Artifact mitigation of ptychography integrated with on-the-fly scanning probe microscopy

We report our experiences with conducting ptychography simultaneously with the X-ray fluorescence measurement using the on-the-fly mode for efficient multi-modality imaging. We demonstrate that the periodic artifact inherent to the raster scan pattern can be mitigated using a sufficiently fine scan step size to provide an overlap ratio of >70%. This allows us to obtain transmitted phase contrast images with enhanced spatial resolution from ptychography while maintaining the fluorescence imaging with continuous-motion scans on pixelated grids. This capability will greatly improve the competence and throughput of scanning probe X-ray microscopy

Structure and Transport in Coatings from Multiscale Computed Tomography of Coatings-New Perspectives for Eelectrochemical Impedance Spectroscopy Modeling?

Computed Tomography (CT) is an approach that has been extensively applied in many areas of science from understanding structures in living organisms to materials science. In materials science, the study of structures within coatings presents challenges on at least two different levels. First, the structure of the coatings needs to be understood from the atomic scale, where dissolution reactions begin, up to length scales which cover the aggregation of inhibitors and other additives, which take place at ∼10−5 m, i.e. 4 to 5 orders of magnitude. CT is a favourable imaging technique since it allows multiscale information to be obtained non-destructively down to tens of nanometres. In this study X-ray absorption contrast imaging has been used to examine structures created using strontium chromate (SrCrO4) particles embedded in an epoxy film. It has been found that SrCrO4 particles can form clusters that extend a few hundred microns in the plane of the film, span the thickness of the film and have fractal characteristics. There are also volumes of low density epoxy of similar sizes and characteristics to the SrCrO4 clusters. The SrCrO4 clusters have a strong influence on the leaching behaviour since the release changes with time. Initially, leaching is controlled by direct dissolution but, as the clusters dissolve, the release is dominated by the fractal dimension of the cluster. The dissolved clusters leave behind voids filled with electrolyte that provide alternative transport pathways for corrosive ions through the polymer. In this paper, the nature of these clusters will be reviewed and the implication for transport properties and electrochemical assessment will be explored

FERM: A FEature-space Representation Measure for Improved Model Evaluation

Understanding whether a particular dataset and task are well represented by a deep learning model can be as crucial as the model's prediction accuracy in many applications. Currently, best prediction performance for large, modern datasets is often achieved by complex and difficult to interpret deep learning models. As deep learning model size and complexity increases compared to the size of the training dataset, the capacity of the model to overfit to inappropriate features and perform poorly or unreliably also increases. Unreliability may not be obvious in traditional performance measures during evaluation so it is important to also consider how well the model is representing the current data distribution. There has previously been little work focusing on measuring this space. We introduce several measures that we collectively name FERM: A FEature-space Representation Measure for determining how well the current feature space representation models the current data distribution and task. We compared our new measures and potential candidates from other related research areas. We demonstrated that our new method, along with two others, have excellent potential to be used for measuring how well a trained model is currently representing a dataset and task. These findings have many implications for deep learning research and applications, including, evaluating when the current model is no longer representing new data well to reduce the frequency of computationally expensive retraining of models, assessing for hard to evaluate failure modes such as model biases that result in particular input samples being poorly represented, guidance on the best hyperparameters to use when updating models with limited new data

A road to reality with topological superconductors

Topological states of matter are a source of low-energy quasiparticles, bound to a defect or propagating along the surface. In a superconductor these are Majorana fermions, described by a real rather than a complex wave function. The absence of complex phase factors promises protection against decoherence in quantum computations based on topological superconductivity. This is a tutorial style introduction written for a Nature Physics focus issue on topological matter.Comment: pre-copy-editing, author-produced version of the published paper: 4 pages, 2 figure

Study of the Decays B0 --> D(*)+D(*)-

The decays B0 --> D*+D*-, B0 --> D*+D- and B0 --> D+D- are studied in 9.7 million Y(4S) --> BBbar decays accumulated with the CLEO detector. We determine Br(B0 --> D*+D*-) = (9.9+4.2-3.3+-1.2)e-4 and limit Br(B0 --> D*+D-) < 6.3e-4 and Br(B0 --> D+D-) < 9.4e-4 at 90% confidence level (CL). We also perform the first angular analysis of the B0 --> D*+D*- decay and determine that the CP-even fraction of the final state is greater than 0.11 at 90% CL. Future measurements of the time dependence of these decays may be useful for the investigation of CP violation in neutral B meson decays.Comment: 21 pages, 5 figures, submitted to Phys. Rev.

Measurement of B(/\c->pKpi)

The /\c->pKpi yield has been measured in a sample of two-jet continuum events containing a both an anticharm tag (Dbar) as well as an antiproton (e+e- -> Dbar pbar X), with the antiproton in the hemisphere opposite the Dbar. Under the hypothesis that such selection criteria tag e+e- -> Dbar pbar (/\c) X events, the /\c->pkpi branching fraction can be determined by measuring the pkpi yield in the same hemisphere as the antiprotons in our Dbar pbar X sample. Combining our results from three independent types of anticharm tags, we obtain B(/\c->pKpi)=(5.0+/-0.5+/-1.2)

Improved Measurement of the Pseudoscalar Decay Constant fDsf_{D_{s}}

We present a new determination of the Ds decay constant, f_{Ds} using 5 million continuum charm events obtained with the CLEO II detector. Our value is derived from our new measured ratio of widths for Ds -> mu nu/Ds -> phi pi of 0.173+/- 0.021 +/- 0.031. Taking the branching ratio for Ds -> phi pi as (3.6 +/- 0.9)% from the PDG, we extract f_{Ds} = (280 +/- 17 +/- 25 +/- 34){MeV}. We compare this result with various model calculations.Comment: 23 page postscript file, postscript file also available through http://w4.lns.cornell.edu/public/CLN

Search for the Decays B^0 -> D^{(*)+} D^{(*)-}

Using the CLEO-II data set we have searched for the Cabibbo-suppressed decays B^0 -> D^{(*)+} D^{(*)-}. For the decay B^0 -> D^{*+} D^{*-}, we observe one candidate signal event, with an expected background of 0.022 +/- 0.011 events. This yield corresponds to a branching fraction of Br(B^0 -> D^{*+} D^{*-}) = (5.3^{+7.1}_{-3.7}(stat) +/- 1.0(syst)) x 10^{-4} and an upper limit of Br(B^0 -> D^{*+} D^{*-}) D^{*\pm} D^\mp and B^0 -> D^+ D^-, no significant excess of signal above the expected background level is seen, and we calculate the 90% CL upper limits on the branching fractions to be Br(B^0 -> D^{*\pm} D^\mp) D^+ D^-) < 1.2 x 10^{-3}.Comment: 12 page postscript file also available through http://w4.lns.cornell.edu/public/CLNS, submitted to Physical Review Letter

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives