The use of reinforcement learning algorithms to meet the challenges of an artificial pancreas

Blood glucose control, for example, in diabetes mellitus or severe illness, requires strict adherence to a protocol of food, insulin administration and exercise personalized to each patient. An artificial pancreas for automated treatment could boost quality of glucose control and patients' independence. The components required for an artificial pancreas are: i) continuous glucose monitoring (CGM), ii) smart controllers and iii) insulin pumps delivering the optimal amount of insulin. In recent years, medical devices for CGM and insulin administration have undergone rapid progression and are now commercially available. Yet, clinically available devices still require regular patients' or caregivers' attention as they operate in open-loop control with frequent user intervention. Dosage-calculating algorithms are currently being studied in intensive care patients [1] , for short overnight control to supplement conventional insulin delivery [2] , and for short periods where patients rest and follow a prescribed food regime [3] . Fully automated algorithms that can respond to the varying activity levels seen in outpatients, with unpredictable and unreported food intake, and which provide the necessary personalized control for individuals is currently beyond the state-of-the-art. Here, we review and discuss reinforcement learning algorithms, controlling insulin in a closed-loop to provide individual insulin dosing regimens that are reactive to the immediate needs of the patient

Diverse syntrophic partnerships from deep-sea methane vents revealed by direct cell capture and metagenomics

Microorganisms play a fundamental role in the cycling of nutrients and energy on our planet. A common strategy for many microorganisms mediating biogeochemical cycles in anoxic environments is syntrophy, frequently necessitating close spatial proximity between microbial partners. We are only now beginning to fully appreciate the diversity and pervasiveness of microbial partnerships in nature, the majority of which cannot be replicated in the laboratory. One notable example of such cooperation is the interspecies association between anaerobic methane oxidizing archaea (ANME) and sulfate-reducing bacteria. These consortia are globally distributed in the environment and provide a significant sink for methane by substantially reducing the export of this potent greenhouse gas into the atmosphere. The interdependence of these currently uncultured microbes renders them difficult to study, and our knowledge of their physiological capabilities in nature is limited. Here, we have developed a method to capture select microorganisms directly from the environment, using combined fluorescence in situ hybridization and immunomagnetic cell capture. We used this method to purify syntrophic anaerobic methane oxidizing ANME-2c archaea and physically associated microorganisms directly from deep-sea marine sediment. Metagenomics, PCR, and microscopy of these purified consortia revealed unexpected diversity of associated bacteria, including Betaproteobacteria and a second sulfate-reducing Deltaproteobacterial partner. The detection of nitrogenase genes within the metagenome and subsequent demonstration of 15N2 incorporation in the biomass of these methane-oxidizing consortia suggest a possible role in new nitrogen inputs by these syntrophic assemblages

Regional but not global temperature variability underestimated by climate models at supradecadal timescales

Knowledge of the characteristics of natural climate variability is vital when assessing the range of plausible future climate trajectories in the next decades to centuries. The reliable detection of climate fluctuations on multidecadal to centennial timescales depends on proxy reconstructions and model simulations, as the instrumental record extends back only a few decades in most parts of the world. Systematic comparisons between model-simulated and proxy-based inferences of natural variability, however, often seem contradictory. Locally, simulated temperature variability is consistently smaller on multidecadal and longer timescales than is indicated by proxy-based reconstructions, implying that climate models or proxy interpretations might have deficiencies. In contrast, at global scales, studies found agreement between simulated and proxy reconstructed temperature variations. Here we review the evidence regarding the scale of natural temperature variability during recent millennia. We identify systematic reconstruction deficiencies that may contribute to differing local and global model–proxy agreement but conclude that they are probably insufficient to resolve such discrepancies. Instead, we argue that regional climate variations persisted for longer timescales than climate models simulating past climate states are able to reproduce. This would imply an underestimation of the regional variability on multidecadal and longer timescales and would bias climate projections and attribution studies. Thus, efforts are needed to improve the simulation of natural variability in climate models accompanied by further refining proxy-based inferences of variability.This study was undertaken by members of CVAS and 2k Network, working groups of the Past Global Changes (PAGES) Global Research association. This is a contribution to the SPACE ERC, STACY and PALMOD projects. The SPACE ERC project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 716092). STACY has been funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, project no. 395588486). This work has also been supported by the German Federal Ministry of Education and Research (BMBF), through the PalMod project (subprojects 01LP1926B (O.B.), 01LP1926D (M.C.) and 01LP1926C (B.E., P.S. and N.W.)) from the Research for Sustainability initiative (FONA). B.E. is supported by the Heinrich Böll Foundation. E.M.-C. was supported by the PARAMOUR project, funded by the Fonds de la Recherche Scientifique–FNRS and the FWO under the Excellence of Science (EOS) programme (grant no. O0100718F, EOS ID no. 30454083). A.H. was supported by a Legacy Grant from the Australian Research Council Centre of Excellence for Australian Biodiversity and Heritage. B.M. was supported by LINKA20102 and the Spanish Ministry of Science and Innovation project CEX2018‐000794‐S. The work originated from discussions at the CVAS working group of PAGES at a workshop at the Internationales Wissenschaftsforum Heidelberg, which was funded by a Hengstberger Prize. We thank N. Beech, C. Brierley, F. Gonzalez-Rouco and M. MacPartland for comments on earlier drafts of the manuscript. This manuscript uses data provided by the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP and PMIP. We thank the research groups for producing and kindly making their model outputs, measurements and palaeoclimate reconstructions available to us. Editorial assistance, in the form of language editing and correction, was provided by XpertScientific Editing and Consulting Services. We acknowledge support by the Open Access Publication Funds of Alfred-Wegener-Institut Helmholtz Zentrum für Polar- und Meeresforschung.Peer ReviewedPostprint (author's final draft

Discrete exterior calculus (DEC) for the surface Navier-Stokes equation

We consider a numerical approach for the incompressible surface Navier-Stokes equation. The approach is based on the covariant form and uses discrete exterior calculus (DEC) in space and a semi-implicit discretization in time. The discretization is described in detail and related to finite difference schemes on staggered grids in flat space for which we demonstrate second order convergence. We compare computational results with a vorticity-stream function approach for surfaces with genus 0 and demonstrate the interplay between topology, geometry and flow properties. Our discretization also allows to handle harmonic vector fields, which we demonstrate on a torus.Comment: 21 pages, 9 figure

The first search for bosonic super-WIMPs with masses up to 1 MeV/c2^2 with GERDA

We present the first search for bosonic super-WIMPs as keV-scale dark matter candidates performed with the GERDA experiment. GERDA is a neutrinoless double-beta decay experiment which operates high-purity germanium detectors enriched in $^{76}$Ge in an ultra-low background environment at the Laboratori Nazionali del Gran Sasso (LNGS) of INFN in Italy. Searches were performed for pseudoscalar and vector particles in the mass region from 60 keV/c$^2$ to 1 MeV/c$^2$. No evidence for a dark matter signal was observed, and the most stringent constraints on the couplings of super-WIMPs with masses above 120 keV/c$^2$ have been set. As an example, at a mass of 150 keV/c$^2$ the most stringent direct limits on the dimensionless couplings of axion-like particles and dark photons to electrons of $g_{ae} < 3 \cdot 10^{-12}$ and ${\alpha'}/{\alpha} < 6.5 \cdot 10^{-24}$ at 90% credible interval, respectively, were obtained.Comment: 6 pages, 3 figures, submitted to Physical Review Letters, added list of authors, updated ref. [21

On two-dimensional surface attractors and repellers on 3-manifolds

We show that if $f: M^3\to M^3$ is an $A$-diffeomorphism with a surface two-dimensional attractor or repeller $\mathcal B$ and $M^2_ \mathcal B$ is a supporting surface for $\mathcal B$, then $\mathcal B = M^2_{\mathcal B}$ and there is $k\geq 1$ such that: 1) $M^2_{\mathcal B}$ is a union $M^2_1\cup...\cup M^2_k$ of disjoint tame surfaces such that every $M^2_i$ is homeomorphic to the 2-torus $T^2$. 2) the restriction of $f^k$ to $M^2_i$ $(i\in\{1,...,k\})$ is conjugate to Anosov automorphism of $T^2$

Rigorous derivation of a nonlinear diffusion equation as fast-reaction limit of a continuous coagulation-fragmentation model with diffusion

Weak solutions of the spatially inhomogeneous (diffusive) Aizenmann-Bak model of coagulation-breakup within a bounded domain with homogeneous Neumann boundary conditions are shown to converge, in the fast reaction limit, towards local equilibria determined by their mass. Moreover, this mass is the solution of a nonlinear diffusion equation whose nonlinearity depends on the (size-dependent) diffusion coefficient. Initial data are assumed to have integrable zero order moment and square integrable first order moment in size, and finite entropy. In contrast to our previous result [CDF2], we are able to show the convergence without assuming uniform bounds from above and below on the number density of clusters

On the verge of Umdeutung in Minnesota: Van Vleck and the correspondence principle (Part One)

In October 1924, the Physical Review, a relatively minor journal at the time, published a remarkable two-part paper by John H. Van Vleck, working in virtual isolation at the University of Minnesota. Van Vleck combined advanced techniques of classical mechanics with Bohr's correspondence principle and Einstein's quantum theory of radiation to find quantum analogues of classical expressions for the emission, absorption, and dispersion of radiation. For modern readers Van Vleck's paper is much easier to follow than the famous paper by Kramers and Heisenberg on dispersion theory, which covers similar terrain and is widely credited to have led directly to Heisenberg's "Umdeutung" paper. This makes Van Vleck's paper extremely valuable for the reconstruction of the genesis of matrix mechanics. It also makes it tempting to ask why Van Vleck did not take the next step and develop matrix mechanics himself.Comment: 82 page

Biological sources and sinks of nitrous oxide and strategies to mitigate emissions

Nitrous oxide (N 2 O) is a powerful atmospheric greenhouse gas and cause of ozone layer depletion. Global emissions continue to rise. More than two-thirds of these emissions arise from bacterial and fungal denitrification and nitrification processes in soils, largely as a result of the application of nitrogenous fertilizers. This article summarizes the outcomes of an interdisciplinary meeting, ‘Nitrous oxide (N 2 O) the forgotten greenhouse gas’, held at the Kavli Royal Society International Centre, from 23 to 24 May 2011. It provides an introduction and background to the nature of the problem, and summarizes the conclusions reached regarding the biological sources and sinks of N 2 O in oceans, soils and wastewaters, and discusses the genetic regulation and molecular details of the enzymes responsible. Techniques for providing global and local N 2 O budgets are discussed. The findings of the meeting are drawn together in a review of strategies for mitigating N 2 O emissions, under three headings, namely: (i) managing soil chemistry and microbiology, (ii) engineering crop plants to fix nitrogen, and (iii) sustainable agricultural intensification. </jats:p

Soil moisture and matric potential-an open field comparison of sensor systems

Soil water content and matric potential are central hydrological state variables. A large variety of automated probes and sensor systems for state monitoring exist and are frequently applied. Most applications solely rely on the calibration by the manufacturers. Until now, there has been no commonly agreed-upon calibration procedure. Moreover, several opinions about the capabilities and reliabilities of specific sensing methods or sensor systems exist and compete. A consortium of several institutions conducted a comparison study of currently available sensor systems for soil water content and matric potential under field conditions. All probes were installed at 0.2mb.s. (metres below surface), following best-practice procedures. We present the set-up and the recorded data of 58 probes of 15 different systems measuring soil moisture and 50 further probes of 14 different systems for matric potential. We briefly discuss the limited coherence of the measurements in a cross-correlation analysis. The measuring campaign was conducted during the growing period of 2016. The monitoring data, results from pedophysical analyses of the soil and laboratory reference measurements for calibration are published in Jackisch et al. (2018, https://doi.org/10.1594/PANGAEA.892319)