Dataset for the paper High durability and stability of 2D nanofluidic devices for long-term single-molecule sensing

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This paper introduces an approach to supporting high-dimensional data cubes at interactive query speeds and moderate storage cost. The approach is based on binary(-domain) data cubes that are judiciously partially materialized; the missing information can ...

Large amounts of data are generated in chemistry labs-nearly all instruments record data in a digital form, yet a considerable proportion is also captured non-digitally and reported in ways non-accessible to both humans and their computational agents. Chem ...

Numerical data for scattering amplitudes of photons in d=4 obtained by solving various optimisation problems. The data is stored in .txt files. Mathematica notebook is provided for loading and plotting the data. ...

This dataset contains corrected particle number concentration data measured during the year long MOSAiC expedition from October 2019 to September 2020. The measurement was performed in the Swiss aerosol container on the D-deck of Research Vessel Polarstern ...

This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) ...

As unconventional sources of geoinformation, massive imagery and text messages from open platforms and social media form a temporally quasi-seamless, spatially multiperspective stream, but with unknown and diverse quality. Due to its complementarity to rem ...

Data cleaning has become an indispensable part of data analysis due to the increasing amount of dirty data. Data scientists spend most of their time preparing dirty data before it can be used for data analysis. Existing solutions that attempt to automate t ...

Designing and implementing online or digital learning material is a demanding task for teachers. This is even more the case when this material is used for more engaged forms of learning, such as inquiry learning. In this article, we give an informed accoun ...

We propose a statistically optimal approach to construct data-driven decisions for stochastic optimization problems. Fundamentally, a data-driven decision is simply a function that maps the available training data to a feasible action. It can always be exp ...

Data transformer apparatus comprising at least a dispatcher module (D), a reader module (R), a converter module (C) and a writer module (W). The dispatcher module (D) is configured to: receive a data transformation request (DTR) including: a first informat ...

In this paper we lay the groundwork for a robust cross-device comparison of data-driven disruption prediction algorithms on DIII-D and JET tokamaks. In order to consistently carry on a comparative analysis, we define physics-based indicators of disruption ...

Dataset for the paper High durability and stability of 2D nanofluidic devices for long-term single-molecule sensing

Chattez avec Graph Search

High-dimensional Data Cubes

Making the collective knowledge of chemistry open and machine actionable

Numerical data for scattering amplitudes of photon in d=4

Continuous corrected particle number concentration data in 10 sec resolution, measured in the Swiss aerosol container during MOSAiC 2019/2020

The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar, and APOGEE-2 Data

Geoinformation Harvesting From Social Media Data: A community remote sensing approach

Holistic, Efficient, and Real-time Cleaning of Heterogeneous Data

Understanding teacher design practices for digital inquiry-based science learning: the case of Go-Lab

A Pareto Dominance Principle for Data-Driven Optimization

Data transformer apparatus

Progress Toward Interpretable Machine Learning-Based Disruption Predictors Across Tokamaks