1. |
|
|
2. |
|
|
3. |
|
|
4. |
|
|
5. |
|
|
6. |
|
|
7. |
- Adcox, K, et al.
(author)
-
PHENIX detector overview
- 2003
-
In: Nuclear Instruments & Methods in Physics Research. Section A: Accelerators, Spectrometers, Detectors, and Associated Equipment. - 0167-5087. ; 499:2-3, s. 469-479
-
Journal article (peer-reviewed)abstract
- The PHENIX detector is designed to perform a broad study of A-A, p-A, and p-p collisions to investigate nuclear matter under extreme conditions. A wide variety of probes, sensitive to all timescales, are used to study systematic variations with species and energy as well as to measure the spin structure of the nucleon. Designing for the needs of the heavy-ion and polarized-proton programs has produced a detector with unparalleled capabilities. PHENIX measures electron and muon pairs, photons, and hadrons with excellent energy and momentum resolution. The detector consists of a large number of subsystems that are discussed in other papers in this volume. The overall design parameters of the detector are presented. (C) 2002 Elsevier Science B.V. All rights reserved.
|
|
8. |
- Adler, SS, et al.
(author)
-
PHENIX on-line systems
- 2003
-
In: Nuclear Instruments & Methods in Physics Research. Section A: Accelerators, Spectrometers, Detectors, and Associated Equipment. - 0167-5087. ; 499:2-3, s. 560-592
-
Journal article (peer-reviewed)abstract
- The PHENIX On-Line system takes signals from the Front End Modules (FEM) on each detector subsystem for the purpose of generating events for physics analysis. Processing of event data begins when the Data Collection Modules (DCM) receive data via fiber-optic links from the FEMs. The DCMs format and zero suppress the data and generate data packets. These packets go to the Event Builders (EvB) that assemble the events in final form. The Level-1 trigger (LVL1) generates a decision for each beam crossing and eliminates uninteresting events. The FEMs carry out all detector processing of the data so that it is delivered to the DCMs using a standard format. The FEMs also provide buffering for LVL1 trigger processing and DCM data collection. This is carried out using an architecture that is pipelined and deadtimeless. All of this is controlled by the Master Timing System (MTS) that distributes the RHIC clocks. A Level-2 trigger (LVL2) gives additional discrimination. A description of the components and operation of the PHENIX On-Line system is given and the solution to a number of electronic infrastructure problems are discussed. (C) 2002 Elsevier Science B.V. All rights reserved.
|
|
9. |
|
|
10. |
|
|
11. |
|
|
12. |
|
|
13. |
|
|
14. |
|
|
15. |
|
|
16. |
|
|
17. |
- Liang, C, et al.
(author)
-
Infertility, recurrent pregnancy loss, and risk of stroke: pooled analysis of individual patient data of 618 851 women
- 2022
-
In: BMJ (Clinical research ed.). - : BMJ. - 1756-1833. ; 377, s. e070603-
-
Journal article (peer-reviewed)abstract
- ObjectiveTo examine the associations of infertility, recurrent miscarriage, and stillbirth with the risk of first non-fatal and fatal stroke, further stratified by stroke subtypes.DesignIndividual participant pooled analysis of eight prospective cohort studies.SettingCohort studies across seven countries (Australia, China, Japan, Netherlands, Sweden, the United Kingdom, and the United States) participating in the InterLACE (International Collaboration for a Life Course Approach to Reproductive Health and Chronic Disease Events) consortium, which was established in June 2012.Participants618 851 women aged 32.0-73.0 years at baseline with data on infertility, miscarriage, or stillbirth, at least one outcome event (non-fatal or fatal stroke), and information on covariates were included; 93 119 women were excluded. Of the participants, 275 863 had data on non-fatal and fatal stroke, 54 716 only had data on non-fatal stroke, and 288 272 only had data on fatal stroke.Main outcome and measuresNon-fatal strokes were identified through self-reported questionnaires, linked hospital data, or national patient registers. Fatal strokes were identified through death registry data.ResultsThe median follow-up for non-fatal stroke and fatal stroke was 13.0 years (interquartile range 12.0-14.0) and 9.4 years (7.6-13.0), respectively. A first non-fatal stroke was experienced by 9265 (2.8%) women and 4003 (0.7%) experienced a fatal stroke. Hazard ratios for non-fatal or fatal stroke were stratified by hypertension and adjusted for race or ethnicity, body mass index, smoking status, education level, and study. Infertility was associated with an increased risk of non-fatal stroke (hazard ratio 1.14, 95% confidence interval 1.08 to 1.20). Recurrent miscarriage (at least three) was associated with higher risk of non-fatal and fatal stroke (1.35, 1.27 to 1.44, and 1.82, 1.58 to 2.10, respectively). Women with stillbirth were at 31% higher risk of non-fatal stroke (1.31, 1.10 to 1.57) and women with recurrent stillbirth were at 26% higher risk of fatal stroke (1.26, 1.15 to 1.39). The increased risk of stroke (non-fatal or fatal) associated with infertility or recurrent stillbirths was mainly driven by a single stroke subtype (non-fatal ischaemic stroke and fatal haemorrhagic stroke), while the increased risk of stroke (non-fatal or fatal) associated with recurrent miscarriages was driven by both subtypes.ConclusionA history of recurrent miscarriages and death or loss of a baby before or during birth could be considered a female specific risk factor for stroke, with differences in risk according to stroke subtypes. These findings could contribute to improved monitoring and stroke prevention for women with such a history.
|
|
18. |
|
|
19. |
|
|
20. |
|
|
21. |
|
|
22. |
|
|
23. |
|
|
24. |
|
|
25. |
|
|
26. |
|
|
27. |
|
|
28. |
|
|
29. |
|
|
30. |
|
|