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Christian Herr,1 Sebastian Mang,1 Bahareh Mozafari,1 Katharina Guenther,1 Thimoteus Speer,2 Martina Seibert,1 Sanjay Kumar Srikakulam,1 Christoph Beisswenger,1 Felix Ritzmann,1 Andreas Keller,3 Rolf Mueller,4 Sigrun Smola,5 Dominic Eisinger,6 Michael Zemlin,7 Guy Danziger,1 Thomas Volk,8 Sabrina Hoersch,8 Marcin Krawczyk,9 Frank Lammert,9 Thomas Adams,9 Gudrun Wagenpfeil,10 Michael Kindermann,11 Constantin Marcu,11 Zuhair Wolf Dietrich Ataya,12 Marc Mittag,13 Konrad Schwarzkopf,13 Florian Custodis,13 Daniel Grandt,13 Harald Schaefer,14 Kai Eltges,14 Philipp M Lepper,1 Robert Bals1 On behalf of the CORSAAR Study Group1Department of Internal Medicine V - Pulmonology, Allergology and Critical Care Medicine, Saarland University, Homburg, 66421, Germany; 2Department of Internal Medicine IV - Nephrology and Hypertension & Translational Cardio-Renal Medicine, Saarland University, Homburg, 66421, Germany; 3Clinical Bioinformatics, Saarland University, Homburg, 66421, Germany; 4Helmholtz-Institute for Pharmaceutical Science Saarland, Saarbrücken, 66123, Germany; 5Institute for Virology, Saarland University, Homburg, 66421, Germany; 6Myriad RBM Inc., Austin, TX, 78759, USA; 7Department of General Pediatrics and Neonatology, Saarland University, Homburg, 66421, Germany; 8Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, Saarland University, Homburg, 66421, Germany; 9Department of Internal Medicine II - Gastroenterology, Saarland University, Homburg, 66421, Germany; 10Institute for Medical Biometry, Epidemiology and Medical Informatics, Saarland University, Homburg, 66421, Germany; 11Department of Internal Medicine, Cardiology and Intensive Care Medicine, Caritas Hospital St. Theresia Saarbrücken, Saarbrücken, 66113, Germany; 12Department of Gastroenterology, Internal and Intensive Care Medicine, Caritas Hospital St. Josef Saarbrücken, Saarbrücken, 66125, Germany; 13Department of Anesthesiology, Gastroenterology and Intensive Care Medicine, Saarbrücken Hospital, Saarbrücken, 66119, Germany; 14Department of Internal Medicine and Pulmonology, SHG-Hospital Völklingen, Saarbrücken, 66333, GermanyCorrespondence: Robert BalsDepartment of Internal Medicine V - Pulmonology, Allergology and Critical Care Medicine, Saarland University, Homburg, 66421, GermanyTel +49 6841 16 15051Email robert.bals@uks.euBackground: COVID-19 comprises several severity stages ranging from oligosymptomatic disease to multi-organ failure and fatal outcomes. The mechanisms why COVID-19 is a mild disease in some patients and progresses to a severe multi-organ and often fatal disease with respiratory failure are not known. Biomarkers that predict the course of disease are urgently needed. The aim of this study was to evaluate a large spectrum of established laboratory measurements.Patients and Methods: Patients from the prospective PULMPOHOM and CORSAAR studies were recruited and comprised 35 patients with COVID-19, 23 with conventional pneumonia, and 28 control patients undergoing elective non-pulmonary surgery. Venous blood was used to measure the serum concentrations of 79 proteins by Luminex multiplex immunoassay technology. Distribution of biomarkers between groups and association with disease severity and outcomes were analyzed.Results: The biomarker profiles between the three groups differed significantly with elevation of specific proteins specific for the respective conditions. Several biomarkers correlated significantly with disease severity and death. Uniform manifold approximation and projection (UMAP) analysis revealed a significant separation of the three disease groups and separated between survivors and deceased patients. Different models were developed to predict mortality based on the baseline measurements of several protein markers. A score combining IL-1ra, IL-8, IL-10, MCP-1, SCF and CA-9 was associated with significantly higher mortality (AUC 0.929).Discussion: Several newly identified blood markers were significantly increased in patients with severe COVID-19 (AAT, EN-RAGE, myoglobin, SAP, TIMP-1, vWF, decorin) or in patients that died (IL-1ra, IL-8, IL-10, MCP-1, SCF, CA-9). The use of established assay technologies allows for rapid translation into clinical practice.Keywords: biomarker, inflammation, SARS-CoV2

COMSOL Multiphysics is a comprehensive simulation software environment for a wide range of applications. COMSOL has an interactive interface that facilitates the modeling procedure and allows an easy coupling of different physical processes. The Subsurface Flow module extends the COMSOL modeling environment to applications related to fluid flow in saturated and variably saturated porous media. COMSOL is increasingly used in the investigation of geophysical, hydrogeological and environmental phenomena. The main goal of this work is to explore the ability of COMSOL for simulating seawater intrusion (SWI) in fractured coastal aquifers. Numerical modeling of such a problem is of high interest as fractured/karstic coastal aquifers are widespread and processes of SWI in the presence of fractures remains poorly understood. We set up a COSMOL model for the popular Henry problem. The accuracy of COMSOL is highlighted by comparison against the semianalytical solutions for simple homogeneous aquifers. For fractured aquifers, the performance of COSMOL is evaluated by comparison against an in-house finite element model based on the discrete fracture model and against the results of existing works. Given its versatility and flexibility, COMSOL shows promise as a tool for SWI in coastal aquifers.

Background and Objectives: Current and voltage signals' distortion caused by the fault in the power system has negative effects upon the operation of the protective devices. One of the influencing factors is the existence of the exponential DC which can significantly distort the signals and lead to a possible malfunction of the protective devices, especially distance and over-current relays. The main problem is the lack of clarity about this component due to the dependence of its time constant and initial amplitude to the configuration of the electrical grid, location and resistance of faulty point. This makes it hard to extract the main frequency phasors of the voltage and current. Methods: Considering the importance of a fast clearance of the fault, this paper offers a method for an effective and fast removal of the decaying-DC that employs a data window with a length that is equal to the half cycle of the main frequency, while the conventional methods mostly use data from one cycle or even more. The proposed method is based upon the extraction of the decaying-DC component's parameters. Results: The efficiency of this method is compared to the conventional Fourier algorithm of Half-Cycle (HCFA) and the mimic filter plus the HCFA. Conclusion: The outcomes display that the proposed method presents a better efficiency from the point of view of the speed and the accuracy of convergence to the final results. [ABSTRACT FROM AUTHOR]

This paper proposes an advanced distribution automation planning problem in which emergency-based demand response plans are incorporated during service restoration process. The fitness function of this planning problem consists of various costs associated with fault occurrence in electric distribution systems consisting of the total yearly cost of customers' interruptions, the total annualized investment cost of control and protection devices deployment, including sectionalizing switches, circuit breakers, and fuses and the total annual cost of performing emergency-based demand response programs in the service restoration process. Moreover, the customers' behavior in participating in the service restoration process is also modeled through using an S-function. The proposed advanced distribution automation planning method is implemented on the fourth bus of the Roy Bilinton test system in order to evaluate its efficacy. The obtained results show that the reliability indices and the total cost of distribution automation are reduced by about 9% and 12% more than the published methods for distribution automation, respectively. [ABSTRACT FROM AUTHOR]

Taking into account the increased rate of nonlinear loads in power systems, recognition and extraction of harmonics and noise seems necessary. The duty of active filter is to identify these non sinusoid currents and take action to cancel them. In this paper, adaptive method is examined and it is observed that adaptive filter might develop appropriate performance in various conditions. Generally speaking, adaptive filter is defined as a filter that its specifications might be changed to achieve to a specific goal and have this change or adaptation automatically and without the need for any intervention. Among the features of this filter, one might refer to its simplicity and powerful structure. [ABSTRACT FROM AUTHOR]

Pneumonia is a common cause of morbidity and mortality and is most often caused by bacterial pathogens. COVID-19 is characterized by lung infection with potential progressive organ failure. The systemic consequences of both disease on the systemic blood metabolome are not fully understood. The aim of this study was to compare the blood metabolome of both diseases and we hypothesize that plasma metabolomics may help to identify the systemic effects of these diseases. Therefore, we profiled the plasma metabolome of 43 cases of COVID-19 pneumonia, 23 cases of non-COVID-19 pneumonia, and 26 controls using a non-targeted approach. Metabolic alterations differentiating the three groups were detected, with specific metabolic changes distinguishing the two types of pneumonia groups. A comparison of venous and arterial blood plasma samples from the same subjects revealed the distinct metabolic effects of pulmonary pneumonia. In addition, a machine learning signature of four metabolites was predictive of the disease outcome of COVID-19 subjects with an area under the curve (AUC) of 86 ± 10 %. Overall, the results of this study uncover systemic metabolic changes that could be linked to the etiology of COVID-19 pneumonia and non-COVID-19 pneumonia.

This paper addresses the application of a static Var compensator (SVC) to improve the damping of interarea oscillations. Optimal location and size of SVC are defined using bifurcation and modal analysis to satisfy its primary application. Furthermore, the best-input signal for damping controller is selected using Hankel singular values and right half plane-zeros. The proposed approach is aimed to design a robust PI controller based on interval plants and Kharitonov's theorem. The objective here is to determine the stability region to attain robust stability, the desired phase margin, gain margin, and bandwidth. The intersection of the resulting stability regions yields the set of kp-ki parameters. In addition, optimal multiobjective design of PI controller using particle swarm optimization (PSO) algorithm is presented. The effectiveness of the suggested controllers in damping of local and interarea oscillation modes of a multimachine power system, over a wide range of loading conditions and system configurations, is confirmed through eigenvalue analysis and nonlinear time domain simulation., (Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.)