Valuing the Resources of Infrastructure: Beyond From-Scratch and Off-the-Shelf Technology Options for Electronic Portfolio Assessment in First-Year Writing

Ongoing technology innovation holds obvious promise for college writing programs with resources to invest in high-end hardware and software. However, many campuses face resource limitations that preclude the adoption of cutting-edge material innovations. As an alternative, the concept of infrastructure (DeVoss, Cushman, & Grabill, 2005) offers a means by which seemingly under-resourced writing programs can recognize and draw upon the expertise and commitment of their faculty to develop in-house technology solutions adapted to specific program needs and institutional contexts while abiding by more obvious material limitations. To illustrate the value of infrastructure, this study reports the experience of one college writing program on a large, public, urban, access-oriented campus with limited material resources that nonetheless developed a system for supporting electronic portfolios by adapting the readily available platforms of Google Docs and Google Sites. After providing a rationale for adopting electronic portfolios grounded in a rhetorically based approach to assessment, the study details the development process for this customized system as well as the collaborative relationships between faculty of different ranks (tenure-track, adjunct, and graduate student) and expertise through which the project evolved. Based on this experience, the study considers some implications that infrastructure holds for writing program administration.     

Parallelizing XML data-streaming workflows via MapReduce

In prior work it has been shown that the design of scientific workflows can benefit from a collection-oriented modeling paradigm which views scientific workflows as pipelines of XML stream processors. In this paper, we present approaches for exploiting data parallelism in XML processing pipelines through novel compilation strategies to the MapReduce framework. Pipelines in our approach consist of sequences of processing steps that receive XML-structured data and produce, often through calls to “black-box” (scientific) functions, modified (i.e., updated) XML structures. Our main contributions are (i) the development of a set of strategies for compiling scientific workflows, modeled as XML processing pipelines, into parallel MapReduce networks, and (ii) a discussion of their advantages and trade-offs, based on a thorough experimental evaluation of the various translation strategies. Our evaluation uses the Hadoop MapReduce system as an implementation platform. Our results show that execution times of XML workflow pipelines can be significantly reduced using our compilation strategies. These efficiency gains, together with the benefits of MapReduce (e.g., fault tolerance) make our approach ideal for executing large-scale, compute-intensive XML-based scientific workflows.     

Multivariate statistical approach to electron backscattered diffraction

This paper assesses the potential of multivariate statistical analysis (MSA) applied to electron backscattered diffraction (EBSD) data. Instead of directly indexing EBSD patterns on an individual basis, this multivariate approach reduces a large (thousands) set of individual EBSD patterns into a core set of statistically derived component EBSD patterns which can be subsequently indexed. The following hypotheses are considered in this paper: (1) experimental EBSD patterns from a microstructure can be analytically treated as linear combinations of spatially simple components, (2) MSA has an angular resolution on par with standard EBSD, (3) MSA can discriminate between similar and dissimilar phases, and (4) the MSA approach can improve the effective spatial resolution of automated EBSD.     

Identification and quantitation of changes in the platelet activating factor family of glycerophospholipids over the course of neuronal differentiation by high-performance liquid chromatography electrospray ionization tandem mass spectrometry

Glycerophospholipids are important structural lipids in membranes with changes associated with progressive neurodegenerative disorders such as Alzheimer disease. Synthesis of the platelet activating factor (PAF) glycerophospholipid subclass is implicated in the control of neuronal differentiation and death. In this article, we combine nanoflow HPLC and mass spectrometry to screen, identify, and quantitate changes in glycerophospholipid subspecies, specifically PAF family members, over the course of neuronal differentiation. Furthermore, precursor ion scans for fragments characteristic of PAF phosphocholine family members and the standard additions of PAF subspecies were combined to perform absolute quantitation of PAF lipids in undifferentiated and differentiated PC12 cells. Surprisingly, a marked asymmetry was detected in the two predominant PAF species (C16:0, C18:0) over the course of differentiation. These results describe a new technique for the sensitive analysis of lipids combining nanoflow HPLC, ESI-MS, and precursor ion scan. Limits of detection of as little as 2 pg of PAF and LPC were obtained, and analysis of the lipidome of as little as 70,000 cells was performed on this system. Furthermore, application to the PC12 model identified a quantifiable difference between PAF molecular species produced over the course of neuronal differentiation.     

Siderophore production and utilization by milk spoilage Pseudomonas species

Many bacteria respond to potentially growth-limiting availability of iron by producing low-molecular-weight iron chelators (siderophores). The aim of this work was to examine the siderophores synthesized and utilized by Pseudomonas spp. implicated in milk spoilage. Twenty isolates of Pseudomonas spp. previously shown to have significant milk spoilage potential were tested for the ability to produce siderophores. Of these, 14 produced pyoverdin and 2 of these also produced pyochelin; 1 produced only pyochelin; 1 produced only salicylate; 2 produced non-pyoverdin, hydroxamate-containing siderophore; and 2 produced chrome azurol sulfonate reactive material that was neither pyoverdin nor pyochelin. There was considerable diversity among the pyoverdins produced. All isolates were shown to utilize iron complexed with exogenous pyoverdin, but usage of particular exogenous pyoverdins differed among isolates. Interference with the iron-uptake systems of the Pseudomonas spp. may be a means by which food spoilage can be slowed, and the pyoverdin system would appear to be a potential target. However, given the diversity of pyoverdins produced and utilized, and the presence of other siderophores, successful interference with bacterial iron acquisition in this context may be challenging.     

Removal of heavy metals from mine water by cyanobacterial calcification

The influence of different illumination intensities on cyanobacterial calcification induced removal of heavy metals from contaminated mine water was studied. Cyanobacterial calcification experiments were performed using a growth medium intended to simulate contaminated mine water. The results indicate that calcification can promote the removal of heavy metal ions. As the illumination intensity became stronger calcification rates increased and the removal of Zn2+ and Cd2+ became more obvious. When the illumination intensity was 10000 lux the removal of Pb2+ was the largest observed: stronger or weaker illumination reduced the amount of lead removed. The removal of three different heavy metals complies with an index function. For identical illumination intensities different ions were removed to different degrees.