The Molecular Spectroscopy Group is an Interest Group of the Royal Society of Chemistry and exists to promote the latest advances in the fields of molecular spectroscopy. We are running a programme of ...

Department of Mathematics and Statistics, Oakland University, Rochester, MI, USA.

While court staff was always well-trained and up to the task, the new rules mandate that judges directly oversee jury selection, a directive clearly designed to reduce potential biases ...

This is, however, not true for electronic Raman transitions (refs. 1, 2 and unpublished results), and this has important implications in the selection rules for these transitions.

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

In this paper, we propose the Stereo Molecular Graph BERT (SMG-BERT) by integrating the 3D space geometric parameters, 2D topological information, and 1D SMILES string into the self-attention-based ...

enabling the direct detection of selection rules for resonant tunnelling between topological surface states. Here the authors identify silicon as an optimal element for anchoring oxygen on copper ...

Hence, the stock selection must be accurate.Here are some of the stock selection rules for intraday trading that will allow you to pick stocks for Intraday trading successfully: 8 Rules for ...

ABSTRACT: This article constructs statistical selection procedures for exponential populations that may differ in only the threshold parameters. The scale parameters of the populations are assumed ...

A recent study by Romina Wild and SISSA Professor Alessandro Laio, along with Felix Wodaczek, Vittorio Del Tatto, and Bingqing Cheng, published in the journal Nature Communications, introduces a new ...

Feb. 7, 2025 — A complex molecular machine, the spliceosome, ensures that the genetic information from the genome, after being transcribed into mRNA precursors, is correctly assembled into ...

Therefore, the generalizability of machine learning models benefits from feature selection, which aims to extract only the most “informative” features and remove noisy “non-informative,” irrelevant ...