Quality Management Class

ERIC Educational Resources Information Center

Weinstein, Larry B.; Petrick, Joseph; Castellano, Joseph; Vokurka, Robert J.

2008-01-01

Instructors face enormous challenges in presenting effective instruction on concepts and tools of quality management. Most textbooks focus on presenting individual concepts or tools and fail to address complex issues confronted in real-world problem-solving situations. The supplementary use of cases does not help students to understand the dynamic…

Podcasting in the STEM disciplines: the implications of supplementary lecture recording and 'lecture flipping'.

PubMed

Hadjianastasis, Marios; Nightingale, Karl P

2016-02-01

Lecture capture or 'podcasting' technology offers a new and engaging format of learning materials that can be used to increase the flexibility and interactivity of learning and teaching environments. Here we discuss different ways that these recordings can be incorporated into STEM discipline teaching, and the impact this can have on students' learning. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The Astronomy Workshop: Computer Assisted Learning Tools with Instructor Support Materials and Student Activities

NASA Astrophysics Data System (ADS)

Deming, Grace; Hamilton, D.; Hayes-Gehrke, M.

2006-12-01

The Astronomy Workshop (http://janus.astro.umd.edu) is a collection of interactive World Wide Web tools that were developed under the direction of Doug Hamilton for use in undergraduate classes, as supplementary materials appropriate for grades 9-12, and by the general public. The philosophy of the website is to foster student and public interest in astronomy by capitalizing on their fascination with computers and the internet. Many of the tools were developed by graduate and undergraduate students at UMD. This website contains over 20 tools on topics including scientific notation, giant impacts, extrasolar planets, astronomical distances, planets, moons, comets, and asteroids. Educators around the country at universities, colleges, and secondary schools have used the Astronomy Workshop’s tools and activities as homework assignments, in-class demos, or extra credit. Since 2005, Grace Deming has assessed several of the Astronomy Workshop’s tools for clarity and effectiveness by interviewing students as they used tools on the website. Based on these interviews, Deming wrote student activities and instructor support materials and posted them to the website. Over the next three years, we will continue to interview students, develop web materials, and field-test activities. We are targeting classes in introductory undergraduate astronomy courses and grades 11-12 for our Spring 2007 field tests. We are interested in hearing your ideas on how we can make the Astronomy Workshop more appealing to educators, museum directors, specialty programs, and professors. This research is funded by NASA EPO grants NNG04GM18G and NNG06GGF99G.

Discrete mixture modeling to address genetic heterogeneity in time-to-event regression

PubMed Central

Eng, Kevin H.; Hanlon, Bret M.

2014-01-01

Motivation: Time-to-event regression models are a critical tool for associating survival time outcomes with molecular data. Despite mounting evidence that genetic subgroups of the same clinical disease exist, little attention has been given to exploring how this heterogeneity affects time-to-event model building and how to accommodate it. Methods able to diagnose and model heterogeneity should be valuable additions to the biomarker discovery toolset. Results: We propose a mixture of survival functions that classifies subjects with similar relationships to a time-to-event response. This model incorporates multivariate regression and model selection and can be fit with an expectation maximization algorithm, we call Cox-assisted clustering. We illustrate a likely manifestation of genetic heterogeneity and demonstrate how it may affect survival models with little warning. An application to gene expression in ovarian cancer DNA repair pathways illustrates how the model may be used to learn new genetic subsets for risk stratification. We explore the implications of this model for censored observations and the effect on genomic predictors and diagnostic analysis. Availability and implementation: R implementation of CAC using standard packages is available at https://gist.github.com/programeng/8620b85146b14b6edf8f Data used in the analysis are publicly available. Contact: kevin.eng@roswellpark.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24532723

DeepMirTar: a deep-learning approach for predicting human miRNA targets.

PubMed

Wen, Ming; Cong, Peisheng; Zhang, Zhimin; Lu, Hongmei; Li, Tonghua

2018-06-01

MicroRNAs (miRNAs) are small noncoding RNAs that function in RNA silencing and post-transcriptional regulation of gene expression by targeting messenger RNAs (mRNAs). Because the underlying mechanisms associated with miRNA binding to mRNA are not fully understood, a major challenge of miRNA studies involves the identification of miRNA-target sites on mRNA. In silico prediction of miRNA-target sites can expedite costly and time-consuming experimental work by providing the most promising miRNA-target-site candidates. In this study, we reported the design and implementation of DeepMirTar, a deep-learning-based approach for accurately predicting human miRNA targets at the site level. The predicted miRNA-target sites are those having canonical or non-canonical seed, and features, including high-level expert-designed, low-level expert-designed, and raw-data-level, were used to represent the miRNA-target site. Comparison with other state-of-the-art machine-learning methods and existing miRNA-target-prediction tools indicated that DeepMirTar improved overall predictive performance. DeepMirTar is freely available at https://github.com/Bjoux2/DeepMirTar_SdA. lith@tongji.edu.cn, hongmeilu@csu.edu.cn. Supplementary data are available at Bioinformatics online.

Facilitating Vocational Development Among Disadvantaged Inner-City Adolescents

ERIC Educational Resources Information Center

Hamdani, Asma

1977-01-01

The purpose of this study was to investigate whether the vocational development process of tenth-grade disadvantaged students can be facilitated through deliberate intervention in the form of supplementary learning experiences. (Author)

The Support to Rural India's Public Education System (STRIPES) trial: a cluster randomised controlled trial of supplementary teaching, learning material and material support.

PubMed

Lakshminarayana, Rashmi; Eble, Alex; Bhakta, Preetha; Frost, Chris; Boone, Peter; Elbourne, Diana; Mann, Vera

2013-01-01

The aim of the STRIPES trial was to assess the effectiveness of providing supplementary, remedial teaching and learning materials (and an additional 'kit' of materials for girls) on a composite of language and mathematics test scores for children in classes two, three and four in public primary schools in villages in the Nagarkurnool division of Andhra Pradesh, India. STRIPES was a cluster randomised trial in which 214 villages were allocated either to the supplementary teaching intervention (n = 107) or to serve as controls (n = 107). 54 of the intervention villages were further randomly allocated to receive additional kit for girls. The study was not blinded. Analysis was conducted on the intention to treat principle, allowing for clustering. Composite test scores were significantly higher in the intervention group (107 villages; 2364 children) than in the control group (106 villages; 2014 children) at the end of the trial (mean difference on a percentage scale 15.8; 95% CI 13.1 to 18.6; p<0.001; 0.75 Standard Deviation (SD) difference). Composite test scores were not significantly different in the 54 villages (614 girls) with the additional kits for girls compared to the 53 villages (636 girls) without these kits at the end of the trial (mean difference on a percentage scale 0.5; 95% CI -4.34 to 5.4; p = 0.84). The cost per 0.1 SD increase in composite test score for intervention without kits is Rs. 382.97 (£4.45, $7.13), and Rs.480.59 (£5.58, $8.94) for the intervention with kits. A 18 month programme of supplementary remedial teaching and learning materials had a substantial impact on language and mathematics scores of primary school students in rural Andhra Pradesh, yet providing a 'kit' of materials to girls in these villages did not lead to any measured additional benefit. Controlled-Trials.com ISRCTN69951502.

QUAST: quality assessment tool for genome assemblies.

PubMed

Gurevich, Alexey; Saveliev, Vladislav; Vyahhi, Nikolay; Tesler, Glenn

2013-04-15

Limitations of genome sequencing techniques have led to dozens of assembly algorithms, none of which is perfect. A number of methods for comparing assemblers have been developed, but none is yet a recognized benchmark. Further, most existing methods for comparing assemblies are only applicable to new assemblies of finished genomes; the problem of evaluating assemblies of previously unsequenced species has not been adequately considered. Here, we present QUAST-a quality assessment tool for evaluating and comparing genome assemblies. This tool improves on leading assembly comparison software with new ideas and quality metrics. QUAST can evaluate assemblies both with a reference genome, as well as without a reference. QUAST produces many reports, summary tables and plots to help scientists in their research and in their publications. In this study, we used QUAST to compare several genome assemblers on three datasets. QUAST tables and plots for all of them are available in the Supplementary Material, and interactive versions of these reports are on the QUAST website. http://bioinf.spbau.ru/quast . Supplementary data are available at Bioinformatics online.

Unbiased classification of spatial strategies in the Barnes maze.

PubMed

Illouz, Tomer; Madar, Ravit; Clague, Charlotte; Griffioen, Kathleen J; Louzoun, Yoram; Okun, Eitan

2016-11-01

Spatial learning is one of the most widely studied cognitive domains in neuroscience. The Morris water maze and the Barnes maze are the most commonly used techniques to assess spatial learning and memory in rodents. Despite the fact that these tasks are well-validated paradigms for testing spatial learning abilities, manual categorization of performance into behavioral strategies is subject to individual interpretation, and thus to bias. We have previously described an unbiased machine-learning algorithm to classify spatial strategies in the Morris water maze. Here, we offer a support vector machine-based, automated, Barnes-maze unbiased strategy (BUNS) classification algorithm, as well as a cognitive score scale that can be used for memory acquisition, reversal training and probe trials. The BUNS algorithm can greatly benefit Barnes maze users as it provides a standardized method of strategy classification and cognitive scoring scale, which cannot be derived from typical Barnes maze data analysis. Freely available on the web at http://okunlab.wix.com/okunlab as a MATLAB application. eitan.okun@biu.ac.ilSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Learning to prescribe - pharmacists' experiences of supplementary prescribing training in England.

PubMed

Cooper, Richard J; Lymn, Joanne; Anderson, Claire; Avery, Anthony; Bissell, Paul; Guillaume, Louise; Hutchinson, Allen; Murphy, Elizabeth; Ratcliffe, Julie; Ward, Paul

2008-12-05

The introduction of non-medical prescribing for professions such as pharmacy and nursing in recent years offers additional responsibilities and opportunities but attendant training issues. In the UK and in contrast to some international models, becoming a non-medical prescriber involves the completion of an accredited training course offered by many higher education institutions, where the skills and knowledge necessary for prescribing are learnt. to explore pharmacists' perceptions and experiences of learning to prescribe on supplementary prescribing (SP) courses, particularly in relation to inter-professional learning, course content and subsequent use of prescribing in practice. A postal questionnaire survey was sent to all 808 SP registered pharmacists in England in April 2007, exploring demographic, training, prescribing, safety culture and general perceptions of SP. After one follow-up, 411 (51%) of pharmacists responded. 82% agreed SP training was useful, 58% agreed courses provided appropriate knowledge and 62% agreed that the necessary prescribing skills were gained. Clinical examination, consultation skills training and practical experience with doctors were valued highly; pharmacology training and some aspects of course delivery were criticised. Mixed views on inter-professional learning were reported - insights into other professions being valued but knowledge and skills differences considered problematic. 67% believed SP and recent independent prescribing (IP) should be taught together, with more diagnostic training wanted; few pharmacists trained in IP, but many were training or intending to train. There was no association between pharmacists' attitudes towards prescribing training and when they undertook training between 2004 and 2007 but earlier cohorts were more likely to be using supplementary prescribing in practice. Pharmacists appeared to value their SP training and suggested improvements that could inform future courses. The benefits of inter-professional learning, however, may conflict with providing profession-specific training. SP training may be perceived to be an instrumental 'stepping stone' in pharmacists' professional project of gaining full IP status.

Effect of transcranial direct current stimulation (tDCS) during complex whole body motor skill learning.

PubMed

Kaminski, Elisabeth; Hoff, Maike; Sehm, Bernhard; Taubert, Marco; Conde, Virginia; Steele, Christopher J; Villringer, Arno; Ragert, Patrick

2013-09-27

The aim of the study was to investigate tDCS effects on motor skill learning in a complex whole body dynamic balance task (DBT). We hypothesized that tDCS over the supplementary motor area (SMA), a region that is known to be involved in the control of multi-joint whole body movements, will result in polarity specific changes in DBT learning. In a randomized sham-controlled, double-blinded parallel design, we applied 20 min of tDCS over the supplementary motor area (SMA) and prefrontal cortex (PFC) while subjects performed a DBT. Anodal tDCS over SMA with the cathode placed over contralateral PFC impaired motor skill learning of the DBT compared to sham. This effect was still present on the second day of training. Reversing the polarity (cathode over SMA, anode over PFC) did not affect motor skill learning neither on the first nor on the second day of training. To better disentangle whether the impaired motor skill learning was due to a modulation of SMA or PFC, we performed an additional control experiment. Here, we applied anodal tDCS over SMA together with a larger and presumably more ineffective electrode (cathode) over PFC. Interestingly this alternative tDCS electrode setup did not affect the outcome of DBT learning. Our results provide novel evidence that a modulation of the (right) PFC seems to impair complex multi-joint motor skill learning. Hence, future studies should take the positioning of both tDCS electrodes into account when investigating complex motor skill learning. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Improving Balance in TBI Using a Low-Cost Customized Virtual Reality Rehabilitation Tool

DTIC Science & Technology

2016-10-01

AWARD NUMBER: W81XWH-14-2-0150 TITLE: Improving Balance in TBI Using a Low-Cost Customized Virtual Reality Rehabilitation Tool PRINCIPAL...AND SUBTITLE Improving Balance in TBI Using a Low-Cost Customized Virtual Reality Rehabilitation Tool 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH...Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The proposed study will implement and evaluate a novel, low-cost, Virtual Reality (VR

BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments

PubMed Central

Thomas, Brandon R.; Chylek, Lily A.; Colvin, Joshua; Sirimulla, Suman; Clayton, Andrew H.A.; Hlavacek, William S.; Posner, Richard G.

2016-01-01

Summary: Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive. Availability and implementation: BioNetFit can be used on stand-alone Mac, Windows/Cygwin, and Linux platforms and on Linux-based clusters running SLURM, Torque/PBS, or SGE. The BioNetFit source code (Perl) is freely available (http://bionetfit.nau.edu). Supplementary information: Supplementary data are available at Bioinformatics online. Contact: bionetgen.help@gmail.com PMID:26556387

Supplementary health insurance as a tool for risk-selection in mandatory basic health insurance markets.

PubMed

Paolucci, Francesco; Schut, Erik; Beck, Konstantin; Gress, Stefan; Van de Voorde, Carine; Zmora, Irit

2007-04-01

As the share of supplementary health insurance (SI) in health care finance is likely to grow, SI may become an increasingly attractive tool for risk-selection in basic health insurance (BI). In this paper, we develop a conceptual framework to assess the probability that insurers will use SI for favourable risk-selection in BI. We apply our framework to five countries in which risk-selection via SI is feasible: Belgium, Germany, Israel, the Netherlands, and Switzerland. For each country, we review the available evidence of SI being used as selection device. We find that the probability that SI is and will be used for risk-selection substantially varies across countries. Finally, we discuss several strategies for policy makers to reduce the chance that SI will be used for risk-selection in BI markets.

Functional differences between statistical learning with and without explicit training

PubMed Central

Reber, Paul J.; Paller, Ken A.

2015-01-01

Humans are capable of rapidly extracting regularities from environmental input, a process known as statistical learning. This type of learning typically occurs automatically, through passive exposure to environmental input. The presumed function of statistical learning is to optimize processing, allowing the brain to more accurately predict and prepare for incoming input. In this study, we ask whether the function of statistical learning may be enhanced through supplementary explicit training, in which underlying regularities are explicitly taught rather than simply abstracted through exposure. Learners were randomly assigned either to an explicit group or an implicit group. All learners were exposed to a continuous stream of repeating nonsense words. Prior to this implicit training, learners in the explicit group received supplementary explicit training on the nonsense words. Statistical learning was assessed through a speeded reaction-time (RT) task, which measured the extent to which learners used acquired statistical knowledge to optimize online processing. Both RTs and brain potentials revealed significant differences in online processing as a function of training condition. RTs showed a crossover interaction; responses in the explicit group were faster to predictable targets and marginally slower to less predictable targets relative to responses in the implicit group. P300 potentials to predictable targets were larger in the explicit group than in the implicit group, suggesting greater recruitment of controlled, effortful processes. Taken together, these results suggest that information abstracted through passive exposure during statistical learning may be processed more automatically and with less effort than information that is acquired explicitly. PMID:26472644

LitPathExplorer: a confidence-based visual text analytics tool for exploring literature-enriched pathway models.

PubMed

Soto, Axel J; Zerva, Chrysoula; Batista-Navarro, Riza; Ananiadou, Sophia

2018-04-15

Pathway models are valuable resources that help us understand the various mechanisms underpinning complex biological processes. Their curation is typically carried out through manual inspection of published scientific literature to find information relevant to a model, which is a laborious and knowledge-intensive task. Furthermore, models curated manually cannot be easily updated and maintained with new evidence extracted from the literature without automated support. We have developed LitPathExplorer, a visual text analytics tool that integrates advanced text mining, semi-supervised learning and interactive visualization, to facilitate the exploration and analysis of pathway models using statements (i.e. events) extracted automatically from the literature and organized according to levels of confidence. LitPathExplorer supports pathway modellers and curators alike by: (i) extracting events from the literature that corroborate existing models with evidence; (ii) discovering new events which can update models; and (iii) providing a confidence value for each event that is automatically computed based on linguistic features and article metadata. Our evaluation of event extraction showed a precision of 89% and a recall of 71%. Evaluation of our confidence measure, when used for ranking sampled events, showed an average precision ranging between 61 and 73%, which can be improved to 95% when the user is involved in the semi-supervised learning process. Qualitative evaluation using pair analytics based on the feedback of three domain experts confirmed the utility of our tool within the context of pathway model exploration. LitPathExplorer is available at http://nactem.ac.uk/LitPathExplorer_BI/. sophia.ananiadou@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

The Beaverton School District Arts for Learning (A4L) Lessons Project, an Investing in Innovation (i3) Development Grant: Student Impact Findings from Years 1, 2, and 3

ERIC Educational Resources Information Center

Nakamoto, Jonathan; Sobolew-Shubin, Sandy; Orland, Martin

2015-01-01

The purpose of this study was to assess the impact of the Arts for Learning (A4L) Lessons Project on the literacy and life skills of students in grades 3, 4, and 5. A4L Lessons is a supplementary literacy curriculum designed to blend the creativity and discipline of the arts with learning science to raise student achievement in reading and…

Fit, Healthy, and Ready To Learn: A School Health Policy Guide. Part II: Policies To Promote Sun Safety and Prevent Skin Cancer.

ERIC Educational Resources Information Center

Fraser, Katherine

This publication is a supplementary chapter to "Fit, Healthy, and Ready to Learn: A School Health Policy Guide; Part I: General School Health Policies, Physical Activity, Healthy Eating, and Tobacco-Use Prevention." It discusses various aspects of a complete school policy and plan to promote sun safety. The first section "Purpose…

ReactPRED: a tool to predict and analyze biochemical reactions.

PubMed

Sivakumar, Tadi Venkata; Giri, Varun; Park, Jin Hwan; Kim, Tae Yong; Bhaduri, Anirban

2016-11-15

Biochemical pathways engineering is often used to synthesize or degrade target chemicals. In silico screening of the biochemical transformation space allows predicting feasible reactions, constituting these pathways. Current enabling tools are customized to predict reactions based on pre-defined biochemical transformations or reaction rule sets. Reaction rule sets are usually curated manually and tailored to specific applications. They are not exhaustive. In addition, current systems are incapable of regulating and refining data with an aim to tune specificity and sensitivity. A robust and flexible tool that allows automated reaction rule set creation along with regulated pathway prediction and analyses is a need. ReactPRED aims to address the same. ReactPRED is an open source flexible and customizable tool enabling users to predict biochemical reactions and pathways. The tool allows automated reaction rule creation from a user defined reaction set. Additionally, reaction rule degree and rule tolerance features allow refinement of predicted data. It is available as a flexible graphical user interface and a console application. ReactPRED is available at: https://sourceforge.net/projects/reactpred/ CONTACT: anirban.b@samsung.com or ty76.kim@samsung.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

SUPER-FOCUS: a tool for agile functional analysis of shotgun metagenomic data

PubMed Central

Green, Kevin T.; Dutilh, Bas E.; Edwards, Robert A.

2016-01-01

Summary: Analyzing the functional profile of a microbial community from unannotated shotgun sequencing reads is one of the important goals in metagenomics. Functional profiling has valuable applications in biological research because it identifies the abundances of the functional genes of the organisms present in the original sample, answering the question what they can do. Currently, available tools do not scale well with increasing data volumes, which is important because both the number and lengths of the reads produced by sequencing platforms keep increasing. Here, we introduce SUPER-FOCUS, SUbsystems Profile by databasE Reduction using FOCUS, an agile homology-based approach using a reduced reference database to report the subsystems present in metagenomic datasets and profile their abundances. SUPER-FOCUS was tested with over 70 real metagenomes, the results showing that it accurately predicts the subsystems present in the profiled microbial communities, and is up to 1000 times faster than other tools. Availability and implementation: SUPER-FOCUS was implemented in Python, and its source code and the tool website are freely available at https://edwards.sdsu.edu/SUPERFOCUS. Contact: redwards@mail.sdsu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26454280

Air-Breathing Hypersonic Vehicle Tracking Control Based on Adaptive Dynamic Programming.

PubMed

Mu, Chaoxu; Ni, Zhen; Sun, Changyin; He, Haibo

2017-03-01

In this paper, we propose a data-driven supplementary control approach with adaptive learning capability for air-breathing hypersonic vehicle tracking control based on action-dependent heuristic dynamic programming (ADHDP). The control action is generated by the combination of sliding mode control (SMC) and the ADHDP controller to track the desired velocity and the desired altitude. In particular, the ADHDP controller observes the differences between the actual velocity/altitude and the desired velocity/altitude, and then provides a supplementary control action accordingly. The ADHDP controller does not rely on the accurate mathematical model function and is data driven. Meanwhile, it is capable to adjust its parameters online over time under various working conditions, which is very suitable for hypersonic vehicle system with parameter uncertainties and disturbances. We verify the adaptive supplementary control approach versus the traditional SMC in the cruising flight, and provide three simulation studies to illustrate the improved performance with the proposed approach.

Science Education in Primary Schools: Is an Animation Worth a Thousand Pictures?

NASA Astrophysics Data System (ADS)

Barak, Miri; Dori, Yehudit J.

2011-10-01

Science teaching deals with abstract concepts and processes that very often cannot be seen or touched. The development of Java, Flash, and other web-based applications allow teachers and educators to present complex animations that attractively illustrate scientific phenomena. Our study evaluated the integration of web-based animated movies into primary schools science curriculum. Our goal was to examine teachers' methods for integrating animated movies and their views about the role of animations in enhancing young students' thinking skills. We also aimed at investigating the effect of animated movies on students' learning outcomes. Applying qualitative and quantitative tools, we conducted informal discussions with science teachers (N = 15) and administered pre- and post-questionnaires to 4th (N = 641) and 5th (N = 694) grade students who were divided into control and experimental groups. The experimental group students studied science while using animated movies and supplementary activities at least once a week. The control group students used only textbooks and still-pictures for learning science. Findings indicated that animated movies support the use of diverse teaching strategies and learning methods, and can promote various thinking skills among students. Findings also indicated that animations can enhance scientific curiosity, the acquisition of scientific language, and fostering scientific thinking. These encouraging results can be explained by the fact that the students made use of both visual-pictorial and auditory-verbal capabilities while exploring animated movies in diverse learning styles and teaching strategies.

JADOPPT: java based AutoDock preparing and processing tool.

PubMed

García-Pérez, Carlos; Peláez, Rafael; Therón, Roberto; Luis López-Pérez, José

2017-02-15

AutoDock is a very popular software package for docking and virtual screening. However, currently it is hard work to visualize more than one result from the virtual screening at a time. To overcome this limitation we have designed JADOPPT, a tool for automatically preparing and processing multiple ligand-protein docked poses obtained from AutoDock. It allows the simultaneous visual assessment and comparison of multiple poses through clustering methods. Moreover, it permits the representation of reference ligands with known binding modes, binding site residues, highly scoring regions for the ligand, and the calculated binding energy of the best ranked results. JADOPPT, supplementary material (Case Studies 1 and 2) and video tutorials are available at http://visualanalytics.land/cgarcia/JADOPPT.html. carlosgarcia@usal.es or pelaez@usal.es. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Hyperlexia and ambient echolalia in a case of cerebral infarction of the left anterior cingulate cortex and corpus callosum.

PubMed

Suzuki, Tadashi; Itoh, Shouichi; Hayashi, Mototaka; Kouno, Masako; Takeda, Katsuhiko

2009-10-01

We report the case of a 69-year-old woman with cerebral infarction in the left anterior cingulate cortex and corpus callosum. She showed hyperlexia, which was a distinctive reading phenomenon, as well as ambient echolalia. Clinical features also included complex disorders such as visual groping, compulsive manipulation of tools, and callosal disconnection syndrome. She read words written on the cover of a book and repeated words emanating from unrelated conversations around her or from hospital announcements. The combination of these two features due to a focal lesion has never been reported previously. The supplementary motor area may control the execution of established subroutines according to external and internal inputs. Hyperlexia as well as the compulsive manipulation of tools could be interpreted as faulty inhibition of preexisting essentially intact motor subroutines by damage to the anterior cingulate cortex reciprocally interconnected with the supplementary motor area.

Biological Dynamics Markup Language (BDML): an open format for representing quantitative biological dynamics data

PubMed Central

Kyoda, Koji; Tohsato, Yukako; Ho, Kenneth H. L.; Onami, Shuichi

2015-01-01

Motivation: Recent progress in live-cell imaging and modeling techniques has resulted in generation of a large amount of quantitative data (from experimental measurements and computer simulations) on spatiotemporal dynamics of biological objects such as molecules, cells and organisms. Although many research groups have independently dedicated their efforts to developing software tools for visualizing and analyzing these data, these tools are often not compatible with each other because of different data formats. Results: We developed an open unified format, Biological Dynamics Markup Language (BDML; current version: 0.2), which provides a basic framework for representing quantitative biological dynamics data for objects ranging from molecules to cells to organisms. BDML is based on Extensible Markup Language (XML). Its advantages are machine and human readability and extensibility. BDML will improve the efficiency of development and evaluation of software tools for data visualization and analysis. Availability and implementation: A specification and a schema file for BDML are freely available online at http://ssbd.qbic.riken.jp/bdml/. Contact: sonami@riken.jp Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:25414366

Never-Ending Learning for Deep Understanding of Natural Language

DTIC Science & Technology

2017-10-01

CA policy clarification memorandum dated 16 Jan 09. 13. SUPPLEMENTARY NOTES 14. ABSTRACT This research has explored the thesis that very... thesis we have built on our earlier research on the Never Ending Language Learning (NELL) computer system, which has been running non- stop since... thesis that very significant amounts of background knowledge can lead to very substantial improvements in the accuracy of deep text analysis and

NMRNet: A deep learning approach to automated peak picking of protein NMR spectra.

PubMed

Klukowski, Piotr; Augoff, Michal; Zieba, Maciej; Drwal, Maciej; Gonczarek, Adam; Walczak, Michal J

2018-03-14

Automated selection of signals in protein NMR spectra, known as peak picking, has been studied for over 20 years, nevertheless existing peak picking methods are still largely deficient. Accurate and precise automated peak picking would accelerate the structure calculation, and analysis of dynamics and interactions of macromolecules. Recent advancement in handling big data, together with an outburst of machine learning techniques, offer an opportunity to tackle the peak picking problem substantially faster than manual picking and on par with human accuracy. In particular, deep learning has proven to systematically achieve human-level performance in various recognition tasks, and thus emerges as an ideal tool to address automated identification of NMR signals. We have applied a convolutional neural network for visual analysis of multidimensional NMR spectra. A comprehensive test on 31 manually-annotated spectra has demonstrated top-tier average precision (AP) of 0.9596, 0.9058 and 0.8271 for backbone, side-chain and NOESY spectra, respectively. Furthermore, a combination of extracted peak lists with automated assignment routine, FLYA, outperformed other methods, including the manual one, and led to correct resonance assignment at the levels of 90.40%, 89.90% and 90.20% for three benchmark proteins. The proposed model is a part of a Dumpling software (platform for protein NMR data analysis), and is available at https://dumpling.bio/. michaljerzywalczak@gmail.compiotr.klukowski@pwr.edu.pl. Supplementary data are available at Bioinformatics online.

libRoadRunner: a high performance SBML simulation and analysis library

PubMed Central

Somogyi, Endre T.; Bouteiller, Jean-Marie; Glazier, James A.; König, Matthias; Medley, J. Kyle; Swat, Maciej H.; Sauro, Herbert M.

2015-01-01

Motivation: This article presents libRoadRunner, an extensible, high-performance, cross-platform, open-source software library for the simulation and analysis of models expressed using Systems Biology Markup Language (SBML). SBML is the most widely used standard for representing dynamic networks, especially biochemical networks. libRoadRunner is fast enough to support large-scale problems such as tissue models, studies that require large numbers of repeated runs and interactive simulations. Results: libRoadRunner is a self-contained library, able to run both as a component inside other tools via its C++ and C bindings, and interactively through its Python interface. Its Python Application Programming Interface (API) is similar to the APIs of MATLAB (www.mathworks.com) and SciPy (http://www.scipy.org/), making it fast and easy to learn. libRoadRunner uses a custom Just-In-Time (JIT) compiler built on the widely used LLVM JIT compiler framework. It compiles SBML-specified models directly into native machine code for a variety of processors, making it appropriate for solving extremely large models or repeated runs. libRoadRunner is flexible, supporting the bulk of the SBML specification (except for delay and non-linear algebraic equations) including several SBML extensions (composition and distributions). It offers multiple deterministic and stochastic integrators, as well as tools for steady-state analysis, stability analysis and structural analysis of the stoichiometric matrix. Availability and implementation: libRoadRunner binary distributions are available for Mac OS X, Linux and Windows. The library is licensed under Apache License Version 2.0. libRoadRunner is also available for ARM-based computers such as the Raspberry Pi. http://www.libroadrunner.org provides online documentation, full build instructions, binaries and a git source repository. Contacts: hsauro@u.washington.edu or somogyie@indiana.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26085503

Developing Save Your Food Kit (Sayofu Kit) to Support Inquiry, Improve Student Learning Outcomes at SMP Plus Hidayatul Mubtadiin and Public Awareness on Food Additives

NASA Astrophysics Data System (ADS)

Astutik, J.

2017-02-01

Food additives are materials that can not be separated from the lives of students and the community. Based on the preliminary questionnaire, it indicates the lack of kit supporting material additives in some schools and communities. The research objectives of this development are (1) to develop Kit experiment (SAYOFU KIT) and supplementary books to improve student learning outcomes in the classroom and public awareness on food additives (2) to describe the feasibility and potential effectiveness of SAYOFU KIT developed (3) to analyze the practice of SAYOFU KIT and benefits for students and the community. This development study uses 4-D models Thiagarajan, et al (1974). Through some stages, they are: defining, designing, developing and disseminating which involes the students and community. The developed SAYOFU KIT includes additives sample kit, borax test kit, curcumin test kit, formaldehyde test kit, modification heater to the identification of dyes and dye test paper. The study is conducted at SMP Plus Hidayatul Mubtadiin, and TKIT Al Uswah. The products are validated by experts and education practitioners. Qualitative data processing uses descriptive method, whereas quantitative data by using the N-gain. The average yield of expert validation of SAYOFU KIT with supplementary books 76.50% teacher’s book and 76.30% student’s book are eligible. The average yield of 96.81% validation of educational practitioners criteria, piloting a small group of 83.15%, and 82.89% field trials are very decent. The average yield on the student questionnaire responses SAYOFU kit and supplementary book is 87.6% with the criteria very well worth it. N-Gain 0:56 cognitive achievement with the criteria enough. The results of the public poll showed 95% feel the benefits SAYOFU kits for testing food. Based from description indicates that SAYOFU Kit developed feasible, practical, useful to support inquiry learning and improve student learning outcomes as well as public awareness of food additives.

Agricultural Record Keeping. Instructor Key and Supplementary Units.

ERIC Educational Resources Information Center

Martin, Donna

This teaching manual is designed to help students with special needs learn and apply recordkeeping skills in agriculture. The material applies specifically to recordkeeping for a supervised agricultural experience program. The units presented here supplement the curriculum guide, "Developing Programs of Supervised Agricultural…

French Teaching Aids.

ERIC Educational Resources Information Center

Miller, J. Dale

Supplementary teaching materials for French language programs are presented in this text. Primarily intended for secondary school students, the study contains seven units of material. They include: (1) French gestures, (2) teaching the interrogative pronouns, (3) French cuisine, (4) recreational learning games, (5) French-English cognates, (6)…

MPRAnator: a web-based tool for the design of massively parallel reporter assay experiments

PubMed Central

Georgakopoulos-Soares, Ilias; Jain, Naman; Gray, Jesse M; Hemberg, Martin

2017-01-01

Motivation: With the rapid advances in DNA synthesis and sequencing technologies and the continuing decline in the associated costs, high-throughput experiments can be performed to investigate the regulatory role of thousands of oligonucleotide sequences simultaneously. Nevertheless, designing high-throughput reporter assay experiments such as massively parallel reporter assays (MPRAs) and similar methods remains challenging. Results: We introduce MPRAnator, a set of tools that facilitate rapid design of MPRA experiments. With MPRA Motif design, a set of variables provides fine control of how motifs are placed into sequences, thereby allowing the investigation of the rules that govern transcription factor (TF) occupancy. MPRA single-nucleotide polymorphism design can be used to systematically examine the functional effects of single or combinations of single-nucleotide polymorphisms at regulatory sequences. Finally, the Transmutation tool allows for the design of negative controls by permitting scrambling, reversing, complementing or introducing multiple random mutations in the input sequences or motifs. Availability and implementation: MPRAnator tool set is implemented in Python, Perl and Javascript and is freely available at www.genomegeek.com and www.sanger.ac.uk/science/tools/mpranator. The source code is available on www.github.com/hemberg-lab/MPRAnator/ under the MIT license. The REST API allows programmatic access to MPRAnator using simple URLs. Contact: igs@sanger.ac.uk or mh26@sanger.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27605100

MPRAnator: a web-based tool for the design of massively parallel reporter assay experiments.

PubMed

Georgakopoulos-Soares, Ilias; Jain, Naman; Gray, Jesse M; Hemberg, Martin

2017-01-01

With the rapid advances in DNA synthesis and sequencing technologies and the continuing decline in the associated costs, high-throughput experiments can be performed to investigate the regulatory role of thousands of oligonucleotide sequences simultaneously. Nevertheless, designing high-throughput reporter assay experiments such as massively parallel reporter assays (MPRAs) and similar methods remains challenging. We introduce MPRAnator, a set of tools that facilitate rapid design of MPRA experiments. With MPRA Motif design, a set of variables provides fine control of how motifs are placed into sequences, thereby allowing the investigation of the rules that govern transcription factor (TF) occupancy. MPRA single-nucleotide polymorphism design can be used to systematically examine the functional effects of single or combinations of single-nucleotide polymorphisms at regulatory sequences. Finally, the Transmutation tool allows for the design of negative controls by permitting scrambling, reversing, complementing or introducing multiple random mutations in the input sequences or motifs. MPRAnator tool set is implemented in Python, Perl and Javascript and is freely available at www.genomegeek.com and www.sanger.ac.uk/science/tools/mpranator The source code is available on www.github.com/hemberg-lab/MPRAnator/ under the MIT license. The REST API allows programmatic access to MPRAnator using simple URLs. igs@sanger.ac.uk or mh26@sanger.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

cTBS disruption of the supplementary motor area perturbs cortical sequence representation but not behavioural performance.

PubMed

Solopchuk, Oleg; Alamia, Andrea; Dricot, Laurence; Duque, Julie; Zénon, Alexandre

2017-12-01

Neuroimaging studies have repeatedly emphasized the role of the supplementary motor area (SMA) in motor sequence learning, but interferential approaches have led to inconsistent findings. Here, we aimed to test the role of the SMA in motor skill learning by combining interferential and neuroimaging techniques. Sixteen subjects were trained on simple finger movement sequences for 4 days. Afterwards, they underwent two neuroimaging sessions, in which they executed both trained and novel sequences. Prior to entering the scanner, the subjects received inhibitory transcranial magnetic stimulation (TMS) over the SMA or a control site. Using multivariate fMRI analysis, we confirmed that motor training enhances the neural representation of motor sequences in the SMA, in accordance with previous findings. However, although SMA inhibition altered sequence representation (i.e. between-sequence decoding accuracy) in this area, behavioural performance remained unimpaired. Our findings question the causal link between the neuroimaging correlate of elementary motor sequence representation in the SMA and sequence generation, calling for a more thorough investigation of the role of this region in performance of learned motor sequences. Copyright © 2017 Elsevier Inc. All rights reserved.

Dynamic Vision for Control

DTIC Science & Technology

2006-07-27

unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The goal of this project was to develop analytical and computational tools to make vision a Viable sensor for...vision.ucla. edu July 27, 2006 Abstract The goal of this project was to develop analytical and computational tools to make vision a viable sensor for the ... sensors . We have proposed the framework of stereoscopic segmentation where multiple images of the same obejcts were jointly processed to extract geometry

Automated benchmarking of peptide-MHC class I binding predictions

PubMed Central

Trolle, Thomas; Metushi, Imir G.; Greenbaum, Jason A.; Kim, Yohan; Sidney, John; Lund, Ole; Sette, Alessandro; Peters, Bjoern; Nielsen, Morten

2015-01-01

Motivation: Numerous in silico methods predicting peptide binding to major histocompatibility complex (MHC) class I molecules have been developed over the last decades. However, the multitude of available prediction tools makes it non-trivial for the end-user to select which tool to use for a given task. To provide a solid basis on which to compare different prediction tools, we here describe a framework for the automated benchmarking of peptide-MHC class I binding prediction tools. The framework runs weekly benchmarks on data that are newly entered into the Immune Epitope Database (IEDB), giving the public access to frequent, up-to-date performance evaluations of all participating tools. To overcome potential selection bias in the data included in the IEDB, a strategy was implemented that suggests a set of peptides for which different prediction methods give divergent predictions as to their binding capability. Upon experimental binding validation, these peptides entered the benchmark study. Results: The benchmark has run for 15 weeks and includes evaluation of 44 datasets covering 17 MHC alleles and more than 4000 peptide-MHC binding measurements. Inspection of the results allows the end-user to make educated selections between participating tools. Of the four participating servers, NetMHCpan performed the best, followed by ANN, SMM and finally ARB. Availability and implementation: Up-to-date performance evaluations of each server can be found online at http://tools.iedb.org/auto_bench/mhci/weekly. All prediction tool developers are invited to participate in the benchmark. Sign-up instructions are available at http://tools.iedb.org/auto_bench/mhci/join. Contact: mniel@cbs.dtu.dk or bpeters@liai.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25717196

Psychological Anthropology: A Modular Approach. Cultural Anthropology.

ERIC Educational Resources Information Center

Kassebaum, Peter

Designed for use as supplementary instructional material in a cultural anthropology course, this learning module traces the history of psychological anthropology, introducing various schools and perspectives within the field of psychology. First, a discussion is provided of biological determinism, examining its historical development and the…

78 FR 43921 - Solicitation for a Cooperative Agreement-Core Competencies for Corrections Learning and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-22

... DEPARTMENT OF JUSTICE National Institute of Corrections Solicitation for a Cooperative Agreement... Corrections, U.S. Department of Justice. ACTION: Solicitation for a Cooperative Agreement. SUMMARY: The..., educational institution, organization, individual or team with expertise in the described areas. SUPPLEMENTARY...

Hoer-Sprech-Uebungen fuer Iraner (Aural-Oral Exercises for Iranians).

ERIC Educational Resources Information Center

Scharf, Kurt

1980-01-01

Exercises are presented as supplementary material for beginning classes. Many examples illustrate ways to consolidate the learned material, with particular reference to the textbook "Ich lerne Deutsch" and its pictures. Other exercises are designed to compare German and Farsi sentence structure. (IFS/WGA)

Anthropological Theory: A Modular Approach. Cultural Anthropology.

ERIC Educational Resources Information Center

Kassebaum, Peter

Designed for use as supplementary instructional material in a cultural anthropology course, this learning module introduces the student to various theoretical perspectives, terms, and influential figures within the field of anthropology. The following historical and conceptual influences on anthropological theory are discussed: (1) the Greek…

A Technology Enhanced Learning Model for Quality Education

NASA Astrophysics Data System (ADS)

Sherly, Elizabeth; Uddin, Md. Meraj

Technology Enhanced Learning and Teaching (TELT) Model provides learning through collaborations and interactions with a framework for content development and collaborative knowledge sharing system as a supplementary for learning to improve the quality of education system. TELT deals with a unique pedagogy model for Technology Enhanced Learning System which includes course management system, digital library, multimedia enriched contents and video lectures, open content management system and collaboration and knowledge sharing systems. Open sources like Moodle and Wiki for content development, video on demand solution with a low cost mid range system, an exhaustive digital library are provided in a portal system. The paper depicts a case study of e-learning initiatives with TELT model at IIITM-K and how effectively implemented.

Eutrophication, A Natural Process.

ERIC Educational Resources Information Center

Monsour, William

This environmental education learning unit deals with the topic of eutrophication. The unit is designed to allow secondary teachers of science, language arts, and social studies to use it as supplementary material in their classroom. Teacher information, unit objectives, the unit text, and appendices are included. The teacher information section…

Health Care Assistant. Instructor [Guide.] Revised.

ERIC Educational Resources Information Center

Missouri Univ., Columbia. Instructional Materials Lab.

This instructor's guide contains 65 lessons designed to aid teachers in presenting a course in basic nursing procedures for students studying for careers as health care assistants. Lesson plans consist of a scope, objectives, suggested supplementary teaching and learning items; references, an introduction, a lesson outline, handouts, evaluation…

Trans-species learning of cellular signaling systems with bimodal deep belief networks

PubMed Central

Chen, Lujia; Cai, Chunhui; Chen, Vicky; Lu, Xinghua

2015-01-01

Motivation: Model organisms play critical roles in biomedical research of human diseases and drug development. An imperative task is to translate information/knowledge acquired from model organisms to humans. In this study, we address a trans-species learning problem: predicting human cell responses to diverse stimuli, based on the responses of rat cells treated with the same stimuli. Results: We hypothesized that rat and human cells share a common signal-encoding mechanism but employ different proteins to transmit signals, and we developed a bimodal deep belief network and a semi-restricted bimodal deep belief network to represent the common encoding mechanism and perform trans-species learning. These ‘deep learning’ models include hierarchically organized latent variables capable of capturing the statistical structures in the observed proteomic data in a distributed fashion. The results show that the models significantly outperform two current state-of-the-art classification algorithms. Our study demonstrated the potential of using deep hierarchical models to simulate cellular signaling systems. Availability and implementation: The software is available at the following URL: http://pubreview.dbmi.pitt.edu/TransSpeciesDeepLearning/. The data are available through SBV IMPROVER website, https://www.sbvimprover.com/challenge-2/overview, upon publication of the report by the organizers. Contact: xinghua@pitt.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25995230

78 FR 15403 - Agency Information Collection Activities; Proposed Collection; Comment Request; Company-Run...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-11

... Activities; Proposed Collection; Comment Request; Company-Run Annual Stress Test Reporting Template and... Federal savings associations titled, ``Company-Run Annual Stress Test Reporting Template and Documentation....occ.gov/tools-forms/forms/bank-operations/stress-test-reporting.html ). SUPPLEMENTARY INFORMATION: The...

What Is Career English?

ERIC Educational Resources Information Center

Brevard County School Board, Cocoa, FL.

English courses which involve the language arts skills and which should be incorporated into major career areas are described in this guide. The guide also describes the units, procedures, activities, supplementary materials, and evaluation tools and is keyed--by number--to the State Accreditation Standards and assessment objectives. Teaching…

Hadoop-BAM: directly manipulating next generation sequencing data in the cloud

PubMed Central

Niemenmaa, Matti; Kallio, Aleksi; Schumacher, André; Klemelä, Petri; Korpelainen, Eija; Heljanko, Keijo

2012-01-01

Summary: Hadoop-BAM is a novel library for the scalable manipulation of aligned next-generation sequencing data in the Hadoop distributed computing framework. It acts as an integration layer between analysis applications and BAM files that are processed using Hadoop. Hadoop-BAM solves the issues related to BAM data access by presenting a convenient API for implementing map and reduce functions that can directly operate on BAM records. It builds on top of the Picard SAM JDK, so tools that rely on the Picard API are expected to be easily convertible to support large-scale distributed processing. In this article we demonstrate the use of Hadoop-BAM by building a coverage summarizing tool for the Chipster genome browser. Our results show that Hadoop offers good scalability, and one should avoid moving data in and out of Hadoop between analysis steps. Availability: Available under the open-source MIT license at http://sourceforge.net/projects/hadoop-bam/ Contact: matti.niemenmaa@aalto.fi Supplementary information: Supplementary material is available at Bioinformatics online. PMID:22302568

Phyx: phylogenetic tools for unix

PubMed Central

Brown, Joseph W.; Walker, Joseph F.; Smith, Stephen A.

2017-01-01

Abstract Summary: The ease with which phylogenomic data can be generated has drastically escalated the computational burden for even routine phylogenetic investigations. To address this, we present phyx: a collection of programs written in C ++ to explore, manipulate, analyze and simulate phylogenetic objects (alignments, trees and MCMC logs). Modelled after Unix/GNU/Linux command line tools, individual programs perform a single task and operate on standard I/O streams that can be piped to quickly and easily form complex analytical pipelines. Because of the stream-centric paradigm, memory requirements are minimized (often only a single tree or sequence in memory at any instance), and hence phyx is capable of efficiently processing very large datasets. Availability and Implementation: phyx runs on POSIX-compliant operating systems. Source code, installation instructions, documentation and example files are freely available under the GNU General Public License at https://github.com/FePhyFoFum/phyx Contact: eebsmith@umich.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28174903

BioQ: tracing experimental origins in public genomic databases using a novel data provenance model

PubMed Central

Saccone, Scott F.; Quan, Jiaxi; Jones, Peter L.

2012-01-01

Motivation: Public genomic databases, which are often used to guide genetic studies of human disease, are now being applied to genomic medicine through in silico integrative genomics. These databases, however, often lack tools for systematically determining the experimental origins of the data. Results: We introduce a new data provenance model that we have implemented in a public web application, BioQ, for assessing the reliability of the data by systematically tracing its experimental origins to the original subjects and biologics. BioQ allows investigators to both visualize data provenance as well as explore individual elements of experimental process flow using precise tools for detailed data exploration and documentation. It includes a number of human genetic variation databases such as the HapMap and 1000 Genomes projects. Availability and implementation: BioQ is freely available to the public at http://bioq.saclab.net Contact: ssaccone@wustl.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22426342

XLinkDB 2.0: integrated, large-scale structural analysis of protein crosslinking data

PubMed Central

Schweppe, Devin K.; Zheng, Chunxiang; Chavez, Juan D.; Navare, Arti T.; Wu, Xia; Eng, Jimmy K.; Bruce, James E.

2016-01-01

Motivation: Large-scale chemical cross-linking with mass spectrometry (XL-MS) analyses are quickly becoming a powerful means for high-throughput determination of protein structural information and protein–protein interactions. Recent studies have garnered thousands of cross-linked interactions, yet the field lacks an effective tool to compile experimental data or access the network and structural knowledge for these large scale analyses. We present XLinkDB 2.0 which integrates tools for network analysis, Protein Databank queries, modeling of predicted protein structures and modeling of docked protein structures. The novel, integrated approach of XLinkDB 2.0 enables the holistic analysis of XL-MS protein interaction data without limitation to the cross-linker or analytical system used for the analysis. Availability and Implementation: XLinkDB 2.0 can be found here, including documentation and help: http://xlinkdb.gs.washington.edu/. Contact: jimbruce@uw.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153666

Short time sports exercise boosts motor imagery patterns: implications of mental practice in rehabilitation programs

PubMed Central

Wriessnegger, Selina C.; Steyrl, David; Koschutnig, Karl; Müller-Putz, Gernot R.

2014-01-01

Motor imagery (MI) is a commonly used paradigm for the study of motor learning or cognitive aspects of action control. The rationale for using MI training to promote the relearning of motor function arises from research on the functional correlates that MI shares with the execution of physical movements. While most of the previous studies investigating MI were based on simple movements in the present study a more attractive mental practice was used to investigate cortical activation during MI. We measured cerebral responses with functional magnetic resonance imaging (fMRI) in twenty three healthy volunteers as they imagined playing soccer or tennis before and after a short physical sports exercise. Our results demonstrated that only 10 min of training are enough to boost MI patterns in motor related brain regions including premotor cortex and supplementary motor area (SMA) but also fronto-parietal and subcortical structures. This supports previous findings that MI has beneficial effects especially in combination with motor execution when used in motor rehabilitation or motor learning processes. We conclude that sports MI combined with an interactive game environment could be a promising additional tool in future rehabilitation programs aiming to improve upper or lower limb functions or support neuroplasticity. PMID:25071505

Co-complex protein membership evaluation using Maximum Entropy on GO ontology and InterPro annotation.

PubMed

Armean, Irina M; Lilley, Kathryn S; Trotter, Matthew W B; Pilkington, Nicholas C V; Holden, Sean B

2018-06-01

Protein-protein interactions (PPI) play a crucial role in our understanding of protein function and biological processes. The standardization and recording of experimental findings is increasingly stored in ontologies, with the Gene Ontology (GO) being one of the most successful projects. Several PPI evaluation algorithms have been based on the application of probabilistic frameworks or machine learning algorithms to GO properties. Here, we introduce a new training set design and machine learning based approach that combines dependent heterogeneous protein annotations from the entire ontology to evaluate putative co-complex protein interactions determined by empirical studies. PPI annotations are built combinatorically using corresponding GO terms and InterPro annotation. We use a S.cerevisiae high-confidence complex dataset as a positive training set. A series of classifiers based on Maximum Entropy and support vector machines (SVMs), each with a composite counterpart algorithm, are trained on a series of training sets. These achieve a high performance area under the ROC curve of ≤0.97, outperforming go2ppi-a previously established prediction tool for protein-protein interactions (PPI) based on Gene Ontology (GO) annotations. https://github.com/ima23/maxent-ppi. sbh11@cl.cam.ac.uk. Supplementary data are available at Bioinformatics online.

75 FR 47552 - Information Collection; Submission for OMB Review, Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-06

... information collection request (ICR) entitled the the National Evaluation of School-Based Learn and Serve...) Electronically by e-mail to: [email protected] . SUPPLEMENTARY INFORMATION: The OMB is particularly interested in..., e.g., permitting electronic submissions of responses. Comments A 60-day public comment Notice was...

A Papago Grammar.

ERIC Educational Resources Information Center

Zepeda, Ofelia

A Papago grammar, intented to help Papago and other junior high, high school and college students learn and appreciate the language and give linguists an overview of the language, contains background information on the language and the book, two grammar units, a unit of five conversations in Papago, and a section of supplementary material. Text…

Social Stratification: A Modular Approach. Cultural Anthropology.

ERIC Educational Resources Information Center

Kassebaum, Peter

Designed for use as supplementary instructional material in a cultural anthropology course, this learning module introduces students to the basic concepts of social stratification, one of the more controversial areas of contemporary social theory. An overview is provided of the explanations that have been put forth by social philosophers for…

Kinship and Social Groups: A Modular Approach. Cultural Anthropology.

ERIC Educational Resources Information Center

Kassebaum, Peter

Designed for use as supplementary instructional material in a cultural anthropology course, this learning module introduces commonly employed terms used in the study of kinship and social groups. Conceptual categories used to describe the social structures of society are defined first, including culture, material culture, nonmaterial culture,…

78 FR 68774 - Onsite Emergency Response Capabilities

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-15

[email protected] . SUPPLEMENTARY INFORMATION: I. Background As a result of the events at the Fukushima Dai-ichi... Force Review of Insights from the Fukushima Dai-ichi Accident'' (ADAMS Accession No. ML111861807), the... in Response to Fukushima Lessons Learned'' (ADAMS Accession No. ML11269A204). The NRC staff...

Introduction to Computers: Parallel Alternative Strategies for Students. Course No. 0200000.

ERIC Educational Resources Information Center

Chauvenne, Sherry; And Others

Parallel Alternative Strategies for Students (PASS) is a content-centered package of alternative methods and materials designed to assist secondary teachers to meet the needs of mainstreamed learning-disabled and emotionally-handicapped students of various achievement levels in the basic education content courses. This supplementary text and…

Illustrated French Idioms.

ERIC Educational Resources Information Center

Ainsa, Serge M.

Designed to promote an awareness of the everyday French language, this supplementary textbook was developed to enable students of French to use idiomatic expressions from the early learning stages to the more advanced levels. The units are arranged as follows according to the verb component of the expression: "avoir,""etre,""faire," the three…

Subdisciplines of Anthropology: A Modular Approach. Cultural Anthropology.

ERIC Educational Resources Information Center

Kassebaum, Peter

Designed for use as supplementary instructional material in a cultural anthropology course, this learning module introduces the idea that anthropology is composed of a number of subdisciplines and that cultural anthropology has numerous subfields which are the specialty areas for many practicing anthropologists. Beginning with a general discussion…

Method and Effectiveness of an Individualized Exercise of Fundamental Mathematics.

ERIC Educational Resources Information Center

Yoshioka, Takayoshi; Nishizawa, Hitoshi; Tsukamoto Takehiko

2001-01-01

Describes a method used to provide mathematics students in Japanese colleges of engineering with supplementary exercises to aid their learning. Outlines the online operation of individualized exercises that help the students to understand mathematical methods used to solve problems and also mathematical ideas or concepts upon which methods are…

American Industries. Junior Hi. Pre-Vocational. Power and Transportation.

ERIC Educational Resources Information Center

Goldsbury, Paul; And Others

Several intermediate performance objectives and corresponding criterion measures are listed for each of 10 terminal objectives in this junior high school power and transportation course guide. Each objective also includes learning steps and suggestions for supplementary instructional aids. The overall focus is on the concepts of industrial…

Creative Programming for Young Minds...on the TRS-80. I-Volume VII and All Stars Programs.

ERIC Educational Resources Information Center

Brown, Devin

These manuals provide self-teaching and individualized instruction activities to assist students in learning BASIC programming. Originally planned as a mathematics enrichment program for academically gifted children, three series of instructional workbooks and supplementary projects for seven microcomputers are now included to accommodate…

Agriculture: A Modular Approach. Cultural Anthropology.

ERIC Educational Resources Information Center

Kassebaum, Peter

Designed for use as supplementary instructional material in a cultural anthropology course this learning module introduces the student to some of the major trends associated with agriculture and its impact upon cultural evolution and complexity. The first section of the module describes major innovations such as animal power, irrigation and the…

Audio Implementation of Still and Motion Pictures. Final Report.

ERIC Educational Resources Information Center

Allen, William H.; And Others

An experiment comparing the pedagogical effectiveness of five different modes of audio narration in motion and still pictures showed only small differences in sixth graders' learning. Ten experimental groups were formed in which the 351 subjects viewed motion pictures and still slides accompanied by supplementary, redundant, directive,…

Law in U.S. History: A Teacher Resource Manual.

ERIC Educational Resources Information Center

Smith, Melinda R., Ed.; And Others

By completing these self-contained, supplementary activities, secondary students will learn about important law-related issues and themes in American history. When students recognize the vital constitutional issues of different periods in history they are helped in understanding the social, political, and economic forces which shaped those…

SEED 2: a user-friendly platform for amplicon high-throughput sequencing data analyses.

PubMed

Vetrovský, Tomáš; Baldrian, Petr; Morais, Daniel; Berger, Bonnie

2018-02-14

Modern molecular methods have increased our ability to describe microbial communities. Along with the advances brought by new sequencing technologies, we now require intensive computational resources to make sense of the large numbers of sequences continuously produced. The software developed by the scientific community to address this demand, although very useful, require experience of the command-line environment, extensive training and have steep learning curves, limiting their use. We created SEED 2, a graphical user interface for handling high-throughput amplicon-sequencing data under Windows operating systems. SEED 2 is the only sequence visualizer that empowers users with tools to handle amplicon-sequencing data of microbial community markers. It is suitable for any marker genes sequences obtained through Illumina, IonTorrent or Sanger sequencing. SEED 2 allows the user to process raw sequencing data, identify specific taxa, produce of OTU-tables, create sequence alignments and construct phylogenetic trees. Standard dual core laptops with 8 GB of RAM can handle ca. 8 million of Illumina PE 300 bp sequences, ca. 4GB of data. SEED 2 was implemented in Object Pascal and uses internal functions and external software for amplicon data processing. SEED 2 is a freeware software, available at http://www.biomed.cas.cz/mbu/lbwrf/seed/ as a self-contained file, including all the dependencies, and does not require installation. Supplementary data contain a comprehensive list of supported functions. daniel.morais@biomed.cas.cz. Supplementary data are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press.

QuASAR: quantitative allele-specific analysis of reads

PubMed Central

Harvey, Chris T.; Moyerbrailean, Gregory A.; Davis, Gordon O.; Wen, Xiaoquan; Luca, Francesca; Pique-Regi, Roger

2015-01-01

Motivation: Expression quantitative trait loci (eQTL) studies have discovered thousands of genetic variants that regulate gene expression, enabling a better understanding of the functional role of non-coding sequences. However, eQTL studies are costly, requiring large sample sizes and genome-wide genotyping of each sample. In contrast, analysis of allele-specific expression (ASE) is becoming a popular approach to detect the effect of genetic variation on gene expression, even within a single individual. This is typically achieved by counting the number of RNA-seq reads matching each allele at heterozygous sites and testing the null hypothesis of a 1:1 allelic ratio. In principle, when genotype information is not readily available, it could be inferred from the RNA-seq reads directly. However, there are currently no existing methods that jointly infer genotypes and conduct ASE inference, while considering uncertainty in the genotype calls. Results: We present QuASAR, quantitative allele-specific analysis of reads, a novel statistical learning method for jointly detecting heterozygous genotypes and inferring ASE. The proposed ASE inference step takes into consideration the uncertainty in the genotype calls, while including parameters that model base-call errors in sequencing and allelic over-dispersion. We validated our method with experimental data for which high-quality genotypes are available. Results for an additional dataset with multiple replicates at different sequencing depths demonstrate that QuASAR is a powerful tool for ASE analysis when genotypes are not available. Availability and implementation: http://github.com/piquelab/QuASAR. Contact: fluca@wayne.edu or rpique@wayne.edu Supplementary information: Supplementary Material is available at Bioinformatics online. PMID:25480375

PipelineDog: a simple and flexible graphic pipeline construction and maintenance tool.

PubMed

Zhou, Anbo; Zhang, Yeting; Sun, Yazhou; Xing, Jinchuan

2018-05-01

Analysis pipelines are an essential part of bioinformatics research, and ad hoc pipelines are frequently created by researchers for prototyping and proof-of-concept purposes. However, most existing pipeline management system or workflow engines are too complex for rapid prototyping or learning the pipeline concept. A lightweight, user-friendly and flexible solution is thus desirable. In this study, we developed a new pipeline construction and maintenance tool, PipelineDog. This is a web-based integrated development environment with a modern web graphical user interface. It offers cross-platform compatibility, project management capabilities, code formatting and error checking functions and an online repository. It uses an easy-to-read/write script system that encourages code reuse. With the online repository, it also encourages sharing of pipelines, which enhances analysis reproducibility and accountability. For most users, PipelineDog requires no software installation. Overall, this web application provides a way to rapidly create and easily manage pipelines. PipelineDog web app is freely available at http://web.pipeline.dog. The command line version is available at http://www.npmjs.com/package/pipelinedog and online repository at http://repo.pipeline.dog. ysun@kean.edu or xing@biology.rutgers.edu or ysun@diagnoa.com. Supplementary data are available at Bioinformatics online.

Development and evaluation of online video teaching resources to enhance student knowledge of livestock handling.

PubMed

Klupiec, C; Pope, S; Taylor, R; Carroll, D; Ward, M H; Celi, P

2014-07-01

To evaluate the effectiveness of online audiovisual materials to support the acquisition of animal handling skills by students of veterinary and animal science. A series of video clips (Livestock Handling modules) demonstrating livestock handling procedures was created and delivered online to students enrolled in the Faculty of Veterinary Science, University of Sydney. The effectiveness of these modules for supporting student learning was evaluated via an online survey. The survey also sought feedback on how students could be better prepared for handling livestock. The survey indicated that students found the videos a useful part of their learning experience, particularly by familiarising them with correct handling procedures and emphasising the importance of safety when handling livestock. Students also highlighted that online delivery supported flexible learning. Suggested improvements of the Livestock Handling modules centred around broadening the content of the videos and improving the user-friendliness of online access. Student feedback regarding how the Faculty could better prepare them for livestock handling was dominated by requests for more opportunities to practise animal handling using live animals. The Livestock Handling audiovisual tool is a valuable supplementary resource for developing students' proficiency in safe and effective handling of livestock. However, the results also clearly reveal a perception by students that more hands-on experience is required for acquisition of animal handling skills. These findings will inform future development of the Faculty's animal handling program. © 2014 Australian Veterinary Association.

75 FR 60495 - Eighteenth Plenary Meeting: RTCA Special Committee 203: Unmanned Aircraft Systems

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-30

..., 20036; telephone (202) 833-9339; fax (202) 833-9434; Web site http://www.rtca.org . SUPPLEMENTARY... Product Team Breakout Session. RTCA Workspace Web Tool. Closing Plenary Session. Plenary Adjourns until... Engineering Workgroup. Control and Communications Workgroup. Sense and Avoid Workgroup. Wednesday, October...

Towards an Analytic Foundation for Network Architecture

DTIC Science & Technology

2010-12-31

SUPPLEMENTARY NOTES N/A 14. ABSTRACT In this project, we develop the analytic tools of stochastic optimization for wireless network design and apply them...and Mung Chiang, “ DaVinci : Dynamically Adaptive Virtual Networks for a Customized Internet,” in Proc. ACM SIGCOMM CoNext Conference, December 2008

77 FR 64314 - National Cybersecurity Center of Excellence (NCCoE)

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-19

... Technology (NIST) Information Technology Laboratory (ITL) invites interested U.S. companies to submit letters... http://csrc.nist.gov/nccoe . SUPPLEMENTARY INFORMATION: The NCCoE, hosted by NIST, is a public- private... Information Technology (IT) systems. By accelerating dissemination and use of these integrated tools and...

C3I Analysis Tools for Development Planning. Volume 1

DTIC Science & Technology

1985-09-27

otherwise as in any manner licensing the holder or any other person or conveying any rights or permission to manufacture, use, or sell any patented... PERSONAL AUTHOR(S) ».A. Vail, G.H. Weissman, J.G. Wohl TYPE OF REPORT ?inal 13b. TIME COVERED FROM SUPPLEMENTARY NOTATION Refer to ESD-TR-86...support for decisions about the relative value of acquisition programs. 5. The software tool developed on a personal computer demonstrates that

Web-based network analysis and visualization using CellMaps

PubMed Central

Salavert, Francisco; García-Alonso, Luz; Sánchez, Rubén; Alonso, Roberto; Bleda, Marta; Medina, Ignacio; Dopazo, Joaquín

2016-01-01

Summary: CellMaps is an HTML5 open-source web tool that allows displaying, editing, exploring and analyzing biological networks as well as integrating metadata into them. Computations and analyses are remotely executed in high-end servers, and all the functionalities are available through RESTful web services. CellMaps can easily be integrated in any web page by using an available JavaScript API. Availability and Implementation: The application is available at: http://cellmaps.babelomics.org/ and the code can be found in: https://github.com/opencb/cell-maps. The client is implemented in JavaScript and the server in C and Java. Contact: jdopazo@cipf.es Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27296979

Use of a Supplementary Internet Based Education Program Improves Sleep Literacy in College Psychology Students

PubMed Central

Quan, Stuart F.; Anderson, Janis L.; Hodge, Gordon K.

2013-01-01

Introduction: Knowledge regarding the importance of sleep in health and performance and good sleep hygiene practices is low, especially among adolescents and young adults. It is important to improve sleep literacy. Introductory psychology is one of the most highly enrolled courses at colleges and universities. This study tested the impact of an Internet-based learning module on improving sleep literacy in this venue. Methods: An Internet-based supplementary learning module containing sleep physiology and hygiene information was developed using content from the Harvard Medical School sleep educational website http://www.understandingsleep.org. Access to the module was provided as an extra credit activity for 2 of 4 sections (Supplemental Sleep, SS, N = 889) of an introductory college psychology course during their standard instruction on sleep and dreaming. The remaining 2 sections (Standard Instruction, SI, N = 878) only were encouraged to visit the website without further direction. Level of knowledge was assessed before and after availability to the module/website and at the end of the semester. Students were asked to complete a survey at the end of the semester inquiring whether they made any changes in their sleep behaviors. Results: Two hundred fifty students participated in the extra credit activity and had data available at all testing points. Students in the SS Group had a significant improvement in sleep knowledge test scores after interacting with the website in comparison to the SI group (19.41 ± 3.15 vs. 17.94 ± 3.08, p < 0.001). This difference persisted, although at a lower level, at the end of the semester. In addition, 55.9% of the SS group versus 45.1% of the SI group indicated that they made changes in their sleep habits after participation in the extra credit sleep activity (p < 0.01). The most common change was a more consistent wake time. Conclusion: Use of a supplementary internet-based sleep learning module has the potential to enhance sleep literacy and change behavior among students enrolled in an introductory college psychology course. Citation: Quan SF; Anderson JL; Hodge GK. Use of a supplementary internet based education program improves sleep literacy in college psychology students. J Clin Sleep Med 2013;9(2):155-160. PMID:23372469

Gene expression inference with deep learning

PubMed Central

Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui

2016-01-01

Motivation: Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. Results: We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. Availability and implementation: D-GEX is available at https://github.com/uci-cbcl/D-GEX. Contact: xhx@ics.uci.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26873929

78 FR 51272 - Agency Information Collection Activities: Revision of an Approved Information Collection; Comment...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-20

... requirement for national banks and Federal savings associations titled, ``Company-Run Annual Stress Test...://www.occ.treas.gov/tools-forms/forms/bank-operations/stress-test-reporting.html ). SUPPLEMENTARY...: Title: Company-Run Annual Stress Test Reporting Template and Documentation for Covered Institutions with...

CscoreTool: fast Hi-C compartment analysis at high resolution.

PubMed

Zheng, Xiaobin; Zheng, Yixian

2018-05-01

The genome-wide chromosome conformation capture (Hi-C) has revealed that the eukaryotic genome can be partitioned into A and B compartments that have distinctive chromatin and transcription features. Current Principle Component Analyses (PCA)-based method for the A/B compartment prediction based on Hi-C data requires substantial CPU time and memory. We report the development of a method, CscoreTool, which enables fast and memory-efficient determination of A/B compartments at high resolution even in datasets with low sequencing depth. https://github.com/scoutzxb/CscoreTool. xzheng@carnegiescience.edu. Supplementary data are available at Bioinformatics online.

Stationary Engineers Apprenticeship. Related Training Modules. 3.1-3.4 Drawing.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of four learning modules on drawing is one of 20 such packets developed for apprenticeship training for stationary engineers. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide (a…

Millwright Apprenticeship. Related Training Modules. 17.1-17.13 Hydraulics.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of 13 learning modules on hydraulics is 1 of 6 such packets developed for apprenticeship training for millwrights. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide (a check list of…

Stationary Engineers Apprenticeship. Related Training Modules. 10.1-10.5 Machine Components.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of five learning modules on machine components is one of 20 such packets developed for apprenticeship training for stationary engineers. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, statement…

Learning the Law: Law Education for Young North Carolinians.

ERIC Educational Resources Information Center

Edwards, Wanda Rushing; Carr, Edward G., Jr.

Arranged in five chapters, this supplementary resource for junior high students contains information on the history, practical applications, and social consequences of the law. In chapter 1, students are introduced to the origin of laws through examination of a fable, the relationship between government and laws, types of laws, and law…

Economic Systems: A Modular Approach. Cultural Anthropology.

ERIC Educational Resources Information Center

Kassebaum, Peter

Designed for use as supplementary instructional material in a cultural anthropology course, this learning module uses a systems approach to allow students to see the connections and similarities which most cultural groups share on the basis of the type of economic organization that they exhibit. The module begins with a general discussion of…

OPASS: An Online Portfolio Assessment and Diagnosis Scheme to Support Web-Based Scientific Inquiry Experiments

ERIC Educational Resources Information Center

Su, Jun-Ming; Lin, Huan-Yu; Tseng, Shian-Shyong; Lu, Chia-Jung

2011-01-01

Promoting the development of students' scientific inquiry capabilities is a major learning objective in science education. As a result, teachers require effective assessment approaches to evaluate students' scientific inquiry-related performance. Teachers must also be able to offer appropriate supplementary instructions, as needed, to students.…

Blending Synchronous Face-to-Face and Computer-Supported Cooperative Learning in a Hybrid Doctoral Seminar

ERIC Educational Resources Information Center

Roseth, Cary; Akcaoglu, Mete; Zellner, Andrea

2013-01-01

Online education is often assumed to be synonymous with asynchronous instruction, existing apart from or supplementary to face-to-face instruction in traditional bricks-and-mortar classrooms. However, expanding access to computer-mediated communication technologies now make new models possible, including distance learners synchronous online…

Paired Learning: Tutoring by Non-Teachers. Incorporating "The Paired Reading Bulletin" No. 5.

ERIC Educational Resources Information Center

Paired Reading Bulletin, 1989

1989-01-01

The eight papers constituting the Proceedings of the fourth National Paired Reading Conference are published in an annual bulletin of the Paired Reading Project, together with seven papers constituting the Supplementary Proceedings of the Peer Tutoring Conference, and nine feature articles, as follows: (1) "Whole-School Policy on Parental…

Life Management Skills. Teacher's Guide [and Student Workbook]. Parallel Alternative Strategies for Students (PASS).

ERIC Educational Resources Information Center

Goldstein, Jeren; Walford, Sylvia

This teacher's guide and student workbook are part of a series of supplementary curriculum packages presenting alternative methods and activities designed to meet the needs of Florida secondary students with mild disabilities or other special learning needs. The Life Management Skills PASS (Parallel Alternative Strategies for Students) teacher's…

Learn Japanese: Secondary School Text, Volume VI.

ERIC Educational Resources Information Center

Hasegawa, Nobuko; And Others

This is the sixth in a series of ten texts designed for teaching Japanese at the secondary level. Also available are supplementary instructional materials and teacher's guides. Throughout the two units of four lessons each, the theme centers around life in Japan as seen through the eyes of an American student. Each unit contains conversations,…

Learn Japanese: Secondary School Text, Volume 5.

ERIC Educational Resources Information Center

Hirai, Bernice; And Others

This is the fifth in a series of ten texts designed for teaching Japanese at the secondary level. Also available are supplementary instructional materials and teacher's guides. Throughout the two units of four lessons each, the theme centers around life in Japan as seen through the eyes of an American student. Each unit contains conversations,…

Stationary Engineers Apprenticeship. Related Training Modules. 8.1-8.13 Hydraulics.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of 13 learning modules on hydraulics is one of 20 such packets developed for apprenticeship training for stationary engineers. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide (a…

Stationary Engineers Apprenticeship. Related Training Modules. 9.1-9.6 Refrigeration.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of six learning modules on refrigeration is one of 20 such packets developed for apprenticeship training for stationary engineers. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, statement of…

Stationary Engineers Apprenticeship. Related Training Modules. 5.1-5.17 Electricity/Electronics.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of 17 learning modules on electricity/electronics is one of 20 such packets developed for apprenticeship training for stationary engineers. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators,…

Millwright Apprenticeship. Related Training Modules. 15.1-15.5 Miscellaneous.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of five learning modules on miscellaneous topics is one of six such packets developed for apprenticeship training for millwrights. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide (a…

The Holocaust and Genocide: A Search for Conscience. A Curriculum Guide.

ERIC Educational Resources Information Center

Flaim, Richard F., Ed.; Reynolds, Edwin W., Jr., Ed.

Designed to facilitate teacher development of a secondary unit on the Holocaust and genocide, this multidisciplinary curriculum guide provides a wide variety of classroom-tested objectives, learning activities, and materials. The guide is organized into six units which may be taught in sequence or used in part as supplementary materials: the…

Virtual-Recitation: A World Wide Web Based Approach to Active Learning in Clinical Pharmacokinetics.

ERIC Educational Resources Information Center

Woodward, Donald K.

1998-01-01

Describes implementation, evaluation of World Wide Web-based component in a Rutgers University (New Jersey) advanced clinical pharmacokinetics course. Scheduling accommodated nontraditional students; each week Web pages providing review and supplementary material and an online quiz were posted after class. Comparison with the previous year's…

Millwright Apprenticeship. Related Training Modules. 13.1-13.2 Air Compressors.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of two learning modules on air compressors is one of six such packets developed for apprenticeship training for millwrights. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide (a check…

Millwright Apprenticeship. Related Training Modules. 12.1-12.3 Feedwater.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of three learning modules on feedwater is one of six such packets developed for apprenticeship training for millwrights. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide (a check list…

Language Practice with Multimedia Supported Web-Based Grammar Revision Material

ERIC Educational Resources Information Center

Baturay, Meltem Huri; Daloglu, Aysegul; Yildirim, Soner

2010-01-01

The aim of this study was to investigate the perceptions of elementary-level English language learners towards web-based, multimedia-annotated grammar learning. WEBGRAM, a system designed to provide supplementary web-based grammar revision material, uses audio-visual aids to enrich the contextual presentation of grammar and allows learners to…

Chapter 7. Creating and Sustaining a Culture of Group Care

ERIC Educational Resources Information Center

Ainsworth, Frank; Fulcher, Leon C.

2006-01-01

Group care centers are established to provide a range of living, learning, treatment, and supervisory opportunities for children and young people who, for a variety of reasons, need alternative, supplementary, or substitute care. It is important, therefore, that group care centres establish an organizational climate, ethos, or culture of caring…

Knowing and Caring Toward an Effective Social Studies Reading Program.

ERIC Educational Resources Information Center

Hubbard, Russ

Hundreds of suitable books are available to include in a reading program to supplement the prescribed social studies curriculum. Gordon Parks's book "The Learning Tree" reflects three criteria teachers should consider when selecting books for use in a supplementary reading program. First, the story has what one reader called "cool…

Bayesian network prior: network analysis of biological data using external knowledge

PubMed Central

Isci, Senol; Dogan, Haluk; Ozturk, Cengizhan; Otu, Hasan H.

2014-01-01

Motivation: Reverse engineering GI networks from experimental data is a challenging task due to the complex nature of the networks and the noise inherent in the data. One way to overcome these hurdles would be incorporating the vast amounts of external biological knowledge when building interaction networks. We propose a framework where GI networks are learned from experimental data using Bayesian networks (BNs) and the incorporation of external knowledge is also done via a BN that we call Bayesian Network Prior (BNP). BNP depicts the relation between various evidence types that contribute to the event ‘gene interaction’ and is used to calculate the probability of a candidate graph (G) in the structure learning process. Results: Our simulation results on synthetic, simulated and real biological data show that the proposed approach can identify the underlying interaction network with high accuracy even when the prior information is distorted and outperforms existing methods. Availability: Accompanying BNP software package is freely available for academic use at http://bioe.bilgi.edu.tr/BNP. Contact: hasan.otu@bilgi.edu.tr Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:24215027

Optimizing ChIP-seq peak detectors using visual labels and supervised machine learning

PubMed Central

Goerner-Potvin, Patricia; Morin, Andreanne; Shao, Xiaojian; Pastinen, Tomi

2017-01-01

Motivation: Many peak detection algorithms have been proposed for ChIP-seq data analysis, but it is not obvious which algorithm and what parameters are optimal for any given dataset. In contrast, regions with and without obvious peaks can be easily labeled by visual inspection of aligned read counts in a genome browser. We propose a supervised machine learning approach for ChIP-seq data analysis, using labels that encode qualitative judgments about which genomic regions contain or do not contain peaks. The main idea is to manually label a small subset of the genome, and then learn a model that makes consistent peak predictions on the rest of the genome. Results: We created 7 new histone mark datasets with 12 826 visually determined labels, and analyzed 3 existing transcription factor datasets. We observed that default peak detection parameters yield high false positive rates, which can be reduced by learning parameters using a relatively small training set of labeled data from the same experiment type. We also observed that labels from different people are highly consistent. Overall, these data indicate that our supervised labeling method is useful for quantitatively training and testing peak detection algorithms. Availability and Implementation: Labeled histone mark data http://cbio.ensmp.fr/~thocking/chip-seq-chunk-db/, R package to compute the label error of predicted peaks https://github.com/tdhock/PeakError Contacts: toby.hocking@mail.mcgill.ca or guil.bourque@mcgill.ca Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27797775

PEA: an integrated R toolkit for plant epitranscriptome analysis.

PubMed

Zhai, Jingjing; Song, Jie; Cheng, Qian; Tang, Yunjia; Ma, Chuang

2018-05-29

The epitranscriptome, also known as chemical modifications of RNA (CMRs), is a newly discovered layer of gene regulation, the biological importance of which emerged through analysis of only a small fraction of CMRs detected by high-throughput sequencing technologies. Understanding of the epitranscriptome is hampered by the absence of computational tools for the systematic analysis of epitranscriptome sequencing data. In addition, no tools have yet been designed for accurate prediction of CMRs in plants, or to extend epitranscriptome analysis from a fraction of the transcriptome to its entirety. Here, we introduce PEA, an integrated R toolkit to facilitate the analysis of plant epitranscriptome data. The PEA toolkit contains a comprehensive collection of functions required for read mapping, CMR calling, motif scanning and discovery, and gene functional enrichment analysis. PEA also takes advantage of machine learning technologies for transcriptome-scale CMR prediction, with high prediction accuracy, using the Positive Samples Only Learning algorithm, which addresses the two-class classification problem by using only positive samples (CMRs), in the absence of negative samples (non-CMRs). Hence PEA is a versatile epitranscriptome analysis pipeline covering CMR calling, prediction, and annotation, and we describe its application to predict N6-methyladenosine (m6A) modifications in Arabidopsis thaliana. Experimental results demonstrate that the toolkit achieved 71.6% sensitivity and 73.7% specificity, which is superior to existing m6A predictors. PEA is potentially broadly applicable to the in-depth study of epitranscriptomics. PEA Docker image is available at https://hub.docker.com/r/malab/pea, source codes and user manual are available at https://github.com/cma2015/PEA. chuangma2006@gmail.com. Supplementary data are available at Bioinformatics online.

Teaching Astronomy with Technology

NASA Astrophysics Data System (ADS)

Austin, Carmen; Impey, Chris David; Wenger, Matthew

2015-01-01

Students today are expected to have access to computers and the Internet. Students young and old, in school and out of school, are interested in learning about astronomy, and have computers to use for this. Teach Astronomy is a website with a comprehensive digital astronomy textbook freely available to students and educators. In addition to the textbook, there are astronomy Wikipedia articles, image archives from Astronomy Picture of the Day and AstroPix, and video lectures covering all topics of astronomy. Teach Astronomy has a unique search tool called the wikimap that can be used to search through all of the resources on the site. Astronomy: State of the Art (ASOTA) is a massive, open, online course (MOOC). Over 18,000 students have enrolled over the past year and half. This MOOC has been presented in various forms. First, only to students on the web, with content released weekly on host site Udemy. Then to university students who met formally in the classroom for educational activities, but were also expected to watch lectures online on their own time. Presently, it is available online for students to go at their own pace. In the future it will be available in an extended format on a new host site, Coursera. ASOTA instructors use social media to interact with students. Students ask questions via the course host site, Udemy. Live question and answer sessions are conducted using Google Hangouts on Air, and interesting and relevant astronomy news, or supplementary educational content is shared via the ASOTA Facebook page. Teaching on the Internet may seem impersonal and impractical, but by learning to use all of these tools, instructors have the ability to interact with students, and keep them engaged.

Light Augmentation Device: A New Surgical Tool for Improved Laparoscopic Visibility and Transillumination: Proof-of-Concept Study.

PubMed

Asti, Emanuele; Nebbia, Fabio; Sironi, Andrea; Bottino, Vincenzo; Bonitta, Gianluca; Bonavina, Luigi

2016-12-01

The light augmentation device (LAD ® ) is a new disposable tool designed to improve observation by transillumination in laparoscopic surgery. It can be introduced into the abdomen through an 11-12 mm port as a supplementary light source. The miniaturized design allows the surgeon to pick up the device with an endograsper and to place it under direct vision where needed. This proof-of-concept study demonstrated safety and efficacy of the device in the animal model.

Prediction of anti-cancer drug response by kernelized multi-task learning.

PubMed

Tan, Mehmet

2016-10-01

Chemotherapy or targeted therapy are two of the main treatment options for many types of cancer. Due to the heterogeneous nature of cancer, the success of the therapeutic agents differs among patients. In this sense, determination of chemotherapeutic response of the malign cells is essential for establishing a personalized treatment protocol and designing new drugs. With the recent technological advances in producing large amounts of pharmacogenomic data, in silico methods have become important tools to achieve this aim. Data produced by using cancer cell lines provide a test bed for machine learning algorithms that try to predict the response of cancer cells to different agents. The potential use of these algorithms in drug discovery/repositioning and personalized treatments motivated us in this study to work on predicting drug response by exploiting the recent pharmacogenomic databases. We aim to improve the prediction of drug response of cancer cell lines. We propose to use a method that employs multi-task learning to improve learning by transfer, and kernels to extract non-linear relationships to predict drug response. The method outperforms three state-of-the-art algorithms on three anti-cancer drug screen datasets. We achieved a mean squared error of 3.305 and 0.501 on two different large scale screen data sets. On a recent challenge dataset, we obtained an error of 0.556. We report the methodological comparison results as well as the performance of the proposed algorithm on each single drug. The results show that the proposed method is a strong candidate to predict drug response of cancer cell lines in silico for pre-clinical studies. The source code of the algorithm and data used can be obtained from http://mtan.etu.edu.tr/Supplementary/kMTrace/. Copyright © 2016 Elsevier B.V. All rights reserved.

Heat*seq: an interactive web tool for high-throughput sequencing experiment comparison with public data.

PubMed

Devailly, Guillaume; Mantsoki, Anna; Joshi, Anagha

2016-11-01

Better protocols and decreasing costs have made high-throughput sequencing experiments now accessible even to small experimental laboratories. However, comparing one or few experiments generated by an individual lab to the vast amount of relevant data freely available in the public domain might be limited due to lack of bioinformatics expertise. Though several tools, including genome browsers, allow such comparison at a single gene level, they do not provide a genome-wide view. We developed Heat*seq, a web-tool that allows genome scale comparison of high throughput experiments chromatin immuno-precipitation followed by sequencing, RNA-sequencing and Cap Analysis of Gene Expression) provided by a user, to the data in the public domain. Heat*seq currently contains over 12 000 experiments across diverse tissues and cell types in human, mouse and drosophila. Heat*seq displays interactive correlation heatmaps, with an ability to dynamically subset datasets to contextualize user experiments. High quality figures and tables are produced and can be downloaded in multiple formats. Web application: http://www.heatstarseq.roslin.ed.ac.uk/ Source code: https://github.com/gdevailly CONTACT: Guillaume.Devailly@roslin.ed.ac.uk or Anagha.Joshi@roslin.ed.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

RNA-Rocket: an RNA-Seq analysis resource for infectious disease research

PubMed Central

Warren, Andrew S.; Aurrecoechea, Cristina; Brunk, Brian; Desai, Prerak; Emrich, Scott; Giraldo-Calderón, Gloria I.; Harb, Omar; Hix, Deborah; Lawson, Daniel; Machi, Dustin; Mao, Chunhong; McClelland, Michael; Nordberg, Eric; Shukla, Maulik; Vosshall, Leslie B.; Wattam, Alice R.; Will, Rebecca; Yoo, Hyun Seung; Sobral, Bruno

2015-01-01

Motivation: RNA-Seq is a method for profiling transcription using high-throughput sequencing and is an important component of many research projects that wish to study transcript isoforms, condition specific expression and transcriptional structure. The methods, tools and technologies used to perform RNA-Seq analysis continue to change, creating a bioinformatics challenge for researchers who wish to exploit these data. Resources that bring together genomic data, analysis tools, educational material and computational infrastructure can minimize the overhead required of life science researchers. Results: RNA-Rocket is a free service that provides access to RNA-Seq and ChIP-Seq analysis tools for studying infectious diseases. The site makes available thousands of pre-indexed genomes, their annotations and the ability to stream results to the bioinformatics resources VectorBase, EuPathDB and PATRIC. The site also provides a combination of experimental data and metadata, examples of pre-computed analysis, step-by-step guides and a user interface designed to enable both novice and experienced users of RNA-Seq data. Availability and implementation: RNA-Rocket is available at rnaseq.pathogenportal.org. Source code for this project can be found at github.com/cidvbi/PathogenPortal. Contact: anwarren@vt.edu Supplementary information: Supplementary materials are available at Bioinformatics online. PMID:25573919

The Ensembl REST API: Ensembl Data for Any Language

PubMed Central

Yates, Andrew; Beal, Kathryn; Keenan, Stephen; McLaren, William; Pignatelli, Miguel; Ritchie, Graham R. S.; Ruffier, Magali; Taylor, Kieron; Vullo, Alessandro; Flicek, Paul

2015-01-01

Motivation: We present a Web service to access Ensembl data using Representational State Transfer (REST). The Ensembl REST server enables the easy retrieval of a wide range of Ensembl data by most programming languages, using standard formats such as JSON and FASTA while minimizing client work. We also introduce bindings to the popular Ensembl Variant Effect Predictor tool permitting large-scale programmatic variant analysis independent of any specific programming language. Availability and implementation: The Ensembl REST API can be accessed at http://rest.ensembl.org and source code is freely available under an Apache 2.0 license from http://github.com/Ensembl/ensembl-rest. Contact: ayates@ebi.ac.uk or flicek@ebi.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25236461

Collaborative Online Teamwork: Exploring Students' Satisfaction and Attitudes with Google Hangouts as a Supplementary Communication Tool

ERIC Educational Resources Information Center

He, Jinxia; Huang, Xiaoxia

2017-01-01

This study examined differences in student satisfaction and perceptions of online teamwork in two cohorts of an undergraduate educational technology course: one delivered fully asynchronously and the other incorporating synchronous Google Hangouts sessions in student online teamwork. Participants included 50 undergraduate students at a large…

EJSCREEN Demographic Indicators 2015 Public

EPA Pesticide Factsheets

EJSCREEN uses demographic factors as very general indicators of a community's potential susceptibility to the types of environmental factors included in this screening tool. There are six demographic indicators: Demographic Index, Supplementary Demographic Index, Individuals under Age 5, Individuals over Age 64, Percent Low-Income, Linguistic Isolation, Percent Minority, and Less than High School Education.

Using Wordle as a Supplementary Research Tool

ERIC Educational Resources Information Center

McNaught, Carmel; Lam, Paul

2010-01-01

A word cloud is a special visualization of text in which the more frequently used words are effectively highlighted by occupying more prominence in the representation. We have used Wordle to produce word-cloud analyses of the spoken and written responses of informants in two research projects. The product demonstrates a fast and visually rich way…

Fostering Innovation Through Robotics Exploration

DTIC Science & Technology

2015-06-01

16 Jan 09. 13. SUPPLEMENTARY NOTES 14. ABSTRACT This effort enhanced Robotics STEM activities by incorporating Cognitive tutors at key points to...make important mathematical decision or implement critical calculations. Program utilized Cognitive Tutor Authoring tools for designing problem...activities by incorporating cognitive tutors at key points to make important mathematical decision or implement critical calculations. The program

The Design of an Intelligent Decision Support Tool for Submarine Commanders

DTIC Science & Technology

2009-06-01

for public release, distribution unlimited 13. SUPPLEMENTARY NOTES The original document contains color images . 14. ABSTRACT 15. SUBJECT TERMS 16...with research supporting the advancement of military technology. Thank you again for your support throughout this process . To Dave Silvia and Carl...26 2.1.3 Voyage Management System

Newspaper Humor: Tool for Critical Thinking and Reading Abilities.

ERIC Educational Resources Information Center

Whitmer, Jean E.

Intended as a supplementary resource for teachers, this paper focuses on using humor to develop students' critical thinking and reading abilities. The paper suggests many newspaper humor activities for predicting word meanings through context clues, including the meanings of words in isolation and in context, in headlines, and in the comics. Next,…

TARDEC’s VICTORY SIL is a Key Tool for Advancing Standardized Ground Vehicle Electronic Architecture

DTIC Science & Technology

2012-08-06

SUPPLEMENTARY NOTES Submitted to 2012 NDIA Ground Vehicle Systems Engineering and Technology Symposium August 14-16 Troy , Michigan 14. ABSTRACT VICTORY...Timing, Threat and Remote Weapons Station. The results were very encouraging with very low power consumption (3.15 Watts ), less than 1% system

Introduction of Sustainable Development in Engineers' Curricula: Problematic and Evaluation Methods

ERIC Educational Resources Information Center

Lourdel, N.; Gondran, N.; Laforest, V.; Brodhag, C.

2005-01-01

Purpose: Owing to its complexity, sustainable development cannot be simply integrated as a supplementary course within the engineers' curricula. The first point of this paper aims to focalise on how to reflect pedagogically. After dealing with these questions, a tool that can evaluate the student's understanding of sustainable development concepts…

77 FR 42504 - Prospective Grant of Exclusive License: Development of a Diagnostic Tool for Diagnosing Benign...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-19

...: [email protected] . SUPPLEMENTARY INFORMATION: This technology is based on the discovery of... which are received by the NIH Office of Technology Transfer on or before August 20, 2012 will be... and Patenting Manager, Office of Technology Transfer, National Institutes of Health, 6011 Executive...

MEANS: python package for Moment Expansion Approximation, iNference and Simulation

PubMed Central

Fan, Sisi; Geissmann, Quentin; Lakatos, Eszter; Lukauskas, Saulius; Ale, Angelique; Babtie, Ann C.; Kirk, Paul D. W.; Stumpf, Michael P. H.

2016-01-01

Motivation: Many biochemical systems require stochastic descriptions. Unfortunately these can only be solved for the simplest cases and their direct simulation can become prohibitively expensive, precluding thorough analysis. As an alternative, moment closure approximation methods generate equations for the time-evolution of the system’s moments and apply a closure ansatz to obtain a closed set of differential equations; that can become the basis for the deterministic analysis of the moments of the outputs of stochastic systems. Results: We present a free, user-friendly tool implementing an efficient moment expansion approximation with parametric closures that integrates well with the IPython interactive environment. Our package enables the analysis of complex stochastic systems without any constraints on the number of species and moments studied and the type of rate laws in the system. In addition to the approximation method our package provides numerous tools to help non-expert users in stochastic analysis. Availability and implementation: https://github.com/theosysbio/means Contacts: m.stumpf@imperial.ac.uk or e.lakatos13@imperial.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153663

Low Voltage Alarm Apprenticeship. Related Training Modules. 29.1-29.5 Drawing.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of five learning modules on drawing is one of eight such packets developed for apprenticeship training for low voltage alarm. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide (a check…

Understanding Sexuality: Unit 3. Parent Education Workbook for Mainstreamed Students. Part I: Relationships. Contemporary Parenting Choices. Module 4.

ERIC Educational Resources Information Center

Iowa State Univ. of Science and Technology, Ames. Dept. of Home Economics Education.

The 2-part student workbook for mainstreamed learning and mentally disabled high school students contains 12 units intended to provide supplementary instruction in the Contemporary Parenting Choices Curriculum in the home economics class. This unit, the third in the Relationships part of the workbook, focuses on understanding sexuality with…

Land Treatment. Instructor Guide. Working for Clean Water: An Information Program for Advisory Committees

ERIC Educational Resources Information Center

Pennsylvania State Univ., Middletown. Inst. of State and Regional Affairs.

Presented is an instructor's manual for a learning session centered on the methodology and feasibility of land treatment of municipal wastewater. A supplementary slide-tape program is available. These materials are components of the Working for Clean Water Project, which is intended to educate advisory groups who are interested in improving…

Learning Unknown Event Models

DTIC Science & Technology

2014-07-01

Intelligence (www.aaai.org). All rights reserved. knowledge engineering, but it is often impractical due to high environment variance, or unknown events...distribution unlimited 13. SUPPLEMENTARY NOTES In Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence , 27-31 July 2014...autonomy for responding to unexpected events in strategy simulations. Computational Intelligence , 29(2), 187-206. Leake, D. B. (1991), Goal-based

Teachers as Learners and Practitioners: Shifting Teaching Practice through Havruta Pedagogy

ERIC Educational Resources Information Center

Kent, Orit; Cook, Allison

2014-01-01

This study presents the cases of two teachers in a Jewish supplementary school whose experiences as learners in a year-long professional development (PD) program shaped their teaching practice. The PD program, based in a theory of havruta text learning, immersed the faculty in the very pedagogy they were being encouraged to use in their teaching…

Review of Use of Animation as a Supplementary Learning Material of Physiology Content in Four Academic Years

ERIC Educational Resources Information Center

Hwang, Isabel; Tam, Michael; Lam, Shun Leung; Lam, Paul

2012-01-01

Dynamic concepts are difficult to explain in traditional media such as still slides. Animations seem to offer the advantage of delivering better representations of these concepts. Compared with static images and text, animations can present procedural information (e.g. biochemical reaction steps, physiological activities) more explicitly as they…

Use of Open Educational Resources: How, Why and Why Not?

ERIC Educational Resources Information Center

Islim, Omer Faruk; Gurel Koybasi, Nergis A.; Cagiltay, Kursat

2016-01-01

Open Educational Resources (OER) and OpenCourseWare (OCW) target barriers of education and learning by sharing knowledge for free to benefit self-learners, educators, and students. This study aims to investigate the use of OER both as a supplementary resource for a traditional course and as a resource for self-learners. First, the attitudes and…

Leamos Sobre Veinte Ocupaciones! Twenty Trades to Read About.

ERIC Educational Resources Information Center

Lamatino, Robyn; Mintz, Adin

Twenty trades are explored in this bilingual supplementary workbook, designed specifically for native Spanish speakers who are in the process of learning English. The purpose of this book is to ease the Spanish-speaking student from his/her native language into English with as little discomfort as possible. There are twenty chapters in the book…

Oceans: Our Continuing Frontier. A Study Guide for Courses by Newspaper.

ERIC Educational Resources Information Center

Hawkins, Helen S.

This study guide is one of several supplementary materials for a 16-week newspaper course about oceans. Learning objectives are to help students understand the potential value of the sea, major sources of pollution, contribution of marine archaeology to knowledge of ancient civilizations, and the decline in fictional writing about the sea. Content…

Classroom Learning Centers: Animals, Levels E-I. A Supplementary Approach for Teaching Science and Art.

ERIC Educational Resources Information Center

Doughty, Ted G.; Richiger, Georgina M.

This publication includes curriculum materials on animals for grades 4-6. The major purposes of this publication are to foster individualized and interdisciplinary science and art activities within elementary classrooms and to provide pupils and teachers with suggestions to encourage the use of zoos, animal parks, and natural history museums.…

Low Voltage Alarm Apprenticeship. Related Training Modules. 28.1-28.12 Human Relations.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of 12 learning modules on human relations is 1 of 8 such packets developed for apprenticeship training for low voltage alarm. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide (a check…

Low Voltage Alarm Apprenticeship. Related Training Modules. 6.1-6.6 Safety.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of six learning modules on safety is one of eight such packets developed for apprenticeship training for low voltage alarm. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide (a check…

Low Voltage Alarm Apprenticeship. Related Training Modules. 27.1-27.4 Computer Usage.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of four learning modules on computer usage is one of eight such packets developed for apprenticeship training for low voltage alarm. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide…

Low Voltage Alarm Apprenticeship. Related Training Modules. 0.1 History of Alarms.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of one learning module on the history of alarms is one of eight such packets developed for apprenticeship training for low voltage alarm. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study…

Low Voltage Alarm Apprenticeship. Related Training Modules. 7.1-26.10 Alarm Basics.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of 70 learning modules on alarm basics is 1 of 8 such packets developed for apprenticeship training for low voltage alarm. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide (a check…

Using Supplementary Materials in the Teaching of English: Pedagogic Scope and Applications

ERIC Educational Resources Information Center

Thakur, Vijay Singh

2015-01-01

For many students learning English as a second/foreign language is an uninteresting, dull experience. Quite often teachers present words, sentence patterns, and grammar rules in a very mechanical manner. As a result, people come to think of the teaching of grammar and vocabulary as a monotonous job. But a resourceful, imaginative and creative…

Recombination Narratives to Accompany "A-LM French One," First Edition.

ERIC Educational Resources Information Center

Coughlin, Dorothy

Supplementary recombination narratives intended for use with the 1961 edition of the text "A-LM French One" are designed to help students learn to manipulate basic textual materials. The sample narratives correlate with Units 4-14 of the text. The teacher is urged to make use of the overhead projector when using the narratives for the…

Low Voltage Alarm Apprenticeship. Related Training Modules. 2.1-5.3 Electricity/Electronics.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of 29 learning modules on electricity/electronics is 1 of 8 such packets developed for apprenticeship training for low voltage alarm. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide…

Impact of Supplementary Feeding on Reproductive Success of White Storks

PubMed Central

Hilgartner, Roland; Stahl, Daniel; Zinner, Dietmar

2014-01-01

European white stork (Ciconia ciconia) populations have been object to several conservation measures such as reintroduction programs, habitat improvement or supplementary feeding in the last decades. Although recent white stork censuses revealed an upward trend of most of the western populations, evaluations of the relative importance of certain conservation measures are still scarce or even lacking. In our study we analyzed the effect of supplementary feeding on the reproductive success of white storks in conjunction with other factors such as weather or nest site characteristics. We present data of 569 breeding events at 80 different nest sites located in variable distances to an artificial feeding site at Affenberg Salem (south-western Germany) collected from 1990–2012. A multilevel Poisson regression revealed that in our study population (1) reproductive success was negatively affected by monthly precipitation in April, May and June, (2) pairs breeding on power poles had a lower reproductive success than pairs breeding on platforms or trees and (3) reproductive success was significantly higher in pairs breeding in close distance to the feeding site. The number of fledglings per nest decreased by 8% per kilometer distance to the feeding site. Our data suggest that supplementary feeding increases fledgling populations which may be a tool to attenuate population losses caused by factors such as habitat deterioration or unfavorable conditions in wintering habitats. PMID:25119566

Exhaustively characterizing feasible logic models of a signaling network using Answer Set Programming

PubMed Central

Guziolowski, Carito; Videla, Santiago; Eduati, Federica; Thiele, Sven; Cokelaer, Thomas; Siegel, Anne; Saez-Rodriguez, Julio

2013-01-01

Motivation: Logic modeling is a useful tool to study signal transduction across multiple pathways. Logic models can be generated by training a network containing the prior knowledge to phospho-proteomics data. The training can be performed using stochastic optimization procedures, but these are unable to guarantee a global optima or to report the complete family of feasible models. This, however, is essential to provide precise insight in the mechanisms underlaying signal transduction and generate reliable predictions. Results: We propose the use of Answer Set Programming to explore exhaustively the space of feasible logic models. Toward this end, we have developed caspo, an open-source Python package that provides a powerful platform to learn and characterize logic models by leveraging the rich modeling language and solving technologies of Answer Set Programming. We illustrate the usefulness of caspo by revisiting a model of pro-growth and inflammatory pathways in liver cells. We show that, if experimental error is taken into account, there are thousands (11 700) of models compatible with the data. Despite the large number, we can extract structural features from the models, such as links that are always (or never) present or modules that appear in a mutual exclusive fashion. To further characterize this family of models, we investigate the input–output behavior of the models. We find 91 behaviors across the 11 700 models and we suggest new experiments to discriminate among them. Our results underscore the importance of characterizing in a global and exhaustive manner the family of feasible models, with important implications for experimental design. Availability: caspo is freely available for download (license GPLv3) and as a web service at http://caspo.genouest.org/. Supplementary information: Supplementary materials are available at Bioinformatics online. Contact: santiago.videla@irisa.fr PMID:23853063

The role of tactile feedback in grip force during laparoscopic training tasks.

PubMed

Wottawa, Christopher R; Cohen, Jeremiah R; Fan, Richard E; Bisley, James W; Culjat, Martin O; Grundfest, Warren S; Dutson, Erik P

2013-04-01

Laparoscopic minimally invasive surgery has revolutionized surgical care by reducing trauma to the patient, thereby decreasing the need for medication and shortening recovery times. During open procedures, surgeons can directly feel tissue characteristics. However, in laparoscopic surgery, tactile feedback during grip is attenuated and limited to the resistance felt in the tool handle. Excessive grip force during laparoscopic surgery can lead to tissue damage. Providing additional supplementary tactile feedback may allow subjects to have better control of grip force and identification of tissue characteristics, potentially decreasing the learning curve associated with complex minimally invasive techniques. A tactile feedback system has been developed and integrated into a modified laparoscopic grasper that allows forces applied at the grasper tips to be felt by the surgeon's hands. In this study, 15 subjects (11 novices, 4 experts) were asked to perform single-handed peg transfers using these laparoscopic graspers in three trials (feedback OFF, ON, OFF). Peak and average grip forces (newtons) during each grip event were measured and compared using a Wilcoxon ranked test in which each subject served as his or her own control. After activating the tactile feedback system, the novice subject population showed significant decreases in grip force (p < 0.003). When the system was deactivated for the third trial, there were significant increases in grip force (p < 0.003). Expert subjects showed no significant improvements with the addition of tactile feedback (p > 0.05 in all cases). Supplementary tactile feedback helped novice subjects reduce grip force during the laparoscopic training task but did not offer improvements for the four expert subjects. This indicates that tactile feedback may be beneficial for laparoscopic training but has limited long-term use in the nonrobotic setting.

A Tool for Measuring Active Learning in the Classroom

PubMed Central

Devlin, John W.; Kirwin, Jennifer L.; Qualters, Donna M.

2007-01-01

Objectives To develop a valid and reliable active-learning inventory tool for use in large classrooms and compare faculty perceptions of active-learning using the Active-Learning Inventory Tool. Methods The Active-Learning Inventory Tool was developed using published literature and validated by national experts in educational research. Reliability was established by trained faculty members who used the Active-Learning Inventory Tool to observe 9 pharmacy lectures. Instructors were then interviewed to elicit perceptions regarding active learning and asked to share their perceptions. Results Per lecture, 13 (range: 4-34) episodes of active learning encompassing 3 (range: 2-5) different types of active learning occurred over 2.2 minutes (0.6-16) per episode. Both interobserver (≥87%) and observer-instructor agreement (≥68%) were high for these outcomes. Conclusions The Active-Learning Inventory Tool is a valid and reliable tool to measure active learning in the classroom. Future studies are needed to determine the impact of the Active-Learning Inventory Tool on teaching and its usefulness in other disciplines. PMID:17998982

[Beeckman's medical learning by reading].

PubMed

Honma, Eio

2008-01-01

Isaac Beeckman (1588-1637) is a self-learning man. He learned medicine by his reading medical books (contemporary and classic). In this paper I study how Beeckman read and understood them. He did not merely memorize them. But he gave some supplementary explanations to their (he thought) insufficient passages, sometimes criticized them and gave mechanical explanation that was based on atomism with hydrostatics. We can find similar ways of reading in the works of Lucretius and Cardano which young Beeckman read repeatedly. Beeckman learned the way of explaining natural phenomena with atomism from Lucretius' De rerum natura, and the way of explaining mechanics with natural philosophy and of demonstrating the principles of natural philosophy with machines from Cardano's De subtilitate. Beeckman's interactive reading is a good style of self-learning, but to avoid some bad effects of self-learning, he had to talk actually to a good respondent such as young Descartes.

Application of learning to rank to protein remote homology detection.

PubMed

Liu, Bin; Chen, Junjie; Wang, Xiaolong

2015-11-01

Protein remote homology detection is one of the fundamental problems in computational biology, aiming to find protein sequences in a database of known structures that are evolutionarily related to a given query protein. Some computational methods treat this problem as a ranking problem and achieve the state-of-the-art performance, such as PSI-BLAST, HHblits and ProtEmbed. This raises the possibility to combine these methods to improve the predictive performance. In this regard, we are to propose a new computational method called ProtDec-LTR for protein remote homology detection, which is able to combine various ranking methods in a supervised manner via using the Learning to Rank (LTR) algorithm derived from natural language processing. Experimental results on a widely used benchmark dataset showed that ProtDec-LTR can achieve an ROC1 score of 0.8442 and an ROC50 score of 0.9023 outperforming all the individual predictors and some state-of-the-art methods. These results indicate that it is correct to treat protein remote homology detection as a ranking problem, and predictive performance improvement can be achieved by combining different ranking approaches in a supervised manner via using LTR. For users' convenience, the software tools of three basic ranking predictors and Learning to Rank algorithm were provided at http://bioinformatics.hitsz.edu.cn/ProtDec-LTR/home/ bliu@insun.hit.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences

PubMed Central

Zhang, Long; Jia, Lianyin; Ren, Yazhou

2017-01-01

Protein-protein interactions (PPIs) play crucial roles in almost all cellular processes. Although a large amount of PPIs have been verified by high-throughput techniques in the past decades, currently known PPIs pairs are still far from complete. Furthermore, the wet-lab experiments based techniques for detecting PPIs are time-consuming and expensive. Hence, it is urgent and essential to develop automatic computational methods to efficiently and accurately predict PPIs. In this paper, a sequence-based approach called DNN-LCTD is developed by combining deep neural networks (DNNs) and a novel local conjoint triad description (LCTD) feature representation. LCTD incorporates the advantage of local description and conjoint triad, thus, it is capable to account for the interactions between residues in both continuous and discontinuous regions of amino acid sequences. DNNs can not only learn suitable features from the data by themselves, but also learn and discover hierarchical representations of data. When performing on the PPIs data of Saccharomyces cerevisiae, DNN-LCTD achieves superior performance with accuracy as 93.12%, precision as 93.75%, sensitivity as 93.83%, area under the receiver operating characteristic curve (AUC) as 97.92%, and it only needs 718 s. These results indicate DNN-LCTD is very promising for predicting PPIs. DNN-LCTD can be a useful supplementary tool for future proteomics study. PMID:29117139

Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences.

PubMed

Wang, Jun; Zhang, Long; Jia, Lianyin; Ren, Yazhou; Yu, Guoxian

2017-11-08

Protein-protein interactions (PPIs) play crucial roles in almost all cellular processes. Although a large amount of PPIs have been verified by high-throughput techniques in the past decades, currently known PPIs pairs are still far from complete. Furthermore, the wet-lab experiments based techniques for detecting PPIs are time-consuming and expensive. Hence, it is urgent and essential to develop automatic computational methods to efficiently and accurately predict PPIs. In this paper, a sequence-based approach called DNN-LCTD is developed by combining deep neural networks (DNNs) and a novel local conjoint triad description (LCTD) feature representation. LCTD incorporates the advantage of local description and conjoint triad, thus, it is capable to account for the interactions between residues in both continuous and discontinuous regions of amino acid sequences. DNNs can not only learn suitable features from the data by themselves, but also learn and discover hierarchical representations of data. When performing on the PPIs data of Saccharomyces cerevisiae , DNN-LCTD achieves superior performance with accuracy as 93.12%, precision as 93.75%, sensitivity as 93.83%, area under the receiver operating characteristic curve (AUC) as 97.92%, and it only needs 718 s. These results indicate DNN-LCTD is very promising for predicting PPIs. DNN-LCTD can be a useful supplementary tool for future proteomics study.

Control of a Supernumerary Robotic Hand by Foot: An Experimental Study in Virtual Reality

PubMed Central

Abdi, Elahe; Burdet, Etienne; Bouri, Mohamed; Bleuler, Hannes

2015-01-01

In the operational theater, the surgical team could highly benefit from a robotic supplementary hand under the surgeon’s full control. The surgeon may so become more autonomous; this may reduce communication errors with the assistants and take over difficult tasks such as holding tools without tremor. In this paper, we therefore examine the possibility to control a third robotic hand with one foot’s movements. Three experiments in virtual reality were designed to assess the feasibility of this control strategy, the learning curve of the subjects in different tasks and the coordination of foot movements with the two natural hands. Results show that the limbs are moved simultaneously, in parallel rather than serially. Participants’ performance improved within a few minutes of practice without any specific difficulty to complete the tasks. Subjective assessment by the subjects indicated that controlling a third hand by foot has been easy and required only negligible physical and mental efforts. The sense of ownership was reported to improve through the experiments. The mental burden was not directly related to the level of motion required by a task, but depended on the type of activity and practice. The most difficult task was moving two hands and foot in opposite directions. These results suggest that a combination of practice and appropriate tasks can enhance the learning process for controlling a robotic hand by foot. PMID:26225938

Evaluation of MALDI-TOF mass spectrometry for identification of environmental yeasts and development of supplementary database.

PubMed

Agustini, Bruna Carla; Silva, Luciano Paulino; Bloch, Carlos; Bonfim, Tania M B; da Silva, Gildo Almeida

2014-06-01

Yeast identification using traditional methods which employ morphological, physiological, and biochemical characteristics can be considered a hard task as it requires experienced microbiologists and a rigorous control in culture conditions that could implicate in different outcomes. Considering clinical or industrial applications, the fast and accurate identification of microorganisms is a crescent demand. Hence, molecular biology approaches has been extensively used and, more recently, protein profiling using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has proved to be an even more efficient tool for taxonomic purposes. Nonetheless, concerning to mass spectrometry, data available for the differentiation of yeast species for industrial purpose is limited and reference databases commercially available comprise almost exclusively clinical microorganisms. In this context, studies focusing on environmental isolates are required to extend the existing databases. The development of a supplementary database and the assessment of a commercial database for taxonomic identifications of environmental yeast are the aims of this study. We challenge MALDI-TOF MS to create protein profiles for 845 yeast strains isolated from grape must and 67.7 % of the strains were successfully identified according to previously available manufacturer database. The remaining 32.3 % strains were not identified due to the absence of a reference spectrum. After matching the correct taxon for these strains by using molecular biology approaches, the spectra concerning the missing species were added in a supplementary database. This new library was able to accurately predict unidentified species at first instance by MALDI-TOF MS, proving it is a powerful tool for the identification of environmental yeasts.

Investigating Student Perceptions of the Chemistry Laboratory and Their Approaches to Learning in the Laboratory

NASA Astrophysics Data System (ADS)

Berger, Spencer Granett

This dissertation explores student perceptions of the instructional chemistry laboratory and the approaches students take when learning in the laboratory environment. To measure student perceptions of the chemistry laboratory, a survey instrument was developed. 413 students responded to the survey during the Fall 2011 semester. Students' perception of the usefulness of the laboratory in helping them learn chemistry in high school was related to several factors regarding their experiences in high school chemistry. Students' perception of the usefulness of the laboratory in helping them learn chemistry in college was also measured. Reasons students provided for the usefulness of the laboratory were categorized. To characterize approaches to learning in the laboratory, students were interviewed midway through semester (N=18). The interviews were used to create a framework describing learning approaches that students use in the laboratory environment. Students were categorized into three levels: students who view the laboratory as a requirement, students who believe that the laboratory augments their understanding, and students who view the laboratory as an important part of science. These categories describe the types of strategies students used when conducting experiments. To further explore the relationship between students' perception of the laboratory and their approaches to learning, two case studies are described. These case studies involve interviews in the beginning and end of the semester. In the interviews, students reflect on what they have learned in the laboratory and describe their perceptions of the laboratory environment. In order to encourage students to adopt higher-level approaches to learning in the laboratory, a metacognitive intervention was created. The intervention involved supplementary questions that students would answer while completing laboratory experiments. The questions were designed to encourage students to think critically about the laboratory procedures. In order to test the effects of the intervention, an experimental group (N=87) completed these supplementary questions during two laboratory experiments while a control group (N=84) performed the same experiments without these additional questions. The effects of the intervention on laboratory exam performance were measured. Students in the experimental group had a higher average on the laboratory exam than students in the control group.

Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks

PubMed Central

Avsec, Žiga; Cheng, Jun; Gagneur, Julien

2018-01-01

Abstract Motivation Regulatory sequences are not solely defined by their nucleic acid sequence but also by their relative distances to genomic landmarks such as transcription start site, exon boundaries or polyadenylation site. Deep learning has become the approach of choice for modeling regulatory sequences because of its strength to learn complex sequence features. However, modeling relative distances to genomic landmarks in deep neural networks has not been addressed. Results Here we developed spline transformation, a neural network module based on splines to flexibly and robustly model distances. Modeling distances to various genomic landmarks with spline transformations significantly increased state-of-the-art prediction accuracy of in vivo RNA-binding protein binding sites for 120 out of 123 proteins. We also developed a deep neural network for human splice branchpoint based on spline transformations that outperformed the current best, already distance-based, machine learning model. Compared to piecewise linear transformation, as obtained by composition of rectified linear units, spline transformation yields higher prediction accuracy as well as faster and more robust training. As spline transformation can be applied to further quantities beyond distances, such as methylation or conservation, we foresee it as a versatile component in the genomics deep learning toolbox. Availability and implementation Spline transformation is implemented as a Keras layer in the CONCISE python package: https://github.com/gagneurlab/concise. Analysis code is available at https://github.com/gagneurlab/Manuscript_Avsec_Bioinformatics_2017. Contact avsec@in.tum.de or gagneur@in.tum.de Supplementary information Supplementary data are available at Bioinformatics online. PMID:29155928

CellSort: a support vector machine tool for optimizing fluorescence-activated cell sorting and reducing experimental effort.

PubMed

Yu, Jessica S; Pertusi, Dante A; Adeniran, Adebola V; Tyo, Keith E J

2017-03-15

High throughput screening by fluorescence activated cell sorting (FACS) is a common task in protein engineering and directed evolution. It can also be a rate-limiting step if high false positive or negative rates necessitate multiple rounds of enrichment. Current FACS software requires the user to define sorting gates by intuition and is practically limited to two dimensions. In cases when multiple rounds of enrichment are required, the software cannot forecast the enrichment effort required. We have developed CellSort, a support vector machine (SVM) algorithm that identifies optimal sorting gates based on machine learning using positive and negative control populations. CellSort can take advantage of more than two dimensions to enhance the ability to distinguish between populations. We also present a Bayesian approach to predict the number of sorting rounds required to enrich a population from a given library size. This Bayesian approach allowed us to determine strategies for biasing the sorting gates in order to reduce the required number of enrichment rounds. This algorithm should be generally useful for improve sorting outcomes and reducing effort when using FACS. Source code available at http://tyolab.northwestern.edu/tools/ . k-tyo@northwestern.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Systematic review and meta-analysis of the role of mental training in the acquisition of technical skills in surgery.

PubMed

Rao, Ahsan; Tait, Ian; Alijani, Afshin

2015-09-01

Mental training is rehearsal of mental imagery without physically performing the task. The aim of the study was to perform systematic review and meta-analysis on all the available data to evaluate the role of mental training in the acquisition of surgical technical skills. The following search databases were used: EMBASE, MEDLINE, Web of Science, Clinicaltrials.gov.uk, SIGN guidelines, NICE guidelines, and Cochrane review register. Meta-analysis was performed using Revman 5.2 statistical software. There were a total of 9 randomized controlled trials with 474 participants, of which 189 participants received mental training. Five randomized controlled trials concluded positive impact of mental training. Mental training group did not show any significant improvement in overall performance of the task carried in each study (P = .06). Mental training can be used as an important supplementary tool in learning surgical skills when run in parallel with physical training and applied to trainees with some experience of the skill. Copyright © 2015 Elsevier Inc. All rights reserved.

Increasing tsunami risk awareness via mobile application

NASA Astrophysics Data System (ADS)

Leelawat, N.; Suppasri, A.; Latcharote, P.; Imamura, F.; Abe, Y.; Sugiyasu, K.

2017-02-01

In the information and communication technology era, smartphones have become a necessity. With the capacity and availability of smart technologies, a number of benefits are possible. As a result, designing a mobile application to increase tsunami awareness has been proposed, and a prototype has been designed and developed. The application uses data from the 2011 Great East Japan Tsunami. Based on the current location determined by a GPS function matched with the nearest point extracted from the detailed mesh data of that earlier disaster, the application generates the inundation depth at the user’s location. Thus, not only local people but also tourists visiting the affected areas can understand the risks involved. Application testing has been conducted in an evacuation experiment involving both Japanese and foreign students. The proposed application can be used as a supplementary information tool in tsunami evacuation drills. It also supports the idea of smart tourism: when people realize their risks, they possess risk awareness and hence can reduce their risks. This application can also be considered a contribution to disaster knowledge and technology, as well as to the lessons learned from the practical outcome.

A survey study on student preferences regarding pathology teaching in Germany: a call for curricular modernization.

PubMed

Herrmann, Florian E M; Lenski, Markus; Steffen, Julius; Kailuweit, Magdalena; Nikolaus, Marc; Koteeswaran, Rajasekaran; Sailer, Andreas; Hanszke, Anna; Wintergerst, Maximilian; Dittmer, Sissi; Mayr, Doris; Genzel-Boroviczény, Orsolya; Eley, Diann S; Fischer, Martin R

2015-06-02

Pathology is a discipline that provides the basis of the understanding of disease in medicine. The past decades have seen a decline in the emphasis laid on pathology teaching in medical schools and outdated pathology curricula have worsened the situation. Student opinions and thoughts are central to the questions of whether and how such curricula should be modernized. A survey was conducted among 1018 German medical students regarding their preferences in pathology teaching modalities and their satisfaction with lecture-based courses. A qualitative analysis was performed comparing a recently modernized pathology curriculum with a traditional lecture-based curriculum. The differences in modalities of teaching used were investigated. Student satisfaction with the lecture-based curriculum positively correlated with student grades (spearman's correlation coefficient 0.24). Additionally, students with lower grades supported changing the curriculum (spearman's correlation coefficient 0.47). The majority supported virtual microscopy, autopsies, seminars and podcasts as preferred didactic methods. The data supports the implementation of a pathology curriculum where tutorials, autopsies and supplementary computer-based learning tools play important roles.

Using forum-based competitions to improve sustainability and motivation in higher education GNSS learning - Chances and risks

NASA Astrophysics Data System (ADS)

Mayer, M.

2012-04-01

The learning strategies of students seem often to be economically adapted to framework requirements in order to achieve best possible examination performances, especially. For this reason, teachers often detect surface level learning characteristics (e.g., accepting facts uncritically, isolated fact storage, fact memorisation) within the learning concepts of students. Therefore, knowledge sustainability is often suffering. This is detectable when trying to build on knowledge of earlier lectures or lecture courses. In order to improve the sustainability of geodetic knowledge, case studies were carried out at the Geodetic Institute of the Karlsruhe Institute of Technology (Karlsruhe, Germany) within the lecture course "Introduction into GNSS positioning". The lecture course "Introduction into GNSS positioning" is a compulsory part of the Bachelor study course "Geodesy and Geoinformatics" and also a supplementary module of the Bachelor study course "Geophysics". The lecture course is aiming for transferring basic knowledge and basic principles of Global Navigation Satellite Systems (e.g., GPS). During the winter semesters 2010/11 and 2011/12 ten resp. 15 students visited this compulsory attendance lecture course. In addition to classroom lectures and practical training (e.g., field exercises), a forum-based competition was included and tested using the forum feature of the learning management system ILIAS. According to the Bologna Declaration, a special focus of the innovative competition concept is on competence-related learning. The developed eLearning-related competition concept supports and motivates the students to learn more sustainable. In addition, the students have to be creative and have to deal with GNSS factual knowledge in order to win the competition. Within the presentation, the didactical concept of the enriched blended learning lecture course and the competition-based case study are discussed. The rules of the competition are presented in detail. During the semesters, the motivation and the amount of effort (e.g., time requirement of learning and teaching) were examined regularly. These parameters are going to be discussed as well. Based on the gained experiences, the forum-based sustainability competition has proofed to be an effective tool, which can contribute significantly to an increased sustainability of students' learning. In addition, the developed forum-based competition concept can be easily transferred to other lecture courses, especially focusing on factual knowledge.

Maintenance manager's manual for small transit agencies. Special report 1985-1986

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fowler, W.

1988-03-01

This publication contains information to assist operators of transit agencies providing public transportation in rural and smaller urban areas to better manage their vehicle maintenance programs. The report includes discussions of maintenance management, maintenance programs preventive maintenance, recordkeeping, selection of type of maintenance operation, in-house maintenance, and maintenance practices. Also included are appendixes giving supplementary information about tire loads; lubrication oil; mechanic hand tools; shop tools; mechanic aptitude tests; technical training resources; maintenance management training resources; and lists of manufacturers of air-conditioning systems, wheelchair lifts and wheelchair ramps.

KMC 3: counting and manipulating k-mer statistics.

PubMed

Kokot, Marek; Dlugosz, Maciej; Deorowicz, Sebastian

2017-09-01

Counting all k -mers in a given dataset is a standard procedure in many bioinformatics applications. We introduce KMC3, a significant improvement of the former KMC2 algorithm together with KMC tools for manipulating k -mer databases. Usefulness of the tools is shown on a few real problems. Program is freely available at http://sun.aei.polsl.pl/REFRESH/kmc . sebastian.deorowicz@polsl.pl. 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

The Effectiveness of a Unit Study-Technology Approach within the High School Band Rehearsal Setting

ERIC Educational Resources Information Center

Gustafson-Hinds, Melissa A.

2010-01-01

The purpose of this research study was to investigate the usefulness of implementing a Comprehensive Musicianship (CMP)--Unit Study within a high school band rehearsal setting, using music technology as a supplementary tool. While previous studies have emphasized the many benefits of Comprehensive Musicianship, it is not clear how such an approach…

Making Air Pollution Visible: A Tool for Promoting Environmental Health Literacy.

PubMed

Cleary, Ekaterina Galkina; Patton, Allison P; Wu, Hsin-Ching; Xie, Alan; Stubblefield, Joseph; Mass, William; Grinstein, Georges; Koch-Weser, Susan; Brugge, Doug; Wong, Carolyn

2017-04-12

Digital maps are instrumental in conveying information about environmental hazards geographically. For laypersons, computer-based maps can serve as tools to promote environmental health literacy about invisible traffic-related air pollution and ultrafine particles. Concentrations of these pollutants are higher near major roadways and increasingly linked to adverse health effects. Interactive computer maps provide visualizations that can allow users to build mental models of the spatial distribution of ultrafine particles in a community and learn about the risk of exposure in a geographic context. The objective of this work was to develop a new software tool appropriate for educating members of the Boston Chinatown community (Boston, MA, USA) about the nature and potential health risks of traffic-related air pollution. The tool, the Interactive Map of Chinatown Traffic Pollution ("Air Pollution Map" hereafter), is a prototype that can be adapted for the purpose of educating community members across a range of socioeconomic contexts. We built the educational visualization tool on the open source Weave software platform. We designed the tool as the centerpiece of a multimodal and intergenerational educational intervention about the health risk of traffic-related air pollution. We used a previously published fine resolution (20 m) hourly land-use regression model of ultrafine particles as the algorithm for predicting pollution levels and applied it to one neighborhood, Boston Chinatown. In designing the map, we consulted community experts to help customize the user interface to communication styles prevalent in the target community. The product is a map that displays ultrafine particulate concentrations averaged across census blocks using a color gradation from white to dark red. The interactive features allow users to explore and learn how changing meteorological conditions and traffic volume influence ultrafine particle concentrations. Users can also select from multiple map layers, such as a street map or satellite view. The map legends and labels are available in both Chinese and English, and are thus accessible to immigrants and residents with proficiency in either language. The map can be either Web or desktop based. The Air Pollution Map incorporates relevant language and landmarks to make complex scientific information about ultrafine particles accessible to members of the Boston Chinatown community. In future work, we will test the map in an educational intervention that features intergenerational colearning and the use of supplementary multimedia presentations. ©Ekaterina Galkina Cleary, Allison P Patton, Hsin-Ching Wu, Alan Xie, Joseph Stubblefield, William Mass, Georges Grinstein, Susan Koch-Weser, Doug Brugge, Carolyn Wong. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 12.04.2017.

Gencrypt: one-way cryptographic hashes to detect overlapping individuals across samples

PubMed Central

Turchin, Michael C.; Hirschhorn, Joel N.

2012-01-01

Summary: Meta-analysis across genome-wide association studies is a common approach for discovering genetic associations. However, in some meta-analysis efforts, individual-level data cannot be broadly shared by study investigators due to privacy and Institutional Review Board concerns. In such cases, researchers cannot confirm that each study represents a unique group of people, leading to potentially inflated test statistics and false positives. To resolve this problem, we created a software tool, Gencrypt, which utilizes a security protocol known as one-way cryptographic hashes to allow overlapping participants to be identified without sharing individual-level data. Availability: Gencrypt is freely available under the GNU general public license v3 at http://www.broadinstitute.org/software/gencrypt/ Contact: joelh@broadinstitute.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22302573

Curriculum Integration in the Senior Secondary School: A Case Study in A National Assessment Context

ERIC Educational Resources Information Center

McPhail, Graham

2018-01-01

This paper considers curriculum integration in the secondary school context and investigates the claims made that it can enhance learning outcomes for students. I argue that curriculum integration should be utilized not as a main means of curricular delivery but as a supplementary opportunity to put disciplinary knowledge to use in certain,…

Strand I - Physical Health; Dental Health for Grades 4-6. Special Edition for Evaluation and Discussion.

ERIC Educational Resources Information Center

New York State Education Dept., Albany. Curriculum Development Center.

This is a curriculum guide for teaching dental health for grades 4-6. Each topic area is outlined under the headings of: (1) reference; (2) major understandings and fundamental concepts; (3) suggested teaching aids and learning activities; and (4) supplementary information for teachers. Main topics include: (1) growth and development of teeth; (2)…

Low Voltage Alarm Apprenticeship. Related Training Modules. 1.1-1.14 Trade Math.

ERIC Educational Resources Information Center

Lane Community Coll., Eugene, OR.

This packet of 14 learning modules on trade math is 1 of 8 such packets developed for apprenticeship training for low voltage alarm. Introductory materials are a complete listing of all available modules and a supplementary reference list. Each module contains some or all of these components: goal, performance indicators, study guide (a check list…

Understanding Life Styles: Unit 4. Parent Education Workbook for Mainstreamed Students. Part I: Relationships. Contemporary Parenting Choices. Module 4.

ERIC Educational Resources Information Center

Iowa State Univ. of Science and Technology, Ames. Dept. of Home Economics Education.

The 2-part student workbook for mainstreamed learning and mentally disabled high school students contains 12 units intended to provide supplementary instruction in the Contemporary Parenting Choices Curriculum in the home economics class. This unit, the fourth in the Relationships part of the workbook, focuses on understanding the married and…

Teachers' Guide for Aviation Education. For Use in Grades Two Through Six. Communication Arts, Science, Social Studies, Health, Career Education.

ERIC Educational Resources Information Center

Federal Aviation Administration (DOT), Washington, DC.

This teacher's guide provides elementary teachers (grades 2-6) with supplementary learning activities centered around the subject of aviation, which may be used to enrich their regular programs. The guide is divided into the following five subject areas: communication arts, science, social studies, health, and careers in aviation. The guides vary…

Promise for Enhancing Children's Reading Attitudes through Peer Reading: A Mixed Method Approach

ERIC Educational Resources Information Center

Lee, Youngju

2014-01-01

Peer-Assisted Learning Strategies (PALS) was implemented for supplementary reading classes in a Korean elementary school. The treatment group children were exposed to PALS during 20 min sessions, 4 times a week, for 8 weeks. The impacts of PALS were investigated in 3 aspects using a mixed-methods approach: improvement in reading attitudes, reading…

Understanding Pregnancy: Unit 7. Parent Education Workbook for Mainstreamed Students. Part II: Child Care. Contemporary Parenting Choices. Module 4.

ERIC Educational Resources Information Center

Iowa State Univ. of Science and Technology, Ames. Dept. of Home Economics Education.

The 2-part student workbook for mainstreamed learning and mentally disabled high school students contains 12 units intended to provide supplementary instruction in the Contemporary Parenting Choices Curriculum in the home economics class. This unit, the first in the Child Care part of the workbook, focuses on understanding pregnancy and includes…

MEMHDX: an interactive tool to expedite the statistical validation and visualization of large HDX-MS datasets.

PubMed

Hourdel, Véronique; Volant, Stevenn; O'Brien, Darragh P; Chenal, Alexandre; Chamot-Rooke, Julia; Dillies, Marie-Agnès; Brier, Sébastien

2016-11-15

With the continued improvement of requisite mass spectrometers and UHPLC systems, Hydrogen/Deuterium eXchange Mass Spectrometry (HDX-MS) workflows are rapidly evolving towards the investigation of more challenging biological systems, including large protein complexes and membrane proteins. The analysis of such extensive systems results in very large HDX-MS datasets for which specific analysis tools are required to speed up data validation and interpretation. We introduce a web application and a new R-package named 'MEMHDX' to help users analyze, validate and visualize large HDX-MS datasets. MEMHDX is composed of two elements. A statistical tool aids in the validation of the results by applying a mixed-effects model for each peptide, in each experimental condition, and at each time point, taking into account the time dependency of the HDX reaction and number of independent replicates. Two adjusted P-values are generated per peptide, one for the 'Change in dynamics' and one for the 'Magnitude of ΔD', and are used to classify the data by means of a 'Logit' representation. A user-friendly interface developed with Shiny by RStudio facilitates the use of the package. This interactive tool allows the user to easily and rapidly validate, visualize and compare the relative deuterium incorporation on the amino acid sequence and 3D structure, providing both spatial and temporal information. MEMHDX is freely available as a web tool at the project home page http://memhdx.c3bi.pasteur.fr CONTACT: marie-agnes.dillies@pasteur.fr or sebastien.brier@pasteur.frSupplementary information: Supplementary data is available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Positive-unlabeled learning for disease gene identification

PubMed Central

Yang, Peng; Li, Xiao-Li; Mei, Jian-Ping; Kwoh, Chee-Keong; Ng, See-Kiong

2012-01-01

Background: Identifying disease genes from human genome is an important but challenging task in biomedical research. Machine learning methods can be applied to discover new disease genes based on the known ones. Existing machine learning methods typically use the known disease genes as the positive training set P and the unknown genes as the negative training set N (non-disease gene set does not exist) to build classifiers to identify new disease genes from the unknown genes. However, such kind of classifiers is actually built from a noisy negative set N as there can be unknown disease genes in N itself. As a result, the classifiers do not perform as well as they could be. Result: Instead of treating the unknown genes as negative examples in N, we treat them as an unlabeled set U. We design a novel positive-unlabeled (PU) learning algorithm PUDI (PU learning for disease gene identification) to build a classifier using P and U. We first partition U into four sets, namely, reliable negative set RN, likely positive set LP, likely negative set LN and weak negative set WN. The weighted support vector machines are then used to build a multi-level classifier based on the four training sets and positive training set P to identify disease genes. Our experimental results demonstrate that our proposed PUDI algorithm outperformed the existing methods significantly. Conclusion: The proposed PUDI algorithm is able to identify disease genes more accurately by treating the unknown data more appropriately as unlabeled set U instead of negative set N. Given that many machine learning problems in biomedical research do involve positive and unlabeled data instead of negative data, it is possible that the machine learning methods for these problems can be further improved by adopting PU learning methods, as we have done here for disease gene identification. Availability and implementation: The executable program and data are available at http://www1.i2r.a-star.edu.sg/∼xlli/PUDI/PUDI.html. Contact: xlli@i2r.a-star.edu.sg or yang0293@e.ntu.edu.sg Supplementary information: Supplementary Data are available at Bioinformatics online. PMID:22923290

Student Assistant for Learning from Text (SALT): a hypermedia reading aid.

PubMed

MacArthur, C A; Haynes, J B

1995-03-01

Student Assistant for Learning from Text (SALT) is a software system for developing hypermedia versions of textbooks designed to help students with learning disabilities and other low-achieving students to compensate for their reading difficulties. In the present study, 10 students with learning disabilities (3 young women and 7 young men ages 15 to 17) in Grades 9 and 10 read passages from a science textbook using a basic computer version and an enhanced computer version. The basic version included the components found in the printed textbook (text, graphics, outline, and questions) and a notebook. The enhanced version added speech synthesis, an on-line glossary, links between questions and text, highlighting of main ideas, and supplementary explanations that summarized important ideas. Students received significantly higher comprehension scores using the enhanced version. Furthermore, students preferred the enhanced version and thought it helped them learn the material better.

NanoPack: visualizing and processing long read sequencing data.

PubMed

De Coster, Wouter; D'Hert, Svenn; Schultz, Darrin T; Cruts, Marc; Van Broeckhoven, Christine

2018-03-14

Here we describe NanoPack, a set of tools developed for visualization and processing of long read sequencing data from Oxford Nanopore Technologies and Pacific Biosciences. The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools. wouter.decoster@molgen.vib-ua.be. Supplementary tables and figures are available at Bioinformatics online.

Texts of Our Institutional Lives: SATs for Writing Placement--A Critique and Counterproposal

ERIC Educational Resources Information Center

Isaacs, Emily; Molloy, Sean A.

2010-01-01

Focusing on writing placement at a particular university, the authors analyze the limits of SAT tests as a tool in this process. They then describe the writing program's adoption of a supplementary measure: a faculty committee's review of essays by students who may need to be reassigned to a different writing course. They describe how and why a…

Analysis of Nature of Science Included in Recent Popular Writing Using Text Mining Techniques

ERIC Educational Resources Information Center

Jiang, Feng; McComas, William F.

2014-01-01

This study examined the inclusion of nature of science (NOS) in popular science writing to determine whether it could serve supplementary resource for teaching NOS and to evaluate the accuracy of text mining and classification as a viable research tool in science education research. Four groups of documents published from 2001 to 2010 were…

Observing System Evaluations Using GODAE Systems

DTIC Science & Technology

2009-09-01

DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release, distribution is unlimite 13. SUPPLEMENTARY NOTES 20091228151 14. ABSTRACT Global ocean...forecast systems, developed under the Global Ocean Data Assimilation Experiment (GODAE), are a powerful means of assessing the impact of different...components of the Global Ocean Observing System (GOOS). Using a range of analysis tools and approaches, GODAE systems are useful for quantifying the

PERT/CPM and Supplementary Analytical Techniques. An Analysis of Aerospace Usage

DTIC Science & Technology

1978-09-01

of a number of new...rapid pace of technological progress in the last 75 years has spawned the development of a. number of very interesting managorial tools, and one of ...support of the oversll effort. PR L g. At one time, use of PERT was mandatory on all major L]OD acquioition contracts . Since that time, the use of

75 FR 23306 - Southern Nuclear Operating Company, et al.: Supplementary Notice of Hearing and Opportunity To...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-03

...'' field when using either the Web-based search (advanced search) engine or the ADAMS FIND tool in Citrix... should enter ``05200011'' in the ``Docket Number'' field in the web-based search (advanced search) engine... ML100740441. To search for documents in ADAMS using Vogtle Units 3 and 4 COL application docket numbers, 52...

Interdependent Self-Construal, Self-Efficacy, and Community Involvement as Predictors of Perceived Knowledge Gain Among MMORPG Players.

PubMed

Hopp, Toby; Barker, Valerie; Schmitz Weiss, Amy

2015-08-01

This study explored the relationship between interdependent self-construal, video game self-efficacy, massively multiplayer online role-playing game (MMORPG) community involvement, and self-reported learning outcomes. The results suggested that self-efficacy and interdependent self-construal were positive and significant predictors of MMORPG community involvement. For its part, MMORPG community involvement was a positive predictor of self-reported learning in both focused and incidental forms. Supplementary analyses suggested that self-efficacy was a comparatively more robust predictor of MMORPG community involvement when compared to self-construal. Moreover, the present data suggest that community involvement significantly facilitated indirect relationships between self-construal, game-relevant self-efficacy, and both focused and incidental learning.

Pareto-optimal phylogenetic tree reconciliation

PubMed Central

Libeskind-Hadas, Ran; Wu, Yi-Chieh; Bansal, Mukul S.; Kellis, Manolis

2014-01-01

Motivation: Phylogenetic tree reconciliation is a widely used method for reconstructing the evolutionary histories of gene families and species, hosts and parasites and other dependent pairs of entities. Reconciliation is typically performed using maximum parsimony, in which each evolutionary event type is assigned a cost and the objective is to find a reconciliation of minimum total cost. It is generally understood that reconciliations are sensitive to event costs, but little is understood about the relationship between event costs and solutions. Moreover, choosing appropriate event costs is a notoriously difficult problem. Results: We address this problem by giving an efficient algorithm for computing Pareto-optimal sets of reconciliations, thus providing the first systematic method for understanding the relationship between event costs and reconciliations. This, in turn, results in new techniques for computing event support values and, for cophylogenetic analyses, performing robust statistical tests. We provide new software tools and demonstrate their use on a number of datasets from evolutionary genomic and cophylogenetic studies. Availability and implementation: Our Python tools are freely available at www.cs.hmc.edu/∼hadas/xscape. Contact: mukul@engr.uconn.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24932009

MSAProbs-MPI: parallel multiple sequence aligner for distributed-memory systems.

PubMed

González-Domínguez, Jorge; Liu, Yongchao; Touriño, Juan; Schmidt, Bertil

2016-12-15

MSAProbs is a state-of-the-art protein multiple sequence alignment tool based on hidden Markov models. It can achieve high alignment accuracy at the expense of relatively long runtimes for large-scale input datasets. In this work we present MSAProbs-MPI, a distributed-memory parallel version of the multithreaded MSAProbs tool that is able to reduce runtimes by exploiting the compute capabilities of common multicore CPU clusters. Our performance evaluation on a cluster with 32 nodes (each containing two Intel Haswell processors) shows reductions in execution time of over one order of magnitude for typical input datasets. Furthermore, MSAProbs-MPI using eight nodes is faster than the GPU-accelerated QuickProbs running on a Tesla K20. Another strong point is that MSAProbs-MPI can deal with large datasets for which MSAProbs and QuickProbs might fail due to time and memory constraints, respectively. Source code in C ++ and MPI running on Linux systems as well as a reference manual are available at http://msaprobs.sourceforge.net CONTACT: jgonzalezd@udc.esSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

CAGEd-oPOSSUM: motif enrichment analysis from CAGE-derived TSSs

PubMed Central

Arenillas, David J.; Forrest, Alistair R. R.; Kawaji, Hideya; Lassmann, Timo; Wasserman, Wyeth W.; Mathelier, Anthony

2016-01-01

With the emergence of large-scale Cap Analysis of Gene Expression (CAGE) datasets from individual labs and the FANTOM consortium, one can now analyze the cis-regulatory regions associated with gene transcription at an unprecedented level of refinement. By coupling transcription factor binding site (TFBS) enrichment analysis with CAGE-derived genomic regions, CAGEd-oPOSSUM can identify TFs that act as key regulators of genes involved in specific mammalian cell and tissue types. The webtool allows for the analysis of CAGE-derived transcription start sites (TSSs) either provided by the user or selected from ∼1300 mammalian samples from the FANTOM5 project with pre-computed TFBS predicted with JASPAR TF binding profiles. The tool helps power insights into the regulation of genes through the study of the specific usage of TSSs within specific cell types and/or under specific conditions. Availability and Implementation: The CAGEd-oPOSUM web tool is implemented in Perl, MySQL and Apache and is available at http://cagedop.cmmt.ubc.ca/CAGEd_oPOSSUM. Contacts: anthony.mathelier@ncmm.uio.no or wyeth@cmmt.ubc.ca Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27334471

Time-specific contribution of the supplementary motor area to intermanual transfer of procedural knowledge

PubMed Central

Perez, MA; Tanaka, S; Wise, SP; Willingham, DT; Cohen, LG

2008-01-01

The supplementary motor area (SMA) makes a crucial contribution to intermanual transfer: the ability to use one hand to perform a skill practiced and learned with the other hand. However, the timing of this contribution relative to movement remains unknown. Here, 33 healthy volunteers performed a 12-item sequence in the serial reaction time task (SRTT). During training, each participant responded to a sequence of visual cues presented at 1 Hz by pressing one of 4 keys with their right hand. The measure of intermanual transfer was response time (RT) during repetition of the trained sequence with the left hand, which was at rest during learning. Participants were divided into 3 groups, which did not differ in their learning rates or amounts. In 2 groups, 1 Hz repetitive transcranial magnetic stimulation (rTMS) induced transient virtual lesions of the SMA during training, either 100 ms before each cue (the premovement group) or during each key press (the movement group). The third group received sham stimulation (the sham group). After training with the right hand, RTs for performance with the left (transfer) hand were longer for the premovement group than for the movement or sham groups. Thus SMA’s most crucial contribution to intermanual transfer occurs in the interval between movements, when the memory of a prior movement plays a role in encoding specific sequences. These results provide insight into frontal-lobe contributions to procedural knowledge. PMID:18815252

Systematic Replication of the Effects of a Supplementary, Technology-Assisted, Storybook Intervention for Preschool Children with Weak Vocabulary and Comprehension Skills

ERIC Educational Resources Information Center

Greenwood, Charles R.; Carta, Judith J.; Kelley, Elizabeth S.; Guerrero, Gabriela; Kong, Na Young; Atwater, Jane; Goldstein, Howard

2016-01-01

In 2013, Spencer, Goldstein, Sherman, et al. reported the promising effects of a supplemental, technology-assisted, storybook intervention (Tier 2) containing embedded instruction targeting the oral language learning of preschool children at risk for delays. We sought to advance knowledge of the intervention by replicating it in a new sample and…

Applying Lessons of Trust in Future Command Arrangements

DTIC Science & Technology

2011-05-19

Approved for Public Release; Distribution is Unlimited Applying Lessons of Trust in Future Command Arrangements A Monograph by Major Robert V...currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 09-05-2011 1. REPORT DATE (DD-MM-YYYY) SAMS Monograph 2...Distribution Unlimited 12. DISTRIBUTION / AVAILABILITY STATEMENT 13. SUPPLEMENTARY NOTES This monograph elucidates lessons of trust learned

SMART Optimization of a Parenting Program for Active Duty Families

DTIC Science & Technology

2017-10-01

study will conduct a randomized trial of individual cognitive behavioral therapy (CBT) intervention and a social-learning family therapy condition for...STATEMENT Approved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The objective of this study is to provide ways...that it benefits service members, their partners, and their children . The program appears to improve parents’ sense of control, or feelings of

A Message Exchange Protocol in Command and Control Systems Integration, using the JC3IEDM

DTIC Science & Technology

2014-06-01

19TH International Command and Control Research and Technology Symposium C2 Agility: Lessons Learned from Research and Operations. A Message...distribution unlimited 13. SUPPLEMENTARY NOTES Presented at the 18th International Command & Control Research & Technology Symposium (ICCRTS) held 16...presents approaches of integration, compares their technologies , points out their advantages, proposes requirements, and provides the design of a protocol

Publisher Correction: The C-terminal tails of endogenous GluA1 and GluA2 differentially contribute to hippocampal synaptic plasticity and learning.

PubMed

Zhou, Zikai; Liu, An; Xia, Shuting; Leung, Celeste; Qi, Junxia; Meng, Yanghong; Xie, Wei; Park, Pojeong; Collingridge, Graham L; Jia, Zhengping

2018-05-11

In the version of this article initially published, the wrong version of Supplementary Fig. 10 was posted and the city for affiliation 4, the Co-innovation Center of Neuroregeneration, Nantong University, was given as Nanjing instead of Nantong. The errors have been corrected in the HTML and PDF versions of the article.

Powered mobility intervention: understanding the position of tool use learning as part of implementing the ALP tool.

PubMed

Nilsson, Lisbeth; Durkin, Josephine

2017-10-01

To explore the knowledge necessary for adoption and implementation of the Assessment of Learning Powered mobility use (ALP) tool in different practice settings for both adults and children. To consult with a diverse population of professionals working with adults and children, in different countries and various settings; who were learning about or using the ALP tool, as part of exploring and implementing research findings. Classical grounded theory with a rigorous comparative analysis of data from informants together with reflections on our own rich experiences of powered mobility practice and comparisons with the literature. A core category learning tool use and a new theory of cognizing tool use, with its interdependent properties: motivation, confidence, permissiveness, attentiveness and co-construction has emerged which explains in greater depth what enables the application of the ALP tool. The scientific knowledge base on tool use learning and the new theory conveys the information necessary for practitioner's cognizing how to apply the learning approach of the ALP tool in order to enable tool use learning through powered mobility practice as a therapeutic intervention in its own right. This opens up the possibility for more children and adults to have access to learning through powered mobility practice. Implications for rehabilitation Tool use learning through powered mobility practice is a therapeutic intervention in its own right. Powered mobility practice can be used as a rehabilitation tool with individuals who may not need to become powered wheelchair users. Motivation, confidence, permissiveness, attentiveness and co-construction are key properties for enabling the application of the learning approach of the ALP tool. Labelling and the use of language, together with honing observational skills through viewing video footage, are key to developing successful learning partnerships.

Use of a supplementary internet based education program improves sleep literacy in college psychology students.

PubMed

Quan, Stuart F; Anderson, Janis L; Hodge, Gordon K

2013-02-01

Knowledge regarding the importance of sleep in health and performance and good sleep hygiene practices is low, especially among adolescents and young adults. It is important to improve sleep literacy. Introductory psychology is one of the most highly enrolled courses at colleges and universities. This study tested the impact of an Internet-based learning module on improving sleep literacy in this venue. An Internet-based supplementary learning module containing sleep physiology and hygiene information was developed using content from the Harvard Medical School sleep educational website http://www.understandingsleep.org. Access to the module was provided as an extra credit activity for 2 of 4 sections (Supplemental Sleep, SS, N = 889) of an introductory college psychology course during their standard instruction on sleep and dreaming. The remaining 2 sections (Standard Instruction, SI, N = 878) only were encouraged to visit the website without further direction. Level of knowledge was assessed before and after availability to the module/website and at the end of the semester. Students were asked to complete a survey at the end of the semester inquiring whether they made any changes in their sleep behaviors. Two hundred fifty students participated in the extra credit activity and had data available at all testing points. Students in the SS Group had a significant improvement in sleep knowledge test scores after interacting with the website in comparison to the SI group (19.41 ± 3.15 vs. 17.94 ± 3.08, p < 0.001). This difference persisted, although at a lower level, at the end of the semester. In addition, 55.9% of the SS group versus 45.1% of the SI group indicated that they made changes in their sleep habits after participation in the extra credit sleep activity (p < 0.01). The most common change was a more consistent wake time. Use of a supplementary internet-based sleep learning module has the potential to enhance sleep literacy and change behavior among students enrolled in an introductory college psychology course.

Effectiveness of Cooperative Learning Instructional Tools With Predict-Observe-Explain Strategy on the Topic of Cuboid and Cube Volume

NASA Astrophysics Data System (ADS)

Nurhuda; Lukito, A.; Masriyah

2018-01-01

This study aims to develop instructional tools and implement it to see the effectiveness. The method used in this research referred to Designing Effective Instruction. Experimental research with two-group pretest-posttest design method was conducted. The instructional tools have been developed is cooperative learning model with predict-observe-explain strategy on the topic of cuboid and cube volume which consist of lesson plans, POE tasks, and Tests. Instructional tools were of good quality by criteria of validity, practicality, and effectiveness. These instructional tools was very effective for teaching the volume of cuboid and cube. Cooperative instructional tool with predict-observe-explain (POE) strategy was good of quality because the teacher was easy to implement the steps of learning, students easy to understand the material and students’ learning outcomes completed classically. Learning by using this instructional tool was effective because learning activities were appropriate and students were very active. Students’ learning outcomes were completed classically and better than conventional learning. This study produced a good instructional tool and effectively used in learning. Therefore, these instructional tools can be used as an alternative to teach volume of cuboid and cube topics.

DrugE-Rank: improving drug–target interaction prediction of new candidate drugs or targets by ensemble learning to rank

PubMed Central

Yuan, Qingjun; Gao, Junning; Wu, Dongliang; Zhang, Shihua; Mamitsuka, Hiroshi; Zhu, Shanfeng

2016-01-01

Motivation: Identifying drug–target interactions is an important task in drug discovery. To reduce heavy time and financial cost in experimental way, many computational approaches have been proposed. Although these approaches have used many different principles, their performance is far from satisfactory, especially in predicting drug–target interactions of new candidate drugs or targets. Methods: Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. Learning to rank is the most powerful technique in the feature-based methods. Similarity-based methods are well accepted, due to their idea of connecting the chemical and genomic spaces, represented by drug and target similarities, respectively. We propose a new method, DrugE-Rank, to improve the prediction performance by nicely combining the advantages of the two different types of methods. That is, DrugE-Rank uses LTR, for which multiple well-known similarity-based methods can be used as components of ensemble learning. Results: The performance of DrugE-Rank is thoroughly examined by three main experiments using data from DrugBank: (i) cross-validation on FDA (US Food and Drug Administration) approved drugs before March 2014; (ii) independent test on FDA approved drugs after March 2014; and (iii) independent test on FDA experimental drugs. Experimental results show that DrugE-Rank outperforms competing methods significantly, especially achieving more than 30% improvement in Area under Prediction Recall curve for FDA approved new drugs and FDA experimental drugs. Availability: http://datamining-iip.fudan.edu.cn/service/DrugE-Rank Contact: zhusf@fudan.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307615

Development of probabilistic thinking-oriented learning tools for probability materials at junior high school students

NASA Astrophysics Data System (ADS)

Sari, Dwi Ivayana; Hermanto, Didik

2017-08-01

This research is a developmental research of probabilistic thinking-oriented learning tools for probability materials at ninth grade students. This study is aimed to produce a good probabilistic thinking-oriented learning tools. The subjects were IX-A students of MTs Model Bangkalan. The stages of this development research used 4-D development model which has been modified into define, design and develop. Teaching learning tools consist of lesson plan, students' worksheet, learning teaching media and students' achievement test. The research instrument used was a sheet of learning tools validation, a sheet of teachers' activities, a sheet of students' activities, students' response questionnaire and students' achievement test. The result of those instruments were analyzed descriptively to answer research objectives. The result was teaching learning tools in which oriented to probabilistic thinking of probability at ninth grade students which has been valid. Since teaching and learning tools have been revised based on validation, and after experiment in class produced that teachers' ability in managing class was effective, students' activities were good, students' responses to the learning tools were positive and the validity, sensitivity and reliability category toward achievement test. In summary, this teaching learning tools can be used by teacher to teach probability for develop students' probabilistic thinking.

ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging

PubMed Central

Ovesný, Martin; Křížek, Pavel; Borkovec, Josef; Švindrych, Zdeněk; Hagen, Guy M.

2014-01-01

Summary: ThunderSTORM is an open-source, interactive and modular plug-in for ImageJ designed for automated processing, analysis and visualization of data acquired by single-molecule localization microscopy methods such as photo-activated localization microscopy and stochastic optical reconstruction microscopy. ThunderSTORM offers an extensive collection of processing and post-processing methods so that users can easily adapt the process of analysis to their data. ThunderSTORM also offers a set of tools for creation of simulated data and quantitative performance evaluation of localization algorithms using Monte Carlo simulations. Availability and implementation: ThunderSTORM and the online documentation are both freely accessible at https://code.google.com/p/thunder-storm/ Contact: guy.hagen@lf1.cuni.cz Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24771516

Chado Controller: advanced annotation management with a community annotation system

PubMed Central

Guignon, Valentin; Droc, Gaëtan; Alaux, Michael; Baurens, Franc-Christophe; Garsmeur, Olivier; Poiron, Claire; Carver, Tim; Rouard, Mathieu; Bocs, Stéphanie

2012-01-01

Summary: We developed a controller that is compliant with the Chado database schema, GBrowse and genome annotation-editing tools such as Artemis and Apollo. It enables the management of public and private data, monitors manual annotation (with controlled vocabularies, structural and functional annotation controls) and stores versions of annotation for all modified features. The Chado controller uses PostgreSQL and Perl. Availability: The Chado Controller package is available for download at http://www.gnpannot.org/content/chado-controller and runs on any Unix-like operating system, and documentation is available at http://www.gnpannot.org/content/chado-controller-doc The system can be tested using the GNPAnnot Sandbox at http://www.gnpannot.org/content/gnpannot-sandbox-form Contact: valentin.guignon@cirad.fr; stephanie.sidibe-bocs@cirad.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22285827

SeqPig: simple and scalable scripting for large sequencing data sets in Hadoop

PubMed Central

Schumacher, André; Pireddu, Luca; Niemenmaa, Matti; Kallio, Aleksi; Korpelainen, Eija; Zanetti, Gianluigi; Heljanko, Keijo

2014-01-01

Summary: Hadoop MapReduce-based approaches have become increasingly popular due to their scalability in processing large sequencing datasets. However, as these methods typically require in-depth expertise in Hadoop and Java, they are still out of reach of many bioinformaticians. To solve this problem, we have created SeqPig, a library and a collection of tools to manipulate, analyze and query sequencing datasets in a scalable and simple manner. SeqPigscripts use the Hadoop-based distributed scripting engine Apache Pig, which automatically parallelizes and distributes data processing tasks. We demonstrate SeqPig’s scalability over many computing nodes and illustrate its use with example scripts. Availability and Implementation: Available under the open source MIT license at http://sourceforge.net/projects/seqpig/ Contact: andre.schumacher@yahoo.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24149054

PWMScan: a fast tool for scanning entire genomes with a position-specific weight matrix.

PubMed

Ambrosini, Giovanna; Groux, Romain; Bucher, Philipp

2018-03-05

Transcription factors (TFs) regulate gene expression by binding to specific short DNA sequences of 5 to 20-bp to regulate the rate of transcription of genetic information from DNA to messenger RNA. We present PWMScan, a fast web-based tool to scan server-resident genomes for matches to a user-supplied PWM or TF binding site model from a public database. The web server and source code are available at http://ccg.vital-it.ch/pwmscan and https://sourceforge.net/projects/pwmscan, respectively. giovanna.ambrosini@epfl.ch. SUPPLEMENTARY DATA ARE AVAILABLE AT BIOINFORMATICS ONLINE.

Seed: a user-friendly tool for exploring and visualizing microbial community data.

PubMed

Beck, Daniel; Dennis, Christopher; Foster, James A

2015-02-15

In this article we present Simple Exploration of Ecological Data (Seed), a data exploration tool for microbial communities. Seed is written in R using the Shiny library. This provides access to powerful R-based functions and libraries through a simple user interface. Seed allows users to explore ecological datasets using principal coordinate analyses, scatter plots, bar plots, hierarchal clustering and heatmaps. Seed is open source and available at https://github.com/danlbek/Seed. danlbek@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

GOLabeler: Improving Sequence-based Large-scale Protein Function Prediction by Learning to Rank.

PubMed

You, Ronghui; Zhang, Zihan; Xiong, Yi; Sun, Fengzhu; Mamitsuka, Hiroshi; Zhu, Shanfeng

2018-03-07

Gene Ontology (GO) has been widely used to annotate functions of proteins and understand their biological roles. Currently only <1% of more than 70 million proteins in UniProtKB have experimental GO annotations, implying the strong necessity of automated function prediction (AFP) of proteins, where AFP is a hard multilabel classification problem due to one protein with a diverse number of GO terms. Most of these proteins have only sequences as input information, indicating the importance of sequence-based AFP (SAFP: sequences are the only input). Furthermore homology-based SAFP tools are competitive in AFP competitions, while they do not necessarily work well for so-called difficult proteins, which have <60% sequence identity to proteins with annotations already. Thus the vital and challenging problem now is how to develop a method for SAFP, particularly for difficult proteins. The key of this method is to extract not only homology information but also diverse, deep- rooted information/evidence from sequence inputs and integrate them into a predictor in a both effective and efficient manner. We propose GOLabeler, which integrates five component classifiers, trained from different features, including GO term frequency, sequence alignment, amino acid trigram, domains and motifs, and biophysical properties, etc., in the framework of learning to rank (LTR), a paradigm of machine learning, especially powerful for multilabel classification. The empirical results obtained by examining GOLabeler extensively and thoroughly by using large-scale datasets revealed numerous favorable aspects of GOLabeler, including significant performance advantage over state-of-the-art AFP methods. http://datamining-iip.fudan.edu.cn/golabeler. zhusf@fudan.edu.cn. Supplementary data are available at Bioinformatics online.

Student participation in World Wide Web-based curriculum development of general chemistry

NASA Astrophysics Data System (ADS)

Hunter, William John Forbes

1998-12-01

This thesis describes an action research investigation of improvements to instruction in General Chemistry at Purdue University. Specifically, the study was conducted to guide continuous reform of curriculum materials delivered via the World Wide Web by involving students, instructors, and curriculum designers. The theoretical framework for this study was based upon constructivist learning theory and knowledge claims were developed using an inductive analysis procedure. This results of this study are assertions made in three domains: learning chemistry content via the World Wide Web, learning about learning via the World Wide Web, and learning about participation in an action research project. In the chemistry content domain, students were able to learn chemical concepts that utilized 3-dimensional visualizations, but not textual and graphical information delivered via the Web. In the learning via the Web domain, the use of feedback, the placement of supplementary aids, navigation, and the perception of conceptual novelty were all important to students' use of the Web. In the participation in action research domain, students learned about the complexity of curriculum. development, and valued their empowerment as part of the process.

A pilot study on conducting mobile learning activities for clinical nursing courses based on the repertory grid approach.

PubMed

Wu, Po-Han; Hwang, Gwo-Jen; Tsai, Chin-Chung; Chen, Ya-Chun; Huang, Yueh-Min

2011-11-01

In clinical nursing courses, students are trained to identify the status of the target patients. The mastery of such ability and skills is very important since patients frequently need to be cared for immediately. In this pilot study, a repertory grid-oriented clinical mobile learning system is developed for a nursing training program. With the assistance of the mobile learning system, the nursing school students are able to learn in an authentic learning scenario, in which they can physically face the target patients, with the personal guidance and supplementary materials from the learning system to support them. To show the effectiveness of this innovative approach, an experiment has been conducted on the "respiratory system" unit of a nursing course. The experimental results show that the innovative approach is helpful to students in improving their learning achievements. Moreover, from the questionnaire surveys, it was found that most students showed favorable attitudes toward the usage of the mobile learning system and their participation in the training program. Copyright © 2010 Elsevier Ltd. All rights reserved.

IgSimulator: a versatile immunosequencing simulator.

PubMed

Safonova, Yana; Lapidus, Alla; Lill, Jennie

2015-10-01

The recent introduction of next-generation sequencing technologies to antibody studies have resulted in a growing number of immunoinformatics tools for antibody repertoire analysis. However, benchmarking these newly emerging tools remains problematic since the gold standard datasets that are needed to validate these tools are typically not available. Since simulating antibody repertoires is often the only feasible way to benchmark new immunoinformatics tools, we developed the IgSimulator tool that addresses various complications in generating realistic antibody repertoires. IgSimulator's code has modular structure and can be easily adapted to new requirements to simulation. IgSimulator is open source and freely available as a C++ and Python program running on all Unix-compatible platforms. The source code is available from yana-safonova.github.io/ig_simulator. safonova.yana@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Improving Students' Understanding of Quantum Measurement. II. Development of Research-Based Learning Tools

ERIC Educational Resources Information Center

Zhu, Guangtian; Singh, Chandralekha

2012-01-01

We describe the development and implementation of research-based learning tools such as the Quantum Interactive Learning Tutorials and peer-instruction tools to reduce students' common difficulties with issues related to measurement in quantum mechanics. A preliminary evaluation shows that these learning tools are effective in improving students'…

iDHS-EL: identifying DNase I hypersensitive sites by fusing three different modes of pseudo nucleotide composition into an ensemble learning framework.

PubMed

Liu, Bin; Long, Ren; Chou, Kuo-Chen

2016-08-15

Regulatory DNA elements are associated with DNase I hypersensitive sites (DHSs). Accordingly, identification of DHSs will provide useful insights for in-depth investigation into the function of noncoding genomic regions. In this study, using the strategy of ensemble learning framework, we proposed a new predictor called iDHS-EL for identifying the location of DHS in human genome. It was formed by fusing three individual Random Forest (RF) classifiers into an ensemble predictor. The three RF operators were respectively based on the three special modes of the general pseudo nucleotide composition (PseKNC): (i) kmer, (ii) reverse complement kmer and (iii) pseudo dinucleotide composition. It has been demonstrated that the new predictor remarkably outperforms the relevant state-of-the-art methods in both accuracy and stability. For the convenience of most experimental scientists, a web server for iDHS-EL is established at http://bioinformatics.hitsz.edu.cn/iDHS-EL, which is the first web-server predictor ever established for identifying DHSs, and by which users can easily get their desired results without the need to go through the mathematical details. We anticipate that IDHS-EL: will become a very useful high throughput tool for genome analysis. bliu@gordonlifescience.org or bliu@insun.hit.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Traumatic Brain Injury Diffusion Magnetic Resonance Imaging Research Roadmap Development Project

DTIC Science & Technology

2012-10-01

Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT . Traumatic Brain Injury ( TBI ) is a public health problem of immense magnitude and...immediate importance that has become endemic among military personnel and veterans. Imaging biomarkers of TBI are needed to support diagnosis and therapy...and to predict TBI consequences while avoiding further injury. Diffusion magnetic resonance imaging has potential to become the non-invasive tool

XDATA

DTIC Science & Technology

2017-12-01

6028 Date Cleared: 30 NOV 2017 13. SUPPLEMENTARY NOTES 14. ABSTRACT Data analysis tools which operate on varied data sources including time series ...public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions...and raw detections from geo-located tweets Micro-paths (10M) (No distance/ time filter) Raw Tracks (10M) Raw Detections (10M) APPROVED FOR PUBLIC

Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding

PubMed Central

Min, Xu; Zeng, Wanwen; Chen, Ning; Chen, Ting; Jiang, Rui

2017-01-01

Abstract Motivation: Experimental techniques for measuring chromatin accessibility are expensive and time consuming, appealing for the development of computational approaches to predict open chromatin regions from DNA sequences. Along this direction, existing methods fall into two classes: one based on handcrafted k-mer features and the other based on convolutional neural networks. Although both categories have shown good performance in specific applications thus far, there still lacks a comprehensive framework to integrate useful k-mer co-occurrence information with recent advances in deep learning. Results: We fill this gap by addressing the problem of chromatin accessibility prediction with a convolutional Long Short-Term Memory (LSTM) network with k-mer embedding. We first split DNA sequences into k-mers and pre-train k-mer embedding vectors based on the co-occurrence matrix of k-mers by using an unsupervised representation learning approach. We then construct a supervised deep learning architecture comprised of an embedding layer, three convolutional layers and a Bidirectional LSTM (BLSTM) layer for feature learning and classification. We demonstrate that our method gains high-quality fixed-length features from variable-length sequences and consistently outperforms baseline methods. We show that k-mer embedding can effectively enhance model performance by exploring different embedding strategies. We also prove the efficacy of both the convolution and the BLSTM layers by comparing two variations of the network architecture. We confirm the robustness of our model to hyper-parameters by performing sensitivity analysis. We hope our method can eventually reinforce our understanding of employing deep learning in genomic studies and shed light on research regarding mechanisms of chromatin accessibility. Availability and implementation: The source code can be downloaded from https://github.com/minxueric/ismb2017_lstm. Contact: tingchen@tsinghua.edu.cn or ruijiang@tsinghua.edu.cn Supplementary information: Supplementary materials are available at Bioinformatics online. PMID:28881969

Discovering online learning barriers: survey of health educational stakeholders in dentistry.

PubMed

Schönwetter, D; Reynolds, P

2013-02-01

Given the exponential explosion of online learning tools and the challenge to harness their influence in dental education, there is a need to determine the current status of online learning tools being adopted at dental schools, the barriers that thwart the potential of adopting these and to capture this information from each of the various stakeholders involved in dental online learning (administrators, instructors, students and software/hardware technicians). The aims of this exploratory study are threefold: first, to understand which online learning tools are currently being adopted at dental schools; second, to determine the barriers in adopting online learning in dental education; and third, to identify a way of better preparing stakeholders in their quest to encourage others at their institutions to adopt online learning tools. Seventy-two participants representing eight countries and 13 stakeholder groups in dentistry were invited to complete the online Survey of Barriers in Online Learning Education in Health Professional Schools. The survey was created for this study but generic to all healthcare education domains. Twenty participants completed the survey. demonstrated that many online learning tools are being successfully adopted at dental schools, but computer-based assessment tools are the least successful. Added to this are challenges of support and resources for online learning tools. Participants offered suggestions of creating a blended (online and face-to-face) tutorial aimed at assisting stakeholders to help their dental schools in adopting online learning tools The information from this study is essential in helping us to better prepare the next generation of dental providers in terms of adopting online learning tools. This paper will not only provide strategies of how best to proceed, but also inspire participants with the necessary tools to move forward as they assist their clients with adopting and sustaining online learning tools and models. © 2012 John Wiley & Sons A/S.

MaGnET: Malaria Genome Exploration Tool.

PubMed

Sharman, Joanna L; Gerloff, Dietlind L

2013-09-15

The Malaria Genome Exploration Tool (MaGnET) is a software tool enabling intuitive 'exploration-style' visualization of functional genomics data relating to the malaria parasite, Plasmodium falciparum. MaGnET provides innovative integrated graphic displays for different datasets, including genomic location of genes, mRNA expression data, protein-protein interactions and more. Any selection of genes to explore made by the user is easily carried over between the different viewers for different datasets, and can be changed interactively at any point (without returning to a search). Free online use (Java Web Start) or download (Java application archive and MySQL database; requires local MySQL installation) at http://malariagenomeexplorer.org joanna.sharman@ed.ac.uk or dgerloff@ffame.org Supplementary data are available at Bioinformatics online.

Overcoming Learning Time and Space Constraints through Technological Tool

ERIC Educational Resources Information Center

Zarei, Nafiseh; Hussin, Supyan; Rashid, Taufik

2015-01-01

Today the use of technological tools has become an evolution in language learning and language acquisition. Many instructors and lecturers believe that integrating Web-based learning tools into language courses allows pupils to become active learners during learning process. This study investigates how the Learning Management Blog (LMB) overcomes…

Development, Implementation and Evaluation of an Audiotape and Accompanying Visuals in Hemodynamics as a Supplementary Teaching Aid for Human Anatomy and Physiology: Curriculum and Program Planning.

ERIC Educational Resources Information Center

Selvadurai, Ranjani H.

The purpose of this study was to develop, implement, and evaluate an audiotape and accompanying handouts on hemodynamics as a supplemental teaching aid in the Health Science Learning Center of New York City Technical College. It was hypothesized that there would be a significant difference between the mean examination grade on hemodynamics of…

Object Toolkit Version 4.3 User’s Manual

DTIC Science & Technology

2016-12-31

unlimited. (OPS-17-12855 dtd 19 Jan 2017) 13. SUPPLEMENTARY NOTES 14. ABSTRACT Object Toolkit is a finite - element model builder specifically designed for...INTRODUCTION 1 What Is Object Toolkit? Object Toolkit is a finite - element model builder specifically designed for creating representations of spacecraft...Nascap-2k and EPIC, the user is not required to purchase or learn expensive finite element generators to create system models. Second, Object Toolkit

Feedback Effects in Computer-Based Skill Learning

DTIC Science & Technology

1989-09-12

SUPPLEMENTARY NOTATION 17 COSATI CODES 18 SUBJECT TERMS (Continue on reverse if necessary and identify by block number) r FIELD GROUP SUB-GROUP I...rather than tangible feedback ( Barringer & Gholson, 1979) and when they receive punishment (either alone or witih reward) rather than reward alone...34graphed" response latencies across the four conditions ( r = .58), indicating that subjects were sensitive to block-by-block trends in their response

The effects of UV radiation during the vegetative period on antioxidant compounds and postharvest quality of broccoli (Brassica oleracea L.).

PubMed

Topcu, Yasin; Dogan, Adem; Kasimoglu, Zehra; Sahin-Nadeem, Hilal; Polat, Ersin; Erkan, Mustafa

2015-08-01

In this study, the effects of supplementary UV radiation during the vegetative period on antioxidant compounds, antioxidant activity and postharvest quality of broccoli heads during long term storage was studied. The broccolis were grown under three different doses of supplementary UV radiation (2.2, 8.8 and 16.4 kJ/m(2)/day) in a soilless system in a glasshouse. Harvested broccoli heads were stored at 0 °C in modified atmosphere packaging for 60 days. The supplementary UV radiation (280-315 nm) during the vegetative period significantly decreased total carotenoid, the chlorophyll a and chlorophyll b content but increased the ascorbic acid, total phenolic and flavonoid contents of broccolis. All supplementary UV treatments slightly reduced the antioxidant activity of the broccolis, however, no remarkable change was observed between 2.2 and 8.8 kJ/m(2) radiation levels. The sinigrin and glucotropaeolin contents of the broccolis were substantially increased by UV treatments. The prolonged storage period resulted in decreased ascorbic acid, total phenolic and flavonoid contents, as well as antioxidant activity. Discoloration of the heads, due to decreased chlorophyll and carotenoid contents, was also observed with prolonged storage duration. Glucosinolates levels showed an increasing tendency till the 45th day of storage, and then their levels started to decline. The weight loss of broccoli heads during storage progressively increased with storage time in all treatments. Total soluble solids, solids content and titratable acidity decreased continuously during storage. Titratable acidity was not affected by UV radiation doses during the storage time whereas soluble solids and solids content (dry matter) were significantly affected by UV doses. Supplementary UV radiation increased the lightness (L*) and chroma (C*) values of the broccoli heads. Pre-harvest UV radiation during vegetative period seems to be a promising tool for increasing the beneficial health components of broccolis. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Language experience differentiates prefrontal and subcortical activation of the cognitive control network in novel word learning

PubMed Central

King, Kelly E.; Hernandez, Arturo E.

2012-01-01

The purpose of this study was to examine the cognitive control mechanisms in adult English speaking monolinguals compared to early sequential Spanish-English bilinguals during the initial stages of novel word learning. Functional magnetic resonance imaging during a lexico-semantic task after only two hours of exposure to novel German vocabulary flashcards showed that monolinguals activated a broader set of cortical control regions associated with higher-level cognitive processes, including the supplementary motor area (SMA), anterior cingulate (ACC), and dorsolateral prefrontal cortex (DLPFC), as well as the caudate, implicated in cognitive control of language. However, bilinguals recruited a more localized subcortical network that included the putamen, associated more with motor control of language. These results suggest that experience managing multiple languages may differentiate the learning strategy and subsequent neural mechanisms of cognitive control used by bilinguals compared to monolinguals in the early stages of novel word learning. PMID:23194816

Direct heuristic dynamic programming for damping oscillations in a large power system.

PubMed

Lu, Chao; Si, Jennie; Xie, Xiaorong

2008-08-01

This paper applies a neural-network-based approximate dynamic programming method, namely, the direct heuristic dynamic programming (direct HDP), to a large power system stability control problem. The direct HDP is a learning- and approximation-based approach to addressing nonlinear coordinated control under uncertainty. One of the major design parameters, the controller learning objective function, is formulated to directly account for network-wide low-frequency oscillation with the presence of nonlinearity, uncertainty, and coupling effect among system components. Results include a novel learning control structure based on the direct HDP with applications to two power system problems. The first case involves static var compensator supplementary damping control, which is used to provide a comprehensive evaluation of the learning control performance. The second case aims at addressing a difficult complex system challenge by providing a new solution to a large interconnected power network oscillation damping control problem that frequently occurs in the China Southern Power Grid.

Brain volumetry and self-regulation of brain activity relevant for neurofeedback.

PubMed

Ninaus, M; Kober, S E; Witte, M; Koschutnig, K; Neuper, C; Wood, G

2015-09-01

Neurofeedback is a technique to learn to control brain signals by means of real time feedback. In the present study, the individual ability to learn two EEG neurofeedback protocols - sensorimotor rhythm and gamma rhythm - was related to structural properties of the brain. The volumes in the anterior insula bilaterally, left thalamus, right frontal operculum, right putamen, right middle frontal gyrus, and right lingual gyrus predicted the outcomes of sensorimotor rhythm training. Gray matter volumes in the supplementary motor area and left middle frontal gyrus predicted the outcomes of gamma rhythm training. These findings combined with further evidence from the literature are compatible with the existence of a more general self-control network, which through self-referential and self-control processes regulates neurofeedback learning. Copyright © 2015 Elsevier B.V. All rights reserved.

Clinical Decision Support Tools for Osteoporosis Disease Management: A Systematic Review of Randomized Controlled Trials

PubMed Central

Straus, Sharon E.

2008-01-01

BACKGROUND Studies indicate a gap between evidence and clinical practice in osteoporosis management. Tools that facilitate clinical decision making at the point of care are promising strategies for closing these practice gaps. OBJECTIVE To systematically review the literature to identify and describe the effectiveness of tools that support clinical decision making in osteoporosis disease management. DATA SOURCES Medline, EMBASE, CINAHL, and EBM Reviews (CDSR, DARE, CCTR, and ACP J Club), and contact with experts in the field. REVIEW METHODS Randomized controlled trials (RCTs) in any language from 1966 to July 2006 investigating disease management interventions in patients at risk for osteoporosis. Outcomes included fractures and bone mineral density (BMD) testing. Two investigators independently assessed articles for relevance and study quality, and extracted data using standardized forms. RESULTS Of 1,246 citations that were screened for relevance, 13 RCTs met the inclusion criteria. Reported study quality was generally poor. Meta-analysis was not done because of methodological and clinical heterogeneity; 77% of studies included a reminder or education as a component of their intervention. Three studies of reminders plus education targeted to physicians and patients showed increased BMD testing (RR range 1.43 to 8.67) and osteoporosis medication use (RR range 1.60 to 8.67). A physician reminder plus a patient risk assessment strategy found reduced fractures [RR 0.58, 95% confidence interval (CI) 0.37 to 0.90] and increased osteoporosis therapy (RR 2.44, CI 1.43 to 4.17). CONCLUSION Multi-component tools that are targeted to physicians and patients may be effective for supporting clinical decision making in osteoporosis disease management. Electronic supplementary material The online version of this article (doi:10.1007/s11606-008-0812-9) contains supplementary material, which is available to authorized users. PMID:18836782

Supplementary insurance as a switching cost for basic health insurance: Empirical results from the Netherlands.

PubMed

Willemse-Duijmelinck, Daniëlle M I D; van de Ven, Wynand P M M; Mosca, Ilaria

2017-10-01

Nearly everyone with a supplementary insurance (SI) in the Netherlands takes out the voluntary SI and the mandatory basic insurance (BI) from the same health insurer. Previous studies show that many high-risks perceive SI as a switching cost for BI. Because consumers' current insurer provides them with a guaranteed renewability, SI is a switching cost if insurers apply selective underwriting to new applicants. Several changes in the Dutch health insurance market increased insurers' incentives to counteract adverse selection for SI. Tools to do so are not only selective underwriting, but also risk rating and product differentiation. If all insurers use the latter tools without selective underwriting, SI is not a switching cost for BI. We investigated to what extent insurers used these tools in the periods 2006-2009 and 2014-2015. Only a few insurers applied selective underwriting: in 2015, 86% of insurers used open enrolment for all their SI products, and the other 14% did use open enrolment for their most common SI products. As measured by our indicators, the proportion of insurers applying risk rating or product differentiation did not increase in the periods considered. Due to the fear of reputation loss insurers may have used 'less visible' tools to counteract adverse selection that are indirect forms of risk rating and product differentiation and do not result in switching costs. So, although many high-risks perceive SI as a switching cost, most insurers apply open enrolment for SI. By providing information to high-risks about their switching opportunities, the government could increase consumer choice and thereby insurers' incentives to invest in high-quality care for high-risks. Copyright © 2017 Elsevier B.V. All rights reserved.

3D-SURFER: software for high-throughput protein surface comparison and analysis

PubMed Central

La, David; Esquivel-Rodríguez, Juan; Venkatraman, Vishwesh; Li, Bin; Sael, Lee; Ueng, Stephen; Ahrendt, Steven; Kihara, Daisuke

2009-01-01

Summary: We present 3D-SURFER, a web-based tool designed to facilitate high-throughput comparison and characterization of proteins based on their surface shape. As each protein is effectively represented by a vector of 3D Zernike descriptors, comparison times for a query protein against the entire PDB take, on an average, only a couple of seconds. The web interface has been designed to be as interactive as possible with displays showing animated protein rotations, CATH codes and structural alignments using the CE program. In addition, geometrically interesting local features of the protein surface, such as pockets that often correspond to ligand binding sites as well as protrusions and flat regions can also be identified and visualized. Availability: 3D-SURFER is a web application that can be freely accessed from: http://dragon.bio.purdue.edu/3d-surfer Contact: dkihara@purdue.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19759195

Online Learning Tools as Supplements for Basic and Clinical Science Education.

PubMed

Ellman, Matthew S; Schwartz, Michael L

2016-01-01

Undergraduate medical educators are increasingly incorporating online learning tools into basic and clinical science curricula. In this paper, we explore the diversity of online learning tools and consider the range of applications for these tools in classroom and bedside learning. Particular advantages of these tools are highlighted, such as delivering foundational knowledge as part of the "flipped classroom" pedagogy and for depicting unusual physical examination findings and advanced clinical communication skills. With accelerated use of online learning, educators and administrators need to consider pedagogic and practical challenges posed by integrating online learning into individual learning activities, courses, and curricula as a whole. We discuss strategies for faculty development and the role of school-wide resources for supporting and using online learning. Finally, we consider the role of online learning in interprofessional, integrated, and competency-based applications among other contemporary trends in medical education are considered.

Online Learning Tools as Supplements for Basic and Clinical Science Education

PubMed Central

Ellman, Matthew S.; Schwartz, Michael L.

2016-01-01

Undergraduate medical educators are increasingly incorporating online learning tools into basic and clinical science curricula. In this paper, we explore the diversity of online learning tools and consider the range of applications for these tools in classroom and bedside learning. Particular advantages of these tools are highlighted, such as delivering foundational knowledge as part of the “flipped classroom” pedagogy and for depicting unusual physical examination findings and advanced clinical communication skills. With accelerated use of online learning, educators and administrators need to consider pedagogic and practical challenges posed by integrating online learning into individual learning activities, courses, and curricula as a whole. We discuss strategies for faculty development and the role of school-wide resources for supporting and using online learning. Finally, we consider the role of online learning in interprofessional, integrated, and competency-based applications among other contemporary trends in medical education are considered. PMID:29349323

Educational software usability: Artifact or Design?

PubMed

Van Nuland, Sonya E; Eagleson, Roy; Rogers, Kem A

2017-03-01

Online educational technologies and e-learning tools are providing new opportunities for students to learn worldwide, and they continue to play an important role in anatomical sciences education. Yet, as we shift to teaching online, particularly within the anatomical sciences, it has become apparent that e-learning tool success is based on more than just user satisfaction and preliminary learning outcomes-rather it is a multidimensional construct that should be addressed from an integrated perspective. The efficiency, effectiveness and satisfaction with which a user can navigate an e-learning tool is known as usability, and represents a construct which we propose can be used to quantitatively evaluate e-learning tool success. To assess the usability of an e-learning tool, usability testing should be employed during the design and development phases (i.e., prior to its release to users) as well as during its delivery (i.e., following its release to users). However, both the commercial educational software industry and individual academic developers in the anatomical sciences have overlooked the added value of additional usability testing. Reducing learner frustration and anxiety during e-learning tool use is essential in ensuring e-learning tool success, and will require a commitment on the part of the developers to engage in usability testing during all stages of an e-learning tool's life cycle. Anat Sci Educ 10: 190-199. © 2016 American Association of Anatomists. © 2016 American Association of Anatomists.

WebCT: integrating computer-mediated communication and resource delivery into a new problem-based curriculum.

PubMed

McLean, Michelle; Murrell, Kathy

2002-03-01

WebCT, front-end software for Internet-delivered material, became an integral part of a problem-based learning, student-centred curriculum introduced in January 2001 at the Nelson R. Mandela School of Medicine (South Africa). A template for six curriculum and two supplementary modules was developed. Organiser and Tool pages were added and files uploaded as each module progressed. This study provides feedback from students with regard to the value of WebCT in their curriculum, as well as discussing the value of WebCT for the delivery of digitized material (e.g., images, videos, PowerPoint presentations). In an anonymous survey following the completion of the first module, students, apparently irrespective of their level of computer literacy, responded positively to the communication facility between staff and students and amongst students, the resources and the URLs. Based on these preliminary responses, WebCT courses for all six modules were developed during 2001. With Faculty support, WebCT will probably be integrated into the rest of the MBChB programme. It will be particularly useful when students are off campus, undertaking electives and community service in the later years.

[Problem-based learning, a strategy to employ it].

PubMed

Guillamet Lloveras, Ana; Celma Vicente, Matilde; González Carrión, Pilar; Cano-Caballero Gálvez, Ma Dolores; Pérez Ramírez, Francisca

2009-02-01

The Virgen de las Nieves University School of Nursing has adopted the methodology of Problem-Based Learning (ABP in Spanish acronym) as a supplementary method to gain specific transversal competencies. In so doing, all basic required/obligatory subjects necessary for a degree have been partially affected. With the objective of identifying and administering all the structural and cultural barriers which could impede the success or effectiveness of its adoption, a strategic analysis at the School was carried out. This technique was based on a) knowing the strong and weak points the School has for adopting the Problem-Based Learning methodology; b) describing the structural problems and necessities to carry out this teaching innovation; c) to discover the needs professors have regarding knowledge and skills related to Problem-Based Learning; d) to prepare students by informing them about the characteristics of Problem-Based Learning; e) to evaluate the results obtained by means of professor and student opinions, f) to adopt the improvements identified. The stages followed were: strategic analysis, preparation, pilot program, adoption and evaluation.

The Impact of Using SMS as Learning Support Tool on Students' Learning

ERIC Educational Resources Information Center

Gasaymeh, Al-Mothana M.; Aldalalah, Osamah M.

2013-01-01

This study aimed to investigate the impact of using Short Message Service (SMS) as learning support tool on students' learning in an introductory programming course. In addition, the study examined students' perceptions of the advantages and disadvantages of the use of SMS as a learning support tool in their class. The participants in this study…

Open Educational Resources in Support of Science Learning: Tools for Inquiry and Observation

ERIC Educational Resources Information Center

Scanlon, Eileen

2012-01-01

This article focuses on the potential of free tools, particularly inquiry tools for influencing participation in twenty-first-century learning in science, as well as influencing the development of communities around tools. Two examples are presented: one on the development of an open source tool for structured inquiry learning that can bridge the…

3D Printed Fluidic Hardware for DNA Assembly

DTIC Science & Technology

2015-04-10

A3909 stepper motor driver, were soldered onto the milled circuit board (Supplementary Figure 8). Custom Arduino - based firmware was written to take...initiatives such as the FabLab Foundation10. Access to digital fabrication tools and open electronics, such as Arduino and Raspberry Pi, enables access to...hardware for assembly of DNA- based genetic circuits. Solid-phase DNA synthesis has declined in price, enabling researchers to routinely design and

TARDEC FIXED HEEL POINT (FHP): DRIVER CAD ACCOMMODATION MODEL VERIFICATION REPORT

DTIC Science & Technology

2017-11-09

SUPPLEMENTARY NOTES N/A 14. ABSTRACT Easy-to-use Computer-Aided Design (CAD) tools, known as accommodation models, are needed by the ground vehicle... designers when developing the interior workspace for the occupant. The TARDEC Fixed Heel Point (FHP): Driver CAD Accommodation Model described in this...is intended to provide the composite boundaries representing the body of the defined target design population, including posture prediction

Applying Genomic and Genetic Tools to Understand and Mitigate Damage from Exposure to Toxins

DTIC Science & Technology

2011-10-01

Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Use of the pyridostigmine bromide during the 1991 Gulf War has been implicated as a contributing...2 EXECUTIVE SUMMARY Treatment of soldiers of the 1991 Gulf War with the drug pyridostigmine bromide for pretreatment against nerve agents has...organism for the characterization of the effects of pyridostigmine bromide (PB) on gene expression using unbiased, high-throughput techniques, specifically

Rapid Deployment of Optimal Control for Building HVAC Systems Using Innovative Software Tools and a Hybrid Heuristic/Model Based Control Approach

DTIC Science & Technology

2017-03-21

for public release; distribution is unlimited 13. SUPPLEMENTARY NOTES None 14. ABSTRACT ESTCP project EW-201409 aimed at demonstrating the benefits ...of innovative software technology for building HV AC systems. These benefits included reduced system energy use and cost as wetl as improved...Control Approach March 2017 This document has been cleared for public release; Distribution Statement A

Feedback: A Key Component in the Design, Development and Validation Stages of Online English/FL Materials

ERIC Educational Resources Information Center

Martínez, Antonio; Sevilla, Ana; Gimeno, Ana; de Siqueira, José Macario

2012-01-01

For the past few years, the authors have been working on the design and development of an online First Certificate in English (FCE) preparatory course and exam simulator in an attempt to provide a supplementary tool and resources for students aiming to achieve a B2 level of English. These materials have been designed in such a way that learners…

Statistical Study of Soviet Nuclear Explosions: Data, Results, and Software Tools

DTIC Science & Technology

1993-11-05

KIRTLAND AFB, NM 87117-6008 Monitored by: ADVANCED RESEARCH PROJECTS AGENCY NUCLEAR MONITORING RESEARCH OFFICE 94-03131 3701 NORTH FAIRFAX DRIVE...AGENCY REPORT NUMBER ARPAINMRO (Attn. Dr. Alan Ryall, Jr.) 3701 North Fairfax Drive Arlington, VA 22203-1714 11. SUPPLEMENTARY NOTES *Department of...dug by them, in Nuclear Explosions for Peaceful Purposes (I. D. Morokhov, Ed.), Atomizdat, Moscow, LLL Report UCRL -Trans-10517, 79-109. Nuttli, 0. W

Analysis of Error Propagation Within Hierarchical Air Combat Models

DTIC Science & Technology

2016-06-01

Model Simulation MANA Map Aware Non-Uniform Automata MCET Mine Warfare Capabilities and Effectiveness Tool MOE measure of effectiveness MOP measure of...model for a two-versus-two air engagement between jet fighters in the stochastic, agent-based Map Aware Non- uniform Automata (MANA) simulation...Master’s thesis, Naval Postgraduate School, Monterey, CA. McIntosh, G. C. (2009). MANA-V (Map aware non-uniform automata – Vector) supplementary manual

A Study of Topic and Topic Change in Conversational Threads

DTIC Science & Technology

2009-09-01

AUTHOR(S) 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS( ES ) 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING / MONITORING AGENCY NAME(S) AND...ADDRESS( ES ) 10. SPONSOR/MONITOR’S ACRONYM(S) 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION / AVAILABILITY STATEMENT 13. SUPPLEMENTARY NOTES...unigrams. By converting documents to a vector space representations, the tools of geometry and algebra can be applied, and questions of difference

Flow Simulations: The Lagrangian Averaged Navier-stokes Equations and Optimization

DTIC Science & Technology

2009-05-19

S) 12. DISTRIBUTION/AVAILABILITY STATEMENT DISTRIBUTION A: APPROVED FOR PUBLIC RELEASE 13. SUPPLEMENTARY NOTES 14. ABSTRACT This project had two...Structures can be an important tool in achieving this goal. As we will demonstate, LCS can be very usefull in identifying the separation manifolds...s) financially responsible for and monitoring the work. 10. SPONSOR/MONITOR’S ACRONYM(S). Enter, if available, e.g. BRL, ARDEC, NADC. 11. SPONSOR

Analyzing large scale genomic data on the cloud with Sparkhit

PubMed Central

Huang, Liren; Krüger, Jan

2018-01-01

Abstract Motivation The increasing amount of next-generation sequencing data poses a fundamental challenge on large scale genomic analytics. Existing tools use different distributed computational platforms to scale-out bioinformatics workloads. However, the scalability of these tools is not efficient. Moreover, they have heavy run time overheads when pre-processing large amounts of data. To address these limitations, we have developed Sparkhit: a distributed bioinformatics framework built on top of the Apache Spark platform. Results Sparkhit integrates a variety of analytical methods. It is implemented in the Spark extended MapReduce model. It runs 92–157 times faster than MetaSpark on metagenomic fragment recruitment and 18–32 times faster than Crossbow on data pre-processing. We analyzed 100 terabytes of data across four genomic projects in the cloud in 21 h, which includes the run times of cluster deployment and data downloading. Furthermore, our application on the entire Human Microbiome Project shotgun sequencing data was completed in 2 h, presenting an approach to easily associate large amounts of public datasets with reference data. Availability and implementation Sparkhit is freely available at: https://rhinempi.github.io/sparkhit/. Contact asczyrba@cebitec.uni-bielefeld.de Supplementary information Supplementary data are available at Bioinformatics online. PMID:29253074

RNA splicing process analysis for identifying antisense oligonucleotide inhibitors with padlock probe-based isothermal amplification† †Electronic supplementary information (ESI) available: Additional experimental materials, methods, DNA sequences and supplementary figures and tables. See DOI: 10.1039/c7sc01336a Click here for additional data file.

PubMed Central

Ren, Xiaojun; Deng, Ruijie; Wang, Lida; Zhang, Kaixiang

2017-01-01

RNA splicing, which mainly involves two transesterification steps, is a fundamental process of gene expression and its abnormal regulation contributes to serious genetic diseases. Antisense oligonucleotides (ASOs) are genetic control tools that can be used to specifically control genes through alteration of the RNA splicing pathway. Despite intensive research, how ASOs or various other factors influence the multiple processes of RNA splicing still remains obscure. This is largely due to an inability to analyze the splicing efficiency of each step in the RNA splicing process with high sensitivity. We addressed this limitation by introducing a padlock probe-based isothermal amplification assay to achieve quantification of the specific products in different splicing steps. With this amplified assay, the roles that ASOs play in RNA splicing inhibition in the first and second steps could be distinguished. We identified that 5′-ASO could block RNA splicing by inhibiting the first step, while 3′-ASO could block RNA splicing by inhibiting the second step. This method provides a versatile tool for assisting efficient ASO design and discovering new splicing modulators and therapeutic drugs. PMID:28989608

HIV classification using the coalescent theory

PubMed Central

Bulla, Ingo; Schultz, Anne-Kathrin; Schreiber, Fabian; Zhang, Ming; Leitner, Thomas; Korber, Bette; Morgenstern, Burkhard; Stanke, Mario

2010-01-01

Motivation: Existing coalescent models and phylogenetic tools based on them are not designed for studying the genealogy of sequences like those of HIV, since in HIV recombinants with multiple cross-over points between the parental strains frequently arise. Hence, ambiguous cases in the classification of HIV sequences into subtypes and circulating recombinant forms (CRFs) have been treated with ad hoc methods in lack of tools based on a comprehensive coalescent model accounting for complex recombination patterns. Results: We developed the program ARGUS that scores classifications of sequences into subtypes and recombinant forms. It reconstructs ancestral recombination graphs (ARGs) that reflect the genealogy of the input sequences given a classification hypothesis. An ARG with maximal probability is approximated using a Markov chain Monte Carlo approach. ARGUS was able to distinguish the correct classification with a low error rate from plausible alternative classifications in simulation studies with realistic parameters. We applied our algorithm to decide between two recently debated alternatives in the classification of CRF02 of HIV-1 and find that CRF02 is indeed a recombinant of Subtypes A and G. Availability: ARGUS is implemented in C++ and the source code is available at http://gobics.de/software Contact: ibulla@uni-goettingen.de Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:20400454

SimPhospho: a software tool enabling confident phosphosite assignment.

PubMed

Suni, Veronika; Suomi, Tomi; Tsubosaka, Tomoya; Imanishi, Susumu Y; Elo, Laura L; Corthals, Garry L

2018-03-27

Mass spectrometry combined with enrichment strategies for phosphorylated peptides has been successfully employed for two decades to identify sites of phosphorylation. However, unambiguous phosphosite assignment is considered challenging. Given that site-specific phosphorylation events function as different molecular switches, validation of phosphorylation sites is of utmost importance. In our earlier study we developed a method based on simulated phosphopeptide spectral libraries, which enables highly sensitive and accurate phosphosite assignments. To promote more widespread use of this method, we here introduce a software implementation with improved usability and performance. We present SimPhospho, a fast and user-friendly tool for accurate simulation of phosphopeptide tandem mass spectra. Simulated phosphopeptide spectral libraries are used to validate and supplement database search results, with a goal to improve reliable phosphoproteome identification and reporting. The presented program can be easily used together with the Trans-Proteomic Pipeline and integrated in a phosphoproteomics data analysis workflow. SimPhospho is available for Windows, Linux and Mac operating systems at https://sourceforge.net/projects/simphospho/. It is open source and implemented in C ++. A user's manual with detailed description of data analysis using SimPhospho as well as test data can be found as supplementary material of this article. Supplementary data are available at https://www.btk.fi/research/ computational-biomedicine/software/.

Systemic evaluation of cellular reprogramming processes exploiting a novel R-tool: eegc

PubMed Central

Zhou, Xiaoyuan; Meng, Guofeng; Nardini, Christine; Mei, Hongkang

2017-01-01

Abstract Motivation Cells derived by cellular engineering, i.e. differentiation of induced pluripotent stem cells and direct lineage reprogramming, carry a tremendous potential for medical applications and in particular for regenerative therapies. These approaches consist in the definition of lineage-specific experimental protocols that, by manipulation of a limited number of biological cues—niche mimicking factors, (in)activation of transcription factors, to name a few—enforce the final expression of cell-specific (marker) molecules. To date, given the intricate complexity of biological pathways, these approaches still present imperfect reprogramming fidelity, with uncertain consequences on the functional properties of the resulting cells. Results We propose a novel tool eegc to evaluate cellular engineering processes, in a systemic rather than marker-based fashion, by integrating transcriptome profiling and functional analysis. Our method clusters genes into categories representing different states of (trans)differentiation and further performs functional and gene regulatory network analyses for each of the categories of the engineered cells, thus offering practical indications on the potential lack of the reprogramming protocol. Availability and Implementation eegc R package is released under the GNU General Public License within the Bioconductor project, freely available at https://bioconductor.org/packages/eegc/. Contact christine.nardini.rsrc@gmail.com or hongkang.k.mei@gsk.com Supplementary information Supplementary data are available at Bioinformatics online. PMID:28398503

Bellman’s GAP—a language and compiler for dynamic programming in sequence analysis

PubMed Central

Sauthoff, Georg; Möhl, Mathias; Janssen, Stefan; Giegerich, Robert

2013-01-01

Motivation: Dynamic programming is ubiquitous in bioinformatics. Developing and implementing non-trivial dynamic programming algorithms is often error prone and tedious. Bellman’s GAP is a new programming system, designed to ease the development of bioinformatics tools based on the dynamic programming technique. Results: In Bellman’s GAP, dynamic programming algorithms are described in a declarative style by tree grammars, evaluation algebras and products formed thereof. This bypasses the design of explicit dynamic programming recurrences and yields programs that are free of subscript errors, modular and easy to modify. The declarative modules are compiled into C++ code that is competitive to carefully hand-crafted implementations. This article introduces the Bellman’s GAP system and its language, GAP-L. It then demonstrates the ease of development and the degree of re-use by creating variants of two common bioinformatics algorithms. Finally, it evaluates Bellman’s GAP as an implementation platform of ‘real-world’ bioinformatics tools. Availability: Bellman’s GAP is available under GPL license from http://bibiserv.cebitec.uni-bielefeld.de/bellmansgap. This Web site includes a repository of re-usable modules for RNA folding based on thermodynamics. Contact: robert@techfak.uni-bielefeld.de Supplementary information: Supplementary data are available at Bioinformatics online PMID:23355290

regSNPs: a strategy for prioritizing regulatory single nucleotide substitutions

PubMed Central

Teng, Mingxiang; Ichikawa, Shoji; Padgett, Leah R.; Wang, Yadong; Mort, Matthew; Cooper, David N.; Koller, Daniel L.; Foroud, Tatiana; Edenberg, Howard J.; Econs, Michael J.; Liu, Yunlong

2012-01-01

Motivation: One of the fundamental questions in genetics study is to identify functional DNA variants that are responsible to a disease or phenotype of interest. Results from large-scale genetics studies, such as genome-wide association studies (GWAS), and the availability of high-throughput sequencing technologies provide opportunities in identifying causal variants. Despite the technical advances, informatics methodologies need to be developed to prioritize thousands of variants for potential causative effects. Results: We present regSNPs, an informatics strategy that integrates several established bioinformatics tools, for prioritizing regulatory SNPs, i.e. the SNPs in the promoter regions that potentially affect phenotype through changing transcription of downstream genes. Comparing to existing tools, regSNPs has two distinct features. It considers degenerative features of binding motifs by calculating the differences on the binding affinity caused by the candidate variants and integrates potential phenotypic effects of various transcription factors. When tested by using the disease-causing variants documented in the Human Gene Mutation Database, regSNPs showed mixed performance on various diseases. regSNPs predicted three SNPs that can potentially affect bone density in a region detected in an earlier linkage study. Potential effects of one of the variants were validated using luciferase reporter assay. Contact: yunliu@iupui.edu Supplementary information: Supplementary data are available at Bioinformatics online PMID:22611130

A Meta-Analysis Method to Advance Design of Technology-Based Learning Tool: Combining Qualitative and Quantitative Research to Understand Learning in Relation to Different Technology Features

ERIC Educational Resources Information Center

Zhang, Lin

2014-01-01

Educators design and create various technology tools to scaffold students' learning. As more and more technology designs are incorporated into learning, growing attention has been paid to the study of technology-based learning tool. This paper discusses the emerging issues, such as how can learning effectiveness be understood in relation to…

The effects of utilizing a near-patient e-learning tool on medical student learning.

PubMed

Selzer, Rob; Tallentire, Victoria R; Foley, Fiona

2015-01-01

This study aimed to develop a near-patient, e-learning tool and explore student views on how utilization of such a tool influenced their learning. Third year medical students from Monash University in Melbourne, Australia were invited to trial a novel, near-patient, e-learning tool in two separate pilots within the ward environment. All participating students were invited to contribute to focus groups which were audio-recorded, transcribed verbatim and thematically analyzed. Four focus groups were conducted with a total of 17 participants. The emerging themes revealed influences on the students' learning both prior to and during a clinical encounter, as well as following completion of an e-learning module. The unifying concept which linked all six themes and formed the central feature of the experience was patient-centered learning. This occurred through the acquisition of contextualized knowledge and the facilitation of workplace integration. Utilization of a near-patient e-learning tool influences medical student learning in a number of complex, inter-related ways. Clinical e-learning tools are poised to become more commonplace and provide many potential benefits to student learning. However, incorporation of technology into clinical encounters requires specific skills which should form an integral part of primary medical training.

Optimal water networks in protein cavities with GAsol and 3D-RISM.

PubMed

Fusani, Lucia; Wall, Ian; Palmer, David; Cortes, Alvaro

2018-06-01

Water molecules in protein binding sites play essential roles in biological processes. The popular 3D-RISM prediction method can calculate the solvent density distribution within minutes, but is difficult to convert it into explicit water molecules. We present GAsol, a tool that is capable of finding the network of water molecules that best fits a particular 3D-RISM density distribution in a fast and accurate manner and that outperforms other available tools by finding the globally optimal solution thanks to its genetic algorithm. https://github.com/accsc/GAsol. BSD 3-clauses license. alvaro.x.cortes@gsk.com. Supplementary data are available at Bioinformatics online.

jSquid: a Java applet for graphical on-line network exploration.

PubMed

Klammer, Martin; Roopra, Sanjit; Sonnhammer, Erik L L

2008-06-15

jSquid is a graph visualization tool for exploring graphs from protein-protein interaction or functional coupling networks. The tool was designed for the FunCoup web site, but can be used for any similar network exploring purpose. The program offers various visualization and graph manipulation techniques to increase the utility for the user. jSquid is available for direct usage and download at http://jSquid.sbc.su.se including source code under the GPLv3 license, and input examples. It requires Java version 5 or higher to run properly. erik.sonnhammer@sbc.su.se Supplementary data are available at Bioinformatics online.

Evaluation of the MSFC facsimile camera system as a tool for extraterrestrial geologic exploration

NASA Technical Reports Server (NTRS)

Wolfe, E. W.; Alderman, J. D.

1971-01-01

Utility of the Marshall Space Flight (MSFC) facsimile camera system for extraterrestrial geologic exploration was investigated during the spring of 1971 near Merriam Crater in northern Arizona. Although the system with its present hard-wired recorder operates erratically, the imagery showed that the camera could be developed as a prime imaging tool for automated missions. Its utility would be enhanced by development of computer techniques that utilize digital camera output for construction of topographic maps, and it needs increased resolution for examining near field details. A supplementary imaging system may be necessary for hand specimen examination at low magnification.

MetaABC--an integrated metagenomics platform for data adjustment, binning and clustering.

PubMed

Su, Chien-Hao; Hsu, Ming-Tsung; Wang, Tse-Yi; Chiang, Sufeng; Cheng, Jen-Hao; Weng, Francis C; Kao, Cheng-Yan; Wang, Daryi; Tsai, Huai-Kuang

2011-08-15

MetaABC is a metagenomic platform that integrates several binning tools coupled with methods for removing artifacts, analyzing unassigned reads and controlling sampling biases. It allows users to arrive at a better interpretation via series of distinct combinations of analysis tools. After execution, MetaABC provides outputs in various visual formats such as tables, pie and bar charts as well as clustering result diagrams. MetaABC source code and documentation are available at http://bits2.iis.sinica.edu.tw/MetaABC/ CONTACT: dywang@gate.sinica.edu.tw; hktsai@iis.sinica.edu.tw Supplementary data are available at Bioinformatics online.

KinLinks: Software Toolkit for Kinship Analysis and Pedigree Generation from NGS Datasets

DTIC Science & Technology

2015-04-21

Retinitis pigmentosa families 2110 and 2111 of 52 individuals across 6 generations (Figure 5a), and 54 geographically diverse samples (Supplementary Table...relationships within the Retinitis pigmentosa family. Machine Learning Classifier for pairwise kinship prediction Ten features were identified for training...family (Figure 4b), and the Retinitis pigmentosa family (Figure 5b). The auto-generated pedigrees were graphed as well as in family-tree format using

An Analysis of the Training and Development of the Contract Specialist 1102 Interns

DTIC Science & Technology

2010-12-01

get a broad view of contracting and interns are encouraged to join groups such as NCMA to help them with learning. The workforce development chiefs...NUMBER 11. SUPPLEMENTARY NOTES The views expressed in this thesis are those of the author and do not reflect the official policy or position of the...Center CECOM Communications Electronics Command CSRS Civil Service Retirement System DA Department of the Army DAPA Defense Acquisition

Not Again! 20th Century Hollow Force Lessons Learned for the 21st Century Military

DTIC Science & Technology

2011-06-17

capabilities in combat units . Although further research is required to determine the optimal balance between the Active and Reserve Component forces, a... UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT Joint Forces Staff College NUMBER Joint Advanced...SUPPLEMENTARY NOTES 14. ABSTRACT This paper investigates the problem of how United States Department of Defense (DoD) planners should organize the

The Effects of Seductive Details on Recognition Tests and Transfer Tasks

DTIC Science & Technology

2008-06-01

Mayer, R. E., Bove, W., Bryman , A ., Mars, R., & Tapangco, L. (1996). When less is more: Meaningful learning from visual and verbal summaries of textbook...unlimited. 20080709 276 U.S. Army Research Institute for the Behavioral and Social Sciences A Directorate of the Department of the Army Deputy Chief...unlimited. 13. SUPPLEMENTARY NOTES Contractor Officer’s Representative and Subject Matter POC: Dr. Paul A . Gade 14. ABSTRACT (Maximum 200 words): This

Auricular Therapy for Treatment of Musculoskeletal Pain in the Setting of Deployed Military Personnel: A Randomized Trial

DTIC Science & Technology

2016-12-01

unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Musculoskeletal injuries resulting in pain are one of the most common reasons for disability and missed...Musculoskeletal injuries resulting in pain are one of the most common reasons for disability and missed duty among military personnel. Preliminary research...activities, for the purpose of enhancing public understanding and increasing interest in learning and careers in science, technology, and the

Mediated learning in the workplace: student perspectives on knowledge resources.

PubMed

Shanahan, Madeleine

2015-01-01

In contemporary clinical practice, student radiographers can use many types of knowledge resources to support their learning. These include workplace experts, digital and nondigital information sources (eg, journals, textbooks, and the Internet), and electronic communication tools such as e-mail and social media. Despite the range of knowledge tools available, there is little available data about radiography students' use of these resources during clinical placement. A 68-item questionnaire was distributed to 62 students enrolled in an Australian university undergraduate radiography program after they completed a clinical placement. Researchers used descriptive statistics to analyze student access to workplace experts and their use of digital and nondigital information sources and electronic communication tools. A 5-point Likert scale (1 = very important; 5 = not important) was used to assess the present importance and perceived future value of knowledge tools for workplace learning. Of the 53 students who completed and returned the questionnaire anonymously, most rely on the knowledge of practicing technologists and on print and electronic information sources to support their learning; some students also use electronic communication tools. Students perceive that these knowledge resources also will be important tools for their future learning as qualified health professionals. The findings from this study present baseline data regarding the value students attribute to multiple knowledge tools and regarding student access to and use of these tools during clinical placement. In addition, most students have access to multiple knowledge tools in the workplace and incorporate these tools simultaneously into their overall learning practice during clinical placement. Although a range of knowledge tools is used in the workplace to support learning among student radiographers, the quality of each tool should be critically analyzed before it is adopted in practice. Integrating practice-based learning with learning mediated by information sources provides a more complete paradigm of learning during clinical placement.

[The Italian instrument evaluating the nursing students clinical learning quality].

PubMed

Palese, Alvisa; Grassetti, Luca; Mansutti, Irene; Destrebecq, Anne; Terzoni, Stefano; Altini, Pietro; Bevilacqua, Anita; Brugnolli, Anna; Benaglio, Carla; Dal Ponte, Adriana; De Biasio, Laura; Dimonte, Valerio; Gambacorti, Benedetta; Fasci, Adriana; Grosso, Silvia; Mantovan, Franco; Marognolli, Oliva; Montalti, Sandra; Nicotera, Raffaela; Randon, Giulia; Stampfl, Brigitte; Tollini, Morena; Canzan, Federica; Saiani, Luisa; Zannini, Lucia

2017-01-01

. The Clinical Learning Quality Evaluation Index for nursing students. The Italian nursing programs, the need to introduce tools evaluating the quality of the clinical learning as perceived by nursing students. Several tools already exist, however, several limitations suggesting the need to develop a new tool. A national project aimed at developing and validating a new instrument capable of measuring the clinical learning quality as experience by nursing students. A validation study design was undertaken from 2015 to 2016. All nursing national programs (n=43) were invited to participate by including all nursing students attending regularly their clinical learning. The tool developed based upon a) literature, b) validated tools already established among other healthcare professionals, and c) consensus expressed by experts and nursing students, was administered to the eligible students. 9606 nursing in 27 universities (62.8%) participated. The psychometric properties of the new instrument ranged from good to excellent. According to the findings, the tool consists in 22 items and five factors: a) quality of the tutorial strategies, b) learning opportunities; c) safety and nursing care quality; d) self-direct learning; e) quality of the learning environment. The tool is already used. Its systematic adoption may support comparison among settings and across different programs; moreover, the tool may also support in accrediting new settings as well as in measuring the effects of strategies aimed at improving the quality of the clinical learning.

[eLearning-radiology.com--sustainability for quality assurance].

PubMed

Ketelsen, D; Talanow, R; Uder, M; Grunewald, M

2009-04-01

The aim of the study was to analyze the availability of published radiological e-learning tools and to establish a solution for quality assurance. Substantial pubmed research was performed to identify radiological e-learning tools. 181 e-learning programs were selected. As examples two databases expanding their programs with external links, Compare (n = 435 external links) and TNT-Radiology (n = 1078 external links), were evaluated. A concept for quality assurance was developed by an international taskforce. At the time of assessment, 56.4 % (102 / 181) of the investigated e-learning tools were accessible at their original URL. A subgroup analysis of programs published 5 to 8 years ago showed significantly inferior availability to programs published 3 to 5 years ago (p < 0.01). The analysis of external links showed 49.2 % and 61.0 % accessible links for the programs Compare (published 2003) and TNT-Radiology (published 2006), respectively. As a consequence, the domain www.eLearning-radiology.com was developed by the taskforce and published online. This tool allows authors to present their programs and users to evaluate the e-learning tools depending on several criteria in order to remove inoperable links and to obtain information about the complexity and quality of the e-learning tools. More than 50 % of investigated radiological e-learning tools on the Internet were not accessible after a period of 5 to 8 years. As a consequence, an independent, international tool for quality assurance was designed and published online under www.eLearning-radiology.com .

PySCeSToolbox: a collection of metabolic pathway analysis tools.

PubMed

Christensen, Carl D; Hofmeyr, Jan-Hendrik S; Rohwer, Johann M

2018-01-01

PySCeSToolbox is an extension to the Python Simulator for Cellular Systems (PySCeS) that includes tools for performing generalized supply-demand analysis, symbolic metabolic control analysis, and a framework for investigating the kinetic and thermodynamic aspects of enzyme-catalyzed reactions. Each tool addresses a different aspect of metabolic behaviour, control, and regulation; the tools complement each other and can be used in conjunction to better understand higher level system behaviour. PySCeSToolbox is available on Linux, Mac OS X and Windows. It is licensed under the BSD 3-clause licence. Code, setup instructions and a link to documentation can be found at https://github.com/PySCeS/PyscesToolbox. jr@sun.ac.za. 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

PANDA-view: An easy-to-use tool for statistical analysis and visualization of quantitative proteomics data.

PubMed

Chang, Cheng; Xu, Kaikun; Guo, Chaoping; Wang, Jinxia; Yan, Qi; Zhang, Jian; He, Fuchu; Zhu, Yunping

2018-05-22

Compared with the numerous software tools developed for identification and quantification of -omics data, there remains a lack of suitable tools for both downstream analysis and data visualization. To help researchers better understand the biological meanings in their -omics data, we present an easy-to-use tool, named PANDA-view, for both statistical analysis and visualization of quantitative proteomics data and other -omics data. PANDA-view contains various kinds of analysis methods such as normalization, missing value imputation, statistical tests, clustering and principal component analysis, as well as the most commonly-used data visualization methods including an interactive volcano plot. Additionally, it provides user-friendly interfaces for protein-peptide-spectrum representation of the quantitative proteomics data. PANDA-view is freely available at https://sourceforge.net/projects/panda-view/. 1987ccpacer@163.com and zhuyunping@gmail.com. Supplementary data are available at Bioinformatics online.

Make Gestures to Learn: Reproducing Gestures Improves the Learning of Anatomical Knowledge More than Just Seeing Gestures

PubMed Central

Cherdieu, Mélaine; Palombi, Olivier; Gerber, Silvain; Troccaz, Jocelyne; Rochet-Capellan, Amélie

2017-01-01

Manual gestures can facilitate problem solving but also language or conceptual learning. Both seeing and making the gestures during learning seem to be beneficial. However, the stronger activation of the motor system in the second case should provide supplementary cues to consolidate and re-enact the mental traces created during learning. We tested this hypothesis in the context of anatomy learning by naïve adult participants. Anatomy is a challenging topic to learn and is of specific interest for research on embodied learning, as the learning content can be directly linked to learners' body. Two groups of participants were asked to look at a video lecture on the forearm anatomy. The video included a model making gestures related to the content of the lecture. Both groups see the gestures but only one also imitate the model. Tests of knowledge were run just after learning and few days later. The results revealed that imitating gestures improves the recall of structures names and their localization on a diagram. This effect was however significant only in long-term assessments. This suggests that: (1) the integration of motor actions and knowledge may require sleep; (2) a specific activation of the motor system during learning may improve the consolidation and/or the retrieval of memories. PMID:29062287

Board and card games for studying electrochemistry: Preliminary research and early design

NASA Astrophysics Data System (ADS)

Kurniawan, Rizmahardian Ashari; Kurniasih, Dedeh; Jukardi

2017-12-01

Games in the chemistry classroom can offer engaging and fun alternative method of learning. However, only a few games in chemistry, especially in electrochemistry subject are available commercially. In this research, we developed board and card games for studying electrochemistry. We surveyed chemistry teacher and students from 10 different senior high schools in Pontianak to decide content and characteristic of the game. We have designed the game that can be played by four students or four group of students, either as a specific instruction in the classroom or as a supplementary learning material. The game was designed to help students understanding the voltaic cell configuration and its voltaic potential.

The Implications of Cognitive Psychology for Computer-Based Learning Tools.

ERIC Educational Resources Information Center

Kozma, Robert B.

1987-01-01

Defines cognitive computer tools as software programs that use the control capabilities of computers to amplify, extend, or enhance human cognition; suggests seven ways in which computers can aid learning; and describes the "Learning Tool," a software package for the Apple Macintosh microcomputer that is designed to aid learning of…

Open Source for Knowledge and Learning Management: Strategies beyond Tools

ERIC Educational Resources Information Center

Lytras, Miltiadis, Ed.; Naeve, Ambjorn, Ed.

2007-01-01

In the last years, knowledge and learning management have made a significant impact on the IT research community. "Open Source for Knowledge and Learning Management: Strategies Beyond Tools" presents learning and knowledge management from a point of view where the basic tools and applications are provided by open source technologies.…

User Studies: Developing Learning Strategy Tool Software for Children.

ERIC Educational Resources Information Center

Fitzgerald, Gail E.; Koury, Kevin A.; Peng, Hsinyi

This paper is a report of user studies for developing learning strategy tool software for children. The prototype software demonstrated is designed for children with learning and behavioral disabilities. The tools consist of easy-to-use templates for creating organizational, memory, and learning approach guides for use in classrooms and at home.…

Factors Influencing Beliefs for Adoption of a Learning Analytics Tool: An Empirical Study

ERIC Educational Resources Information Center

Ali, Liaqat; Asadi, Mohsen; Gasevic, Dragan; Jovanovic, Jelena; Hatala, Marek

2013-01-01

Present research and development offer various learning analytics tools providing insights into different aspects of learning processes. Adoption of a specific tool for practice is based on how its learning analytics are perceived by educators to support their pedagogical and organizational goals. In this paper, we propose and empirically validate…

Textbook-Bundled Metacognitive Tools: A Study of LearnSmart's Efficacy in General Chemistry

ERIC Educational Resources Information Center

Thadani, Vandana; Bouvier-Brown, Nicole C.

2016-01-01

College textbook publishers increasingly bundle sophisticated technology-based study tools with their texts. These tools appear promising, but empirical work on their efficacy is needed. We examined whether LearnSmart, a study tool bundled with McGraw-Hill's textbook "Chemistry" (Chang & Goldsby, 2013), improved learning in an…

Improving Organizational Learning: Defining Units of Learning from Social Tools

ERIC Educational Resources Information Center

Menolli, André Luís Andrade; Reinehr, Sheila; Malucelli, Andreia

2013-01-01

New technologies, such as social networks, wikis, blogs and other social tools, enable collaborative work and are important facilitators of the social learning process. Many companies are using these types of tools as substitutes for their intranets, especially software development companies. However, the content generated by these tools in many…

Supplementary physicians' fees: a sustainable system?

PubMed

Calcoen, Piet; van de Ven, Wynand P M M

2018-01-25

In Belgium and France, physicians can charge a supplementary fee on top of the tariff set by the mandatory basic health insurance scheme. In both countries, the supplementary fee system is under pressure because of financial sustainability concerns and a lack of added value for the patient. Expenditure on supplementary fees is increasing much faster than total health expenditure. So far, measures taken to curb this trend have not been successful. For certain categories of physicians, supplementary fees represent one-third of total income. For patients, however, the added value of supplementary fees is not that clear. Supplementary fees can buy comfort and access to physicians who refuse to treat patients who are not willing to pay supplementary fees. Perceived quality of care plays an important role in patients' willingness to pay supplementary fees. Today, there is no evidence that physicians who charge supplementary fees provide better quality of care than physicians who do not. However, linking supplementary fees to objectively proven quality of care and limiting access to top quality care to patients able and willing to pay supplementary fees might not be socially acceptable in many countries. Our conclusion is that supplementary physicians' fees are not sustainable.

Hybrid E-Learning Tool TransLearning: Video Storytelling to Foster Vicarious Learning within Multi-Stakeholder Collaboration Networks

ERIC Educational Resources Information Center

van der Meij, Marjoleine G.; Kupper, Frank; Beers, Pieter J.; Broerse, Jacqueline E. W.

2016-01-01

E-learning and storytelling approaches can support informal vicarious learning within geographically widely distributed multi-stakeholder collaboration networks. This case study evaluates hybrid e-learning and video-storytelling approach "TransLearning" by investigation into how its storytelling e-tool supported informal vicarious…

Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance tool.

PubMed

Auerbach, Raymond K; Chen, Bin; Butte, Atul J

2013-08-01

Biological analysis has shifted from identifying genes and transcripts to mapping these genes and transcripts to biological functions. The ENCODE Project has generated hundreds of ChIP-Seq experiments spanning multiple transcription factors and cell lines for public use, but tools for a biomedical scientist to analyze these data are either non-existent or tailored to narrow biological questions. We present the ENCODE ChIP-Seq Significance Tool, a flexible web application leveraging public ENCODE data to identify enriched transcription factors in a gene or transcript list for comparative analyses. The ENCODE ChIP-Seq Significance Tool is written in JavaScript on the client side and has been tested on Google Chrome, Apple Safari and Mozilla Firefox browsers. Server-side scripts are written in PHP and leverage R and a MySQL database. The tool is available at http://encodeqt.stanford.edu. abutte@stanford.edu Supplementary material is available at Bioinformatics online.

Developing a Tool to Measure the Impact of E-Learning on the Teachers of Higher Education

ERIC Educational Resources Information Center

Kumar, M. Rajesh; Kumar, R. Krishna

2008-01-01

The trend of using e-learning as a teaching tool is now rapidly expanding into education. Although e-learning environments are becoming popular there is minimal research on the impact of e-learning on the teachers. The purpose of this study is to develop a tool to measure the impact of e-learning on the teachers' of higher education in the Indian…

The Challenge of Access: Using Road Construction as a Tool in Counterinsurgency

DTIC Science & Technology

2011-06-10

northward, as shown in figure 9. Built by the United States in the 1950s, the dam and its downstream channels provide water for irrigation across the...12. DISTRIBUTION / AVAILABILITY STATEMENT Approved for Public Release; Distribution is Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT This...consolidated Russian control. It also brought Russia closer to an overriding strategic objective, the procurement of a warm water port from which to project

Understanding Social Media and Mass Mobilization in the Operational Environment

DTIC Science & Technology

2015-05-21

Word of mouth became the main tool for planning the next steps, confirmed Saif. Demonstrators at Tahrir agreed before they left to convene the next day...environment. Whereas large groups had to rely on information distributed in the group through word of mouth in the past, modern mass mobilization uses social...Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The advent of social media combined with unfettered access to inexpensive mobile electronic devices has

The Asset-Based Context Matrix: A Tool for Assessing Children's Learning Opportunities and Participation in Natural Environments

ERIC Educational Resources Information Center

Wilson, Linda L.; Mott, Donald W.; Batman, Deb

2004-01-01

This article provides a description of the "Asset-Based Context Matrix" (ABC Matrix). The ABC Matrix is an assessment tool for designing interventions for children in natural learning environments. The tool is based on research evidence indicating that children's learning is enhanced in contextually meaningful learning environments. The ABC Matrix…

A State for Excellence: New Jersey Boosts Learning Power with Online Video Resources

ERIC Educational Resources Information Center

Duff, Victoria; Sauer, Wendy; Gleason, Sonia Caus

2011-01-01

The New Jersey Department of Education supports all districts with a tool kit of valuable resources for planning and creating collaborative learning structures that focus on getting results for all students. This tool kit was the basis for the creation of Learning Forward's "Becoming a Learning School" (2009). The tool kit helps…

iSELF: The Development of an Internet-Tool for Self-Evaluation and Learner Feedback

ERIC Educational Resources Information Center

Theunissen, Nicolet; Stubbé, Hester

2014-01-01

This paper describes the theoretical basis and development of the iSELF: an Internet-tool for Self-Evaluation and Learner Feedback to stimulate self-directed learning in ubiquitous learning environments. In ubiquitous learning, learners follow their own trails of interest, scaffolded by coaches, peers and tools for thinking and learning.…

Developing an Intelligent Diagnosis and Assessment E-Learning Tool for Introductory Programming

ERIC Educational Resources Information Center

Huang, Chenn-Jung; Chen, Chun-Hua; Luo, Yun-Cheng; Chen, Hong-Xin; Chuang, Yi-Ta

2008-01-01

Recently, a lot of open source e-learning platforms have been offered for free in the Internet. We thus incorporate the intelligent diagnosis and assessment tool into an open software e-learning platform developed for programming language courses, wherein the proposed learning diagnosis assessment tools based on text mining and machine learning…

On Recommending Web 2.0 Tools to Personalise Learning

ERIC Educational Resources Information Center

Juškeviciene, Anita; Kurilovas, Eugenijus

2014-01-01

The paper aims to present research results on using Web 2.0 tools for learning personalisation. In the work, personalised Web 2.0 tools selection method is presented. This method takes into account student's learning preferences for content and communication modes tailored to the learning activities with a view to help the learner to quickly and…

Academic perceptions amongst educators towards eLearning tools in dental education.

PubMed

Handal, Boris; Groenlund, Catherine; Gerzina, Tania

2011-04-01

This paper reports an explorative study about academic educators' perceptions towards learning management systems (LMS) and eLearning tools as used in dental education. Fifty-five educators participated in an online survey which explored their views on eLearning tools within the context of their own professional training background and teaching needs. In general, educators felt that the eLearning LMS (also known as WebCT/Blackboard) was a tool that suited their teaching and learning needs in terms of flexibility, interactivity and accessibility despite a significant level of self-reported lack of competence in the technology. The paper describes current eLearning professional development initiatives in light of these findings. © 2011 FDI World Dental Federation.

Fast metabolite identification with Input Output Kernel Regression

PubMed Central

Brouard, Céline; Shen, Huibin; Dührkop, Kai; d'Alché-Buc, Florence; Böcker, Sebastian; Rousu, Juho

2016-01-01

Motivation: An important problematic of metabolomics is to identify metabolites using tandem mass spectrometry data. Machine learning methods have been proposed recently to solve this problem by predicting molecular fingerprint vectors and matching these fingerprints against existing molecular structure databases. In this work we propose to address the metabolite identification problem using a structured output prediction approach. This type of approach is not limited to vector output space and can handle structured output space such as the molecule space. Results: We use the Input Output Kernel Regression method to learn the mapping between tandem mass spectra and molecular structures. The principle of this method is to encode the similarities in the input (spectra) space and the similarities in the output (molecule) space using two kernel functions. This method approximates the spectra-molecule mapping in two phases. The first phase corresponds to a regression problem from the input space to the feature space associated to the output kernel. The second phase is a preimage problem, consisting in mapping back the predicted output feature vectors to the molecule space. We show that our approach achieves state-of-the-art accuracy in metabolite identification. Moreover, our method has the advantage of decreasing the running times for the training step and the test step by several orders of magnitude over the preceding methods. Availability and implementation: Contact: celine.brouard@aalto.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307628

Introducing New Learning Tools into a Standard Classroom: A Multi-Tool Approach to Integrating Fuel-Cell Concepts into Introductory College Chemistry

ERIC Educational Resources Information Center

D'Amato, Matthew J.; Lux, Kenneth W.; Walz, Kenneth A.; Kerby, Holly Walter; Anderegg, Barbara

2007-01-01

A multi-tool approach incorporating traditional lectures, multimedia learning objects, and a laboratory activity were introduced as the concepts surrounding hydrogen fuel-cell technology in college chemistry courses. The new tools are adaptable, facilitating use in different educational environments and address variety of learning styles to…

MEAT: An Authoring Tool for Generating Adaptable Learning Resources

ERIC Educational Resources Information Center

Kuo, Yen-Hung; Huang, Yueh-Min

2009-01-01

Mobile learning (m-learning) is a new trend in the e-learning field. The learning services in m-learning environments are supported by fundamental functions, especially the content and assessment services, which need an authoring tool to rapidly generate adaptable learning resources. To fulfill the imperious demand, this study proposes an…

Digital interactive learning of oral radiographic anatomy.

PubMed

Vuchkova, J; Maybury, T; Farah, C S

2012-02-01

Studies reporting high number of diagnostic errors made from radiographs suggest the need to improve the learning of radiographic interpretation in the dental curriculum. Given studies that show student preference for computer-assisted or digital technologies, the purpose of this study was to develop an interactive digital tool and to determine whether it was more successful than a conventional radiology textbook in assisting dental students with the learning of radiographic anatomy. Eighty-eight dental students underwent a learning phase of radiographic anatomy using an interactive digital tool alongside a conventional radiology textbook. The success of the digital tool, when compared to the textbook, was assessed by quantitative means using a radiographic interpretation test and by qualitative means using a structured Likert scale survey, asking students to evaluate their own learning outcomes from the digital tool. Student evaluations of the digital tool showed that almost all participants (95%) indicated that the tool positively enhanced their learning of radiographic anatomy and interpretation. The success of the digital tool in assisting the learning of radiographic interpretation is discussed in the broader context of learning and teaching curricula, and preference (by students) for the use of this digital form when compared to the conventional literate form of the textbook. Whilst traditional textbooks are still valued in the dental curriculum, it is evident that the preference for computer-assisted learning of oral radiographic anatomy enhances the learning experience by enabling students to interact and better engage with the course material. © 2011 John Wiley & Sons A/S.

A rapid review of serious games: From healthcare education to dental education.

PubMed

Sipiyaruk, K; Gallagher, J E; Hatzipanagos, S; Reynolds, P A

2018-03-24

Games involving technology have the potential to enhance hand-eye coordination and decision-making skills. As a result, game characteristics have been applied to education and training, where they are known as serious games. There is an increase in the volume of literature on serious games in healthcare education; however, evidence on their impact is still ambiguous. The aims of this study were (i) to identify high-quality evidence (systematic reviews or meta-analyses) regarding impacts of serious games on healthcare education; and (ii) to explore evidence regarding impacts of serious games in dental education. A rapid review of the literature was undertaken to synthesise available evidence and examine serious games in healthcare education (Stage 1) and dental education (Stage 2). Nine systematic reviews were included in Stage 1, four of which were of high, three of moderate and two of low quality. For Stage 2, two randomised control trials with moderate quality were included. The findings demonstrated that serious games are potentially effective learning tools in terms of knowledge and skills improvement, although outcomes of serious games over traditional learning approaches were not consistent. In addition, serious games appeared to be more engaging and satisfying for students, which could be considered as the most important positive impact. Serious games provide an option for healthcare and dental education but remain underutilised and researched. At best, they offer a similar experience to other methods in relation to educational outcome; however, they can provide a supplementary strategy to engage students and improve learner satisfaction. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A Non-science Major Undergraduate Seminar on the NASA Earth Observing System (EOS): A Student Perspective

NASA Astrophysics Data System (ADS)

Weatherford, V. L.; Redemann, J.

2003-12-01

Titled "Observing Climate Change From Space-what tools do we have?", this non-science major freshman seminar at UCLA is the culmination of a year-long interdisciplinary program sponsored by the Institute of the Environment and the College Honors programs at the University. Focusing on the anthropogenic and natural causes of climate change, students study climate forcings and learn about satellite and other technological means of monitoring climate and weather. NASA's Terra satellite is highlighted as one of the most recent and comprehensive monitoring systems put into space and the role of future NASA platforms in the "A-train"-constellation of satellites is discussed. Course material is typically presented in a Power-Point presentation by the instructor, with assigned supplementary reading to stimulate class discussion. In addition to preparing lectures for class presentation, students work on a final term paper and oral presentation which constitutes the majority of their grade. Field trips to the San Gabriel mountains to take atmospheric measurements with handheld sunphotometers and to JPL, Pasadena (CA) to listen to a NASA scientist discuss the MISR instrument aboard the Terra satellite help bring a real-world perspective to the science learned in the classroom. In this paper, we will describe the objectives and structure of this class and present measurement results taken during the field trip to the San Gabriel Mountains. In this context we will discuss the potential relevance of hands-on experience to meeting class objectives and give a student perspective of the overall class experience.

Developing 21st century skills through the use of student personal learning networks

NASA Astrophysics Data System (ADS)

Miller, Robert D.

This research was conducted to study the development of 21st century communication, collaboration, and digital literacy skills of students at the high school level through the use of online social network tools. The importance of this study was based on evidence high school and college students are not graduating with the requisite skills of communication, collaboration, and digital literacy skills yet employers see these skills important to the success of their employees. The challenge addressed through this study was how high schools can integrate social network tools into traditional learning environments to foster the development of these 21st century skills. A qualitative research study was completed through the use of case study. One high school class in a suburban high performing town in Connecticut was selected as the research site and the sample population of eleven student participants engaged in two sets of interviews and learned through the use social network tools for one semester of the school year. The primary social network tools used were Facebook, Diigo, Google Sites, Google Docs, and Twitter. The data collected and analyzed partially supported the transfer of the theory of connectivism at the high school level. The students actively engaged in collaborative learning and research. Key results indicated a heightened engagement in learning, the development of collaborative learning and research skills, and a greater understanding of how to use social network tools for effective public communication. The use of social network tools with high school students was a positive experience that led to an increased awareness of the students as to the benefits social network tools have as a learning tool. The data supported the continued use of social network tools to develop 21st century communication, collaboration, and digital literacy skills. Future research in this area may explore emerging social network tools as well as the long term impact these tools have on the development of lifelong learning skills and quantitative data linked to student learning.

Introducing an Avatar Acceptance Model: Student Intention to Use 3D Immersive Learning Tools in an Online Learning Classroom

ERIC Educational Resources Information Center

Kemp, Jeremy William

2011-01-01

This quantitative survey study examines the willingness of online students to adopt an immersive virtual environment as a classroom tool and compares this with their feelings about more traditional learning modes including our ANGEL learning management system and the Elluminate live Web conferencing tool. I surveyed 1,108 graduate students in…

Development and Evaluation of a Case-Based Digital Learning Tool about Children's Mathematical Thinking for Elementary School Teachers (L-TEST)

ERIC Educational Resources Information Center

Olkun, Sinan; Altun, Arif; Deryakulu, Deniz

2009-01-01

It is important for teachers of mathematics to know how pupils react to certain mathematical situations and what these reactions imply, in order to design more effective instructional environments based on their learning needs. This study reports the development processes of a digital learning tool (Learning Tool for Elementary School Teachers…

Integration of Web 2.0 Tools in Learning a Programming Course

ERIC Educational Resources Information Center

Majid, Nazatul Aini Abd

2014-01-01

Web 2.0 tools are expected to assist students to acquire knowledge effectively in their university environment. However, the lack of effort from lecturers in planning the learning process can make it difficult for the students to optimize their learning experiences. The aim of this paper is to integrate Web 2.0 tools with learning strategy in…

Computer Assisted Learning for Biomedical Engineering Education: Tools

DTIC Science & Technology

2001-10-25

COMPUTER ASSISTED LEARNING FOR BIOMEDICAL ENGINEERING EDUCATION : TOOLS Ayhan ÝSTANBULLU1 Ýnan GÜLER2 1 Department of Electronic...of Technical Education , Gazi University, 06500 Ankara, Türkiye Abstract- Interactive multimedia learning environment is being proposed...Assisted Learning (CAL) are given and some tools used in this area are explained. Together with the developments in the area of distance education

Showing Up Is Half the Battle: Assessing Different Contextualized Learning Tools to Increase the Performance in Introductory Computer Science Courses

ERIC Educational Resources Information Center

Rolka, Christine; Remshagen, Anja

2015-01-01

Contextualized learning is considered beneficial for student success. In this article, we assess the impact of context-based learning tools on student grade performance in an introductory computer science course. In particular, we investigate two central questions: (1) does the use context-based learning tools, robots and animations, affect…

GRAM-CNN: a deep learning approach with local context for named entity recognition in biomedical text

PubMed Central

Zhu, Qile; Li, Xiaolin; Conesa, Ana; Pereira, Cécile

2018-01-01

Abstract Motivation Best performing named entity recognition (NER) methods for biomedical literature are based on hand-crafted features or task-specific rules, which are costly to produce and difficult to generalize to other corpora. End-to-end neural networks achieve state-of-the-art performance without hand-crafted features and task-specific knowledge in non-biomedical NER tasks. However, in the biomedical domain, using the same architecture does not yield competitive performance compared with conventional machine learning models. Results We propose a novel end-to-end deep learning approach for biomedical NER tasks that leverages the local contexts based on n-gram character and word embeddings via Convolutional Neural Network (CNN). We call this approach GRAM-CNN. To automatically label a word, this method uses the local information around a word. Therefore, the GRAM-CNN method does not require any specific knowledge or feature engineering and can be theoretically applied to a wide range of existing NER problems. The GRAM-CNN approach was evaluated on three well-known biomedical datasets containing different BioNER entities. It obtained an F1-score of 87.26% on the Biocreative II dataset, 87.26% on the NCBI dataset and 72.57% on the JNLPBA dataset. Those results put GRAM-CNN in the lead of the biological NER methods. To the best of our knowledge, we are the first to apply CNN based structures to BioNER problems. Availability and implementation The GRAM-CNN source code, datasets and pre-trained model are available online at: https://github.com/valdersoul/GRAM-CNN. Contact andyli@ece.ufl.edu or aconesa@ufl.edu Supplementary information Supplementary data are available at Bioinformatics online. PMID:29272325

Knowledge Retention after an Online Tutorial: A Randomized Educational Experiment among Resident Physicians

PubMed Central

Harless, Charles E.; Higa, Jerilyn K.; Bjork, Elizabeth L.; Bjork, Robert A.; Bazargan, Mohsen; Mangione, Carol M.

2008-01-01

BACKGROUND The time course of physicians’ knowledge retention after learning activities has not been well characterized. Understanding the time course of retention is critical to optimizing the reinforcement of knowledge. DESIGN Educational follow-up experiment with knowledge retention measured at 1 of 6 randomly assigned time intervals (0–55 days) after an online tutorial covering 2 American Diabetes Association guidelines. PARTICIPANTS Internal and family medicine residents. MEASUREMENTS Multiple-choice knowledge tests, subject characteristics including critical appraisal skills, and learner satisfaction. RESULTS Of 197 residents invited, 91 (46%) completed the tutorial and were randomized; of these, 87 (96%) provided complete follow-up data. Ninety-two percent of the subjects rated the tutorial as “very good” or “excellent.” Mean knowledge scores increased from 50% before the tutorial to 76% among those tested immediately afterward. Score gains were only half as great at 3–8 days and no significant retention was measurable at 55 days. The shape of the retention curve corresponded with a 1/4-power transformation of the delay interval. In multivariate analyses, critical appraisal skills and participant age were associated with greater initial learning, but no participant characteristic significantly modified the rate of decline in retention. CONCLUSIONS Education that appears successful from immediate posttests and learner evaluations can result in knowledge that is mostly lost to recall over the ensuing days and weeks. To achieve longer-term retention, physicians should review or otherwise reinforce new learning after as little as 1 week. Electronic supplementary material The online version of this article (doi:10.1007/s11606-008-0604-2) contains supplementary material, which is available to authorized users. PMID:18446414

What time is it? Deep learning approaches for circadian rhythms

PubMed Central

Agostinelli, Forest; Ceglia, Nicholas; Shahbaba, Babak; Sassone-Corsi, Paolo; Baldi, Pierre

2016-01-01

Motivation: Circadian rhythms date back to the origins of life, are found in virtually every species and every cell, and play fundamental roles in functions ranging from metabolism to cognition. Modern high-throughput technologies allow the measurement of concentrations of transcripts, metabolites and other species along the circadian cycle creating novel computational challenges and opportunities, including the problems of inferring whether a given species oscillate in circadian fashion or not, and inferring the time at which a set of measurements was taken. Results: We first curate several large synthetic and biological time series datasets containing labels for both periodic and aperiodic signals. We then use deep learning methods to develop and train BIO_CYCLE, a system to robustly estimate which signals are periodic in high-throughput circadian experiments, producing estimates of amplitudes, periods, phases, as well as several statistical significance measures. Using the curated data, BIO_CYCLE is compared to other approaches and shown to achieve state-of-the-art performance across multiple metrics. We then use deep learning methods to develop and train BIO_CLOCK to robustly estimate the time at which a particular single-time-point transcriptomic experiment was carried. In most cases, BIO_CLOCK can reliably predict time, within approximately 1 h, using the expression levels of only a small number of core clock genes. BIO_CLOCK is shown to work reasonably well across tissue types, and often with only small degradation across conditions. BIO_CLOCK is used to annotate most mouse experiments found in the GEO database with an inferred time stamp. Availability and Implementation: All data and software are publicly available on the CircadiOmics web portal: circadiomics.igb.uci.edu/. Contacts: fagostin@uci.edu or pfbaldi@uci.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307647

Deconvolving molecular signatures of interactions between microbial colonies

PubMed Central

Harn, Y.-C.; Powers, M. J.; Shank, E. A.; Jojic, V.

2015-01-01

Motivation: The interactions between microbial colonies through chemical signaling are not well understood. A microbial colony can use different molecules to inhibit or accelerate the growth of other colonies. A better understanding of the molecules involved in these interactions could lead to advancements in health and medicine. Imaging mass spectrometry (IMS) applied to co-cultured microbial communities aims to capture the spatial characteristics of the colonies’ molecular fingerprints. These data are high-dimensional and require computational analysis methods to interpret. Results: Here, we present a dictionary learning method that deconvolves spectra of different molecules from IMS data. We call this method MOLecular Dictionary Learning (MOLDL). Unlike standard dictionary learning methods which assume Gaussian-distributed data, our method uses the Poisson distribution to capture the count nature of the mass spectrometry data. Also, our method incorporates universally applicable information on common ion types of molecules in MALDI mass spectrometry. This greatly reduces model parameterization and increases deconvolution accuracy by eliminating spurious solutions. Moreover, our method leverages the spatial nature of IMS data by assuming that nearby locations share similar abundances, thus avoiding overfitting to noise. Tests on simulated datasets show that this method has good performance in recovering molecule dictionaries. We also tested our method on real data measured on a microbial community composed of two species. We confirmed through follow-up validation experiments that our method recovered true and complete signatures of molecules. These results indicate that our method can discover molecules in IMS data reliably, and hence can help advance the study of interaction of microbial colonies. Availability and implementation: The code used in this paper is available at: https://github.com/frizfealer/IMS_project. Contact: vjojic@cs.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26072476

"Development Radar": The Co-Configuration of a Tool in a Learning Network

ERIC Educational Resources Information Center

Toiviainen, Hanna; Kerosuo, Hannele; Syrjala, Tuula

2009-01-01

Purpose: The paper aims to argue that new tools are needed for operating, developing and learning in work-life networks where academic and practice knowledge are intertwined in multiple levels of and in boundary-crossing across activities. At best, tools for learning are designed in a process of co-configuration, as the analysis of one tool,…

The implementation of e-learning tools to enhance undergraduate bioinformatics teaching and learning: a case study in the National University of Singapore

PubMed Central

2009-01-01

Background The rapid advancement of computer and information technology in recent years has resulted in the rise of e-learning technologies to enhance and complement traditional classroom teaching in many fields, including bioinformatics. This paper records the experience of implementing e-learning technology to support problem-based learning (PBL) in the teaching of two undergraduate bioinformatics classes in the National University of Singapore. Results Survey results further established the efficiency and suitability of e-learning tools to supplement PBL in bioinformatics education. 63.16% of year three bioinformatics students showed a positive response regarding the usefulness of the Learning Activity Management System (LAMS) e-learning tool in guiding the learning and discussion process involved in PBL and in enhancing the learning experience by breaking down PBL activities into a sequential workflow. On the other hand, 89.81% of year two bioinformatics students indicated that their revision process was positively impacted with the use of LAMS for guiding the learning process, while 60.19% agreed that the breakdown of activities into a sequential step-by-step workflow by LAMS enhances the learning experience Conclusion We show that e-learning tools are useful for supplementing PBL in bioinformatics education. The results suggest that it is feasible to develop and adopt e-learning tools to supplement a variety of instructional strategies in the future. PMID:19958511

Efficient analysis of large-scale genome-wide data with two R packages: bigstatsr and bigsnpr.

PubMed

Privé, Florian; Aschard, Hugues; Ziyatdinov, Andrey; Blum, Michael G B

2017-03-30

Genome-wide datasets produced for association studies have dramatically increased in size over the past few years, with modern datasets commonly including millions of variants measured in dozens of thousands of individuals. This increase in data size is a major challenge severely slowing down genomic analyses, leading to some software becoming obsolete and researchers having limited access to diverse analysis tools. Here we present two R packages, bigstatsr and bigsnpr, allowing for the analysis of large scale genomic data to be performed within R. To address large data size, the packages use memory-mapping for accessing data matrices stored on disk instead of in RAM. To perform data pre-processing and data analysis, the packages integrate most of the tools that are commonly used, either through transparent system calls to existing software, or through updated or improved implementation of existing methods. In particular, the packages implement fast and accurate computations of principal component analysis and association studies, functions to remove SNPs in linkage disequilibrium and algorithms to learn polygenic risk scores on millions of SNPs. We illustrate applications of the two R packages by analyzing a case-control genomic dataset for celiac disease, performing an association study and computing Polygenic Risk Scores. Finally, we demonstrate the scalability of the R packages by analyzing a simulated genome-wide dataset including 500,000 individuals and 1 million markers on a single desktop computer. https://privefl.github.io/bigstatsr/ & https://privefl.github.io/bigsnpr/. florian.prive@univ-grenoble-alpes.fr & michael.blum@univ-grenoble-alpes.fr. Supplementary materials are available at Bioinformatics online.

Language experience differentiates prefrontal and subcortical activation of the cognitive control network in novel word learning.

PubMed

Bradley, Kailyn A L; King, Kelly E; Hernandez, Arturo E

2013-02-15

The purpose of this study was to examine the cognitive control mechanisms in adult English speaking monolinguals compared to early sequential Spanish-English bilinguals during the initial stages of novel word learning. Functional magnetic resonance imaging during a lexico-semantic task after only 2h of exposure to novel German vocabulary flashcards showed that monolinguals activated a broader set of cortical control regions associated with higher-level cognitive processes, including the supplementary motor area (SMA), anterior cingulate (ACC), and dorsolateral prefrontal cortex (DLPFC), as well as the caudate, implicated in cognitive control of language. However, bilinguals recruited a more localized subcortical network that included the putamen, associated more with motor control of language. These results suggest that experience managing multiple languages may differentiate the learning strategy and subsequent neural mechanisms of cognitive control used by bilinguals compared to monolinguals in the early stages of novel word learning. Copyright © 2012 Elsevier Inc. All rights reserved.

[The age of Gutenberg is over: a consideration of medical education--past, present and future].

PubMed

Burg, G; French, L E

2012-04-01

Education is the basis for reliable medical care and medical progress. Our medical knowledge has increased more in the past 50 years than in the 500 years before. The spatial and human resource capacity of our universities cannot cope with the existing academic structures and needs. Part of the problem can be solved by "blended learning", that is a combination of traditional teaching methods (frontal lectures, courses, bedside teaching) with supplementary web-based e-learning. In addition to conveying a sound basic knowledge, the ability to cope with modern media and prepare for lifelong learning must also be taught. Out of the large number of e-learning platforms for undergraduate students offered in the internet, we present the program DOIT (Dermatology Online with Interactive Technology; http://www.swisdom.org) and the program Dermokrates (http://www.Dermokrates.com) of the German, Austrian and Swiss Dermatological Societies for postgraduate Continuing Medical Education (CME). The biggest obstacle in the implementation of new developments is the stubborn adherence to traditional structures.

TomoEED: Fast Edge-Enhancing Denoising of Tomographic Volumes.

PubMed

Moreno, J J; Martínez-Sánchez, A; Martínez, J A; Garzón, E M; Fernández, J J

2018-05-29

TomoEED is an optimized software tool for fast feature-preserving noise filtering of large 3D tomographic volumes on CPUs and GPUs. The tool is based on the anisotropic nonlinear diffusion method. It has been developed with special emphasis in the reduction of the computational demands by using different strategies, from the algorithmic to the high performance computing perspectives. TomoEED manages to filter large volumes in a matter of minutes in standard computers. TomoEED has been developed in C. It is available for Linux platforms at http://www.cnb.csic.es/%7ejjfernandez/tomoeed. gmartin@ual.es, JJ.Fernandez@csic.es. Supplementary data are available at Bioinformatics online.

GAPIT: genome association and prediction integrated tool.

PubMed

Lipka, Alexander E; Tian, Feng; Wang, Qishan; Peiffer, Jason; Li, Meng; Bradbury, Peter J; Gore, Michael A; Buckler, Edward S; Zhang, Zhiwu

2012-09-15

Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. http://www.maizegenetics.net/GAPIT. zhiwu.zhang@cornell.edu Supplementary data are available at Bioinformatics online.

rnaQUAST: a quality assessment tool for de novo transcriptome assemblies.

PubMed

Bushmanova, Elena; Antipov, Dmitry; Lapidus, Alla; Suvorov, Vladimir; Prjibelski, Andrey D

2016-07-15

Ability to generate large RNA-Seq datasets created a demand for both de novo and reference-based transcriptome assemblers. However, while many transcriptome assemblers are now available, there is still no unified quality assessment tool for RNA-Seq assemblies. We present rnaQUAST-a tool for evaluating RNA-Seq assembly quality and benchmarking transcriptome assemblers using reference genome and gene database. rnaQUAST calculates various metrics that demonstrate completeness and correctness levels of the assembled transcripts, and outputs them in a user-friendly report. rnaQUAST is implemented in Python and is freely available at http://bioinf.spbau.ru/en/rnaquast ap@bioinf.spbau.ru Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

RxnSim: a tool to compare biochemical reactions.

PubMed

Giri, Varun; Sivakumar, Tadi Venkata; Cho, Kwang Myung; Kim, Tae Yong; Bhaduri, Anirban

2015-11-15

: Quantitative assessment of chemical reaction similarity aids database searches, classification of reactions and identification of candidate enzymes. Most methods evaluate reaction similarity based on chemical transformation patterns. We describe a tool, RxnSim, which computes reaction similarity based on the molecular signatures of participating molecules. The tool is able to compare reactions based on similarities of substrates and products in addition to their transformation. It allows masking of user-defined chemical moieties for weighted similarity computations. RxnSim is implemented in R and is freely available from the Comprehensive R Archive Network, CRAN (http://cran.r-project.org/web/packages/RxnSim/). anirban.b@samsung.com or ty76.kim@samsung.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Tools4miRs - one place to gather all the tools for miRNA analysis.

PubMed

Lukasik, Anna; Wójcikowski, Maciej; Zielenkiewicz, Piotr

2016-09-01

MiRNAs are short, non-coding molecules that negatively regulate gene expression and thereby play several important roles in living organisms. Dozens of computational methods for miRNA-related research have been developed, which greatly differ in various aspects. The substantial availability of difficult-to-compare approaches makes it challenging for the user to select a proper tool and prompts the need for a solution that will collect and categorize all the methods. Here, we present tools4miRs, the first platform that gathers currently more than 160 methods for broadly defined miRNA analysis. The collected tools are classified into several general and more detailed categories in which the users can additionally filter the available methods according to their specific research needs, capabilities and preferences. Tools4miRs is also a web-based target prediction meta-server that incorporates user-designated target prediction methods into the analysis of user-provided data. Tools4miRs is implemented in Python using Django and is freely available at tools4mirs.org. piotr@ibb.waw.pl Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

In response to 'Can sugars be produced from fatty acids? A test case for pathway analysis tools'.

PubMed

Faust, Karoline; Croes, Didier; van Helden, Jacques

2009-12-01

In their article entitled 'Can sugars be produced from fatty acids? A test case for pathway analysis tools' de Figueiredo and co-authors assess the performance of three pathway prediction tools (METATOOL, PathFinding and Pathway Hunter Tool) using the synthesis of glucose-6-phosphate (G6P) from acetyl-CoA in humans as a test case. We think that this article is biased for three reasons: (i) the metabolic networks used as input for the respective tools were of very different sizes; (ii) the 'assessment' is restricted to two study cases; (iii) developers are inherently more skilled to use their own tools than those developed by other people. We extended the analyses led by de Figueiredo and clearly show that the apparent superior performance of their tool (METATOOL) is partly due to the differences in input network sizes. We also see a conceptual problem in the comparison of tools that serve different purposes. In our opinion, metabolic path finding and elementary mode analysis are answering different biological questions, and should be considered as complementary rather than competitive approaches. Supplementary data are available at Bioinformatics online.

Journal Writing as an Adult Learning Tool. Practice Application Brief No. 22.

ERIC Educational Resources Information Center

Kerka, Sandra

Journals can be valuable tools for fostering adult learning and experience. Research has supported the following assumptions about learning from journals: (1) articulating connections between new and existing knowledge improves learning; (2) writing about learning is a way of demonstrating what has been learned; (3) journal writing accentuates…

Mobile Learning: A Powerful Tool for Ubiquitous Language Learning

ERIC Educational Resources Information Center

Gomes, Nelson; Lopes, Sérgio; Araújo, Sílvia

2016-01-01

Mobile devices (smartphones, tablets, e-readers, etc.) have come to be used as tools for mobile learning. Several studies support the integration of such technological devices with learning, particularly with language learning. In this paper, we wish to present an Android app designed for the teaching and learning of Portuguese as a foreign…

Deep Learning Improves Antimicrobial Peptide Recognition.

PubMed

Veltri, Daniel; Kamath, Uday; Shehu, Amarda

2018-03-24

Bacterial resistance to antibiotics is a growing concern. Antimicrobial peptides (AMPs), natural components of innate immunity, are popular targets for developing new drugs. Machine learning methods are now commonly adopted by wet-laboratory researchers to screen for promising candidates. In this work we utilize deep learning to recognize antimicrobial activity. We propose a neural network model with convolutional and recurrent layers that leverage primary sequence composition. Results show that the proposed model outperforms state-of-the-art classification models on a comprehensive data set. By utilizing the embedding weights, we also present a reduced-alphabet representation and show that reasonable AMP recognition can be maintained using nine amino-acid types. Models and data sets are made freely available through the Antimicrobial Peptide Scanner vr.2 web server at: www.ampscanner.com. amarda@gmu.edu for general inquiries and dan.veltri@gmail.com for web server information. Supplementary data are available at Bioinformatics online.

bnstruct: an R package for Bayesian Network structure learning in the presence of missing data.

PubMed

Franzin, Alberto; Sambo, Francesco; Di Camillo, Barbara

2017-04-15

A Bayesian Network is a probabilistic graphical model that encodes probabilistic dependencies between a set of random variables. We introduce bnstruct, an open source R package to (i) learn the structure and the parameters of a Bayesian Network from data in the presence of missing values and (ii) perform reasoning and inference on the learned Bayesian Networks. To the best of our knowledge, there is no other open source software that provides methods for all of these tasks, particularly the manipulation of missing data, which is a common situation in practice. The software is implemented in R and C and is available on CRAN under a GPL licence. francesco.sambo@unipd.it. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Developing Media Module Proposed to Editor in Editorial Division

NASA Astrophysics Data System (ADS)

Kristanto, A.; Mustaji; Mariono, A.; Sulistiowati; Nuryati, D. W.

2018-01-01

In this era of technology in Indonesia, various publishers introduce themselves and participate in advancing the quality of education through the publication of various books as the learning sources. One of the publishers is PT. JP Press. In compiling the learning sources, we found some problems that are left unresolved by the editor. The purpose of this research is to overcome the problems that exist in PT. JP Press by developing media module. This development research uses the ADDIE model. The types of data used in this study are qualitative and quantitative data obtained based on the results of structured interviews with material experts and media experts, as well as the editorial response questionnaire provided for individual try-out and small group try-out. Therefore, it can be concluded that the medium of elementary school supplementary module proposed to the editors of PT. JP Press is valuable to be used in the teaching and learning activities.

[Blended-learning in psychosomatics and psychotherapy - Increasing the satisfaction and knowledge of students with a web-based e-learning tool].

PubMed

Ferber, Julia; Schneider, Gudrun; Havlik, Linda; Heuft, Gereon; Friederichs, Hendrik; Schrewe, Franz-Bernhard; Schulz-Steinel, Andrea; Burgmer, Markus

2014-01-01

To improve the synergy of established methods of teaching, the Department of Psychosomatics and Psychotherapy, University Hospital Münster, developed a web-based elearning tool using video clips of standardized patients. The effect of this blended-learning approach was evaluated. A multiple-choice test was performed by a naive (without the e-learning tool) and an experimental (with the tool) cohort of medical students to test the groups' expertise in psychosomatics. In addition, participants' satisfaction with the new tool was evaluated (numeric rating scale of 0-10). The experimental cohort was more satisfied with the curriculum and more interested in psychosomatics. Furthermore, the experimental cohort scored significantly better in the multiple-choice test. The new tool proved to be an important addition to the classical curriculum as a blended-learning approach which improves students' satisfaction and knowledge in psychosomatics.

Design and Development of a Self-Assessment Tool and Investigating its Effectiveness for E-Learning

ERIC Educational Resources Information Center

Domun, Manisha; Bahadur, Goonesh K.

2014-01-01

One of the most effective tools in e-learning is the Self-Assessment Tool (SAT) and research has shown that students need to accurately assess their own performance thus improving their learning. The study involved the design and development of a self-assessment tool based on the Revised Blooms taxonomy Framework. As a second step in investigating…

A Relative Ranking Approach for Nano-Enabled Applications to Improve Risk-Based Decision Making: A Case Study of Army Materiel

DTIC Science & Technology

2014-12-24

scenarios. The USACEHR has been conducting research and devel- opment efforts on the incorporation of various ENMs into Army materiel, ranging from food ...materiel characteristics, and (3) apply the algorithm and associated risk ranking tool to prioritize additional assessments based on the human health risk...online correspondence to confirm, edit, and supplement the inventory with additional information (See Section 1 in Supplementary Information (SI) for

ST Spot Detector: a web-based application for automatic spot and tissue detection for spatial Transcriptomics image datasets.

PubMed

Wong, Kim; Navarro, José Fernández; Bergenstråhle, Ludvig; Ståhl, Patrik L; Lundeberg, Joakim

2018-06-01

Spatial Transcriptomics (ST) is a method which combines high resolution tissue imaging with high troughput transcriptome sequencing data. This data must be aligned with the images for correct visualization, a process that involves several manual steps. Here we present ST Spot Detector, a web tool that automates and facilitates this alignment through a user friendly interface. jose.fernandez.navarro@scilifelab.se. Supplementary data are available at Bioinformatics online.

Programming strategy for efficient modeling of dynamics in a population of heterogeneous cells.

PubMed

Hald, Bjørn Olav; Garkier Hendriksen, Morten; Sørensen, Preben Graae

2013-05-15

Heterogeneity is a ubiquitous property of biological systems. Even in a genetically identical population of a single cell type, cell-to-cell differences are observed. Although the functional behavior of a given population is generally robust, the consequences of heterogeneity are fairly unpredictable. In heterogeneous populations, synchronization of events becomes a cardinal problem-particularly for phase coherence in oscillating systems. The present article presents a novel strategy for construction of large-scale simulation programs of heterogeneous biological entities. The strategy is designed to be tractable, to handle heterogeneity and to handle computational cost issues simultaneously, primarily by writing a generator of the 'model to be simulated'. We apply the strategy to model glycolytic oscillations among thousands of yeast cells coupled through the extracellular medium. The usefulness is illustrated through (i) benchmarking, showing an almost linear relationship between model size and run time, and (ii) analysis of the resulting simulations, showing that contrary to the experimental situation, synchronous oscillations are surprisingly hard to achieve, underpinning the need for tools to study heterogeneity. Thus, we present an efficient strategy to model the biological heterogeneity, neglected by ordinary mean-field models. This tool is well posed to facilitate the elucidation of the physiologically vital problem of synchronization. The complete python code is available as Supplementary Information. bjornhald@gmail.com or pgs@kiku.dk Supplementary data are available at Bioinformatics online.

Characterization of focal breast lesions by means of elastography.

PubMed

Fischer, T; Sack, I; Thomas, A

2013-09-01

The modern method of sonoelastography of the breast is used for differentiating focal lesions. This review gives an overview of the different techniques available and discusses their roles in the routine clinical setting. The presented techniques include compression or vibration elastography as well as shear wave elastography. Descriptions of the methods are supplemented by a discussion of the clinical role of each technique based on the most recent literature. We discuss by outlining two recent experimental approaches - MRI and tomosynthesis elastography. Currently available data suggest that elastography is an important supplementary tool for the differentiation of breast tumors under routine clinical conditions. The specificity improves with the immediate availability of additional diagnostic information using real-time techniques and/or the calculation of strain ratios (SR). Elastography is especially helpful in women with involuted breasts for differentiating BI-RADS-US 3 and 4 lesions and for evaluating very small cancers without the typical imaging features of malignancy. Here, elastography techniques are highly specific, while the sensitivity decreases compared to B-mode ultrasound. SR calculation is especially helpful in women who have a high risk of breast cancer and high pretest likelihood. B-mode ultrasound is still the first-line method for the initial evaluation of the breast. If suspicious findings are detected, elastography with or without SR calculation is the most crucial supplementary tool. © Georg Thieme Verlag KG Stuttgart · New York.

Blended Teaching & Learning

ERIC Educational Resources Information Center

Pape, Liz

2010-01-01

Blended learning is using online tools to communicate, collaborate and publish, to extend the school day or year and to develop the 21st-century skills students need. With blended learning, teachers can use online tools and resources as part of their daily classroom instruction. Using many of the online tools and resources students already are…

Modes of Learning in Religious Education

ERIC Educational Resources Information Center

Afdal, Geir

2015-01-01

This article is a contribution to the discussion of learning processes in religious education (RE) classrooms. Sociocultural theories of learning, understood here as tool-mediated processes, are used in an analysis of three RE classroom conversations. The analysis focuses on the language tools that are used in conversations; how the tools mediate;…

Individual and social learning processes involved in the acquisition and generalization of tool use in macaques

PubMed Central

Macellini, S.; Maranesi, M.; Bonini, L.; Simone, L.; Rozzi, S.; Ferrari, P. F.; Fogassi, L.

2012-01-01

Macaques can efficiently use several tools, but their capacity to discriminate the relevant physical features of a tool and the social factors contributing to their acquisition are still poorly explored. In a series of studies, we investigated macaques' ability to generalize the use of a stick as a tool to new objects having different physical features (study 1), or to new contexts, requiring them to adapt the previously learned motor strategy (study 2). We then assessed whether the observation of a skilled model might facilitate tool-use learning by naive observer monkeys (study 3). Results of study 1 and study 2 showed that monkeys trained to use a tool generalize this ability to tools of different shape and length, and learn to adapt their motor strategy to a new task. Study 3 demonstrated that observing a skilled model increases the observers' manipulations of a stick, thus facilitating the individual discovery of the relevant properties of this object as a tool. These findings support the view that in macaques, the motor system can be modified through tool use and that it has a limited capacity to adjust the learnt motor skills to a new context. Social factors, although important to facilitate the interaction with tools, are not crucial for tool-use learning. PMID:22106424

DeepSig: deep learning improves signal peptide detection in proteins.

PubMed

Savojardo, Castrense; Martelli, Pier Luigi; Fariselli, Piero; Casadio, Rita

2018-05-15

The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website. pierluigi.martelli@unibo.it. Supplementary data are available at Bioinformatics online.

Heuristics for connectivity-based brain parcellation of SMA/pre-SMA through force-directed graph layout.

PubMed

Crippa, Alessandro; Cerliani, Leonardo; Nanetti, Luca; Roerdink, Jos B T M

2011-02-01

We propose the use of force-directed graph layout as an explorative tool for connectivity-based brain parcellation studies. The method can be used as a heuristic to find the number of clusters intrinsically present in the data (if any) and to investigate their organisation. It provides an intuitive representation of the structure of the data and facilitates interactive exploration of properties of single seed voxels as well as relations among (groups of) voxels. We validate the method on synthetic data sets and we investigate the changes in connectivity in the supplementary motor cortex, a brain region whose parcellation has been previously investigated via connectivity studies. This region is supposed to present two easily distinguishable connectivity patterns, putatively denoted by SMA (supplementary motor area) and pre-SMA. Our method provides insights with respect to the connectivity patterns of the premotor cortex. These present a substantial variation among subjects, and their subdivision into two well-separated clusters is not always straightforward. Copyright © 2010 Elsevier Inc. All rights reserved.

Bambus 2: scaffolding metagenomes

PubMed Central

Koren, Sergey; Treangen, Todd J.; Pop, Mihai

2011-01-01

Motivation: Sequencing projects increasingly target samples from non-clonal sources. In particular, metagenomics has enabled scientists to begin to characterize the structure of microbial communities. The software tools developed for assembling and analyzing sequencing data for clonal organisms are, however, unable to adequately process data derived from non-clonal sources. Results: We present a new scaffolder, Bambus 2, to address some of the challenges encountered when analyzing metagenomes. Our approach relies on a combination of a novel method for detecting genomic repeats and algorithms that analyze assembly graphs to identify biologically meaningful genomic variants. We compare our software to current assemblers using simulated and real data. We demonstrate that the repeat detection algorithms have higher sensitivity than current approaches without sacrificing specificity. In metagenomic datasets, the scaffolder avoids false joins between distantly related organisms while obtaining long-range contiguity. Bambus 2 represents a first step toward automated metagenomic assembly. Availability: Bambus 2 is open source and available from http://amos.sf.net. Contact: mpop@umiacs.umd.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:21926123

ImmuneDB: a system for the analysis and exploration of high-throughput adaptive immune receptor sequencing data.

PubMed

Rosenfeld, Aaron M; Meng, Wenzhao; Luning Prak, Eline T; Hershberg, Uri

2017-01-15

As high-throughput sequencing of B cells becomes more common, the need for tools to analyze the large quantity of data also increases. This article introduces ImmuneDB, a system for analyzing vast amounts of heavy chain variable region sequences and exploring the resulting data. It can take as input raw FASTA/FASTQ data, identify genes, determine clones, construct lineages, as well as provide information such as selection pressure and mutation analysis. It uses an industry leading database, MySQL, to provide fast analysis and avoid the complexities of using error prone flat-files. ImmuneDB is freely available at http://immunedb.comA demo of the ImmuneDB web interface is available at: http://immunedb.com/demo CONTACT: Uh25@drexel.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

ChromA: signal-based retention time alignment for chromatography–mass spectrometry data

PubMed Central

Hoffmann, Nils; Stoye, Jens

2009-01-01

Summary: We describe ChromA, a web-based alignment tool for chromatography–mass spectrometry data from the metabolomics and proteomics domains. Users can supply their data in open and standardized file formats for retention time alignment using dynamic time warping with different configurable local distance and similarity functions. Additionally, user-defined anchors can be used to constrain and speedup the alignment. A neighborhood around each anchor can be added to increase the flexibility of the constrained alignment. ChromA offers different visualizations of the alignment for easier qualitative interpretation and comparison of the data. For the multiple alignment of more than two data files, the center-star approximation is applied to select a reference among input files to align to. Availability: ChromA is available at http://bibiserv.techfak.uni-bielefeld.de/chroma. Executables and source code under the L-GPL v3 license are provided for download at the same location. Contact: stoye@techfak.uni-bielefeld.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19505941

DEsubs: an R package for flexible identification of differentially expressed subpathways using RNA-seq experiments.

PubMed

Vrahatis, Aristidis G; Balomenos, Panos; Tsakalidis, Athanasios K; Bezerianos, Anastasios

2016-12-15

DEsubs is a network-based systems biology R package that extracts disease-perturbed subpathways within a pathway network as recorded by RNA-seq experiments. It contains an extensive and customized framework with a broad range of operation modes at all stages of the subpathway analysis, enabling so a case-specific approach. The operation modes include pathway network construction and processing, subpathway extraction, visualization and enrichment analysis with regard to various biological and pharmacological features. Its capabilities render DEsubs a tool-guide for both the modeler and experimentalist for the identification of more robust systems-level drug targets and biomarkers for complex diseases. DEsubs is implemented as an R package following Bioconductor guidelines: http://bioconductor.org/packages/DEsubs/ CONTACT: tassos.bezerianos@nus.edu.sgSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The Personal Digital Library (PDL)-based e-learning: Using the PDL as an e-learning support tool

NASA Astrophysics Data System (ADS)

Deng, Xiaozhao; Ruan, Jianhai

The paper describes a support tool for learners engaged in e-learning, the Personal Digital Library (PDL). The characteristics and functionality of the PDL are presented. Suggested steps for constructing and managing a PDL are outlined and discussed briefly. The authors believe that the PDL as a support tool of e-learning will be important and essential in the future.

Theory-Led Design of Instruments and Representations in Learning Analytics: Developing a Novel Tool for Orchestration of Online Collaborative Learning

ERIC Educational Resources Information Center

Kelly, Nick; Thompson, Kate; Yeoman, Pippa

2015-01-01

This paper describes theory-led design as a way of developing novel tools for learning analytics (LA). It focuses upon the domain of automated discourse analysis (ADA) of group learning activities to help an instructor to orchestrate online groups in real-time. The paper outlines the literature on the development of LA tools within the domain of…

Improving pedagogic competence using an e-learning approach for pre-service mathematics teachers

NASA Astrophysics Data System (ADS)

Retnowati, E.; Murdiyani, N. M.; Marsigit; Sugiman; Mahmudi, A.

2018-03-01

This article reported a classroom action research that was aimed to improve student’s pedagogic competence during a course namely Methods of Mathematics Instruction. An asynchronous e-learning approach was provided as supplementary material to the main lecture. This e-learning consisted of selected references and educational website addresses and also facilitated online discussions about various methods of mathematics instructions. The subject was twenty-six pre-service teachers in the Department of Mathematics Education, Yogyakarta State University, Indonesia, conducted by the researchers. The research completed three cycles, where each cycle consisted of plan-action-reflection. Through observation, documentation, and interview, it was concluded that asynchronous e-learning might be used to improve pedagogic competence when direct instruction is also applied in the classroom. Direct instruction in this study provided review, explanation, scheme, and examples which could be used by students to select relevant resources in the e-learning portal. Moreover, the pedagogic competence improved after students accomplished assignments to identify aspects of pedagogic instruction either from analyzing videos in e-learning course or simulating in the classroom with direct commentaries. Supporting factors were enthusiasm, discipline, and interactions among students and lecturer that were built throughout the lectures.

Perspectives on Machine Learning for Classification of Schizotypy Using fMRI Data.

PubMed

Madsen, Kristoffer H; Krohne, Laerke G; Cai, Xin-Lu; Wang, Yi; Chan, Raymond C K

2018-03-15

Functional magnetic resonance imaging is capable of estimating functional activation and connectivity in the human brain, and lately there has been increased interest in the use of these functional modalities combined with machine learning for identification of psychiatric traits. While these methods bear great potential for early diagnosis and better understanding of disease processes, there are wide ranges of processing choices and pitfalls that may severely hamper interpretation and generalization performance unless carefully considered. In this perspective article, we aim to motivate the use of machine learning schizotypy research. To this end, we describe common data processing steps while commenting on best practices and procedures. First, we introduce the important role of schizotypy to motivate the importance of reliable classification, and summarize existing machine learning literature on schizotypy. Then, we describe procedures for extraction of features based on fMRI data, including statistical parametric mapping, parcellation, complex network analysis, and decomposition methods, as well as classification with a special focus on support vector classification and deep learning. We provide more detailed descriptions and software as supplementary material. Finally, we present current challenges in machine learning for classification of schizotypy and comment on future trends and perspectives.

Accurate in silico prediction of species-specific methylation sites based on information gain feature optimization.

PubMed

Wen, Ping-Ping; Shi, Shao-Ping; Xu, Hao-Dong; Wang, Li-Na; Qiu, Jian-Ding

2016-10-15

As one of the most important reversible types of post-translational modification, protein methylation catalyzed by methyltransferases carries many pivotal biological functions as well as many essential biological processes. Identification of methylation sites is prerequisite for decoding methylation regulatory networks in living cells and understanding their physiological roles. Experimental methods are limitations of labor-intensive and time-consuming. While in silicon approaches are cost-effective and high-throughput manner to predict potential methylation sites, but those previous predictors only have a mixed model and their prediction performances are not fully satisfactory now. Recently, with increasing availability of quantitative methylation datasets in diverse species (especially in eukaryotes), there is a growing need to develop a species-specific predictor. Here, we designed a tool named PSSMe based on information gain (IG) feature optimization method for species-specific methylation site prediction. The IG method was adopted to analyze the importance and contribution of each feature, then select the valuable dimension feature vectors to reconstitute a new orderly feature, which was applied to build the finally prediction model. Finally, our method improves prediction performance of accuracy about 15% comparing with single features. Furthermore, our species-specific model significantly improves the predictive performance compare with other general methylation prediction tools. Hence, our prediction results serve as useful resources to elucidate the mechanism of arginine or lysine methylation and facilitate hypothesis-driven experimental design and validation. The tool online service is implemented by C# language and freely available at http://bioinfo.ncu.edu.cn/PSSMe.aspx CONTACT: jdqiu@ncu.edu.cnSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

miRCat2: accurate prediction of plant and animal microRNAs from next-generation sequencing datasets

PubMed Central

Paicu, Claudia; Mohorianu, Irina; Stocks, Matthew; Xu, Ping; Coince, Aurore; Billmeier, Martina; Dalmay, Tamas; Moulton, Vincent; Moxon, Simon

2017-01-01

Abstract Motivation MicroRNAs are a class of ∼21–22 nt small RNAs which are excised from a stable hairpin-like secondary structure. They have important gene regulatory functions and are involved in many pathways including developmental timing, organogenesis and development in eukaryotes. There are several computational tools for miRNA detection from next-generation sequencing datasets. However, many of these tools suffer from high false positive and false negative rates. Here we present a novel miRNA prediction algorithm, miRCat2. miRCat2 incorporates a new entropy-based approach to detect miRNA loci, which is designed to cope with the high sequencing depth of current next-generation sequencing datasets. It has a user-friendly interface and produces graphical representations of the hairpin structure and plots depicting the alignment of sequences on the secondary structure. Results We test miRCat2 on a number of animal and plant datasets and present a comparative analysis with miRCat, miRDeep2, miRPlant and miReap. We also use mutants in the miRNA biogenesis pathway to evaluate the predictions of these tools. Results indicate that miRCat2 has an improved accuracy compared with other methods tested. Moreover, miRCat2 predicts several new miRNAs that are differentially expressed in wild-type versus mutants in the miRNA biogenesis pathway. Availability and Implementation miRCat2 is part of the UEA small RNA Workbench and is freely available from http://srna-workbench.cmp.uea.ac.uk/. Contact v.moulton@uea.ac.uk or s.moxon@uea.ac.uk Supplementary information Supplementary data are available at Bioinformatics online. PMID:28407097

Technology Enhanced Learning for People with Intellectual Disabilities and Cerebral Paralysis: The MAS Platform

NASA Astrophysics Data System (ADS)

Colomo-Palacios, Ricardo; Paniagua-Martín, Fernando; García-Crespo, Ángel; Ruiz-Mezcua, Belén

Education for students with disabilities now takes place in a wide range of settings, thus, including a wider range of assistive tools. As a result of this, one of the most interesting application domains of technology enhanced learning is related to the adoption of learning technologies and designs for people with disabilities. Following this unstoppable trend, this paper presents MAS, a software platform aimed to help people with severe intellectual disabilities and cerebral paralysis in their learning processes. MAS, as a technology enhanced learning platform, provides several tools that supports learning and monitoring for people with special needs, including adaptative games, data processing and monitoring tools. Installed in a special needs education institution in Madrid, Spain, MAS provides special educators with a tool that improved students education processes.

The Comprehensive Evaluation of Electronic Learning Tools and Educational Software (CEELTES)

ERIC Educational Resources Information Center

Karolcík, Štefan; Cipková, Elena; Hrušecký, Roman; Veselský, Milan

2015-01-01

Despite the fact that digital technologies are more and more used in the learning and education process, there is still lack of professional evaluation tools capable of assessing the quality of used digital teaching aids in a comprehensive and objective manner. Construction of the Comprehensive Evaluation of Electronic Learning Tools and…

Discovering the Motivations of Students When Using an Online Learning Tool

ERIC Educational Resources Information Center

Saadé, Raafat George; Al Sharhan, Jamal

2015-01-01

In an educational setting, the use of online learning tools impacts student performance. Motivation and beliefs play an important role in predicting student decisions to use these learning tools. However, IT-personality entailing playfulness on the web, perceived personal innovativeness, and enjoyment may have an impact on motivations. In this…

Blended Teaching and Learning

ERIC Educational Resources Information Center

Pape, Liz

2010-01-01

"Blended learning" is using online tools to communicate, collaborate, and publish, to extend the school day or year and to develop the 21st-century skills students need. With blended learning, teachers can use online tools and resources as part of their daily classroom instruction. Using many of the online tools and resources students already are…

An Online Authoring Tool for Creating Activity-Based Learning Objects

ERIC Educational Resources Information Center

Ahn, Jeong Yong; Mun, Gil Seong; Han, Kyung Soo; Choi, Sook Hee

2017-01-01

As higher education increasingly relies on e-learning, the need for tools that will allow teachers themselves to develop effective e-learning objects as simply and quickly as possible has also been increasingly recognized. This article discusses the design and development of a novel tool, Enook (Evolutionary note book), for creating activity-based…

Evaluation of Knowla: An Online Assessment and Learning Tool

ERIC Educational Resources Information Center

Thompson, Meredith Myra; Braude, Eric John

2016-01-01

The assessment of learning in large online courses requires tools that are valid, reliable, easy to administer, and can be automatically scored. We have evaluated an online assessment and learning tool called Knowledge Assembly, or Knowla. Knowla measures a student's knowledge in a particular subject by having the student assemble a set of…

Development and Testing of the Collaboration in the Clinical Learning Environment (CCLE) Tool

ERIC Educational Resources Information Center

Hooven, Katie J.

2016-01-01

The purpose of this study was to develop and psychometrically test the Collaboration in the Clinical Learning Environment (CCLE) Tool. The researcher acknowledged two distinct populations that required input into this particular tool development: staff nurses who work on floors that are considered clinical learning environments for students, and…

Concept Mapping Using Cmap Tools to Enhance Meaningful Learning

NASA Astrophysics Data System (ADS)

Cañas, Alberto J.; Novak, Joseph D.

Concept maps are graphical tools that have been used in all facets of education and training for organizing and representing knowledge. When learners build concept maps, meaningful learning is facilitated. Computer-based concept mapping software such as CmapTools have further extended the use of concept mapping and greatly enhanced the potential of the tool, facilitating the implementation of a concept map-centered learning environment. In this chapter, we briefly present concept mapping and its theoretical foundation, and illustrate how it can lead to an improved learning environment when it is combined with CmapTools and the Internet. We present the nationwide “Proyecto Conéctate al Conocimiento” in Panama as an example of how concept mapping, together with technology, can be adopted by hundreds of schools as a means to enhance meaningful learning.

Prediction of site-specific interactions in antibody-antigen complexes: the proABC method and server.

PubMed

Olimpieri, Pier Paolo; Chailyan, Anna; Tramontano, Anna; Marcatili, Paolo

2013-09-15

Antibodies or immunoglobulins are proteins of paramount importance in the immune system. They are extremely relevant as diagnostic, biotechnological and therapeutic tools. Their modular structure makes it easy to re-engineer them for specific purposes. Short of undergoing a trial and error process, these experiments, as well as others, need to rely on an understanding of the specific determinants of the antibody binding mode. In this article, we present a method to identify, on the basis of the antibody sequence alone, which residues of an antibody directly interact with its cognate antigen. The method, based on the random forest automatic learning techniques, reaches a recall and specificity as high as 80% and is implemented as a free and easy-to-use server, named prediction of Antibody Contacts. We believe that it can be of great help in re-design experiments as well as a guide for molecular docking experiments. The results that we obtained also allowed us to dissect which features of the antibody sequence contribute most to the involvement of specific residues in binding to the antigen. http://www.biocomputing.it/proABC. anna.tramontano@uniroma1.it or paolo.marcatili@gmail.com Supplementary data are available at Bioinformatics online.

Engaged Learning Using the Internet: SURWEB as a Student-Focused Learning Tool.

ERIC Educational Resources Information Center

Barker, Bruce O.; Bills, Lynn

The engaged learning model centers on information and communications technologies as tools to assist teachers in helping students take responsibility for their own learning, become knowledge explorers, and collaborate with others to find information and to seek answers to problems. This paper defines engaged learning, and outlines the following…

Integrated Authoring Tool for Mobile Augmented Reality-Based E-Learning Applications

ERIC Educational Resources Information Center

Lobo, Marcos Fermin; Álvarez García, Víctor Manuel; del Puerto Paule Ruiz, María

2013-01-01

Learning management systems are increasingly being used to complement classroom teaching and learning and in some instances even replace traditional classroom settings with online educational tools. Mobile augmented reality is an innovative trend in e-learning that is creating new opportunities for teaching and learning. This article proposes a…

A Study of the Effects of Digital Learning on Learning Motivation and Learning Outcome

ERIC Educational Resources Information Center

Lin, Ming-Hung; Chen, Huang-Cheng; Liu, Kuang-Sheng

2017-01-01

In the modern society when intelligent mobile devices become popular, the Internet breaks through the restrictions on time and space and becomes a ubiquitous learning tool. Designing teaching activity for digital learning and flexibly applying technology tools are the key issues for current information technology integrated education. In this…

The value of online learning and MRI: finding a niche for expensive technologies.

PubMed

Cook, David A

2014-11-01

The benefits of online learning come at a price. How can we optimize the overall value? Critically appraise the value of online learning. Narrative review. Several prevalent myths overinflate the value of online learning. These include that online learning is cheap and easy (it is usually more expensive), that it is more efficient (efficiency depends on the instructional design, not the modality), that it will transform education (fundamental learning principles have not changed), and that the Net Generation expects it (there is no evidence of pent-up demand). However, online learning does add real value by enhancing flexibility, control and analytics. Costs may also go down if disruptive innovations (e.g. low-cost, low-tech, but instructionally sound "good enough" online learning) supplant technically superior but more expensive online learning products. Cost-lowering strategies include focusing on core principles of learning rather than technologies, using easy-to-learn authoring tools, repurposing content (organizing and sequencing existing resources rather than creating new content) and using course templates. Online learning represents just one tool in an educator's toolbox, as does the MRI for clinicians. We need to use the right tool(s) for the right learner at the right dose, time and route.

Publisher Correction: Resistance to nonribosomal peptide antibiotics mediated by D-stereospecific peptidases.

PubMed

Li, Yong-Xin; Zhong, Zheng; Hou, Peng; Zhang, Wei-Peng; Qian, Pei-Yuan

2018-03-07

In the version of this article originally published, the links and files for the Supplementary Information, including Supplementary Tables 1-5, Supplementary Figures 1-25, Supplementary Note, Supplementary Datasets 1-4 and the Life Sciences Reporting Summary, were missing in the HTML. The error has been corrected in the HTML version of this article.

Author Correction: Uplift of the central transantarctic mountains.

PubMed

Wannamaker, Phil; Hill, Graham; Stodt, John; Maris, Virginie; Ogawa, Yasuo; Selway, Kate; Boren, Goran; Bertrand, Edward; Uhlmann, Daniel; Ayling, Bridget; Green, A Marie; Feucht, Daniel

2018-02-16

The original version of this Article incorrectly referenced the Figures in the Supplementary Information. References in the main Article to Supplementary Figure 7 through to Supplementary Figure 20 were previously incorrectly cited as Supplementary Figure 5 through to Supplementary Figure 18, respectively. This has now been corrected in both the PDF and HTML versions of the Article.

Challenge of engaging all students via self-paced interactive electronic learning tutorials for introductory physics

NASA Astrophysics Data System (ADS)

DeVore, Seth; Marshman, Emily; Singh, Chandralekha

2017-06-01

As research-based, self-paced electronic learning tools become increasingly available, a critical issue educators encounter is implementing strategies to ensure that all students engage with them as intended. Here, we first discuss the effectiveness of electronic learning tutorials as self-paced learning tools in large enrollment brick and mortar introductory physics courses and then propose a framework for helping students engage effectively with the learning tools. The tutorials were developed via research in physics education and were found to be effective for a diverse group of introductory physics students in one-on-one implementation. Instructors encouraged the use of these tools in a self-paced learning environment by telling students that they would be helpful for solving the assigned homework problems and that the underlying physics principles in the tutorial problems would be similar to those in the in-class quizzes (which we call paired problems). We find that many students in the courses in which these interactive electronic learning tutorials were assigned as a self-study tool performed poorly on the paired problems. In contrast, a majority of student volunteers in one-on-one implementation greatly benefited from the tutorials and performed well on the paired problems. The significantly lower overall performance on paired problems administered as an in-class quiz compared to the performance of student volunteers who used the research-based tutorials in one-on-one implementation suggests that many students enrolled in introductory physics courses did not effectively engage with the tutorials outside of class and may have only used them superficially. The findings suggest that many students in need of out-of-class remediation via self-paced learning tools may have difficulty motivating themselves and may lack the self-regulation and time-management skills to engage effectively with tools specially designed to help them learn at their own pace. We conclude by proposing a theoretical framework to help students with diverse prior preparations engage effectively with self-paced learning tools.

REDItools: high-throughput RNA editing detection made easy.

PubMed

Picardi, Ernesto; Pesole, Graziano

2013-07-15

The reliable detection of RNA editing sites from massive sequencing data remains challenging and, although several methodologies have been proposed, no computational tools have been released to date. Here, we introduce REDItools a suite of python scripts to perform high-throughput investigation of RNA editing using next-generation sequencing data. REDItools are in python programming language and freely available at http://code.google.com/p/reditools/. ernesto.picardi@uniba.it or graziano.pesole@uniba.it Supplementary data are available at Bioinformatics online.

Payload specialist Robert Cenker after adjusting DSO equipment

NASA Image and Video Library

1986-01-12

61C-05-035 (12-17 Jan 1986) --- Robert J. Cenker, 61-C payload specialist representing RCA, returns a tiny tool to its stowage position after adjusting the inner workings of a device used in one of a number of detailed supplementary objective (DSO) studies for NASA's Space Biomedical Research Institute. The device is a pair of ocular counter-rolling goggles used by U.S. Rep. Bill Nelson (D., Florida), 61-C's other payload specialist aboard the Columbia for this five-day flight.

The Effect of Harp Music on Heart Rate, Mean Blood Pressure, Respiratory Rate, and Body Temperature in the African Green Monkey

DTIC Science & Technology

2007-01-01

harp music on heart rate, mean blood pressure, respiratory rate, and body temperature in the African green monkey. Journal of Medical Primatology 36:95...13. SUPPLEMENTARY NOTES 14. ABSTRACT Background: The effectiveness of recorded harp music as a tool for relaxation for nonhuman primates (NHP) is...Chlorocebus aethiops). After post-surgical recovery, animals were exposed to recorded harp music . Telemetry data were collected on heart rate, mean

Large scale 20mm photography for range resources analysis in the Western United States. [Casa Grande, Arizona, Mercury, Nevada, and Mojave Desert

NASA Technical Reports Server (NTRS)

Tueller, P. T.

1977-01-01

Large scale 70mm aerial photography is a valuable supplementary tool for rangeland studies. A wide assortment of applications were developed varying from vegetation mapping to assessing environmental impact on rangelands. Color and color infrared stereo pairs are useful for effectively sampling sites limited by ground accessibility. They allow an increased sample size at similar or lower cost than ground sampling techniques and provide a permanent record.

Use of Electronic Tag Data and Associated Analytical Tools to Identify and Predict Habitat Utilization of Marine Predators

DTIC Science & Technology

2013-09-30

fin, sperm and humpback whales). RESULTS The tracking data reveal that the California Current Large Marine Ecosystem (CCLME; Supplementary...within 1u31u grid cells. b, Density of large marine predators within the CCLME at a 0.25 º 30.25º resolution. The CCLME is a highly retentive area...sooty shearwaters). The retention with and attraction to the CCLME is consistent with the high productivity of this region that supports large

Bear Market Coercion: Russian Use of Energy as a Coercive Tool in Central Asia and Eastern Europe

DTIC Science & Technology

2009-06-01

SUPPLEMENTARY NOTES The original document contains color images. 14. ABSTRACT This study considers the efficacy of economic coercion as a means of...Crimean War was no less disastrous than the Cold War, and the Treaty of Paris no less damaging to Russia’s perceived honor than the breakup of the Soviet...the other. Economic coercion involves potential gains and losses that are relative, not only to the original baseline, but also to the realm of

Use of the Webinar Tool (Elluminate) to Support Training: The Effects of Webinar-Learning Implementation from Student-Trainers' Perspective

ERIC Educational Resources Information Center

Wang, Shiang-Kwei; Hsu, Hui-Yin

2008-01-01

Recently, webinar (web seminar) tools (e.g., Elluminate, Adobe Acrobat Connect, Live Meeting) have been attracting more and more attention with the advancement of online learning technologies because webinar tools facilitate real-time communication and enrich the interactivity in an online learning environment. Corporations have long adopted…

A Usability Study of Users' Perceptions toward a Multimedia Computer-Assisted Learning Tool for Neuroanatomy

ERIC Educational Resources Information Center

Gould, Douglas J.; Terrell, Mark A.; Fleming, Jo

2008-01-01

This usability study evaluated users' perceptions of a multimedia prototype for a new e-learning tool: Anatomy of the Central Nervous System: A Multimedia Course. Usability testing is a collection of formative evaluation methods that inform the developmental design of e-learning tools to maximize user acceptance, satisfaction, and adoption.…

Information and Communication Technologies: A Tool Empowering and Developing the Horizon of the Learner

ERIC Educational Resources Information Center

Debande, Olivier; Ottersten, Eugenia Kazamaki

2004-01-01

In this article, we focus on the implementation and development of ICT in the education sector, challenging and developing the traditional learning environment whilst introducing new educational tools including e-learning. The paper investigates ICT as a tool empowering and developing learners lifelong learning opportunities. It defines a model of…

Challenges of Blended E-Learning Tools in Mathematics: Students' Perspectives University of Uyo

ERIC Educational Resources Information Center

Umoh, Joseph B.; Akpan, Ekemini T.

2014-01-01

An in-depth knowledge of pedagogical approaches can help improve the formulation of effective and efficient pedagogy, tools and technology to support and enhance the teaching and learning of Mathematics in higher institutions. This study investigated students' perceptions of the challenges of blended e-learning tools in the teaching and learning…

A Case Study of Using a Social Annotation Tool to Support Collaboratively Learning

ERIC Educational Resources Information Center

Gao, Fei

2013-01-01

The purpose of the study was to understand student interaction and learning supported by a collaboratively social annotation tool--Diigo. The researcher examined through a case study how students participated and interacted when learning an online text with the social annotation tool--Diigo, and how they perceived their experience. The findings…

Effects of supplementary lighting by natural light for growth of Brassica chinensis

NASA Astrophysics Data System (ADS)

Yeh, Shih-Chuan; Lee, Hui-Ping; Kao, Shih-Tse; Lu, Ju-Lin

2016-04-01

This paper present a model of cultivated chamber with supplementary natural colour light. We investigate the effects of supplementary natural red light and natural blue light on growth of Brassica chinensis under natural white light illumination. After 4 weeks of supplementary colour light treatment, the experiment results shown that the weight of fresh leaf were not affected by supplementary natural blue light. However, those Brassica chinensis were cultivated in the chambers with supplementary natural red light obtained a significant increasing of fresh weight of leaf under both white light illuminate models. The combination of natural white light with supplementary natural red light illumination will be benefits in growth for cultivation and energy saving.

Convolutional neural network architectures for predicting DNA–protein binding

PubMed Central

Zeng, Haoyang; Edwards, Matthew D.; Liu, Ge; Gifford, David K.

2016-01-01

Motivation: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA–protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth understanding of how to match CNN architecture to a given task is needed to fully harness the power of CNNs for computational biology applications. Results: We present a systematic exploration of CNN architectures for predicting DNA sequence binding using a large compendium of transcription factor datasets. We identify the best-performing architectures by varying CNN width, depth and pooling designs. We find that adding convolutional kernels to a network is important for motif-based tasks. We show the benefits of CNNs in learning rich higher-order sequence features, such as secondary motifs and local sequence context, by comparing network performance on multiple modeling tasks ranging in difficulty. We also demonstrate how careful construction of sequence benchmark datasets, using approaches that control potentially confounding effects like positional or motif strength bias, is critical in making fair comparisons between competing methods. We explore how to establish the sufficiency of training data for these learning tasks, and we have created a flexible cloud-based framework that permits the rapid exploration of alternative neural network architectures for problems in computational biology. Availability and Implementation: All the models analyzed are available at http://cnn.csail.mit.edu. Contact: gifford@mit.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307608

Scholarship Opportunities for Trainees and Clinician Educators: Learning Outcomes from a Case Report Writing Workshop

PubMed Central

Sridhar, Arun R. Mahankali; Willett, Lisa L.; Castiglioni, Analia; Heudebert, Gustavo; Landry, Michael; Centor, Robert M.

2008-01-01

Introduction Publishing a case report demonstrates scholarly productivity for trainees and clinician-educators. Aim To assess the learning outcomes from a case report writing workshop. Setting Medical students, residents, fellows and clinician-educators attending a workshop. Program Description Case report writing workshop conducted nine times at different venues. Program Evaluation Before and after each workshop, participants self-rated their perceived competence to write a case report, likelihood of submitting a case report to a meeting or for publication in the next 6–12 months, and perceived career benefit of writing a case report (on a five-point Likert scale). The 214 participants were from 3 countries and 27 states or provinces; most participants were trainees (64.5 %). Self-rated competence for writing a case report improved from a mean of 2.5 to 3.5 (a 0.99 increase; 95% CI, 0.88–1.12, p < 0.001). The perceived likelihood of submitting a case report, and the perceived career benefit of writing one, also showed statistically significant improvements (p = 0.002, p = 0.001; respectively). Nine of 98 participants published a case report 16–41 months after workshop completion. Discussion The workshop increased participants’ perception that they could present or publish a case report. Electronic Supplementary Material The online version of this article (doi:10.1007/s11606-008-0873-9) contains supplementary material, which is available to authorized users. PMID:19104902

Performance Assessment and Translation of Physiologically Based Pharmacokinetic Models From acslX to Berkeley Madonna, MATLAB, and R Language: Oxytetracycline and Gold Nanoparticles As Case Examples.

PubMed

Lin, Zhoumeng; Jaberi-Douraki, Majid; He, Chunla; Jin, Shiqiang; Yang, Raymond S H; Fisher, Jeffrey W; Riviere, Jim E

2017-07-01

Many physiologically based pharmacokinetic (PBPK) models for environmental chemicals, drugs, and nanomaterials have been developed to aid risk and safety assessments using acslX. However, acslX has been rendered sunset since November 2015. Alternative modeling tools and tutorials are needed for future PBPK applications. This forum article aimed to: (1) demonstrate the performance of 4 PBPK modeling software packages (acslX, Berkeley Madonna, MATLAB, and R language) tested using 2 existing models (oxytetracycline and gold nanoparticles); (2) provide a tutorial of PBPK model code conversion from acslX to Berkeley Madonna, MATLAB, and R language; (3) discuss the advantages and disadvantages of each software package in the implementation of PBPK models in toxicology, and (4) share our perspective about future direction in this field. Simulation results of plasma/tissue concentrations/amounts of oxytetracycline and gold from different models were compared visually and statistically with linear regression analyses. Simulation results from the original models were correlated well with results from the recoded models, with time-concentration/amount curves nearly superimposable and determination coefficients of 0.86-1.00. Step-by-step explanations of the recoding of the models in different software programs are provided in the Supplementary Data. In summary, this article presents a tutorial of PBPK model code conversion for a small molecule and a nanoparticle among 4 software packages, and a performance comparison of these software packages in PBPK model implementation. This tutorial helps beginners learn PBPK modeling, provides suggestions for selecting a suitable tool for future projects, and may lead to the transition from acslX to alternative modeling tools. © The Author 2017. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

EMHP: an accurate automated hole masking algorithm for single-particle cryo-EM image processing.

PubMed

Berndsen, Zachary; Bowman, Charles; Jang, Haerin; Ward, Andrew B

2017-12-01

The Electron Microscopy Hole Punch (EMHP) is a streamlined suite of tools for quick assessment, sorting and hole masking of electron micrographs. With recent advances in single-particle electron cryo-microscopy (cryo-EM) data processing allowing for the rapid determination of protein structures using a smaller computational footprint, we saw the need for a fast and simple tool for data pre-processing that could run independent of existing high-performance computing (HPC) infrastructures. EMHP provides a data preprocessing platform in a small package that requires minimal python dependencies to function. https://www.bitbucket.org/chazbot/emhp Apache 2.0 License. bowman@scripps.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

FRED 2: an immunoinformatics framework for Python.

PubMed

Schubert, Benjamin; Walzer, Mathias; Brachvogel, Hans-Philipp; Szolek, András; Mohr, Christopher; Kohlbacher, Oliver

2016-07-01

Immunoinformatics approaches are widely used in a variety of applications from basic immunological to applied biomedical research. Complex data integration is inevitable in immunological research and usually requires comprehensive pipelines including multiple tools and data sources. Non-standard input and output formats of immunoinformatics tools make the development of such applications difficult. Here we present FRED 2, an open-source immunoinformatics framework offering easy and unified access to methods for epitope prediction and other immunoinformatics applications. FRED 2 is implemented in Python and designed to be extendable and flexible to allow rapid prototyping of complex applications. FRED 2 is available at http://fred-2.github.io schubert@informatik.uni-tuebingen.de Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Lifelong Learning Organisers: Requirements for Tools for Supporting Episodic and Semantic Learning

ERIC Educational Resources Information Center

Vavoula, Giasemi; Sharples, Mike

2009-01-01

We propose Lifelong Learning Organisers (LLOs) as tools to support the capturing, organisation and retrieval of personal learning experiences, resources and notes, over a range of learning topics, at different times and places. The paper discusses general requirements for the design of LLOs based on findings from a diary-based study of everyday…

Rapid e-Learning Tools Selection Process for Cognitive and Psychomotor Learning Objectives

ERIC Educational Resources Information Center

Ku, David Tawei; Huang, Yung-Hsin

2012-01-01

This study developed a decision making process for the selection of rapid e-learning tools that could match different learning domains. With the development of the Internet, the speed of information updates has become faster than ever. E-learning has rapidly become the mainstream for corporate training and academic instruction. In order to reduce…

Designing a Moodle Course with the CADMOS Learning Design Tool

ERIC Educational Resources Information Center

Katsamani, Maria; Retalis, Symeon; Boloudakis, Michail

2012-01-01

CADMOS is a graphical learning design (LD) authoring tool that helps a teacher design a unit of learning in two layers: (i) the conceptual layer, which seems like a concept map and contains the learning activities with their associated learning resources and (ii) the flow layer, which contains the orchestration of these activities. One of CADMOS'…

Integrating Concept Mapping into Information Systems Education for Meaningful Learning and Assessment

ERIC Educational Resources Information Center

Wei, Wei; Yue, Kwok-Bun

2017-01-01

Concept map (CM) is a theoretically sound yet easy to learn tool and can be effectively used to represent knowledge. Even though many disciplines have adopted CM as a teaching and learning tool to improve learning effectiveness, its application in IS curriculum is sparse. Meaningful learning happens when one iteratively integrates new concepts and…

Effects of Online Interaction via Computer-Mediated Communication (CMC) Tools on an E-Mathematics Learning Outcome

ERIC Educational Resources Information Center

Okonta, Olomeruom

2010-01-01

Recent research studies in open and distance learning have focused on the differences between traditional learning versus online learning, the benefits of computer-mediated communication (CMC) tools in an e-learning environment, and the relationship between online discussion posts and students' achievement. In fact, there is an extant…

Lessons learned applying CASE methods/tools to Ada software development projects

NASA Technical Reports Server (NTRS)

Blumberg, Maurice H.; Randall, Richard L.

1993-01-01

This paper describes the lessons learned from introducing CASE methods/tools into organizations and applying them to actual Ada software development projects. This paper will be useful to any organization planning to introduce a software engineering environment (SEE) or evolving an existing one. It contains management level lessons learned, as well as lessons learned in using specific SEE tools/methods. The experiences presented are from Alpha Test projects established under the STARS (Software Technology for Adaptable and Reliable Systems) project. They reflect the front end efforts by those projects to understand the tools/methods, initial experiences in their introduction and use, and later experiences in the use of specific tools/methods and the introduction of new ones.

Neural substrates of visuomotor learning based on improved feedback control and prediction

PubMed Central

Grafton, Scott T.; Schmitt, Paul; Horn, John Van; Diedrichsen, Jörn

2008-01-01

Motor skills emerge from learning feedforward commands as well as improvements in feedback control. These two components of learning were investigated in a compensatory visuomotor tracking task on a trial-by-trial basis. Between trial learning was characterized with a state-space model to provide smoothed estimates of feedforward and feedback learning, separable from random fluctuations in motor performance and error. The resultant parameters were correlated with brain activity using magnetic resonance imaging. Learning related to the generation of a feedforward command correlated with activity in dorsal premotor cortex, inferior parietal lobule, supplementary motor area and cingulate motor area, supporting a role of these areas in retrieving and executing a predictive motor command. Modulation of feedback control was associated with activity in bilateral posterior superior parietal lobule as well as right ventral premotor cortex. Performance error correlated with activity in a widespread cortical and subcortical network including bilateral parietal, premotor and rostral anterior cingulate cortex as well as the cerebellar cortex. Finally, trial-by-trial changes of kinematics, as measured by mean absolute hand acceleration, correlated with activity in motor cortex and anterior cerebellum. The results demonstrate that incremental, learning dependent changes can be modeled on a trial-by-trial basis and neural substrates for feedforward control of novel motor programs are localized to secondary motor areas. PMID:18032069

Educational Tools: Thinking Outside the Box

PubMed Central

Woods, Majka

2016-01-01

The understanding, study, and use of educational tools and their application to the education of adults in professional fields are increasingly important. In this review, we have compiled a description of educational tools on the basis of the teaching and learning setting: the classroom, simulation center, hospital or clinic, and independent learning space. When available, examples of tools used in nephrology are provided. We emphasize that time should be taken to consider the goals of the educational activity and the type of learners and use the most appropriate tools needed to meet the goals. Constant reassessment of tools is important to discover innovation and reforms that improve teaching and learning. PMID:26536900

Interactive, technology-enhanced self-regulated learning tools in healthcare education: a literature review.

PubMed

Petty, Julia

2013-01-01

Learning technology is increasingly being implemented for programmes of blended learning within nurse education. With a growing emphasis on self-directed study particularly in post-basic education, there is a need for learners to be guided in their learning away from practice and limited classroom time. Technology-enabled (TE) tools which engage learners actively can play a part in this. The effectiveness and value of interactive TE learning strategies within healthcare is the focus of this paper. To identify literature that explores the effectiveness of interactive, TE tools on knowledge acquisition and learner satisfaction within healthcare with a view to evaluating their use for post-basic nurse education. A Literature Review was performed focusing on papers exploring the comparative value and perceived benefit of TE tools compared to traditional modes of learning within healthcare. The Databases identified as most suitable due to their relevance to healthcare were accessed through EBSCOhost. Primary, Boolean and advanced searches on key terms were undertaken. Inclusion and exclusion criteria were applied which resulted in a final selection of 11 studies for critique. Analysis of the literature found that knowledge acquisition in most cases was enhanced and measured learner satisfaction was generally positive for interactive, self-regulated TE tools. However, TE education may not suit all learners and this is critiqued in the light of the identified limitations. Interactive self regulation and/or testing can be a valuable learning strategy that can be incorporated into self-directed programmes of study for post-registration learners. Whilst acknowledging the learning styles not suited to such tools, the concurrent use of self-directed TE tools with those learning strategies necessitating a more social presence can work together to support enhancement of knowledge required to deliver rationale for nursing practice. Copyright © 2012 Elsevier Ltd. All rights reserved.

The Reliability of Tweets as a Supplementary Method of Seasonal Influenza Surveillance

PubMed Central

Aslam, Anoshé A; Spitzberg, Brian H; An, Li; Gawron, J Mark; Gupta, Dipak K; Peddecord, K Michael; Nagel, Anna C; Allen, Christopher; Yang, Jiue-An; Lindsay, Suzanne

2014-01-01

Background Existing influenza surveillance in the United States is focused on the collection of data from sentinel physicians and hospitals; however, the compilation and distribution of reports are usually delayed by up to 2 weeks. With the popularity of social media growing, the Internet is a source for syndromic surveillance due to the availability of large amounts of data. In this study, tweets, or posts of 140 characters or less, from the website Twitter were collected and analyzed for their potential as surveillance for seasonal influenza. Objective There were three aims: (1) to improve the correlation of tweets to sentinel-provided influenza-like illness (ILI) rates by city through filtering and a machine-learning classifier, (2) to observe correlations of tweets for emergency department ILI rates by city, and (3) to explore correlations for tweets to laboratory-confirmed influenza cases in San Diego. Methods Tweets containing the keyword “flu” were collected within a 17-mile radius from 11 US cities selected for population and availability of ILI data. At the end of the collection period, 159,802 tweets were used for correlation analyses with sentinel-provided ILI and emergency department ILI rates as reported by the corresponding city or county health department. Two separate methods were used to observe correlations between tweets and ILI rates: filtering the tweets by type (non-retweets, retweets, tweets with a URL, tweets without a URL), and the use of a machine-learning classifier that determined whether a tweet was “valid”, or from a user who was likely ill with the flu. Results Correlations varied by city but general trends were observed. Non-retweets and tweets without a URL had higher and more significant (P<.05) correlations than retweets and tweets with a URL. Correlations of tweets to emergency department ILI rates were higher than the correlations observed for sentinel-provided ILI for most of the cities. The machine-learning classifier yielded the highest correlations for many of the cities when using the sentinel-provided or emergency department ILI as well as the number of laboratory-confirmed influenza cases in San Diego. High correlation values (r=.93) with significance at P<.001 were observed for laboratory-confirmed influenza cases for most categories and tweets determined to be valid by the classifier. Conclusions Compared to tweet analyses in the previous influenza season, this study demonstrated increased accuracy in using Twitter as a supplementary surveillance tool for influenza as better filtering and classification methods yielded higher correlations for the 2013-2014 influenza season than those found for tweets in the previous influenza season, where emergency department ILI rates were better correlated to tweets than sentinel-provided ILI rates. Further investigations in the field would require expansion with regard to the location that the tweets are collected from, as well as the availability of more ILI data. PMID:25406040

Effects of dividing attention on memory for declarative and procedural aspects of tool use.

PubMed

Roy, Shumita; Park, Norman W

2016-07-01

Tool-related knowledge and skills are supported by a complex set of memory processes that are not well understood. Some aspects of tools are mediated by either declarative or procedural memory, while other aspects may rely on an interaction of both systems. Although motor skill learning is believed to be primarily supported by procedural memory, there is debate in the current literature regarding the role of declarative memory. Growing evidence suggests that declarative memory may be involved during early stages of motor skill learning, although findings have been mixed. In the current experiment, healthy, younger adults were trained to use a set of novel complex tools and were tested on their memory for various aspects of the tools. Declarative memory encoding was interrupted by dividing attention during training. Findings showed that dividing attention during training was detrimental for subsequent memory for tool attributes as well as accurate demonstration of tool use and tool grasping. However, dividing attention did not interfere with motor skill learning, suggesting that declarative memory is not essential for skill learning associated with tools.

Sustaining Teacher Control in a Blog-Based Personal Learning Environment

ERIC Educational Resources Information Center

Tomberg, Vladimir; Laanpere, Mart; Ley, Tobias; Normak, Peeter

2013-01-01

Various tools and services based on Web 2.0 (mainly blogs, wikis, social networking tools) are increasingly used in formal education to create personal learning environments, providing self-directed learners with more freedom, choice, and control over their learning. In such distributed and personalized learning environments, the traditional role…

Orchestration of Social Modes in E-Learning

ERIC Educational Resources Information Center

Weinberger, Armin; Papadopoulos, Pantelis M.

2016-01-01

The concept of orchestration has recently emerged as a useful metaphor in technology-enhanced learning research communities, because of its explanatory power and appeal in describing how different learning activities, tools, and arrangements could be combined to promote learning. More than a buffet of tools offering possibilities to the teachers,…

Web-Based Learning Design Tool

ERIC Educational Resources Information Center

Bruno, F. B.; Silva, T. L. K.; Silva, R. P.; Teixeira, F. G.

2012-01-01

Purpose: The purpose of this paper is to propose a web-based tool that enables the development and provision of learning designs and its reuse and re-contextualization as generative learning objects, aimed at developing educational materials. Design/methodology/approach: The use of learning objects can facilitate the process of production and…

From Presentation to Interaction: New Goals for Online Learning Technologies

ERIC Educational Resources Information Center

Tu, Chih-Hsiung

2005-01-01

Educators have used online technology in the past as information presentation tools and information storage tools to support learning. Researchers identify online technologies with large capacities and capabilities to enhance human learning in an interactive fashion. Online learning technology should move away from the use of computer technology…

Mobile Adaptive Communication Support for Vocabulary Acquisition

ERIC Educational Resources Information Center

Epp, Carrie Demmans

2014-01-01

This work explores the use of an adaptive mobile tool for language learning. A school-based deployment study showed that the tool supported learning. A second study is being conducted in informal learning environments. Current work focuses on building models that increase our understanding of the relationship between application usage and learning.

Advancing Research in Second Language Writing through Computational Tools and Machine Learning Techniques: A Research Agenda

ERIC Educational Resources Information Center

Crossley, Scott A.

2013-01-01

This paper provides an agenda for replication studies focusing on second language (L2) writing and the use of natural language processing (NLP) tools and machine learning algorithms. Specifically, it introduces a range of the available NLP tools and machine learning algorithms and demonstrates how these could be used to replicate seminal studies…

A Tale of Two Communication Tools: Discussion-Forum and Mobile Instant-Messaging Apps in Collaborative Learning

ERIC Educational Resources Information Center

Sun, Zhong; Lin, Chin-Hsi; Wu, Minhua; Zhou, Jianshe; Luo, Liming

2018-01-01

Computer-supported collaborative learning (CSCL) has shown considerable promise, but thus far the literature has tended to focus on individual technological tools, without due regard for how the choice of one such tool over another impacts CSCL, either in outline or in detail. The present study, therefore, directly compared the learning-related…

A Silent Revolution: From Sketching to Coding--A Case Study on Code-Based Design Tool Learning

ERIC Educational Resources Information Center

Xu, Song; Fan, Kuo-Kuang

2017-01-01

Along with the information technology rising, Computer Aided Design activities are becoming more modern and more complex. But learning how to operation these new design tools has become the main problem lying in front of each designer. This study was purpose on finding problems encountered during code-based design tools learning period of…

Understanding the Effects of Databases as Cognitive Tools in a Problem-Based Multimedia Learning Environment

ERIC Educational Resources Information Center

Li, Rui; Liu, Min

2007-01-01

The purpose of this study is to examine the potential of using computer databases as cognitive tools to share learners' cognitive load and facilitate learning in a multimedia problem-based learning (PBL) environment designed for sixth graders. Two research questions were: (a) can the computer database tool share sixth-graders' cognitive load? and…

The Right Tools for the Job--Technology Options for Adult Online Learning and Collaboration

ERIC Educational Resources Information Center

Regional Educational Laboratory, 2014

2014-01-01

Many options exist for using technology as a tool for adult learning, and each day, it becomes easier to share information online than it ever has been. Online learning technology has grown from one-sided communications to numerous options for audience engagement and interactivity. This guide introduces a variety of tools, online platforms, and…

Preservice Teachers' Perceptions about Using Mobile Phones and Laptops in Education as Mobile Learning Tools

ERIC Educational Resources Information Center

Sad, Süleyman Nihat; Göktas, Özlem

2014-01-01

The purpose of this research was to investigate preservice teachers' perceptions about using m-phones and laptops in education as mobile learning tools. A total of 1087 preservice teachers participated in the study. The results indicated that preservice teachers perceived laptops potentially stronger than m-phones as m-learning tools. In…

Assessment of minimum permissible geometrical parameters of a near-to-eye display.

PubMed

Valyukh, Sergiy; Slobodyanyuk, Oleksandr

2015-07-20

Light weight and small dimensions are some of the most important characteristics of near-to-eye displays (NEDs). These displays consist of two basic parts: a microdisplay for generating an image and supplementary optics in order to see the image. Nowadays, the pixel size of microdisplays may be less than 4 μm, which makes the supplementary optics the major factor in defining restrictions on a NED dimensions or at least on the distance between the microdisplay and the eye. The goal of the present work is to find answers to the following two questions: how small this distance can be in principle and what is the microdisplay maximum resolution that stays effective to see through the supplementary optics placed in immediate vicinity of the eye. To explore the first question, we consider an aberration-free magnifier, which is the initial stage in elaboration of a real optical system. In this case, the paraxial approximation and the transfer matrix method are ideal tools for simulation of light propagation from the microdisplay through the magnifier and the human eye's optical system to the retina. The human eye is considered according to the Gullstrand model. Parameters of the magnifier, its location with respect to the eye and the microdisplay, and the depth of field, which can be interpreted as the tolerance of the microdisplay position, are determined and discussed. The second question related to the microdisplay maximum resolution is investigated by using the principles of wave optics.

High School Online: Pedagogy, Preferences, and Practices of Three Online Teachers

ERIC Educational Resources Information Center

Kerr, Shantia

2011-01-01

This multiple case study explores how three online, high school teachers used technological tools to create meaningful learning activities for their students. Findings reveal that teachers use a wide variety of tools and approaches to online learning. Tools are categorized as content, communication, and management tools. Approaches include…

Recommender System and Web 2.0 Tools to Enhance a Blended Learning Model

ERIC Educational Resources Information Center

Hoic-Bozic, Natasa; Dlab, Martina Holenko; Mornar, Vedran

2016-01-01

Blended learning models that combine face-to-face and online learning are of great importance in modern higher education. However, their development should be in line with the recent changes in e-learning that emphasize a student-centered approach and use tools available on the Web to support the learning process. This paper presents research on…

Visual Literacy Skills of Students in College-Level Biology: Learning Outcomes Following Digital or Hand-Drawing Activities

ERIC Educational Resources Information Center

Bell, Justine C.

2014-01-01

To test the claim that digital learning tools enhance the acquisition of visual literacy in this generation of biology students, a learning intervention was carried out with 33 students enrolled in an introductory college biology course. This study compared learning outcomes following two types of learning tools: a traditional drawing activity, or…

The Learning Loss Scale as an Assessment Tool: An Empirical Examination of Convergent Validity with Performative Measures

ERIC Educational Resources Information Center

Hooker, John; Denker, Katherine

2014-01-01

Higher education has placed an increasingly greater value on assessment. The Learning Loss Scale may be an appropriate tool to assess learning across disciplines. In this paper, we review the culture of assessment, conceptualizations of cognitive learning, the Learning Loss Scale, and a theoretical explanation, and then we test this measure to…

Designing Web 2.0 Based Constructivist-Oriented E-Learning Units

ERIC Educational Resources Information Center

Chai, Ching Sing; Woo, Huay Lit; Wang, Qiyun

2010-01-01

Purpose: The main purpose of this paper is to present how meaningful e-learning units can be created by using an online tool called Meaningful E-learning Units (MeLU). The paper also aims to describe how created e-learning units can be shared by teachers and students. Design/methodology/approach: This tool can help to produce e-learning units that…

Ant colony optimization algorithm for interpretable Bayesian classifiers combination: application to medical predictions.

PubMed

Bouktif, Salah; Hanna, Eileen Marie; Zaki, Nazar; Abu Khousa, Eman

2014-01-01

Prediction and classification techniques have been well studied by machine learning researchers and developed for several real-word problems. However, the level of acceptance and success of prediction models are still below expectation due to some difficulties such as the low performance of prediction models when they are applied in different environments. Such a problem has been addressed by many researchers, mainly from the machine learning community. A second problem, principally raised by model users in different communities, such as managers, economists, engineers, biologists, and medical practitioners, etc., is the prediction models' interpretability. The latter is the ability of a model to explain its predictions and exhibit the causality relationships between the inputs and the outputs. In the case of classification, a successful way to alleviate the low performance is to use ensemble classiers. It is an intuitive strategy to activate collaboration between different classifiers towards a better performance than individual classier. Unfortunately, ensemble classifiers method do not take into account the interpretability of the final classification outcome. It even worsens the original interpretability of the individual classifiers. In this paper we propose a novel implementation of classifiers combination approach that does not only promote the overall performance but also preserves the interpretability of the resulting model. We propose a solution based on Ant Colony Optimization and tailored for the case of Bayesian classifiers. We validate our proposed solution with case studies from medical domain namely, heart disease and Cardiotography-based predictions, problems where interpretability is critical to make appropriate clinical decisions. The datasets, Prediction Models and software tool together with supplementary materials are available at http://faculty.uaeu.ac.ae/salahb/ACO4BC.htm.

Deep learning-based subdivision approach for large scale macromolecules structure recovery from electron cryo tomograms.

PubMed

Xu, Min; Chai, Xiaoqi; Muthakana, Hariank; Liang, Xiaodan; Yang, Ge; Zeev-Ben-Mordehai, Tzviya; Xing, Eric P

2017-07-15

Cellular Electron CryoTomography (CECT) enables 3D visualization of cellular organization at near-native state and in sub-molecular resolution, making it a powerful tool for analyzing structures of macromolecular complexes and their spatial organizations inside single cells. However, high degree of structural complexity together with practical imaging limitations makes the systematic de novo discovery of structures within cells challenging. It would likely require averaging and classifying millions of subtomograms potentially containing hundreds of highly heterogeneous structural classes. Although it is no longer difficult to acquire CECT data containing such amount of subtomograms due to advances in data acquisition automation, existing computational approaches have very limited scalability or discrimination ability, making them incapable of processing such amount of data. To complement existing approaches, in this article we propose a new approach for subdividing subtomograms into smaller but relatively homogeneous subsets. The structures in these subsets can then be separately recovered using existing computation intensive methods. Our approach is based on supervised structural feature extraction using deep learning, in combination with unsupervised clustering and reference-free classification. Our experiments show that, compared with existing unsupervised rotation invariant feature and pose-normalization based approaches, our new approach achieves significant improvements in both discrimination ability and scalability. More importantly, our new approach is able to discover new structural classes and recover structures that do not exist in training data. Source code freely available at http://www.cs.cmu.edu/∼mxu1/software . mxu1@cs.cmu.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

SpliceRover: Interpretable Convolutional Neural: Networks for Improved Splice Site Prediction.

PubMed

Zuallaert, Jasper; Godin, Fréderic; Kim, Mijung; Soete, Arne; Saeys, Yvan; De Neve, Wesley

2018-06-21

During the last decade, improvements in high-throughput sequencing have generated a wealth of genomic data. Functionally interpreting these sequences and finding the biological signals that are hallmarks of gene function and regulation is currently mostly done using automated genome annotation platforms, which mainly rely on integrated machine learning frameworks to identify different functional sites of interest, including splice sites. Splicing is an essential step in the gene regulation process, and the correct identification of splice sites is a major cornerstone in a genome annotation system. In this paper, we present SpliceRover, a predictive deep learning approach that outperforms the state-of-the-art in splice site prediction. SpliceRover uses convolutional neural networks (CNNs), which have been shown to obtain cutting edge performance on a wide variety of prediction tasks. We adapted this approach to deal with genomic sequence inputs, and show it consistently outperforms already existing approaches, with relative improvements in prediction effectiveness of up to 80.9% when measured in terms of false discovery rate. However, a major criticism of CNNs concerns their "black box" nature, as mechanisms to obtain insight into their reasoning processes are limited. To facilitate interpretability of the SpliceRover models, we introduce an approach to visualize the biologically relevant information learnt. We show that our visualization approach is able to recover features known to be important for splice site prediction (binding motifs around the splice site, presence of polypyrimidine tracts and branch points), as well as reveal new features (e.g., several types of exclusion patterns near splice sites). SpliceRover is available as a web service. The prediction tool and instructions can be found at http://bioit2.irc.ugent.be/splicerover/. Supplementary materials are available at Bioinformatics online.

Machine learning for the structure–energy–property landscapes of molecular crystals† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc04665k

PubMed Central

Yang, Jack; Campbell, Joshua E.; Day, Graeme M.; Ceriotti, Michele

2017-01-01

Molecular crystals play an important role in several fields of science and technology. They frequently crystallize in different polymorphs with substantially different physical properties. To help guide the synthesis of candidate materials, atomic-scale modelling can be used to enumerate the stable polymorphs and to predict their properties, as well as to propose heuristic rules to rationalize the correlations between crystal structure and materials properties. Here we show how a recently-developed machine-learning (ML) framework can be used to achieve inexpensive and accurate predictions of the stability and properties of polymorphs, and a data-driven classification that is less biased and more flexible than typical heuristic rules. We discuss, as examples, the lattice energy and property landscapes of pentacene and two azapentacene isomers that are of interest as organic semiconductor materials. We show that we can estimate force field or DFT lattice energies with sub-kJ mol–1 accuracy, using only a few hundred reference configurations, and reduce by a factor of ten the computational effort needed to predict charge mobility in the crystal structures. The automatic structural classification of the polymorphs reveals a more detailed picture of molecular packing than that provided by conventional heuristics, and helps disentangle the role of hydrogen bonded and π-stacking interactions in determining molecular self-assembly. This observation demonstrates that ML is not just a black-box scheme to interpolate between reference calculations, but can also be used as a tool to gain intuitive insights into structure–property relations in molecular crystal engineering. PMID:29675175

Tool Use of Experienced Learners in Computer-Based Learning Environments: Can Tools Be Beneficial?

ERIC Educational Resources Information Center

Juarez Collazo, Norma A.; Corradi, David; Elen, Jan; Clarebout, Geraldine

2014-01-01

Research has documented the use of tools in computer-based learning environments as problematic, that is, learners do not use the tools and when they do, they tend to do it suboptimally. This study attempts to disentangle cause and effect of this suboptimal tool use for experienced learners. More specifically, learner variables (metacognitive and…

[Computer-assisted education in problem-solving in neurology; a randomized educational study].

PubMed

Weverling, G J; Stam, J; ten Cate, T J; van Crevel, H

1996-02-24

To determine the effect of computer-based medical teaching (CBMT) as a supplementary method to teach clinical problem-solving during the clerkship in neurology. Randomized controlled blinded study. Academic Medical Centre, Amsterdam, the Netherlands. 103 Students were assigned at random to a group with access to CBMT and a control group. CBMT consisted of 20 computer-simulated patients with neurological diseases, and was permanently available during five weeks to students in the CBMT group. The ability to recognize and solve neurological problems was assessed with two free-response tests, scored by two blinded observers. The CBMT students scored significantly better on the test related to the CBMT cases (mean score 7.5 on a zero to 10 point scale; control group 6.2; p < 0.001). There was no significant difference on the control test not related to the problems practised with CBMT. CBMT can be an effective method for teaching clinical problem-solving, when used as a supplementary teaching facility during a clinical clerkship. The increased ability to solve problems learned by CBMT had no demonstrable effect on the performance with other neurological problems.

HEALER: homomorphic computation of ExAct Logistic rEgRession for secure rare disease variants analysis in GWAS

PubMed Central

Wang, Shuang; Zhang, Yuchen; Dai, Wenrui; Lauter, Kristin; Kim, Miran; Tang, Yuzhe; Xiong, Hongkai; Jiang, Xiaoqian

2016-01-01

Motivation: Genome-wide association studies (GWAS) have been widely used in discovering the association between genotypes and phenotypes. Human genome data contain valuable but highly sensitive information. Unprotected disclosure of such information might put individual’s privacy at risk. It is important to protect human genome data. Exact logistic regression is a bias-reduction method based on a penalized likelihood to discover rare variants that are associated with disease susceptibility. We propose the HEALER framework to facilitate secure rare variants analysis with a small sample size. Results: We target at the algorithm design aiming at reducing the computational and storage costs to learn a homomorphic exact logistic regression model (i.e. evaluate P-values of coefficients), where the circuit depth is proportional to the logarithmic scale of data size. We evaluate the algorithm performance using rare Kawasaki Disease datasets. Availability and implementation: Download HEALER at http://research.ucsd-dbmi.org/HEALER/ Contact: shw070@ucsd.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26446135

48 CFR 836.576 - Supplementary labor standards provisions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 5 2010-10-01 2010-10-01 false Supplementary labor... 836.576 Supplementary labor standards provisions. The contracting officer shall insert the clause at 852.236-85, Supplementary labor standards provisions, in solicitations and contracts for construction...

Problem-Centered Supplemental Instruction in Biology: Influence on Content Recall, Content Understanding, and Problem Solving Ability

NASA Astrophysics Data System (ADS)

Gardner, Joel; Belland, Brian R.

2017-08-01

To address the need for effective, efficient ways to apply active learning in undergraduate biology courses, in this paper, we propose a problem-centered approach that utilizes supplemental web-based instructional materials based on principles of active learning. We compared two supplementary web-based modules using active learning strategies: the first used Merrill's First Principles of Instruction as a framework for organizing multiple active learning strategies; the second used a traditional web-based approach. Results indicated that (a) the First Principles group gained significantly from pretest to posttest at the Remember level ( t(40) = -1.432, p = 0.08, ES = 0.4) and at the Problem Solving level ( U = 142.5, N1 = 21, N2 = 21, p = .02, ES = 0.7) and (b) the Traditional group gained significantly from pretest to posttest at the Remember level ( t(36) = 1.762, p = 0.043, ES = 0.6). Those in the First Principles group were significantly more likely than the traditional group to be confident in their ability to solve problems in the future (χ2 (2, N = 40) = 3.585, p = 0.09).

Medical students' online learning technology needs.

PubMed

Han, Heeyoung; Nelson, Erica; Wetter, Nathan

2014-02-01

This study investigated medical students' online learning technology needs at a medical school. The study aimed to provide evidence-based guidance for technology selection and online learning design in medical education. The authors developed a 120-item survey in collaboration with the New Technology in Medical Education (NTIME) committee at the Southern Illinois University School of Medicine (SIUSOM). Overall, 123 of 290 medical students (42%) at the medical school participated in the survey. The survey focused on five major areas: students' hardware and software use; perception of educational technology (ET) in general; online behaviours; perception of ET use at the school; and demographic information. Students perceived multimedia tools, scheduling tools, communication tools, collaborative authoring tools, learning management systems and electronic health records useful educational technologies for their learning. They did not consider social networking tools useful for their learning, despite their frequent use. Third-year students were less satisfied with current technology integration in the curriculum, information sharing and collaborative learning than other years. Students in clerkships perceived mobile devices as useful for their learning. Students using a mobile device (i.e. a smartphone) go online, text message, visit social networking sites and are online during classes more frequently than non-users. Medical students' ET needs differ between preclinical and clinical years. Technology supporting ubiquitous mobile learning and health information technology (HIT) systems at hospitals and out-patient clinics can be integrated into clerkship curricula. © 2014 John Wiley & Sons Ltd.

PORTAAL: A Classroom Observation Tool Assessing Evidence-Based Teaching Practices for Active Learning in Large Science, Technology, Engineering, and Mathematics Classes

PubMed Central

Eddy, Sarah L.; Converse, Mercedes; Wenderoth, Mary Pat

2015-01-01

There is extensive evidence that active learning works better than a completely passive lecture. Despite this evidence, adoption of these evidence-based teaching practices remains low. In this paper, we offer one tool to help faculty members implement active learning. This tool identifies 21 readily implemented elements that have been shown to increase student outcomes related to achievement, logic development, or other relevant learning goals with college-age students. Thus, this tool both clarifies the research-supported elements of best practices for instructor implementation of active learning in the classroom setting and measures instructors’ alignment with these practices. We describe how we reviewed the discipline-based education research literature to identify best practices in active learning for adult learners in the classroom and used these results to develop an observation tool (Practical Observation Rubric To Assess Active Learning, or PORTAAL) that documents the extent to which instructors incorporate these practices into their classrooms. We then use PORTAAL to explore the classroom practices of 25 introductory biology instructors who employ some form of active learning. Overall, PORTAAL documents how well aligned classrooms are with research-supported best practices for active learning and provides specific feedback and guidance to instructors to allow them to identify what they do well and what could be improved. PMID:26033871

PORTAAL: A Classroom Observation Tool Assessing Evidence-Based Teaching Practices for Active Learning in Large Science, Technology, Engineering, and Mathematics Classes

ERIC Educational Resources Information Center

Eddy, Sarah L.; Converse, Mercedes; Wenderoth, Mary Pat

2015-01-01

There is extensive evidence that active learning works better than a completely passive lecture. Despite this evidence, adoption of these evidence-based teaching practices remains low. In this paper, we offer one tool to help faculty members implement active learning. This tool identifies 21 readily implemented elements that have been shown to…

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments

PubMed Central

MacLean, Brendan; Tomazela, Daniela M.; Shulman, Nicholas; Chambers, Matthew; Finney, Gregory L.; Frewen, Barbara; Kern, Randall; Tabb, David L.; Liebler, Daniel C.; MacCoss, Michael J.

2010-01-01

Summary: Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Availability: Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project. Contact: brendanx@u.washington.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20147306

COMPADRE: an R and web resource for pathway activity analysis by component decompositions.

PubMed

Ramos-Rodriguez, Roberto-Rafael; Cuevas-Diaz-Duran, Raquel; Falciani, Francesco; Tamez-Peña, Jose-Gerardo; Trevino, Victor

2012-10-15

The analysis of biological networks has become essential to study functional genomic data. Compadre is a tool to estimate pathway/gene sets activity indexes using sub-matrix decompositions for biological networks analyses. The Compadre pipeline also includes one of the direct uses of activity indexes to detect altered gene sets. For this, the gene expression sub-matrix of a gene set is decomposed into components, which are used to test differences between groups of samples. This procedure is performed with and without differentially expressed genes to decrease false calls. During this process, Compadre also performs an over-representation test. Compadre already implements four decomposition methods [principal component analysis (PCA), Isomaps, independent component analysis (ICA) and non-negative matrix factorization (NMF)], six statistical tests (t- and f-test, SAM, Kruskal-Wallis, Welch and Brown-Forsythe), several gene sets (KEGG, BioCarta, Reactome, GO and MsigDB) and can be easily expanded. Our simulation results shown in Supplementary Information suggest that Compadre detects more pathways than over-representation tools like David, Babelomics and Webgestalt and less false positives than PLAGE. The output is composed of results from decomposition and over-representation analyses providing a more complete biological picture. Examples provided in Supplementary Information show the utility, versatility and simplicity of Compadre for analyses of biological networks. Compadre is freely available at http://bioinformatica.mty.itesm.mx:8080/compadre. The R package is also available at https://sourceforge.net/p/compadre.

Strategic Reflection on the Use of eLearning Freeware Tools in Higher Education

ERIC Educational Resources Information Center

Gaviola Feck, Dolores

2016-01-01

People are self-learning on the Internet and the various eLearning freeware tools of the 21st century diffuses a whole new pedagogy; yet, generational trends from organizations, corporations, and academic institutions minimally show implementation of various blended learning approaches online into their organizational culture and climate. The…

Measurement Learning Trajectories: A Tool for Professional Development

ERIC Educational Resources Information Center

McCool, Jenni K.

2009-01-01

This study investigated the ways in which a teacher developed conceptions of measurement teaching and learning as she collaborated with a researcher to learn and implement a measurement learning trajectory with two of her students. Teachers need tools that effectively address the content area of measurement and can be used to improve their…

Promoting Learning of Instructional Design via Overlay Design Tools

ERIC Educational Resources Information Center

Carle, Andrew Jacob

2012-01-01

I begin by introducing Virtual Design Apprenticeship (VDA), a learning model--built on a solid foundation of education principles and theories--that promotes learning of design skills via overlay design tools. In VDA, when an individual needs to learn a new design skill or paradigm she is provided accessible, concrete examples that have been…