NIR-Emission Spectroscopy for Local Temperature Measurements in Premixed Hydrogen/Air Flames

Adopting hydrogen fuel for combustion at scale requires a deeper understanding of the flame behavior with respect to the combustion properties of H2 and type of burner used. Non-invasive optical diagnostics have the potential to enhance our understanding of H2 combustion. For instance, near-infrared emission spectroscopy yields path-averaged information that can be employed to characterize the temperature field. In H2 flames, the emission spectrum of water vapor can be used to quantify the temperature field and elucidate the underlying physical processes. In the present study, temperature is determined throughout a premixed turbulent H2/air flame via NIR spectra, accounting for effects of the instrument and experimental configuration

Quantifying cloud performance and dependability:Taxonomy, metric design, and emerging challenges

In only a decade, cloud computing has emerged from a pursuit for a service-driven information and communication technology (ICT), becoming a significant fraction of the ICT market. Responding to the growth of the market, many alternative cloud services and their underlying systems are currently vying for the attention of cloud users and providers. To make informed choices between competing cloud service providers, permit the cost-benefit analysis of cloud-based systems, and enable system DevOps to evaluate and tune the performance of these complex ecosystems, appropriate performance metrics, benchmarks, tools, and methodologies are necessary. This requires re-examining old system properties and considering new system properties, possibly leading to the re-design of classic benchmarking metrics such as expressing performance as throughput and latency (response time). In this work, we address these requirements by focusing on four system properties: (i) elasticity of the cloud service, to accommodate large variations in the amount of service requested, (ii) performance isolation between the tenants of shared cloud systems and resulting performance variability, (iii) availability of cloud services and systems, and (iv) the operational risk of running a production system in a cloud environment. Focusing on key metrics for each of these properties, we review the state-of-the-art, then select or propose new metrics together with measurement approaches. We see the presented metrics as a foundation toward upcoming, future industry-standard cloud benchmarks

Correction to: EGFR/Ras-induced CCL20 production modulates the tumour microenvironment

The article ‘EGFR/Ras-induced CCL20 production modulates the tumour microenvironment’, written by Andreas Hippe, Stephan Alexander Braun, Péter Oláh, Peter Arne Gerber, Anne Schorr, Stephan Seeliger, Stephanie Holtz, Katharina Jannasch, Andor Pivarcsi, Bettina Buhren, Holger Schrumpf, Andreas Kislat, Erich Bünemann, Martin Steinhoff, Jens Fischer, Sérgio A. Lira, Petra Boukamp, Peter Hevezi, Nikolas Hendrik Stoecklein, Thomas Hoffmann, Frauke Alves, Jonathan Sleeman, Thomas Bauer, Jörg Klufa, Nicole Amberg, Maria Sibilia, Albert Zlotnik, Anja Müller- Homey and Bernhard Homey, was originally published electronically on the publisher’s internet portal on 30 June 2020 without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on 16 September 2021 to © The Author(s) 2021 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/ licenses/by/4.0/. Open Access funding enabled and organized by Projekt DEAL

Ancient Origin of the New Developmental Superfamily DANGER

Developmental proteins play a pivotal role in the origin of animal complexity and diversity. We report here the identification of a highly divergent developmental protein superfamily (DANGER), which originated before the emergence of animals (∼850 million years ago) and experienced major expansion-contraction events during metazoan evolution. Sequence analysis demonstrates that DANGER proteins diverged via multiple mechanisms, including amino acid substitution, intron gain and/or loss, and recombination. Divergence for DANGER proteins is substantially greater than for the prototypic member of the superfamily (Mab-21 family) and other developmental protein families (e.g., WNT proteins). DANGER proteins are widely expressed and display species-dependent tissue expression patterns, with many members having roles in development. DANGER1A, which regulates the inositol trisphosphate receptor, promotes the differentiation and outgrowth of neuronal processes. Regulation of development may be a universal function of DANGER family members. This family provides a model system to investigate how rapid protein divergence contributes to morphological complexity

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe

Entwicklung einer Methodik zur Bestimmung der Schaltverluste von diskreten 400V-GaN-Halbbrücken

Basierend auf aktuellen und zukünftigen Entwicklungsprämissen miniaturisierter automobiler Leistungselektronik wird in dieser Thesis die diskret verortete 400 Volt Gallium-Nitrid Halbbrücke als Kernkomponente einer fahrzeuggebundenen Hochvoltspeicher-Ladertopologie mit 3,7 Kilowatt Ladeleistung betrachtet. Die nachfolgende Methodikentwicklung zur Quantifizierung zeittransienten Schaltverhaltens und damit insbesondere generierter Halbbrückenverlustleistungen diskutiert die Vorteile der in dieser Arbeit entwickelten VERILOG Halbleitersimulation auf Basis verfügbarer ASM-HEMT Modelle der Compact Model Coalition gegenüber der Genauigkeit konventioneller SPICE-Simulation. Simulative Durchführungen dieser Arbeit berücksichtigen notwendige Betriebsparameter der Halbbrücke, insbesondere Totzeiten sowie deren Detektion per zum Patent angemeldeter Auswertelogik, und erlauben darüber hinaus in VERILOG die globale Schaltzellenoptimierung. Simulative Ergebnisse werden anhand einer dedizierten Power Factor Correction Stufe zeittransient und kalorimetrisch validiert. Die vorgestellten Simulationsmethodiken erlauben somit zukünftig die vollständig virtualisierte Hardwareauslegung von Leistungselektronik hinsichtlich Zeit- und Verlustverhalten.Based on current and future development premises of miniaturized automotive power electronics, this thesis deals with a discrete 400 Volt gallium nitride half bridge as key component of a high-voltage onboard charging topology with an output power of 3.7 kilowatts. The developed method quantizes time-transient switching characteristics with special focus on induced half bridge power losses. Accuracy of the presented novel VERILOG simulation of semiconductors based on ASM-HEMT models of the Compact Model Coalition is concluded to be superior to state-of-the-art SPICE simulations. Carried out simulative approaches additionally allow for global switch cell optimization in VERILOG, consider essential operational parameters and especially include transitional dead times detectable via patend pending circuitry. Simulative results are validated based on time-transient and calorimetric observations of a dedicated power factor correction stage. In future, presented simulation approaches may serve as a fully virtualized hardware development environment, accurately prediciting time and loss domain behaviour of power electronics