12,278 research outputs found
Weight changes following lower limb arthroplasty : a prospective observational study
The aim of this study was to assess patterns of weight loss/gain following total hip or knee joint replacement. Four hundred and fifty primary lower limb arthroplasty patients, where the current surgery was the last limiting factor to improved mobility, were selected. Over a one year period 212 gained weight (mean 5.03kg), 92 remained static, and 146 lost weight. The median change was a weight gain of 0.50Kg (p=0.002). All patients had a significant improvement in Oxford outcome scores. Hip arthroplasty patients were statistically more likely to gain weight than knee arthroplasty patients. A successful arthroplasty, restoring a patient's mobility, does not necessarily lead to subsequent weight loss. The majority of patients put on weight with an overall net weight gain. No adverse effect on functional outcome was noted
The adaptive problem of absent third-party punishment
Language is a uniquely human behaviour, which has presented unique adaptive problems. Prominent among these is the transmission of information that may affect an individual’s reputation. The possibility of punishment of those with a low reputation by absent third parties has created a selective pressure on human beings that is not shared by any other species. This has led to the evolution of unique cognitive structures that are capable of handling such a novel adaptive challenge. One of these, we argue, is the propositional theory of mind, which enables individuals to model, and potentially manipulate, their own reputation in the minds of other group members, by representing the beliefs that others have about the first party’s intentions and actions. Support for our theoretical model is provided by an observational study on tattling in two preschools, and an experimental study of giving under threat of gossip in a dictator game
Low-frequency QPO from the 11 Hz accreting pulsar in Terzan 5: not frame dragging
We report on 6 RXTE observations taken during the 2010 outburst of the 11 Hz
accreting pulsar IGR J17480-2446 located in the globular cluster Terzan 5.
During these observations we find power spectra which resemble those seen in
Z-type high-luminosity neutron star low-mass X-ray binaries, with a
quasi-periodic oscillation (QPO) in the 35-50 Hz range simultaneous with a kHz
QPO and broad band noise. Using well known frequency-frequency correlations, we
identify the 35-50 Hz QPOs as the horizontal branch oscillations (HBO), which
were previously suggested to be due to Lense-Thirring precession. As IGR
J17480-2446 spins more than an order of magnitude more slowly than any of the
other neutron stars where these QPOs were found, this QPO can not be explained
by frame dragging. By extension, this casts doubt on the Lense-Thirring
precession model for other low-frequency QPOs in neutron-star and perhaps even
black-hole systems.Comment: 6 pages, 5 figures, Accepted for publication in ApJ
Joining up health and bioinformatics: e-science meets e-health
CLEF (Co-operative Clinical e-Science Framework) is an MRC sponsored project in the e-Science programme that aims to establish methodologies and a technical infrastructure forthe next generation of integrated clinical and bioscience research. It is developing methodsfor managing and using pseudonymised repositories of the long-term patient histories whichcan be linked to genetic, genomic information or used to support patient care. CLEF concentrateson removing key barriers to managing such repositories ? ethical issues, informationcapture, integration of disparate sources into coherent ?chronicles? of events, userorientedmechanisms for querying and displaying the information, and compiling the requiredknowledge resources. This paper describes the overall information flow and technicalapproach designed to meet these aims within a Grid framework
Effect of daily restriction and age at initiation of a skip-a-day program for young broiler breeders.
Two experiments were conducted with Cobb feather sex broiler breeders comparing skip-a-day (SAD) feeding programs which began at either 2, 4, 6 or 8 wk of age. A fifth program, daily restriction started at 2 wk of age, was also compared. Chicks hatched in December and July, respectively, in Experiments 1 and 2 were exposed to natural daylight until 20 wk of age. All birds were fed ad libitum until the respective restriction programs began. All grower programs terminated at 20 wk of age. A breeder diet was given daily after 20 wk. Males and females were grown together. Sexual maturity was reached earlier in the 2-wk restriction groups (2-wi SAD in Experiment 1 and the 2-wk daily restriction in both experiments) than in the 8-wk SAD group. Egg production in Experiment 1 was also improved by the early restriction. Fertility and hatchability were not significantly affected by treatment. Based on the results of these experiments a SAD program beginning at 2 wk of age was as good as or better than one initiated at later ages. The 2-wk daily restriction program was equivalent to the 2-wk SAD program
Lighting of end of lay broiler breeders: fluorescent versus incandescent.
An 18-week experiment was conducted to investigate the effects of changing from incandescent to fluorescent lighting on egg production, egg weight, fertility, and hatchability of end of lay broiler breeders housed in an open-sided house. Forty-eight-week-old Cobb feather-sexed broiler breeders were housed, 30 females and 3 males per pen, in a total of 28 pens. Incandescent lights had been used previously, so pens were randomly assigned to either fluorescent or incandescent lights giving 20 lx of light at bird level. Lights used were 60 W incandescent and 22 W fluorescent cool-white circular. Body weight and egg production were measured weekly, and fertility, hatchability, and egg weight were determined monthly from 48 to 65 weeks of age. No significant treatment effects were observed on body weight, fertility, hatchability, or egg weight. A significant reduction in egg production was observed with fluorescent lighting from Weeks 58 to 65. The reduced egg production indicated it was detrimental to change from incandescent to cool-white fluorescent lighting
Dynamic Analysis of Executables to Detect and Characterize Malware
It is needed to ensure the integrity of systems that process sensitive
information and control many aspects of everyday life. We examine the use of
machine learning algorithms to detect malware using the system calls generated
by executables-alleviating attempts at obfuscation as the behavior is monitored
rather than the bytes of an executable. We examine several machine learning
techniques for detecting malware including random forests, deep learning
techniques, and liquid state machines. The experiments examine the effects of
concept drift on each algorithm to understand how well the algorithms
generalize to novel malware samples by testing them on data that was collected
after the training data. The results suggest that each of the examined machine
learning algorithms is a viable solution to detect malware-achieving between
90% and 95% class-averaged accuracy (CAA). In real-world scenarios, the
performance evaluation on an operational network may not match the performance
achieved in training. Namely, the CAA may be about the same, but the values for
precision and recall over the malware can change significantly. We structure
experiments to highlight these caveats and offer insights into expected
performance in operational environments. In addition, we use the induced models
to gain a better understanding about what differentiates the malware samples
from the goodware, which can further be used as a forensics tool to understand
what the malware (or goodware) was doing to provide directions for
investigation and remediation.Comment: 9 pages, 6 Tables, 4 Figure
Dynamic mooring simulation with Code_Aster with application to a floating wind turbine
This is the final version of the article. Available from Elsevier via the DOI in this record.The design of reliable station-keeping systems for permanent floating structures such as offshore renewable energy devices is vital to their lifelong integrity. In highly dynamic and/or deep-water applications, including hydrodynamics and structural dynamics in the mooring analysis is paramount for the accurate prediction of the loading on the lines and hence their dimensioning. This article presents a new workflow based on EDF R&D's open-source, finite-element analysis tool Code_Aster, enabling the dynamic analysis of catenary mooring systems, with application to a floating wind turbine concept. The University of Maine DeepCwind-OC4 basin test campaign is used for validation, showing that Code_Aster can satisfactorily predict the fairlead tensions in both regular and irregular waves. In the latter case, all of the three main spectral components of tension observed in the experiments are found numerically. Also, the dynamic line tension is systematically compared with that provided by the classic quasi-static approach, thereby confirming its limitations. Robust dynamic simulation of catenary moorings is shown to be possible using this generalist finite-element software, provided that the inputs be organised consistently with the physics of offshore hydromechanics.IDCORE is funded by the ETI and the RCUK Energy programme, grant number EP/J500847/1. The authors are grateful for the funding provided by these institutions, and to EDF R&D for hosting and supervising the industrial doctorate which expressed the present work
Photoelectro-Photometric Survey of Night Sky Conditions in the Vicinity of Iowa City
During the summer 1962, a systematic survey of night sky conditions in the vicinity of Iowa City was carried out for the purpose of selecting the best site for the proposed research observatory of the State University of Iowa. A photoelectric photometer was attached to the Newtonian focus of an 11-inch reflector whose equatorial mounting was modified to a horizontal system. The equipment was carried by a truck and observations were made at six different sites, ranging in distance from eight to twenty-three miles in all directions from the city. In order to eliminate random errors due to variations in sky conditions from night to night, measurements of scattered city lights and the atmospheric extinctions were taken on at least two different sites during the same night and were repeated for six or seven different moonless nights at each site. As a result, it was concluded that the region about twelve miles south-southwest of the city is least affected by the artificial city light
Tracking Cyber Adversaries with Adaptive Indicators of Compromise
A forensics investigation after a breach often uncovers network and host
indicators of compromise (IOCs) that can be deployed to sensors to allow early
detection of the adversary in the future. Over time, the adversary will change
tactics, techniques, and procedures (TTPs), which will also change the data
generated. If the IOCs are not kept up-to-date with the adversary's new TTPs,
the adversary will no longer be detected once all of the IOCs become invalid.
Tracking the Known (TTK) is the problem of keeping IOCs, in this case regular
expressions (regexes), up-to-date with a dynamic adversary. Our framework
solves the TTK problem in an automated, cyclic fashion to bracket a previously
discovered adversary. This tracking is accomplished through a data-driven
approach of self-adapting a given model based on its own detection
capabilities.
In our initial experiments, we found that the true positive rate (TPR) of the
adaptive solution degrades much less significantly over time than the naive
solution, suggesting that self-updating the model allows the continued
detection of positives (i.e., adversaries). The cost for this performance is in
the false positive rate (FPR), which increases over time for the adaptive
solution, but remains constant for the naive solution. However, the difference
in overall detection performance, as measured by the area under the curve
(AUC), between the two methods is negligible. This result suggests that
self-updating the model over time should be done in practice to continue to
detect known, evolving adversaries.Comment: This was presented at the 4th Annual Conf. on Computational Science &
Computational Intelligence (CSCI'17) held Dec 14-16, 2017 in Las Vegas,
Nevada, US
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