4,308 research outputs found
Classical and quantum algorithms for scaling problems
This thesis is concerned with scaling problems, which have a plethora of connections to different areas of mathematics, physics and computer science. Although many structural aspects of these problems are understood by now, we only know how to solve them efficiently in special cases.We give new algorithms for non-commutative scaling problems with complexity guarantees that match the prior state of the art. To this end, we extend the well-known (self-concordance based) interior-point method (IPM) framework to Riemannian manifolds, motivated by its success in the commutative setting. Moreover, the IPM framework does not obviously suffer from the same obstructions to efficiency as previous methods. It also yields the first high-precision algorithms for other natural geometric problems in non-positive curvature.For the (commutative) problems of matrix scaling and balancing, we show that quantum algorithms can outperform the (already very efficient) state-of-the-art classical algorithms. Their time complexity can be sublinear in the input size; in certain parameter regimes they are also optimal, whereas in others we show no quantum speedup over the classical methods is possible. Along the way, we provide improvements over the long-standing state of the art for searching for all marked elements in a list, and computing the sum of a list of numbers.We identify a new application in the context of tensor networks for quantum many-body physics. We define a computable canonical form for uniform projected entangled pair states (as the solution to a scaling problem), circumventing previously known undecidability results. We also show, by characterizing the invariant polynomials, that the canonical form is determined by evaluating the tensor network contractions on networks of bounded size
Climate Change and Critical Agrarian Studies
Climate change is perhaps the greatest threat to humanity today and plays out as a cruel engine of myriad forms of injustice, violence and destruction. The effects of climate change from human-made emissions of greenhouse gases are devastating and accelerating; yet are uncertain and uneven both in terms of geography and socio-economic impacts. Emerging from the dynamics of capitalism since the industrial revolution â as well as industrialisation under state-led socialism â the consequences of climate change are especially profound for the countryside and its inhabitants. The book interrogates the narratives and strategies that frame climate change and examines the institutionalised responses in agrarian settings, highlighting what exclusions and inclusions result. It explores how different people â in relation to class and other co-constituted axes of social difference such as gender, race, ethnicity, age and occupation â are affected by climate change, as well as the climate adaptation and mitigation responses being implemented in rural areas. The book in turn explores how climate change â and the responses to it - affect processes of social differentiation, trajectories of accumulation and in turn agrarian politics. Finally, the book examines what strategies are required to confront climate change, and the underlying political-economic dynamics that cause it, reflecting on what this means for agrarian struggles across the world. The 26 chapters in this volume explore how the relationship between capitalism and climate change plays out in the rural world and, in particular, the way agrarian struggles connect with the huge challenge of climate change. Through a huge variety of case studies alongside more conceptual chapters, the book makes the often-missing connection between climate change and critical agrarian studies. The book argues that making the connection between climate and agrarian justice is crucial
The consolidated European synthesis of CHâ and NâO emissions for the European Union and United Kingdom: 1990â2019
Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CHâ and NâO emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27â+âUK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990â2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CHâ emissions, over the updated 2015â2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5âTgâCHââyrc (EDGARv6.0, last year 2018) and 18.4âTgâCHââyrâ»Âč (GAINS, last year 2015), close to the NGHGI estimates of 17.5±2.1âTgâCHââyrâ»Âč. TD inversion estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high-resolution regional TD inversions report a mean emission of 34âTgâCHââyrâ»Âč. Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24âTgâCHââyrâ»Âč inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACHâHIMMELI model, natural rivers, lake and reservoir emissions, geological sources, and biomass burning together could account for the gap between NGHGI and inversions and account for 8âTgâCHââyrâ»Âč. For NâO emissions, over the 2015â2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9âTgâNâOâyrâ»Âč, close to the NGHGI data (0.8±55â%âTgâNâOâyrâ»Âč). Over the same period, the mean of TD global and regional inversions was 1.4âTgâNâOâyrâ»Âč (excluding TOMCAT, which reported no data). The TD and BU comparison method defined in this study can be operationalized for future annual updates for the calculation of CHâ and NâO budgets at the national and EU27â+âUK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, which is of great importance for CHâ and NâO, and may help identify sector contributions to divergence between prior and posterior estimates at the annual and/or inter-annual scale. Even if currently comparison between CHâ and NâO inversion estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emission inventories for CHâ, NâO and other GHGs. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.7553800 (Petrescu et al., 2023)
Proceedings of SIRM 2023 - The 15th European Conference on Rotordynamics
It was our great honor and pleasure to host the SIRM Conference after 2003 and 2011 for the third time in Darmstadt. Rotordynamics covers a huge variety of different applications and challenges which are all in the scope of this conference. The conference was opened with a keynote lecture given by Rainer Nordmann, one of the three founders of SIRM âSchwingungen in rotierenden Maschinenâ. In total 53 papers passed our strict review process and were presented. This impressively shows that rotordynamics is relevant as ever. These contributions cover a very wide spectrum of session topics: fluid bearings and seals; air foil bearings; magnetic bearings; rotor blade interaction; rotor fluid interactions; unbalance and balancing; vibrations in turbomachines; vibration control; instability; electrical machines; monitoring, identification and diagnosis; advanced numerical tools and nonlinearities as well as general rotordynamics. The international character of the conference has been significantly enhanced by the Scientific Board since the 14th SIRM resulting on one hand in an expanded Scientific Committee which meanwhile consists of 31 members from 13 different European countries and on the other hand in the new name âEuropean Conference on Rotordynamicsâ. This new international profile has also been
emphasized by participants of the 15th SIRM coming from 17 different countries out of three continents. We experienced a vital discussion and dialogue between industry and academia at the conference where roughly one third of the papers were presented by industry and two thirds by academia being an excellent basis to follow a bidirectional transfer what we call xchange at Technical University of Darmstadt. At this point we also want to give our special thanks to the eleven industry sponsors for their great support of the conference. On behalf of the Darmstadt Local Committee I welcome you to read the papers of the 15th SIRM giving you further insight into the topics and presentations
On the Utility of Representation Learning Algorithms for Myoelectric Interfacing
Electrical activity produced by muscles during voluntary movement is a reflection of the firing patterns of relevant motor neurons and, by extension, the latent motor intent driving the movement. Once transduced via electromyography (EMG) and converted into digital form, this activity can be processed to provide an estimate of the original motor intent and is as such a feasible basis for non-invasive efferent neural interfacing. EMG-based motor intent decoding has so far received the most attention in the field of upper-limb prosthetics, where alternative means of interfacing are scarce and the utility of better control apparent. Whereas myoelectric prostheses have been available since the 1960s, available EMG control interfaces still lag behind the mechanical capabilities of the artificial limbs they are intended to steerâa gap at least partially due to limitations in current methods for translating EMG into appropriate motion commands. As the relationship between EMG signals and concurrent effector kinematics is highly non-linear and apparently stochastic, finding ways to accurately extract and combine relevant information from across electrode sites is still an active area of inquiry.This dissertation comprises an introduction and eight papers that explore issues afflicting the status quo of myoelectric decoding and possible solutions, all related through their use of learning algorithms and deep Artificial Neural Network (ANN) models. Paper I presents a Convolutional Neural Network (CNN) for multi-label movement decoding of high-density surface EMG (HD-sEMG) signals. Inspired by the successful use of CNNs in Paper I and the work of others, Paper II presents a method for automatic design of CNN architectures for use in myocontrol. Paper III introduces an ANN architecture with an appertaining training framework from which simultaneous and proportional control emerges. Paper Iv introduce a dataset of HD-sEMG signals for use with learning algorithms. Paper v applies a Recurrent Neural Network (RNN) model to decode finger forces from intramuscular EMG. Paper vI introduces a Transformer model for myoelectric interfacing that do not need additional training data to function with previously unseen users. Paper vII compares the performance of a Long Short-Term Memory (LSTM) network to that of classical pattern recognition algorithms. Lastly, paper vIII describes a framework for synthesizing EMG from multi-articulate gestures intended to reduce training burden
Data-driven exact model order reduction for computational multiscale methods to predict high-cycle fatigue-damage in short-fiber reinforced plastics
Motiviert durch die Entwicklung energieeffizienterer Maschinen und Transportmittel hat der Leichtbau in den letzten Jahren enorm an Wichtigkeit gewonnen. Eine wichtige Klasse der Leichtbaumaterialien sind die faserverstĂ€rkten Kunststoffe. In der vorliegenden Arbeit liegt der Fokus auf der Entwicklung und Bereitstellung von Materialmodellen zur Vorhersage des ErmĂŒdungsverhaltens kurzglasfaserverstĂ€rkter Thermoplaste. Diese Materialien unterscheiden sich dabei durch ihre Aufschmelzbarkeit und ihrer damit einhergehenden besseren Recyclebarkeit von thermosetbasierten Materialien. AuĂerdem erlauben die Kurzglasfasern im Gegensatz zu Langfasern eine einfache und zeiteffiziente Herstellung komplexer Komponenten.
ErmĂŒdung ist ein wichtiger Versagensmechanismus in solchen Komponenten, insbesondere fĂŒr Bauteile z.B. in Fahrzeugen, die vibrationsartigen Belastungen ausgesetzt sind. Durch die inherente Anisotropie des Materials sind die experimentelle Charakterisierung und Vorhersage dieses Versagensmechanismus jedoch Ă€uĂerst zeitintensiv und stellen somit eine wesentliche Herausforderung im Entwicklungsprozess und fĂŒr die breitere Anwendung solcher Bauteile dar. Daher ist die Entwicklung komplementĂ€rer simulativer Methoden von groĂem Interesse.
Im Rahmen dieser Arbeit werden Methoden zur Vorhersage der ErmĂŒdungsschĂ€digung kurzglasfaserverstĂ€rkter Werkstoffe im Rahmen einer Multiskalenmethode entwickelt. Die in der Arbeit betrachteten Multiskalenmodelle bieten die Möglichkeit, allein anhand der experimentellen Charakterisierungen der Materialparameter der Konstituenten, d.h. Faser und Matrix, komplexe anisotrope Effekte des Verbundmaterials vorherzusagen. Der experimentelle Aufwand kann dadurch enorm reduziert werden. Dazu werden zunĂ€chst Materialmodelle fĂŒr die Konstituenten des Komposits entwickelt. Mithilfe FFT-basierter rechnergestĂŒtzter Homogenisierung wird daraus das Materialverhalten des Komposits fĂŒr verschiedene Mikrostrukturen und LastfĂ€lle vorhergesagt. Die vorberechneten LastfĂ€lle auf Mikrostrukturebene werden mit datengetriebenen Methoden auf die Makroskala ĂŒbertragen. Das ermöglicht eine effiziente Berechnung von Bauteilen in wenigen Stunden, wohingegen eine entsprechende Berechnung mit geometrischer Auflösung aller einzelnen Fasern der Mikrostruktur auf heutigen Computern viele Jahre dauern wĂŒrden.
FĂŒr die Matrix werden unterschiedliche SchĂ€digungsmodelle untersucht. Ihre Vor- und Nachteile werden analysiert. Die Mikrostruktursimulationen geben einen Einblick in den Einfluss verschiedener statistischer Parameter wie FaserlĂ€ngen und Faservolumengehalt auf das Kompositverhalten. Ein neues Modellordnungsreduktionsverfahren wird entwickelt und zur Simulation des ErmĂŒdungsschĂ€digungsverhaltens auf Bauteilebene angewandt. Weiter werden Modellerweiterungen zur BerĂŒcksichtigung des R-Wert-VerhĂ€ltnisses und viskoelastischer Effekte in der Evolution der ErmĂŒdungsschĂ€digung entwickelt und mit experimentellen Ergebnissen validiert.
Das entstandene Simulationsframework erlaubt nach Vorrechnungen auf einer geringen Menge von Mikrostrukturen und LastfĂ€llen eine effiziente Makrosimulation eines Bauteils vorzunehmen. Dabei können Effekte wie ViskoelastizitĂ€t und R-Wert-AbhĂ€ngigkeit je nach gewĂŒnschter Modellierungstiefe berĂŒcksichtigt oder vernachlĂ€ssigt werden, um immer das effizientste Modell, das alle relevanten Effekte abbildet, nutzen zu können
The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom : 1990-2019
Funding Information: We thank AurĂ©lie Paquirissamy, GĂ©raud Moulas and the ARTTIC team for the great managerial support offered during the project. FAOSTAT statistics are produced and disseminated with the support of its member countries to the FAO regular budget. Annual, gap-filled and harmonized NGHGI uncertainty estimates for the EU and its member states were provided by the EU GHG inventory team (European Environment Agency and its European Topic Centre on Climate change mitigation). Most top-down inverse simulations referred to in this paper rely for the derivation of optimized flux fields on observational data provided by surface stations that are part of networks like ICOS (datasets: 10.18160/P7E9-EKEA , Integrated Non-CO Observing System, 2018a, and 10.18160/B3Q6-JKA0 , Integrated Non-CO Observing System, 2018b), AGAGE, NOAA (Obspack Globalview CH: 10.25925/20221001 , Schuldt et al., 2017), CSIRO and/or WMO GAW. We thank all station PIs and their organizations for providing these valuable datasets. We acknowledge the work of other members of the EDGAR group (Edwin Schaaf, Jos Olivier) and the outstanding scientific contribution to the VERIFY project of Peter Bergamaschi. Timo Vesala thanks ICOS-Finland, University of Helsinki. The TM5-CAMS inversions are available from https://atmosphere.copernicus.eu (last access: June 2022); Arjo Segers acknowledges support from the Copernicus Atmosphere Monitoring Service, implemented by the European Centre for Medium-Range Weather Forecasts on behalf of the European Commission (grant no. CAMS2_55). This research has been supported by the European Commission, Horizon 2020 Framework Programme (VERIFY, grant no. 776810). Ronny Lauerwald received support from the CLand Convergence Institute. Prabir Patra received support from the Environment Research and Technology Development Fund (grant no. JPMEERF20182002) of the Environmental Restoration and Conservation Agency of Japan. Pierre Regnier received financial support from the H2020 project ESM2025 â Earth System Models for the Future (grant no. 101003536). David Basviken received support from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (METLAKE, grant no. 725546). Greet Janssens-Maenhout received support from the European Union's Horizon 2020 research and innovation program (CoCO, grant no. 958927). Tuula Aalto received support from the Finnish Academy (grants nos. 351311 and 345531). Sönke Zhaele received support from the ERC consolidator grant QUINCY (grant no. 647204).Peer reviewedPublisher PD
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Integrated Geophysical Analysis of Passive Continental Margins: Insights into the Crustal Structure of the Namibian Margin from Magnetotelluric, Gravity, and Seismic Data
Passive continental margin research amalgamates the investigation of many broad topics, such as the emergence of oceanic crust, lithospheric stress patterns and plume-lithosphere interaction, reservoir potential, methane cycle, and general global geodynamics. Central tasks in this field of research are geophysical investigations of the structure, composition, and dynamic of the passive margin crust and upper mantle. A key practice to improve geophysical models and their interpretation, is the integrated analysis of multiple data, or the integration of complementary models and data. In this thesis, I compare four different inversion results based on data from the Namibian passive continental margin. These are a) a single method MT inversion; b) constrained inversion of MT data, cross-gradient coupled with a fixed structural density model; c) cross-gradient coupled joint inversion of MT and satellite gravity data; d) constrained inversion of MT data, cross-gradient coupled with a fixed gradient velocity model. To bridge the formal analysis of geophysical models with geological interpretations, I define a link between the physical parameter models and geological units. Therefore, the results from the joint MT and gravity inversion (c) are correlated through a user-unbiased clustering analysis. This clustering analysis results in a distinct difference in the signature of the transitional crust south of- and along the supposed hot-spot track Walvis Ridge. I ascribe this contrast to an increase in magmatic activity above the volcanic center along Walvis Ridge. Furthermore, the analysis helps to clearly identify areas of interlayered massive, and weathered volcanic flows, which are usually only identified in reflection seismic studies as seaward dipping reflectors. Lastly, the clustering helps to differentiate two types of sediment cover. Namely, one of near-shore, thick, clastic sediments, and one of further offshore located, more biogenic, marine sediments
Tradition and Innovation in Construction Project Management
This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings
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