822 research outputs found
Learning and climate change
Learning – i.e. the acquisition of new information that leads to changes in our assessment of uncertainty – plays a prominent role in the international climate policy debate. For example, the view that we should postpone actions until we know more continues to be influential. The latest work on learning and climate change includes new theoretical models, better informed simulations of how learning affects the optimal timing of emissions reductions, analyses of how new information could affect the prospects for reaching and maintaining political agreements and for adapting to climate change, and explorations of how learning could lead us astray rather than closer to the truth. Despite the diversity of this new work, a clear consensus on a central point is that the prospect of learning does not support the postponement of emissions reductions today.Learning; Uncertainty; Climate change; Decision analysis
The Cow: Discovery of a Luminous, Hot, and Rapidly Evolving Transient
We present the ATLAS discovery and initial analysis of the first 18 days of the unusual transient event, ATLAS18qqn/AT2018cow. It is characterized by a high peak luminosity (~1.7 × 1044 erg s−1), rapidly evolving light curves (>5 mag rise to peak in ~3.5 days), and hot blackbody spectra, peaking at ~27,000 K that are relatively featureless and unchanging over the first two weeks. The bolometric light curve cannot be powered by radioactive decay under realistic assumptions. The detection of high-energy emission may suggest a central engine as the powering source. Using a magnetar model, we estimated an ejected mass of 0.1–0.4 M , which lies between that of low-energy core-collapse events and the kilonova, AT2017gfo. The spectra cooled rapidly from 27,000 to 15,000 K in just over two weeks but remained smooth and featureless. Broad and shallow emission lines appear after about 20 days, and we tentatively identify them as He i although they would be redshifted from their rest wavelengths. We rule out that there are any features in the spectra due to intermediate mass elements up to and including the Fe group. The presence of r-process elements cannot be ruled out. If these lines are due to He, then we suggest a low-mass star with residual He as a potential progenitor. Alternatively, models of magnetars formed in neutron star mergers, or accretion onto a central compact object, give plausible matches to the data
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
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
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
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
Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector
Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente
First Observation of and Decays
We have observed new channels for decays with an in the final
state. We study 3-prong tau decays, using the and
\eta\to 3\piz decay modes and 1-prong decays with two \piz's using the
channel. The measured branching fractions are
\B(\tau^{-}\to \pi^{-}\pi^{-}\pi^{+}\eta\nu_{\tau})
=(3.4^{+0.6}_{-0.5}\pm0.6)\times10^{-4} and \B(\tau^{-}\to
\pi^{-}2\piz\eta\nu_{\tau}
=(1.4\pm0.6\pm0.3)\times10^{-4}. We observe clear evidence for
substructure and measure \B(\tau^{-}\to
f_1\pi^{-}\nu_{\tau})=(5.8^{+1.4}_{-1.3}\pm1.8)\times10^{-4}. We have also
searched for production and obtain 90% CL upper limits
\B(\tau^{-}\to \pi^{-}\eta'\nu_\tau)<7.4\times10^{-5} and \B(\tau^{-}\to
\pi^{-}\piz\eta'\nu_\tau)<8.0\times10^{-5}.Comment: 11 page postscript file, postscript file also available through
http://w4.lns.cornell.edu/public/CLN
Small Screen, Big Tourism: The Role of Popular Korean Television Dramas in South Korean Tourism
This paper examines a popular cultural phenomenon originating in Korea which has assumed significance across Asia and beyond. This ‘Korean wave’ or Hallyu includes the circulation and consumption of Korean popular television dramas. An exploratory case study approach is presented to provide insights on the relationships between this phenomenon and patterns of tourism in Korea related to the wider concept of screen-tourism. The paper addresses the relative lack of attention to television programming within the film tourism literature, particularly in non-Western and non-English language settings. Some common assumptions in the film tourism literature are challenged here, including: the inter-changeability of large-screen films and programmes produced for the television; and the inter-cultural circulation of film and television programmes as catalysts for tourism. Our findings illustrate that the inter-cultural circulation of Hallyu television dramas, particularly in neighbouring countries in Asia, may be interpreted in relation to theories of cultural proximity. A need to understand the complex patterns and political economy of distribution, circulation and reception of television programmes is also identified. The paper argues for more research that links visitor flows with television audience research and which recognizes the organizational infrastructures that allow media productions to go beyond circulation in domestic TV markets. Professional expertise and networks, transnational business relationships, ownership and national media regulatory regimes are highlighted, as is the extent to which media professionals and organizations connect with the domestic and international tourism sector
Managing the climate commons at the nexus of ecology, behaviour and economics
Sustainably managing coupled ecological–economic systems requires not only an understanding of the environmental factors that affect them, but also knowledge of the interactions and feedback cycles that operate between resource dynamics and activities attributable to human intervention. The socioeconomic dynamics, in turn, call for an investigation of the behavioural drivers behind human action. We argue that a multidisciplinary approach is needed in order to tackle the increasingly pressing and intertwined environmental challenges faced by modern societies. Academic contributions to climate change policy have been constrained by methodological and terminological differences, so we discuss how programmes aimed at cross-disciplinary education and involvement in governance may help to unlock scholars' potential to propose new solutions
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