The full detector simulation for the Atlas experiment: status and outlook

The simulation of the ATLAS detector is a major challenge, given the complexity of the detector and the demanding environment of the LHC. The apparatus, one of the biggest and most complex ever designed, requires a detailed, flexible and, if possible, fast simulation which is needed already today to deal with questions related to design optimization, to issues raised by staging scenarios, and of course to enable detailed physics studies to lay the basis for the first physics discoveries. Scalability and robustness stand out as the most critical issues that are to be faced in the implementation of such a simulation. In this paper we present the status of the present simulation and the adopted solutions in terms of speed optimization, centralization of services, framework facilities and persistency solutions. Emphasis is put on the global performance when the different detector components are collected together in a full and detailed simulation. The reference tool adopted is Geant4.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 6 pages. PSN TUMT00

AKAP79/150 Anchoring of Calcineurin Controls Neuronal L-Type Ca2+ Channel Activity and Nuclear Signaling

SummaryNeuronal L-type calcium channels contribute to dendritic excitability and activity-dependent changes in gene expression that influence synaptic strength. Phosphorylation-mediated enhancement of L-type channels containing the CaV1.2 pore-forming subunit is promoted by A-kinase anchoring proteins (AKAPs) that target cAMP-dependent protein kinase (PKA) to the channel. Although PKA increases L-type channel activity in dendrites and dendritic spines, the mechanism of enhancement in neurons remains poorly understood. Here, we show that CaV1.2 interacts directly with AKAP79/150, which binds both PKA and the Ca2+/calmodulin-activated phosphatase calcineurin (CaN). Cotargeting of PKA and CaN by AKAP79/150 confers bidirectional regulation of L-type current amplitude in transfected HEK293 cells and hippocampal neurons. However, anchored CaN dominantly suppresses PKA enhancement of the channel. Additionally, activation of the transcription factor NFATc4 via local Ca2+ influx through L-type channels requires AKAP79/150, suggesting that this signaling complex promotes neuronal L channel signaling to the nucleus through NFATc4

Surface monitoring of road pavements using mobile crowdsensing technology

Pavement-surface characteristics should be considered during road maintenance for safe and comfortable driving. A detailed and up-to-date report of road-pavement network conditions is required to optimize a maintenance plan. However, manual road inspection methods, such as periodic visual surveys, are time-consuming and expensive. A common technology used to address this issue is SmartRoadSense, a collaborative system for the automatic detection of road-surface characteristics using Global Positioning System receivers and triaxial accelerometers contained in mobile devices. In this study, the results of the SmartRoadSense surveys conducted on Provincial Road 2 (SP2) in Salerno, Italy, were compared with the Distress Cadastre data for the same province and the pavement condition indices of different sections of the SP2. Although the effectiveness of the crowdsensing-based SmartRoadSense was found to vary with the distress type, the system was confirmed to be very efficient for monitoring the most critical road failures

Fast shower simulation in the ATLAS calorimeter

The time to simulate pp collisions in the ATLAS detector is largely dominated by the showering of electromagnetic particles in the heavy parts of the detector, especially the electromagnetic barrel and endcap calorimeters. Two procedures have been developed to accelerate the processing time of electromagnetic particles in these regions: (1) a fast shower parameterisation and (2) a frozen shower library. Both work by generating the response of the calorimeter to electrons and positrons with Geant 4, and then reintroduce the response into the simulation at runtime. In the fast shower parameterisation technique, a parameterisation is tuned to single electrons and used later by simulation. In the frozen shower technique, actual showers from low-energy particles are used in the simulation. Full Geant 4 simulation is used to develop showers down to ~1 GeV, at which point the shower is terminated by substituting a frozen shower. Judicious use of both techniques over the entire electromagnetic portion of the ATLAS calorimeter produces an important improvement of CPU time. We discuss the algorithms and their performance in this paper

The ATLAS Simulation: an LHC Challenge

The simulation program for the ATLAS experiment at CERN is currently in a full operational mode and integrated into the ATLAS common analysis framework, Athena. The OO approach, based on GEANT4, and in use during the DC2 data challenge has been interfaced within Athena and to GEANT4 using the LCG dictionaries and Python scripting. The robustness of the application was proved during the DC2 data challenge. The Python interface has added the flexibility, modularity and interactivity that the simulation tool requires in order to be able to provide a common implementation of different full ATLAS simulation setups, test beams and cosmic ray applications. Generation, simulation and digitization steps were exercised for performance and robustness tests. The comparison with real data has been possible in the context of the ATLAS Combined Test Beam (2004) and ongoing cosmic ray studies

Generalized Richardson-Lucy (GRL) for analyzing multi-shell diffusion MRI data

Spherical deconvolution is a widely used approach to quantify fiber orientation distribution from diffusion MRI data. The damped Richardson-Lucy (dRL) is developed to perform robust spherical deconvolution on single shell diffusion MRI data. While the dRL algorithm could in theory be directly applied to multi-shell data, it is not optimised to model the signal from multiple tissue types. In this work, we introduce a new framework based on dRL - dubbed Generalized Richardson Lucy (GRL) - that uses multi-shell data in combination with user-chosen tissue models to disentangle partial volume effects and increase the accuracy in FOD estimation. The optimal weighting of multi-shell data in the fit and the robustness to noise and partial volume effects of GRL was studied with synthetic data. Subsequently, we investigated the performances of GRL in comparison to dRL on a high-resolution diffusion MRI dataset from the Human Connectome Project and on an MRI dataset acquired at 3T on a clinical scanner. The feasibility of including intra-voxel incoherent motion (IVIM) effects in the modelling was studied on a third dataset. Results of simulations show that GRL can robustly disentangle different tissue types at SNR above 20 and improves the angular accuracy of the FOD estimation. On real data, GRL provides signal fraction maps that are physiologically plausible and consistent between datasets. When considering IVIM effects, high blood pseudo-diffusion fraction is observed in the medial temporal lobe and in the sagittal sinus. In comparison to dRL, GRL provides sharper FODs and less spurious peaks in presence of partial volume effects and results in a better tract termination at the grey/white matter interface or at the outer cortical surface. In conclusion, GRL offers a new modular and flexible framework to perform spherical deconvolution of multi-shell data

Increased functional connectivity within alpha and theta frequency bands in dysphoria: A resting-state EEG study

Background: The understanding of neurophysiological correlates underlying the risk of developing depression may have a significant impact on its early and objective identification. Research has identified abnormal resting-state electroencephalography (EEG) power and functional connectivity patterns in major depression. However, the entity of dysfunctional EEG dynamics in dysphoria is yet unknown. Methods: 32-channel EEG was recorded in 26 female individuals with dysphoria and in 38 age-matched, female healthy controls. EEG power spectra and alpha asymmetry in frontal and posterior channels were calculated in a 4-minute resting condition. An EEG functional connectivity analysis was conducted through phase locking values, particularly mean phase coherence. Results: While individuals with dysphoria did not differ from controls in EEG spectra and asymmetry, they exhibited dysfunctional brain connectivity. Particularly, in the theta band (4-8 Hz), participants with dysphoria showed increased connectivity between right frontal and central areas and right temporal and left occipital areas. Moreover, in the alpha band (8-12 Hz), dysphoria was associated with increased connectivity between right and left prefrontal cortex and between frontal and central-occipital areas bilaterally. Limitations: All participants belonged to the female gender and were relatively young. Mean phase coherence did not allow to compute the causal and directional relation between brain areas. Conclusions: An increased EEG functional connectivity in the theta and alpha bands characterizes dysphoria. These patterns may be associated with the excessive self-focus and ruminative thinking that typifies depressive symptoms. EEG connectivity patterns may represent a promising measure to identify individuals with a higher risk of developing depression

White matter integrity as a predictor of response to treatment in first episode psychosis

The integrity of brain white matter connections is central to a patient's ability to respond to pharmacological interventions. This study tested this hypothesis using a specific measure of white matter integrity, and examining its relationship to treatment response using a prospective design in patients within their first episode of psychosis. Diffusion tensor imaging data were acquired in 63 patients with first episode psychosis and 52 healthy control subjects (baseline). Response was assessed after 12 weeks and patients were classified as responders or non-responders according to treatment outcome. At this second time-point, they also underwent a second diffusion tensor imaging scan. Tract-based spatial statistics were used to assess fractional anisotropy as a marker of white matter integrity. At baseline, non-responders showed lower fractional anisotropy than both responders and healthy control subjects (P < 0.05; family-wise error-corrected), mainly in the uncinate, cingulum and corpus callosum, whereas responders were indistinguishable from healthy control subjects. After 12 weeks, there was an increase in fractional anisotropy in both responders and non-responders, positively correlated with antipsychotic exposure. This represents one of the largest, controlled investigations of white matter integrity and response to antipsychotic treatment early in psychosis. These data, together with earlier findings on cortical grey matter, suggest that grey and white matter integrity at the start of treatment is an important moderator of response to antipsychotics. These findings can inform patient stratification to anticipate care needs, and raise the possibility that antipsychotics may restore white matter integrity as part of the therapeutic response

Multiobjective railway alignment optimization using ballastless track and reduced cross-section in tunnel

The increasing need for railway planning and design to connect growing cities in inland mountainous areas has pushed engineering efforts toward the research of railway tracks that must comply with more restrictive constraints. In this study, a multiobjective alignment optimization (HAO), commonly used for highway projects, was carried out to identify a better solution for constructing a high-speed railway track considering technical and economic feasibilities. Then, two different and innovative scenarios were investigated: an unconventional ballastless superstructure, which is more environment-friendly than a gravel superstructure, and a reduced cross-section in a tunnel, which enables a slower design speed and then, less restrictive geometric constraints and earthmoving. The results showed that the first solution obtained a better performance with a slight increase in cost. Moreover, both scenarios improved the preliminary alignment optimization, reducing the overall cost by 11% for the first scenario and 20% for the second one

Anchored phosphatases modulate glucose homeostasis.

Endocrine release of insulin principally controls glucose homeostasis. Nutrient-induced exocytosis of insulin granules from pancreatic β-cells involves ion channels and mobilization of Ca(2+) and cyclic AMP (cAMP) signalling pathways. Whole-animal physiology, islet studies and live-β-cell imaging approaches reveal that ablation of the kinase/phosphatase anchoring protein AKAP150 impairs insulin secretion in mice. Loss of AKAP150 impacts L-type Ca(2+) currents, and attenuates cytoplasmic accumulation of Ca(2+) and cAMP in β-cells. Yet surprisingly AKAP150 null animals display improved glucose handling and heightened insulin sensitivity in skeletal muscle. More refined analyses of AKAP150 knock-in mice unable to anchor protein kinase A or protein phosphatase 2B uncover an unexpected observation that tethering of phosphatases to a seven-residue sequence of the anchoring protein is the predominant molecular event underlying these metabolic phenotypes. Thus anchored signalling events that facilitate insulin secretion and glucose homeostasis may be set by AKAP150 associated phosphatase activity