Reionization history constraints from neural network based predictions of high-redshift quasar continua

Observations of the early Universe suggest that reionization was complete by $z\sim6$, however, the exact history of this process is still unknown. One method for measuring the evolution of the neutral fraction throughout this epoch is via observing the Ly$\alpha$ damping wings of high-redshift quasars. In order to constrain the neutral fraction from quasar observations, one needs an accurate model of the quasar spectrum around Ly$\alpha$, after the spectrum has been processed by its host galaxy but before it is altered by absorption and damping in the intervening IGM. In this paper, we present a novel machine learning approach, using artificial neural networks, to reconstruct quasar continua around Ly$\alpha$. Our QSANNdRA algorithm improves the error in this reconstruction compared to the state-of-the-art PCA-based model in the literature by 14.2% on average, and provides an improvement of 6.1% on average when compared to an extension thereof. In comparison with the extended PCA model, QSANNdRA further achieves an improvement of 22.1% and 16.8% when evaluated on low-redshift quasars most similar to the two high-redshift quasars under consideration, ULAS J1120+0641 at $z=7.0851$ and ULAS J1342+0928 at $z=7.5413$, respectively. Using our more accurate reconstructions of these two $z>7$ quasars, we estimate the neutral fraction of the IGM using a homogeneous reionization model and find $\bar{x}_\mathrm{HI} = 0.25^{+0.05}_{-0.05}$ at $z=7.0851$ and $\bar{x}_\mathrm{HI} = 0.60^{+0.11}_{-0.11}$ at $z=7.5413$. Our results are consistent with the literature and favour a rapid end to reionization

Functional consequences of sphingomyelinase-induced changes in erythrocyte membrane structure.

Inflammation enhances the secretion of sphingomyelinases (SMases). SMases catalyze the hydrolysis of sphingomyelin into phosphocholine and ceramide. In erythrocytes, ceramide formation leads to exposure of the removal signal phosphatidylserine (PS), creating a potential link between SMase activity and anemia of inflammation. Therefore, we studied the effects of SMase on various pathophysiologically relevant parameters of erythrocyte homeostasis. Time-lapse confocal microscopy revealed a SMase-induced transition from the discoid to a spherical shape, followed by PS exposure, and finally loss of cytoplasmic content. Also, SMase treatment resulted in ceramide-associated alterations in membrane-cytoskeleton interactions and membrane organization, including microdomain formation. Furthermore, we observed increases in membrane fragility, vesiculation and invagination, and large protein clusters. These changes were associated with enhanced erythrocyte retention in a spleen-mimicking model. Erythrocyte storage under blood bank conditions and during physiological aging increased the sensitivity to SMase. A low SMase activity already induced morphological and structural changes, demonstrating the potential of SMase to disturb erythrocyte homeostasis. Our analyses provide a comprehensive picture in which ceramide-induced changes in membrane microdomain organization disrupt the membrane-cytoskeleton interaction and membrane integrity, leading to vesiculation, reduced deformability, and finally loss of erythrocyte content. Understanding these processes is highly relevant for understanding anemia during chronic inflammation, especially in critically ill patients receiving blood transfusions

Temporal True and Surrogate Fitness Landscape Analysis for Expensive Bi-Objective Optimisation

Many real-world problems have expensive-to-compute fitness functions and are multi-objective in nature. Surrogate-assisted evolutionary algorithms are often used to tackle such problems. Despite this, literature about analysing the fitness landscapes induced by surrogate models is limited, and even non-existent for multi-objective problems. This study addresses this critical gap by comparing landscapes of the true fitness function with those of surrogate models for multi-objective functions. Moreover, it does so temporally by examining landscape features at different points in time during optimisation, in the vicinity of the population at that point in time. We consider the BBOB bi-objective benchmark functions in our experiments. The results of the fitness landscape analysis reveals significant differences between true and surrogate features at different time points during optimisation. Despite these differences, the true and surrogate landscape features still show high correlations between each other. Furthermore, this study identifies which landscape features are related to search and demonstrates that both surrogate and true landscape features are capable of predicting algorithm performance. These findings indicate that temporal analysis of the landscape features may help to facilitate the design of surrogate switching approaches to improve performance in multi-objective optimisation

Dual role of DNA methylation inside and outside of CTCF-binding regions in the transcriptional regulation of the telomerase hTERT gene

Expression of hTERT is the major limiting factor for telomerase activity. We previously showed that methylation of the hTERT promoter is necessary for its transcription and that CTCF can repress hTERT transcription by binding to the first exon. In this study, we used electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation (ChIP) to show that CTCF does not bind the methylated first exon of hTERT. Treatment of telomerase-positive cells with 5-azadC led to a strong demethylation of hTERT 5′-regulatory region, reactivation of CTCF binding and downregulation of hTERT. Although complete hTERT promoter methylation was associated with full transcriptional repression, detailed mapping showed that, in telomerase-positive cells, not all the CpG sites were methylated, especially in the promoter region. Using a methylation cassette assay, selective demethylation of 110 bp within the core promoter significantly increased hTERT transcriptional activity. This study underlines the dual role of DNA methylation in hTERT transcriptional regulation. In our model, hTERT methylation prevents binding of the CTCF repressor, but partial hypomethylation of the core promoter is necessary for hTERT expression

Investigating Real-World Benefits of High-Frequency Gain in Bone-Anchored Users with Ecological Momentary Assessment and Real-Time Data Logging

Purpose: To compare listening ability (speech reception thresholds) and real-life listening experience in users with a percutaneous bone conduction device (BCD) with two listening programs differing only in high-frequency gain. In situ real-life experiences were recorded with ecological momentary assessment (EMA) techniques combined with real-time acoustical data logging and standard retrospective questionnaires. Methods: Nineteen experienced BCD users participated in this study. They all used a Ponto 4 BCD from Oticon Medical during a 4-week trial period. Environmental data and device parameters (i.e., device usage and volume control) were logged in real-time on an iPhone via a custom iOS research app. At the end of the trial period, subjects filled in APHAB, SSQ, and preference questionnaires. Listening abilities with the two programs were evaluated with speech reception threshold tests. Results: The APHAB and SSQ questionnaires did not reveal any differences between the two listening programs. The EMAs revealed group-level effects, indicating that in speech and noisy listening environments, subjects preferred the default listening program, and found the program with additional high-frequency gain too loud. This finding was corroborated by the volume log—subjects avoided the higher volume control setting and reacted more to changes in environmental sound pressure levels when using the high-frequency gain program. Finally, day-to-day changes in EMAs revealed acclimatization effects in the listening experience for ratings of “sound quality” and “program suitability” of the BCD, but not for ratings of “loudness perception” and “speech understanding”. The acclimatization effect did not differ among the listening programs. Conclusion: Adding custom high-frequency amplification to the BCD target-gain prescription improves speech reception in laboratory tests under quiet conditions, but results in poorer real-life listening experiences due to loudness

Uncorking the potential of wine language for young wine tourists

Effective communication with consumers underpins growth in wine knowledge that, in turn, contributes to growth in wine consumption. Indeed, tasting notes may enhance consumers’ experiences of wine. Yet wine language is full of fuzzy concepts. In this chapter, we consider the language used to talk about wine, specifically the humanlike features of wine (e.g., wine is described as honest, sexy, shy, or brooding). We demonstrate that metaphoric language is integral to the experience of wine and influences consumer behaviour. We discuss practical implications for the cellar door experience, and for effective and ethical wine communication. We conclude that metaphoric language is a pedagogical and cultural platform for engaging younger wine tourists in the cellar door experience, which is a significant revenue source for micro, small, and medium wineries

The development of a glucose prediction model in critically ill patients

Purpose: The aim of the current study is to develop a prediction model for glucose levels applicable for all patients admitted to the ICU with an expected ICU stay of at least 24 h. This model will be incorporated in a closed-loop glucose system to continuously and automatically control glucose values. Methods: Data from a previous single-center randomized controlled study was used. All patients received a FreeStyle Navigator II subcutaneous CGM system from Abbott during their ICU stay. The total dataset was randomly divided into a training set and a validation set. A glucose prediction model was developed based on historical glucose data. Accuracy of the prediction model was determined using the Mean Squared Difference (MSD), the Mean Absolute Difference (MAD) and a Clarke Error Grid (CEG). Results: The dataset included 94 ICU patients with a total of 134,673 glucose measurements points that were used for modelling. MSD was 0.410 +/- 0.495 for the model, the MAD was 5.19 +/- 2.63 and in the CEG 99.8% of the data points were in the clinically acceptable regions. Conclusion: In this study a glucose prediction model for ICU patients is developed. This study shows that it is possible to accurately predict a patient's glucose 30 min ahead based on historical glucose data. This is the first step in the development of a closed-loop glucose system. (C) 2021 Elsevier B.V. All rights reserved