538 research outputs found
Localization of Electrical Insulation Failures in Superconducting Collared Coils by Analysis of the Distortion of a Pulsed Magnetic Field
The localization of possible electrical faults in superconducting accelerator magnets may, in most cases, be a complex, expensive and time-consuming process. In particular, inter-turn short circuits and failures of the ground insulation are well detectable when the magnet is collared, but often disappear after disassembly for repair due to the release of the pre-stress in the coils. The fault localization method presented in this paper is based on the measurement and analysis of the magnetic field generated inside the magnet aperture by a high voltage pulse. The presence of the fault modifies the distribution of the current in the coils and produces a distortion of the magnetic field. The described method aims at locating both the longitudinal and azimuthal position of the fault-affected area. The test method, the transient case FEM models and the implemented experimental set-up are presented and discussed for the LHC dipole models
Towards Intelligent Databases
This article is a presentation of the objectives and techniques
of deductive databases. The deductive approach to databases aims at extending
with intensional definitions other database paradigms that describe
applications extensionaUy. We first show how constructive specifications can
be expressed with deduction rules, and how normative conditions can be defined
using integrity constraints. We outline the principles of bottom-up and
top-down query answering procedures and present the techniques used for
integrity checking. We then argue that it is often desirable to manage with
a database system not only database applications, but also specifications of
system components. We present such meta-level specifications and discuss
their advantages over conventional approaches
Passive tracer in a flow corresponding to a two dimensional stochastic Navier Stokes equations
In this paper we prove the law of large numbers and central limit theorem for
trajectories of a particle carried by a two dimensional Eulerian velocity
field. The field is given by a solution of a stochastic Navier--Stokes system
with a non-degenerate noise. The spectral gap property, with respect to
Wasserstein metric, for such a system has been shown in [9]. In the present
paper we show that a similar property holds for the environment process
corresponding to the Lagrangian observations of the velocity. In consequence we
conclude the law of large numbers and the central limit theorem for the tracer.
The proof of the central limit theorem relies on the martingale approximation
of the trajectory process
The benefits of inositol-stabilized arginine silicate as a workout ingredient
Background The purpose of this study was to examine the benefits of inositol-stabilized arginine silicate (ASI; Nitrosigine) as a workout ingredient in healthy adults. ASI has been previously shown to significantly enhance blood levels of arginine up to six hours post-dose and increase nitric oxide levels. To investigate reports of enhanced energy, increased muscle pump and stamina during workouts, and faster muscle recovery post-workout, ASI (1,500mg/ day) was tested in a double-blind placebo-controlled crossover-design (DBPC-X) study using the POMS vigor-activity and fatigue-inertia sub-scores, blood flow measurements, leg circumference measurements, and biomarkers of muscle recovery (creatine kinase (CK) and lactate dehydrogenase (LDH)) as outcome measures
Sepsis biomarkers and diagnostic tools with a focus on machine learning.
Over the last years, there have been advances in the use of data-driven techniques to improve the definition, early recognition, subtypes characterisation, prognostication and treatment personalisation of sepsis. Some of those involve the discovery or evaluation of biomarkers or digital signatures of sepsis or sepsis sub-phenotypes. It is hoped that their identification may improve timeliness and accuracy of diagnosis, suggest physiological pathways and therapeutic targets, inform targeted recruitment into clinical trials, and optimise clinical management. Given the complexities of the sepsis response, panels of biomarkers or models combining biomarkers and clinical data are necessary, as well as specific data analysis methods, which broadly fall under the scope of machine learning. This narrative review gives a brief overview of the main machine learning techniques (mainly in the realms of supervised and unsupervised methods) and published applications that have been used to create sepsis diagnostic tools and identify biomarkers
Cut Points and Diffusions in Random Environment
In this article we investigate the asymptotic behavior of a new class of
multi-dimensional diffusions in random environment. We introduce cut times in
the spirit of the work done by Bolthausen, Sznitman and Zeitouni, see [4], in
the discrete setting providing a decoupling effect in the process. This allows
us to take advantage of an ergodic structure to derive a strong law of large
numbers with possibly vanishing limiting velocity and a central limit theorem
under the quenched measure.Comment: 44 pages; accepted for publication in "Journal of Theoretical
Probability
Muons tomography applied to geosciences and volcanology
Imaging the inner part of large geological targets is an important issue in
geosciences with various applications. Dif- ferent approaches already exist
(e.g. gravimetry, electrical tomography) that give access to a wide range of
informations but with identified limitations or drawbacks (e.g. intrinsic
ambiguity of the inverse problem, time consuming deployment of sensors over
large distances). Here we present an alternative and complementary tomography
method based on the measurement of the cosmic muons flux attenuation through
the geological structures. We detail the basics of this muon tomography with a
special emphasis on the photo-active detectors.Comment: Invited talk at the 6th conference on New Developments In
Photodetection (NDIP'11), Lyon-France, July 4-8, 2011; Nuclear Instruments
and Methods in Physics Research Section A, 201
A Brownian particle in a microscopic periodic potential
We study a model for a massive test particle in a microscopic periodic
potential and interacting with a reservoir of light particles. In the regime
considered, the fluctuations in the test particle's momentum resulting from
collisions typically outweigh the shifts in momentum generated by the periodic
force, and so the force is effectively a perturbative contribution. The
mathematical starting point is an idealized reduced dynamics for the test
particle given by a linear Boltzmann equation. In the limit that the mass ratio
of a single reservoir particle to the test particle tends to zero, we show that
there is convergence to the Ornstein-Uhlenbeck process under the standard
normalizations for the test particle variables. Our analysis is primarily
directed towards bounding the perturbative effect of the periodic potential on
the particle's momentum.Comment: 60 pages. We reorganized the article and made a few simplifications
of the conten
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β2-adrenergic signalling promotes cell migration by upregulating expression of the metastasis-associated molecule LYPD3
Metastasis is associated with poor prognosis in breast cancer. Although some studies suggest beta-blockers increase survival by delaying metastasis, others have been discordant. This study provides both insights into the anomalous findings and identifies potential biomarkers that may be treatment targets. Cell line models of basal-type and oestrogen receptor-positive breast cancer were profiled for basal levels of adrenoceptor gene/protein expression, and β2-adrenoceptor mediated cell behaviour including migration, invasion, adhesion, and survival in response to adrenoceptor agonist/antagonist treatment. Protein profiling and histology identified biomarkers and drug targets. Baseline levels of adrenoceptor gene expression are higher in basal-type rather than oestrogen receptor-positive cancer cells. Norepinephrine (NE) treatment increased invasive capacity in all cell lines but did not increase proliferation/survival. Protein profiling revealed the upregulation of the pro-metastatic gene Ly6/PLAUR Domain-Containing Protein 3 (LYPD3) in norepinephrine-treated MDA-MB-468 cells. Histology confirmed selective LYPD3 expression in primary and metastatic breast tumour samples. These findings demonstrate that basal-type cancer cells show a more aggressive adrenoceptor-β2-activated phenotype in the resting and stimulated state, which is attenuated by adrenoceptor-β2 inhibition. This study also highlights the first association between ADRβ2 signalling and LYPD3; its knockdown significantly reduced the basal and norepinephrine-induced activity of MCF-7 cells in vitro. The regulation of ADRβ2 signalling by LYPD3 and its metastasis promoting activities, reveal LYPD3 as a promising therapeutic target in the treatment of breast and other cancers
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