Theoretical investigation of the force and dynamically coupled torsional-axial-lateral dynamic response of eared rotors

Difficulties in solution methodology to be used to deal with the potentially higher nonlinear rotor equations when dynamic coupling is included. A solution methodology is selected to solve the nonlinear differential equations. The selected method was verified to give good results even at large nonlinearity levels. The transfer matrix methodology is extended to the solution of nonlinear problems

Rateless Coding for Gaussian Channels

A rateless code-i.e., a rate-compatible family of codes-has the property that codewords of the higher rate codes are prefixes of those of the lower rate ones. A perfect family of such codes is one in which each of the codes in the family is capacity-achieving. We show by construction that perfect rateless codes with low-complexity decoding algorithms exist for additive white Gaussian noise channels. Our construction involves the use of layered encoding and successive decoding, together with repetition using time-varying layer weights. As an illustration of our framework, we design a practical three-rate code family. We further construct rich sets of near-perfect rateless codes within our architecture that require either significantly fewer layers or lower complexity than their perfect counterparts. Variations of the basic construction are also developed, including one for time-varying channels in which there is no a priori stochastic model.Comment: 18 page

A Generic Algorithm for IACT Optical Efficiency Calibration using Muons

Muons produced in Extensive Air Showers (EAS) generate ring-like images in Imaging Atmospheric Cherenkov Telescopes when travelling near parallel to the optical axis. From geometrical parameters of these images, the absolute amount of light emitted may be calculated analytically. Comparing the amount of light recorded in these images to expectation is a well established technique for telescope optical efficiency calibration. However, this calculation is usually performed under the assumption of an approximately circular telescope mirror. The H.E.S.S. experiment entered its second phase in 2012, with the addition of a fifth telescope with a non-circular 600m$^2$ mirror. Due to the differing mirror shape of this telescope to the original four H.E.S.S. telescopes, adaptations to the standard muon calibration were required. We present a generalised muon calibration procedure, adaptable to telescopes of differing shapes and sizes, and demonstrate its performance on the H.E.S.S. II array.Comment: In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherland

Potential for measuring the longitudinal and lateral profile of muons in TeV air showers with IACTs

Muons are copiously produced within hadronic extensive air showers (EAS) occurring in the Earth's atmosphere, and are used by particle air shower detectors as a means of identifying the primary cosmic ray which initiated the EAS. Imaging Atmospheric Cherenkov Telescopes (IACTs), designed for the detection of gamma-ray initiated EAS for the purposes of Very High Energy (VHE) gamma-ray astronomy, are subject to a considerable background signal due to hadronic EAS. Although hadronic EAS are typically rejected for gamma-ray analysis purposes, single muons produced within such showers generate clearly identifiable signals in IACTs and muon images are routinely retained and used for calibration purposes. For IACT arrays operating with a stereoscopic trigger, when a muon triggers one telescope, other telescopes in IACT arrays usually detect the associated hadronic EAS. We demonstrate for the first time the potential of IACT arrays for competitive measurements of the muon content of air showers, their lateral distribution and longitudinal profile of production slant heights in the TeV energy range. Such information can provide useful input to hadronic interaction models.Comment: 15 pages, 11 figures, 2 tables, accepted for publication in Astroparticle Physic

Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial.

IntroductionSeveral methods have been developed to electronically monitor patients for severe sepsis, but few provide predictive capabilities to enable early intervention; furthermore, no severe sepsis prediction systems have been previously validated in a randomised study. We tested the use of a machine learning-based severe sepsis prediction system for reductions in average length of stay and in-hospital mortality rate.MethodsWe conducted a randomised controlled clinical trial at two medical-surgical intensive care units at the University of California, San Francisco Medical Center, evaluating the primary outcome of average length of stay, and secondary outcome of in-hospital mortality rate from December 2016 to February 2017. Adult patients (18+) admitted to participating units were eligible for this factorial, open-label study. Enrolled patients were assigned to a trial arm by a random allocation sequence. In the control group, only the current severe sepsis detector was used; in the experimental group, the machine learning algorithm (MLA) was also used. On receiving an alert, the care team evaluated the patient and initiated the severe sepsis bundle, if appropriate. Although participants were randomly assigned to a trial arm, group assignments were automatically revealed for any patients who received MLA alerts.ResultsOutcomes from 75 patients in the control and 67 patients in the experimental group were analysed. Average length of stay decreased from 13.0 days in the control to 10.3 days in the experimental group (p=0.042). In-hospital mortality decreased by 12.4 percentage points when using the MLA (p=0.018), a relative reduction of 58.0%. No adverse events were reported during this trial.ConclusionThe MLA was associated with improved patient outcomes. This is the first randomised controlled trial of a sepsis surveillance system to demonstrate statistically significant differences in length of stay and in-hospital mortality.Trial registrationNCT03015454

Payroll employment data: measuring the effects of annual benchmark revisions

During the recovery from the 2001 recession, the business press and economic analysts used payroll employment data released monthly by the U.S. Bureau of Labor Statistics (BLS) as evidence of protracted weakness in the labor market. But using these monthly releases for this type of analysis can be premature and potentially misleading. The initial BLS releases can differ substantially from payroll employment data that are revised to incorporate information from less timely but more complete sources. ; This article highlights the historical revisions to the aggregate nonfarm payroll employment series. Examining both monthly survey-based revisions and the more extensive annual benchmark revisions, the authors focus specifically on how the sequence of data revisions modifies payroll employment estimates from their initial release. The graphs in the article display the magnitude and direction of each revision from the initial estimate for a particular month to its currently published value, demonstrating that the largest portion of enduring change for the estimates occurs in the benchmark revisions. ; The authors then investigate empirically whether these revisions contain information that can be exploited to anticipate future revisions. The analysis shows that previous benchmark data revisions are useful for explaining the variation in subsequent payroll employment benchmark data. Such information, the authors note, could prove useful for further research aimed at modeling better real-time estimates of employment conditions.Employment (Economic theory)

Identification of phenological stages and vegetative types for land use classification

There are no author-identified significant results in this report

A study of possible sea state information in the sample and hold gate statistics for the GEOS-3 satellite altimeter

The statistical variations in the sample gate outputs of the GEOS-3 satellite altimeter were studied for possible sea state information. After examination of a large number of statistical characteristics of the altimeter waveforms, it was found that the best sea predictor for H-1/3 in the range of 0 to 3 meters was the 75th percentile of sample and hold gate number 11