Tightening research-practice connections: Applying insights and strategies during design charrettes

McKenney, S., Gomez, K., & Reiser, B. (2012). Tightening research-practice connections: Applying insights and strategies during design charrettes. In J. van Aalst, K. Thompson, M. J. Jacobson, & P. Reimann (Eds.), The future of learning: Proceedings of the 10th international conference of the learning sciences (Vol. 2, pp. 590-591). Sydney, NSW, Australia: International Society of the Learning Sciences.Design charrettes feature hands-on activities for capturing, analyzing and developing the knowledge, values, and vision of its participants. In this workshop, using a design charrette approach, participants will (a) consider how their research informs formal and informal practice, (b) learn about a variety of outlets for bringing research to practice audiences, and (c) consider who might benefit from learning about the research. Participants will discuss different modes of research-practice interaction, and their implications for the production and use of new knowledge. Individuals will analyze their current approaches to knowledge dissemination for use and participants will share existing strategies to stimulate fruitful and mutually informing research-practice connections. Participants will designs their own research-practice connections, both through individual projects and through the ISLS community

Data Materialization: A Hybrid Process for Crafting a Teapot

Data materialization is a workflow developed to create 3D objects from data-informed designs. Building upon traditional metalwork and craft, and new technology's data visualization with generative art, this workflow expresses conceptually relevant data through 3D forms which are fabricated in traditional media. The process allows for the subtle application of data in visual art, allowing the aesthetic allure of the art object or installation to inspire intellectual intrigue. This paper describes the technical and creative process of Modern Dowry, a silver-plated 3D-print teapot on view at the Museum of the City of New York, June 2017--June 2018.Museum of the City of New York; Jeannine Falino; the National Science Foundation for supporting the Computing in the Arts workshops (DUE 1323610, DUE 1323605, DUE 1323593); Reiser’s fellow principle investigators (Bill Manaris, Renee McCauley, Jennifer Burg and Rebecca Bruce); Seton Hall University’s Digital Humanities Fellowship Program for funding and support; and Vassar College’s Creative Arts Across Disciplines Program for their summer residency and exceptional collegiality

A Methodology for Appropriate Testing When Data is Heterogeneous Using EXCEL

A Methodology for Appropriate Testing When Data is Heterogeneous was originally published and copy written in the mid-1990s in Turbo Pascal and a 16-bit operating system.  While working on an ergonomic dissertation (Yearout, 1987), the author determined that the perceptual lighting preference data was heterogeneous and not normal.  Drs. Milliken and Johnson, the authors of Analysis of Messy Data Volume I: Designed Experiments (1989), advised that Satterthwaite’s Approximation with Bonferroni’s Adjustment to correct for pairwise error be used to analyze the heterogeneous data. This technique of applying linear combinations with adjusted degrees of freedom allowed the use of t-Table criteria to make group comparisons without using standard nonparametric techniques.  Thus data with unequal variances and unequal sample sizes could be analyzed without losing valuable information.  Variances to the 4th power were so large that they could not be reentered into basic calculators.  The solution was to develop an original software package which was written in Turbo Pascal on a 7 ¼ inch disk 16-bit operating system.  Current operating systems of 32 and 64 bits and more efficient programming languages have made the software obsolete and unusable. Using the old system could result either in many returns being incorrect or the system terminating.  The purpose of this research was to develop a spreadsheet algorithm with multiple interactive EXCEL worksheets that will efficiently apply Satterthwaite’s Approximation with Bonferroni’s Adjustment to solve the messy data problem.  To ensure that the pedagogy is accurate, the resulting package was successfully tested in the classroom with academically diverse students.  A comparison between this technique and EXCEL’s Add-Ins Analysis ToolPak for a t-test Two-Sample Assuming Unequal Variances was conducted using several different data sets.  The results of this comparison were that the EXCEL Add-Ins returned incorrect significant differences.  Engineers, ergonomists, psychologists, and social scientists will find the developed program very useful. A major benefit is that spreadsheets will continue to be current regardless of evolving operating systems’ status

Submillisievert Computed Tomography of the Chest Using Model-Based Iterative Algorithm: Optimization of Tube Voltage With Regard to Patient Size

Objective: The aim of this study was to define optimal tube potential for soft tissue and vessel visualization in dose-reduced chest CT protocols using model-based iterative algorithm in average and overweight patients. Methods: Thirty-six patients receiving chest CTaccording to 3 protocols (120 kVp/noise index [NI], 60;100 kVp/NI, 65;80 kVp/NI, 70) were included in this prospective study, approved by the ethics committee. Patients' physical parameters and dose descriptors were recorded. Images were reconstructed with model-based algorithm. Two radiologists evaluated image quality and lesion conspicuity;the protocols were intraindividually compared with preceding control CT reconstructed with statistical algorithm (120 kVp/NI, 20). Mean and standard deviation of attenuation of the muscle and fat tissues and signal-to-noise ratio of the aorta were measured. Results: Diagnostic images (lesion conspicuity, 95%-100%) were acquired in average and overweight patients at 1.34, 1.02, and 1.08 mGy and at 3.41, 3.20, and 2.88 mGy at 120, 100, and 80 kVp, respectively. Data are given as CT dose index volume values. Conclusions: Model-based algorithm allows for submillisievert chest CT in average patients;the use of 100 kVp is recommended

Imaging characteristics of intravascular spherical contrast agents for grating-based x-ray dark-field imaging - effects of concentrations, spherical sizes and applied voltage

This study investigates the x-ray scattering characteristics of microsphere particles in x-ray-grating-based interferometric imaging at different concentrations, bubble sizes and tube voltages (kV). Attenuation (ATI), dark-field (DFI) and phase-contrast (PCI) images were acquired. Signal-to-noise (SNR) and contrast-to-noise ratios with water (CNRw) and air as reference (CNRa) were determined. In all modalities, a linear relationship between SNR and microbubbles concentration, respectively, microsphere size was found. A significant gain of SNR was found when varying kV. SNR was significantly higher in DFI and PCI than ATI. The highest gain of SNR was shown at 60kV for all media in ATI and DFI, at 80kV for PCI. SNR for all media was significantly higher compared to air and was slightly lower compared to water. A linear relationship was found between CNRa, CNRw, concentration and size. With increasing concentration and decreasing size, CNRa and CNRw increased in DFI, but decreased in PCI. Best CNRa and CNRw was found at specific combination of kV and concentration/size. Highest average CNRa and CNRw was found for microspheres in ATI and PCI, for microbubbles in DFI. Microspheres are a promising contrast-media for grating-based-interferometry, if kV, microsphere size and concentration are appropriately combined

The Plant Ontology Database: a community resource for plant structure and developmental stages controlled vocabulary and annotations

The Plant Ontology Consortium (POC, http://www.plantontology.org) is a collaborative effort among model plant genome databases and plant researchers that aims to create, maintain and facilitate the use of a controlled vocabulary (ontology) for plants. The ontology allows users to ascribe attributes of plant structure (anatomy and morphology) and developmental stages to data types, such as genes and phenotypes, to provide a semantic framework to make meaningful cross-species and database comparisons. The POC builds upon groundbreaking work by the Gene Ontology Consortium (GOC) by adopting and extending the GOC's principles, existing software and database structure. Over the past year, POC has added hundreds of ontology terms to associate with thousands of genes and gene products from Arabidopsis, rice and maize, which are available through a newly updated web-based browser (http://www.plantontology.org/amigo/go.cgi) for viewing, searching and querying. The Consortium has also implemented new functionalities to facilitate the application of PO in genomic research and updated the website to keep the contents current. In this report, we present a brief description of resources available from the website, changes to the interfaces, data updates, community activities and future enhancement

The Plant Ontology Database: a community resource for plant structure and developmental stages controlled vocabulary and annotations

The Plant Ontology Consortium (POC, http://www.plantontology.org) is a collaborative effort among model plant genome databases and plant researchers that aims to create, maintain and facilitate the use of a controlled vocabulary (ontology) for plants. The ontology allows users to ascribe attributes of plant structure (anatomy and morphology) and developmental stages to data types, such as genes and phenotypes, to provide a semantic framework to make meaningful cross-species and database comparisons. The POC builds upon groundbreaking work by the Gene Ontology Consortium (GOC) by adopting and extending the GOC's principles, existing software and database structure. Over the past year, POC has added hundreds of ontology terms to associate with thousands of genes and gene products from Arabidopsis, rice and maize, which are available through a newly updated web-based browser (http://www.plantontology.org/amigo/go.cgi) for viewing, searching and querying. The Consortium has also implemented new functionalities to facilitate the application of PO in genomic research and updated the website to keep the contents current. In this report, we present a brief description of resources available from the website, changes to the interfaces, data updates, community activities and future enhancement

Plant Ontology (PO): a Controlled Vocabulary of Plant Structures and Growth Stages

The Plant Ontology Consortium (POC) (www.plantontology.org) is a collaborative effort among several plant databases and experts in plant systematics, botany and genomics. A primary goal of the POC is to develop simple yet robust and extensible controlled vocabularies that accurately reflect the biology of plant structures and developmental stages. These provide a network of vocabularies linked by relationships (ontology) to facilitate queries that cut across datasets within a database or between multiple databases. The current version of the ontology integrates diverse vocabularies used to describe Arabidopsis, maize and rice (Oryza sp.) anatomy, morphology and growth stages. Using the ontology browser, over 3500 gene annotations from three species-specific databases, The Arabidopsis Information Resource (TAIR) for Arabidopsis, Gramene for rice and MaizeGDB for maize, can now be queried and retrieved

Qualitative and Quantitative Imaging Evaluation of Renal Cell Carcinoma Subtypes with Grating-based X-ray Phase-contrast CT

Current clinical imaging methods face limitations in the detection and correct characterization of different subtypes of renal cell carcinoma (RCC), while these are important for therapy and prognosis. The present study evaluates the potential of grating-based X-ray phase-contrast computed tomography (gbPC-CT) for visualization and characterization of human RCC subtypes. The imaging results for 23 ex vivo formalin-fixed human kidney specimens obtained with phase-contrast CT were compared to the results of the absorption-based CT (gbCT), clinical CT and a 3T MRI and validated using histology. Regions of interest were placed on each specimen for quantitative evaluation. Qualitative and quantitative gbPC-CT imaging could significantly discriminate between normal kidney cortex (54 +/- 4 HUp) and clear cell (42 +/- 10), papillary (43 +/- 6) and chromophobe RCCs (39 +/- 7), p < 0.05 respectively. The sensitivity for detection of tumor areas was 100%, 50% and 40% for gbPC-CT, gbCT and clinical CT, respectively. RCC architecture like fibrous strands, pseudocapsules, necrosis or hyalinization was depicted clearly in gbPC-CT and was not equally well visualized in gbCT, clinical CT and MRI. The results show that gbPC-CT enables improved discrimination of normal kidney parenchyma and tumorous tissues as well as different soft-tissue components of RCCs without the use of contrast media

Whole-Plant Growth Stage Ontology for Angiosperms and Its Application in Plant Biology

Plant growth stages are identified as distinct morphological landmarks in a continuous developmental process. The terms describing these developmental stages record the morphological appearance of the plant at a specific point in its life cycle. The widely differing morphology of plant species consequently gave rise to heterogeneous vocabularies describing growth and development. Each species or family specific community developed distinct terminologies for describing whole-plant growth stages. This semantic heterogeneity made it impossible to use growth stage description contained within plant biology databases to make meaningful computational comparisons. The Plant Ontology Consortium (http://www.plantontology.org) was founded to develop standard ontologies describing plant anatomical as well as growth and developmental stages that can be used for annotation of gene expression patterns and phenotypes of all flowering plants. In this article, we describe the development of a generic whole-plant growth stage ontology that describes the spatiotemporal stages of plant growth as a set of landmark events that progress from germination to senescence. This ontology represents a synthesis and integration of terms and concepts from a variety of species-specific vocabularies previously used for describing phenotypes and genomic information. It provides a common platform for annotating gene function and gene expression in relation to the developmental trajectory of a plant described at the organismal level. As proof of concept the Plant Ontology Consortium used the plant ontology growth stage ontology to annotate genes and phenotypes in plants with initial emphasis on those represented in The Arabidopsis Information Resource, Gramene database, and MaizeGDB.This is the publisher’s final pdf. The published article is copyrighted by the American Society of Plant Biologists and can be found at: http://www.plantphysiol.org/