Return to sports after COVID-19: a position paper from the Dutch Sports Cardiology Section of the Netherlands Society of Cardiology

The coronavirus disease 2019 (COVID-19) pandemic has led to preventive measures worldwide. With the decline of infection rates, less stringent restrictions for sports and exercise are being implemented. COVID-19 is associated with significant cardiovascular complications; however there are limited data on cardiovascular complications and long-term outcomes in both competitive (elite) athletes and highly active individuals. Based on different categories of disease severity (asymptomatic, regional/systemic symptoms, hospitalisation, myocardial damage, and/or myocarditis), in this point-of-view article we offer the (sports) cardiologist or sports physician in the Netherlands a practical guide to pre-participation screening, and diagnostic and management strategies in all athletes >16 years of age after COVID-19 infection

Partial enumerative sphere shaping

The dependency between the Gaussianity of the input distribution for the additive white Gaussian noise (AWGN) channel and the gap-to-capacity is discussed. We show that a set of particular approximations to the Maxwell- Boltzmann (MB) distribution virtually closes most of the shaping gap. We relate these symbol-level distributions to bit-level distributions, and demonstrate that they correspond to keeping some of the amplitude bit-levels uniform and independent of the others. Then we propose partial enumerative sphere shaping (P-ESS) to realize such distributions in the probabilistic amplitude shaping (PAS) framework. Simulations over the AWGN channel exhibit that shaping 2 amplitude bits of 16-ASK have almost the same performance as shaping 3 bits, which is 1.3 dB more power- efficient than uniform signaling at a rate of 3 bit/symbol. In this way, required storage and computational complexity of shaping are reduced by factors of 6 and 3, respectively.</p

Enumerative sphere shaping for wireless communications with short packets

Probabilistic amplitude shaping (PAS) combines an outer shaping layer with an inner, systematic forward error correction (FEC) layer to close the shaping gap. Proposed for PAS, constant composition distribution matching (CCDM) produces amplitude sequences with a fixed empirical distribution. We show that CCDM suffers from high rate losses for small block lengths, and we propose to use Enumerative Sphere Shaping (ESS) instead. ESS minimizes the rate loss at any block length. Furthermore, we discuss the computational complexity of ESS and demonstrate that it is significantly smaller than shell mapping (SM), which is another method to perform sphere shaping. We then study the choice of design parameters for PAS. Following Wachsmann et al., we show that for a given constellation and target rate, there is an optimum balance between the FEC code rate and the entropy of the Maxwell-Boltzmann distribution that minimizes the gap-to-capacity. Moreover, we demonstrate how to utilize the non-systematic convolutional code from IEEE 802.11 in PAS. Simulations over the additive white Gaussian noise (AWGN) and frequency-selective channels exhibit that ESS is up to 1.6 and 0.7 dB more energy-efficient than uniform signaling at block lengths as small as 96 symbols, respectively, with convolutional and low-density parity-check (LDPC) codes

Enumerative sphere shaping for wireless communications with short packets

Probabilistic amplitude shaping (PAS) combines an outer shaping layer with an inner, systematic forward error correction (FEC) layer to close the shaping gap. Proposed for PAS, constant composition distribution matching (CCDM) produces amplitude sequences with a fixed empirical distribution. We show that CCDM suffers from high rate losses for small block lengths, and we propose to use Enumerative Sphere Shaping (ESS) instead. ESS minimizes the rate loss at any block length. Furthermore, we discuss the computational complexity of ESS and demonstrate that it is significantly smaller than shell mapping (SM), which is another method to perform sphere shaping. We then study the choice of design parameters for PAS. Following Wachsmann et al., we show that for a given constellation and target rate, there is an optimum balance between the FEC code rate and the entropy of the Maxwell-Boltzmann distribution that minimizes the gap-to-capacity. Moreover, we demonstrate how to utilize the non-systematic convolutional code from IEEE 802.11 in PAS. Simulations over the additive white Gaussian noise (AWGN) and frequency-selective channels exhibit that ESS is up to 1.6 and 0.7 dB more energy-efficient than uniform signaling at block lengths as small as 96 symbols, respectively, with convolutional and low-density parity-check (LDPC) codes

Control of automotive waste heat recovery systems with parallel evaporators

In this paper, Model Predictive Control (MPC) is applied to control a Waste Heat Recovery system for a highly dynamic automotive application. As a benchmark, a commonly applied control strategy is used that consists of a feedforward based on engine conditions and of two PI controllers that individually control the post-EGR and post-exhaust evaporator temperature. By controlling the temperatures, this strategy deals with the constraints on working fluid temperature and aims to guarantee vapor state at the evaporator outlet. To design the local PI controllers, a frequency domain based loop shaping method is applied. Using a high-fidelity Waste Heat Recovery system model, the performance of the MPC and PI controller is compared in simulations over a World Harmonized Transient Cycle for both cold-start and hot-start conditions. Due to the availability of a model and knowledge of the engine disturbance, the MPC strategy is shown to outperform the reference PI controller, it gives higher energy recovery and guarantees operation within safety margins with respect to physical capabilities of the plant

Low-complexity Enumerative Coding Techniques with Applications to Amplitude Shaping

Practical implementation of enumerative sphere shaping (ESS) is considered. First, an on-the-fly computation method is proposed such that the required storage is significantly decreased, e.g., by a factor of 7 for 8-ary amplitude-shift keying (ASK) at blocklength N = 64 and shaping rate of 1.75 bit/amplitude. Then a sliding window shaping (SWS) architecture is introduced to eliminate the necessity to realize high precision arithmetic operations, and to decrease the computational complexity of ESS. The SWS procedure only requires three 16-bit arithmetic operations per output symbol for 8-ASK

Survival and emigration rates in Kentish Charadrius alexandrinus ans Ringed Plovers Ch. hiaticula in the Delta area, SW-Netherlands.

Ringed Plover Charadrius hiaticula and Kentish Plover Charadrius alexandrinus are typical species of the Delta area, southwest Netherlands. A major part of the Dutch population of both species occurs in this area. Between 1999 and 2002 the breeding populations in the Dutch Delta were studied. One of the aims of the study was to estimate survival, emigration and dispersal rates and to explain variation therein. To estimate annual apparent survival rates we used mark-recapture analyses (program MARK) of the resighting histories of colour ringed individuals. The best survival model of Ringed Plover showed an age (first years against adults) and year effect. Apparent survival in the last year of study was much lower than in previous years. Also juvenile survival of Kentish Plover was considerably (40%) lower than adult survival. Furthermore, two year old females had a lower survival rate than older females. In the first year after marking the apparent survival of females was 40% lower than in later years. Kentish Plovers that were unsuccessful in breeding were more prone to disperse the year after. Generally, breeding dispersal in both species was restricted to short distances (media

Development of a Matlab/Simulink Tool to Facilitate System Analysis and Simulation via the Adjoint and Covariance Methods

The COVariance and ADjoint Analysis Tool (COVAD) is a specially designed software tool, written for the Matlab/Simulink environment, which allows the user the capability to carry out system analysis and simulation using the adjoint, covariance or Monte Carlo methods. This paper describes phase one of the COVAD evolution, which includes a user-friendly and flexible Graphical User Interface (GUI), a missile homing loop template, an adjoint construction module, a Monte Carlo simulation module and various analysis and plotting options. As an illustration, the application of the software to the preliminary analysis of a generic guided missile homing loop problem is included. The covariance analysis module is still under construction and will not be covered here. It is scheduled to appear in phase two of the COVAD development