Thermal emission from finite photonic crystals

We present a microscopic theory of thermal emission from finite-sized photonic crystals and show that the directional spectral emissivity and related quantities can be evaluated via standard bandstructure computations without any approximation. We then identify the physical mechanisms through which interfaces modify the potentially super-Planckian radiation flow inside infinite photonic crystals, such that thermal emission from finite-sized samples is consistent with the fundamental limits set by Planck's law. As an application, we further demonstrate that a judicious choice of a photonic crystal's surface termination facilitates considerable control over both the spectral and angular thermal emission properties. © 2009 American Institute of Physics

Motion Deblurring in the Wild

The task of image deblurring is a very ill-posed problem as both the image and the blur are unknown. Moreover, when pictures are taken in the wild, this task becomes even more challenging due to the blur varying spatially and the occlusions between the object. Due to the complexity of the general image model we propose a novel convolutional network architecture which directly generates the sharp image.This network is built in three stages, and exploits the benefits of pyramid schemes often used in blind deconvolution. One of the main difficulties in training such a network is to design a suitable dataset. While useful data can be obtained by synthetically blurring a collection of images, more realistic data must be collected in the wild. To obtain such data we use a high frame rate video camera and keep one frame as the sharp image and frame average as the corresponding blurred image. We show that this realistic dataset is key in achieving state-of-the-art performance and dealing with occlusions

Homogeneous catalysis under ultra-dilute conditions: TAML/NaClO oxidation of persistent metaldehyde

This document is the unedited Author’s version of a Submitted Work that was subsequently accepted for publication in Journal of the American Chemical Society, copyright © American Chemical Society after peer review. To access the final edited and published work see https://doi.org/10.1021/jacs.6b11145TAML activators enable homogenous oxidation catalysis where the catalyst and substrate (S) are ultra-dilute (pM–low μM) and the oxidant is very dilute (high nM–low mM). Water contamination by exceptionally persistent micropollutants (MPs), including metaldehyde (Met), provides an ideal space for determining the characteristics and utilitarian limits of this ultradilute catalysis. The low MP concentrations decrease throughout catalysis with S oxidation (kII) and catalyst inactivation (ki) competing for the active catalyst. The percentage of substrate converted (%Cvn) can be increased by discovering methods to increase kII/ki. Here we show that NaClO extends catalyst lifetime to increase the Met turnover number (TON) threefold compared with H2O2, highlighting the importance of oxidant choice as a design tool in TAML systems. Met oxidation studies (pH 7, D2O, 0.01 M phosphate, 25 °C) monitored by 1H NMR spectroscopy show benign acetic acid as the only significant product. Analysis of TAML/NaClO treated Met solutions employing successive identical catalyst doses revealed that the processes can be modeled by the recently published relationship between the initial and final [S] (S0 and S∞, respectively), the initial [catalyst] (FeTot) and kII/ki. Consequently, this study establishes that S is proportional to S0 and that the %Cvn is conserved across all catalyst doses in multicatalyst-dose processes because the rate of the kII process depends on [S] while that of the ki process does not. A general tool for determining the FeTot required to effect a desired %Cvn is presented. Examination of the dependence of TON on kII/ki and FeTot at a fixed S0 indicates that for any TAML process employing FeTot < 1 10-6 M, small catalyst doses are not more efficient than one large dose.T.J.C thanks the Heinz Endowments for funding. NMR instrumentation at CMU was partially supported by NSF (CHE-0130903 and CHE-1039870)

Training Auto-encoder-based Optimizers for Terahertz Image Reconstruction

Terahertz (THz) sensing is a promising imaging technology for a wide variety of different applications. Extracting the interpretable and physically meaningful parameters for such applications, however, requires solving an inverse problem in which a model function determined by these parameters needs to be fitted to the measured data. Since the underlying optimization problem is nonconvex and very costly to solve, we propose learning the prediction of suitable parameters from the measured data directly. More precisely, we develop a model-based autoencoder in which the encoder network predicts suitable parameters and the decoder is fixed to a physically meaningful model function, such that we can train the encoding network in an unsupervised way. We illustrate numerically that the resulting network is more than 140 times faster than classical optimization techniques while making predictions with only slightly higher objective values. Using such predictions as starting points of local optimization techniques allows us to converge to better local minima about twice as fast as optimization without the network-based initialization.Comment: This is a pre-print of a conference paper published in German Conference on Pattern Recognition (GCPR) 201

End-to-end Interpretable Learning of Non-blind Image Deblurring

Non-blind image deblurring is typically formulated as a linear least-squares problem regularized by natural priors on the corresponding sharp picture's gradients, which can be solved, for example, using a half-quadratic splitting method with Richardson fixed-point iterations for its least-squares updates and a proximal operator for the auxiliary variable updates. We propose to precondition the Richardson solver using approximate inverse filters of the (known) blur and natural image prior kernels. Using convolutions instead of a generic linear preconditioner allows extremely efficient parameter sharing across the image, and leads to significant gains in accuracy and/or speed compared to classical FFT and conjugate-gradient methods. More importantly, the proposed architecture is easily adapted to learning both the preconditioner and the proximal operator using CNN embeddings. This yields a simple and efficient algorithm for non-blind image deblurring which is fully interpretable, can be learned end to end, and whose accuracy matches or exceeds the state of the art, quite significantly, in the non-uniform case.Comment: Accepted at ECCV2020 (poster

A critical review of PASBio's argument structures for biomedical verbs

BACKGROUND: Propositional representations of biomedical knowledge are a critical component of most aspects of semantic mining in biomedicine. However, the proper set of propositions has yet to be determined. Recently, the PASBio project proposed a set of propositions and argument structures for biomedical verbs. This initial set of representations presents an opportunity for evaluating the suitability of predicate-argument structures as a scheme for representing verbal semantics in the biomedical domain. Here, we quantitatively evaluate several dimensions of the initial PASBio propositional structure repository. RESULTS: We propose a number of metrics and heuristics related to arity, role labelling, argument realization, and corpus coverage for evaluating large-scale predicate-argument structure proposals. We evaluate the metrics and heuristics by applying them to PASBio 1.0. CONCLUSION: PASBio demonstrates the suitability of predicate-argument structures for representing aspects of the semantics of biomedical verbs. Metrics related to theta-criterion violations and to the distribution of arguments are able to detect flaws in semantic representations, given a set of predicate-argument structures and a relatively small corpus annotated with them

Distribution of immunodeficiency fact files with XML – from Web to WAP

BACKGROUND: Although biomedical information is growing rapidly, it is difficult to find and retrieve validated data especially for rare hereditary diseases. There is an increased need for services capable of integrating and validating information as well as proving it in a logically organized structure. A XML-based language enables creation of open source databases for storage, maintenance and delivery for different platforms. METHODS: Here we present a new data model called fact file and an XML-based specification Inherited Disease Markup Language (IDML), that were developed to facilitate disease information integration, storage and exchange. The data model was applied to primary immunodeficiencies, but it can be used for any hereditary disease. Fact files integrate biomedical, genetic and clinical information related to hereditary diseases. RESULTS: IDML and fact files were used to build a comprehensive Web and WAP accessible knowledge base ImmunoDeficiency Resource (IDR) available at . A fact file is a user oriented user interface, which serves as a starting point to explore information on hereditary diseases. CONCLUSION: The IDML enables the seamless integration and presentation of genetic and disease information resources in the Internet. IDML can be used to build information services for all kinds of inherited diseases. The open source specification and related programs are available at

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

The minor C-allele of rs2014355 in ACADS is associated with reduced insulin release following an oral glucose load

<p>Abstract</p> <p>Background</p> <p>A genome-wide association study (GWAS) using metabolite concentrations as proxies for enzymatic activity, suggested that two variants: rs2014355 in the gene encoding short-chain acyl-coenzyme A dehydrogenase (<it>ACADS</it>) and rs11161510 in the gene encoding medium-chain acyl-coenzyme A dehydrogenase (<it>ACADM</it>) impair fatty acid β-oxidation. Chronic exposure to fatty acids due to an impaired β-oxidation may down-regulate the glucose-stimulated insulin release and result in an increased risk of type 2 diabetes (T2D). We aimed to investigate whether the two variants associate with altered insulin release following an oral glucose load or with T2D.</p> <p>Methods</p> <p>The variants were genotyped using KASPar^®PCR SNP genotyping system and investigated for associations with estimates of insulin release and insulin sensitivity following an oral glucose tolerance test (OGTT) in a random sample of middle-aged Danish individuals (<it>n</it>_{<it>ACADS </it>}= 4,324; <it>n</it>_{<it>ACADM </it>}= 4,337). The T2D-case-control study involved a total of ~8,300 Danish individuals (<it>n</it>_{<it>ACADS </it>}= 8,313; <it>n</it>_{<it>ACADM </it>}= 8,344).</p> <p>Results</p> <p>In glucose-tolerant individuals the minor C-allele of rs2014355 of <it>ACADS </it>associated with reduced measures of serum insulin at 30 min following an oral glucose load (per allele effect (β) = -3.8% (-6.3%;-1.3%), <it>P </it>= 0.003), reduced incremental area under the insulin curve (β = -3.6% (-6.3%;-0.9%), <it>P </it>= 0.009), reduced acute insulin response (β = -2.2% (-4.2%;0.2%), <it>P </it>= 0.03), and with increased insulin sensitivity ISI_Matsuda(β = 2.9% (0.5%;5.2%), <it>P </it>= 0.02). The C-allele did not associate with two other measures of insulin sensitivity or with a derived disposition index. The C-allele was not associated with T2D in the case-control analysis (OR 1.07, 95% CI 0.96-1.18, <it>P </it>= 0.21). rs11161510 of <it>ACADM </it>did not associate with any indices of glucose-stimulated insulin release or with T2D.</p> <p>Conclusions</p> <p>In glucose-tolerant individuals the minor C-allele of rs2014355 of <it>ACADS </it>was associated with reduced measures of glucose-stimulated insulin release during an OGTT, a finding which in part may be mediated through an impaired β-oxidation of fatty acids.</p