On the truncation of the harmonic oscillator wavepacket

We present an interesting result regarding the implication of truncating the wavepacket of the harmonic oscillator. We show that disregarding the non-significant tails of a function which is the superposition of eigenfunctions of the harmonic oscillator has a remarkable consequence: namely, there exist infinitely many different superpositions giving rise to the same function on the interval. Uniqueness, in the case of a wavepacket, is restored by a postulate of quantum mechanics

Stringent neutron-star limits on large extra dimensions

Supernovae (SNe) are copious sources for Kaluza-Klein gravitons which are generic for theories with large extra dimensions. These massive particles are produced with average velocities ~0.5 c so that many of them are gravitationally retained by the SN core. Every neutron star thus has a halo of KK gravitons which decay into nu bar-nu, e^+e^- and gamma gamma on time scales \~10^9 years. The EGRET gamma-flux limits (E_gamma ~ 100 MeV) for nearby neutron stars constrain the fundamental scale for n=2 extra dimensions to M >500 TeV, and M>30 TeV for n=3. The upcoming GLAST satellite is a factor ~30 more sensitive and thus may detect KK decays, for example at the nearby neutron star RX J185635--3754. The requirement that neutron stars are not excessively heated by KK decays implies M>1700 TeV for n=2, and M>60 TeV for n=3.Comment: Minor changes, matches version to appear in PR

Atomic structure and vibrational properties of icosahedral B4_4C boron carbide

The atomic structure of icosahedral B$_4$C boron carbide is determined by comparing existing infra-red absorption and Raman diffusion measurements with the predictions of accurate {\it ab initio} lattice-dynamical calculations performed for different structural models. This allows us to unambiguously determine the location of the carbon atom within the boron icosahedron, a task presently beyond X-ray and neutron diffraction ability. By examining the inter- and intra-icosahedral contributions to the stiffness we show that, contrary to recent conjectures, intra-icosahedral bonds are harder.Comment: 9 pages including 3 figures, accepted in Physical Review Letter

The Interstellar Environment of our Galaxy

We review the current knowledge and understanding of the interstellar medium of our galaxy. We first present each of the three basic constituents - ordinary matter, cosmic rays, and magnetic fields - of the interstellar medium, laying emphasis on their physical and chemical properties inferred from a broad range of observations. We then position the different interstellar constituents, both with respect to each other and with respect to stars, within the general galactic ecosystem.Comment: 39 pages, 12 figures (including 3 figures in 2 parts

X-ray absorption spectroscopy study of diluted magnetic semiconductors: Zn1-xMxSe (M = Mn, Fe, Co) and Zn1-xMnxY (Y = Se, Te)

We have investigated 3d electronic states of doped transition metals in II-VI diluted magnetic semiconductors, Zn1-xMxSe (M = Mn, Fe, Co) and Zn1-xMnxY (Y = Se, Te), using the transition-metal L2,3-edge X-ray absorption spectroscopy (XAS) measurements. In order to explain the XAS spectra, we employed a tetragonal cluster model calculation, which includes not only the full ionic multiplet structure but also configuration interaction (CI). The results show that CI is essential to describe the experimental spectra adequately, indicating the strong hybridization between the transition metal 3d and the ligand p orbitals. In the study of Zn1-xMnxY (Y = Se, Te), we also found considerable spectral change in the Mn L2,3-edge XAS spectra for different ligands, confirming the importance of the hybridization effects in these materials.Comment: This paper consists of 22 pages including 4 figures. This paper is submitted to Physical Review

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Fitting the integrated Spectral Energy Distributions of Galaxies

Fitting the spectral energy distributions (SEDs) of galaxies is an almost universally used technique that has matured significantly in the last decade. Model predictions and fitting procedures have improved significantly over this time, attempting to keep up with the vastly increased volume and quality of available data. We review here the field of SED fitting, describing the modelling of ultraviolet to infrared galaxy SEDs, the creation of multiwavelength data sets, and the methods used to fit model SEDs to observed galaxy data sets. We touch upon the achievements and challenges in the major ingredients of SED fitting, with a special emphasis on describing the interplay between the quality of the available data, the quality of the available models, and the best fitting technique to use in order to obtain a realistic measurement as well as realistic uncertainties. We conclude that SED fitting can be used effectively to derive a range of physical properties of galaxies, such as redshift, stellar masses, star formation rates, dust masses, and metallicities, with care taken not to over-interpret the available data. Yet there still exist many issues such as estimating the age of the oldest stars in a galaxy, finer details ofdust properties and dust-star geometry, and the influences of poorly understood, luminous stellar types and phases. The challenge for the coming years will be to improve both the models and the observational data sets to resolve these uncertainties. The present review will be made available on an interactive, moderated web page (sedfitting.org), where the community can access and change the text. The intention is to expand the text and keep it up to date over the coming years.Comment: 54 pages, 26 figures, Accepted for publication in Astrophysics & Space Scienc

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment