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We have applied the Coulomb and proximity potential model,CPPM to calculate the half lives for various clusters decay of the selected even-even isotopes of the chosen nuclei. These nuclei are Hf, W, Os, Pt, and Hg in the 5d transition metal…

Nuclear Theory · Physics 2016-01-14 K. E. Abd El Mageed , L. I. Abou Salem , K. A. Gado , Asmaa G. Shalaby

In this article, we consider the Chew, Goldberger \& Low (CGL) plasma flow equations, which is a set of nonlinear, non-conservative hyperbolic PDEs modelling anisotropic plasma flows. These equations incorporate the double adiabatic…

Numerical Analysis · Mathematics 2024-06-10 Chetan Singh , Anshu Yadav , Deepak Bhoriya , Harish Kumar , Dinshaw S. Balsara

Model distillation has been a popular method for producing interpretable machine learning. It uses an interpretable "student" model to mimic the predictions made by the black box "teacher" model. However, when the student model is sensitive…

Machine Learning · Statistics 2023-05-01 Yunzhe Zhou , Peiru Xu , Giles Hooker

A hybrid approach combining the Tabular Prior-data Fitted Network (TabPFN) with the Coulomb and Proximity Potential Model (CPPM) is developed to investigate $\alpha$-particle preformation factors $P_{\alpha}$ and their impact on…

Nuclear Theory · Physics 2026-03-12 Panpan Qi , Xuanpeng Xiao , Gongming Yu , Haitao Yang , Qiang Hu

Weight decay is a standard regularization technique for training large language models (LLMs). While it is common to assign a uniform decay rate to every layer, this approach overlooks the structural diversity of LLMs and the varying…

Computation and Language · Computer Science 2025-11-06 Di He , Songjun Tu , Ajay Jaiswal , Li Shen , Ganzhao Yuan , Shiwei Liu , Lu Yin

The alpha-decay half-lives and the alpha-capture cross-sections are evaluated in the framework of unified model for alpha-decay and alpha-capture. In the framework of this model the alpha-decay and alpha-capture are considered as…

Nuclear Theory · Physics 2010-12-02 V. Yu. Denisov , A. A. Khudenko

We present a review of the Non-additive Stochastic Model for supercooled liquids (NSM), an efficient approach for diffusive processes that provides a suitable interpretation for the non-Arrhenius dynamics in these materials. Based on a…

Nine models were evaluated as candidate glomerular filtration rate (GFR) reference standards in three datasets using [$^{51}$Cr(EDTA)]$^-$ or [$^{169}$Yb(DTPA)]$^{2-}$ anions in 98 studies. Noncompartmental methods formed an upper limit for…

Quantitative Methods · Quantitative Biology 2024-01-26 Carl A. Wesolowski

Deep learning-based fluence map prediction(DL-FMP) method has been reported in the literature, which generated fluence maps for desired dose by deep neural network(DNN)-based inverse mapping. We hypothesized that DL-FMP is similar to…

Medical Physics · Physics 2021-05-03 Lin Ma , Mingli Chen , Xuejun Gu , Weiguo Lu

We introduceDropDim, a structured dropout method designed for regularizing the self-attention mechanism, which is a key component of the transformer. In contrast to the general dropout method, which randomly drops neurons, DropDim drops…

Computation and Language · Computer Science 2023-04-21 Hao Zhang , Dan Qu , Keji Shao , Xukui Yang

Semi-Lagrangian (SL) schemes are known as a major numerical tool for solving transport equations with many advantages and have been widely deployed in the fields of computational fluid dynamics, plasma physics modeling, numerical weather…

Numerical Analysis · Mathematics 2023-08-09 Yongsheng Chen , Wei Guo , Xinghui Zhong

The discrete direct deconvolution model (D3M) is developed for the large-eddy simulation (LES) of turbulence. The D3M is a discrete approximation of previous direct deconvolution model studied by Chang et al. ["The effect of sub-filter…

Fluid Dynamics · Physics 2024-02-16 Ning Chang , Zelong Yuan , Yunpeng Wang , Jianchun Wang

We report a new detection of neutral deuterium in the sub Damped Lyman Alpha system with low metallicity [O/H]\,=\,$-2.042 \pm 0.005$ at $z_{\rm abs}=2.437$ towards QSO~J\,1444$+$2919. The hydrogen column density in this system is…

Astrophysics of Galaxies · Physics 2016-04-06 S. A. Balashev , E. O. Zavarygin , A. V. Ivanchik , K. N. Telikova , D. A. Varshalovich

The scalability of Generalized Linear Models (GLMs) for large-scale, high-dimensional data often forces a trade-off between computational feasibility and statistical accuracy, particularly for inference on pre-specified parameters. While…

Methodology · Statistics 2025-12-09 Bo Fu , Dandan Jiang

The assessment of left atrial appendage (LAA) thrombogenesis has experienced major advances with the adoption of patient-specific computational fluid dynamics (CFD) simulations. Nonetheless, due to the vast computational resources and long…

Machine Learning · Computer Science 2022-10-20 Xabier Morales , Jordi Mill , Guillem Simeon , Kristine A. Juhl , Ole De Backer , Rasmus R. Paulsen , Oscar Camara

Recently, V.Yu. Denisov proposed a new empirical formula incorporating the deformation of the daughter nucleus, which has significantly improved the description of $\alpha$-decay half-lives for even-even nuclei compared to formulas…

Nuclear Theory · Physics 2026-04-10 Jinyu Hu , Chen Wu

This paper addresses the efficient solution of linear systems arising from curl-conforming finite element discretizations of $H(\mathrm{curl})$ elliptic problems with heterogeneous coefficients. We first employ the discrete form of a…

Numerical Analysis · Mathematics 2025-06-10 Chupeng Ma , Yongwei Zhang

In this paper, we carefully look at the $\alpha$ -decay half-lives of 196 even-even nuclei using a two-potential approach that is made better by taking into account an alpha particle's effective mass that changes with coordinates. The…

Nuclear Theory · Physics 2025-10-22 Jinyu Hu , Chen Wu

In this paper, a finite volume element (FVE) method is considered for spatial approximations of time-fractional diffusion equations involving a Riemann-Liouville fractional derivative of order $\alpha \in (0,1)$ in time. Improving upon…

Numerical Analysis · Mathematics 2017-02-14 Samir Karaa , Amiya K. Pani

We develop a machine-learning framework to predict the electron localization function (ELF) of pure, dense hydrogen directly from atomic geometry, bypassing explicit electronic-structure calculations. Trained on first-principles data…