High-sensitive protein analysis by FESI-CEMALDI-MS

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A comprehensive review of digital twin-part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives

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Energy efficiency is crucial for the sustainable operation of all industrial and urban sectors. However, practicing engineers have seldom access to open-source tools that can readily evaluate and compare scenarios in terms of energy consumption, cost, and ...

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The monumental progress in the development of machine learning models has led to a plethora of applications with transformative effects in engineering and science. This has also turned the attention of the research community towards the pursuit of construc ...

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A new age in protein design empowered by deep learning

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The rapid progress in the field of deep learning has had a significant impact on protein design. Deep learning methods have recently produced a breakthrough in protein structure prediction, leading to the availability of high-quality models for millions of ...

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Data-Driven Control and Optimization under Noisy and Uncertain Conditions

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Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

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Hypergraph-Based Fast Distributed AC Power Flow Optimization

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This paper presents a novel distributed approach for solving AC power flow (PF) problems. The optimization problem is reformulated into a distributed form using a communication structure corresponding to a hypergraph, by which complex relationships between ...

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A Geometric Transformer for Structural Biology: Development and Applications of the Protein Structure Transformer

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Proteins, the central building blocks of life, play pivotal roles in nearly every biological function. To do so, these macromolecular structures interact with their surrounding environment in complex ways, leading to diverse functional behaviors. The predi ...

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Structural impact of the start-up sequence on Pelton turbines lifetime: Analytical prediction and polynomial optimization

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Hydropower plants play a crucial role in the power system facing ambitious renewable energy targets. Due to their inherent controllability, they are well suited to provide flexibility to the grid. However, an increased flexibility provision leads to a prol ...

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Unbiasing time-dependent Variational Monte Carlo by projected quantum evolution

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We analyze the accuracy and sample complexity of variational Monte Carlo approaches to simulate the dynamics of many-body quantum systems classically. By systematically studying the relevant stochastic estimators, we are able to: (i) prove that the most us ...

Verein Forderung Open Access Publizierens Quantenwissenschaf2023

Proposed residual stress model for hot‐rolled wide flange steel cross sections

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Residual stresses in hot-rolled wide flange steel cross sections may lead to premature yielding, accelerated corrosion and brittle fracture of steel members. The above phenomena lead to a loss of a steel member's stiffness and resistance under mechanical l ...

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Generative power of a protein language model trained on multiple sequence alignments

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Computational models starting from large ensembles of evolutionarily related protein sequences capture a representation of protein families and learn constraints associated to protein structure and function. They thus open the possibility for generating no ...

eLIFE SCIENCES PUBL LTD2023