University of California, Santa Cruz

About: University of California, Santa Cruz is a education organization based out in Santa Cruz, California, United States. It is known for research contribution in the topics: Galaxy & Population. The organization has 15541 authors who have published 44120 publications receiving 2759983 citations. The organization is also known as: UCSC & UC, Santa Cruz.

Measurements of the Higgs boson production and decay rates and constraints on its couplings from a combined ATLAS and CMS analysis of the LHC pp collision data at √s = 7 and 8 TeV

Abstract: Combined ATLAS and CMS measurements of the Higgs boson production and decay rates, as well as constraints on its couplings to vector bosons and fermions, are presented. The combination is based on the analysis of five production processes, namely gluon fusion, vector boson fusion, and associated production with a $W$ or a $Z$ boson or a pair of top quarks, and of the six decay modes $H \to ZZ, WW$, $\gamma\gamma, \tau\tau, bb$, and $\mu\mu$. All results are reported assuming a value of 125.09 GeV for the Higgs boson mass, the result of the combined measurement by the ATLAS and CMS experiments. The analysis uses the CERN LHC proton--proton collision data recorded by the ATLAS and CMS experiments in 2011 and 2012, corresponding to integrated luminosities per experiment of approximately 5 fb$^{-1}$ at $\sqrt{s}=7$ TeV and 20 fb$^{-1}$ at $\sqrt{s} = 8$ TeV. The Higgs boson production and decay rates measured by the two experiments are combined within the context of three generic parameterisations: two based on cross sections and branching fractions, and one on ratios of coupling modifiers. Several interpretations of the measurements with more model-dependent parameterisations are also given. The combined signal yield relative to the Standard Model prediction is measured to be 1.09 $\pm$ 0.11. The combined measurements lead to observed significances for the vector boson fusion production process and for the $H \to \tau\tau$ decay of $5.4$ and $5.5$ standard deviations, respectively. The data are consistent with the Standard Model predictions for all parameterisations considered.

Classifying Software Changes: Clean or Buggy?

Abstract: This paper introduces a new technique for predicting latent software bugs, called change classification. Change classification uses a machine learning classifier to determine whether a new software change is more similar to prior buggy changes or clean changes. In this manner, change classification predicts the existence of bugs in software changes. The classifier is trained using features (in the machine learning sense) extracted from the revision history of a software project stored in its software configuration management repository. The trained classifier can classify changes as buggy or clean, with a 78 percent accuracy and a 60 percent buggy change recall on average. Change classification has several desirable qualities: 1) The prediction granularity is small (a change to a single file), 2) predictions do not require semantic information about the source code, 3) the technique works for a broad array of project types and programming languages, and 4) predictions can be made immediately upon the completion of a change. Contributions of this paper include a description of the change classification approach, techniques for extracting features from the source code and change histories, a characterization of the performance of change classification across 12 open source projects, and an evaluation of the predictive power of different groups of features.

The UCSC Genome Browser database: 2016 update.

Abstract: For the past 15 years, the UCSC Genome Browser (http://genome.ucsc.edu/) has served the international research community by offering an integrated platform for viewing and analyzing information from a large database of genome assemblies and their associated annotations. The UCSC Genome Browser has been under continuous development since its inception with new data sets and software features added frequently. Some release highlights of this year include new and updated genome browsers for various assemblies, including bonobo and zebrafish; new gene annotation sets; improvements to track and assembly hub support; and a new interactive tool, the "Data Integrator", for intersecting data from multiple tracks. We have greatly expanded the data sets available on the most recent human assembly, hg38/GRCh38, to include updated gene prediction sets from GENCODE, more phenotype- and disease-associated variants from ClinVar and ClinGen, more genomic regulatory data, and a new multiple genome alignment.

Facile Synthesis of Highly Photoactive α-Fe2O3-Based Films for Water Oxidation

Abstract: This work reports a facile method for preparing highly photoactive α-Fe2O3 films as well as their implementation as photoanodes for water oxidation. Transparent α-Fe2O3 films were prepared by a new deposition–annealing (DA) process using nontoxic iron(III) chloride as the Fe precursor, followed by annealing at 550 °C in air. Ti-doped α-Fe2O3 films were prepared by the same method, with titanium butoxide added as the Ti precursor. Impedance measurements show that the Ti-dopant serves as an electron donor and increases the donor density by 2 orders of magnitude. The photoelectrochemical performance of undoped and Ti-doped α-Fe2O3 photoanodes was characterized and optimized through controlled variation of the Fe and Ti precursor concentration, annealing conditions, and the number of DA cycles. Compared to the undoped sample, the photocurrent onset potential of Ti-doped α-Fe2O3 is shifted about 0.1–0.2 V to lower potential, thus improving the photocurrent and incident photon to current conversion efficiency (...

Elephant shark genome provides unique insights into gnathostome evolution

Abstract: The emergence of jawed vertebrates (gnathostomes) from jawless vertebrates was accompanied by major morphological and physiological innovations, such as hinged jaws, paired fins and immunoglobulin-based adaptive immunity. Gnathostomes subsequently diverged into two groups, the cartilaginous fishes and the bony vertebrates. Here we report the whole-genome analysis of a cartilaginous fish, the elephant shark (Callorhinchus milii). We find that the C. milii genome is the slowest evolving of all known vertebrates, including the ‘living fossil’ coelacanth, and features extensive synteny conservation with tetrapod genomes, making it a good model for comparative analyses of gnathostome genomes. Our functional studies suggest that the lack of genes encoding secreted calcium-binding phosphoproteins in cartilaginous fishes explains the absence of bone in their endoskeleton. Furthermore, the adaptive immune system of cartilaginous fishes is unusual: it lacks the canonical CD4 co-receptor and most transcription factors, cytokines and cytokine receptors related to the CD4 lineage, despite the presence of polymorphic major histocompatibility complex class II molecules. It thus presents a new model for understanding the origin of adaptive immunity. Whole-genome analysis of the elephant shark, a cartilaginous fish, shows that it is the slowest evolving of all known vertebrates, lacks critical bone formation genes and has an unusual adaptive immune system. The elephant shark (Callorhinchus milii) is a cartilaginous fish native to the temperate waters off southern Australia and New Zealand, living at depths of 200 to 500 metres and migrating into shallow waters during spring for breeding. The genome sequence is published in this issue of Nature. Comparison with other vertebrate genomes shows that it is the slowest evolving genome of all known vertebrates — coelacanth included. Genome analysis points to an unusual adaptive immune system lacking the CD4 receptor and some associated cytokines, indicating that cartilaginous fishes possess a primordial gnathostome adaptive immune system. Also absent are genes encoding secreted calcium-binding phosphoproteins, in line with the absence of bone in cartilaginous fish.