An improved method for measuring muon energy using the truncated mean of dE/dx

The measurement of muon energy is critical for many analyses in large Cherenkov detectors, particularly those that involve separating extraterrestrial neutrinos from the atmospheric neutrino background. Muon energy has traditionally been determined by measuring the specific energy loss (dE/dx) along the muon's path and relating the dE/dx to the muon energy. Because high-energy muons (E_mu > 1 TeV) lose energy randomly, the spread in dE/dx values is quite large, leading to a typical energy resolution of 0.29 in log10(E_mu) for a muon observed over a 1 km path length in the IceCube detector. In this paper, we present an improved method that uses a truncated mean and other techniques to determine the muon energy. The muon track is divided into separate segments with individual dE/dx values. The elimination of segments with the highest dE/dx results in an overall dE/dx that is more closely correlated to the muon energy. This method results in an energy resolution of 0.22 in log10(E_mu), which gives a 26% improvement. This technique is applicable to any large water or ice detector and potentially to large scintillator or liquid argon detectors.Comment: 12 pages, 16 figure

All-particle cosmic ray energy spectrum measured with 26 IceTop stations

We report on a measurement of the cosmic ray energy spectrum with the IceTop air shower array, the surface component of the IceCube Neutrino Observatory at the South Pole. The data used in this analysis were taken between June and October, 2007, with 26 surface stations operational at that time, corresponding to about one third of the final array. The fiducial area used in this analysis was 0.122 km^2. The analysis investigated the energy spectrum from 1 to 100 PeV measured for three different zenith angle ranges between 0{\deg} and 46{\deg}. Because of the isotropy of cosmic rays in this energy range the spectra from all zenith angle intervals have to agree. The cosmic-ray energy spectrum was determined under different assumptions on the primary mass composition. Good agreement of spectra in the three zenith angle ranges was found for the assumption of pure proton and a simple two-component model. For zenith angles {\theta} < 30{\deg}, where the mass dependence is smallest, the knee in the cosmic ray energy spectrum was observed between 3.5 and 4.32 PeV, depending on composition assumption. Spectral indices above the knee range from -3.08 to -3.11 depending on primary mass composition assumption. Moreover, an indication of a flattening of the spectrum above 22 PeV were observed.Comment: 38 pages, 17 figure

Neutrino oscillation studies with IceCube-DeepCore

AbstractIceCube, a gigaton-scale neutrino detector located at the South Pole, was primarily designed to search for astrophysical neutrinos with energies of PeV and higher. This goal has been achieved with the detection of the highest energy neutrinos to date. At the other end of the energy spectrum, the DeepCore extension lowers the energy threshold of the detector to approximately 10 GeV and opens the door for oscillation studies using atmospheric neutrinos. An analysis of the disappearance of these neutrinos has been completed, with the results produced being complementary with dedicated oscillation experiments. Following a review of the detector principle and performance, the method used to make these calculations, as well as the results, is detailed. Finally, the future prospects of IceCube-DeepCore and the next generation of neutrino experiments at the South Pole (IceCube-Gen2, specifically the PINGU sub-detector) are briefly discussed

A muon-track reconstruction exploiting stochastic losses for large-scale Cherenkov detectors

IceCube is a cubic-kilometer Cherenkov telescope operating at the South Pole. The main goal of IceCube is the detection of astrophysical neutrinos and the identification of their sources. High-energy muon neutrinos are observed via the secondary muons produced in charge current interactions with nuclei in the ice. Currently, the best performing muon track directional reconstruction is based on a maximum likelihood method using the arrival time distribution of Cherenkov photons registered by the experiment\u27s photomultipliers. A known systematic shortcoming of the prevailing method is to assume a continuous energy loss along the muon track. However at energies >1 TeV the light yield from muons is dominated by stochastic showers. This paper discusses a generalized ansatz where the expected arrival time distribution is parametrized by a stochastic muon energy loss pattern. This more realistic parametrization of the loss profile leads to an improvement of the muon angular resolution of up to 20% for through-going tracks and up to a factor 2 for starting tracks over existing algorithms. Additionally, the procedure to estimate the directional reconstruction uncertainty has been improved to be more robust against numerical errors

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

Metastasising fibroblasts show an HDAC6-dependent increase in migration speed and loss of directionality linked to major changes in the vimentin interactome

Metastasising cells express the intermediate filament protein vimentin, which is used to diagnose invasive tumours in the clinic. We aimed to clarify how vimentin regulates the motility of metastasising fibroblasts. STED super-resolution microscopy, live-cell imaging and quantitative proteomics revealed that oncogene-expressing and metastasising fibroblasts show a less-elongated cell shape, reduced cell spreading, increased cell migration speed, reduced directionality, and stronger coupling between these migration parameters compared to normal control cells. In total, we identified and compared 555 proteins in the vimentin interactome. In metastasising cells, the levels of keratin 18 and Rab5C were increased, while those of actin and collagen were decreased. Inhibition of HDAC6 reversed the shape, spreading and migration phenotypes of metastasising cells back to normal. Inhibition of HDAC6 also decreased the levels of talin 1, tropomyosin, Rab GDI β, collagen and emilin 1 in the vimentin interactome, and partially reversed the nanoscale vimentin organisation in oncogene-expressing cells. These findings describe the changes in the vimentin interactome and nanoscale distribution that accompany the defective cell shape, spreading and migration of metastasising cells. These results support the hypothesis that oncogenes can act through HDAC6 to regulate the vimentin binding of the cytoskeletal and cell–extracellular matrix adhesion components that contribute to the defective motility of metastasising cells

Actionable Mining of Large, Multi-relational Data using Localized Predictive Models

Abstract. Many large datasets associated with modern predictive data mining applications are quite complex and heterogeneous, possibly involving multiple relations, or exhibiting a dyadic nature with associated side-information. For example, one may be interested in predicting the preferences of a large set of customers for a variety of products, given various properties of both customers and products, as well as past purchase history, a social network on the customers, and a conceptual hierarchy on the products. This article provides an overview of recent innovative approaches to predictive modeling for such types of data, and also provides some concrete application scenarios to highlight the issues involved. The common philosophy in all the approaches described is to pursue a simultaneous problem decomposition and modeling strategy that can exploit heterogeneity in behavior, use the wide variety of information available and also yield relatively more interpretable solutions as compared to global ”one-shot ” approaches. Since both the problem domains and approaches considered are quite new, we also highlight the potential for further investigations on several occasions throughout this article.