cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
A Multibody Dynamic Analysis of a Motorcycle with a Multilink Front Suspension
Creators: name: Minaker, Bruce
name: Durfy, Bruce
Publisher: name: figshare
Year: 2016
Subjects: subject: 91106 Special Vehicles
subject: FOS: Environmental engineering
subject: 91304 Dynamics, Vibration and Vibration Control
subject: FOS: Mechanical engineering
subject: Mechanical Engineering

description: The paper describes a novel multilink motorcycle front suspension concept that separates the steering and suspension kinematics, and explores its dynamic behaviour to determine its potential performance improvement over a conventional telescopic fork suspension, or other linkage based designs. The suspension mechanism described in the current paper is, to the best of the authors’ knowledge, novel and unused, and presents a number of design advantages. The paper provides a detailed description of the front suspension mechanism, and explores the effect of the mechanism geometry on the overall dynamic behaviour. The pitch centre location and pitch response to braking, the frequency response, and the modal analysis are all considered.
How does silica affect Fe(II)-catalysed transformation of ferrihydrite and lepidocrocite?
Creators: name: Schulz, Katrin
name: Thomas Arrigo, Laurel K.
name: Rothwell, Katherine A.
name: Kretzschmar, Ruben
Publisher: name: ETH Zurich
Year: 2020

description: Ferric iron (Fe(III)) minerals, such as ferrihydrite and lepidocrocite, can be reduced to ferrous iron (Fe(II)) through microbial reductive dissolution under reducing soil conditions, to form dissolved Fe(II) or mixed Fe(II)-Fe(III) mineral phases. The dissolved Fe(II) catalyses iron mineral transformation to more crystalline iron phases. Silica (Si), in the form of silicic acid, is an ubiquitous component of natural soil solutions and is known to hinder the iron mineral transformation process. However, the mechanisms and the mineral phases that are formed during ferrihydrite and lepidocrocite transformation in the presence of Si remain unclear. We reacted ferrihydrite, Si-ferrihydrite co-precipitates, lepidocrocite and Si-adsorbed lepidocrocite with 0.3 mM and 3 mM isotopically labelled 57Fe(II) for four weeks. At six time points, we sampled the solid and the aqueous phase, to follow iron mineral transformation by X-ray diffraction and dissolved Fe(II) dynamics. In addition, we tracked the iron atom exchange between the aqueous and the solid phase by measuring the 57/56Fe isotope ratio in filtrates and dissolved solid phases. Our data demonstrates the hindering effect of Si on Fe(II) catalysed ferrihydrite and lepidocrocite transformation. The presence of Si decreased the initial Fe(II) adsorption and strongly slowed down the iron atom exchange, especially in the lepidocrocite treatment. Collectively, the results of this study demonstrate, how Si can impact iron mineral transformation in soils with different Fe(II) release potentials under reducing conditions.
description: EGUsphere
Transitioning to No Poverty
Creators: name: Günther, Isabel
name: Lahoti, Rahul
Publisher: name: ETH Zurich
Year: 2021

description: Transitioning to No Poverty is part of MDPI's new Open Access book series Transitioning to Sustainability. With this series, MDPI pursues environmentally and socially relevant research which contributes to efforts toward a sustainable world. Transitioning to Sustainability aims to add to the conversation about regional and global sustainable development according to the 17 SDGs. Set to be published in 2020/2021, the book series is intended to reach beyond disciplinary, even academic boundaries.
description: Transitioning to Sustainability, 1
description: ISSN:2624-9324
description: ISSN:2624-9332
description: ISBN:978-3-03897-860-2
description: ISBN:978-3-03897-861-9
Reduced order modelling of large finite element structures with geometric and contact nonlinearities: application to blade-casing interaction in aircraft engines
Creators: name: Vizzaccaro, Alessandra
Publisher: name: Imperial College London
Year: 2021

description: The numerical simulation of structural vibration of aircraft engines components is of crucial importance for engine manufacturers both in the design stage and in the assessment of failures. Protracted vibration of rotor blades shortens their lives and might cause blade failure due to high cycle fatigue. To ensure the structural integrity of blades, accurate predictions of their dynamic behaviour are necessary. In this respect, numerical models based on linear approximations are no longer representative of the actual behaviour of the blade that is affected by several nonlinear forces. Finite element models of blades are usually large models with a high number of degrees of freedom and complex geometry. To compute the nonlinear dynamic behaviour of blade in a fast yet accurate manner, reduced order models are necessary. The main focus of this thesis is the assessment and investigation of reduced order modelling methods for geometrically nonlinear structures. It will be shown that reduced order modelling methods based on modal coordinates displays a slow convergence of the basis when applied to structures discretised with three dimensional finite elements. Direct methods based on modal derivatives have instead the advantage of being computed directly in physical basis and the computation of the reduced dynamics can be done non-intrusively from any generic finite element software. However, the applicability of these methods is restricted to the case of a clear separation between the mode of interest and the modes coupled with it through the nonlinear forces. Invariant manifold based methods are instead able to reproduce the correct dynamics even without a slow/fast separation between modes, thanks to the inclusion of velocity dependent terms in the nonlinear mapping. However, invariant manifold methods are based on modal coordinates thus making their applicability limited to relatively small structures. In this work, a direct method fully in physical coordinates able to compute the invariant manifold through normal form is proposed and its capabilities assessed.
MiR-137 and miR-122, two outer subventricular zone-enriched non-coding RNAs, regulate basal progenitor expansion and neuronal differentiation
Creators: name: Tomasello, Ugo
name: Klingler, Esther
name: Niquille, Mathieu
name: Mule, Nandkishor
name: de Vevey, Laura
name: Prados, Julien
name: Santinha, António J.
name: Platt, Randall
name: Borrell, Victor
name: Jabaudon, Denis
name: Dayer, Alexandre
Publisher: name: ETH Zurich
Year: 2021

description: bioRxiv
Relational VAE: A Continuous Latent Variable Model for Graph Structured Data
Creators: name: Mylonas, Charilaos
name: Abdallah, Imad
name: Chatzi, Eleni
Publisher: name: ETH Zurich
Year: 2021

description: Graph Networks (GNs) enable the fusion of prior knowledge and relational reasoning with flexible function approximations. In this work, a general GN-based model is proposed which takes full advantage of the relational modeling capabilities of GNs and extends these to probabilistic modeling with Variational Bayes (VB). To that end, we combine complementary pre-existing approaches on VB for graph data and propose an approach that relies on graph-structured latent and conditioning variables. It is demonstrated that Neural Processes can also be viewed through the lens of the proposed model. We show applications on the problem of structured probability density modeling for simulated and real wind farm monitoring data, as well as on the meta-learning of simulated Gaussian Process data. We release the source code, along with the simulated datasets.
description: arXiv
Diagnostic potential of the mid-infrared space interferometer LIFE for studying Earth analogues
Creators: name: Alei, Eleonora
name: Konrad, Björn
name: Mollière, Paul
name: Quanz, Sascha Patrick
name: Angerhausen, Daniel
name: LIFE Collaboration
Publisher: name: ETH Zurich
Year: 2021

description: EPSC Abstracts, 15
Atmospheric Retrieval of Cloudy Venus-Twin Exoplanets in the Context of the LIFE Mission
Creators: name: Konrad, Björn
name: Alei, Eleonora
name: Angerhausen, Daniel
name: Quanz, Sascha Patrick
name: LIFE Collaboration
Publisher: name: ETH Zurich
Year: 2021

description: EPSC Abstracts, 15
Fairleigh Dickinson University's PublicMind Poll: New Jersey March 2013
Creators: name: Fairleigh Dickinson University's PublicMind
Publisher: name: Roper Center for Public Opinion Research
Year: 2020

description: Registered to vote (1); President Barack Obama job approval (1); country right direction/wrong track (1); New Jersey Governor Chris Christie job approval (1); New Jersey right direction/wrong track (1); vote for Governor Christie vs. NJ Senator Barbara Buono in election for governor (1); vote for Mayor Cory Booker vs. Geraldo Rivera for United States Senate (1); Christie likeability and policies (1); Medicaid expansion (2); Christie changed how government is run in New Jersey (1); aftermath of Hurricane Sandy (4); online gambling in New Jersey (3); federal regulation of gambling (3); trust in cable news sources (2) which Democrat would you like to see elected to United States Senate (1); own or rent (1); public employee pension system membership (1); casino or slots visit in past 12 months (2); sports bet or office pool in last 12 months (1).
Dynamics of Palaeclimates. Lecture 1 : The complex climate system: a range of time scales
Creators: name: Crucifix, Michel
Publisher: name: figshare
Year: 2016
Subjects: Climate Science

description: Lecture given at the Autumn school : "Dynamics of natural (eco)-systems: theory and applications", organised at the MichaelStifelCenter Jena (Germany), 27 September 2016 (updated on 6th december 2016)
RumbleML: program the lakehouse with JSONiq
Creators: name: Fourny, Ghislain
name: Dao, David
name: Berker Cikis, Can
name: Zhang, Ce
name: Alonso, Gustavo
Publisher: name: ETH Zurich
Year: 2021
Subjects: Database
Query languages
Data lakehouses
JSONiq
Machine learning
Data cleaning

description: Lakehouse systems have reached in the past few years unprecedented size and heterogeneity and have been embraced by many industry players. However, they are often difficult to use as they lack the declarative language and optimization possibilities of relational engines. This paper introduces RumbleML, a high-level, declarative library integrated into the RumbleDB engine and with the JSONiq language. RumbleML allows using a single platform for data cleaning, data preparation, training, and inference, as well as management of models and results. It does it using a purely declarative language (JSONiq) for all these tasks and without any performance loss over existing platforms (e.g. Spark).  
The key insights of the design of RumbleML are that training sets, evaluation sets, and test sets can be represented as homogeneous sequences of flat objects; that models can be seamlessly embodied in function items mapping input test sets into prediction-augmented result sets; and that estimators can be seamlessly embodied in function items mapping input training sets to models. We argue that this makes JSONiq a viable and seamless programming language for data lakehouses across all their features, whether database-related or machine-learning-related. While lakehouses bring Machine Learning and Data Wrangling on the same platform, RumbleML also brings them to the same language, JSONiq. In the paper, we present the first prototype and compare its performance to Spark showing the benefit of a huge functionality and productivity gain for cleaning up, normalizing, validating data, feeding it into Machine Learning pipelines, and analyzing the output, all within the same system and language and at scale.
pmVAE: Learning Interpretable Single-Cell Representations with Pathway Modules
Creators: name: Gut, Gilles
name: Stark, Stefan G.
name: Rätsch, Gunnar
name: Davidson, Natalie R.
Publisher: name: ETH Zurich
Year: 2021

description: Motivation Deep learning techniques have yielded tremendous progress in the field of computational biology over the last decade, however many of these techniques are opaque to the user. To provide interpretable results, methods have incorporated biological priors directly into the learning task; one such biological prior is pathway structure. While pathways represent most biological processes in the cell, the high level of correlation and hierarchical structure make it complicated to determine an appropriate computational representation.Results Here, we present pathway module Variational Autoencoder (pmVAE). Our method encodes pathway information by restricting the structure of our VAE to mirror gene-pathway memberships. Its architecture is composed of a set of subnetworks, which we refer to as pathway modules. The subnetworks learn interpretable latent representations by factorizing the latent space according to pathway gene sets. We directly address correlation between pathways by balancing a module-specific local loss and a global reconstruction loss. Furthermore, since many pathways are by nature hierarchical and therefore the product of multiple downstream signals, we model each pathway as a multidimensional vector. Due to their factorization over pathways, the representations allow for easy and interpretable analysis of multiple downstream effects, such as cell type and biological stimulus, within the contexts of each pathway. We compare pmVAE against two other state-of-the-art methods on two single-cell RNA-seq case-control data sets, demonstrating that our pathway representations are both more discriminative and consistent in detecting pathways targeted by a perturbation.Availability and implementation https://github.com/ratschlab/pmvaeCompeting Interest StatementThe authors have declared no competing interest.
description: bioRxiv
Applying systems thinking to improve “zero deforestation” policies in highly forested tropical countries
Creators: name: Lyons-White, Joss Patrick
Publisher: name: Imperial College London
Year: 2021

description: Tropical deforestation is associated with climate change, biodiversity loss, and the loss of ecosystem services. In response, dozens of companies have adopted commitments to “zero deforestation” when producing agricultural commodities such as palm oil. However, zero deforestation commitments have proven challenging to implement, and inequitable in some situations. Targets set by international coalitions of organisations to achieve zero net deforestation globally by 2020 have been missed. Here, I investigate options for improving the implementation of zero deforestation commitments to support more effective and equitable forest conservation in the palm oil sector. I focus on highly forested countries where zero deforestation commitments can conflict with national development goals involving agriculture. My research applies Critical Systems Heuristics (CSH), a systems thinking methodology that is novel in forest conservation. CSH can help identify options for improving “wicked” problems like tropical deforestation, which are characterised by complexity and diverse perspectives. I begin by reviewing conceptual and practical problems with attaining zero deforestation, before presenting two qualitative case studies examining stakeholders’ perspectives on zero deforestation commitments in Gabon and Liberia. In both cases I apply CSH and focus on the High Carbon Stock Approach, a tool for implementing zero deforestation in palm oil production. I then reflect on the utility of CSH for conservation research. Finally, I review the importance of mixing zero deforestation commitments with complementary mechanisms to reduce deforestation. My research provides the first empirical assessment of zero deforestation commitments’ implementation that focuses on social issues in highly forested countries with emerging palm oil industries. I find that zero deforestation represents an international perspective that marginalises national and local perspectives on sustainable palm oil production. This produces problems with commitments’ legitimacy, equity, and effectiveness. A more flexible and systemic approach is required, if zero deforestation commitments are to effectively and equitably reduce deforestation.
SECEDO: SNV-based subclone detection using ultra-low coverage single-cell DNA sequencing
Creators: name: Rozhoňová, Hana
name: Danciu, Daniel
name: Stark, Stefan
name: Rätsch, Gunnar
name: Kahles, André
name: Lehmann, Kjong-Van
Publisher: name: ETH Zurich
Year: 2021
Subjects: single-cell sequencing
intra-tumor heterogeneity
clustering

description: Recently developed single-cell DNA sequencing technologies enable whole-genome, amplification-free sequencing of thousands of cells at the cost of ultra-low coverage of the sequenced data (< 0.05x per cell), which mostly limits their usage to the identification of copy number alterations (CNAs) in multi-megabase segments. Aside from CNA-based subclone detection, single-nucleotide variant (SNV)-based subclone detection may contribute to a more comprehensive view on intra-tumor heterogeneity. Due to the low coverage of the data, the identification of SNVs is only possible when superimposing the sequenced genomes of hundreds of genetically similar cells. Here we present Single Cell Data Tumor Clusterer (SECEDO, lat. ‘to separate’), a new method to cluster tumor cells based solely on SNVs, inferred on ultra-low coverage single-cell DNA sequencing data. The core aspects of the method are an efficient Bayesian filtering of relevant loci and the exploitation of read overlaps and phasing information. We applied SECEDO to a synthetic dataset simulating 7,250 cells and eight tumor subclones from a single patient, and were able to accurately reconstruct the clonal composition, detecting 92.11% of the somatic SNVs, with the smallest clusters representing only 6.9% of the total population. When applied to four real single-cell sequencing datasets from a breast cancer patient, SECEDO was able to recover the major clonal composition in each dataset at the original sequencing depth of 0.03x per cell, an 8-fold improvement relative to the state of the art. Variant calling on the resulting clusters recovered more than twice as many SNVs with double the allelic ratio compared to calling on all cells together, demonstrating the utility of SECEDO.SECEDO is implemented in C++ and is publicly available at https://github.com/ratschlab/secedo.Competing Interest StatementThe authors have declared no competing interest.
description: bioRxiv
Lossless Indexing with Counting de Bruijn Graphs
Creators: name: Karasikov, Mikhail
name: Mustafa, Harun
name: Rätsch, Gunnar
name: Kahles, André
Publisher: name: ETH Zurich
Year: 2021

description: High-throughput sequencing data is rapidly accumulating in public repositories. Making this resource accessible for interactive analysis at scale requires efficient approaches for its storage and indexing. There have recently been remarkable advances in solving the experiment discovery problem and building compressed representations of annotated de Bruijn graphs where k-mer sets can be efficiently indexed and interactively queried. However, approaches for representing and retrieving other quantitative attributes such as gene expression or genome positions in a general manner have yet to be developed.In this work, we propose the concept of Counting de Bruijn graphs generalizing the notion of annotated (or colored) de Bruijn graphs. Counting de Bruijn graphs supplement each node-label relation with one or many attributes (e.g., a k-mer count or its positions in genome). To represent them, we first observe that many schemes for the representation of compressed binary matrices already support the rank operation on the columns or rows, which can be used to define an inherent indexing of any additional quantitative attributes. Based on this property, we generalize these schemes and introduce a new approach for representing non-binary sparse matrices in compressed data structures. Finally, we notice that relation attributes are often easily predictable from a node’s local neighborhood in the graph. Notable examples are genome positions shifting by 1 for neighboring nodes in the graph, or expression levels that are often shared across neighbors. We exploit this regularity of graph annotations and apply an invertible delta-like coding to achieve better compression.We show that Counting de Bruijn graphs index k-mer counts from 2,652 human RNA-Seq read sets in representations over 8-fold smaller and yet faster to query compared to state-of-the-art bioinformatics tools. Furthermore, Counting de Bruijn graphs with positional annotations losslessly represent entire reads in indexes on average 27% smaller than the input compressed with gzip -9 for human Illumina RNA-Seq and 57% smaller for PacBio HiFi sequencing of viral samples. A complete joint searchable index of all viral PacBio SMRT reads from NCBI’s SRA (152,884 read sets, 875 Gbp) comprises only 178 GB. Finally, on the full RefSeq collection, they generate a lossless and fully queryable index that is 4.4-fold smaller compared to the MegaBLAST index. The techniques proposed in this work naturally complement existing methods and tools employing de Bruijn graphs and significantly broaden their applicability: from indexing k-mer counts and genome positions to implementing novel sequence alignment algorithms on top of highly compressed and fully searchable graph-based sequence indexes.Availability https://github.com/ratschlab/counting_dbgCompeting Interest StatementThe authors have declared no competing interest.
description: bioRxiv
Boosting Variational Inference With Locally Adaptive Step-Sizes
Creators: name: Dresdner, Gideon
name: Shekhar, Saurav
name: Pedregosa, Fabian
name: Locatello, Francesco
name: Rätsch, Gunnar
Publisher: name: ETH Zurich
Year: 2021

description: Variational Inference makes a trade-off between the capacity of the variational family and the tractability of finding an approximate posterior distribution. Instead, Boosting Variational Inference allows practitioners to obtain increasingly good posterior approximations by spending more compute. The main obstacle to widespread adoption of Boosting Variational Inference is the amount of resources necessary to improve over a strong Variational Inference baseline. In our work, we trace this limitation back to the global curvature of the KL-divergence. We characterize how the global curvature impacts time and memory consumption, address the problem with the notion of local curvature, and provide a novel approximate backtracking algorithm for estimating local curvature. We give new theoretical convergence rates for our algorithms and provide experimental validation on synthetic and real-world datasets.
description: arXiv
The potential of big data and new technologies in human rights research (blog post)
Creators: name: Gkliati, Mariana
Publisher: name: figshare
Year: 2016
Subjects: subject: Law
subject: FOS: Law

description: In legal studies, discussion of new technologies has often focused on the risks to privacy and data protection. Mariana Gkliati outlines how such technologies may be seen not only as Orwellian threats but also as opportunities for human rights research. Some advances have already been made and there remains much to learn from other fields. However, to build on such progress institutions must be prepared to invest in developing technologies, encourage interdisciplinary work and establish a robust ethical research framework.
 
title: Prisoner programs within Darwin Correctional Centre
title: an analysis of perceived program needs by prisoners and prison officers
titleType: Subtitle
Creators: name: Rysavy, Paul
Publisher: name: Charles Darwin University
Year: 1997

description: Using a survey research design, the study investigated prisoner and prison officer attitudes towards a range of rehabilitative and leisure programs for prisoners within Darwin Correctional Centre. The sample consisted of 168 male prisoners, seven female prisoners and 49 officers. Demographic details were obtained from prisoners and from officers. Prisoners were asked to rate on a three point scale perceived anticipated personal benefit from participation in pre-release, crisis counselling, communicable diseases education, drug and alcohol counselling and education, violence/aggression, religious, parenting, hobby/recreation and sports programs. Aboriginal prisoners, who constitute 66% of the prisoner population were also asked to rate perceived benefit from participation in Aboriginal art, cultural and visitor programs. Officers were asked to rate perceived importance of the cited programs on a similar three point scale, as well as provide views regarding additional desired programs, interest in involvement in delivery of programs and barriers to program implementation. Four hypotheses were tested: that prisoners would perceive hobby/recreation and sports programs more positively than officers, that of the rehabilitative programs investigated, pre-release programs would receive the highest number of positive responses from prisoners, that of all the programs investigated, violence/aggression programs would receive the highest number of positive responses from officers, and that for prisoners, greater length of experience within the correctional system would predict less perceived benefit from participation in rehabilitative programs while for officers lenghtier correctional experience would predict less perceived importance of all prisoner programs. Responses were analysed using descriptive, correlational and inferential statistical procedures. The first three hypotheses were supported while the fourth was not. Numerous demographic variables were identified as significant predictors of attitude towards specific programs and results are discussed in the context of implications for implementation of appropriate programs.
Single-Round Remodeling of the Active Site of an Artificial Metalloenzyme using an Ultrahigh-Throughput Double Emulsion Screening Assay
Creators: name: Vallapurackal, Jaicy
name: Stucki, Ariane
name: Liang, Alexandria Deliz
name: Klehr, Juliane
name: Dittrich, Petra S.
name: Ward, Thomas R.
Publisher: name: ETH Zurich
Year: 2021

description: The potential of high-throughput compartmentalization renders droplet microfluidics an attractive tool for directed evolution of enzymes as it permits maintenance of the phenotype-genotype linkage throughout the entire optimization procedure. In particular, water-in-oil-in-water double emulsions droplets (DEs) produced by microfluidics enable the analysis of reaction compartments at ultra-high-throughput using commercially available fluorescence-activated cell sorting (FACS) devices. Here we report a streamlined method applicable for the ultrahigh-throughput screening of an artificial metalloenzyme (ArM), an artificial deallylase (ADAse), in double emulsions. The DE-protocol was validated by screening a four hundred member, double-mutant streptavidin library for the CpRu-catalyzed uncaging of aminocoumarin. The most active variants, identified by next generation sequencing of the sorted DE droplets with highest fluorescent intensity, are in good agreement with 96-well plate screening hits. These findings, thus, pave the way towards the systematic implementation of commercially available FACS for the directed evolution of metalloenzymes making ultrahigh-throughput screening more broadly accessible. The use of microfluidics for the formation of uniform compartments with precise control over reagents and cell encapsulation further facilitates the establishment of highly reliable quantitative assays.
description: bioRxiv
Building on shared research and sharing the data underlying a PhD || Engineering Photonics
Creators: name: Hardeman, Megan
name: Harja, Adrian
name: Team Figshare
Publisher: name: figshare
Year: 2018
Subjects: subject: 20504 Photonics, Optoelectronics and Optical Communications
subject: FOS: Physical sciences

description: Building upon shared research and sharing the data underlying a PhD - a figshare case study of Matthew Partridge's Engineering Photonics research.
Forecast of omicron wave time evolution
Creators: name: Schlickeiser, Reinhard
name: Kröger, Martin
Publisher: name: ETH Zurich
Year: 2022
Subjects: coronavirus
extrapolation
omicron mutant
Covid-19

description: Adopting an early doubling time of three days for the rate of new infections with the omicron mutant the temporal evolution of the omicron wave in different countries is predicted. The predictions are based on the susceptible-infectious-recovered/removed (SIR) epidemic compartment model with a constant stationary ratio k=mu(t)/a(t) between the infection (a(t)) and recovery (mu(t)) rate. The fixed early doubling time then uniquely relates the initial infection rate a(0) to the ratio k, which therefore determines the full temporal evolution of the omicron waves. For each country three scenarios (optimistic, pessimistic, intermediate) are considered and the resulting pandemic parameters are calculated. These include the total number of infected persons, the maximum rate of new infections, the peak time and the maximum 7-day incidence per 100000 persons. Among the considered European countries Denmark has the smallest omicron peak time and the recently observed saturation of the 7-day incidence value at 2478 is in excellent agreement with the prediction in the optimistic scenario. For Germany we predict peak times of the omicron wave ranging from 32 to 38 and 45 days after the start of the omicron wave in the optimistic, intermediate and pessimistic scenario, respectively, with corresponding maximum SDI values of 7090, 13263 and 28911, respectively. Adopting Jan 1st, 2022 as the starting date our predictions implies that the maximum of the omicron wave is reached between Feb 1 and Feb 15, 2022. Rather similar values are predicted for Switzerland. Due to an order of magnitude smaller omicron hospitalization rate, due to the high percentage of vaccinated and boostered population, the German health system can cope with maximum omicron SDI value of 2800 which is about a factor 2.5 smaller than the maximum omicron SDI value 7090 in the optimistic case. By either reducing the duration of intensive care during this period of maximum, and/or by making use of the nonuniform spread of the omicron wave across Germany, it seems that the German health system can barely cope with the omicron wave avoiding triage decisions.The reduced omicron hospitalization rate also causes significantly smaller mortality rates compared to the earlier mutants in Germany. In the optimistic scenario one obtains for the total number of fatalities 7445 and for the maximum death rate 418 per day which are about one order of magnitude smaller than the beta fatality rate and total number.
MSNovelist: De novo structure generation from mass spectra
Creators: name: Stravs, Michael A.
name: Dührkop, Kai
name: Böcker, Sebastian
name: Zamboni, Nicola
Publisher: name: ETH Zurich
Year: 2021

description: Structural elucidation of small molecules de novo from mass spectra is a longstanding, yet unsolved problem. Current methods rely on finding some similarity with spectra of known compounds deposited in spectral libraries, but do not solve the problem of predicting structures for novel or poorly represented compound classes. We present MSNovelist that combines fingerprint prediction with an encoder-decoder neural network to generate structures de novo from fragment spectra. In evaluation, MSNovelist correctly reproduced 61% of database annotations for a GNPS reference dataset. In a bryophyte MS2 dataset, our de novo structure prediction substantially outscored the best database candidate for seven features, and a potential novel natural product with a flavonoid core was identified. MSNovelist allows predicting structures solely from MS2 data, and is therefore ideally suited to complement library-based annotation in the case of poorly represented analyte classes and novel compounds.
description: bioRxiv
Dynamic analysis of sugar metabolism reveals the mechanisms of action of synthetic sugar analogs
Creators: name: van Scherpenzeel, Monique
name: Conte, Federica
name: Büll,
Christian
name: Ashikov, Angel
name: Hermans, Esther
name: Willems,
Anke
name: van Tol, Walinka
name: Kragt, Else
name: Moret, Ed E.
name: Heise, Torben
name: Langereis, Jeroen D.
name: Rossing,
Emiel
name: Zimmermann, Michael
name: Rubio-Gozalbo, M. Estela
name: de Jonge, Marien I.
name: Adema, Gosse J.
name: Zamboni, Nicola
name: Boltje, Thomas
name: Lefeber, Dirk J.
Publisher: name: ETH Zurich
Year: 2020
Subjects: Glycosylation
Metabolism
Metabolic oligosaccharide engineering
Sialic acid
Synthetic sugar analog

description: Synthetic sugar analogs are widely applied in metabolic oligosaccharide engineering (MOE) and as novel drugs to interfere with glycoconjugate biosynthesis. However, mechanistic insights on their exact metabolism in the cell and over time are mostly lacking. We developed sensitive ion-pair UHPLC-QqQ mass spectrometry methodology for analysis of sugar metabolites in organisms and in model cells and identified novel low abundant nucleotide sugars in human cells, such as ADP-glucose and UDP-arabinose, and CMP-sialic acid (CMP-NeuNAc) in Drosophila. Dynamic tracing of propargyloxycarbonyl (Poc) labeled analogs, commonly used for MOE, revealed that ManNPoc is metabolized to both CMP-NeuNPoc and UDP-GlcNPoc. Finally, combined treatment of B16-F10 melanoma cells with antitumor compound 3Fax-NeuNAc and 13C-labeled GlcNAc revealed that endogenous CMP-NeuNAc levels started to decrease before a subsequent decrease of ManNAc 6-phosphate was observed. This implicates 3Fax-NeuNAc first acts as a substrate for cytosolic CMP-sialic acid synthetase and subsequently its product CMP-3Fax-NeuNAc functions as a feed-back inhibitor for UDP-GlcNAc 2-epimerase/N-acetylmannosamine kinase. Thus, dynamic analysis of sugar metabolites provides key insights into the time-dependent metabolism of synthetic sugars, which is important for the rational design of analogs with optimized effects.
description: bioRxiv
Characterizations of higher rank hyperbolicity
Creators: name: Goldhirsch, Tommaso
name: Lang, Urs
Publisher: name: ETH Zurich
Year: 2021

description: The concept of Gromov hyperbolicity manifests itself in many different ways. With only mild assumptions on the underlying metric space, the spectrum of equivalent properties includes various thin triangle conditions, the stability of quasi-geodesics (the Morse lemma), a linear isoperimetric inequality for 1-cycles, and a sub-quadratic isoperimetric inequality. We present a similar list of six equivalent properties in the context of generalized non-positive curvature and higher asymptotic rank. This complements results of Wenger and of Kleiner and the second author. We give a largely self-contained proof, providing some improvements and simplifications for the known part.
description: arXiv
TECHNOLOGY INTEGRATION IN THE K-6 CLASSROOM
Creators: name: Nash, Lori A.
Publisher: name: Zenodo
Year: 2022
Subjects: technology
implementation
integration
teachers
curriculum

description: Two terms are often associated with technology and its use in classrooms: implementation and integration. Implementing technology in the classroom means that students and teachers use the devices to do work (e.g., word processing, internet searches, reading books, etc.). To fully integrate technology in the classroom, devices and equipment should be used, but such use should support curricular goals, help students reach their goals, and become a part of the classroom routine. Integration of technology allows students to enhance learning in ways they could not without technology being available. This study addresses the reality that technology is not effectively integrated into elementary classrooms. The data show that teachers are struggling with technology integration in the classroom. Most think they are integrating technology when they are implementing it. There are also significant barriers that prevent teachers from fully integrating technology into the classroom.
Characterizing biautomatic groups
Creators: name: Amrhein, Aischa
Publisher: name: ETH Zurich
Year: 2021

description: This paper corrects the characterisation of biautomatic groups presented in Lemma 2.5.5 in the book Word Processing in Groups by Epstein et al. We present a counterexample to the lemma, and we reformulate the lemma to give a valid characterisation of biautomatic groups.
description: arXiv
networkGWAS: A network-based approach for genome-wide association studies in structured populations
Creators: name: Muzio, Giulia
name: O’Bray, Leslie
name: Meng-Papaxanthos, Laetitia
name: Klatt, Juliane
name: Borgwardt, Karsten
Publisher: name: ETH Zurich
Year: 2021
Subjects: GWAS
Biological networks
Computational biology
Graph kernels
Neighborhood agregation

description: While the search for associations between genetic markers and complex traits has discovered tens of thousands of trait-related genetic variants, the vast majority of these only explain a tiny fraction of observed phenotypic variation. One possible strategy to detect stronger associations is to aggregate the effects of several genetic markers and to test entire genes, pathways or (sub)networks of genes for association to a phenotype. The latter, network-based genome-wide association studies, in particular suffers from a huge search space and an inherent multiple testing problem. As a consequence, current approaches are either based on greedy feature selection, thereby risking that they miss relevant associations, and/or neglect doing a multiple testing correction, which can lead to an abundance of false positive findings. To address the shortcomings of current approaches of network-based genome-wide association studies, we propose networkGWAS, a computationally efficient and statistically sound approach to gene-based genome-wide association studies based on mixed models and neighborhood aggregation. It allows for population structure correction and for well-calibrated p-values, which we obtain through a block permutation scheme. networkGWAS successfully detects known or plausible associations on simulated rare variants from H. sapiens data as well as semi-simulated and real data with common variants from A. thaliana and enables the systematic combination of gene-based genome-wide association studies with biological network information.
description: bioRxiv
1,3,4-Thiadiazoles and 1,3-thiazoles from one-pot reaction of bisthioureas with 2-(bis(methylthio)methylene)malononitrile and ethyl 2-cyano-3,3-bis(methylthio)acrylate
Creators: name: Aly, Ashraf A.
name: Hassan, Alaa A.
name: Bräse, Stefan
name: Ibrahim, Mahmoud A. A.
name: El-Shimaa S. M. Abd Al-Latif
name: Spuling, Eduard
name: Nieger, Martin
Publisher: name: Taylor & Francis
Year: 2016
Subjects: subject: Biophysics
subject: Biochemistry
subject: 29999 Physical Sciences not elsewhere classified
subject: FOS: Physical sciences
subject: Medicine
subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Pharmacology
subject: Biotechnology
subject: 69999 Biological Sciences not elsewhere classified
subject: Developmental Biology
subject: Inorganic Chemistry
subject: FOS: Chemical sciences
subject: 110309 Infectious Diseases
subject: FOS: Health sciences
subject: Plant Biology

description: Bisthioureas reacted with either 2-(bis(methylthio)methylene)malononitrile or ethyl 2-cyano-3,3-bis(methylthio)acrylate to give 1,3,4-thiadiazoles and 1,3-thiazoles. Only, the reactive allyl derivative of bisthioureas reacted with the bis(methylthio)methylene compounds to give 1,3-thiazoles. The mechanism was discussed. The structures of products were proved by MS, IR, NMR and elemental analyses and X-ray structure analysis.
Determinants of SARS-CoV-2 transmission to guide vaccination strategy in an urban area
Creators: name: Brüningk, Sarah
name: Klatt, Juliane
name: Stange, Madlen
name: Mari, Alfredo
name: Brunner, Myrta
name: Roloff, Tim-Christoph
name: Seth-Smith, Helena M.B.
name: Schweitzer, Michael
name: Leuzinger, Karoline
name: Søgaard, Kirstine K.
name: Albertos Torres, Diana
name: Gensch, Alexander
name: Schlotterbeck, Ann-Kathrin
name: Nickel, Christian H.
name: Ritz, Nicole
name: Heininger, Ulrich
name: Bielicki, Julia
name: Rentsch, Katharina
name: Fuchs, Simon
name: Bingisser, Roland
name: Siegemund, Martin
name: Pargger, Hans
name: Ciardo, Diana
name: Dubuis, Olivier
name: Buser, Andreas
name: Tschudin-Sutter, Sarah
name: Battegay, Manuel
name: Schneider-Sliwa, Rita
name: Borgwardt, Karsten
name: Hirsch, Hans H.
name: Egli, Adrian
Publisher: name: ETH Zurich
Year: 2021

description: Background Transmission chains within small urban areas (accommodating∼30% of the European population) greatly contribute to case burden and economic impact during the ongoing COVID-19 pandemic, and should be a focus for preventive measures to achieve containment. Here, at very high spatio-temporal resolution, we analysed determinants of SARS-CoV-2 transmission in a European urban area, Basel-City (Switzerland). Methodology. We combined detailed epidemiological, intra-city mobility, and socioeconomic data-sets with whole-genome-sequencing during the first SARS-CoV-2 wave. For this, we succeeded in sequencing 44% of all reported cases from Basel-City and performed phylogenetic clustering and compartmental modelling based on the dominating viral variant (B.1-C15324T; 60% of cases) to identify drivers and patterns of transmission. Based on these results we simulated vaccination scenarios and corresponding healthcare-system burden (intensive-care-unit occupancy). Principal Findings. Transmissions were driven by socioeconomically weaker and highly mobile population groups with mostly cryptic transmissions, whereas amongst more senior population transmission was clustered. Simulated vaccination scenarios assuming 60-90% transmission reduction, and 70-90% reduction of severe cases showed that prioritizing mobile, socioeconomically weaker populations for vaccination would effectively reduce case numbers. However, long-term intensive-care-unit occupation would also be effectively reduced if senior population groups were prioritized, provided there were no changes in testing and prevention strategies. Conclusions. Reducing SARS-CoV-2 transmission through vaccination strongly depends on the efficacy of the deployed vaccine. A combined strategy of protecting risk groups by extensive testing coupled with vaccination of the drivers of transmission (i.e. highly mobile groups) would be most effective at reducing the spread of SARS-CoV-2 within an urban area.
description: medRxiv
Kilitbahir Yeni Sayı: Sayı 16
Creators: name: Deniz, Osman Murat
Publisher: name: Zenodo
Year: 2020

description: Editörden… Değerli Bilim İnsanları Hakemlerimiz ve yazarlarımızla birlikte dergimizin 16. sayısını okuyucularımızla buluşturmaktan kıvanç duymaktayız.
The shared and unique genetic relationship between mental well-being, depression and anxiety symptoms and cognitive function in healthy twins
Creators: name: Routledge, Kylie M.
name: Burton, Karen L. O.
name: Williams, Leanne M.
name: Harris, Anthony
name: Schofield, Peter R.
name: C. Richard Clark
name: Gatt, Justine M.
Publisher: name: Taylor & Francis
Year: 2016
Subjects: subject: Genetics
subject: FOS: Biological sciences
subject: Neuroscience
subject: Biotechnology
subject: Sociology
subject: FOS: Sociology
subject: 111714 Mental Health
subject: FOS: Health sciences

description: Alterations to cognitive function are often reported with depression and anxiety symptoms, yet few studies have examined the same associations with mental well-being. This study examined the association between mental well-being, depression and anxiety symptoms and cognitive function in 1502 healthy adult monozygotic (MZ) and dizygotic (DZ) twins, and the shared/unique contribution of genetic (G) and environmental (E) variance. Using linear mixed models, mental well-being was positively associated (p β = 0.127), inhibition (β = 0.096), cognitive flexibility (β = 0.149), motor coordination (β = 0.114) and working memory (β = 0.156), whereas depression and anxiety symptoms were associated (p β = −0.134), inhibition (β = −0.139), cognitive flexibility (β = −0.116) and executive function (β = −0.139). Bivariate twin modelling showed well-being shared a small environmental correlation with motor coordination and a small genetic correlation with working memory. Trivariate twin modelling showed well-being shared a small genetic correlation with inhibition, whereas depression and anxiety symptoms shared a small environmental correlation with inhibition. The remaining variance was mostly driven by unique G and/or E variance. Overall, well-being and depression and anxiety symptoms show both independent and shared relationships with cognitive functions but this is largely attributable to unique G or E variance and small shared G/E variance between pairs of variables.
Thermodynamic stability and P-V criticality of nonsingular-AdS black holes endowed with clouds of strings
Creators: name: Sood, Ashima
name: Kumar, Arun
name: Singh, J. K.
name: Ghosh, Sushant G.
Publisher: name: arXiv
Year: 2022
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: We investigate the extended phase space thermodynamics of nonsingular-AdS black holes minimally coupled to clouds of strings in which we consider the cosmological constant ($Λ$) as the pressure ($P$) of the black holes and its conjugate variable thermodynamical volume ($V$) of the black holes. Owing to the background clouds of strings parameter ($a$), we analyse the Hawking temperature, entropy and specific heat on horizon radius for fixed-parameter $k$. We find that the strings clouds background does not alter small/large black hole (SBH/LBH) phase transition but occurs at a larger horizon radius, and two second-order phase transitions occur at a smaller horizon radius. Indeed, the $G$--$T$ plots exhibit a swallowtail below the critical pressure, implying that the first-order phase transition is analogous to the liquid-gas phase transition at a lower temperature and lower critical pressure. To further examine the analogy between nonsingular-AdS black holes and a liquid-gas system, we derive the exact critical points and probe the effects of a cloud of strings on $P-V$ criticality to find that the isotherms undergo liquid-gas like phase transition for $\tilde{T}\,
description: 12 pages, 16 figures
title: 1. Chant zäläsäña par Bälay Täšomä
Creators: name: Wion, Anaïs
name: Bolay, Anne
Publisher: name: COCOON - https://cocoon.huma-num.fr (Huma-Num - CNRS)
publisherIdentifier: https://ror.org/04ces3204
publisherIdentifierScheme: ROR
Year: 2020

description: Bälay Täšoma, septuagénaire lors de l'entretien, descend d'une prestigieuse lignée d'azmari puisque son père était qänazmač Täšomä Kebrité, le yä-azmari šum du Wällo sous Haylä Sellasié. Il reçut ce titre ainsi que 3 gaša de terres à Wäldya et dans la campagne proche en récompense de son engagement dans la résistance pendant l'occupation italienne. Ce serait les célébres Gobäna Amédé et Bälay Märša qui auraient intercéder en sa faveur pour qu'il obtienne ses privilèges.
Building upon shared research and sharing the data underlying a PhD || Engineering Photonics
Creators: name: Partridge, Matthew
name: Hardeman, Megan
name: Harja, Adrian
Publisher: name: figshare
Year: 2016
Subjects: subject: 20504 Photonics, Optoelectronics and Optical Communications
subject: FOS: Physical sciences

description: Building upon shared research and sharing the data underlying a PhD - a figshare case study of Matthew Partridge's Engineering Photonics research.