Heterostructures for High Performance Devices

Contains table of contents for Part I, table of contents for Section 1, an introduction, reports on eighteen research projects and a list of publications.Charles S. Draper Laboratories Contract DL-H-418483DARPA/NCIPTJoint Services Electronics Program Contract DAAL03-89-C-0001Joint Services Electronics Program Contract DAAL03-92-C-0001IBM Corporation FellowshipNational Science Foundation FellowshipVitesse SemiconductorGTE LaboratoriesCharles S. Draper LaboratoriesElectronics and Telecommunications Research Institute (ETRI) FellowshipNational Science Foundation/Northeastern UniversityTRW SystemsU.S. Army Research OfficeNational Science FoundationAT&T Bell Laboratories FellowshipNational Science Foundation Grant ECS 90-0774

Prediction of second neurological attack in patients with clinically isolated syndrome using support vector machines

The aim of this study is to predict the conversion from clinically isolated syndrome to clinically definite multiple sclerosis using support vector machines. The two groups of converters and non-converters are classified using features that were calculated from baseline data of 73 patients. The data consists of standard magnetic resonance images, binary lesion masks, and clinical and demographic information. 15 features were calculated and all combinations of them were iteratively tested for their predictive capacity using polynomial kernels and radial basis functions with leave-one-out cross-validation. The accuracy of this prediction is up to 86.4% with a sensitivity and specificity in the same range indicating that this is a feasible approach for the prediction of a second clinical attack in patients with clinically isolated syndromes, and that the chosen features are appropriate. The two features gender and location of onset lesions have been used in all feature combinations leading to a high accuracy suggesting that they are highly predictive. However, it is necessary to add supporting features to maximise the accuracy. © 2013 IEEE

Involvement of placental growth factor in Wallerian degeneration

Wallerian degeneration (WD) is an inflammatory process of nerve degeneration, which occurs more rapidly in the peripheral nervous system compared with the central nervous system, resulting, respectively in successful and aborted axon regeneration. In the peripheral nervous system, Schwann cells (SCs) and macrophages, under the control of a network of cytokines and chemokines, represent the main cell types involved in this process. Within this network, the role of placental growth factor (PlGF) remains totally unknown. However, properties like monocyte activation/attraction, ability to increase expression of pro-inflammatory molecules, as well as neuroprotective effects, make it a candidate likely implicated in this process. Also, nothing is described about the expression and localization of this molecule in the peripheral nervous system. To address these original questions, we decided to study PlGF expression under physiological and degenerative conditions and to explore its role in WD, using a model of sciatic nerve transection in wild-type and Pgf(-/-) mice. Our data show dynamic changes of PlGF expression, from periaxonal in normal nerve to SCs 24h postinjury, in parallel with a p65/NF-κB recruitment on Pgf promoter. After injury, SC proliferation is reduced by 30% in absence of PlGF. Macrophage invasion is significantly delayed in Pgf(-/-) mice compared with wild-type mice, which results in worse functional recovery. MCP-1 and proMMP-9 exhibit a 3-fold reduction of their relative expressions in Pgf(-/-) injured nerves, as demonstrated by cytokine array. In conclusion, this work originally describes PlGF as a novel member of the cytokine network of WD

What is the role of non-invasive measurements of atherosclerosis in individual cardiovascular risk prediction?

Contains fulltext : 53208.pdf (publisher's version ) (Closed access)Primary prevention of CVD (cardiovascular disease) is mainly based on the assessment of individual cardiovascular risk factors. However, often, only the most important (conventional) cardiovascular risk factors are determined, and every level of risk factor exposure is associated with a substantial variation in the amount of atherosclerosis. Measuring the effect of risk factor exposure over time directly in the vessel might (partially) overcome these shortcomings. Several non-invasive imaging techniques have the potential to accomplish this, each of these techniques focusing on a different stage of the atherosclerotic process. In this review, we aim to define the current role of various of these non-invasive measurements of atherosclerosis in individual cardiovascular risk prediction, taking into account the most recent insights about validity and reproducibility of these techniques and the results of recent prospective outcome trials. We conclude that, although the clinical application of FMD (flow-mediated dilation) and PWA (pulse wave analysis) in individual cardiovascular risk prediction seems far away, there may be a role for PWV (pulse wave velocity) and IMT (intima-media thickness) measurements in the near future

Development of the CMS detector for the CERN LHC Run 3

International audienceSince the initial data taking of the CERN LHC, the CMS experiment has undergone substantial upgrades and improvements. This paper discusses the CMS detector as it is configured for the third data-taking period of the CERN LHC, Run 3, which started in 2022. The entire silicon pixel tracking detector was replaced. A new powering system for the superconducting solenoid was installed. The electronics of the hadron calorimeter was upgraded. All the muon electronic systems were upgraded, and new muon detector stations were added, including a gas electron multiplier detector. The precision proton spectrometer was upgraded. The dedicated luminosity detectors and the beam loss monitor were refurbished. Substantial improvements to the trigger, data acquisition, software, and computing systems were also implemented, including a new hybrid CPU/GPU farm for the high-level trigger

Development of the CMS detector for the CERN LHC Run 3

Since the initial data taking of the CERN LHC, the CMS experiment has undergone substantial upgrades and improvements. This paper discusses the CMS detector as it is configured for the third data-taking period of the CERN LHC, Run 3, which started in 2022. The entire silicon pixel tracking detector was replaced. A new powering system for the superconducting solenoid was installed. The electronics of the hadron calorimeter was upgraded. All the muon electronic systems were upgraded, and new muon detector stations were added, including a gas electron multiplier detector. The precision proton spectrometer was upgraded. The dedicated luminosity detectors and the beam loss monitor were refurbished. Substantial improvements to the trigger, data acquisition, software, and computing systems were also implemented, including a new hybrid CPU/GPU farm for the high-level trigger.Since the initial data taking of the CERN LHC, the CMS experiment has undergone substantial upgrades and improvements. This paper discusses the CMS detector as it is configured for the third data-taking period of the CERN LHC, Run 3, which started in 2022. The entire silicon pixel tracking detector was replaced. A new powering system for the superconducting solenoid was installed. The electronics of the hadron calorimeter was upgraded. All the muon electronic systems were upgraded, and new muon detector stations were added, including a gas electron multiplier detector. The precision proton spectrometer was upgraded. The dedicated luminosity detectors and the beam loss monitor were refurbished. Substantial improvements to the trigger, data acquisition, software, and computing systems were also implemented, including a new hybrid CPU/GPU farm for the high-level trigger

Development of the CMS detector for the CERN LHC Run 3

International audienceSince the initial data taking of the CERN LHC, the CMS experiment has undergone substantial upgrades and improvements. This paper discusses the CMS detector as it is configured for the third data-taking period of the CERN LHC, Run 3, which started in 2022. The entire silicon pixel tracking detector was replaced. A new powering system for the superconducting solenoid was installed. The electronics of the hadron calorimeter was upgraded. All the muon electronic systems were upgraded, and new muon detector stations were added, including a gas electron multiplier detector. The precision proton spectrometer was upgraded. The dedicated luminosity detectors and the beam loss monitor were refurbished. Substantial improvements to the trigger, data acquisition, software, and computing systems were also implemented, including a new hybrid CPU/GPU farm for the high-level trigger

Development of the CMS detector for the CERN LHC Run 3

International audienceSince the initial data taking of the CERN LHC, the CMS experiment has undergone substantial upgrades and improvements. This paper discusses the CMS detector as it is configured for the third data-taking period of the CERN LHC, Run 3, which started in 2022. The entire silicon pixel tracking detector was replaced. A new powering system for the superconducting solenoid was installed. The electronics of the hadron calorimeter was upgraded. All the muon electronic systems were upgraded, and new muon detector stations were added, including a gas electron multiplier detector. The precision proton spectrometer was upgraded. The dedicated luminosity detectors and the beam loss monitor were refurbished. Substantial improvements to the trigger, data acquisition, software, and computing systems were also implemented, including a new hybrid CPU/GPU farm for the high-level trigger