CMB Lensing Reconstruction on the Full Sky

Gravitational lensing of the microwave background by the intervening dark matter mainly arises from large-angle fluctuations in the projected gravitational potential and hence offers a unique opportunity to study the physics of the dark sector at large scales. Studies with surveys that cover greater than a percent of the sky will require techniques that incorporate the curvature of the sky. We lay the groundwork for these studies by deriving the full sky minimum variance quadratic estimators of the lensing potential from the CMB temperature and polarization fields. We also present a general technique for constructing these estimators, with harmonic space convolutions replaced by real space products, that is appropriate for both the full sky limit and the flat sky approximation. This also extends previous treatments to include estimators involving the temperature-polarization cross-correlation and should be useful for next generation experiments in which most of the additional information from polarization comes from this channel due to sensitivity limitations.Comment: Accepted for publication in Phys. Rev. D; typos correcte

Lensing Reconstruction with CMB Temperature and Polarization

Weak gravitational lensing by intervening large-scale structure induces a distinct signature in the cosmic microwave background (CMB) that can be used to reconstruct the weak-lensing displacement map. Estimators for individual Fourier modes of this map can be combined to produce an estimator for the lensing-potenial power spectrum. The naive estimator for this quantity will be biased upwards by the uncertainty associated with reconstructing individual modes; we present an iterative scheme for removing this bias. The variance and covariance of the lensing-potenial power spectrum estimator are calculated and evaluated numerically in a $\Lambda$CDM universe for Planck and future polarization-sensitive CMB experiments.Comment: 15 pages, 3 figures, submitted to PR

High-throughput screening of monoclonal antibodies against plant cell wall glycans by hierarchical clustering of their carbohydrate microarray binding profiles

Antibody-producing hybridoma cell lines were created following immunisation with a crude extract of cell wall polymers from the plant Arabidopsis thaliana. In order to rapidly screen the specificities of individual monoclonal antibodies (mAbs), their binding to microarrays containing 50 cell wall glycans immobilized on nitrocellulose was assessed. Hierarchical clustering of microarray binding profiles from newly produced mAbs, together with the profiles for mAbs with previously defined specificities allowed the rapid assignments of mAb binding to antigen classes. mAb specificities were further investigated using subsequent immunochemical and biochemical analyses and two novel mAbs are described in detail. mAb LM13 binds to an arabinanase-sensitive pectic epitope and mAb LM14, binds to an epitope occurring on arabinogalactan-proteins. Both mAbs display novel patterns of recognition of cell walls in plant materials

The last stand before MAP: cosmological parameters from lensing, CMB and galaxy clustering

Cosmic shear measurements have now improved to the point where they deserve to be treated on par with CMB and galaxy clustering data for cosmological parameter analysis, using the full measured aperture mass variance curve rather than a mere phenomenological parametrization thereof. We perform a detailed 9-parameter analysis of recent lensing (RCS), CMB (up to Archeops) and galaxy clustering (2dF) data, both separately and jointly. CMB and 2dF data are consistent with a simple flat adiabatic scale-invariant model with Omega_Lambda=0.72+/-0.09, omega_cdm=0.115+/- 0.013, omega_b=0.024+/-0.003, and a hint of reionization around z~8. Lensing helps further tighten these constraints, but reveals tension regarding the power spectrum normalization: including the RCS survey results raises sigma8 significantly and forces other parameters to uncomfortable values. Indeed, sigma8 is emerging as the currently most controversial cosmological parameter, and we discuss possible resolutions of this sigma8 problem. We also comment on the disturbing fact that many recent analyses (including this one) obtain error bars smaller than the Fisher matrix bound. We produce a CMB power spectrum combining all existing experiments, and using it for a "MAP versus world" comparison next month will provide a powerful test of how realistic the error estimates have been in the cosmology community.Comment: Added references and Fisher error discussion. Combined CMB data, window and covariance matrix for January "MAP vs World" contest at http://www.hep.upenn.edu/~max/cmblsslens.html or from [email protected]

Track A Basic Science

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138319/1/jia218438.pd

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe