Principal Flow Patterns across renewable electricity networks

Using Principal Component Analysis (PCA), the nodal injection and line flow patterns in a network model of a future highly renewable European electricity system are investigated. It is shown that the number of principal components needed to describe 95$\%$ of the nodal power injection variance first increases with the spatial resolution of the system representation. The number of relevant components then saturates at around 76 components for network sizes larger than 512 nodes, which can be related to the correlation length of wind patterns over Europe. Remarkably, the application of PCA to the transmission line power flow statistics shows that irrespective of the spatial scale of the system representation a very low number of only 8 principal flow patterns is sufficient to capture 95$\%$ of the corresponding spatio-temporal variance. This result can be theoretically explained by a particular alignment of some principal injection patterns with topological patterns inherent to the network structure of the European transmission system

Reactive Stepping for Humanoid Robots using Reinforcement Learning: Application to Standing Push Recovery on the Exoskeleton Atalante

State-of-the-art reinforcement learning is now able to learn versatile locomotion, balancing and push-recovery capabilities for bipedal robots in simulation. Yet, the reality gap has mostly been overlooked and the simulated results hardly transfer to real hardware. Either it is unsuccessful in practice because the physics is over-simplified and hardware limitations are ignored, or regularity is not guaranteed, and unexpected hazardous motions can occur. This paper presents a reinforcement learning framework capable of learning robust standing push recovery for bipedal robots that smoothly transfer to reality, providing only instantaneous proprioceptive observations. By combining original termination conditions and policy smoothness conditioning, we achieve stable learning, sim-to-real transfer and safety using a policy without memory nor explicit history. Reward engineering is then used to give insights into how to keep balance. We demonstrate its performance in reality on the lower-limb medical exoskeleton Atalante

Building an Optical Free-Electron Laser in the Traveling-Wave Thomson-Scattering Geometry

We show how optical free-electron lasers and enhanced incoherent Thomson scattering radiation sources can be realized with Traveling-Wave Thomson-Scattering (TWTS) today. Emphasis is put on the realization of optical free-electron lasers (OFELs) with existing state-of-the-art technology for laser systems and electron accelerators. The conceptual design of optical setups for the preparation of laser pulses suitable for TWTS OFELs and enhanced Thomson sources is presented. We further provide expressions to estimate the acceptable alignment tolerances of optical components for TWTS OFEL operation. Examples of TWTS OFELs radiating at 100 nm, 13.5 nm and 1.5 Å as well as an incoherent source producing 30 keV photons highlight the feasibility of the concept and detail the procedure to determine the optical components parameters of a TWTS setup

Primordial black holes in braneworld cosmologies: astrophysical constraints

In two recent papers we explored the modifications to primordial black hole physics when one moves to the simplest braneworld model, Randall--Sundrum type II. Both the evaporation law and the cosmological evolution of the population can be modified, and additionally accretion of energy from the background can be dominant over evaporation at high energies. In this paper we present a detailed study of how this impacts upon various astrophysical constraints, analyzing constraints from the present density, from the present high-energy photon background radiation, from distortion of the microwave background spectrum, and from processes affecting light element abundances both during and after nucleosynthesis. Typically, the constraints on the formation rate of primordial black holes weaken as compared to the standard cosmology if black hole accretion is unimportant at high energies, but can be strengthened in the case of efficient accretion.Comment: 17 pages RevTeX4 file with three figures incorporated; final paper in series astro-ph/0205149 and astro-ph/0208299. Minor changes to match version accepted by Physical Review

Altered fibrin clot structure and dysregulated fibrinolysis contribute to thrombosis risk in severe COVID-19

The high incidence of thrombotic events suggests a possible role of the contact system pathway in COVID-19 pathology. Here, we demonstrate altered levels of factor XII (FXII) and its activation products in critically ill COVID-19 patients in comparison to patients with severe acute respiratory distress syndrome due to influenza virus (ARDS-influenza). Compatible with this data, we report rapid consumption of FXII in COVID-19, but not in ARDS-influenza, plasma. Interestingly, the lag phase in fibrin formation, triggered by the FXII activator kaolin, was not prolonged in COVID-19 as opposed to ARDS-influenza. Using confocal and electron microscopy, we showed that increased FXII activation rate, in conjunction with elevated fibrinogen levels, triggers formation of fibrinolysis-resistant, compact clots with thin fibers and small pores in COVID-19. Accordingly, clot lysis was markedly impaired in COVID-19 as opposed to ARDS-infleunza subjects. Dysregulatated fibrinolytic system, as evidenced by elevated levels of thrombin-activatable fibrinolysis inhibitor, tissue-plasminogen activator, and plasminogen activator inhibitor-1 in COVID-19 potentiated this effect. Analysis of lung tissue sections revealed wide-spread extra- and intra-vascular compact fibrin deposits in COVID-19 patients. Together, compact fibrin network structure and dysregulated fibrinolysis may collectively contribute to high incidence of thrombotic events in COVID-19

Multi-omic signature of body weight change: results from a population-based cohort study

BACKGROUND: Excess body weight is a major risk factor for cardiometabolic diseases. The complex molecular mechanisms of body weight change-induced metabolic perturbations are not fully understood. Specifically, in-depth molecular characterization of long-term body weight change in the general population is lacking. Here, we pursued a multi-omic approach to comprehensively study metabolic consequences of body weight change during a seven-year follow-up in a large prospective study. METHODS: We used data from the population-based Cooperative Health Research in the Region of Augsburg (KORA) S4/F4 cohort. At follow-up (F4), two-platform serum metabolomics and whole blood gene expression measurements were obtained for 1,631 and 689 participants, respectively. Using weighted correlation network analysis, omics data were clustered into modules of closely connected molecules, followed by the formation of a partial correlation network from the modules. Association of the omics modules with previous annual percentage weight change was then determined using linear models. In addition, we performed pathway enrichment analyses, stability analyses, and assessed the relation of the omics modules with clinical traits. RESULTS: Four metabolite and two gene expression modules were significantly and stably associated with body weight change (P-values ranging from 1.9 × 10−4 to 1.2 × 10−24). The four metabolite modules covered major branches of metabolism, with VLDL, LDL and large HDL subclasses, triglycerides, branched-chain amino acids and markers of energy metabolism among the main representative molecules. One gene expression module suggests a role of weight change in red blood cell development. The other gene expression module largely overlaps with the lipid-leukocyte (LL) module previously reported to interact with serum metabolites, for which we identify additional co-expressed genes. The omics modules were interrelated and showed cross-sectional associations with clinical traits. Moreover, weight gain and weight loss showed largely opposing associations with the omics modules. CONCLUSIONS: Long-term weight change in the general population globally associates with serum metabolite concentrations. An integrated metabolomics and transcriptomics approach improved the understanding of molecular mechanisms underlying the association of weight gain with changes in lipid and amino acid metabolism, insulin sensitivity, mitochondrial function as well as blood cell development and function