Urban Infrastructures: Criticality, Vulnerability and Protection. Report of the International Conference of the Research Training Group KRITIS at Technische Universität Darmstadt, Germany

From the 7th to the 8th of February 2019, more than 70 scientists from different disciplines and countries came together for the international Conference “Urban Infrastructure: Criticality, Vulnerability and Protection” which was organised by the Research Training Group KRITIS at Technische Universität Darmstadt. The focus of the conference was on networked critical infrastructures (CI) in cities as socio-technical systems that require special protection strategies due to their vulnerabilities. Five multidisciplinary panels on Governance, Spatiality, Temporality, Safety and Security, and ICT Solutions elucidated urban CI protection. The keynote lectures by Per Högselius (KTH Royal Institute of Technology, Stockholm), Jon Coaffee (University of Warwick; New York University) and Christoph Lamers (State Fire Service Institute North Rhine Westfalia) highlighted and deepened the aspects relevant to this context. Despite all the diversity of the contributions from many different disciplines, one aspect has always been prominent: the enormous complexity of urban CI. Regardless of the task at hand - governing and planning cities, creating security concepts and making cities more resilient - the complexity of the CI systems must always be considered. On the conference, civil engineers, computer scientists, urban and spatial planners, architects, sociologists, political scientists, historians and philosophers as well as practitioners from public administration, and operators of critical infrastructures made interesting suggestions on how to deal with the uncertainties involved. It also became clear that current challenges require approaches that cannot be found in a single discipline alone

Transformations of Infrastructure Systems: Report of the second International Conference of the Research Training Group KRITIS at the Technical University Darmstadt, Germany

On the 4th and 5th of November 2021, more than 50 scholars from different disciplines and countries came together in an online conference to discuss the multiple aspects of Transformations of Infrastructure Systems at the second international conference organized by the Research Training Group KRITIS at the Technical University of Darmstadt, Germany. The focus of this conference was on the dynamic and changing nature of infrastructure systems and describing, understanding, and explaining transformation processes of infrastructures. Within the four multidisciplinary panels (Safety, Cultures, Governance, and both Temporality and Spatiality) the participants shared their research and knowledge on various aspects of transformation of infrastructure Systems. The conference gave an insight into the triggers of transformations and highlighted the conditions under which they take place and the consequences. The keynote lectures by Prof. Dr. Timothy Moss (Humboldt University of Berlin), Dr. Anique Hommels (Maastricht University), and Niklas Vespermann (Federal Network Agency, Germany) further highlighted and deepened the aspects relevant to this context

The ribosome assembly factor Nep1 responsible for Bowen–Conradi syndrome is a pseudouridine-N1-specific methyltransferase

Nep1 (Emg1) is a highly conserved nucleolar protein with an essential function in ribosome biogenesis. A mutation in the human Nep1 homolog causes Bowen–Conradi syndrome—a severe developmental disorder. Structures of Nep1 revealed a dimer with a fold similar to the SPOUT-class of RNA-methyltransferases suggesting that Nep1 acts as a methyltransferase in ribosome biogenesis. The target for this putative methyltransferase activity has not been identified yet. We characterized the RNA-binding specificity of Methanocaldococcus jannaschii Nep1 by fluorescence- and NMR-spectroscopy as well as by yeast three-hybrid screening. Nep1 binds with high affinity to short RNA oligonucleotides corresponding to nt 910–921 of M. jannaschii 16S rRNA through a highly conserved basic surface cleft along the dimer interface. Nep1 only methylates RNAs containing a pseudouridine at a position corresponding to a previously identified hypermodified N1-methyl-N3-(3-amino-3-carboxypropyl) pseudouridine (m1acp3-Ψ) in eukaryotic 18S rRNAs. Analysis of the methylated nucleoside by MALDI-mass spectrometry, HPLC and NMR shows that the methyl group is transferred to the N1 of the pseudouridine. Thus, Nep1 is the first identified example of an N1-specific pseudouridine methyltransferase. This enzymatic activity is also conserved in human Nep1 suggesting that Nep1 is the methyltransferase in the biosynthesis of m1acp3-Ψ in eukaryotic 18S rRNAs

Accurate and fast deep learning dose prediction for a preclinical microbeam radiation therapy study using low-statistics Monte Carlo simulations

Microbeam radiation therapy (MRT) utilizes coplanar synchrotron radiation beamlets and is a proposed treatment approach for several tumour diagnoses that currently have poor clinical treatment outcomes, such as gliosarcomas. Prescription dose estimations for treating preclinical gliosarcoma models in MRT studies at the Imaging and Medical Beamline at the Australian Synchrotron currently rely on Monte Carlo (MC) simulations. The steep dose gradients associated with the 50$\,\mu$m wide coplanar beamlets present a significant challenge for precise MC simulation of the MRT irradiation treatment field in a short time frame. Much research has been conducted on fast dose estimation methods for clinically available treatments. However, such methods, including GPU Monte Carlo implementations and machine learning (ML) models, are unavailable for novel and emerging cancer radiation treatment options like MRT. In this work, the successful application of a fast and accurate machine learning dose prediction model in a retrospective preclinical MRT rodent study is presented for the first time. The ML model predicts the peak doses in the path of the microbeams and the valley doses between them, delivered to the gliosarcoma in rodent patients. The predictions of the ML model show excellent agreement with low-noise MC simulations, especially within the investigated tumour volume. This agreement is despite the ML model being deliberately trained with MC-calculated samples exhibiting significantly higher statistical uncertainties. The successful use of high-noise training set data samples, which are much faster to generate, encourages and accelerates the transfer of the ML model to different treatment modalities for other future applications in novel radiation cancer therapies

Chiral and deconfinement transition from correlation functions: SU(2) vs. SU(3)

We study a gauge invariant order parameter for deconfinement and the chiral condensate in SU(2) and SU(3) Yang-Mills theory in the vicinity of the deconfinement phase transition using the Landau gauge quark and gluon propagators. We determine the gluon propagator from lattice calculations and the quark propagator from its Dyson-Schwinger equation, using the gluon propagator as input. The critical temperature and a deconfinement order parameter are extracted from the gluon propagator and from the dependency of the quark propagator on the temporal boundary conditions. The chiral transition is determined using the quark condensate as order parameter. We investigate whether and how a difference in the chiral and deconfinement transition between SU(2) and SU(3) is manifest.Comment: 15 pages, 9 figures. For clarification one paragraph and two references added in the introduction and two sentences at the end of the first and last paragraph of the summary. Appeared in EPJ

Two-loop HTL Thermodynamics with Quarks

We calculate the quark contribution to the free energy of a hot quark-gluon plasma to two-loop order using hard-thermal-loop (HTL) perturbation theory. All ultraviolet divergences can be absorbed into renormalizations of the vacuum energy and the HTL quark and gluon mass parameters. The quark and gluon HTL mass parameters are determined self-consistently by a variational prescription. Combining the quark contribution with the two-loop HTL perturbation theory free energy for pure-glue we obtain the total two-loop QCD free energy. Comparisons are made with lattice estimates of the free energy for N_f=2 and with exact numerical results obtained in the large-N_f limit.Comment: 33 pages, 6 figure

Resummation in Hot Field Theories

There has been significant progress in our understanding of finite-temperature field theory over the past decade. In this paper, we review the progress in perturbative thermal field theory focusing on thermodynamic quantities. We first discuss the breakdown of naive perturbation theory at finite temperature and the need for an effective expansion that resums an infinite class of diagrams in the perturbative expansion. This effective expansion which is due to Braaten and Pisarski, can be used to systematically calculate various static and dynamical quantities as a weak-coupling expansion in powers of g. However, it turns that the weak-coupling expansion for thermodynamic quantities are useless unless the coupling constant is very small. We critically discuss various ways of reorganizing the perturbative series for thermal field theories in order to improve its convergence. These include screened perturbation theory (SPT), hard-thermal-loop perturbation theory (HTLPT), the Phi-derivable approach, dimensionally reduced (DR) SPT, and the DR Phi-derivable approach.Comment: 82 pages, 20 figures; v2 - typos corrected, references adde

HER2 and ESR1 mRNA expression levels and response to neoadjuvant trastuzumab plus chemotherapy in patients with primary breast cancer

Introduction: Recent data suggest that benefit from trastuzumab and chemotherapy might be related to expression of HER2 and estrogen receptor (ESR1). Therefore, we investigated HER2 and ESR1 mRNA levels in core biopsies of HER2-positive breast carcinomas from patients treated within the neoadjuvant GeparQuattro trial. Methods: HER2 levels were centrally analyzed by immunohistochemistry (IHC), silver in-situ hybridization (SISH) and qRT-PCR in 217 pretherapeutic formalin-fixed, paraffin-embedded (FFPE) core biopsies. All tumors had been HER2-positive by local pathology and had been treated with neoadjuvant trastuzumab/ chemotherapy in GeparQuattro. Results: Only 73% of the tumors (158 of 217) were centrally HER2-positive (cHER2-positive) by IHC/SISH, with cHER2-positive tumors showing a significantly higher pCR rate (46.8% vs. 20.3%, p<0.0005). HER2 status by qRT-PCR showed a concordance of 88.5% with the central IHC/SISH status, with a low pCR rate in those tumors that were HER2-negative by mRNA analysis (21.1% vs. 49.6%, p<0.0005). The level of HER2 mRNA expression was linked to response rate in ESR1-positive tumors, but not in ESR1-negative tumors. HER2 mRNA expression was significantly associated with pCR in the HER2-positive/ESR1-positive tumors (p=0.004), but not in HER2-positive/ESR1-negative tumors. Conclusions: Only patients with cHER2-positive tumors - irrespective of the method used - have an increased pCR rate with trastuzumab plus chemotherapy. In patients with cHER2-negative tumors the pCR rate is comparable to the pCR rate in the non-trastuzumab treated HER-negative population. Response to trastuzumab is correlated to HER2 mRNA levels only in ESR1-positive tumors. This study adds further evidence to the different biology of both subsets within the HER2-positive group