Iterative-deepening heuristic search for optimal and semi-optimal resource allocation

It is demonstrated that when iterative-deepening A asterisk (IDA asterisk) is applied to one type of resource allocation problem, it uses far less storage than A asterisk, but opens far more nodes and thus has unacceptable time complexity. This is shown to be due, at least in part, to the low-valued effective branching factor that is a characteristic of problems with real-valued cost functions. The semi-optimal, epsilon-admissible IDA asterisk sub epsilon search algorithm that the authors described was shown to open fewer nodes than both A asterisk and IDA asterisk with storage complexity proportional to the depth of the search tree

Interactional Research Into Problem-Based Learning

Problem-based learning (PBL) has been deployed as a student-centered instructional approach and curriculum design in a wide range of academic fields across the world. The majority of educational research to date has focused on knowledge-based outcomes addressing why PBL is useful. Researchers of PBL are developing a growing interest in qualitative research with a process-driven orientation to examining learning interactions. It is essential to broaden this research base so as to support PBL designs and approaches to leading students into higher-order thinking and a deeper approach to learning. Interactional Research Into Problem-Based Learning explores how students learn in an inquiry-led approach such as PBL. Included are studies that focus on learning in situ and go beyond measuring the outcomes of PBL. The goal is to further expand the PBL research base of qualitative investigations examining the social dimension and lived experience of teaching and learning within the PBL process. A second aim of this volume is to shed light on the methodological aspects of researching PBL, adding new perspectives to the current trends in qualitative studies on PBL. Chapters cover ethnographic approaches to video analysis, introspective protocols such as stimulated recall, and longitudinal qualitative studies using discourse-based analytic approaches. Specifically, this book will further contribute to the current educational research both theoretically and empirically in the following key areas: students’ learning processes in PBL over time and across contexts; the nature of quality interactions in PBL tutorials; the (inter)cultural aspects of learning in PBL; facilitation processes and group dynamics in synchronous and asynchronous face-to-face and blended PBL; and the developing nature of PBL learner identity.https://docs.lib.purdue.edu/purduepress_previews/1058/thumbnail.jp

Online Searching in PBL Tutorials

This study aims to explore how online searching plays a role during PBL tutorials in two undergraduate health sciences curricula, Medicine and Dentistry. Utilizing Interactional Ethnography (IE) as an organizing framework for data collection and analysis, and drawing on a critical theory of technology as an explanatory lens, enabled a textured understanding of student practices and beliefs regarding online searching during face-to-face PBL tutorials. Two event maps trace key transitions in learning regarding online searching in one cycle of problem-based learning in each program. From a critical perspective, analysis of students’ stimulated recall interviews indicated that the use of students’ personal mobile devices with online searching capacity is considered a dynamic pedagogically and socially constructed process. Online searching during the PBL process is also viewed as a “site-of-struggle” where there are challenges for first-year undergraduates when implementing such learning technologies in PBL tutorials

AgBase: a unified resource for functional analysis in agriculture

Analysis of functional genomics (transcriptomics and proteomics) datasets is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation. To facilitate systems biology in these species we have established the curated, web-accessible, public resource ‘AgBase’ (). We have improved the structural annotation of agriculturally important genomes by experimentally confirming the in vivo expression of electronically predicted proteins and by proteogenomic mapping. Proteogenomic data are available from the AgBase proteogenomics link. We contribute Gene Ontology (GO) annotations and we provide a two tier system of GO annotations for users. The ‘GO Consortium’ gene association file contains the most rigorous GO annotations based solely on experimental data. The ‘Community’ gene association file contains GO annotations based on expert community knowledge (annotations based directly from author statements and submitted annotations from the community) and annotations for predicted proteins. We have developed two tools for proteomics analysis and these are freely available on request. A suite of tools for analyzing functional genomics datasets using the GO is available online at the AgBase site. We encourage and publicly acknowledge GO annotations from researchers and provide an online mechanism for agricultural researchers to submit requests for GO annotations

The Proteogenomic Mapping Tool

<p>Abstract</p> <p>Background</p> <p>High-throughput mass spectrometry (MS) proteomics data is increasingly being used to complement traditional structural genome annotation methods. To keep pace with the high speed of experimental data generation and to aid in structural genome annotation, experimentally observed peptides need to be mapped back to their source genome location quickly and exactly. Previously, the tools to do this have been limited to custom scripts designed by individual research groups to analyze their own data, are generally not widely available, and do not scale well with large eukaryotic genomes.</p> <p>Results</p> <p>The Proteogenomic Mapping Tool includes a Java implementation of the Aho-Corasick string searching algorithm which takes as input standardized file types and rapidly searches experimentally observed peptides against a given genome translated in all 6 reading frames for exact matches. The Java implementation allows the application to scale well with larger eukaryotic genomes while providing cross-platform functionality.</p> <p>Conclusions</p> <p>The Proteogenomic Mapping Tool provides a standalone application for mapping peptides back to their source genome on a number of operating system platforms with standard desktop computer hardware and executes very rapidly for a variety of datasets. Allowing the selection of different genetic codes for different organisms allows researchers to easily customize the tool to their own research interests and is recommended for anyone working to structurally annotate genomes using MS derived proteomics data.</p

A Qualitative Study on How Health Professional Students and Their PBL Facilitators Perceive the Use of Mobile Devices During PBL

Mobile devices are increasingly being used by undergraduate students to access online information in the problem-based learning (PBL) process, initially in the self-directed phase, and more recently within face-to-face tutorials. This qualitative study across three undergraduate health professional programs used semi-structured interviews to investigate facilitators’ and students’ perceptions of mobile device usage in PBL tutorials. Transcribed interviews were analyzed thematically, drawing on the principles of grounded theory. Implications for future practice were identified. Students perceived that mobile devices are useful and convenient for instant access to various sources of information, for note taking, and for visually sharing their research and ideas. Despite some facilitator concerns that mobile devices are potentially distracting in face-to-face PBL tutorials, students prioritized collaboration through brainstorming and sharing ideas with group members in face-to-face tutorials over searching online. Facilitators and students suggested practical guidelines for mobile device usage in tutorials to enhance critical thinking in PBL

Chickspress: a resource for chicken gene expression

High-throughput sequencing and proteomics technologies are markedly increasing the amount of RNA and peptide data that are available to researchers, which are typically made publicly available via data repositories such as the NCBI Sequence Read Archive and proteome archives, respectively. These data sets contain valuable information about when and where gene products are expressed, but this information is not readily obtainable from archived data sets. Here we report Chickspress (http://geneatlas.arl.arizona.edu), the first publicly available gene expression resource for chicken tissues. Since there is no single source of chicken gene models, Chickspress incorporates both NCBI and Ensembl gene models and links these gene sets with experimental gene expression data and QTL information. By linking gene models from both NCBI and Ensembl gene prediction pipelines, researchers can, for the first time, easily compare gene models from each of these prediction workflows to available experimental data for these products. We use Chickspress data to show the differences between these gene annotation pipelines. Chickspress also provides rapid search, visualization and download capacity for chicken gene sets based upon tissue type, developmental stage and experiment type. This first Chickspress release contains 161 gene expression data sets, including expression of mRNAs, miRNAs, proteins and peptides. We provide several examples demonstrating how researchers may use this resource.National Institutes of Health [R24 GM079326]; US Department of Agriculture National Institute of Food and Agriculture [2011-67015-30332]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]