Abstract
Background: Ensuring healthcare delivery is dependent both on the prediction of the future demand for healthcare services and on the estimation and planning for the Health Human Resources needed to properly deliver these services. Although the Health Human Resources planning is a fascinating and widely researched topic, and despite the number of methodologies that have been used, no consensus on the best way of planning the future workforce requirements has been reported in the literature. This paper aims to contribute to the extension and diversity of the range of available methods to forecast the demand for Health Human Resources and assist in tackling the challenge of translating healthcare services to workforce requirements. Methods: A method to empirically quantify the relation between healthcare services and Health Human Resources requirements is proposed. For each one of the three groups of specialties identified-Surgical specialties, Medical specialties and Diagnostic specialties (e.g., pathologists)-a Labor Requirements Function relating the number of physicians with a set of specialty-specific workload and capital variables is developed. This approach, which assumes that health managers and decision-makers control the labor levels more easily than they control the amount of healthcare services demanded, is then applied to a panel dataset comprising information on 142 public hospitals, during a 12-year period. Results: This method provides interesting insights on healthcare services delivery: the number of physicians required to meet expected variations in the demand for healthcare, the effect of the technological progress on healthcare services delivery, the time spent on each type of care, the impact of Human Resources concentration on productivity, and the possible resource allocations given the opportunity cost of the physicians' labor. Conclusions: The empirical method proposed is simple and flexible and produces statistically strong models to estimate Health Human Resources requirements. Moreover, it can enable a more informed allocation of the available resources and help to achieve a more efficient delivery of healthcare services.

Abstract
This paper presents the modeling and simulation of a spherical autonomous underwater vehicle. The robot was developed under the European Union H2020 innovation action UNEXMIN for the exploration of underground flooded mines, and is a small spherical robot with thrusters and an internal pendulum for pitch control. A model of the vehicle is presented, initially without the pendulum, then an extended formulation is derived accounting for a multibody dynamic description of the system. Experimental identification results for the determination of drag parameters are presented as well. A Modelica based simulator is developed for dynamic simulation of the vehicle, and is integrated with the Matlab/Simulink environment. The simulator is then validated based on preliminary experimental results.

Abstract

Abstract
Devido ao ambiente hipercompetitivo que as empresas industriais enfrentam, a adequada implementação de Meta-Organizações, como plataformas organizacionais que promovam o desenvolvimento de modelos avançados de sistemas de produção em rede, virtuais e ubíquas, torna-se fundamental para a sustentabilidade da Meta-Organização e das empresas industriais que a constituem. A estratégia de implementação encontra-se relacionada com o entendimento que as empresas industriais, no caso específico deste estudo, as Pequenas e Médias Empresas (PMEs) industriais de clusters regionais, têm acerca deste tipo de Meta-Organização. Este estudo tem como objetivo validar as principais hipóteses: 1) as empresas da região estão conscientes da necessidade da adoção de Meta-Organizações como plataformas organizacionais para o desenvolvimento de modelos de Empresas Virtuais e Ubíquas; e 2) as empresas da região estão aptas para a utilização de Meta-Organizações no apoio ao desenvolvimento de modelos de Empresas Virtuais e Ubíquas. Para validação destas teses foram desenvolvidos modelos teóricos originais utilizando o método estatístico de Análise de Equações Estruturais constituídos por oito constructos: “Prática”, “Gestão do Conhecimento”, “Característica da PME Industrial”, “Conhecimento”, “Necessidade de Estruturas de Meta-Organização para Empresas Virtuais e Ubíquas”, “Necessidade para a Gestão da Meta-Organização para Empresas Virtuais e Ubíquas”, “Consciência” e “Aptidão”. A recolha de dados foi realizada através da implementação de um inquérito original em que participaram 236 PMEs (industriais ou que trabalham com a indústria) da região da Península Ibérica. Os resultados obtidos validam as principais hipóteses sobre a consciência e a aptidão das empresas e fornecem outros resultados derivados de outras hipóteses inerentes aos modelos desenvolvidos. O presente estudo contribui para definir os mecanismos de escolha da implementação de Meta- Organizações que apoiam o desenvolvimento de modelos de Empresas Virtuais e Ubíquas.;Due to the hypercompetitive environment that industrial enterprises face, a proper implementation of the Meta-Organizations, as organizational platforms, that promote the development of advanced models of networked, virtual and ubiquitous production systems, becomes fundamental for the sustainability of the Meta-Organization and of the industrial enterprises that belong to it. The implementation strategy is related to the understanding that the industrial enterprises, in the specific case of this study, the Industrial Small and Medium-sized Enterprises (SMEs) of regional clusters, have about this type of Meta-Organization. This study aims to validate the following main hypotheses: 1) enterprises in the region are aware of the need to adopt Meta-Organizations as an organizational platform for the development of Virtual and Ubiquitous Enterprises models; and 2) enterprises in the region are prepared to use Meta- Organizations to support the development of Virtual and Ubiquitous Enterprises models. To validate these theses, original theoretical models were developed using the statistical method of Structural Equation Modeling constituted by eight constructs: “Practice”, “Knowledge Management”, “Characteristics of Industrial SME”, “Knowledge”, “Need for Meta-Organization Structures for Virtual and Ubiquitous Enterprises”, “Need for Meta-Organization Management for Virtual and Ubiquitous Enterprises”, “Awareness”, and “Preparedness”. Data collection was carried out through the implementation of an original survey in which 236 SMEs (industrial or those working with the industry) in the Iberian Peninsula region participated. The results validate the main hypotheses concerning enterprises’ awareness and preparedness, and provide further results derived from other hypotheses inherent to the developed models. The present study contributes to define the mechanisms of choice for the implementation of Meta- Organizations that support the development of Virtual and Ubiquitous Enterprises models.

Abstract
Automatic parallelization of sequential code has become increasingly relevant in multicore programming. In particular, loop parallelization continues to be a promising optimization technique for scienti.c applications, and can provide considerable speedups for program execution. Furthermore, if we can verify that there are no true data dependencies between loop iterations, they can be easily parallelized. This paper describes Clava AutoPar, a library for the Clava weaver that performs automatic and symbolic parallelization of C code. The library is composed of two main parts, parallel loop detection and source-to-source code parallelization. The system is entirely automatic and attempts to statically detect parallel loops for a given input program, without any user intervention or profiling information. We obtained a geometric mean speedup of 1.5 for a set of programs from the C version of the NAS benchmark, and experimental results suggest that the performance obtained with Clava AutoPar is comparable or better than other similar research and commercial tools.

Abstract
This paper presents the concept of a tapered deep neural network, subject to unsupervised training layer by layer, under a criterion of maximum entropy, to perform the estimation of breaker status in the absence of a specific sensor signal. The almost perfect prediction power of the model confirms the conjecture that the knowledge of the topology of a network is hidden in the electric measurement values in the network. A test case is presented with computing speed accelerated by using a GPU (graphics processing unit). The comparison with a previous model illustrates the superiority of the novel approach. © 2018 IEEE.