17,526 research outputs found
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The role of human factors in stereotyping behavior and perception of digital library users: A robust clustering approach
To deliver effective personalization for digital library users, it is necessary to identify which human factors are most relevant in determining the behavior and perception of these users. This paper examines three key human factors: cognitive styles, levels of expertise and gender differences, and utilizes three individual clustering techniques: k-means, hierarchical clustering and fuzzy clustering to understand user behavior and perception. Moreover, robust clustering, capable of correcting the bias of individual clustering techniques, is used to obtain a deeper understanding. The robust clustering approach produced results that highlighted the relevance of cognitive style for user behavior, i.e., cognitive style dominates and justifies each of the robust clusters created. We also found that perception was mainly determined by the level of expertise of a user. We conclude that robust clustering is an effective technique to analyze user behavior and perception
Building the Brazilian Academic Genealogy Tree
Along the history, many researchers provided remarkable contributions to
science, not only advancing knowledge but also in terms of mentoring new
scientists. Currently, identifying and studying the formation of researchers
over the years is a challenging task as current repositories of theses and
dissertations are cataloged in a decentralized way through many local digital
libraries. Following our previous work in which we created and analyzed a large
collection of genealogy trees extracted from NDLTD, in this paper we focus our
attention on building such trees for the Brazilian research community. For
this, we use data from the Lattes Platform, an internationally renowned
initiative from CNPq, the Brazilian National Council for Scientific and
Technological Development, for managing information about individual
researchers and research groups in Brazil
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Developing Children's Oral Health Assessment Toolkits Using Machine Learning Algorithm.
ObjectivesEvaluating children's oral health status and treatment needs is challenging. We aim to build oral health assessment toolkits to predict Children's Oral Health Status Index (COHSI) score and referral for treatment needs (RFTN) of oral health. Parent and Child toolkits consist of short-form survey items (12 for children and 8 for parents) with and without children's demographic information (7 questions) to predict the child's oral health status and need for treatment.MethodsData were collected from 12 dental practices in Los Angeles County from 2015 to 2016. We predicted COHSI score and RFTN using random Bootstrap samples with manually introduced Gaussian noise together with machine learning algorithms, such as Extreme Gradient Boosting and Naive Bayesian algorithms (using R). The toolkits predicted the probability of treatment needs and the COHSI score with percentile (ranking). The performance of the toolkits was evaluated internally and externally by residual mean square error (RMSE), correlation, sensitivity and specificity.ResultsThe toolkits were developed based on survey responses from 545 families with children aged 2 to 17 y. The sensitivity and specificity for predicting RFTN were 93% and 49% respectively with the external data. The correlation(s) between predicted and clinically determined COHSI was 0.88 (and 0.91 for its percentile). The RMSEs of the COHSI toolkit were 4.2 for COHSI (and 1.3 for its percentile).ConclusionsSurvey responses from children and their parents/guardians are predictive for clinical outcomes. The toolkits can be used by oral health programs at baseline among school populations. The toolkits can also be used to quantify differences between pre- and post-dental care program implementation. The toolkits' predicted oral health scores can be used to stratify samples in oral health research.Knowledge transfer statementThis study creates the oral health toolkits that combine self- and proxy- reported short forms with children's demographic characteristics to predict children's oral health and treatment needs using Machine Learning algorithms. The toolkits can be used by oral health programs at baseline among school populations to quantify differences between pre and post dental care program implementation. The toolkits can also be used to stratify samples according to the treatment needs and oral health status
On the role of magnetic reconnection in jet/accretion disk systems
The most accepted model for jet production is based on the
magneto-centrifugal acceleration out off an accretion disk that surrounds the
central source (Blandford & Payne, 1982). This scenario, however, does not
explain, e.g., the quasi-periodic ejection phenomena often observed in
different astrophysical jet classes. de Gouveia Dal Pino & Lazarian (2005)
(hereafter GDPL) have proposed that the large scale superluminal ejections
observed in microquasars during radio flare events could be produced by violent
magnetic reconnection (MR) episodes. Here, we extend this model to other
accretion disk systems, namely: active galactic nuclei (AGNs) and young stellar
objects (YSOs), and also discuss its role on jet heating and particle
acceleration.Comment: To be published in the IAU Highlights of Astronomy, Volume 15, XXVII
IAU General Assembly, August 2009, Ian F. Corbett et al., eds., 201
The momentum analyticity of two-point correlators from perturbation theory and AdS/CFT
The momentum plane analyticity of two point function of a relativistic
thermal field theory at zero chemical potential is explored. A general
principle regarding the location of the singularities is extracted. In the case
of the N=4 supersymmetric Yang-Mills theory at large , a qualitative
change in the nature of the singularity (branch points versus simple poles)
from the weak coupling regime to the strong coupling regime is observed with
the aid of the AdS/CFT correspondence.Comment: 18 pages, 3 figures, typos fixed, 1 figure update
Retaining Expression on De-identified Faces
© Springer International Publishing AG 2017The extensive use of video surveillance along with advances in face recognition has ignited concerns about the privacy of the people identifiable in the recorded documents. A face de-identification algorithm, named k-Same, has been proposed by prior research and guarantees to thwart face recognition software. However, like many previous attempts in face de-identification, kSame fails to preserve the utility such as gender and expression of the original data. To overcome this, a new algorithm is proposed here to preserve data utility as well as protect privacy. In terms of utility preservation, this new algorithm is capable of preserving not only the category of the facial expression (e.g., happy or sad) but also the intensity of the expression. This new algorithm for face de-identification possesses a great potential especially with real-world images and videos as each facial expression in real life is a continuous motion consisting of images of the same expression with various degrees of intensity.Peer reviewe
Children born in July and August: a study on the age regulation in primary school and student’s education access and development
Electronic Devices Based on Purified Carbon Nanotubes Grown By High Pressure Decomposition of Carbon Monoxide
The excellent properties of transistors, wires, and sensors made from
single-walled carbon nanotubes (SWNTs) make them promising candidates for use
in advanced nanoelectronic systems. Gas-phase growth procedures such as the
high pressure decomposition of carbon monoxide (HiPCO) method yield large
quantities of small diameter semiconducting SWNTs, which are ideal for use in
nanoelectronic circuits. As-grown HiPCO material, however, commonly contains a
large fraction of carbonaceous impurities that degrade properties of SWNT
devices. Here we demonstrate a purification, deposition, and fabrication
process that yields devices consisting of metallic and semiconducting nanotubes
with electronic characteristics vastly superior to those of circuits made from
raw HiPCO. Source-drain current measurements on the circuits as a function of
temperature and backgate voltage are used to quantify the energy gap of
semiconducting nanotubes in a field effect transistor geometry. This work
demonstrates significant progress towards the goal of producing complex
integrated circuits from bulk-grown SWNT material.Comment: 6 pages, 4 figures, to appear in Nature Material
Upconversion Nanoparticle-Based Cell Membrane-Coated cRGD Peptide Bioorthogonally Labeled Nanoplatform for Glioblastoma Treatment
Glioblastoma is hard to be eradicated partly because of the obstructive blood-brain barrier (BBB) and the dynamic autophagy activities of glioblastoma. Here, hydroxychloroquine (HDX)-loaded yolk-shell upconversion nanoparticle (UCNP)@Zn0.5Cd0.5S nanoparticle coating with the cyclic Arg-Gly-Asp (cRGD)-grafted glioblastoma cell membrane for near-infrared (NIR)-triggered treatment of glioblastoma is prepared for the first time. [email protected] (abbreviated as YSN, yolk-shell nanoparticle) under NIR radiation will generate reactive oxygen species for imposing cytotoxicity. HDX, the only available autophagy inhibitor in clinical studies, can enhance cytotoxicity by preventing damaged organelles from being recycled. The cRGD-decorated cell membrane allowed the HDX-loaded nanoparticles to efficiently bypass the BBB and specifically target glioblastoma cells. Exceptional treatment efficacy of the NIR-triggered chemotherapy and photodynamic therapy was achieved in U87 cells and in the mouse glioblastoma model as well. Our results provided proof-of-concept evidence that HDX@YSN@CCM@cRGD could overcome the delivery barriers and achieve targeted treatment of glioblastoma
High-Pressure Synthesis, Crystal Structures, and Properties of A-Site Columnar-Ordered Quadruple Perovskites NaRMn2Ti4O12 with R = Sm, Eu, Gd, Dy, Ho, Y
The formation of NaRMn2Ti4O12 compounds (R = rare earth) under high pressure (about 6 GPa) and high temperature (about 1750 K) conditions was studied. Such compounds with R = Sm, Eu, Gd, Dy, Ho, Y adopt an A-site columnar-ordered quadruple-perovskite structure with the generic chemical formula A2A′A″B4O12. Their crystal structures were studied by powder synchrotron X-ray and neutron diffraction between 1.5 and 300 K. They maintain a paraelectric structure with centrosymmetric space group P42/nmc (No. 137) at all temperatures, in comparison with the related CaMnTi2O6 perovskite, in which a ferroelectric transition occurs at 630 K. The centrosymmetric structure was also confirmed by second-harmonic generation. It has a cation distribution of [Na+R3+]A[Mn2+]A′[Mn2+]A″[Ti4+4]BO12 (to match with the generic chemical formula) with statistical distributions of Na+ and R3+ at the large A site and a strongly split position of Mn2+ at the square-planar A′ site. We found a C-type long-range antiferromagnetic structure of Mn2+ ions at the A′ and A″ sites below TN = 12 K for R = Dy and found that the presence of Dy3+ disturbs the long-range ordering of Mn2+ below a second transition at lower temperatures. The first magnetic transition occurs below 8–13 K in all compounds, but the second magnetic transition occurs only for R = Dy, Sm, Eu. All compounds show large dielectric constants of a possible extrinsic origin similar to that of CaCu3Ti4O12. NaRMn2Ti4O12 with R = Er–Lu crystallized in the GdFeO3-type Pnma perovskite structure, and NaRMn2Ti4O12 with R = La, Nd contained two perovskite phases: an AA′3B4O12-type Im3̅ phase and a GdFeO3-type Pnma phase
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