Asymptotic normality of the Parzen-Rosenblatt density estimator for strongly mixing random fields

We prove the asymptotic normality of the kernel density estimator (introduced by Rosenblatt (1956) and Parzen (1962)) in the context of stationary strongly mixing random fields. Our approach is based on the Lindeberg's method rather than on Bernstein's small-block-large-block technique and coupling arguments widely used in previous works on nonparametric estimation for spatial processes. Our method allows us to consider only minimal conditions on the bandwidth parameter and provides a simple criterion on the (non-uniform) strong mixing coefficients which do not depend on the bandwith.Comment: 16 page

Nonlinear description of transversal motion in a laminar boundary layer with streaks

The nonlinear streamwise growth of a spanwise periodic array of steady streaks in a flat plate boundary layer is numerically computed using the well known Reduced Navier-Stokes formulation. It is found that the flow configuration changes substantially when the amplitude of the streaks grows and the nonlinear effects come into play. The transversal motion (in the wall normal-spanwise plane), which is normally not considered, becomes non-negligible in the nonlinear regime, and it strongly distorts the streamwise velocity profiles, which end up being quite different from those predicted by the linear theory. We analyze in detail the resulting flow patterns for the nonlinearly saturated streaks, and compare them with available experimental results

Mesenchymal chondrosarcoma: prognostic factors and outcome in 113 patients. A European Musculoskeletal Oncology Society study

BACKGROUND: Mesenchymal chondrosarcoma (MCS) is a distinct, very rare sarcoma with little evidence supporting treatment recommendations. PATIENTS AND METHODS: Specialist centres collaborated to report prognostic factors and outcome for 113 patients. RESULTS: Median age was 30 years (range: 11-80), male/female ratio 1.1. Primary sites were extremities (40%), trunk (47%) and head and neck (13%), 41 arising primarily in soft tissue. Seventeen patients had metastases at diagnosis. Mean follow-up was 14.9 years (range: 1-34), median overall survival (OS) 17 years (95% confidence interval (CI): 10.3-28.6). Ninety-five of 96 patients with localised disease underwent surgery, 54 additionally received combination chemotherapy. Sixty-five of 95 patients are alive and 45 progression-free (5 local recurrence, 34 distant metastases, 11 combined). Median progression-free survival (PFS) and OS were 7 (95% CI: 3.03-10.96) and 20 (95% CI: 12.63-27.36) years respectively. Chemotherapy administration in patients with localised disease was associated with reduced risk of recurrence (P=0.046; hazard ratio (HR)=0.482 95% CI: 0.213-0.996) and death (P=0.004; HR=0.445 95% CI: 0.256-0.774). Clear resection margins predicted less frequent local recurrence (2% versus 27%; P=0.002). Primary site and origin did not influence survival. The absence of metastases at diagnosis was associated with a significantly better outcome (P<0.0001). Data on radiotherapy indications, dose and fractionation were insufficiently complete, to allow comment of its impact on outcomes. Median OS for patients with metastases at presentation was 3 years (95% CI: 0-4.25). CONCLUSIONS: Prognosis in MCS varies considerably. Metastatic disease at diagnosis has the strongest impact on survival. Complete resection and adjuvant chemotherapy should be considered as standard of care for localised disease

Theoretical Properties of Projection Based Multilayer Perceptrons with Functional Inputs

Many real world data are sampled functions. As shown by Functional Data Analysis (FDA) methods, spectra, time series, images, gesture recognition data, etc. can be processed more efficiently if their functional nature is taken into account during the data analysis process. This is done by extending standard data analysis methods so that they can apply to functional inputs. A general way to achieve this goal is to compute projections of the functional data onto a finite dimensional sub-space of the functional space. The coordinates of the data on a basis of this sub-space provide standard vector representations of the functions. The obtained vectors can be processed by any standard method. In our previous work, this general approach has been used to define projection based Multilayer Perceptrons (MLPs) with functional inputs. We study in this paper important theoretical properties of the proposed model. We show in particular that MLPs with functional inputs are universal approximators: they can approximate to arbitrary accuracy any continuous mapping from a compact sub-space of a functional space to R. Moreover, we provide a consistency result that shows that any mapping from a functional space to R can be learned thanks to examples by a projection based MLP: the generalization mean square error of the MLP decreases to the smallest possible mean square error on the data when the number of examples goes to infinity

Assessing potential sources of clustering in individually randomised trials

Recent reviews have shown that while clustering is extremely common in individually randomised trials (for example, clustering within centre, therapist, or surgeon), it is rarely accounted for in the trial analysis. Our aim is to develop a general framework for assessing whether potential sources of clustering must be accounted for in the trial analysis to obtain valid type I error rates (non-ignorable clustering), with a particular focus on individually randomised trials

Activating words without language: beta and theta oscillations reflect lexical access and control processes during verbal and non-verbal object recognition tasks

The intention to name an object modulates neural responses during object recognition tasks. However, the nature of this modulation is still unclear. We established whether a core operation in language, i.e. lexical access, can be observed even when the task does not require language (size-judgment task), and whether response selection in verbal versus non-verbal semantic tasks relies on similar neuronal processes. We measured and compared neuronal oscillatory activities and behavioral responses to the same set of pictures of meaningful objects, while the type of task participants had to perform (picture-naming versus size-judgment) and the type of stimuli to measure lexical access (cognate versus non-cognate) were manipulated. Despite activation of words was facilitated when the task required explicit word-retrieval (picture-naming task), lexical access occurred even without the intention to name the object (non-verbal size-judgment task). Activation of words and response selection were accompanied by beta (25-35 Hz) desynchronization and theta (3-7 Hz) synchronization, respectively. These effects were observed in both picture-naming and size-judgment tasks, suggesting that words became activated via similar mechanisms, irrespective of whether the task involves language explicitly. This finding has important implications to understand the link between core linguistic operations and performance in verbal and non-verbal semantic tasks

The ATLAS Trigger/DAQ Authorlist, version 3.1

This is the ATLAS Trigger/DAQ Authorlist, version 3.1, 17 September 200

The ATLAS Trigger/DAQ Authorlist, version 2.0

This is the ATLAS Trigger/DAQ Authorlist, version 2.0, 31 July 200

Flame spread over solid fuel in low-speed concurrent flow

This research program is concerned with the effect of low speed flow on the spreading and extinction processes of flames over solid fuels. Primary attention is given to flame propagation in concurrent flow - the more hazardous situation from the point of view of fire safety

The ATLAS Trigger/DAQ Authorlist, version 1.0

This is a reference document giving the ATLAS Trigger/DAQ author list, version 1.0 of 20 Nov 2008