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Building upon the efficient implementation of hybrid density functionals (HDFs) for large-scale periodic systems within the framework of numerical atomic orbital bases using the localized resolution of identity (RI) technique, we have developed an algorithm that exploits the space group symmetry in key operation steps of HDF calculations, leading to further improvements in two ways. First, the reduction of -points in the Brillouin zone can reduce the number of Kohn-Sham equations to be solved. This necessitates the correct implementation of the rotation relation between the density matrices of equivalent -points within the representation of atomic orbitals. Second, the reduction of the real-space sector can accelerate the construction of the exact-exchange part of the Hamiltonian in real space. We have implemented this algorithm in the ABACUS software interfaced with LibRI and tested its performance for several types of crystal systems with different symmetries. The expected speed-up is achieved in both aspects: the time of solving the Kohn-Sham equations decreases in proportion with the reduction of -points, while the construction of the Hamiltonian in real space is sped up by several times, with the degree of acceleration depending on the size and symmetry of the system.
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http://dx.doi.org/10.1021/acs.jctc.5c00537 | DOI Listing |
J Appl Stat
February 2025
RBS, International University of Rabat, Technopolis, Sala-Al-Jadida, Morocco.
The paper first highlights important drawbacks and biases related to the common use of time-rescaling to assess the goodness-of-fit (Gof) of self-exciting temporal point process (SETPP) models. Then it presents a new predictive time-rescaling approach leading to an asymptotically unbiased Gof framework for general SETPPs in the case of single observed trajectories. The predictive approach focuses on forecasting accuracy and addresses the bias problem resulting from the plugged-in estimated parameters.
View Article and Find Full Text PDFEur J Public Health
September 2025
Data Governance, Sciensano, Brussels, Belgium.
The European Health Data Space aims to transform health data management across the EU, supporting both primary and secondary uses of health data while ensuring trust through General Data Protection Regulation compliance. As part of the HealthData@EU Pilot, this study investigates coronavirus disease 2019 (COVID-19) testing, vaccination, and hospitalization metrics across six European countries, with a focus on socioeconomic disparities and challenges in cross-border data access and standardization. This observational, retrospective cohort study used a federated analysis framework across Belgium, Croatia, Denmark, Finland, and France.
View Article and Find Full Text PDFInt J Numer Method Biomed Eng
September 2025
School of Mathematics and Statistics, University of Glasgow, Glasgow, UK.
Blood perfusion in cardiac tissues involves intricate interactions among vascular networks and tissue mechanics. Perfusion deficit is one of the leading causes of cardiac diseases, and modeling certain cardiac conditions that are clinically infeasible, invasive, or costly can provide valuable supplementary insights to aid clinicians. However, existing homogeneous perfusion models lack the complexity required for patient-specific simulations.
View Article and Find Full Text PDFBMC Public Health
September 2025
Department of Mathematics, Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau, Gottlieb-Daimler-Str.48, Kaiserslautern, 67663, Germany.
We study the dynamics of coexisting influenza and SARS-CoV-2 by adapting a well-established age-specific COVID-19 model to a multi-pathogen framework. Sensitivity analysis and adjustment of the model to real-world data are used to investigate the influence of age-related factors on disease dynamics. Our findings underscore the critical role that transmission rates play in shaping the spread of influenza and COVID-19.
View Article and Find Full Text PDFBMC Health Serv Res
September 2025
African Population and Health Research Center (APHRC), APHRC Campus, 2nd Floor, Manga Close off Kirawa Road, P.O. Box 10787-00100, Nairobi, Kenya.
Background: Maternal healthcare (MHC) in Cameroon reflects the persistent challenges in Sub-Saharan Africa, where high maternal mortality continues despite improved service utilization, stressing inequitable effective coverage (EC). This study applied EC cascade analysis-including service contact, continuity, and input-adjusted coverage-to quantify geographic and socioeconomic disparities, informing equity-focused strategies to dismantle structural barriers in the MHC continuum.
Methods: We combined population and health facility data (2018 Cameroon Demographic and Health Survey and 2015 Emergency Obstetric and Neonatal Care Assessment) to estimate the input-adjusted coverage of antenatal care (ANC) and intra-and postpartum care (IPC).