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A new and efficient magnetisation transfer P-31 magnetic resonance fingerprinting (MT-P-31-MRF) approach is introduced to measure the creatine kinase metabolic rate kCK

{k}_{\mathrm{CK}}

between phosphocreatine (PCr) and adenosine triphosphate (ATP) i ...

In the current era of big data, aggregation queries on high-dimensional datasets are frequently utilized to uncover hidden patterns, trends, and correlations critical for effective business decision-making. Data cubes facilitate such queries by employing p ...

ML-based edge devices may face memory and computational errors that affect applications' reliability and performance. These errors can be the result of particular working conditions (e.g., radiation areas in physical experiments or avionics) or could be th ...

Models trained with counterfactually augmented data learn representations of the causal structure of tasks, enabling robust generalization. However, high-quality counterfactual data is scarce for most tasks and not easily generated at scale. When crowdsour ...

Deep-learning-based digital twins (DDT) are a promising tool for data-driven system health management because they can be trained directly on operational data. A major challenge for efficient training however is that industrial datasets remain unlabeled. T ...

The successes of deep learning for semantic segmentation can in be, in part, attributed to its scale: a notion that encapsulates the largeness of these computational architectures and the labeled datasets they are trained on. These resource requirements hi ...

Situated in the intersection of audiovisual archives, computational methods, and immersive interactions, this work probes the increasingly important accessibility issues from a two-fold approach. Firstly, the work proposes an ontological data model to hand ...

The outstanding information processing capacity of the brain relies on numerous molecular mechanisms. It is an extremely energy-expensive function, which involves specialization and collaboration of different cell types. A common framework to study the com ...

This dataset complements the article "Frequency regulation with storage: On losses and profits" by Dirk Lauinger, François Vuille, and Daniel Kuhn, available at https://arxiv.org/abs/2306.02987. The dataset contains the following files: 1.

This article proposes an original approach to urban events mapping. At the theoretical level, the article is based on rhythmanalysis and recent research on urban rhythms. It contrasts with previous research by departing from everyday rhythms to tackle the ...

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Fast in vivo assay of creatine kinase activity in the human brain by P-31 magnetic resonance fingerprinting

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Hardware-Software co-design Methodologies for Edge AI Optimization

DISCO: Distilling Counterfactuals with Large Language Models

A Study on Gradient-based Meta-learning for Robust Deep Digital Twins

Confidence Matters: Applications to Semantic Segmentation

Encoding and Decoding Narratives: Datafication and Alternative Access Models for Audiovisual Archives

Molecular reconstruction and simulation of the Neuron-Glia-Vasculature system

Dataset for the article "Frequency regulation with storage: On losses and profits"

Rhythmanalysis of Urban Events: Empirical Elements from the Montreux Jazz Festival