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

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 $N_c$, 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

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