Holography is arguably the most promising technology to provide wide field-of-view compact eyeglasses-style near-eye displays for augmented and virtual reality. However, the image quality of existing holographic displays is far from that of current generation conventional displays, effectively making today's holographic display systems impractical. This gap stems predominantly from the severe deviations in the idealized approximations of the "unknown" light transport model in a real holographic display, used for computing holograms. In this work, we depart from such approximate "ideal" coherent light transport models for computing holograms. Instead, we learn the deviations of the real display from the ideal light transport from the images measured using a display-camera hardware system. After this unknown light propagation is learned, we use it to compensate for severe aberrations in real holographic imagery. The proposed hardware-in-the-loop approach is robust to spatial, temporal and hardware deviations, and improves the image quality of existing methods qualitatively and quantitatively in SNR and perceptual quality. We validate our approach on a holographic display prototype and show that the method can fully compensate unknown aberrations and erroneous and non-linear SLM phase delays, without explicitly modeling them. As a result, the proposed method significantly outperforms existing state-of-the-art methods in simulation and experimentation - just by observing captured holographic images.

Neonates are at increased risk of infections compared to adults. To dissect the mechanisms that contribute to neonatal immune deficiency, we compared MHC-II antigen processing and presentation by monocytes from umbilical cord blood and unrelated adult controls. Antigen-specific, co-stimulation-independent murine T hybridoma cells were used to detect peptide:HLA-DR complexes. Relative to adult monocytes, neonatal monocytes were significantly defective in processing and presentation of protein antigens and presentation of exogenous peptide. Defects in responses to protein antigens and exogenous peptide were of similar magnitude (56-81% decrease), indicating that the defect lies in antigen presentation as opposed to intracellular antigen processing. Average surface MHC-II levels on neonatal monocytes were 38% less than on adult monocytes. However, there was no correlation between decreased MHC-II expression on individual neonatal monocyte samples and reduced T cell responses. We demonstrate for the first time that neonatal monocytes are defective in MHC-II antigen presentation by a mechanism not correlated with decreased MHC-II expression.

Introduction: A discussion of 'waves' of the COVID-19 epidemic in different countries is a part of the national conversation for many, but there is no hard and fast means of delineating these waves in the available data and their connection to waves in the sense of mathematical epidemiology is only tenuous. Methods: We present an algorithm which processes a general time series to identify substantial, significant and sustained periods of increase in the value of the time series, which could reasonably be described as 'observed waves'. This provides an objective means of describing observed waves in time series. Results: The output of the algorithm as applied to epidemiological time series related to COVID-19 corresponds to visual intuition and expert opinion. Inspecting the results of individual countries shows how consecutive observed waves can differ greatly with respect to the case fatality ratio. Furthermore, in large countries, a more detailed analysis shows that consecutive observed waves have different geographical ranges. We also show how waves can be modulated by government interventions and find that early implementation of non-pharmaceutical interventions correlates with a reduced number of observed waves and reduced mortality burden in those waves. Conclusion: It is possible to identify observed waves of disease by algorithmic methods and the results can be fruitfully used to analyse the progression of the epidemic.

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