Subkelvin tunneling spectroscopy showing Bardeen-Cooper-Schrieffer superconductivity in heavily boron-doped silicon epilayers

Scanning tunneling spectroscopies in the subKelvin temperature range were performed on superconducting Silicon epilayers doped with Boron in the atomic percent range. The resulting local differential conductance behaved as expected for a homogeneous superconductor, with an energy gap dispersion below +/- 10%. The spectral shape, the amplitude and temperature dependence of the superconductivity gap follow the BCS model, bringing further support to the hypothesis of a hole pairing mechanism mediated by phonons in the weak coupling limit.Comment: 4 pages, 3 figure

Nurturing the young shoots of talent: Using action research for exploration and theory building

This is an Author's Accepted Manuscript of an article published in European Early Childhood Education Research Journal, 19(4), 433-450, 2011, copyright Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/1350293X.2011.623515.This paper reports the outcomes of a set of action research projects carried out by teacher researchers in 14 local education authorities in England, working collaboratively with university tutors, over a period of three years. The common aim of all the projects was to explore practical ways of nurturing the gifts and talents of children aged four–seven years. The project was funded by the Department of Education and Skills in England as part of the government's gifted and talented programme. The project teachers felt that their understanding of issues relating to nurturing the gifts and talents of younger children was enhanced through their engagement in the project. It was possible to map the findings of the projects to the English government's National Quality Standards for gifted and talented education which include: (1) identification; (2) effective provision in the classroom; (3) enabling curriculum entitlement and choice; (4) assessment for learning; (5) engaging with community, families and beyond. The findings are also analysed within the framework of good practice in educating children in the first years of schooling. Participating practitioners felt that action research offered them a suitable methodology to explore the complexity of the topic of giftedness through cycles of planning, action and reflection and personal theory building

Histogram-based models on non-thin section chest CT predict invasiveness of primary lung adenocarcinoma subsolid nodules.

109 pathologically proven subsolid nodules (SSN) were segmented by 2 readers on non-thin section chest CT with a lung nodule analysis software followed by extraction of CT attenuation histogram and geometric features. Functional data analysis of histograms provided data driven features (FPC1,2,3) used in further model building. Nodules were classified as pre-invasive (P1, atypical adenomatous hyperplasia and adenocarcinoma in situ), minimally invasive (P2) and invasive adenocarcinomas (P3). P1 and P2 were grouped together (T1) versus P3 (T2). Various combinations of features were compared in predictive models for binary nodule classification (T1/T2), using multiple logistic regression and non-linear classifiers. Area under ROC curve (AUC) was used as diagnostic performance criteria. Inter-reader variability was assessed using Cohen's Kappa and intra-class coefficient (ICC). Three models predicting invasiveness of SSN were selected based on AUC. First model included 87.5 percentile of CT lesion attenuation (Q.875), interquartile range (IQR), volume and maximum/minimum diameter ratio (AUC:0.89, 95%CI:[0.75 1]). Second model included FPC1, volume and diameter ratio (AUC:0.91, 95%CI:[0.77 1]). Third model included FPC1, FPC2 and volume (AUC:0.89, 95%CI:[0.73 1]). Inter-reader variability was excellent (Kappa:0.95, ICC:0.98). Parsimonious models using histogram and geometric features differentiated invasive from minimally invasive/pre-invasive SSN with good predictive performance in non-thin section CT

Entropy and the driving force for the filling of carbon nanotubes with water

The spontaneous filling of hydrophobic carbon nanotubes (CNTs) by water observed both experimentally and from simulations is counterintuitive because confinement is generally expected to decrease both entropy and bonding, and remains largely unexplained. Here we report the entropy, enthalpy, and free energy extracted from molecular dynamics simulations of water confined in CNTs from 0.8 to 2.7-nm diameters. We find for all sizes that water inside the CNTs is more stable than in the bulk, but the nature of the favorable confinement of water changes dramatically with CNT diameter. Thus we find (i) an entropy (both rotational and translational) stabilized, vapor-like phase of water for small CNTs (0.8–1.0 nm), (ii) an enthalpy stabilized, ice-like phase for medium-sized CNTs (1.1–1.2 nm), and (iii) a bulk-like liquid phase for tubes larger than 1.4 nm, stabilized by the increased translational entropy as the waters sample a larger configurational space. Simulations with structureless coarse-grained water models further reveal that the observed free energies and sequence of transitions arise from the tetrahedral structure of liquid water. These results offer a broad theoretical basis for understanding water transport through CNTs and other nanostructures important in nanofluidics, nanofiltrations, and desalination

Weighted norm inequalities, off-diagonal estimates and elliptic operators. Part IV: Riesz transforms on manifolds and weights

This is the fourth article of our series. Here, we study weighted norm inequalities for the Riesz transform of the Laplace-Beltrami operator on Riemannian manifolds and of subelliptic sum of squares on Lie groups, under the doubling volume property and Gaussian upper bounds.Comment: 12 pages. Fourth of 4 papers. Important revision: improvement of main result by eliminating use of Poincar\'e inequalities replaced by the weaker Gaussian keat kernel bound

Gapless spin-liquid state in the structurally disorder-free triangular antiferromagnet NaYbO2_2

We present the structural characterization and low-temperature magnetism of the triangular-lattice delafossite NaYbO$_2$. Synchrotron x-ray diffraction and neutron scattering exclude both structural disorder and crystal-electric-field randomness, whereas heat-capacity measurements and muon spectroscopy reveal the absence of magnetic order and persistent spin dynamics down to at least 70\,mK. Continuous magnetic excitations with the low-energy spectral weight accumulating at the $K$-point of the Brillouin zone indicate the formation of a novel spin-liquid phase in a triangular antiferromagnet. This phase is gapless and shows a non-trivial evolution of the low-temperature specific heat. Our work demonstrates that NaYbO$_2$ practically gives the most direct experimental access to the spin-liquid physics of triangular antiferromagnets.Comment: 6 pages, 4figure

Diffusion and social networks: revisiting medical innovation with agents

the classic study on diffusion of Tetracycline by Coleman, Katz and Menzel (1966). Medical Innovation articulates how different patterns of interpersonal communications can influence the diffusion process at different stages of adoption. In their pioneering study, individual network (discussion, friendship or advice) was perceived as a set of disjointed pairs, and the extent of influences were therefore, evaluated for pairs of individuals. Given the existence of overlapping networks and consequent influences on doctors’ adoption decisions, the complexity of actual events was not captured by pair analysis. Subsequent reanalyses (Burt 1987, Strang and Tuma 1993, Valente 1995, Van den Bulte and Lilien 2001) failed to capture the complexity involved in the diffusion process and had a static exposure of the network structure. In this paper, for the first time, we address these limitations by combining Agent-Based Modeling (ABM) and network analysis. Based on the findings of Coleman et. al. (1966) study, we develop a diffusion model, Gammanym. Using SMALLTALK programming language, Gammanym is developed with CORMAS platform under Visual Works environment. The medical community is portrayed in an 8 X 8 spatial grid. The unit cell captures three different locations for professional interactions: practices, hospitals, and conference centers, randomly located over the spatial grid. Two social agents- Doctor and Laboratory are depicted in the model. Doctors are the principal agents in the diffusion process and are initially located at their respective practices. A doctor’s adoption decision is influenced by a random friendship network, and a professional network created through discussions with office colleagues, or hospital visits or conference attendance. A communicating agent, Laboratory, on the other hand, influences doctors’ adoption decisions by sending information through multiple channels: medical representatives or detailman visiting practices, journals sent to doctors’ practices and commercial flyers available during conferences. Doctors’ decisions to adopt a new drug involve interdependent local interactions among different entities in Gammanym. The cumulative adoption curves (Figure 1) are derived for three sets of initial conditions, based on which network topology and evolution of uptake are analyzed. The three scenarios are specified to evaluate the degree of influences by different factors in the diffusion process: baseline scenario with one seed (initial adopter), one detailman and one journal; heavy media scenario with one seed but increasing degrees of external influence, with five detailman and four journals; and integration scenario with one seed, without any external influence from the laboratory

Diffusion and social networks: revisiting medical innovation with agents

the classic study on diffusion of Tetracycline by Coleman, Katz and Menzel (1966). Medical Innovation articulates how different patterns of interpersonal communications can influence the diffusion process at different stages of adoption. In their pioneering study, individual network (discussion, friendship or advice) was perceived as a set of disjointed pairs, and the extent of influences were therefore, evaluated for pairs of individuals. Given the existence of overlapping networks and consequent influences on doctors’ adoption decisions, the complexity of actual events was not captured by pair analysis. Subsequent reanalyses (Burt 1987, Strang and Tuma 1993, Valente 1995, Van den Bulte and Lilien 2001) failed to capture the complexity involved in the diffusion process and had a static exposure of the network structure. In this paper, for the first time, we address these limitations by combining Agent-Based Modeling (ABM) and network analysis. Based on the findings of Coleman et. al. (1966) study, we develop a diffusion model, Gammanym. Using SMALLTALK programming language, Gammanym is developed with CORMAS platform under Visual Works environment. The medical community is portrayed in an 8 X 8 spatial grid. The unit cell captures three different locations for professional interactions: practices, hospitals, and conference centers, randomly located over the spatial grid. Two social agents- Doctor and Laboratory are depicted in the model. Doctors are the principal agents in the diffusion process and are initially located at their respective practices. A doctor’s adoption decision is influenced by a random friendship network, and a professional network created through discussions with office colleagues, or hospital visits or conference attendance. A communicating agent, Laboratory, on the other hand, influences doctors’ adoption decisions by sending information through multiple channels: medical representatives or detailman visiting practices, journals sent to doctors’ practices and commercial flyers available during conferences. Doctors’ decisions to adopt a new drug involve interdependent local interactions among different entities in Gammanym. The cumulative adoption curves (Figure 1) are derived for three sets of initial conditions, based on which network topology and evolution of uptake are analyzed. The three scenarios are specified to evaluate the degree of influences by different factors in the diffusion process: baseline scenario with one seed (initial adopter), one detailman and one journal; heavy media scenario with one seed but increasing degrees of external influence, with five detailman and four journals; and integration scenario with one seed, without any external influence from the laboratory