Naval Research Laboratory Information Technology Division

The genetics underlying severe COVID-19 The immune system is complex and involves many genes, including those that encode cytokines known as interferons (IFNs). Individuals that lack specific IFNs can be more susceptible to infectious diseases. Furthermore, the autoantibody system dampens IFN response to prevent damage from pathogen-induced inflammation. Two studies now examine the likelihood that genetics affects the risk of severe coronavirus disease 2019 (COVID-19) through components of this system (see the Perspective by Beck and Aksentijevich). Q. Zhang et al. used a candidate gene approach and identified patients with severe COVID-19 who have mutations in genes involved in the regulation of type I and III IFN immunity. They found enrichment of these genes in patients and conclude that genetics may determine the clinical course of the infection. Bastard et al. identified individuals with high titers of neutralizing autoantibodies against type I IFN-α2 and IFN-ω in about 10% of patients with severe COVID-19 pneumonia. These autoantibodies were not found either in infected people who were asymptomatic or had milder phenotype or in healthy individuals. Together, these studies identify a means by which individuals at highest risk of life-threatening COVID-19 can be identified. Science , this issue p. eabd4570 , p. eabd4585 ; see also p. 404

The genetics underlying severe COVID-19 The immune system is complex and involves many genes, including those that encode cytokines known as interferons (IFNs). Individuals that lack specific IFNs can be more susceptible to infectious diseases. Furthermore, the autoantibody system dampens IFN response to prevent damage from pathogen-induced inflammation. Two studies now examine the likelihood that genetics affects the risk of severe coronavirus disease 2019 (COVID-19) through components of this system (see the Perspective by Beck and Aksentijevich). Q. Zhang et al. used a candidate gene approach and identified patients with severe COVID-19 who have mutations in genes involved in the regulation of type I and III IFN immunity. They found enrichment of these genes in patients and conclude that genetics may determine the clinical course of the infection. Bastard et al. identified individuals with high titers of neutralizing autoantibodies against type I IFN-α2 and IFN-ω in about 10% of patients with severe COVID-19 pneumonia. These autoantibodies were not found either in infected people who were asymptomatic or had milder phenotype or in healthy individuals. Together, these studies identify a means by which individuals at highest risk of life-threatening COVID-19 can be identified. Science , this issue p. eabd4570 , p. eabd4585 ; see also p. 404

BACKGROUND: DNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age. RESULTS: Here we test whether differences between people's chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age (Δage) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between Δage and mortality. A 5-year higher Δage is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher Δage. A pedigree-based heritability analysis of Δage was conducted in a separate cohort. The heritability of Δage was 0.43. CONCLUSIONS: DNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors.

Onion routing is an infrastructure for private communication over a public network. It provides anonymous connections that are strongly resistant to both eavesdropping and traffic analysis. Onion routing's anonymous connections are bidirectional, near real-time, and can be used anywhere a socket connection can be used. Any identifying information must be in the data stream carried over an anonymous connection. An onion is a data structure that is treated as the destination address by onion routers; thus, it is used to establish an anonymous connection. Onions themselves appear different to each onion router as well as to network observers. The same goes for data carried over the connections they establish. Proxy-aware applications, such as Web browsers and e-mail clients, require no modification to use onion routing, and do so through a series of proxies. A prototype onion routing network is running between our lab and other sites. This paper describes anonymous connections and their implementation using onion routing. This paper also describes several application proxies for onion routing, as well as configurations of onion routing networks.

We discuss the problem of counting the maximum number of distinct states that an isolated physical system can pass through in a given period of time — its maximum speed of dynamical evolution. Previous analyses have given bounds in terms of ΔE, the standard deviation of the energy of the system; here we give a strict bound that depends only on E − E0, the system's average energy minus its ground state energy. We also discuss bounds on information processing rates implied by our bound on the speed of dynamical evolution. For example, adding 1 J of energy to a given computer can never increase its processing rate by more than about 3 × 1033 operations per second.

Polychromatic flow cytometry results in complex, multivariate datasets. To date, tools for the aggregate analysis of these datasets across multiple specimens grouped by different categorical variables, such as demographic information, have not been optimized. Often, the exploration of such datasets is accomplished by visualization of patterns with pie charts or bar charts, without easy access to statistical comparisons of measurements that comprise multiple components. Here we report on algorithms and a graphical interface we developed for these purposes. In particular, we discuss thresholding necessary for accurate representation of data in pie charts, the implications for display and comparison of normalized versus unnormalized data, and the effects of averaging when samples with significant background noise are present. Finally, we define a statistic for the nonparametric comparison of complex distributions to test for difference between groups of samples based on multi-component measurements. While originally developed to support the analysis of T cell functional profiles, these techniques are amenable to a broad range of datatypes.

in volume. Furthermore, results raise important issues regarding water use in transboundary river basins and aquifers, including the necessity of international water use treaties and resolving discrepancies in international water law, while amplifying the need for increased monitoring for core components of the water budget.

Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the 'transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts.

The ethanol-producing bacterium Zymomonas mobilis was metabolically engineered to broaden its range of fermentable substrates to include the pentose sugar xylose. Two operons encoding xylose assimilation and pentose phosphate pathway enzymes were constructed and transformed into Z. mobilis in order to generate a strain that grew on xylose and efficiently fermented it to ethanol. Thus, anaerobic fermentation of a pentose sugar to ethanol was achieved through a combination of the pentose phosphate and Entner-Doudoroff pathways. Furthermore, this strain efficiently fermented both glucose and xylose, which is essential for economical conversion of lignocellulosic biomass to ethanol.

A methodologically simple approach to estimate snow depth from spaceborne microwave instruments is described. The scattering signal observed in multifrequency passive microwave data is used to detect snow cover. Wet snow, frozen ground, precipitation, and other anomalous scattering signals are screened using established methods. The results from two different approaches (a simple time and continentwide static approach and a space and time dynamic approach) to estimating snow depth were compared. The static approach, based on radiative transfer calculations, assumes a temporally constant grain size and density. The dynamic approach assumes that snowpack properties are spatially and temporally dynamic and requires two simple empirical models of density and snowpack grain radius evolution, plus a dense media radiative transfer model based on the quasicrystalline approximation and sticky particle theory. To test the approaches, a four-year record of daily snow depth measurements at 71 meteorological stations plus passive microwave data from the Special Sensor Microwave Imager, land cover data and a digital elevation model were used. In addition, testing was performed for a global dataset of over 1000 World Meteorological Organization meteorological stations recording snow depth during the 2000-2001 winter season. When compared with the snow depth data, the new algorithm had an average error of 23 cm for the one-year dataset and 21 cm for the four-year dataset (131% and 94% relative error, respectively). More importantly, the dynamic algorithm tended to underestimate the snow depth less than the static algorithm. This approach will be developed further and implemented for use with the Advanced Microwave Scanning Radiometer-Earth Observing System aboard Aqua.

Abstract A satellite-based 1° by 1° normalized difference vegetation index (NDVI) data set has been processed to derive land surface parameters for general circulation models of the atmosphere (GCMs). Prior to calculation of the land surface parameters, corrections were applied to the source NDVI data set to account for (i) obvious anomalies in the data time-series, (ii) the effect of variations in solar zenith angle, (iii) data dropouts in cold regions where a temperature threshold procedure designed to screen for clouds also eliminates cold land surface points, and (iv) persistent cloud cover in the tropics. An outline of the procedures for calculating land surface parameters from the corrected NDVI data set is given, and a brief description is provided of source material that was used in addition to the NDVI data. The data sets summarized in this paper should represent improvements over prescriptions currently used in land surface parameterizations in that the spatial and temporal dynamics of key land surface parameters, in particular of those related to vegetation, are obtained from direct measurements rather than indirectly inferred from survey-based land cover classifications.

Mice rendered deficient in interleukin-10 (IL-10) by gene targeting (IL-10(-/-) mice) develop chronic enterocolitis resembling human inflammatory bowel disease (IBD) when maintained in conventional animal facilities. However, they display a minimal and delayed intestinal inflammatory response when reared under specific-pathogen-free (SPF) conditions, suggesting the involvement of a microbial component in pathogenesis. We show here that experimental infection with a single bacterial agent, Helicobacter hepaticus, induces chronic colitis in SPF-reared IL-10(-/-) mice and that the disease is accompanied by a type 1 cytokine response (gamma interferon [IFN-gamma], tumor necrosis factor alpha, and nitric oxide) detected by restimulation of spleen and mesenteric lymph node cells with a soluble H. hepaticus antigen (Ag) preparation. In contrast, wild-type (WT) animals infected with the same bacteria did not develop disease and produced IL-10 as the dominant cytokine in response to Helicobacter Ag. Strong H. hepaticus-reactive antibody responses as measured by Ag-specific total immunoglobulin G (IgG), IgG1, IgG2a, IgG2b, IgG3, and IgA were observed in both WT and IL-10(-/-) mice. In vivo neutralization of IFN-gamma or IL-12 resulted in a significant reduction of intestinal inflammation in H. hepaticus-infected IL-10(-/-) mice, suggesting an important role for these cytokines in the development of colitis in the model. Taken together, these microbial reconstitution experiments formally establish that a defined bacterial agent can serve as the immunological target in the development of large bowel inflammation in IL-10(-/-) mice and argue that in nonimmunocompromised hosts IL-10 stimulated in response to intestinal flora is important in preventing IBD.

Launched in February 2013, the Landsat-8 carries on-board the Thermal Infrared Sensor (TIRS), a two-band thermal pushbroom imager, to maintain the thermal imaging capability of the Landsat program. The TIRS bands are centered at roughly 10.9 and 12 μm (Bands 10 and 11 respectively). They have 100 m spatial resolution and image coincidently with the Operational Land Imager (OLI), also on-board Landsat-8. The TIRS instrument has an internal calibration system consisting of a variable temperature blackbody and a special viewport with which it can see deep space; a two point calibration can be performed twice an orbit. Immediately after launch, a rigorous vicarious calibration program was started to validate the absolute calibration of the system. The two vicarious calibration teams, NASA/Jet Propulsion Laboratory (JPL) and the Rochester Institute of Technology (RIT), both make use of buoys deployed on large water bodies as the primary monitoring technique. RIT took advantage of cross-calibration opportunity soon after launch when Landsat-8 and Landsat-7 were imaging the same targets within a few minutes of each other to perform a validation of the absolute calibration. Terra MODIS is also being used for regular monitoring of the TIRS absolute calibration. The buoy initial results showed a large error in both bands, 0.29 and 0.51 W/m2·sr·μm or −2.1 K and −4.4 K at 300 K in Band 10 and 11 respectively, where TIRS data was too hot. A calibration update was recommended for both bands to correct for a bias error and was implemented on 3 February 2014 in the USGS/EROS processing system, but the residual variability is still larger than desired for both bands (0.12 and 0.2 W/m2·sr·μm or 0.87 and 1.67 K at 300 K). Additional work has uncovered the source of the calibration error: out-of-field stray light. While analysis continues to characterize the stray light contribution, the vicarious calibration work proceeds. The additional data have not changed the statistical assessment but indicate that the correction (particularly in band 11) is probably only valid for a subset of data. While the stray light effect is small enough in Band 10 to make the data useful across a wide array of applications, the effect in Band 11 is larger and the vicarious results suggest that Band 11 data should not be used where absolute calibration is required.

We numerically investigate the transition of the static quark-antiquark string into a static-light meson-antimeson system. Improving noise reduction techniques, we are able to resolve the signature of string breaking dynamics for ${n}_{f}=2$ lattice QCD at zero temperature. This result can be related to properties of quarkonium systems. We also study short-distance interactions between two static-light mesons.

El Niño/Southern Oscillation related climate anomalies were analyzed by using a combination of satellite measurements of elevated sea-surface temperatures and subsequent elevated rainfall and satellite-derived normalized difference vegetation index data. A Rift Valley fever (RVF) risk mapping model using these climate data predicted areas where outbreaks of RVF in humans and animals were expected and occurred in the Horn of Africa from December 2006 to May 2007. The predictions were subsequently confirmed by entomological and epidemiological field investigations of virus activity in the areas identified as at risk. Accurate spatial and temporal predictions of disease activity, as it occurred first in southern Somalia and then through much of Kenya before affecting northern Tanzania, provided a 2 to 6 week period of warning for the Horn of Africa that facilitated disease outbreak response and mitigation activities. To our knowledge, this is the first prospective prediction of a RVF outbreak.

Electroactive interfaces distinguish electrochemistry from chemistry and enable electrochemical energy devices like batteries, fuel cells, and electric double layer capacitors. In batteries, electrolytes should be either thermodynamically stable at the electrode interfaces or kinetically stable by forming an electronically insulating but ionically conducting interphase. In addition to a traditional optimization of electrolytes by adding cosolvents and sacrificial additives to preferentially reduce or oxidize at the electrode surfaces, knowledge of the local electrolyte composition and structure within the double layer as a function of voltage constitutes the basis of manipulating an interphase and expanding the operating windows of electrochemical devices. In this work, we focus on how the molecular-scale insight into the solvent and ion partitioning in the electrolyte double layer as a function of applied potential could predict changes in electrolyte stability and its initial oxidation and reduction reactions. In molecular dynamics (MD) simulations, highly concentrated lithium aqueous and nonaqueous electrolytes were found to exclude the solvent molecules from directly interacting with the positive electrode surface, which provides an additional mechanism for extending the electrolyte oxidation stability in addition to the well-established simple elimination of "free" solvent at high salt concentrations. We demonstrate that depending on their chemical structures, the anions could be designed to preferentially adsorb or desorb from the positive electrode with increasing electrode potential. This provides additional leverage to dictate the order of anion oxidation and to effectively select a sacrificial anion for decomposition. The opposite electrosorption behaviors of bis(trifluoromethane)sulfonimide (TFSI) and trifluoromethanesulfonate (OTF) as predicted by MD simulation in highly concentrated aqueous electrolytes were confirmed by surface enhanced infrared spectroscopy. The proton transfer (H-transfer) reactions between solvent molecules on the cathode surface coupled with solvent oxidation were found to be ubiquitous for common Li-ion electrolyte components and dependent on the local molecular environment. Quantum chemistry (QC) calculations on the representative clusters showed that the majority of solvents such as carbonates, phosphates, sulfones, and ethers have significantly lower oxidation potential when oxidation is coupled with H-transfer, while without H-transfer their oxidation potentials reside well beyond battery operating potentials. Thus, screening of the solvent oxidation limits without considering H-transfer reactions is unlikely to be relevant, except for solvents containing unsaturated functionalities (such as C═C) that oxidize without H-transfer. On the anode, the F-transfer reaction and LiF formation during anion and fluorinated solvent reduction could be enhanced or diminished depending on salt and solvent partitioning in the double layer, again giving an additional tool to manipulate the order of reductive decompositions and interphase chemistry. Combined with experimental efforts, modeling results highlight the promise of interphasial compositional control by either bringing the desired components closer to the electrode surface to facilitate redox reaction or expelling them so that they are kinetically shielded from the potential of the electrode.

Two-dimensional Euler turbulence and drift turbulence in a pure-electron plasma column have been experimentally observed to relax to metaequilibrium states that do not maximize the Boltzmann entropy, but rather seem to minimize enstrophy. We show that a recent generalization of thermodynamics and statistics due to Tsallis [Phys. Lett. A 195, 329 (1994); J. Stat. Phys. 52, 479 (1988)] is capable of explaining this phenomenon in a natural way. In particular, the maximization of the generalized entropy ${S}_{q}$ with $q=\frac{1}{2}$ for the pure-electron plasma column leads to precisely the same profiles predicted by the restricted minimum enstrophy theory of Huang and Driscoll [Phys. Rev. Lett. 72, 2187 (1994)]. These observations make possible the construction of a comprehensive thermodynamic description of two-dimensional turbulence.

Land surface processes modulate the severity of heat waves, droughts, and other extreme events. However, models show contrasting effects of land surface changes on extreme temperatures. Here, we use an earth system model from the Geophysical Fluid Dynamics Laboratory to investigate regional impacts of land use and land cover change on combined extremes of temperature and humidity, namely aridity and moist enthalpy, quantities central to human physiological experience of near-surface climate. The model's near-surface temperature response to deforestation is consistent with recent observations, and conversion of mid-latitude natural forests to cropland and pastures is accompanied by an increase in the occurrence of hot-dry summers from once-in-a-decade to every 2-3 years. In the tropics, long time-scale oceanic variability precludes determination of how much of a small, but significant, increase in moist enthalpy throughout the year stems from the model's novel representation of historical patterns of wood harvesting, shifting cultivation, and regrowth of secondary vegetation and how much is forced by internal variability within the tropical oceans.

In the Project for Intercomparison of Land-Surface Parameterization Schemes phase 2a experiment, meteorological data for the year 1987 from Cabauw, the Netherlands, were used as inputs to 23 land-surface flux schemes designed for use in climate and weather models. Schemes were evaluated by comparing their outputs with long-term measurements of surface sensible heat fluxes into the atmosphere and the ground, and of upward longwave radiation and total net radiative fluxes, and also comparing them with latent heat fluxes derived from a surface energy balance. Tuning of schemes by use of the observed flux data was not permitted. On an annual basis, the predicted surface radiative temperature exhibits a range of 2 K across schemes, consistent with the range of about 10 W m 2 in predicted surface net radiation. Most modeled values of monthly net radiation differ from the observations by less than the estimated maximum monthly observational error (10 W m 2 ). However, modeled radiative surface temperature appears to have a systematic positive bias in most schemes; this might be explained by an error in assumed emissivity and by models' neglect of canopy thermal heterogeneity. Annual means of sensible and latent heat fluxes, into which net radiation is partitioned, have ranges across schemes of

This paper presents a general theory of system composition for "possibilistic" security properties. We see that these properties fall outside of the Alpern-Schneider safety/liveness domain and hence, are not subject to the Abadi-Lamport composition principle. We then introduce a set of trace constructors called selective interleaving functions and show that possibilistic security properties are closure properties with respect to different classes of selective interleaving functions. This provides a uniform framework for analyzing these properties and allows us to construct a partial ordering for them. We present a number of composition constructs, show the extent to which each preserves closure with respect to different classes of selective interleaving functions, and show that they are sufficient for forming the general hook-up construction. We see that although closure under a class of selective interleaving functions is generally preserved by product and cascading, it is not generally preserved by feedback, internal system, composition constructs, or refinement. We examine the reason for this.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>