110 research outputs found

    Early processed electroencephalography for the monitoring of deeply sedated mechanically ventilated critically ill patients.

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    Deep sedation may be indicated in the intensive care unit (ICU) for the management of acute organ failure, but leads to sedative-induced delirium. Whether processed electroencephalography (p-EEG) is useful in this setting is unclear. We conducted a single-centre observational study of non-neurological ICU patients sedated according to a standardized guideline of deep sedation (Richmond Agitation Sedation Scale [RASS] between -5 and -4) during the acute phase of respiratory and/or cardio-circulatory failure. The SedLine (Masimo Incorporated, Irvine, California) was used to monitor the Patient State Index (PSI) (ranging from 0 to 100, <25 = very deep sedation and >50 = light sedation to full awareness) during the first 72 h of care. Delirium was assessed with the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). The median duration of PSI monitoring was 43 h. Patients spent 49% in median of the total PSI monitoring duration with a PSI <25. Patients with delirium (n = 41/97, 42%) spent a higher percentage of total monitored time with PSI <25 (median 67% [19-91] vs. 47% [12.2-78.9]) in non-delirious patients (p .047). After adjusting for the cumulative dose of analgesia and sedation, increased time spent with PSI <25 was associated with higher delirium (odds ratio 1.014; 95% CI 1.001-1.027, p = .036). A clinical protocol of deep sedation targeted to RASS at the acute ICU phase may be associated with prolonged EEG suppression and increased delirium. Whether PSI-targeted sedation may help reducing sedative dose and delirium deserves further clinical investigation. Patients requiring deep sedation are at high risk of being over-sedated and developing delirium despite the application of an evidence-based sedation guideline. Development of early objective measures are essential to improve sedation management in these critically ill patients

    Accuracy and Reliability of Pelvimetry Measures Obtained by Manual or Automatic Labeling of Three-Dimensional Pelvic Models.

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    (1) Background: The morphology of the pelvic cavity is important for decision-making in obstetrics. This study aimed to estimate the accuracy and reliability of pelvimetry measures obtained when radiologists manually label anatomical landmarks on three-dimensional (3D) pelvic models. A second objective was to design an automatic labeling method. (2) Methods: Three operators segmented 10 computed tomography scans each. Three radiologists then labeled 12 anatomical landmarks on the pelvic models, which allowed for the calculation of 15 pelvimetry measures. Additionally, an automatic labeling method was developed based on a reference pelvic model, including reference anatomical landmarks, matching the individual pelvic models. (3) Results: Heterogeneity among landmarks in radiologists' labeling accuracy was observed, with some landmarks being rarely mislabeled by more than 4 mm and others being frequently mislabeled by 10 mm or more. The propagation to the pelvimetry measures was limited; only one out of the 15 measures reported a median error above 5 mm or 5°, and all measures showed moderate to excellent inter-radiologist reliability. The automatic method outperformed manual labeling. (4) Conclusions: This study confirmed the suitability of pelvimetry measures based on manual labeling of 3D pelvic models. Automatic labeling offers promising perspectives to decrease the demand on radiologists, standardize the labeling, and describe the pelvic cavity in more detail

    On Proper Polynomial Maps of C2.\mathbb{C}^2.

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    Two proper polynomial maps f1,f2 ⁣:C2C2f_1, f_2 \colon \mathbb{C}^2 \longrightarrow \mathbb{C}^2 are said to be \emph{equivalent} if there exist Φ1,Φ2Aut(C2)\Phi_1, \Phi_2 \in \textrm{Aut}(\mathbb{C}^2) such that f2=Φ2f1Φ1f_2=\Phi_2 \circ f_1 \circ \Phi_1. We investigate proper polynomial maps of arbitrary topological degree d2d \geq 2 up to equivalence. Under the further assumption that the maps are Galois coverings we also provide the complete description of equivalence classes. This widely extends previous results obtained by Lamy in the case d=2d=2.Comment: 15 pages. Final version, to appear in Journal of Geometric Analysi

    A 1400-years flood frequency reconstruction for the Basque country (N Spain): Integrating geological, historical and instrumental datasets

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    We present the first reconstruction of past flood events variability in the Basque Country and Western Ebro Basin (Northern Spain) integrating instrumental hydrological datasets (last 20 years), documentary archives (last 700 years) and Lake Arreo (655 m a.s.l.) sedimentary paleoflood record (last 1400 years). In this lake, allochthonous coarse and fine detrital layers (CDL and FDL respectively) intercalated within endogenic laminites were identified and interpreted as high- and moderate-energy flood events. The interplay between human activities and hydroclimate variability has controlled the deposition of these flood layers. Gauged data for the last 20 years suggest that floods are typically generated by heavy rainfall events on saturated soils after several days of continuous rainfall. These events occur mostly during the cold season (Oct–May). The reconstructed frequency of high-magnitude flood events from the lake record is coherent with the historical cold-season floods from Basque rivers. The lowest flood frequency took place during the 6–7th and 10–15th centuries, while higher flood frequency occurred during the 8–9th centuries and the last 500 years. Fluvial and lacustrine paleoflood records and documentary evidence show abrupt and large increases in extreme flood frequency during the termination of the Little Ice Age (1830–1870 CE) and mid to late 20th century, both periods of Rapid Climate Change (RCC). The significant increase in flood frequency observed during RCC suggests that a similar pattern could be expected in the near future with the ongoing global warming.</p

    Physical Processes in Star Formation

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    © 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00693-8.Star formation is a complex multi-scale phenomenon that is of significant importance for astrophysics in general. Stars and star formation are key pillars in observational astronomy from local star forming regions in the Milky Way up to high-redshift galaxies. From a theoretical perspective, star formation and feedback processes (radiation, winds, and supernovae) play a pivotal role in advancing our understanding of the physical processes at work, both individually and of their interactions. In this review we will give an overview of the main processes that are important for the understanding of star formation. We start with an observationally motivated view on star formation from a global perspective and outline the general paradigm of the life-cycle of molecular clouds, in which star formation is the key process to close the cycle. After that we focus on the thermal and chemical aspects in star forming regions, discuss turbulence and magnetic fields as well as gravitational forces. Finally, we review the most important stellar feedback mechanisms.Peer reviewedFinal Accepted Versio

    Alignment of the CMS silicon tracker during commissioning with cosmic rays

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    This is the Pre-print version of the Article. The official published version of the Paper can be accessed from the link below - Copyright @ 2010 IOPThe CMS silicon tracker, consisting of 1440 silicon pixel and 15 148 silicon strip detector modules, has been aligned using more than three million cosmic ray charged particles, with additional information from optical surveys. The positions of the modules were determined with respect to cosmic ray trajectories to an average precision of 3–4 microns RMS in the barrel and 3–14 microns RMS in the endcap in the most sensitive coordinate. The results have been validated by several studies, including laser beam cross-checks, track fit self-consistency, track residuals in overlapping module regions, and track parameter resolution, and are compared with predictions obtained from simulation. Correlated systematic effects have been investigated. The track parameter resolutions obtained with this alignment are close to the design performance.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)

    Commissioning and performance of the CMS pixel tracker with cosmic ray muons

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    This is the Pre-print version of the Article. The official published verion of the Paper can be accessed from the link below - Copyright @ 2010 IOPThe pixel detector of the Compact Muon Solenoid experiment consists of three barrel layers and two disks for each endcap. The detector was installed in summer 2008, commissioned with charge injections, and operated in the 3.8 T magnetic field during cosmic ray data taking. This paper reports on the first running experience and presents results on the pixel tracker performance, which are found to be in line with the design specifications of this detector. The transverse impact parameter resolution measured in a sample of high momentum muons is 18 microns.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)

    Performance of the CMS drift-tube chamber local trigger with cosmic rays

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    The performance of the Local Trigger based on the drift-tube system of the CMS experiment has been studied using muons from cosmic ray events collected during the commissioning of the detector in 2008. The properties of the system are extensively tested and compared with the simulation. The effect of the random arrival time of the cosmic rays on the trigger performance is reported, and the results are compared with the design expectations for proton-proton collisions and with previous measurements obtained with muon beams

    Performance of the CMS Level-1 trigger during commissioning with cosmic ray muons and LHC beams

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    This is the Pre-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2010 IOPThe CMS Level-1 trigger was used to select cosmic ray muons and LHC beam events during data-taking runs in 2008, and to estimate the level of detector noise. This paper describes the trigger components used, the algorithms that were executed, and the trigger synchronisation. Using data from extended cosmic ray runs, the muon, electron/photon, and jet triggers have been validated, and their performance evaluated. Efficiencies were found to be high, resolutions were found to be good, and rates as expected.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)
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