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Frequently carrying high loads and performing repetitive tasks compromises the ergonomics of individuals, a recurrent scenario in hospital environments. In this paper, we design a logistic planner of a fleet of autonomous mobile robots for the automation of transporting trolleys around the hospital, which is independent of the space configuration, and robust to loss of network and deadlocks. Our robotic solution has an innovative gripping system capable of grasping and pulling non-modified standard trolleys just by coupling a plate. Robots are able to navigate autonomously, to avoid obstacles assuring the safety of operators, to identify and dock a trolley, to access charging stations and elevators, and to communicate with the latter. An interface was built allowing users to command the robots through a web server. It is shown how the proposed methodology behaves in experiments conducted at the Faculty of Engineering of the University of Porto and Braga's Hospital.

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The task of Sentence Compression aims at producing a shorter version of a given sentence. This task may assist many other applications, as Automatic Summarization and Text Simplification. In this paper, we investigate methods for Sentence Compression for Portuguese. We focus on machine learning-based algorithms and propose new strategies. We also create reference corpora/datasets for the area, allowing to train and to test the methods of interest. Our results show that some of our methods outperform previous initiatives for Portuguese and produce competitive results with a state of the art method in the area.

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Abstract
High Level Synthesis (HLS) tools targeting Field Programmable Gate Arrays (FPGAs) aim to provide a method for programming these devices via high-level abstractions. Initially, HLS support for FPGAs focused on compiling C/C CC to hardware circuits. This raised the issue of determining the programming practices which resulted in the best performing circuits. Recently, to further increase the applicability of HLS approaches, renewed effort was placed on support for HLS of OpenCL code for FPGA, raising the same issues of coding practices and performance portability. This paper explores the performance of OpenCL code compiled for FPGAs for different coding techniques. We evaluate the use of task-kernels versus NDRange kernels, data vectorization, the use of on-chip local memories, and data transfer optimizations by exploiting burst access inference. We present this exploration via a case study of the k-means algorithm, and produce a total of 10 OpenCL implementations of the kernel. To determine the effects of different data set characteristics, and to determine the gains from specialization based on number of attributes, we generated a total of 12 integer data sets. The data sets vary regarding the number of instances, number of attributes (i.e., features), and number of clusters. We also vary the number of processing cores, and present the resulting required resources and operating frequencies. Finally, we execute the same OpenCL code on a 4 GHz Intel i7-6700K CPU, showing that the FPGA achieves speedups up to 1.54 x for four cases, and energy savings up to 80% in all cases.

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Objectives: The purpose of this study was to investigate whether propagation velocities of naturally occurring shear waves (SWs) at mitral valve closure (MVC) increase with the degree of diffuse myocardial injury (DMI) and with invasively determined LV filling pressures as a reflection of an increase in myocardial stiffness in heart transplantation (HTx) recipients. Background: After orthotopic HTx, allografts undergo DMI that contributes to functional impairment, especially to increased passive myocardial stiffness, which is an important pathophysiological determinant of left ventricular (LV) diastolic dysfunction. Echocardiographic SW elastography is an emerging approach for measuring myocardial stiffness in vivo. Natural SWs occur after mechanical excitation of the myocardium, for example, after MVC, and their propagation velocity is directly related to myocardial stiffness, thus providing an opportunity to assess myocardial stiffness at end-diastole. Methods: A total of 52 HTx recipients who underwent right heart catheterization (all) and cardiac magnetic resonance (CMR) (n = 23) during their annual check-up were prospectively enrolled. Echocardiographic SW elastography was performed in parasternal long axis views of the LV using an experimental scanner at 1,135 ± 270 frames per second. The degree of DMI was quantified with T1 mapping. Results: SW velocity at MVC correlated best with native myocardial T1 values (r = 0.75; p < 0.0001) and was the best noninvasive parameter that correlated with pulmonary capillary wedge pressures (PCWP) (r = 0.54; p < 0.001). Standard echocardiographic parameters of LV diastolic function correlated poorly with both native T1 and PCWP values. Conclusions: End-diastolic SW propagation velocities, as measure of myocardial stiffness, showed a good correlation with CMR-defined diffuse myocardial injury and with invasively determined LV filling pressures in patients with HTx. Thus, these findings suggest that SW elastography has the potential to become a valuable noninvasive method for the assessment of diastolic myocardial properties in HTx recipients. © 2020 American College of Cardiology Foundation

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