A dinosaur trackway from the Purbeck Beds of Swanage, England

During 1962 a dinosaur trackway was unearthed in a quarry of Upper Jurassic/Lower Cretaceous building-stone at Langton Maltravers near Swanage. The primary tracks had been removed initially but secondary impressions were still visible and these were marked with black paint. It was concluded that the prints were made by a tridactyl bipedal species of dinosaur, probably of megalosaurian type. A quantity of overburden covered part of the trackway and it was arranged for this to be removed so that the primary tracks could be collected. The trackway, which was 22 metres long as preserved, showed a somewhat sinuous gait of a true biped with no tail-drag and only occasional evidence of what may have been front foot impressions. Two individuals had made the footprints, walking on a similar course about one metre apart. The tracks of these two were collected, as was a third trackway which went off at an angle to the right. Above the stratum containing the prints was another layer which contained prints of an undoubted iguanodontid type

The first-mover advantage in scientific publication

Mathematical models of the scientific citation process predict a strong "first-mover" effect under which the first papers in a field will, essentially regardless of content, receive citations at a rate enormously higher than papers published later. Moreover papers are expected to retain this advantage in perpetuity -- they should receive more citations indefinitely, no matter how many other papers are published after them. We test this conjecture against data from a selection of fields and in several cases find a first-mover effect of a magnitude similar to that predicted by the theory. Were we wearing our cynical hat today, we might say that the scientist who wants to become famous is better off -- by a wide margin -- writing a modest paper in next year's hottest field than an outstanding paper in this year's. On the other hand, there are some papers, albeit only a small fraction, that buck the trend and attract significantly more citations than theory predicts despite having relatively late publication dates. We suggest that papers of this kind, though they often receive comparatively few citations overall, are probably worthy of our attention.Comment: 7 pages, 3 figure

MonALISA : A Distributed Monitoring Service Architecture

The MonALISA (Monitoring Agents in A Large Integrated Services Architecture) system provides a distributed monitoring service. MonALISA is based on a scalable Dynamic Distributed Services Architecture which is designed to meet the needs of physics collaborations for monitoring global Grid systems, and is implemented using JINI/JAVA and WSDL/SOAP technologies. The scalability of the system derives from the use of multithreaded Station Servers to host a variety of loosely coupled self-describing dynamic services, the ability of each service to register itself and then to be discovered and used by any other services, or clients that require such information, and the ability of all services and clients subscribing to a set of events (state changes) in the system to be notified automatically. The framework integrates several existing monitoring tools and procedures to collect parameters describing computational nodes, applications and network performance. It has built-in SNMP support and network-performance monitoring algorithms that enable it to monitor end-to-end network performance as well as the performance and state of site facilities in a Grid. MonALISA is currently running around the clock on the US CMS test Grid as well as an increasing number of other sites. It is also being used to monitor the performance and optimize the interconnections among the reflectors in the VRVS system.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 8 pages, pdf. PSN MOET00

Improved Measurement of Muon Antineutrino Disappearance in MINOS

We report an improved measurement of ν̅_μ disappearance over a distance of 735 km using the MINOS detectors and the Fermilab Main Injector neutrino beam in a ν̅_μ-enhanced configuration. From a total exposure of 2.95×10^20 protons on target, of which 42% have not been previously analyzed, we make the most precise measurement of Δm̅^2=[2.62_(-0.28)^(+0.31)(stat)±0.09(syst)]×10^(-3)  eV^2 and constrain the ν_μ mixing angle sin^(2)(2θ̅)>0.75 (90% C.L.). These values are in agreement with Δm^2 and sin^(2)(2θ) measured for νμ, removing the tension reported in [ P. Adamson et al. Phys. Rev. Lett. 107 021801 (2011)]

Observation of Muon Neutrino Disappearance with the MINOS Detectors in the NuMI Neutrino Beam

This Letter reports results from the MINOS experiment based on its initial exposure to neutrinos from the Fermilab NuMI beam. The rates and energy spectra of charged current ν_μ interactions are compared in two detectors located along the beam axis at distances of 1 and 735 km. With 1.27×10^(20) 120 GeV protons incident on the NuMI target, 215 events with energies below 30 GeV are observed at the Far Detector, compared to an expectation of 336±14 events. The data are consistent with ν_μ disappearance via oscillations with Δm_(32)^2|=2.74_(-0.26)^(+0.44)×10^(-3)  eV^2 and sin^2(2θ_(23))>0.87 (68% C.L.)

A note on the Zassenhaus product formula

We provide a simple method for the calculation of the terms c_n in the Zassenhaus product $e^{a+b}=e^a e^b \prod_{n=2}^{\infty} e^{c_n}$ for non-commuting a and b. This method has been implemented in a computer program. Furthermore, we formulate a conjecture on how to translate these results into nested commutators. This conjecture was checked up to order n=17 using a computer

First observations of separated atmospheric ν_μ and ν̅ _μ events in the MINOS detector

The complete 5.4 kton MINOS far detector has been taking data since the beginning of August 2003 at a depth of 2070 meters water-equivalent in the Soudan mine, Minnesota. This paper presents the first MINOS observations of ν_μ and ν̅ _μ charged-current atmospheric neutrino interactions based on an exposure of 418 days. The ratio of upward- to downward-going events in the data is compared to the Monte Carlo expectation in the absence of neutrino oscillations, giving R^(data)_(up/down/R^(MC)_(up/down) = 0:62^(+0.19)_(0:14)(stat.) ± 0.02(sys.). An extended maximum likelihood analysis of the observed L/E distributions excludes the null hypothesis of no neutrino oscillations at the 98% confidence level. Using the curvature of the observed muons in the 1.3 T MINOS magnetic field ν_μ and ν̅ _μ interactions are separated. The ratio of ν̅ _μ to ν_μ events in the data is compared to the Monte Carlo expectation assuming neutrinos and antineutrinos oscillate in the same manner, giving R^(data)_(ν_μ/ν̅ _μ) / R^(MC)_(ν_μ/ν̅ _μ) = 0.96^(+0:38)_(0.27)(stat.) ± 0.15(sys.), where the errors are the statistical and systematic uncertainties. Although the statistics are limited, this is the first direct observation of atmospheric neutrino interactions separately for ν_μ and ν̅ _μ

NN^k networks for Content-Based Image Retrieval

This paper describes a novel interaction technique to support content-based image search in large image collections. The idea is to represent each image as a vertex in a directed graph. Given a set of image features, an arc is established between two images if there exists at least one combination of features for which one image is retrieved as the nearest neighbour of the other. Each arc is weighted by the proportion of feature combinations for which the nearest neighbour relationship holds. By thus integrating the retrieval results over all possible feature combinations, the resulting network helps expose the semantic richness of images and thus provides an elegant solution to the problem of feature weighting in content-based image retrieval.We give details of the method used for network generation and describe the ways a user can interact with the structure. We also provide an analysis of the network’s topology and provide quantitative evidence for the usefulness of the technique

Why social networks are different from other types of networks

We argue that social networks differ from most other types of networks, including technological and biological networks, in two important ways. First, they have non-trivial clustering or network transitivity, and second, they show positive correlations, also called assortative mixing, between the degrees of adjacent vertices. Social networks are often divided into groups or communities, and it has recently been suggested that this division could account for the observed clustering. We demonstrate that group structure in networks can also account for degree correlations. We show using a simple model that we should expect assortative mixing in such networks whenever there is variation in the sizes of the groups and that the predicted level of assortative mixing compares well with that observed in real-world networks.Comment: 9 pages, 2 figure