131 research outputs found
Pedagogical and Acquisitional Implications of the Intonational Map Provided by Korean Textbook Example Conversations
Through the analyzation of a corpus of K-ToBI annotated speech taken from beginning level textbook conversation recordings, this paper aims to determine the global attributes of Slow, Clear Speech (SCS) on Korean prosody production, and to implicate these effects in the pedagogy of beginning-level Korean. In an analysis of the features that make Korean SCS distinct, four common themes emerged. First, there is final lengthening on Accentual Phrases (APs). Second, there are additional pauses and breaks between APs. Third, there is broad use of pitch reset and of focus in small syntactic frames. And fourth, boundary tones are typically flat and disaffected. Intonation plays a key role in the pursuit of L2 Korean intelligibility and is integral to strong acquisition of Korean. However, instructors rarely speak at normal speech rates (SR) with normal articulation, and typically use SCS with their beginning students. Students will recall frequently heard or salient intonational patterns, so instructors must take care to use intonational patterns intentionally. Thus, it is proposed that instructors of beginner students give explicit instruction and direct feedback on intonation and show natural speech examples often from various speakers, among other strategies to mitigate the effects of SCS on student intonational acquisition
Evaluating the End-User Experience of Private Browsing Mode
Nowadays, all major web browsers have a private browsing mode. However, the
mode's benefits and limitations are not particularly understood. Through the
use of survey studies, prior work has found that most users are either unaware
of private browsing or do not use it. Further, those who do use private
browsing generally have misconceptions about what protection it provides.
However, prior work has not investigated \emph{why} users misunderstand the
benefits and limitations of private browsing. In this work, we do so by
designing and conducting a three-part study: (1) an analytical approach
combining cognitive walkthrough and heuristic evaluation to inspect the user
interface of private mode in different browsers; (2) a qualitative,
interview-based study to explore users' mental models of private browsing and
its security goals; (3) a participatory design study to investigate why
existing browser disclosures, the in-browser explanations of private browsing
mode, do not communicate the security goals of private browsing to users.
Participants critiqued the browser disclosures of three web browsers: Brave,
Firefox, and Google Chrome, and then designed new ones. We find that the user
interface of private mode in different web browsers violates several
well-established design guidelines and heuristics. Further, most participants
had incorrect mental models of private browsing, influencing their
understanding and usage of private mode. Additionally, we find that existing
browser disclosures are not only vague, but also misleading. None of the three
studied browser disclosures communicates or explains the primary security goal
of private browsing. Drawing from the results of our user study, we extract a
set of design recommendations that we encourage browser designers to validate,
in order to design more effective and informative browser disclosures related
to private mode
Faculty roles and role preferences in ten fields of professional study
Teaching faculty in ten entry-level professional fields reported varying amounts of time devoted to teaching, research, consulting, and professional practice but did not differ in time devoted to administration. The faculty member's own role view was most closely related to time use, but for time spent in teaching and research, faculty age and institutional type (but not gender) were also significant predictors. Even after several general demographic characteristics and environmental variables that potentially differentiate professional from discipline-based faculty are taken into account, different professional fields may be characterized by group climates which influence or reinforce certain faculty roles.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43598/1/11162_2004_Article_BF00991875.pd
The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe
The preponderance of matter over antimatter in the early Universe, the
dynamics of the supernova bursts that produced the heavy elements necessary for
life and whether protons eventually decay --- these mysteries at the forefront
of particle physics and astrophysics are key to understanding the early
evolution of our Universe, its current state and its eventual fate. The
Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed
plan for a world-class experiment dedicated to addressing these questions. LBNE
is conceived around three central components: (1) a new, high-intensity
neutrino source generated from a megawatt-class proton accelerator at Fermi
National Accelerator Laboratory, (2) a near neutrino detector just downstream
of the source, and (3) a massive liquid argon time-projection chamber deployed
as a far detector deep underground at the Sanford Underground Research
Facility. This facility, located at the site of the former Homestake Mine in
Lead, South Dakota, is approximately 1,300 km from the neutrino source at
Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino
charge-parity symmetry violation and mass ordering effects. This ambitious yet
cost-effective design incorporates scalability and flexibility and can
accommodate a variety of upgrades and contributions. With its exceptional
combination of experimental configuration, technical capabilities, and
potential for transformative discoveries, LBNE promises to be a vital facility
for the field of particle physics worldwide, providing physicists from around
the globe with opportunities to collaborate in a twenty to thirty year program
of exciting science. In this document we provide a comprehensive overview of
LBNE's scientific objectives, its place in the landscape of neutrino physics
worldwide, the technologies it will incorporate and the capabilities it will
possess.Comment: Major update of previous version. This is the reference document for
LBNE science program and current status. Chapters 1, 3, and 9 provide a
comprehensive overview of LBNE's scientific objectives, its place in the
landscape of neutrino physics worldwide, the technologies it will incorporate
and the capabilities it will possess. 288 pages, 116 figure
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
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Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis
Multifactorial mechanisms underlying late-onset Alzheimer's disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD–abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system's integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions
Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images
Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease
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