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

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Accurately measuring behavior is critical to understanding brain function. While traditional behavioral analysis has relied on human observation and manual processing, advances in machine learning and computer vision have begun to automate the field. This ...

A key challenge in microresonator-based frequency combs has been achieving f-2f self-referencing, which requires a powerful, octave-spanning microcomb. Stable self-referenced combs have numerous applications including ultra-low-noise microwave generation a ...

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 ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

Over the course of history, the relationship between cities and their waters has shown different gradients of interweaving, marked by cycles of bonding and distancing. Following a period of complete neglect of urban watercourses, the versatile, multifacete ...

This document contains all the data and the details of the analysis used in the manuscript titled " Control of Ge island coalescence for the formation of nanowires on silicon." https://doi.org/10.1039/D3NH00573A ...

Numerous conductor designs for pulsed magnets based on High Temperature Superconductors (HTS), featuring stacks of tapes are currently being proposed. A major contribution to the AC losses is expected to be given by hysteresis losses. Several numerical mod ...

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”. This work aims to study and demonstrate ...

Traditional martial arts are treasures of humanity's knowledge and critical carriers of sociocultural memories throughout history. However, such treasured practices have encountered various challenges in knowledge transmission and now feature many entries ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

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 ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...

It is of great interest to the energy community to understand how the mechano-physico-chemical phenomena that eventually lead to device degradation are related to the startup, operation, and shutdown phases. For electrocatalytic systems operating in liquid ...

Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

The near-surface boundary layer above patchy snow cover in mountainous terrain is characterized by a highly complex interplay of various flows on multiple scales. In this study, we present data from a comprehensive field campaign that cover a period of 21 ...

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

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From Pose to Behavior: Advancing Multi-Individual Pose Estimation and Hierarchical Action Segmentation with Transformers

Octave-Spanning Kerr Frequency Comb in a Si3N4 Microresonator at Electronically Detectable Repetition Rate

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

Reliable data-driven decision-making through optimal transport

Machine Learning for Modeling Stock Returns

Data and scripts for the RaFSIP scheme

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Quartiers rhodaniens en transition

Data set for control of Ge island coalescence for the formation of nanowires on silicon

Validation and Application of Hysteresis Loss Model for HTS Stacks and Conductors for Fusion Applications

Robust machine learning for neuroscientific inference

Dataset for '3D printing of customizable transient bioelectronics and sensors'

Ontology-based Knowledge Representation for Traditional Martial Arts

Extensions of Peer Prediction Incentive Mechanisms

Orchestrating chromosome conformation capture analysis with Bioconductor

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Data-driven statistical optimization of a groundwater monitoring network

Quasi-operando Transmission Electron Microscopy Diagnostics for Electrocatalytic Processes in Liquids

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants

Turbulence in the Strongly Heterogeneous Near-Surface Boundary Layer over Patchy Snow