Showing papers by "Johannes Kepler University of Linz published in 2021"
Daniel J. Klionsky1, Amal Kamal Abdel-Aziz2, Sara Abdelfatah3, Mahmoud Abdellatif4 +2980 more•Institutions (777)
TL;DR: In this article, the authors present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes.
Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.
1,129 citations
Innsbruck Medical University1, The Catholic University of America2, First Faculty of Medicine, Charles University in Prague3, Copenhagen University Hospital4, University of Cologne5, University College London6, Leiden University Medical Center7, Institut Gustave Roussy8, Agostino Gemelli University Polyclinic9, Imperial College London10, University of Navarra11, Johannes Kepler University of Linz12, Erasmus University Rotterdam13, Humboldt University of Berlin14, Medical University of Vienna15, The Royal Marsden NHS Foundation Trust16, University of Amsterdam17, Dresden University of Technology18, European Institute of Oncology19
TL;DR: A European consensus conference on endometrial carcinoma was held in 2014 to produce multi-disciplinary evidence-based guidelines on selected questions as mentioned in this paper, and the European Society of Gynaecological Oncology (ESGO), the European SocieTy for Radiotherapy and Oncologies (ESTRO), and the EPSP jointly decided to update these evidence-base guidelines and to cover new topics in order to improve the quality of care for women with endometrium carcinoma across Europe and worldwide.
Abstract: A European consensus conference on endometrial carcinoma was held in 2014 to produce multi-disciplinary evidence-based guidelines on selected questions. Given the large body of literature on the management of endometrial carcinoma published since 2014, the European Society of Gynaecological Oncology (ESGO), the European SocieTy for Radiotherapy and Oncology (ESTRO), and the European Society of Pathology (ESP) jointly decided to update these evidence-based guidelines and to cover new topics in order to improve the quality of care for women with endometrial carcinoma across Europe and worldwide.
584 citations
TL;DR: The potential pathophysiological mechanisms for SARS‐CoV‐2 hepatic tropism as well as acute and possibly long‐term liver injury in COVID‐19 are discussed.
Abstract: The recent outbreak of coronavirus disease 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has resulted in a world-wide pandemic. Disseminated lung injury with the development of acute respiratory distress syndrome (ARDS) is the main cause of mortality in COVID-19. Although liver failure does not seem to occur in the absence of pre-existing liver disease, hepatic involvement in COVID-19 may correlate with overall disease severity and serve as a prognostic factor for the development of ARDS. The spectrum of liver injury in COVID-19 may range from direct infection by SARS-CoV-2, indirect involvement by systemic inflammation, hypoxic changes, iatrogenic causes such as drugs and ventilation to exacerbation of underlying liver disease. This concise review discusses the potential pathophysiological mechanisms for SARS-CoV-2 hepatic tropism as well as acute and possibly long-term liver injury in COVID-19.
245 citations
TL;DR: This commentary is a call to action for the hydrology community to focus on developing a quantitative understanding of where and when hydrological process understanding is valuable in a modeling discipline increasingly dominated by machine learning.
Abstract: We suggest that there is a potential danger to the hydrological sciences community in not recognizing how transformative machine learning will be for the future of hydrological modeling. Given the recent success of machine learning applied to modeling problems, it is unclear what the role of hydrological theory might be in the future. We suggest that a central challenge in hydrology right now should be to clearly delineate where and when hydrological theory adds value to prediction systems. Lessons learned from the history of hydrological modeling motivate several clear next steps toward integrating machine learning into hydrological modeling workflows.
174 citations
Max Delbrück Center for Molecular Medicine1, Charité2, Johannes Kepler University of Linz3, Free University of Berlin4, Icahn School of Medicine at Mount Sinai5, Regeneron6, University of Oxford7, University of Hamburg8, University of Natural Resources and Life Sciences, Vienna9, City University of Hong Kong10, Francis Crick Institute11
TL;DR: In this article, the authors show that SARS-CoV-2 evokes cellular senescence as a primary stress response in infected cells, and suggest that senolytic targeting of virus-infected cells is a treatment option against SARS and perhaps other viral infections.
Abstract: Derailed cytokine and immune cell networks account for the organ damage and the clinical severity of COVID-19 (refs. 1–4). Here we show that SARS-CoV-2, like other viruses, evokes cellular senescence as a primary stress response in infected cells. Virus-induced senescence (VIS) is indistinguishable from other forms of cellular senescence and is accompanied by a senescence-associated secretory phenotype (SASP), which comprises pro-inflammatory cytokines, extracellular-matrix-active factors and pro-coagulatory mediators5–7. Patients with COVID-19 displayed markers of senescence in their airway mucosa in situ and increased serum levels of SASP factors. In vitro assays demonstrated macrophage activation with SASP-reminiscent secretion, complement lysis and SASP-amplifying secondary senescence of endothelial cells, which mirrored hallmark features of COVID-19 such as macrophage and neutrophil infiltration, endothelial damage and widespread thrombosis in affected lung tissue1,8,9. Moreover, supernatant from VIS cells, including SARS-CoV-2-induced senescence, induced neutrophil extracellular trap formation and activation of platelets and the clotting cascade. Senolytics such as navitoclax and a combination of dasatinib plus quercetin selectively eliminated VIS cells, mitigated COVID-19-reminiscent lung disease and reduced inflammation in SARS-CoV-2-infected hamsters and mice. Our findings mark VIS as a pathogenic trigger of COVID-19-related cytokine escalation and organ damage, and suggest that senolytic targeting of virus-infected cells is a treatment option against SARS-CoV-2 and perhaps other viral infections. Virus-induced senescence is a central pathogenic feature in COVID-19, and senolytics, which promote apoptosis of senescent cells, can reduce disease severity in hamsters,mice, as well as humans infected with SARS-CoV-2.
139 citations
TL;DR: The authors present the results from a structured review of the literature, identifying and analyzing the most quoted and dominant definitions of social media and alternative terms that were used between 1994 and 2019 to identify their major applications.
Abstract: In this article, the authors present the results from a structured review of the literature, identifying and analyzing the most quoted and dominant definitions of social media (SM) and alternative ...
112 citations
University of Florida1, University of Rochester2, Stanford University3, University of Chicago4, Food and Drug Administration5, Buck Institute for Research on Aging6, Henry Ford Hospital7, University of Minnesota8, Queen Mary University of London9, National Technical University of Athens10, University of Nantes11, University of Texas Southwestern Medical Center12, Virginia Commonwealth University13, Charité14, Johannes Kepler University of Linz15, Mayo Clinic16, Vanderbilt University17, Memorial Sloan Kettering Cancer Center18, Imperial College London19, Indiana University20, University of Texas Health Science Center at San Antonio21
TL;DR: In this article, the authors provided a summary of the discussion at the National Cancer Institute Workshop on Radiation, Senescence, and Cancer (August 10-11, 2020), which focused on the current status of cellular senescence research, heterogeneity of therapy-induced cellular cell-senescence and molecular biomarkers, and a concept of "one-two-punch" cancer therapy.
Abstract: Cellular senescence is an essential tumor suppressive mechanism that prevents the propagation of oncogenically activated, genetically unstable, and/or damaged cells Induction of tumor cell senescence is also one of the underlying mechanisms by which cancer therapies exert antitumor activity However, an increasing body of evidence from preclinical studies demonstrates that radiation and chemotherapy cause accumulation of senescent cells (SnCs) both in tumor and normal tissue SnCs in tumors can, paradoxically, promote tumor relapse, metastasis, and resistance to therapy, in part, through expression of the senescence-associated secretory phenotype In addition, SnCs in normal tissue can contribute to certain radiation- and chemotherapy-induced side effects Because of its multiple roles, cellular senescence could serve as an important target in the fight against cancer This commentary provides a summary of the discussion at the National Cancer Institute Workshop on Radiation, Senescence, and Cancer (August 10-11, 2020, National Cancer Institute, Bethesda, MD) regarding the current status of senescence research, heterogeneity of therapy-induced senescence, current status of senotherapeutics and molecular biomarkers, a concept of "one-two punch" cancer therapy (consisting of therapeutics to induce tumor cell senescence followed by selective clearance of SnCs), and its integration with personalized adaptive tumor therapy It also identifies key knowledge gaps and outlines future directions in this emerging field to improve treatment outcomes for cancer patients
100 citations
TL;DR: This study proposes two Multi-Timescale LSTM (MTS-LSTM) architectures that jointly predict multiple timescales within one model, as they process long-past inputs at a single temporal resolution and branch out into each individual timescale for more recent input steps.
Abstract: . Long Short-Term Memory (LSTM) networks have been applied to daily discharge prediction with remarkable success.
Many practical applications, however, require predictions at more granular timescales.
For instance, accurate prediction of short but extreme flood peaks can make a lifesaving difference, yet such peaks may escape the coarse temporal resolution of daily predictions.
Naively training an LSTM on hourly data, however, entails very long input sequences that make learning difficult and computationally expensive.
In this study, we propose two multi-timescale LSTM (MTS-LSTM) architectures that jointly predict multiple timescales within one model, as they process long-past inputs at a different temporal resolution than more recent inputs.
In a benchmark on 516 basins across the continental United States, these models achieved significantly higher Nash–Sutcliffe efficiency (NSE) values than the US National Water Model.
Compared to naive prediction with distinct LSTMs per timescale, the multi-timescale architectures are computationally more efficient with no loss in accuracy.
Beyond prediction quality, the multi-timescale LSTM can process different input variables at different timescales, which is especially relevant to operational applications where the lead time of meteorological forcings depends on their temporal resolution.
95 citations
TL;DR: This article offers a critical review of systematic literature reviews published in the Academy of Management Annals and the International Journal of Management Reviews between 2004 and 2018 and identifies several descriptive features such as the mean number of research items included in systematic reviews, themean number of databases used, and the mean coverage period of such reviews.
Abstract: Systematic review techniques are about to become the “new normal” in reviews of management research. However, there is not yet much advice on how to organize the sample selection process as part of...
94 citations
TL;DR: This review outlines the rise of sustainable materials in soft and bioinspired robotics, targeting all robotic components from actuators to energy storage and electronics, and outlines the first steps initiate the evolution of robotics and guide them into a sustainable future.
Abstract: The advancement of technology has a profound and far-reaching impact on the society, now penetrating all areas of life. From cradle to grave, one is supported by and depends on a wide range of electronic and robotic appliances, with an ever more intimate integration of the digital and biological spheres. These advances, however, often come at the price of negatively impacting our ecosystem, with growing demands on energy, contributions to greenhouse gas emissions and environmental pollution-from production to improper disposal. Mitigating these adverse effects is among the grand challenges of the society and at the forefront of materials research. The currently emerging forms of soft, biologically inspired electronics and robotics have the unique potential of becoming not only like their natural antitypes in performance and capabilities, but also in terms of their ecological footprint. This review outlines the rise of sustainable materials in soft and bioinspired robotics, targeting all robotic components from actuators to energy storage and electronics. The state-of-the-art in biobased robotics spans flourishing fields and applications ranging from microbots operating in vivo to biohybrid machines and fully biodegradable yet resilient actuators. These first steps initiate the evolution of robotics and guide them into a sustainable future.
89 citations
TL;DR: In this article, the authors study the performance of classical and quantum machine learning (ML) models in predicting outcomes of physical experiments and show that for any input distribution D(x), a classical ML model can provide accurate predictions on average by accessing E a number of times comparable to the optimal quantum ML model.
Abstract: We study the performance of classical and quantum machine learning (ML) models in predicting outcomes of physical experiments. The experiments depend on an input parameter x and involve execution of a (possibly unknown) quantum process E. Our figure of merit is the number of runs of E required to achieve a desired prediction performance. We consider classical ML models that perform a measurement and record the classical outcome after each run of E, and quantum ML models that can access E coherently to acquire quantum data; the classical or quantum data are then used to predict the outcomes of future experiments. We prove that for any input distribution D(x), a classical ML model can provide accurate predictions on average by accessing E a number of times comparable to the optimal quantum ML model. In contrast, for achieving an accurate prediction on all inputs, we prove that the exponential quantum advantage is possible. For example, to predict the expectations of all Pauli observables in an n-qubit system ρ, classical ML models require 2^{Ω(n)} copies of ρ, but we present a quantum ML model using only O(n) copies. Our results clarify where the quantum advantage is possible and highlight the potential for classical ML models to address challenging quantum problems in physics and chemistry.
02 Mar 2021
TL;DR: This work compares six different GNN-based generative models in GraphINVENT, and shows that ultimately the gated-graph neural network performs best against the metrics considered here.
Abstract: Deep learning methods applied to chemistry can be used to accelerate the discovery of new molecules. This work introduces GraphINVENT, a platform developed for graph-based molecular design using graph neural networks (GNNs). GraphINVENT uses a tiered deep neural network architecture to probabilistically generate new molecules a single bond at a time. All models implemented in GraphINVENT can quickly learn to build molecules resembling the training set molecules without any explicit programming of chemical rules. The models have been benchmarked using the MOSES distribution-based metrics, showing how GraphINVENT models compare well with state-of-the-art generative models. This work is one of the first thorough graph-based molecular design studies, and illustrates how GNN-based models are promising tools for molecular discovery.
TL;DR: Investigation of the presence of SARS-CoV-2 RNA in different organs in correlation with tissue damage and post-mortem viral dynamics in COVID-19 deceased found viral RNA was detected more frequently in the lungs and throat than in the intestine.
Abstract: The persistence of SARS-CoV-2 after death of infected individuals is unclear. The aim of this study was to investigate the presence of SARS-CoV-2 RNA in different organs in correlation with tissue damage and post-mortem viral dynamics in COVID-19 deceased. Twenty-eight patients (17 males, 11 females; age 66–96 years; mean 82.9, median 82.5 years) diagnosed with COVID-19 were studied. Swabs were taken post-mortem during autopsy (N = 19) from the throat, both lungs, intestine, gallbladder, and brain or without autopsy (N = 9) only from the throat. Selective amplification of target nucleic acid from the samples was achieved by using primers for ORF1a/b non-structural region and the structural protein envelope E-gene of the virus. The results of 125 post-mortem and 47 ante-mortem swabs were presented as cycle threshold (Ct) values and categorized as strong, moderate, and weak. Viral RNA was detected more frequently in the lungs and throat than in the intestine. Blood, bile, and the brain were negative. Consecutive throat swabs were positive up to 128 h after death without significant increase of Ct values. All lungs showed diffuse alveolar damage, thrombosis, and infarction and less frequently bronchopneumonia irrespective of Ct values. In 30% the intestine revealed focal ischemic changes. Nucleocapsid protein of SARS-CoV-2 was detected by immunohistochemistry in bronchial and intestinal epithelium, bronchial glands, and pneumocytes. In conclusion, viral RNA is still present several days after death, most frequently in the respiratory tract and associated with severe and fatal organ damage. Potential infectivity cannot be ruled out post-mortem.
TL;DR: The potential of combining AFM with optical microscopy and spectroscopy to address the full complexity of biological systems and to tackle fundamental challenges in life sciences is highlighted.
Abstract: During the last three decades, a series of key technological improvements turned atomic force microscopy (AFM) into a nanoscopic laboratory to directly observe and chemically characterize molecular and cell biological systems under physiological conditions. Here, we review key technological improvements that have established AFM as an analytical tool to observe and quantify native biological systems from the micro- to the nanoscale. Native biological systems include living tissues, cells, and cellular components such as single or complexed proteins, nucleic acids, lipids, or sugars. We showcase the procedures to customize nanoscopic chemical laboratories by functionalizing AFM tips and outline the advantages and limitations in applying different AFM modes to chemically image, sense, and manipulate biosystems at (sub)nanometer spatial and millisecond temporal resolution. We further discuss theoretical approaches to extract the kinetic and thermodynamic parameters of specific biomolecular interactions detected by AFM for single bonds and extend the discussion to multiple bonds. Finally, we highlight the potential of combining AFM with optical microscopy and spectroscopy to address the full complexity of biological systems and to tackle fundamental challenges in life sciences.
TL;DR: A diverse body of research is found, particularly for the varying content characteristics that affect engagement, yet without any conclusive results, and potential confounding effects causing such diverging results are highlighted.
Abstract: We present a review of N = 45 studies, which deals with the effect of characteristics of social media content (e.g., topic or length) on behavioral engagement. In addition, we reviewed the possibility of a mediating effect of emotional responses in this context (e.g., arousing content has been shown to increase engagement behavior). We find a diverse body of research, particularly for the varying content characteristics that affect engagement, yet without any conclusive results. We therefore also highlight potential confounding effects causing such diverging results for the relationship between content characteristics and content engagement. We find no study that evaluates the mediating effect of emotional responses in the content—engagement relationship and therefore call for further investigations. In addition, future research should apply an extended communication model adapted for the social media context to guarantee rigorous research.
TL;DR: In order to challenge high working temperature, low response and low selectivity of present NO2 sensor, porous SnO2 nanotoasts with a large surface area (79.94 m2/g) were synthesized as mentioned in this paper.
Johannes Kepler University of Linz1, Linköping University2, Karolinska University Hospital3, Loyola University Chicago4, Veterans Health Administration5, National Institutes of Health6, Agency for Science, Technology and Research7, McMaster University8, University of Cambridge9, Innsbruck Medical University10
Abstract: Patients with kidney diseases should be prioritized for COVID-19 vaccination and the available data suggest that replication-defective viral-vectored vaccines and mRNA vaccines are safe to use. As vaccine responses are likely to be lower in patients with kidney diseases than in the general population, highly potent vaccines should be preferred.
University of Amsterdam1, University of Lisbon2, University of Tübingen3, University of Bern4, Radboud University Nijmegen5, National Institute for Health Research6, Albert Schweitzer Hospital7, University of Helsinki8, University of British Columbia9, National and Kapodistrian University of Athens10, University Hospital Heidelberg11, University of Gothenburg12, Sahlgrenska University Hospital13, Imperial College London14, Mater Misericordiae University Hospital15, University of Medicine and Health Sciences16, University College Dublin17, Hannover Medical School18, Hamilton General Hospital19, University of La Laguna20, Northumbria Healthcare NHS Foundation Trust21, University of Alberta Hospital22, John Hunter Hospital23, François Rabelais University24, McGill University Health Centre25, Leipzig University26, Ottawa Hospital27, Umeå University28, University of Toulouse29, University of Messina30, University Hospital Bonn31, Lyon College32, Caritas Hospital33, Ashford University34, Agostino Gemelli University Polyclinic35, Princess Alexandra Hospital36, Toronto General Hospital37, Surrey Memorial Hospital38, University of Ulm39, Johannes Kepler University of Linz40, University of Porto41, Oslo University Hospital42, Leiden University43, Royal Holloway, University of London44, Foothills Medical Centre45, University of Edinburgh46, University Hospital Southampton NHS Foundation Trust47, Medical University of Graz48, University of Kiel49, Royal Adelaide Hospital50
TL;DR: In this article, the authors describe the clinical characteristics and outcome of patients with cerebral venous sinus thrombosis (CVST) after SARS-CoV-2 vaccination with and without TTS.
Abstract: Importance Thrombosis with thrombocytopenia syndrome (TTS) has been reported after vaccination with the SARS-CoV-2 vaccines ChAdOx1 nCov-19 (Oxford–AstraZeneca) and Ad26.COV2.S (Janssen/Johnson & Johnson). Objective To describe the clinical characteristics and outcome of patients with cerebral venous sinus thrombosis (CVST) after SARS-CoV-2 vaccination with and without TTS. Design, Setting, and Participants This cohort study used data from an international registry of consecutive patients with CVST within 28 days of SARS-CoV-2 vaccination included between March 29 and June 18, 2021, from 81 hospitals in 19 countries. For reference, data from patients with CVST between 2015 and 2018 were derived from an existing international registry. Clinical characteristics and mortality rate were described for adults with (1) CVST in the setting of SARS-CoV-2 vaccine–induced immune thrombotic thrombocytopenia, (2) CVST after SARS-CoV-2 vaccination not fulling criteria for TTS, and (3) CVST unrelated to SARS-CoV-2 vaccination. Exposures Patients were classified as having TTS if they had new-onset thrombocytopenia without recent exposure to heparin, in accordance with the Brighton Collaboration interim criteria. Main Outcomes and Measures Clinical characteristics and mortality rate. Results Of 116 patients with postvaccination CVST, 78 (67.2%) had TTS, of whom 76 had been vaccinated with ChAdOx1 nCov-19; 38 (32.8%) had no indication of TTS. The control group included 207 patients with CVST before the COVID-19 pandemic. A total of 63 of 78 (81%), 30 of 38 (79%), and 145 of 207 (70.0%) patients, respectively, were female, and the mean (SD) age was 45 (14), 55 (20), and 42 (16) years, respectively. Concomitant thromboembolism occurred in 25 of 70 patients (36%) in the TTS group, 2 of 35 (6%) in the no TTS group, and 10 of 206 (4.9%) in the control group, and in-hospital mortality rates were 47% (36 of 76; 95% CI, 37-58), 5% (2 of 37; 95% CI, 1-18), and 3.9% (8 of 207; 95% CI, 2.0-7.4), respectively. The mortality rate was 61% (14 of 23) among patients in the TTS group diagnosed before the condition garnered attention in the scientific community and 42% (22 of 53) among patients diagnosed later. Conclusions and Relevance In this cohort study of patients with CVST, a distinct clinical profile and high mortality rate was observed in patients meeting criteria for TTS after SARS-CoV-2 vaccination.
TL;DR: A general novel methodology, scaled polynomial constant unit activation function “SPOCU,” is introduced and shown to work satisfactorily on a variety of problems, and it is shown that SPOCU can overcome already introduced activation functions with good properties on generic problems.
Abstract: We address the following problem: given a set of complex images or a large database, the numerical and computational complexity and quality of approximation for neural network may drastically differ from one activation function to another. A general novel methodology, scaled polynomial constant unit activation function “SPOCU,” is introduced and shown to work satisfactorily on a variety of problems. Moreover, we show that SPOCU can overcome already introduced activation functions with good properties, e.g., SELU and ReLU, on generic problems. In order to explain the good properties of SPOCU, we provide several theoretical and practical motivations, including tissue growth model and memristive cellular nonlinear networks. We also provide estimation strategy for SPOCU parameters and its relation to generation of random type of Sierpinski carpet, related to the [pppq] model. One of the attractive properties of SPOCU is its genuine normalization of the output of layers. We illustrate SPOCU methodology on cancer discrimination, including mammary and prostate cancer and data from Wisconsin Diagnostic Breast Cancer dataset. Moreover, we compared SPOCU with SELU and ReLU on large dataset MNIST, which justifies usefulness of SPOCU by its very good performance.
TL;DR: A reset protocol is reported that returns a qubit to the ground state from all relevant higher level states and finds lower rates of logical errors and an improved scaling and stability of error suppression with increasing qubit number.
Abstract: Quantum computing can become scalable through error correction, but logical error rates only decrease with system size when physical errors are sufficiently uncorrelated. During computation, unused high energy levels of the qubits can become excited, creating leakage states that are long-lived and mobile. Particularly for superconducting transmon qubits, this leakage opens a path to errors that are correlated in space and time. Here, we report a reset protocol that returns a qubit to the ground state from all relevant higher level states. We test its performance with the bit-flip stabilizer code, a simplified version of the surface code for quantum error correction. We investigate the accumulation and dynamics of leakage during error correction. Using this protocol, we find lower rates of logical errors and an improved scaling and stability of error suppression with increasing qubit number. This demonstration provides a key step on the path towards scalable quantum computing.
TL;DR: In this article, a mixed-method approach, comprising of a literature review and quantitative analyses of 150 German mid-sized firms in the engineering industry, is demonstrated how ambidexterity, exploration and exploitation, in conjunction with strategic agility, affect the competitive advantage of firms.
TL;DR: In this article, a systematischen Uberblick uber den quantitativen Forschungsstand zur Schulsituation and zum Lehren and Lernen wahrend the Corona-Pandemie is presented.
Abstract: Der Review gibt einen systematischen Uberblick uber den quantitativen Forschungsstand zur Schulsituation und zum Lehren und Lernen wahrend der Corona-Pandemie. Der Review umfasst 97 Online-Befragungen, die in der Zeit vom 24. Marz 2020 bis 11. November 2020 durchgefuhrt wurden und 255.955 Falle (Schuler*innen, Eltern, Lehrkrafte, Schulleitungen u. a.) erfassten. Die Analyse und Synthese der Befunde erfolgt entlang zweier Modelle, dem Phasenmodell des Forschungsprozesses und einem integrativen Modell zur Distance Education. Der Review macht deutlich, dass zentrale Aspekte des Lehrens und Lernens wahrend den coronabedingten Schulschliesungen im Fruhjahr 2020, wie bspw. Merkmale des Fernunterrichts (z. B. Qualitatsdimensionen), Schulermerkmale (z. B. Selbstandigkeit) und Merkmale der hauslichen Ressourcen fur das Lernen (z. B. die elterliche Unterstutzung), bereits Gegenstand vieler Befragungen waren. Die Schulsituation wahrend der Corona-Pandemie stellt daher kein unerforschtes Phanomen mehr dar. Vielmehr fordert das wissenschaftliche Ethos von Forscher*innen dieses Feldes, den aktuellen Forschungsstand in ihren Arbeiten zu berucksichtigen. Der vorgelegte Review soll diese Aufgabe erleichtern, indem nicht nur die existierenden Befragungen gelistet, sondern deren zentrale Erkenntnisse synthetisiert werden. Daruber hinaus liefert der Review eine relevante Informationsbasis fur Entscheidungen und fur das Handeln in den jeweiligen Verantwortungsbereichen der Politik, Verwaltung und Schulpraxis. Gleichzeitig warnt der Review vor einer unreflektierten Ubernahme der Befunde, indem die wissenschaftliche Qualitat der Befragungen kritisch diskutiert wird.
TL;DR: In this article, an efficient derandomization procedure that iteratively replaces random single-qubit measurements by fixed Pauli measurements was proposed, and the resulting deterministic measurement procedure is guaranteed to perform at least as well as the randomized one.
Abstract: We consider the problem of jointly estimating expectation values of many Pauli observables, a crucial subroutine in variational quantum algorithms. Starting with randomized measurements, we propose an efficient derandomization procedure that iteratively replaces random single-qubit measurements by fixed Pauli measurements; the resulting deterministic measurement procedure is guaranteed to perform at least as well as the randomized one. In particular, for estimating any $L$ low-weight Pauli observables, a deterministic measurement on only of order $\mathrm{log}(L)$ copies of a quantum state suffices. In some cases, for example, when some of the Pauli observables have high weight, the derandomized procedure is substantially better than the randomized one. Specifically, numerical experiments highlight the advantages of our derandomized protocol over various previous methods for estimating the ground-state energies of small molecules.
TL;DR: In this paper, the authors have analyzed how loop extrusion is mediated by human cohesin-NIPBL complexes, which enable chromatin folding in interphase cells, and they have identified DNA binding sites and large-scale conformational changes that are required for loop extrusions and determined how these are coordinated.
Innsbruck Medical University1, Leiden University Medical Center2, The Catholic University of America3, First Faculty of Medicine, Charles University in Prague4, Copenhagen University Hospital5, University of Cologne6, University College London7, Institut Gustave Roussy8, Agostino Gemelli University Polyclinic9, Imperial College London10, University of Navarra11, Johannes Kepler University of Linz12, Erasmus University Rotterdam13, Humboldt University of Berlin14, Charité15, Medical University of Vienna16, The Royal Marsden NHS Foundation Trust17, University of Amsterdam18, Dresden University of Technology19, European Institute of Oncology20, Hospital Universitari Arnau de Vilanova21
TL;DR: A European consensus conference on endometrial carcinoma was held in 2014 to produce multidisciplinary evidence-based guidelines on selected questions as discussed by the authors, and the authors of the guidelines are based on the best available evidence and expert agreement.
Abstract: A European consensus conference on endometrial carcinoma was held in 2014 to produce multidisciplinary evidence-based guidelines on selected questions. Given the large body of literature on the management of endometrial carcinoma published since 2014, the European Society of Gynaecological Oncology (ESGO), the European SocieTy for Radiotherapy & Oncology (ESTRO) and the European Society of Pathology (ESP) jointly decided to update these evidence-based guidelines and to cover new topics in order to improve the quality of care for women with endometrial carcinoma across Europe and worldwide. ESGO/ESTRO/ESP nominated an international multidisciplinary development group consisting of practicing clinicians and researchers who have demonstrated leadership and expertise in the care and research of endometrial carcinoma (27 experts across Europe). To ensure that the guidelines are evidence-based, the literature published since 2014, identified from a systematic search was reviewed and critically appraised. In the absence of any clear scientific evidence, judgment was based on the professional experience and consensus of the development group. The guidelines are thus based on the best available evidence and expert agreement. Prior to publication, the guidelines were reviewed by 191 independent international practitioners in cancer care delivery and patient representatives. The guidelines comprehensively cover endometrial carcinoma staging, definition of prognostic risk groups integrating molecular markers, pre- and intra-operative work-up, fertility preservation, management for early, advanced, metastatic, and recurrent disease and palliative treatment. Principles of radiotherapy and pathological evaluation are also defined.
TL;DR: P-type MnSb2 Te4, previously considered topologically trivial, is shown to be a ferromagnetic topological insulator for a few percent Mn excess and a critical exponent of the magnetization β ≈ 1 is found, indicating the vicinity of a quantum critical point.
Abstract: Ferromagnetic topological insulators exhibit the quantum anomalous Hall effect, which is potentially useful for high-precision metrology, edge channel spintronics, and topological qubits. The stable 2+ state of Mn enables intrinsic magnetic topological insulators. MnBi2Te4 is, however, antiferromagnetic with 25 K Neel temperature and is strongly n-doped. In this work, p-type MnSb2Te4, previously considered topologically trivial, is shown to be a ferromagnetic topological insulator for a few percent Mn excess. i) Ferromagnetic hysteresis with record Curie temperature of 45-50 K, ii) out-of-plane magnetic anisotropy, iii) a 2D Dirac cone with the Dirac point close to the Fermi level, iv) out-of-plane spin polarization as revealed by photoelectron spectroscopy, and v) a magnetically induced bandgap closing at the Curie temperature, demonstrated by scanning tunneling spectroscopy (STS), are shown. Moreover, a critical exponent of the magnetization beta approximate to 1 is found, indicating the vicinity of a quantum critical point. Ab initio calculations reveal that Mn-Sb site exchange provides the ferromagnetic interlayer coupling and the slight excess of Mn nearly doubles the Curie temperature. Remaining deviations from the ferromagnetic order open the inverted bulk bandgap and render MnSb2Te4 a robust topological insulator and new benchmark for magnetic topological insulators.
TL;DR: In this paper, an adapting H-infinity controller is introduced as the combination of the adapting and Hinfinity strategies for the desired reference tracking of the sphere position in the Maglev process.
RWTH Aachen University1, Technische Universität München2, Johannes Kepler University of Linz3, University of Bern4, University Health System5, Yonsei University6, The Royal Marsden NHS Foundation Trust7, University College London8, University of Leeds9, St James's University Hospital10, Augsburg College11, University of Siena12, University of Chicago13, University of Düsseldorf14, Heidelberg University15, University Hospital Heidelberg16
TL;DR: In this article, a deep learning-based classifier was used to detect microsatellite instability and Epstein-Barr virus (EBV) positivity from histology slides without annotating tumour containing regions.
Abstract: Summary Background Response to immunotherapy in gastric cancer is associated with microsatellite instability (or mismatch repair deficiency) and Epstein-Barr virus (EBV) positivity. We therefore aimed to develop and validate deep learning-based classifiers to detect microsatellite instability and EBV status from routine histology slides. Methods In this retrospective, multicentre study, we collected tissue samples from ten cohorts of patients with gastric cancer from seven countries (South Korea, Switzerland, Japan, Italy, Germany, the UK and the USA). We trained a deep learning-based classifier to detect microsatellite instability and EBV positivity from digitised, haematoxylin and eosin stained resection slides without annotating tumour containing regions. The performance of the classifier was assessed by within-cohort cross-validation in all ten cohorts and by external validation, for which we split the cohorts into a five-cohort training dataset and a five-cohort test dataset. We measured the area under the receiver operating curve (AUROC) for detection of microsatellite instability and EBV status. Microsatellite instability and EBV status were determined to be detectable if the lower bound of the 95% CI for the AUROC was above 0·5. Findings Across the ten cohorts, our analysis included 2823 patients with known microsatellite instability status and 2685 patients with known EBV status. In the within-cohort cross-validation, the deep learning-based classifier could detect microsatellite instability status in nine of ten cohorts, with AUROCs ranging from 0·597 (95% CI 0·522–0·737) to 0·836 (0·795–0·880) and EBV status in five of eight cohorts, with AUROCs ranging from 0·819 (0·752–0·841) to 0·897 (0·513–0·966). Training a classifier on the pooled training dataset and testing it on the five remaining cohorts resulted in high classification performance with AUROCs ranging from 0·723 (95% CI 0·676–0·794) to 0·863 (0·747–0·969) for detection of microsatellite instability and from 0·672 (0·403–0·989) to 0·859 (0·823–0·919) for detection of EBV status. Interpretation Classifiers became increasingly robust when trained on pooled cohorts. After prospective validation, this deep learning-based tissue classification system could be used as an inexpensive predictive biomarker for immunotherapy in gastric cancer. Funding German Cancer Aid and German Federal Ministry of Health.
TL;DR: A notion of fairness based on the performance gap of a RS between the users with different demographics is defined, and a variety of collaborative filtering algorithms are evaluated in terms of accuracy and beyond-accuracy metrics to explore the fairness in the RS results toward a specific gender group.
Abstract: Although recommender systems (RSs) play a crucial role in our society, previous studies have revealed that the performance of RSs may considerably differ between groups of individuals with different characteristics or from different demographics. In this case, a RS is considered to be unfair when it does not perform equally well for different groups of users. Considering the importance of RSs in the distribution and consumption of musical content worldwide, a careful evaluation of fairness in the context of music RSs is crucial. To this end, we first introduce LFM-2b, a novel large-scale real-world dataset of music listening records, comprising a subset to investigate bias of RSs regarding users’ demographics. We then define a notion of fairness based on the performance gap of a RS between the users with different demographics, and evaluate a variety of collaborative filtering algorithms in terms of accuracy and beyond-accuracy metrics to explore the fairness in the RS results toward a specific gender group. We observe the existence of significant discrepancies (unfairness) between the performance of algorithms across male and female user groups. Based on these discrepancies, we explore to what extent recommender algorithms lead to intensifying the underlying population bias in the final results. We also study the effect of a resampling strategy, commonly used as debiasing method , which yields slight improvements in the fairness measures of various algorithms while maintaining their accuracy and beyond-accuracy performance.