Performance of self bit synchronizers for binary overlapping signals

This research is concerned with the optimum and suboptimum ways of providing self bit synchronization for binary overlapping signals. A maximum likelihood synchronizer is derived as the optimum approach. The suboptimum ways are those employing decision-directed feedback and matched derivative filter techniques which are proposed for treating the overlapping signals. Combining the two suboptimum techniques along with the bandlimited version of the overlapping signal, a suboptimum synchronizer is derived. The performance of the above synchronizer is evaluated by Monte Carlo simulation techniques. Finally, a bit synchronizer using nonlinear filtering theory is considered. The performance of a nonlinear bit synchronizer is discussed --Abstract, page ii

Fault detection on sequential machines

This paper presents an algorithm for deriving an optimum test sequence for detecting faults in a synchronous machine. In this study, the flow table is used as a tool to generate the fault detection tests. The fault stuck-at-1 (or stuck-at-0 ) is said to be present when a permanent signal valued 1 (or 0) appears on a component of the machine. Only single faults are treated . The result of the procedure is one or more test sequences guaranteed to detect a set of faults (Fp). First, sequential machines with feedback lines as memory elements are considered . Then the memory elements are changed to R-S flip-flops. Finally, several suggestions for further work are made --Abstract, Page ii

Nonequilibrium transport in quantum impurity models: Exact path integral simulations

We simulate the nonequilibrium dynamics of two generic many-body quantum impurity models by employing the recently developed iterative influence-functional path integral method [Phys. Rev. B {\bf 82}, 205323 (2010)]. This general approach is presented here in the context of quantum transport in molecular electronic junctions. Models of particular interest include the single impurity Anderson model and the related spinless two-state Anderson dot. In both cases we study the time evolution of the dot occupation and the current characteristics at finite temperature. A comparison to mean-field results is presented, when applicable

The MALATANG Survey : The L GAS-L IR Correlation on Sub-kiloparsec Scale in Six Nearby Star-forming Galaxies as Traced by HCN J = 4 → 3 and HCO + J = 4 → 3

This is an author-created, un-copyedited version of an article published in The Astrophysical Journal. The Version of Record is available online at https://doi.org/10.3847/1538-4357/aac512.We present HCN J = 4→3 and HCO+ J = 4→3 maps of six nearby star-forming galaxies, NGC 253, NGC 1068, IC 342, M82, M83, and NGC 6946, obtained with the James Clerk Maxwell Telescope as part of the MALATANG survey. All galaxies were mapped in the central 2×2 region at 14 (FWHM) resolution (corresponding to linear scales of ∼0.2-1.0 kpc). The LIR-Ldense relation, where the dense gas is traced by the HCN J = 4→3 and the HCO+ J = 4→3 emission, measured in our sample of spatially resolved galaxies is found to follow the linear correlation established globally in galaxies within the scatter. We find that the luminosity ratio, LIR/Ldense, shows systematic variations with LIR within individual spatially resolved galaxies, whereas the galaxy-integrated ratios vary little. A rising trend is also found between LIR/Ldense ratio and the warm-dust temperature gauged by the 70 μm/100 μm flux ratio. We find that the luminosity ratios of IR/HCN (4-3) and IR/HCO+ (4-3), which can be taken as a proxy for the star formation efficiency (SFE) in the dense molecular gas (SFE dense), appear to be nearly independent of the dense gas fraction ( f dense) for our sample of galaxies. The SFE of the total molecular gas (SFEmol) is found to increase substantially with f dense when combining our data with those on local (ultra)luminous infrared galaxies and high-z quasars. The mean LHCN(4-3) LHCO+(4-3) line ratio measured for the six targeted galaxies is 0.9±0.6. No significant correlation is found for the L'HCN(4-3) L'HCO+(4-3) ratio with the star formation rate as traced by L IR, nor with the warm-dust temperature, for the different populations of galaxies.Peer reviewe

Cross-National Differences in Victimization : Disentangling the Impact of Composition and Context

Varying rates of criminal victimization across countries are assumed to be the outcome of countrylevel structural constraints that determine the supply ofmotivated o¡enders, as well as the differential composition within countries of suitable targets and capable guardianship. However, previous empirical tests of these ‘compositional’ and ‘contextual’ explanations of cross-national di¡erences have been performed upon macro-level crime data due to the unavailability of comparable individual-level data across countries. This limitation has had two important consequences for cross-national crime research. First, micro-/meso-level mechanisms underlying cross-national differences cannot be truly inferred from macro-level data. Secondly, the e¡ects of contextual measures (e.g. income inequality) on crime are uncontrolled for compositional heterogeneity. In this paper, these limitations are overcome by analysing individual-level victimization data across 18 countries from the International CrimeVictims Survey. Results from multi-level analyses on theft and violent victimization indicate that the national level of income inequality is positively related to risk, independent of compositional (i.e. micro- and meso-level) di¡erences. Furthermore, crossnational variation in victimization rates is not only shaped by di¡erences in national context, but also by varying composition. More speci¢cally, countries had higher crime rates the more they consisted of urban residents and regions with lowaverage social cohesion.

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

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

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

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