A first implementation of analytic gradients for spinor-based relativistic equation-of-motion coupled-cluster singles and doubles method using an exact two-component Hamiltonian augmented with atomic mean-field spin-orbit integrals is reported. To demonstrate its applicability, we present calculations of equilibrium structures and harmonic vibrational frequencies for the electronic ground and excited states of the radium mono-amide molecule (RaNH2) and the radium mono-methoxide molecule (RaOCH3). Spin-orbit coupling is shown to quench Jahn-Teller effects in the first excited state of RaOCH3, resulting in a C3v equilibrium structure. The calculations also show that the radium atoms in these molecules serve as efficient optical cycling centers.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1063/5.0175041 | DOI Listing |
Sensors (Basel)
December 2024
Laboratory of Reinforced Concrete and Seismic Design, Department of Civil Engineering, Democritus University of Thrace, 67100 Xanthi, Greece.
One of the most critical components of reinforced concrete structures are beam-column joint systems, which greatly affect the overall behavior of a structure during a major seismic event. According to modern design codes, if the system fails, it should fail due to the flexural yielding of the beam and not due to the shear failure of the joint. Thus, a reliable tool is required for the prediction of the failure mode of the joints in a preexisting population of structures.
View Article and Find Full Text PDFHum Brain Mapp
January 2025
Amsterdam UMC, Department of Radiology and Nuclear Medicine, University of Amsterdam, Amsterdam, the Netherlands.
Accurately predicting individual antidepressant treatment response could expedite the lengthy trial-and-error process of finding an effective treatment for major depressive disorder (MDD). We tested and compared machine learning-based methods that predict individual-level pharmacotherapeutic treatment response using cortical morphometry from multisite longitudinal cohorts. We conducted an international analysis of pooled data from six sites of the ENIGMA-MDD consortium (n = 262 MDD patients; age = 36.
View Article and Find Full Text PDFAnn Epidemiol
January 2025
School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Pietermaritzburg Campus, Pietermaritz.
Purpose: Epidemiologic studies are important in assessing risk factors of mortality. Machine learning (ML) is efficient in analyzing multidimensional data to unravel dependencies between risk factors and health outcomes.
Methods: Using a representative sample from the National Health and Nutrition Examination Survey data collected from 2009 to 2016 linked to the National Death Index public-use mortality data through December 31, 2019, we applied logistic, random forests, k-Nearest Neighbors, multivariate adaptive regression splines, support vector machines, extreme gradient boosting, and super learner ML algorithms to study risk factors of all-cause mortality.
Int J Pharm
January 2025
BioDev Drug Product Development Department, WuXi Biologics, 190 Hedan Road, Shanghai 200131, China. Electronic address:
In the realm of therapeutic antibodies, co-formulations comprising two or more monoclonal antibodies (mAbs) have emerged as a promising strategy, offering enhanced treatment efficacy, improved efficiency, and prolonged intellectual property protection. These advantages have sparked significant interest among both patients and pharmaceutical companies. However, the quantification and analysis of individual mAbs within such co-formulations pose a substantial challenge due to their similar physicochemical properties.
View Article and Find Full Text PDFJ Chromatogr B Analyt Technol Biomed Life Sci
December 2024
Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa. Electronic address:
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!