159 resultados para Shenhu Area


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BACKGROUND: This study investigated the effect of socioeconomic deprivation on preoperative disease and outcome following unicompartmental knee replacement (UKR).

METHODS: 307 Oxford UKRs implanted between 2008 and 2013 under the care of one surgeon using the same surgical technique were analysed. Deprivation was quantified using the Northern Ireland Multiple Deprivation Measure. Preoperative disease severity and postoperative outcome were measured using the Oxford Knee Score (OKS).

RESULTS: There was no difference in preoperative OKS between deprivation groups. Preoperative knee range of motion (ROM) was significantly reduced in more deprived patients with 10° less ROM than least deprived patients. Postoperatively there was no difference in OKS improvement between deprivation groups (p=0.46), with improvements of 19.5 and 21.0 units in the most and least deprived groups respectively. There was no significant association between deprivation and OKS improvement on unadjusted or adjusted analysis. Preoperative OKS, Short Form 12 mental component score and length of stay were significant independent predictors of OKS improvement. A significantly lower proportion of the most deprived group (15%) reported being able to walk an unlimited distance compared to the least deprived group (41%) one year postoperatively.

CONCLUSION: More deprived patients can achieve similar improvements in OKS to less deprived patients following UKR.

LEVEL OF EVIDENCE: 2b - retrospective cohort study of prognosis.

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To evaluate the performance of the co-channel transmission based communication, we propose a new metric for area spectral efficiency (ASE) of interference limited ad-hoc network by assuming that the nodes are randomly distributed according to a Poisson point processes (PPP). We introduce a utility function, U = ASE/delay and derive the optimal ALOHA transmission probability p and the SIR threshold τ that jointly maximize the ASE and minimize the local delay. Finally, numerical results have been conducted to confirm that the joint optimization based on the U metric achieves a significant performance gain compared to conventional systems.

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Given the success of patch-based approaches to image denoising,this paper addresses the ill-posed problem of patch size selection.Large patch sizes improve noise robustness in the presence of good matches, but can also lead to artefacts in textured regions due to the rare patch effect; smaller patch sizes reconstruct details more accurately but risk over-fitting to the noise in uniform regions. We propose to jointly optimize each matching patch’s identity and size for gray scale image denoising, and present several implementations.The new approach effectively selects the largest matching areas, subject to the constraints of the available data and noise level, to improve noise robustness. Experiments on standard test images demonstrate our approach’s ability to improve on fixed-size reconstruction, particularly at high noise levels, on smoother image regions.

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Channel randomness can be exploited to generate secret keys. However, to ensure secrecy, it is necessary that the channel response of any eavesdropping party remain sufficiently de-correlated with that of the legitimate users'. In this paper, we investigate whether such de-correlation occurs for a body area network (BAN) operating in an indoor environment at 2.45 GHz. The hypothetical BAN configuration consisted of two legitimate transceivers, one situated on the user's left wrist and the other on the user's waist. The eavesdroppers were positioned in either a co-located or distributed manner in the area surrounding the BAN user. Using the simultaneous channel response measured at the legitimate BAN nodes and the eavesdropper positions for stationary and mobile scenarios, we analyze the localized correlation coefficient. This allows us to determine if it is possible to generate secret keys in the presence of multiple eavesdroppers in an indoor environment. Our experimental results show that although channel reciprocity was observed for both the stationary and the mobile scenarios, a higher de-correlation between the legitimate users' channels was observed for the stationary case. This indicates that mobile scenarios are better suited for secret key generation.

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The recent European economic crisis has dramatically exposed the failures of
the various institutional mechanisms in place to maintain economic stability
in Europe, and has unveiled the difficulty in achieving international coordination
on fiscal and financial stability policies. Drawing on the European
experience, this article analyzes the concept of economic stability in international
law and highlights the peculiar problems connected to its maintenance
or promotion. First, we demonstrate that policies that safeguard and
protect economic stability are largely regulated and managed at the national
level, due to their inextricable relationship with the exercise of national political
power. Until recently, more limited levels of pan-European integration
did not make the coordination of economic stability policies seem necessary.
However, a much deeper level of economic integration makes it very difficult
to tackle an international economic crisis through national responses. If EU
Member states wish to maintain and deepen economic integration, they
must accept an erosion of sovereignty over their economic stability policies.
This will not only deprive states of a fundamental anchor of political power,
but also create a challenge for the maintenance of democratic control over
economic policies. Second, this article argues that soft law approaches are
likely ineffective in enforcing the regulatory disciplines required to ensure
economic stability.

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The integration of an ever growing proportion of large scale distributed renewable generation has increased the probability of maloperation of the traditional RoCoF and vector shift relays. With reduced inertia due to non-synchronous penetration in a power grid, system wide disturbances have forced the utility industry to design advanced protection schemes to prevent system degradation and avoid cascading outages leading to widespread blackouts. This paper explores a novel adaptive nonlinear approach applied to islanding detection, based on wide area phase angle measurements. This is challenging, since the voltage phase angles from different locations exhibit not only strong nonlinear but also time-varying characteristics. The adaptive nonlinear technique, called moving window kernel principal component analysis is proposed to model the time-varying and nonlinear trends in the voltage phase angle data. The effectiveness of the technique is exemplified using both DigSilent simulated cases and real test cases recorded from the Great Britain and Ireland power systems by the OpenPMU project.