The cosmic large-scale structure (LSS) provides a unique testing ground for connecting fundamental physics to astronomical observations. Modeling the LSS requires numerical N-body simulations or perturbative techniques that both come with distinct shortcomings. Here we present the first unified numerical approach, enabled by new time integration and discreteness reduction schemes, and demonstrate its convergence at the field level. In particular, we show that our simulations (i) can be initialized directly at time zero, and (ii) can be made to agree with high-order Lagrangian perturbation theory in the fluid limit. This enables fast, self-consistent, and UV-complete forward modeling of LSS observables.
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http://dx.doi.org/10.1103/PhysRevLett.132.131003 | DOI Listing |
Chemosphere
December 2024
Department of Civil, Environmental and Ocean Engineering, Stevens Institute of Technology, 1 Castle Point Terrace, Hoboken, NJ, 07030, USA. Electronic address:
Phosphate (PO(III)) contamination in water bodies poses significant environmental challenges, necessitating efficient and accurate methods to predict and optimize its removal. The current study addresses this issue by predicting the adsorption capacity of PO(III) ions onto biochar-based materials using five probabilistic machine learning models: eXtreme Gradient Boosting LSS (XGBoostLSS), Natural Gradient Boosting, Bayesian Neural Networks (NN), Probabilistic NN, and Monte-Carlo Dropout NN. Utilizing a dataset of 2952 data points with 16 inputs, XGBoostLSS demonstrated the highest R (0.
View Article and Find Full Text PDFJ Med Internet Res
December 2024
Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Background: Lumbar spinal stenosis (LSS) is a major cause of pain and disability in older individuals worldwide. Although increasing studies of traditional machine learning (TML) and deep learning (DL) were conducted in the field of diagnosing LSS and gained prominent results, the performance of these models has not been analyzed systematically.
Objective: This systematic review and meta-analysis aimed to pool the results and evaluate the heterogeneity of the current studies in using TML or DL models to diagnose LSS, thereby providing more comprehensive information for further clinical application.
Br J Clin Pharmacol
December 2024
Department of Pharmacology, Toxicology and Pharmacovigilance, CHU de Limoges, Limoges, France.
Aims: Mycophenolic acid (MPA), the active component of enteric-coated mycophenolate sodium (EC-MPS), exhibits highly variable pharmacokinetics. Only a few population pharmacokinetic (popPK) models and Bayesian estimators (MAP-BE) exist for estimating MPA AUC and all in renal transplantation. This study aimed to develop a popPK model and MAP-BE for MPA AUC estimation using a limited sampling strategy (LSS) in solid organ transplant (SOT), haematopoietic stem cell (HSC) recipients and patients with autoimmune diseases (AID) on EC-MPS.
View Article and Find Full Text PDFNat Commun
December 2024
Department of Biochemistry, University of Washington, Seattle, WA, 98195, USA.
Pseudosymmetric hetero-oligomers with three or more unique subunits with overall structural (but not sequence) symmetry play key roles in biology, and systematic approaches for generating such proteins de novo would provide new routes to controlling cell signaling and designing complex protein materials. However, the de novo design of protein hetero-oligomers with three or more distinct chains with nearly identical structures is a challenging unsolved problem because it requires the accurate design of multiple protein-protein interfaces simultaneously. Here, we describe a divide-and-conquer approach that breaks the multiple-interface design challenge into a set of more tractable symmetric single-interface redesign tasks, followed by structural recombination of the validated homo-oligomers into pseudosymmetric hetero-oligomers.
View Article and Find Full Text PDFJ Clin Med
November 2024
Department of Neurosurgery, College of Medicine, The University of Tennessee Health Sciences, Memphis, TN 38163, USA.
Lumbar spinal stenosis (LSS) is a major cause of chronic lower back and leg pain, and is traditionally diagnosed through labor-intensive analysis of magnetic resonance imaging (MRI) scans by radiologists. This study aims to streamline the diagnostic process by developing an automated radiology report generation (ARRG) system using a vision-language (VL) model. We utilized a Generative Image-to-Text (GIT) model, originally designed for visual question answering (VQA) and image captioning.
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