We describe our citizen science approach and technologies designed to introduce students in upper secondary schools to computational thinking and engineering. Using an Arduino microcontroller and low-cost sensors we have developed the air:bit, a programmable sensor kit that students build and program to collect air quality data. In our course, students develop their own research questions regarding ...

Rupture of the plate boundary fault during the 2011 Tohoku-oki earthquake with moment magnitude 9.0 is thought to have propagated to the trench. Surface exposure of the fault has not yet been confirmed because of great depths that are challenging to access and study. Using a manned submersible in the Japan Trench, we explored and visually assessed the seafloor near the epicenter. On the eastern slope ...

An important part of diagnostics is to gain insight into properties that characterize a disease. Machine learning has been used for this purpose, for instance, to identify biomarkers in genomics. However, when patient data are presented as images, identifying properties that characterize a disease becomes far more challenging. A common strategy involves extracting features from the images and ...

The risk of sea-spray icing on vessels and marine structures in cold regions highlights the need for an accurate and robust marine-icing estimation model. To develop such a model, it is crucial to accurately determine the quantity of liquid water available for freezing on the structure, as it directly influences ice formation. As sea spray constitutes the primary source of liquid water contributing ...

Herein, we report the synthesis of highly reduced bipyridyl magnesium complexes and the first example of a stable organic magnesium electride supported by quantum mechanical computations and X-ray diffraction. These complexes serve as unconventional homogeneous reductants due to their high solubility, modular redox potentials, and formation of insoluble, non-coordinating byproducts. The applicability ...

A major barrier to applying deep segmentation models in the medical domain is their typical data-hungry nature, requiring experts to collect and label large amounts of data for training. As a reaction, prototypical few-shot segmentation (FSS) models have recently gained traction as data-efficient alternatives. Nevertheless, despite the recent progress of these models, they still have some essential ...

A class of DNA folds/structures known collectively as G-quadruplexes (G4) commonly forms in guanine-rich areas of genomes. G4-DNA is thought to have a functional role in the regulation of gene transcription and telomerase-mediated telomere maintenance and, therefore, is a target for drugs. The details of the molecular interactions that cause stacking of the guanine-tetrads are not well-understood, ...

Symmetry assumptions on the geometrical framework have provided successful mechanisms to develop physically meaningful solutions to many problems. In tele-parallel gravity, invariance of the frame and spin-connection under a group of motions defines an affine symmetry group. Here, we assume there exists a three-dimensional group of affine symmetries acting simply transitively on a spatial hypersurface ...

Patient-gathered self-management data and shared decision-making are touted as the answer to improving an individual’s health situation as well as collaboration between patients and their providers leading to more effective treatment plans. However, there is a gap between this ideal and reality – a lack of data-sharing technology. Here, we present the impact that the FullFlow System for sharing ...

Deep learning has the potential to revolutionize medical practice by automating and performing important tasks like detecting and delineating the size and locations of cancers in medical images. However, most deep learning models rely on augmentation techniques that treat medical images as natural images. For contrast-enhanced Computed Tomography (CT) images in particular, the signals producing the ...