Ultra-high-cardinality geometric shaping in the finite SNR regime.

Four-dimensional (4D) constellations with up to 131 072 points (17 bit/4D-sym) are designed for the first time using geometric shaping. The constellations are optimized in terms of mutual information (MI) and generalized MI (GMI) for the additive white Gaussian noise (AWGN) channel, targeting a forward error correction (FEC) rate of 0.8 at finite signal-to-noise ratios. The presented 15-17 bit constellations are currently the highest-performing constellations in the literature, having a gap to the AWGN capacity as low as 0.17 dB (MI) and 0.45 dB (GMI) at 17 bit/4D-sym. For lower cardinalities, our constellations match or closely approach the performance of previously published optimized constellations. We also show that (GMI-)optimized constellations with a symmetry constraint, optimized for a FEC rate of 0.8, perform nearly identical to their unconstrained counterparts for cardinalities above 8 bit/4D-sym. A symmetry constraint for MI-optimized constellations is shown to have a negative impact in general. The proposed procedure relies on a Monte-Carlo-based approach for evaluating performance and is extendable to other (nonlinear) channels. Stochastic gradient descent is used for the optimization algorithm for which the gradients are computed using automatic differentiation. This article is part of the theme issue 'Celebrating the 15th anniversary of the Royal Society Newton International Fellowship'.

Can lactate levels and lactate kinetics predict mortality in patients with COVID-19 with using qCSI scoring system?

INTRODUCTION: In this study, we aimed to investigate the relationship between blood lactate levels and lactate kinetics (lactate clearance and Δ lactate) for predicting mortality in patients with COVID-19 admitted to the emergency department. METHODS: This study was performed as a retrospective study that included patients admitted to the emergency department between March 1st, 2020, and January 1st, 2022. Lactate levels were recorded at the first admission (0 h lactate) and the highest blood lactate levels in the first 24 h of follow-up (2nd highest lactate). Lactate kinetics were calculated. Clinical severity was determined according to the quick COVID Severity Index (qCSI). RESULTS: 300 patients were included in the study. Lactate levels at admission were similar in groups with or without mortality, but 2nd highest lactate levels were found to be significantly higher in the group with mortality (p < 0.001). Lactate clearance and ∆ lactate levels were also found to be lower in the mortality group (p < 0.001). Lactate kinetics in patients in the clinically low severity group were lower in the mortality group (p = 0.02 and p = 0.039, respectively). In the low-intermediate and high-intermediate groups, 0-h lactate and 2nd highest lactate levels were found to be higher in the mortality group, and lactate kinetics were similar in the groups with and without mortality. In the group with high clinical severity, 2nd highest lactate levels were found to be higher in the group with mortality (p = 0.010). Lactate kinetics were also found to be significantly lower in the mortality group (p < 0.001). In the high qCSI group, based on ROC analysis, the AUC for 2nd highest lactate levels predicting mortality was 0.642 (95% CI: 0.548-0.728). The optimal cut-off value for mortality was greater than >2.4 mmol/L (60.6% sensitivity, 67.4% specificity). The AUC for lactate clearance was 0.748 (95% CI: 0.659-0.824). The lactate clearance cut-off value was ≤ -177.78% (49.3% sensitivity, 100% specificity). The AUC for ∆ lactate was 0.707 (95% CI: 0.616-0.787). The optimal ∆ lactate cut-off was ≤ -2 mmol/L (45.1% sensitivity, 93.5% specificity). CONCLUSION: In COVID-19, 2nd highest blood lactate and lactate kinetics were found to be prognostic indicators of the disease. High 2nd highest lactate levels and low lactate kinetics in patients with high clinical severity were guiding physicians regarding the outcome of the disease.

Supranutritional Maternal Organic Selenium Supplementation during Different Trimesters of Pregnancy Affects the Muscle Gene Transcriptome of Newborn Beef Calves in a Time-Dependent Manner.

Selenium (Se) is an essential micronutrient for growth and immune function in beef cattle. We previously showed that supranutritional maternal organic Se supplementation during late pregnancy improves immune function in their newborn calves; however, the effects of maternal organic Se-supplementation on fetal programming during different pregnancy stages have yet to be elucidated. Herein, we investigated the effects of supranutritional maternal organic Se-supplementation in different pregnancy trimesters on their beef calf's genome-wide transcriptome profiles. Within 12 to 48 h of birth, whole blood and Longissimus dorsi (LD) muscle biopsies were collected from calves born to 40 crossbred Angus cows that received, except for the control group (CTR), Se-yeast boluses (105 mg of Se/wk) during the first (TR1), second (TR2), or third (TR3) trimester of gestation. Whole-blood Se concentrations of newborn calves increased from CTR, TR1, TR2 to TR3, whereas muscle Se concentrations of newborn calves were only increased in TR3 group. We identified 3048 unique differentially expressed genes (DEGs) across all group comparisons (FDR ≤ 0.05 and |log2FC| ≥ 1.5). Furthermore, we predicted 237 unique transcription factors that putatively regulate the DEGs. Independent of supplementation trimester, supranutritional maternal organic Se supplementation downregulated genes involved in adaptive immunity in all trimesters. Dependent on supplementation trimester, genes involved in muscle development were upregulated by TR3 Se supplementation and downregulated by TR1 Se-supplementation, and genes involved in collagen formation were downregulated by TR2 Se-supplementation. Supranutritional maternal organic Se supplementation in the last trimester of pregnancy resulted in upregulation of myosin and actin filament associated genes, potentially allowing for optimal muscle function and contraction. Our findings suggest a beneficial effect of supranutritional maternal organic Se supplementation during late gestation on Se-status and muscle development and function of newborn calves.

Probabilistic Shaping for Finite Blocklengths: Distribution Matching and Sphere Shaping.

In this paper, we provide a systematic comparison of distribution matching (DM) and sphere shaping (SpSh) algorithms for short blocklength probabilistic amplitude shaping. For asymptotically large blocklengths, constant composition distribution matching (CCDM) is known to generate the target capacity-achieving distribution. However, as the blocklength decreases, the resulting rate loss diminishes the efficiency of CCDM. We claim that for such short blocklengths over the additive white Gaussian noise (AWGN) channel, the objective of shaping should be reformulated as obtaining the most energy-efficient signal space for a given rate (rather than matching distributions). In light of this interpretation, multiset-partition DM (MPDM) and SpSh are reviewed as energy-efficient shaping techniques. Numerical results show that both have smaller rate losses than CCDM. SpSh-whose sole objective is to maximize the energy efficiency-is shown to have the minimum rate loss amongst all, which is particularly apparent for ultra short blocklengths. We provide simulation results of the end-to-end decoding performance showing that up to 1 dB improvement in power efficiency over uniform signaling can be obtained with MPDM and SpSh at blocklengths around 200. Finally, we present a discussion on the complexity of these algorithms from the perspectives of latency, storage and computations.

Achievable Information Rates for Probabilistic Amplitude Shaping: An Alternative Approach via Random Sign-Coding Arguments.

Probabilistic amplitude shaping (PAS) is a coded modulation strategy in which constellation shaping and channel coding are combined. PAS has attracted considerable attention in both wireless and optical communications. Achievable information rates (AIRs) of PAS have been investigated in the literature using Gallager's error exponent approach. In particular, it has been shown that PAS achieves the capacity of the additive white Gaussian noise channel (Böcherer, 2018). In this work, we revisit the capacity-achieving property of PAS and derive AIRs using weak typicality. Our objective is to provide alternative proofs based on random sign-coding arguments that are as constructive as possible. Accordingly, in our proofs, only some signs of the channel inputs are drawn from a random code, while the remaining signs and amplitudes are produced constructively. We consider both symbol-metric and bit-metric decoding.