Abstract
With rising healthcare costs, using health personnel and resources efficiently and effectively is critical. International cross-country and simple worker-to-population ratio comparisons are frequently used for improving the efficiency of health systems, planning of health human resources and guiding policy changes. These comparisons are made between countries typically of the same continental region. However, if used imprudently, inconsistencies arising from frail comparisons of health systems may outweigh the positive benefits brought by new policy insights. In this work, we propose a different approach to international health system comparisons. We present a methodology to group similar countries in terms of mortality, morbidity, utilisation levels, and human and physical resources, which are all factors that influence health gains. Instead of constructing an absolute rank or comparing against the average, the method finds countries that share similar ground, upon which more reliable comparisons can then be conducted, including performance analysis. We apply this methodology using data from the World Health Organization's Health for All database, and we present some interesting empirical relationships between indicators that may provide new insights into how such information can be used to promote better healthcare planning and policy guidance.

Abstract
Built-in sensors in most modern smartphones open multipleopportunities for novel context-aware applications. Although the HumanActivity Recognition field seized such opportunity, many challengesare yet to be addressed, such as the differences in movement by peopledoing the same activities. This paper exposes empirical research onOnline Semi-supervised Learning (OSSL), an under-explored incrementalapproach capable of adapting the classification model to the userby continuously updating it as data from the users own input signalsarrives. Ultimately, we achieved an average accuracy increase of 0.18percentage points (PP) resulting in a 82.76% accuracy model with NaiveBayes, 0.14 PP accuracy increase resulting in a 83.03% accuracy modelwith a Democratic Ensemble, and 0.08 PP accuracy increase resultingin a 84.63% accuracy model with a Confidence Ensemble. These modelscould detect 3 stationary activities, 3 active activities, and all transitionsbetween the stationary activities, totaling 12 distinct activities

Abstract
Background/Aims: Intradialytic hypotension (IDH) is a serious and frequent complication of hemodialysis (HD). Thus far, data are scarcely available to assess the impact of first versus subsequent HD sessions of the week in IDH. Therefore, the purpose of this work was to evaluate IDH risk in patients on thrice-weekly HD. Methods: We conducted an analysis of all blood pressure (BP) measurements obtained during 492 HD treatments given to 41 prevalent adult patients over a one month period. A logistic regression model for repeated binary observations was used to determine the association between hypotension and patient and dialysis factors. Results: The incidence of IDH was 32.5%. First dialysis session of the week was associated with a 9% higher risk of hypotension relatively to the second one. The risk was even higher from the first to the third session of the week (60%) and from the second to the third (50%). A higher hypotension odds ratio was also associated with age (1.03, 90% CI: 1.01-1.06), higher predialysis BP (1.04, 90% CI: 1.03-1.05) and higher phosphorus level (1.38, 90% CI: 1.07-1.76). The risk decreased 24.4% for each additional antihypertensive drug taken by the patient. Conclusions: The odds of hypotension occurrence decrease throughout dialysis sessions of the week. Minimizing modifiable risk factors may decrease IDH episodes. (C) 2016 The Author(s) Published by S. Karger AG, Basel

Abstract
Nowadays compilers include tens or hundreds of optimization passes, which makes it difficult to find sequences of optimizations that achieve compiled code more optimized than the one obtained using typical compiler options such as -O2 and -O3. The problem involves both the selection of the compiler passes to use and their ordering in the compilation pipeline. The improvement achieved by the use of custom phase orders for each function can be significant, and thus important to satisfy strict requirements such as the ones present in high-performance embedded computing systems. In this paper we present a new and fast iterative approach to the phase selection and ordering challenges resulting in compiled code with higher performance than the one achieved with the standard optimization levels of the LLVM compiler. The obtained performance improvements are comparable with the ones achieved by other iterative approaches while requiring considerably less time and resources. Our approach is based on sampling over a graph representing transitions between compiler passes. We performed a number of experiments targeting the LEON3 microarchitecture using the Clang/LLVM 3.7 compiler, considering 140 LLVM passes and a set of 42 representative signal and image processing C functions. An exhaustive cross-validation shows our new exploration method is able to achieve a geometric mean performance speedup of 1.28x over the best individually selected -OX flag when considering 100,000 iterations; versus geometric mean speedups from 1.16x to 1.25x obtained with state-of-the-art iterative methods not using the graph. From the set of exploration methods tested, our new method is the only one consistently finding compiler sequences that result in performance improvements when considering 100 or less exploration iterations. Specifically, it achieved geometric mean speedups of 1.08x and 1.16x for 10 and 100 iterations, respectively.

Abstract
Fiber probe structures composed of two physical microcavities were created using focused ion beam technology. These structures have a tip-like shape as they were milled in preciously etched tapered fiber tips. The microprobes are then characterized for temperature and refractive index sensing using a signal filtering technique to discriminate signals from distinct microcavities. Using fast Fourier transforms combined with band-pass filters, it is possible to reconstruct the spectra of each cavity independently and thus measure their individual spectral shifts.

Abstract
A comprehensive dynamic model based on Direct-Quadrature (DQ) rotating frame is proposed in this paper that is used along with a capability curve (CC) based on the active and reactive power to control a grid-connected single-phase voltage-source inverter (SPVSI). With the proposed dynamic model, a droop-passivity based controller can be designed for the grid-connected inverter in the presence of nonlinear loads. Stability analysis of the proposed control technique is also discussed in the paper as well as design principles. Moreover, an accurate performance area of SPVSI active and reactive power in dynamic transitions is achieved using the CC. Furthermore, an effective harmonic compensation scheme along with a proper active and reactive power sharing algorithm are performed by a well-designed reference waveform generation process. Performance of the grid-connected SPVSI, under the proposed controller, is thoroughly evaluated in the Matlab/Simulink environment.