Lithium tantalate photonic integrated circuits for volume manufacturing

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Information regarding the Dataset, corresponding to the paper: “Thakur, M., Cai, N., Zhang, M. et al. High durability and stability of 2D nanofluidic devices for long-term single-molecule sensing. npj 2D Mater Appl 7, 11 (2023). https://doi.org/10.1038/s41 ...

This dataset supports the publication 'Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid' by Lebo Molefe and John M. Kolinski, Physical Review E, (2023). The data are surface profiles of textured surf ...

Data-driven control can facilitate the rapid development of controllers, offering an alternative to conventional approaches. In order to maintain consistency between any known underlying physical laws and a data-driven decision-making process, preprocessin ...

Raw data associated with the publication "Host starvation and in hospite degradation of algal symbionts shape the heat stress response of the Cassiopea-Symbiodiniaceae symbiosis". Temperature profile, daily measurements, physiological measurements, element ...

Raw data and Matlab scripts from the publication at https://doi.org/10.1021/jacs.3c01279 All codes are provided free of charge and come with no warranty. Future use (original or modified) is required to cite: Zenedo data deposit at DOI 10.5281/zenodo. ...

Data repository for the following publication: A. Duque-Prata*, H.-Y. Chen*, L. Müller, M. Oppermann, M. Puppin, C. Serpa, C. Bostedt and M. Chergui, “Ultrafast deep-ultraviolet study of photoexcited aqueous Ferrioxalate”, submitted to ChemPhotoCh ...

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems". The corresponding scripts can be accessed on GitHub (https://github.com/axgoujon/convex_ridge_regularizers). The data is organized as follows: - ct_data_sets.tar.gz: contains prepr ...

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 ...

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 ...

We demonstrate a hybrid photonic integrated laser with intrinsic linewidth of 40 Hz, while offering megahertz actuation bandwidth with the tuning range larger than 1 GHz, attained by a DFB laser self-injection locking to a high-Q Si3N4 microresonator with ...

A traditional machine learning pipeline involves collecting massive amounts of data centrally on a server and training models to fit the data. However, increasing concerns about the privacy and security of user's data, combined with the sheer growth in the ...

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 ...

The constant flux of data and queries alike has been pushing the boundaries of data analysis systems. The increasing size of raw data files has made data loading an expensive operation that delays the data-to-insight time. To alleviate the loading cost, in ...

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 ...

We propose GoldFinger, a new compact and fast-to-compute binary representation of datasets to approximate Jaccard’s index. We illustrate the effectiveness of GoldFinger on the emblematic big data problem of K-Nearest-Neighbor (KNN) graph construction and s ...

Data cleaning is a time-consuming process that depends on the data analysis that users perform. Existing solutions treat data cleaning as a separate offline process that takes place before analysis begins. Applying data cleaning before analysis assumes a p ...

We propose fingerprinting, a new technique that consists in constructing compact, fast-to-compute and privacy-preserving binary representations of datasets. We illustrate the effectiveness of our approach on the emblematic big data problem of K-Nearest-Nei ...

Participatory sensing has become a new data collection paradigm that leverages the wisdom of the crowd for big data applications without spending cost to buy dedicated sensors. It collects data from human sensors by using their own devices such as cell pho ...

Lithium tantalate photonic integrated circuits for volume manufacturing

Chattez avec Graph Search

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

Dataset for "Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid"

Physically Consistent Multiple-Step Data-Driven Predictions Using Physics-Based Filters

Data for "Host starvation and in hospite degradation of algal symbionts shape the heat stress response of the Cassiopea-Symbiodiniaceae symbiosis"

Imaging radial distribution functions of complex particles by relayed dynamic nuclear polarization

Data for "Ultrafast deep-ultraviolet study of photoexcited aqueous Ferrioxalate"

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems"

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

High-dimensional Data Cubes

Low-noise, Frequency-agile, Hybrid Integrated Laser for LiDAR

Optimization methods for collaborative learning

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

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

Adaptive partitioning and indexing for in situ query processing

Progress Toward Interpretable Machine Learning-Based Disruption Predictors Across Tokamaks

Smaller, Faster & Lighter KNN Graph Constructions

Cleaning Denial Constraint Violations through Relaxation

Query-driven Repair of Functional Dependency Violations

Fingerprinting Big Data: The Case of KNN Graph Construction

Efficient User Guidance for Validating Participatory Sensing Data