SmartD: Smart Meter Data Analytics Dashboard

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Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data st ...

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preservi ...

Grid cells in the entorhinal cortex (EC) encode an individual’s location in space, integrating both environmental and multisensory bodily cues. Notably, body-derived signals are also primary signals for the sense of self. While studies have demonstrated th ...

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

We present a combination technique based on mixed differences of both spatial approximations and quadrature formulae for the stochastic variables to solve efficiently a class of optimal control problems (OCPs) constrained by random partial differential equ ...

This paper presents a novel hybrid framework for generating and updating a synthetic population. We call it hybrid because it combines model-based and data-driven approaches. Existing generators produce a snapshot of synthetic data that becomes outdated ov ...

Modern power distribution systems are experiencing a large-scale integration of Converter-Interfaced Distributed Energy Resources (CIDERs). Their presence complicates the analysis and mitigation of harmonics, whose creation and propagation may be amplified ...

Geometric properties of lattice quantum gravity in two dimensions are studied numerically via Monte Carlo on Euclidean Dynamical Triangulations. A new computational method is proposed to simulate gravity coupled with fermions, which allows the study of int ...

A central question in multi-agent strategic games deals with learning the underlying utilities driving the agents' behaviour. Motivated by the increasing availability of large data-sets, we develop an unifying data-driven technique to estimate agents' util ...

The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data prin ...

Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simul ...

The decentralisation and unpredictability of new renewable energy sources require rethinking our energy system. Data-driven approaches, such as reinforcement learning (RL), have emerged as new control strategies for operating these systems, but they have n ...

CEBRA is a machine-learning method that can be used to compress time series in a way that reveals otherwise hidden structures in the variability of the data. It excels at processing behavioural and neural data recorded simultaneously, and it can decode act ...

Acoustic emission (AE) monitoring is a useful technique to monitor the health of a structure continuously, helping to prevent potential failure. AE are elastic waves produced and emitted during fracture processes inside a material and are recorded by senso ...

Discovering new materials is essential but challenging, time-consuming, and expensive. In many cases, simulations can be useful for estimating material properties. For many of the most interesting properties, however, simulations are infeasible because of ...

The nitrogen-vacancy (NV) center in diamond is a powerful and versatile quantum sensor for diverse quantities. In particular, relaxometry (or T1), can be used to detect magnetic noise at the nanoscale. For experiments with single NV centers the analysis of ...

Information collected through sensor measurements has the potential to improve knowledge of complex-system behavior, leading to better decisions related to system management. In this situation, and particularly when using digital twins, the quality of sens ...

Alloys composed of several elements in roughly equimolar composition, often referred to as high-entropy alloys, have long been of interest for their thermodynamics and peculiar mechanical properties, and more recently for their potential application in cat ...

Macromolecular mass fingerprinting using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry is a quick tool for biochemical analysis. In combination with algorithms for automated data analysis and interpretation, it has wide appli ...

We propose a framework for the construction of 4D scientific models for cities of the past. It leverages both the use of computational methods for bootstrapping, and a collaborative interface for visualisation and edition. This permits to continuously enri ...

SmartD: Smart Meter Data Analytics Dashboard

Chat with Graph Search

Orchestrating chromosome conformation capture analysis with Bioconductor

Live-cell imaging powered by computation

Changes in spatial self-consciousness elicit grid cell–like representation in the entorhinal cortex

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

A Combination Technique for Optimal Control Problems Constrained by Random PDEs

Hybrid Simulator for Capturing Dynamics of Synthetic Populations

Unified Harmonic Power-Flow and Stability Analysis of Power Grids with Converter-Interfaced Distributed Energy Resources

Hausdorff dimension of fermions on a random lattice

Data-Driven Behaviour Estimation in Parametric Games

Shared metadata for data-centric materials science

Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science

Reinforcement Learning for Joint Design and Control of Battery-PV Systems

Brain dynamics uncovered using a machine-learning algorithm

Automatic and high-precision acoustic emission-based structural health monitoring of concrete structures

Toward data-driven materials design: From atoms to pilot plants

Optimizing Data Processing for Nanodiamond Based Relaxometry

Methodology for selecting measurement points that optimize information gain for model updating

Modeling high-entropy transition metal alloys with alchemical compression

Algorithms push forward the application of MALDI-TOF mass fingerprinting in rapid precise diagnosis

From Automated Bootstrapping to Collaborative Editing: A Framework for 4D City Reconstruction