Nuclear emulsion readout techniques developed for the CHORUS experiment

The CHORUS experiment is pursuing the study of the production and decay of short lived particles from neutrino interactions in a nuclear emulsion target. The extraction of the full information from the emulsion sheets has been possible only thanks to the development of fully automatic microscopes. The technique of automatic scanning, pioneered in Nagoya, involves precision mechanics, high quality optics and a readout scheme allowing for fast decisions. From the R&D efforts within the various institutes of the CHORUS collaboration, the complementary approaches adopted by the Nagoya and CERN/NIKHEF groups are described here. Both are based on the principle that all information from the emulsion sheets should be extracted at the highest possible rate, limited only by the camera readout and the mechanical stability of the microscope stage. (12 refs)

The POOL Data Storage, Cache and Conversion Mechanism

The POOL data storage mechanism is intended to satisfy the needs of the LHC experiments to store and analyze the data from the detector response of particle collisions at the LHC proton-proton collider. Both the data rate and the data volumes will largely differ from the past experience. The POOL data storage mechanism is intended to be able to cope with the experiment's requirements applying a flexible multi technology data persistency mechanism. The developed technology independent approach is flexible enough to adopt new technologies, take advantage of existing schema evolution mechanisms and allows users to access data in a technology independent way. The framework consists of several components, which can be individually adopted and integrated into existing experiment frameworks.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 5 pages, PDF, 6 figures. PSN MOKT00

Supporting group maintenance through prognostics-enhanced dynamic dependability prediction

Condition-based maintenance strategies adapt maintenance planning through the integration of online condition monitoring of assets. The accuracy and cost-effectiveness of these strategies can be improved by integrating prognostics predictions and grouping maintenance actions respectively. In complex industrial systems, however, effective condition-based maintenance is intricate. Such systems are comprised of repairable assets which can fail in different ways, with various effects, and typically governed by dynamics which include time-dependent and conditional events. In this context, system reliability prediction is complex and effective maintenance planning is virtually impossible prior to system deployment and hard even in the case of condition-based maintenance. Addressing these issues, this paper presents an online system maintenance method that takes into account the system dynamics. The method employs an online predictive diagnosis algorithm to distinguish between critical and non-critical assets. A prognostics-updated method for predicting the system health is then employed to yield well-informed, more accurate, condition-based suggestions for the maintenance of critical assets and for the group-based reactive repair of non-critical assets. The cost-effectiveness of the approach is discussed in a case study from the power industry

Invariant Killing spinors in 11D and type II supergravities

We present all isotropy groups and associated $\Sigma$ groups, up to discrete identifications of the component connected to the identity, of spinors of eleven-dimensional and type II supergravities. The $\Sigma$ groups are products of a Spin group and an R-symmetry group of a suitable lower dimensional supergravity theory. Using the case of SU(4)-invariant spinors as a paradigm, we demonstrate that the $\Sigma$ groups, and so the R-symmetry groups of lower-dimensional supergravity theories arising from compactifications, have disconnected components. These lead to discrete symmetry groups reminiscent of R-parity. We examine the role of disconnected components of the $\Sigma$ groups in the choice of Killing spinor representatives and in the context of compactifications.Comment: 22 pages, typos correcte

MAPPING OF CODA ATTENUATION AT THE EXTEND OF THE NATIONAL SEISMOLOGICAL NETWORK OF GREECE

Coda decay rates of 538 vertical components corresponding to local earthquakes which occurred in Greece during the period 1998 to 1999 were used to deduce the coda quality factor (Qc) characteristics in the Hellenic area. The seismograms have been selected from a broader sample of 776 records obtained at 8 stations of the National Seismographic Network operated by the Institute of Geodynamics of the National Observatory of Athens. Earthquake magnitudes range from 2.5 to 4.0; epicentral distances and depths are smaller than 100 km and 40 km, respectively. Using the Single Back Scattering model, the dependence of Qc on frequencies between 1 and 10 Hz has been investigated at each station and the usual Qc =Qo f relationships have been deduced. The spatial distribution of Qo has been drawn using waves that sample approximately equivalent ellipsoidal volumes with semiminor axis up to 100 km. The corresponding map shows a decreasing trend in SN direction

Aquaporin-4 and brain edema.

Aquaporin-4 (AQP4) is a water-channel protein expressed strongly in the brain, predominantly in astrocyte foot processes at the borders between the brain parenchyma and major fluid compartments, including cerebrospinal fluid (CSF) and blood. This distribution suggests that AQP4 controls water fluxes into and out of the brain parenchyma. Experiments using AQP4-null mice provide strong evidence for AQP4 involvement in cerebral water balance. AQP4-null mice are protected from cellular (cytotoxic) brain edema produced by water intoxication, brain ischemia, or meningitis. However, AQP4 deletion aggravates vasogenic (fluid leak) brain edema produced by tumor, cortical freeze, intraparenchymal fluid infusion, or brain abscess. In cytotoxic edema, AQP4 deletion slows the rate of water entry into brain, whereas in vasogenic edema, AQP4 deletion reduces the rate of water outflow from brain parenchyma. AQP4 deletion also worsens obstructive hydrocephalus. Recently, AQP4 was also found to play a major role in processes unrelated to brain edema, including astrocyte migration and neuronal excitability. These findings suggest that modulation of AQP4 expression or function may be beneficial in several cerebral disorders, including hyponatremic brain edema, hydrocephalus, stroke, tumor, infection, epilepsy, and traumatic brain injury

Measurement of Intraspinal Pressure After Spinal Cord Injury: Technical Note from the Injured Spinal Cord Pressure Evaluation Study.

Intracranial pressure (ICP) is routinely measured in patients with severe traumatic brain injury (TBI). We describe a novel technique that allowed us to monitor intraspinal pressure (ISP) at the injury site in 14 patients who had severe acute traumatic spinal cord injury (TSCI), analogous to monitoring ICP after brain injury. A Codman probe was inserted subdurally to measure the pressure of the injured spinal cord compressed against the surrounding dura. Our key finding is that it is feasible and safe to monitor ISP for up to a week in patients after TSCI, starting within 72 h of the injury. With practice, probe insertion and calibration take less than 10 min. The ISP signal characteristics after TSCI were similar to the ICP signal characteristics recorded after TBI. Importantly, there were no associated complications. Future studies are required to determine whether reducing ISP improves neurological outcome after severe TSCI

Hyperk\"ahler torsion structures invariant by nilpotent Lie groups

We study HKT structures on nilpotent Lie groups and on associated nilmanifolds. We exhibit three weak HKT structures on $\R^8$ which are homogeneous with respect to extensions of Heisenberg type Lie groups. The corresponding hypercomplex structures are of a special kind, called abelian. We prove that on any 2-step nilpotent Lie group all invariant HKT structures arise from abelian hypercomplex structures. Furthermore, we use a correspondence between abelian hypercomplex structures and subspaces of ${\frak sp}(n)$ to produce continuous families of compact and noncompact of manifolds carrying non isometric HKT structures. Finally, geometrical properties of invariant HKT structures on 2-step nilpotent Lie groups are obtained.Comment: LateX, 12 page

Scalar Field Probes of Power-Law Space-Time Singularities

We analyse the effective potential of the scalar wave equation near generic space-time singularities of power-law type (Szekeres-Iyer metrics) and show that the effective potential exhibits a universal and scale invariant leading x^{-2} inverse square behaviour in the ``tortoise coordinate'' x provided that the metrics satisfy the strict Dominant Energy Condition (DEC). This result parallels that obtained in hep-th/0403252 for probes consisting of families of massless particles (null geodesic deviation, a.k.a. the Penrose Limit). The detailed properties of the scalar wave operator depend sensitively on the numerical coefficient of the x^{-2}-term, and as one application we show that timelike singularities satisfying the DEC are quantum mechanically singular in the sense of the Horowitz-Marolf (essential self-adjointness) criterion. We also comment on some related issues like the near-singularity behaviour of the scalar fields permitted by the Friedrichs extension.Comment: v2: 21 pages, JHEP3.cls, one reference adde

Supporting group maintenance through prognostics-enhanced dynamic dependability prediction

Condition-based maintenance strategies adapt maintenance planning through the integration of online condition monitoring of assets. The accuracy and cost-effectiveness of these strategies can be improved by integrating prognostics predictions and grouping maintenance actions respectively. In complex industrial systems, however, effective condition-based maintenance is intricate. Such systems are comprised of repairable assets which can fail in different ways, with various effects, and typically governed by dynamics which include time-dependent and conditional events. In this context, system reliability prediction is complex and effective maintenance planning is virtually impossible prior to system deployment and hard even in the case of condition-based maintenance. Addressing these issues, this paper presents an online system maintenance method that takes into account the system dynamics. The method employs an online predictive diagnosis algorithm to distinguish between critical and non-critical assets. A prognostics-updated method for predicting the system health is then employed to yield well-informed, more accurate, condition-based suggestions for the maintenance of critical assets and for the group-based reactive repair of non-critical assets. The cost-effectiveness of the approach is discussed in a case study from the power industry