Beam Based Alignment of Interaction Region Magnets

In conventional beam based alignment (BBA) procedures, the relative alignment of a quadrupole to a nearby beam position monitor is determined by finding a beam position in the quadrupole at which the closed orbit does not change when the quadrupole field is varied. The final focus magnets of the interaction regions (IR) of circular colliders often have some specialized properties that make it difficult to perform conventional beam based alignment procedures. At the HERA interaction points, for example, these properties are: (a) The quadrupoles are quite strong and long. Therefore a thin lens approximation is quite imprecise. (b) The effects of angular magnet offsets become significant. (c) The possibilities to steer the beam are limited as long as the alignment is not within specifications. (d) The beam orbit has design offsets and design angles with respect to the axis of the low-beta quadrupoles. (e) Often quadrupoles do not have a beam position monitor in their vicinity. Here we present a beam based alignment procedure that determines the relative offset of the closed orbit from a quadrupole center without requiring large orbit changes or monitors next to the quadrupole. Taking into account the alignment angle allows us to reduce the sensitivity to optical errors by one to two orders of magnitude. We also show how the BBA measurements of all IR quadrupoles can be used to determine the global position of the magnets. The sensitivity to errors of this method is evaluated and its applicability to HERA is shown

Antibiotic Class and Outcome in Post-stroke Infections: An Individual Participant Data Pooled Analysis of VISTA-Acute

Antibiotics; Post-stroke infections; Post-stroke pneumoniaAntibiòtics; Infeccions posteriors a un accident cerebrovascular; Pneumònia posterior a un accident cerebrovascularAntibióticos; Infecciones posteriores a un accidente cerebrovascular; Neumonía posterior a un accidente cerebrovascularIntroduction: Antibiotics used to treat post-stroke infections have differing antimicrobial and anti-inflammatory effects. Our aim was to investigate whether antibiotic class was associated with outcome after post-stroke infection. Methods: We analyzed pooled individual participant data from the Virtual International Stroke Trials Archive (VISTA)-Acute. Patients with ischemic stroke and with an infection treated with systemic antibiotic therapy during the first 2 weeks after stroke onset were eligible. Antibiotics were grouped into eight classes, according to antimicrobial mechanism and prevalence. The primary analysis investigated whether antibiotic class for any infection, or for pneumonia, was independently associated with a shift in 90 day modified Rankin Scale (mRS) using ordinal logistic regression. Results: 2,708 patients were eligible (median age [IQR] = 74 [65 to 80] y; 51% female; median [IQR] NIHSS score = 15 [11 to 19]). Pneumonia occurred in 35%. Treatment with macrolides (5% of any infections; 9% of pneumonias) was independently associated with more favorable mRS distribution for any infection [OR (95% CI) = 0.59 (0.42 to 0.83), p = 0.004] and for pneumonia [OR (95% CI) = 0.46 (0.29 to 0.73), p = 0.001]. Unfavorable mRS distribution was independently associated with treatment of any infection either with carbapenems, cephalosporins or monobactams [OR (95% CI) = 1.62 (1.33 to 1.97), p < 0.001], penicillin plus β-lactamase inhibitors [OR (95% CI) = 1.26 (1.03 to 1.54), p = 0.025] or with aminoglycosides [OR (95% CI) = 1.73 (1.22 to 2.46), p = 0.002]. Conclusion: This retrospective study has several limitations including effect modification and confounding by indication. Macrolides may have favorable immune-modulatory effects in stroke-associated infections. Prospective evaluation of the impact of antibiotic class on treatment of post-stroke infections is warranted.The Open Access Publication Fund of Charité—Universitätsmedizin Berlin and Professor Meisel as corresponding author will provide funding to cover the open access publication/article processing fe

Detecting chaos in particle accelerators through the frequency map analysis method

The motion of beams in particle accelerators is dominated by a plethora of non-linear effects which can enhance chaotic motion and limit their performance. The application of advanced non-linear dynamics methods for detecting and correcting these effects and thereby increasing the region of beam stability plays an essential role during the accelerator design phase but also their operation. After describing the nature of non-linear effects and their impact on performance parameters of different particle accelerator categories, the theory of non-linear particle motion is outlined. The recent developments on the methods employed for the analysis of chaotic beam motion are detailed. In particular, the ability of the frequency map analysis method to detect chaotic motion and guide the correction of non-linear effects is demonstrated in particle tracking simulations but also experimental data.Comment: Submitted for publication in Chaos, Focus Issue: Chaos Detection Methods and Predictabilit

Work Plans of the EUROTeV Technical Work Packages for 2005-2007

This report summarises the status of the work in the seven scientific Work Packages of EUROTeV as presented during the ILC-European Regional Meeting at Royal Holloway in June 2005. The purpose of the meeting was to monitor the progress and to contrast the developments inside EUROTeV with the worldwide developments of the GDE. The presentations of the entire meeting are available from http://www.pp.rhul.ac.uk/workshop/

A Storage Ring based Option for the LHeC

The LHeC aims at the generation of hadron-lepton collisions with center of mass energies in the TeV scale and luminosities of the order of $10^{32}-10^{33} cm^{-2} sec^{-1}$ by taking advantage of the existing LHC 7 TeV proton ring and adding a high energy electron accelerator. This paper presents technical considerations and potential parameter choices for such a machine and outlines some of the challenges arising when an electron storage ring based option, constructed within the existing infrastructure of the LHC, is chosen

Machine learning in Huntington’s disease:exploring the Enroll-HD dataset for prognosis and driving capability prediction

Background: In biomedicine, machine learning (ML) has proven beneficial for the prognosis and diagnosis of different diseases, including cancer and neurodegenerative disorders. For rare diseases, however, the requirement for large datasets often prevents this approach. Huntington’s disease (HD) is a rare neurodegenerative disorder caused by a CAG repeat expansion in the coding region of the huntingtin gene. The world’s largest observational study for HD, Enroll-HD, describes over 21,000 participants. As such, Enroll-HD is amenable to ML methods. In this study, we pre-processed and imputed Enroll-HD with ML methods to maximise the inclusion of participants and variables. With this dataset we developed models to improve the prediction of the age at onset (AAO) and compared it to the well-established Langbehn formula. In addition, we used recurrent neural networks (RNNs) to demonstrate the utility of ML methods for longitudinal datasets, assessing driving capabilities by learning from previous participant assessments. Results: Simple pre-processing imputed around 42% of missing values in Enroll-HD. Also, 167 variables were retained as a result of imputing with ML. We found that multiple ML models were able to outperform the Langbehn formula. The best ML model (light gradient boosting machine) improved the prognosis of AAO compared to the Langbehn formula by 9.2%, based on root mean squared error in the test set. In addition, our ML model provides more accurate prognosis for a wider CAG repeat range compared to the Langbehn formula. Driving capability was predicted with an accuracy of 85.2%. The resulting pre-processing workflow and code to train the ML models are available to be used for related HD predictions at: https://github.com/JasperO98/hdml/tree/main . Conclusions: Our pre-processing workflow made it possible to resolve the missing values and include most participants and variables in Enroll-HD. We show the added value of a ML approach, which improved AAO predictions and allowed for the development of an advisory model that can assist clinicians and participants in estimating future driving capability.</p

Injection Straight Pulsed Magnet Error Tolerance Study for Top-Off Injection

NSLS II is designed to work in top-off injection mode. The injection straight includes a septum and four fast kicker magnets. The pulsed magnet errors will excite a betatron oscillation. This paper gives the formulas of each error contribution to the oscillation amplitude at various source points in the ring. These are compared with simulation results. Based on the simple formulas, we can specify the error tolerances on the pulsed magnets with the goal to minimize the injection transient and scale it to similar machines. The NSLS-II is a 3 GeV third generation synchrotron light source under construction at Brookhaven National Laboratory. Due to its short lifetime, NSLS-II storage ring requires the top-off injection (once per minute) during which the stored beam orbit is highly desired as transparent. But the errors, from the SR pulsed magnets at the injection straight - kickers (non-closed injection bump) and pulsed septum (time-dependent stray field), excite a stored beam betatron oscillation. The magnitude of the perturbation can be large disturning some of the user experiments. In 2010 injection straight review, based on the experts experiences in ALS, DIAMOND, SLS and SPEAR, we came to the conclusion that the acceptable oscillation amplitude at the long straight is set as 100 {micro}m (i.e. 0.7 {sigma}x) in horizontal plane and 12 {micro}m, 2.5 {sigma}y, in vertical plane for NSLS II. This paper gives the analysis estimate of the different error source tolerance from the pulse magnets and scales it to our requirements. The result is compared with simulation

The Large Hadron-Electron Collider (LHEC) at the LHC

Sub-atomic physics at the energy frontier probes the structure of the fundamental quanta of the Universe. The Large Hadron Collider (LHC) at CERN opens for the first time the ‘terascale’ (TeV energy scale) to experimental scrutiny, exposing the physics of the Universe at the subattometric (∼ 10−19 m, 10−10 as) scale. The LHC will also take the science of nuclear matter to hitherto unparalleled energy densities. The hadron beams, protons or ions, in the LHC underpin this horizon, and also offer new experimental possibilities at this energy scale. A Large Hadron electron Collider, LHeC, in which an electron (positron) beam of energy 60 to 140 GeV is in collision with one of the LHC hadron beams, makes possible terascale leptonhadron physics. The LHeC is presently being evaluated in the form of two options, ‘ring-ring’ and ‘linac-ring’, either of which operate simultaneously with pp or ion-ion collisions in other LHC interaction regions. Each option takes advantage of recent advances in radio-frequency, in linear acceleration, and in other associated technologies, to achieve ep luminosity as large as 1033 cm−2s−1