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Economic inequality is, nowadays, frequently perceived as following a growing trend with impact on political and religious agendas. However, there is a wide range of inequality measures, each of which pointing to a possibly different degree of inequality. Furthermore, regardless of the measure used, it only acknowledges the momentary population inequality, failing to capture the individuals evolution over time. In this paper, several inequality measures were analyzed in order to compare the typical single time instant degree of wealth inequality (population perspective) to the one obtained from the individuals’ wealth mean over several time instants (individuals perspective). The proposed generalization of a simple addictive model, for limited time average of individual’s wealth, allows us to verify that the typically used inequality measures for a given snapshot instant of the population significantly overestimate the individuals’ wealth inequality over time. Moreover, that is more extreme for the ratios than for the indices analyzed. [ABSTRACT FROM AUTHOR]

Purpose Treatment outcome prediction is an important emerging topic in oncologic care. To support radiation oncologists on their decisions, with individualized, tailored treatment regimens increasingly becoming the standard of care, accurate tools to predict tumour response to treatment are needed. The goal of this work is to identify the most determinant factor(s) for treatment response aiming to develop prediction models that robustly estimate tumour response to radiation therapy in patients with head-and-neck cancer. Patients and methods A population-based cohort study was performed on 92 patients with head-and-neck cancer treated with radiation from 2007 until 2014 at the Portuguese Institute of Oncology of Coimbra (IPOCFG). Correlation analysis and multivariate binary logistic regression analysis were conducted in order to explore the predictive power of the considered predictors. Performance of the models is expressed as the area under the curve (AUC) of the receiver operating characteristics (ROC) curve. A nomogram to predict treatment failure was developed. Results Significant prognostic factors for treatment failure, after multivariate regression, were older age, non-concomitant radiation therapy and larger primary tumour volume. A regression model with these predictors revealed an AUC of .78 for an independent data set. Conclusion For patients with head-and-neck cancer treated with definitive radiation, we have developed a prediction nomogram based on models that presented good discriminative ability in making predictions of tumour response to treatment. The probability of treatment failure is higher for older patients with larger tumours treated with non-concomitant radiation. [ABSTRACT FROM AUTHOR]

The planning of radiotherapy treatments is based on the use of mathematical optimization models and algorithms. A treatment plan will correspond to an admissible solution to a problem that is defined by the medical prescription. The medical prescription defines the constraints that have to be satisfied, and that are patient dependent. To find a treatment plan complying with all the defined constraints, an objective function is built, having a set of parameters that can be tuned. In the clinical practice, the objective function parameters are tuned through a trial-and-error procedure. One common way of defining this objective function is to consider as parameters weights that are related with the importance of the corresponding structures of interest (volumes to treat and organs to spare), as well as upper and lower bounds that are related with the constraints defined by the medical prescription. Some treatment options, like the set of irradiation directions (beam angles), are usually defined beforehand by the planner, considering previous experiences with similar cases. This trial-and-error process is lengthy, since it can take up to several hours to calculate an admissible treatment plan for a single patient. There have been some research efforts to automate the treatment planning procedure, releasing the planner for other important tasks in the radiotherapy treatment workflow and guaranteeing the consistent calculation of high-quality plans. In this work derivative-free optimization algorithms are integrated with fuzzy inference systems that automatically tune the objective function parameters so that an admissible solution is found. This fully automated approach was tested and assessed considering six head-and-neck cancer cases already treated at the Portuguese Institute of Oncology at Coimbra (IPOC). For the clinical cases tested, comparisons between different treatment plans clearly favor the proposed approach. For a similar tumor coverage, it was possible to improve the sparing of the spinal cord, brainstem and parotids. Automating radiotherapy treatment planning can contribute to improved treatment plans in a consistent way. [ABSTRACT FROM AUTHOR]

This work presents a calibration study of the k – ω SST turbulence model for small scale wind turbines. To accomplish this, two different sets of blades were designed, built, tested and simulated. The first set applied the NACA 0012 and the second the NACA 4412 airfoil. The numerical investigation was taken using the CFD (computational fluid dynamics) code OpenFOAM and the turbulence model was calibrated testing several values for the β ∗ , including its canonical value, 0.09. The numerical calibration (the main contribution of this paper), extended previous results, which stated that different β ∗ values could calibrate the k – ω SST turbulence model for small wind turbines, mainly for the drag effects. The study broadened this conclusion, once the model was calibrated for a quite wide range of tip speed ratio values, from the turbine startup ( λ = 0) until its highest experimental value ( λ ≅ 8). As a secondary contribution, the results show that the model could be adjusted to simulate average field data, even though these being subject to its inherent variabilities. The main conclusion was that, for the sets of blades studied, the lowest RMSE value was obtained for β ∗ = 0.27. [ABSTRACT FROM AUTHOR]

Abstract: The selection of appropriate beam directions is decisive for the quality of the treatment, both for maximizing tumor doses and for organs sparing. However, the beam angle optimization (BAO) problem is still an open problem and, most of the time, beam directions continue to be manually selected in clinical practice which requires many trial and error iterations between selecting beam angles and computing fluence patterns until a suitable treatment is achieved. The goal of BAO is to improve the quality of the directions used and, at the same time, release the treatment planner for other tasks. The objective of this paper is to introduce a new approach for the resolution of the BAO problem, using pattern search methods to tackle this highly non-convex optimization problem. Pattern search methods are derivative-free optimization methods with the ability to avoid local entrapment. Moreover, they require few function value evaluations to progress and converge. These two characteristics gathered together make pattern search methods suited to address the BAO problem. A set of clinical examples of head-and-neck cases is used to discuss the benefits of using pattern search methods in the optimization of the BAO problem. [Copyright &y& Elsevier]

Abstract: The intensity modulated radiation therapy (IMRT) treatment planning problem is usually divided into three smaller problems that are solved sequentially: the geometry problem, intensity problem, and realization problem. That division has the consequence of causing a plan quality deterioration arising from the transition between the intensity problem and the realization problem. Typically, on the beamlet-based approach, after the optimal beamlet intensities are determined, they are discretized over a range of values using a distance criterion (rounding). However, that decision criterion is not appropriate and we present empirical evidence that this can lead to a significant deterioration of the treatment plan quality regardless of the model used to tackle the intensity problem. We propose a combinatorial optimization approach and a probabilistic binary tabu search algorithm to enable an improved transition from optimized to delivery fluence maps in IMRT by minimizing the deterioration of the treatment plan quality and improving organ sparing at the same time. Four head and neck clinical examples were used to test the ability of the proposed formulation and resolution method to obtain improved plans compared to the usual rounding procedure. The results obtained present a clear improvement of the treatment plan quality both in terms of target coverage and also in terms of parotid sparing. [Copyright &y& Elsevier]

The current COVID-19 pandemic caught everyone off guard and is an excellent case study to investigate the real impact of population density on emerging highly contagious infectious diseases. The relationship between the threat of COVID-19 and population density has been widely debated not only in scientific articles, but also in magazines and reports around the world. It appeared both in the columns of experts and in the speeches of politicians, yet without reaching any consensus. In this study, using COVID-19 data from France, we try to shed light on this debate. An alternative density measure, weighted by population, is used. This novel density measure clearly outperforms the commonly used density in terms of relationship with COVID-19 deaths and proved to be competitive with some of the best known predictors, including population. A multifractal analysis, characterizing different space distributions of population in France, is used to further understand the relation between density and COVID-19 mortality rate. [ABSTRACT FROM AUTHOR]

Introduction Active children often choose after-school sport experiences, among which swimming and soccer are at the top of the list of most popular sports in several countries. Athletic skills are increased but little is known about the effects on global motor development. The purpose of our study was to analyze changes on global motor development after 5, 10 and 30 months of swimming and soccer practice [1–3] . Methods The study sample consisted of 35 preschool-aged boys (4.9 ± 0.5 years): 13 children had no involvement in organized sports programs; 11 children were swimmers at a beginner level; 11 children were soccer players at a beginner level. The “test of gross motor development 2” [3] was used to assess children's fundamental movement skill competence (locomotion and object control skills) in three distinct phases: after five (T5), 10 (T10) and 30 (T30) months of accumulated sports practice (practising 2 times per week). Results Our results showed that the soccer participants had a higher ( P < 0.05) global motor ratio (at T 5 , T 10 and T 30 ) and standard scores for locomotion and object control (T 10 and T 30 ) than the swimming participants and non-participants. Both sport participant groups significantly improved ( P < 0.05) their global motor ratio and the standard scores for locomotion and object control between T 5 and T 10 . Between (T 10 –T 30 ), the standard scores for control of objects significantly improved ( P < 0.05) only for the swimming participants. In fact, the global motor ratio and the standard scores for object control significantly decreased ( P < 0.05) between T 10 and T 30 for soccer participants. No significant changes ( P > 0.05) were noted between (T 5 –T 10 ) and (T 10 –T 30 ) for non-participants. Conclusions These results suggest that sports practice during childhood seems to prompt motor development. Despite the improved motor skill competence of the soccer participants at (T 5 –T 10 ) and (T 10 –T 30 ), the swimmers showed an ongoing motor development particularly in object control skills. [ABSTRACT FROM AUTHOR]

The growth dynamics of firms have been object of numerous studies by econophysicists. The vast majority of these studies was done for large developed countries including the United States of America (US), France and Italy. These studies were conducted for countries with strong economies and whose business fabric has different characteristics from countries such as Portugal or Spain, with more large-sized firms and less micro-sized firms. It is thus important to study the growth dynamics of firms in Portugal and Spain, countries with economies that typically display anemic growth indexes and have a larger percentage of micro-sized firms. Considering two large samples of Portuguese and Spanish firms, we find that the size distribution of firms is well fitted by the generalized Pareto distribution. Moreover, the distribution of Iberian firms annual growth rates is best approximated by the Cauchy distribution rather than the Laplace distribution. Firms growth standard deviation conditional on size is well approximated by power-law relationships with a scaling exponent close to 1 2 for micro/small-sized firms and close to 0 for medium/large-sized firms. • The distribution of firm growth in Portuguese and Spanish firms is characterized. • Size distribution is well fitted by the generalized Pareto distribution. • Distribution of annual growth rates is best approximated by the Cauchy distribution. • Firms growth standard deviation is well approximated by power-law relationships. [ABSTRACT FROM AUTHOR]

• CD4-positive cells mainly present in brain and kidneys of immunosuppressed rabbits. • CD8-positive cells mainly present in kidneys of immunosuppressed rabbits. • MHCII cells more predominant in brain of immunocompetent rabbits. • Change in phenotype of Th1- to Th2-like in brain and kidneys granulomas by an unknown mechanism. Encephalitozoon cuniculi (E. cuniculi) is a fungi-related, obligate, zoonotic, spore-forming intracellular eukaryotic microorganism. This emerging pathogen causes granulomas in brain and kidneys of infected individuals. The objective of this study was to detect the distribution of CD4, CD8 and MHCII-positive cells within granulomas in these organs in infected immunocompetent (group A) and infected immunosuppressed (group B) New Zealand white rabbits using immunohistochemistry. In brain, labeled CD4 immune cells were mainly located in the periphery of granulomas in group B. Kidneys of groups A and B, displayed CD4-positive in granulomas and were significant different when compared to brain. CD8 immune cells in brain and kidneys were disseminated in the granulomas in groups A and B; however, no significant difference was observed. MHCII-positive cells were more numerous in brain sections of group B and were significantly different when compared to kidney sections. Granulomas were not observed in control animals of group C and D. In conclusion, we identified CD4-positive cells in both the brain and kidneys of immunocompetent and immunosuppressed animals; CD8-positive cells were more numerous in brain of immunosuppressed rabbits and MHCII cells were more predominant in brain of immunocompetent rabbits. Apparently, the immunosuppression stimulated a change in the cellular phenotype of Th1- to Th2-like granulomas in brain and kidneys by an unknown mechanism. These results increase our understanding of CD4, CD8 and MHCII positive cells within the E. cuniculi granuloma microenvironment and will help in future microsporidian granulomas studies of both immunocompetent and immunosuppressed individuals. [ABSTRACT FROM AUTHOR]