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While there exist a plethora of deep learning tools and frameworks, the fast-growing complexity of the field brings new demands and challenges, such as more flexible network design, speedy computation on distributed setting, and…
For many decades, experimental solid mechanics has played a crucial role in characterizing and understanding the mechanical properties of natural and novel materials. Recent advances in machine learning (ML) provide new opportunities for…
The purpose of this article is to review the current status of a frontier in dynamic spintronics and contemporary magnetism, in which much progress has been made in the past decade, based on the creation of a variety of micro- and…
The continuous evolution of cities poses significant challenges in terms of managing and understanding their complex dynamics. With the increasing demand for transparency and the growing availability of open urban data, it has become…
Geophysical electromagnetics (EM) plays an important role in mineral exploration and is increasingly being used to help solve other problems of relevance to society. In this article we reflect, from our perspective at University of British…
Recent results obtained by various authors on the properties of HgMn stars are reviewed. Substantial progress has been achieved in the study of abundances and isotopic anomalies. The results about the magnetic fields and membership in…
The field of neutrino physics is currently very exciting, with several recent results pointing to new physics. I will give an overview of the current experimental situation, focusing primarily on neutrino oscillation results. The data are…
A virtual observatory will not only enhance many current scientific investigations, but it will also enable entirely new scientific explorations due to both the federation of vast amounts of multiwavelength data and the new archival…
Some recent advances in the theoretical description of the Nucleon electromagnetic form factors, both in the space- and time-like regions, will be briefly illustrated. In particular, both the present stage of the lattice calculations and…
Photonic devices play an increasingly important role in advancing physics and engineering, and while improvements in nanofabrication and computational methods have driven dramatic progress in expanding the range of achievable optical…
Data-driven science is heralded as a new paradigm in materials science. In this field, data is the new resource, and knowledge is extracted from materials data sets that are too big or complex for traditional human reasoning - typically…
Information extraction can support novel and effective access paths for digital libraries. Nevertheless, designing reliable extraction workflows can be cost-intensive in practice. On the one hand, suitable extraction methods rely on…
The present technical notes offer a brief summary of the essential points of electromagnetism at the undergraduate physics level. Some problems are presented at the end of each section; those with solutions are marked with an asterisk.
Most major scientific results produced by ground-based gamma-ray telescopes in the last 30 years have been obtained by expert members of the collaborations operating these instruments. This is due to the proprietary data and software…
Several important and unique experimental high-energy physics programmes at a variety of facilities are coming to an end, including those at HERA, the B-factories and the Tevatron. The wealth of physics data from these experiments is the…
A brief outlook on low-energy nuclear physics is presented. Selected recent developments in nuclear structure theory are highlighted and a few open questions are discussed.
Many applications from camera arrays to sensor networks require efficient compression and processing of correlated data, which in general is collected in a distributed fashion. While information-theoretic foundations of distributed…
This paper provides a review of developments in the physics of two-dimensional electron systems in perpendicular magnetic fields.
High-quality datasets are typically required for accomplishing data-driven tasks, such as training medical diagnosis models, predicting real-time traffic conditions, or conducting experiments to validate research hypotheses. Consequently,…
New technologies for acquiring biological information such as eDNA, acoustic or optical sensors, make it possible to generate spatial community observations at unprecedented scales. The potential of these novel community data to standardize…