The 2013-16 Ebola virus disease outbreak in west Africa was associated with unprecedented challenges in the provision of care to patients with Ebola virus disease, including absence of pre-existing isolation and treatment facilities, patients' reluctance to present for medical care, and limitations in the provision of supportive medical care. Case fatality rates in west Africa were initially greater than 70%, but decreased with improvements in supportive care. To inform optimal care in a future outbreak of Ebola virus disease, we employed the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology to develop evidence-based guidelines for the delivery of supportive care to patients admitted to Ebola treatment units. Key recommendations include administration of oral and, as necessary, intravenous hydration; systematic monitoring of vital signs and volume status; availability of key biochemical testing; adequate staffing ratios; and availability of analgesics, including opioids, for pain relief.

Diabetes mellitus (DM) is a metabolic disorder characterized by blood glucose levels above normal limits. The impact of this disease on the population has increased in recent years. It is already a public health problem worldwide and one of the leading causes of death. Recently, several proposals have been developed for better and regular monitoring of glucose. However, theses proposals do not discard erroneous readings and they are not able to anticipate a critical condition. In this work, we propose an algorithm based on the double moving average supported by an IoT architecture to prevent possible complications in elderly patients. The algorithm uses historical readings to construct a series. Given a number of periods, it is possible to calculate averages of different subsets and trends for the next periods and, in this way, the prognosis is obtained. With the prognosis, it is possible to notify the doctor and relatives in advance about a possible critical condition in the patient. The aim of our work is to validate the architecture and prognosis algorithm used for elderly persons. Tests of the algorithm and the architecture were performed with different readings and it was shown that the system generated corresponding notifications before the glucose values were higher than those defined by the WHO (World Health Organization), thus avoiding unnecessary alarms.

Hybrid MIMO communication systems are defined as a combination of architectures designed to achieve both multiplexing gain (such as VBLAST), and diversity gain, (such as STBC) such that transmission schemes that have both high spectral efficiency and link reliability can be developed. In this paper we introduce a new way to represent hybrid systems, in which the detection process is carried out in a unified manner for both spatial and diversity transmitted symbols, using an OSIC algorithm, but symbol by symbol, just as single VBLAST systems performs. In this paper we present an efficient and low-complexity, ordered, successive interference cancellation receiver based on sorted QR decomposition for the hybrid STBC-VBLAST transmission scheme. We show how the use of our detection scheme proposal outperforms other recent hybrid detection schemes in terms of bit error rate, even when there is precoding at the transmitter. We also show our proposal has lower complexity, achieved by exploiting the structure of the linear dispersion matrices. 1

In this work we propose a very low complexity OSIC detector based on Sorted QR decomposition (SQRD) for signal detection in hybrid STBC-VBLAST systems where the number of receive antennas is at least equal to the number of transmit layers. The proposed detector reduces the complexity by at least 50% compared with the conventional SQRD algorithm, and uses Givens Rotations implemented using CORDIC to calculate the QR decomposition. We show how the proposed detection scheme outperforms other recent detection schemes for STBC-VBLAST systems in terms of bit error rate and required complexity. 1

This paper presents a proposal for an architecture in FPGA for the implementation of a low complexity near maximum likelihood (Near-ML) detection algorithm for a multiple input-multiple output (MIMO) quadrature spatial modulation (QSM) transmission system. The proposed low complexity detection algorithm is based on a tree search and a spherical detection strategy. Our proposal was verified in the context of a MIMO receiver. The effects of the finite length arithmetic and limited precision were evaluated in terms of their impact on the receiver bit error rate (BER). We defined the minimum fixed point word size required not to impact performance adversely for n T transmit antennas and n R receive antennas. The results showed that the proposal performed very near to optimal with the advantage of a meaningful reduction in the complexity of the receiver. The performance analysis of the proposed detector of the MIMO receiver under these conditions showed a strong robustness on the numerical precision, which allowed having a receiver performance very close to that obtained with floating point arithmetic in terms of BER; therefore, we believe this architecture can be an attractive candidate for its implementation in current communications standards.