Reducing Hardships: Student Motivations, Educational Workflows, and Technology Choices in Academic Settings

Objective – This study examines The University of Manitoba student attitudes toward technology’s role in University study spaces and in their own educational workflows. Methods - A series of semi-structured group interviews were conducted with current undergraduate and graduate students at The University of Manitoba. Three group interviews were conducted with questions about individual technology and space use while studying in the library, and three group interviews were conducted with questions about group collaboration using technologies and tools in group study spaces. Transcripts were coded iteratively and separately by the researchers, analyzed for interrater reliability, categorized, and reviewed using axial coding to identify major themes. Through continued examination of these themes, a single theory emerged. Results - The participants expressed a strong need for independence and feelings of control over their workflows, technological tools, and environments. They discussed how interpersonal concerns and anxieties motivated their workflow choices and acknowledged the (often conflicting) motivational forces of personal necessity and personal preference. When examining the motivations behind the selection of technologies and work practices, it became clear that the respondents make technology and workflow decisions in an attempt to minimize their experience of perceived hardships. These perceived hardships could be social, emotional, educational, environmental, or temporal in nature, and the weight of any one hardship on decision making varied according to the individual. Conclusions - Libraries should be aware of this foundational user motivation and make choices accordingly - identifying and minimizing hardships whenever possible, unless they are necessary to achieve learning or service-specific goals. Additional research is required to help articulate the nuances experienced by particular student demographics. Librarians and future researchers should also consider investigating the potential disconnect between librarian and user attitudes toward technology, the prioritization of user-centered decision-making, and whether or not systematically disadvantaged social groups have different attitudes toward technology and its place in library spaces and academic work.https://journal.lib.uoguelph.ca/index.php/perj/article/view/545

Rasch analysis of the Patient Rated Elbow Evaluation questionnaire

© 2015 Vincent et al. Background: The Patient Rated Elbow Evaluation (PREE) was developed as an elbow joint specific measure of pain and disability and validated with classical psychometric methods. More recently, Rasch analysis has contributed new methods for analyzing the clinical measurement properties of self-report outcome measures. The objective of the study was to determine aspects of validity of the PREE using the Rasch model to assess the overall fit of the PREE data, the response scaling, individual item fit, differential item functioning (DIF), local dependency, unidimensionality and person separation index (PSI). Methods: A convenience sample of 236 patients (Age range 21-79 years; M: F- 97:139) with elbow disorders were recruited from the Roth|McFarlane Hand and Upper Limb Centre, London, Ontario, Canada. The baseline scores of the PREE were used. Rasch analysis was conducted using RUMM 2030 software on the 3 sub scales of the PREE separately. Results: The 3 sub scales showed misfit initially with disordered thresholds on17 out of 20 items), uniform DIF was observed for two items ( Carrying a 10lbs object from specific activities subscale for age group; and household work from the usual activities subscale for gender); multidimensionality and local dependency. The Pain subscale satisfied Rasch expectations when item 2 Pain - At rest was split for age group, while the usual activities subscale readily stood up to Rasch requirements when the item 2 household work was split for gender. The specific activities subscale demonstrated fit to the Rasch model when sub test analysis accounted for local dependency. All three subscales of the PREE were well targeted and had high reliability (PSI \u3e0.80). Conclusion: The three subscales of the PREE appear to be robust when tested against the Rasch model when subject to a few alterations. The value of changing the 0-10 format is questionable given its widespread use; further Rasch-based analysis of whether these findings are stable in other samples is warranted

Unsupervised Adaptation for High-Dimensional with Limited-Sample Data Classification Using Variational Autoencoder

High-dimensional with limited-sample size (HDLSS) datasets exhibit two critical problems: (1) Due to the insufficiently small-sample size, there is a lack of enough samples to build classification models. Classification models with a limited-sample may lead to overfitting and produce erroneous or meaningless results. (2) The 'curse of dimensionality' phenomena is often an obstacle to the use of many methods for solving the high-dimensional with limited-sample size problem and reduces classification accuracy. This study proposes an unsupervised framework for high-dimensional limited-sample size data classification using dimension reduction based on variational autoencoder (VAE). First, the deep learning method variational autoencoder is applied to project high-dimensional data onto lower-dimensional space. Then, clustering is applied to the obtained latent-space of VAE to find the data groups and classify input data. The method is validated by comparing the clustering results with actual labels using purity, rand index, and normalized mutual information. Moreover, to evaluate the proposed model strength, we analyzed 14 datasets from the Arizona State University Digital Repository. Also, an empirical comparison of dimensionality reduction techniques shown to conclude their applicability in the high-dimensional with limited-sample size data settings. Experimental results demonstrate that variational autoencoder can achieve more accuracy than traditional dimensionality reduction techniques in high-dimensional with limited-sample-size data analysis

Functional diversification of Argonautes in nematodes:an expanding universe

In the last decade, many diverse RNAi (RNA interference) pathways have been discovered that mediate gene silencing at epigenetic, transcriptional and post-transcriptional levels. The diversity of RNAi pathways is inherently linked to the evolution of Ago (Argonaute) proteins, the central protein component of RISCs (RNA-induced silencing complexes). An increasing number of diverse Agos have been identified in different species. The functions of most of these proteins are not yet known, but they are generally assumed to play roles in development, genome stability and/or protection against viruses. Recent research in the nematode Caenorhabditis elegans has expanded the breadth of RNAi functions to include transgenerational epigenetic memory and, possibly, environmental sensing. These functions are inherently linked to the production of secondary siRNAs (small interfering RNAs) that bind to members of a clade of WAGOs (worm-specific Agos). In the present article, we review briefly what is known about the evolution and function of Ago proteins in eukaryotes, including the expansion of WAGOs in nematodes. We postulate that the rapid evolution of WAGOs enables the exceptional functional plasticity of nematodes, including their capacity for parasitism

Patient Perception of Physician Attire Before and After Disclosure of the Risks of Microbial Contamination

Background: The white coat is traditionally considered to be the appropriate attire for physicians but it may also be contaminated with microbes and act as a potential source of infection. We aimed to study patients’ acceptance of physicians’ attire, their underlying reasons, and their reactions to an educational intervention with regards to the risks of contamination. Methods: We conducted a voluntary ques­tionnaire survey at a university teaching hospital in Hong Kong from February to July 2012. 262 patient-responses from adult inpatients and outpatients across various specialties were analysed. Results: White coats were highly favoured (90.8%) when compared with scrubs (22.1%), smart casual (7.6%) and formal (7.3%) wears. ’Professional image’ and ‘ease of identification’ were the main attributes of the white coat. Most patients (92.2%) would prefer doctors washing their white coats every few days, whilst 80.9% believed that doctors were actually doing so. After patients were informed of the potential risk of microbial contamination, white coats remained as the most favoured attire (66.4%), but with scrubs doubling in popularity (45.8%). Smart casual (9.2%) and formal attire (4.6%) remain the least accepted. Conclusion: Despite cross-infections being a significant concern within the healthcare environments, patients’ predominant acceptance and perceived attributes towards the white coat were maintained after an educational intervention on the risks of microbial contamination

Direct Optimal Mapping for 21cm Cosmology: A Demonstration with the Hydrogen Epoch of Reionization Array

Motivated by the desire for wide-field images with well-defined statistical properties for 21cm cosmology, we implement an optimal mapping pipeline that computes a maximum likelihood estimator for the sky using the interferometric measurement equation. We demonstrate this direct optimal mapping with data from the Hydrogen Epoch of Reionization (HERA) Phase I observations. After validating the pipeline with simulated data, we develop a maximum likelihood figure-of-merit for comparing four sky models at 166MHz with a bandwidth of 100kHz. The HERA data agree with the GLEAM catalogs to <10%. After subtracting the GLEAM point sources, the HERA data discriminate between the different continuum sky models, providing most support for the model of Byrne et al. 2021. We report the computation cost for mapping the HERA Phase I data and project the computation for the HERA 320-antenna data; both are feasible with a modern server. The algorithm is broadly applicable to other interferometers and is valid for wide-field and non-coplanar arrays.Comment: 16 pages, 10 figures, 2 tables, published on Ap

The Community Land Model version 5 : description of new features, benchmarking, and impact of forcing uncertainty

The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time‐evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5

Neurophysiological Defects and Neuronal Gene Deregulation in Drosophila mir-124 Mutants

miR-124 is conserved in sequence and neuronal expression across the animal kingdom and is predicted to have hundreds of mRNA targets. Diverse defects in neural development and function were reported from miR-124 antisense studies in vertebrates, but a nematode knockout of mir-124 surprisingly lacked detectable phenotypes. To provide genetic insight from Drosophila, we deleted its single mir-124 locus and found that it is dispensable for gross aspects of neural specification and differentiation. On the other hand, we detected a variety of mutant phenotypes that were rescuable by a mir-124 genomic transgene, including short lifespan, increased dendrite variation, impaired larval locomotion, and aberrant synaptic release at the NMJ. These phenotypes reflect extensive requirements of miR-124 even under optimal culture conditions. Comparison of the transcriptomes of cells from wild-type and mir-124 mutant animals, purified on the basis of mir-124 promoter activity, revealed broad upregulation of direct miR-124 targets. However, in contrast to the proposed mutual exclusion model for miR-124 function, its functional targets were relatively highly expressed in miR-124–expressing cells and were not enriched in genes annotated with epidermal expression. A notable aspect of the direct miR-124 network was coordinate targeting of five positive components in the retrograde BMP signaling pathway, whose activation in neurons increases synaptic release at the NMJ, similar to mir-124 mutants. Derepression of the direct miR-124 target network also had many secondary effects, including over-activity of other post-transcriptional repressors and a net incomplete transition from a neuroblast to a neuronal gene expression signature. Altogether, these studies demonstrate complex consequences of miR-124 loss on neural gene expression and neurophysiology