Fade Depth Prediction Using Human Presence for Real Life WSN Deployment

Current problem in real life WSN deployment is determining fade depth in indoor propagation scenario for link power budget analysis using (fade margin parameter). Due to the fact that human presence impacts the performance of wireless networks, this paper proposes a statistical approach for shadow fading prediction using various real life parameters. Considered parameters within this paper include statistically mapped human presence and the number of people through time compared to the received signal strength. This paper proposes an empirical model fade depth prediction model derived from a comprehensive set of measured data in indoor propagation scenario. It is shown that the measured fade depth has high correlations with the number of people in non-line-of-sight condition, giving a solid foundation for the fade depth prediction model. In line-of-sight conditions this correlations is significantly lower. By using the proposed model in real life deployment scenarios of WSNs, the data loss and power consumption can be reduced by the means of intelligently planning and designing Wireless Sensor Network

artcat: Sample-size calculation for an ordered categorical outcome

We describe a new command, artcat, that calculates sample size or power for a randomized controlled trial or similar experiment with an ordered categorical outcome, where analysis is by the proportional-odds model. artcat implements the method of Whitehead (1993, Statistics in Medicine 12: 2257–2271). We also propose and implement a new method that 1) allows the user to specify a treatment effect that does not obey the proportional-odds assumption, 2) offers greater accuracy for large treatment effects, and 3) allows for noninferiority trials. We illustrate the command and explore the value of an ordered categorical outcome over a binary outcome in various settings. We show by simulation that the methods perform well and that the new method is more accurate than Whitehead’s method

artbin: Extended sample size for randomized trials with binary outcomes

We describe the command artbin, which offers various new facilities for the calculation of sample size for binary outcome variables that are not otherwise available in Stata. While artbin has been available since 2004, it has not been previously described in the Stata Journal. artbin has been recently updated to include new options for different statistical tests, methods and study designs, improved syntax, and better handling of noninferiority trials. In this article, we describe the updated version of artbin and detail the various formulas used within artbin in different settings

Fracture toughness measurement in fused quartz using triangular chevron-notched micro-cantilevers

We extend to flat surfaces the fracture toughness method presented in Acts Materialia vol. 86 (2015) p.385 and measure in this manner the fracture toughness of fused quartz. Tests give 0.67 +/- 0.01 MPa m(1/2) which agrees with earlier microscopic and macroscopic test data for the fast fracture toughness of this material. Data show no signs of sub-critical crack growth; this observation is at variance with what one would expect from literature data on the phenomenon. (C) 2015 The Authors. Published by Elsevier Ltd

Quality of care indicators for head and neck cancers : the experience of the European project RARECAREnet

Background: Monitoring and improving quality of cancer care has become pivotal today. This is especially relevant for head and neck cancers since the disease is complex, it needs multi therapy, patients tend to be older, they tend to have comorbidities and limited social support. However, information on quality of care for head and neck cancers is scarce. In the context of the project "Information Network on Rare Cancers" we aimed to identify indicators of quality of care specific for the head and neck cancers management and to measure the quality of care for head and neck cancers in different EU Member States. Methods: We defined indicators of quality of care for head and neck cancers based on a multidisciplinary and expert-based consensus process at a European level. To test the proposed indicators, we performed an observational population-based retrospective study in four countries (Ireland, Italy, Netherlands, and Slovenia) in the years 2009-2011. Results: The main quality indicators identified are: availability of formalized multidisciplinary team, participation in clinical and translational research; timeliness of care, high quality of surgery and radiotherapy, and of pathological reporting. For head and neck cancers, the quality of care did not reach the optimal standards in most of the countries analyzed. A high proportion of patients was diagnosed at an advanced disease stage, showed delays in starting treatment (especially for radiotherapy), and there was only a very limited use of multi therapy. Conclusions: According to the achieved consensus, indicators of quality of care for head and neck cancers have to cover the patient journey (i.e., diagnosis and treatment). Our results, showed suboptimal quality of care across countries and call for solutions for ensuring good quality of care for head and neck cancer patients in all EU countries. One possible option might be to refer head and neck cancer patients to specialized centers or to networks including specialized centers