Accessing E-books through Academic Library Web Sites

This article examines access to electronic books as provided on theWeb sites of academic libraries in the Association of Research Libraries (ARL). Our goal was to discover the ways in which that access occurs and to analyze the merit of the various approaches. We found some common barriers to access, as well as many cases of exemplary access. Many libraries could improve access to e-books by providing guidance to the content of e-book packages, by including the word “book” in links from the homepage to the pages that provide e-books, by providing a one-step limit to e-books in the catalog, by explaining which types of resources are available through search structures outside the catalog, and by featuring e-books in library publicity and instruction

Peer Evaluation of Teaching in an Online Information Literacy Course

This paper reports on the development and implementation of a process of peer evaluation of teaching to assess librarian instruction in a high-enrollment online information literacy course for undergraduates. This paper also traces a shift within libraries from peer coaching to peer evaluation models. One common model for peer evaluation, using pre- and post-observation meetings between instructor and evaluator, as well as a formal summative report, has been adapted to focus attention on key aspects of online teaching. The paper also discusses the need for evaluating librarians’ online teaching performance, as distinct from online course design

Competencies for Bibliographers: A Process for Writing a Collection Development Competencies Document

Competency statements for librarians are one way of measuring performance against a set standard. The Iowa State University Library established a task force to develop a collection development competencies document for its subject bibliographers. The literature review revealed that while there were many examples of competency documents, little had been written about the process of developing a competencies document. This article details the process used to write the competencies document at Iowa State University. The completed document is a blend of existing standards and local practice that can be adapted to any library

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer’s disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, ‘shape connections’ between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images

Alzheimer’s Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1–3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature