Superconductivity at 43 K in Samarium-arsenide Oxides SmFeAsO1−xFxSmFeAsO_{1-x}F_x

Since the discovery of high-transition temperature ($T_c$) superconductivity in layered copper oxides, extensive efforts have been devoted to explore the higher $T_c$ superconductivity. However, the $T_c$ higher than 40 K can be obtained only in the copper oxide superconductors so far. The highest reported value of $T_c$ for non-copper-oxide bulk superconductivity is 39 K in $MgB_2$.\cite{jun} The $T_c$ of about 40 K is close to or above the theoretical value predicted from BCS theory.\cite{mcmillan} Therefore, it is very significant to search for non-copper oxide superconductor with the transition temperature higher than 40 K to understand the mechanism of high-$T_c$ superconductivity. Here we report the discovery of bulk superconductivity in samarium-arsenide oxides $SmFeAsO_{1-x}F_x$ with ZrCuAiAs type structure. Resistivity and magnetization measurements show strong evidences for transition temperature as high as 43 K. $SmFeAsO_{1-x}F_x$ is the first non-copper oxide superconductor with $T_c$ higher than 40 K. The $T_c$ higher than 40 K may be a strong argument to consider $SmFeAsO_{1-x}F_x$ as an unconventional superconductor.Comment: 8 pages, 4 figure

Fluid Particle Accelerations in Fully Developed Turbulence

The motion of fluid particles as they are pushed along erratic trajectories by fluctuating pressure gradients is fundamental to transport and mixing in turbulence. It is essential in cloud formation and atmospheric transport, processes in stirred chemical reactors and combustion systems, and in the industrial production of nanoparticles. The perspective of particle trajectories has been used successfully to describe mixing and transport in turbulence, but issues of fundamental importance remain unresolved. One such issue is the Heisenberg-Yaglom prediction of fluid particle accelerations, based on the 1941 scaling theory of Kolmogorov (K41). Here we report acceleration measurements using a detector adapted from high-energy physics to track particles in a laboratory water flow at Reynolds numbers up to 63,000. We find that universal K41 scaling of the acceleration variance is attained at high Reynolds numbers. Our data show strong intermittency---particles are observed with accelerations of up to 1,500 times the acceleration of gravity (40 times the root mean square value). Finally, we find that accelerations manifest the anisotropy of the large scale flow at all Reynolds numbers studied.Comment: 7 pages, 4 figure

Developmental changes in the role of different metalinguistic awareness skills in Chinese reading acquisition from preschool to third grade

Copyright @ 2014 Wei et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.The present study investigated the relationship between Chinese reading skills and metalinguistic awareness skills such as phonological, morphological, and orthographic awareness for 101 Preschool, 94 Grade-1, 98 Grade-2, and 98 Grade-3 children from two primary schools in Mainland China. The aim of the study was to examine how each of these metalinguistic awareness skills would exert their influence on the success of reading in Chinese with age. The results showed that all three metalinguistic awareness skills significantly predicted reading success. It further revealed that orthographic awareness played a dominant role in the early stages of reading acquisition, and its influence decreased with age, while the opposite was true for the contribution of morphological awareness. The results were in stark contrast with studies in English, where phonological awareness is typically shown as the single most potent metalinguistic awareness factor in literacy acquisition. In order to account for the current data, a three-stage model of reading acquisition in Chinese is discussed.National Natural Science Foundation of China and Knowledge Innovation Program of the Chinese Academy of Sciences

Artificial intelligence in cancer imaging: Clinical challenges and applications

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care

Experimental and numerical investigations on the seismic behavior of bridge piers with vertical unbonded prestressing strands

In the performance-based seismic bridge design, piers are expected to undergo large inelastic deformations during severe earthquakes, which in turn can result in large residual drift and concrete crack in the bridge piers. In this paper, longitudinal unbonded prestressing strands are used to minimize residual drift and residual concrete crack width in reinforced concrete (RC) bridge piers. Seven pier specimens were designed and tested quasi-statically and the numerical simulations were carried out. The effectiveness of using vertical unbonded prestressing strands to mitigate the residual drift and concrete crack width of RC bridge piers are examined and discussed in detail. It is found that the residual drift and residual concrete crack width of the piers can be reduced significantly by using the prestressing strands. Moreover, the strands can increase the lateral strength of the piers while have little influence on the ductility capacity of the piers. The hysteretic curves, residual drifts and strand stress of the piers predicted by the numerical model agree well with the testing data and can be used to assess the cyclic behavior of the piers

Many faces of low mass neutralino dark matter in the unconstrained MSSM, LHC data and new signals

If all strongly interacting sparticles (the squarks and the gluinos) in an unconstrained minimal supersymmetric standard model (MSSM) are heavier than the corresponding mass lower limits in the minimal supergravity (mSUGRA) model, obtained by the current LHC experiments, then the existing data allow a variety of electroweak (EW) sectors with light sparticles yielding dark matter (DM) relic density allowed by the WMAP data. Some of the sparticles may lie just above the existing lower bounds from LEP and lead to many novel DM producing mechanisms not common in mSUGRA. This is illustrated by revisiting the above squark-gluino mass limits obtained by the ATLAS Collaboration, with an unconstrained EW sector with masses not correlated with the strong sector. Using their selection criteria and the corresponding cross section limits, we find at the generator level using Pythia, that the changes in the mass limits, if any, are by at most 10-12% in most scenarios. In some cases, however, the relaxation of the gluino mass limits are larger ($\approx 20$). If a subset of the strongly interacting sparticles in an unconstrained MSSM are within the reach of the LHC, then signals sensitive to the EW sector may be obtained. This is illustrated by simulating the $blj$\etslash, $l= e and \mu$, and $b\tau j$\etslash signals in i) the light stop scenario and ii) the light stop-gluino scenario with various light EW sectors allowed by the WMAP data. Some of the more general models may be realized with non-universal scalar and gaugino masses.Comment: 27 pages, 1 figure, references added, minor changes in text, to appear in JHE

Graphene plasmonics

Two rich and vibrant fields of investigation, graphene physics and plasmonics, strongly overlap. Not only does graphene possess intrinsic plasmons that are tunable and adjustable, but a combination of graphene with noble-metal nanostructures promises a variety of exciting applications for conventional plasmonics. The versatility of graphene means that graphene-based plasmonics may enable the manufacture of novel optical devices working in different frequency ranges, from terahertz to the visible, with extremely high speed, low driving voltage, low power consumption and compact sizes. Here we review the field emerging at the intersection of graphene physics and plasmonics.Comment: Review article; 12 pages, 6 figures, 99 references (final version available only at publisher's web site

The SU(2 vertical bar 3) dynamic two-loop form factors

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