Short-term efficacy and safety of betamethasone valerate 2.25 mg medicated plaster in patients with chronic lateral epicondylitis: Results of a randomised, double blind, placebo-controlled study

Background. This placebo-controlled, double-blind study evaluated the short-term effects of betamethasone valerate (BMV) 2.25mg medicated plaster in patients with chronic lateral elbow tendinopathy (LET). Methods. Adult outpatients with LET and on-movement pain intensity ≥50 mm at a 0-100mm visual analogue scale (VAS) were randomised to receive BMV (N=101) or placebo (N=98), 12 hours/day for 4 weeks. Pain decrease from baseline to Day 28 was the primary endpoint. Other endpoints were: patient-rated tennis elbow evaluation (PRTEE), use of rescue paracetamol, tolerability at the application site. Results. Decrease in mean pain VAS from baseline to Day 28 was significantly higher with BMV vs. placebo: the difference between groups (intent-to-treat) was-8.57 mm (95% CI:-16.19 to-0.95 mm; p=0.028). Higher pain decreases in the BMV group over placebo were reported weekly during each control visit and daily in patients’ measurements on diaries. Treatment with BMV also led to higher decreases vs. placebo in PRTEE total, pain and functional disability score. Use of paracetamol was minimal. BMV plaster was well tolerated for general and local adverse events. Conclusions. BMV 2.25mg plaster was superior to placebo and well tolerated in patients with painful chronic LET

Effect of shunt resistance on the performance of mc-Silicon solar cells: a combined electro-optical and thermal investigation

In this paper we discuss the effect of shunt resistance on the electro-optical characteristics of multicrystalline silicon (mc-Si) solar cells at different illumination levels. The analysis is based on combined electro-optical characterization and thermographic measurements of solar cells with similar efficiencies, but with different shunt resistance levels. In order to understand how the shunt resistance can affect the performance of mc-Si solar cells, a special setup for J-V characterization at several illumination levels was developed. Results indicate that (i) a low shunt resistance is strongly correlated to the presence of hot spots, which can be identified by means of infrared thermography; (ii) solar cells with different shunt resistance levels can show significantly different fill factors and efficiencies, particularly at low irradiation levels. This can strongly influence the reliability of modules at low illumination conditions; (iii) the electrical characteristics of mc-Si solar cells can be modeled with good results, by considering the equivalent two-diode electrical model and solving it by a circuit simulator like SPICE

Virtualization and cognitive management of real world objects in the internet of things

This paper presents a framework for the virtualization of real world objects and the cognitive management of their virtual counterparts. The framework consists of three levels of functionality and each level comprises cognitive entities that provide the means for self-management and learning, allowing for smart, flexible applications and objects. The presented framework enables the abstraction of the heterogeneity that derives from the vast amount of diverse objects/devices, while enhancing reliability and facilitates the consideration of the views of various users/stakeholders (owners of objects & communication means) for ensuring proper application provision, business integrity and, therefore, maximization of exploitation opportunities. The paper also presents a corresponding prototype that has been developed for the validation of the proposed approach, in a real-life fire detection scenario in a Smart Home

Enabling smart cities through a cognitive management framework for the internet of things

The Internet of Things (IoT) is expected to substantially support sustainable development of future smart cities. This article identifies the main issues that may prevent IoT from playing this crucial role, such as the heterogeneity among connected objects and the unreliable nature of associated services. To solve these issues, a cognitive management framework for IoT is proposed, in which dynamically changing real-world objects are represented in a virtualized environment, and where cognition and proximity are used to select the most relevant objects for the purpose of an application in an intelligent and autonomic way. Part of the framework is instantiated in terms of building blocks and demonstrated through a smart city scenario that horizontally spans several application domains. This preliminary proof of concept reveals the high potential that self-reconfigurable IoT can achieve in the context of smart cities