检索结果-内蒙古大学图书馆

MicroRNA bta-miR-365-3p inhibits proliferation but promotes differentiation of primary bovine myoblasts by targeting the activin A receptor type Ⅰ

学校读者我要写书评

暂无评论

Journal of Animal science and Biotechnology 2021年第1期12卷 141-154页

作者： Dan Hao Xiaogang Wang Xiao Wang Bo Thomsen Yu Yang Xianyong Lan Yongzhen Huang Hong Chen College of Animal Science and Technology Northwest A&F UniversityShaanxi Key Laboratory of Animal GeneticsBreeding and ReproductionYangling 712100ShaanxiChina Department of Molecular Biology and Genetics Aarhus University8000 Aarhus CDenmark Quantitative Genomics Bioinformatics and Computational Biology GroupDepartment of Applied Mathematics and Computer ScienceTechnical University of DenmarkRichard Petersens PladsBuilding 3242800 Kongens LyngbyDenmark.

Background: MicroRNAs act as post-transcriptional regulators that repress translation or degrade mRNA *** microRNA has many mRNA targets and each mRNA may be targeted by several microRNAs. Skeletal muscles express a plethora of microRNA genes that regulate muscle development and function by controlling the expression of protein-coding target genes. To expand our understanding of the role of microRNA, specifically btamiR-365-3 p, in muscle biology, we investigated its functions in regulating primary bovine myoblast proliferation and ***: Firstly, we found that bta-miR-365-3 p was predominantly expressed in skeletal muscle and heart tissue in Chinese Qinchuan beef cattle. Quantitative PCR and western blotting results showed that overexpression of btamiR-365-3 p significantly reduced the expression levels of cyclin D1(CCND1), cyclin dependent kinase 2(CDK2) and proliferating cell nuclear antigen(PCNA) but stimulated the expression levels of muscle differentiation markers, i.e.,MYOD1, MYOG at both mRNA and protein level. Moreover, downregulation of bta-miR-365-3 p increased the expression of CCND1, CDK2 and PCNA but decreased the expression of MYOD1 and MYOG at both mRNA and protein levels. Furthermore, flow cytometry, EdU proliferation assays and immunostaining results showed that increased levels of bta-miR-365-3 p suppressed cell proliferation but promoted myotube formation, whereas decreased levels of bta-miR-365-3 p resulted in the opposite consequences. Finally, we identified that activin A receptor type I(ACVR1) could be a direct target of bta-miR-365-3 p. It was demonstrated that bta-miR-365-3 p can bind to the 3'UTR of ACVR1 gene to regulate its expression based on dual luciferase gene reporter ***, knock-down of ACVR1 was associated with decreased expressions of CDK2, CCND1 and PCNA but increased expression of MYOG and MYOD1 both at mRNA and protein ***: Collectively, these data suggested that bta-m

关键词： ACVR1 Bta-miR-365-3p Cattle Primary bovine myoblast

Global solutions of three-dimensional inviscid MHD fluids with velocity damping in horizontally periodic domains

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Jiang, Fei Jiang, Song Zhaoa, Youyi College of Mathematics and Computer Science Fuzhou University Fuzhou350108 China Institute of Applied Physics and Computational Mathematics Beijing100088 China

The two-dimensional (2D) existence result of global(-in-time) solutions for the motion equations of incompressible, inviscid, non-resistive magnetohydrodynamic (MHD) fluids with velocity damping had been established in [Wu–Wu–Xu, SIAM J. Math. Anal. 47 (2013), 2630–2656]. This paper further studies the existence of global solutions for the three-dimensional (a dimension of real world) initial-boundary value problem in a horizontally periodic domain with finite height. Motivated by the multi-layers energy method introduced in [Guo–Tice, Arch. Ration. Mech. Anal. 207 (2013), 459–531], we develop a new type of two-layer energy structure to overcome the difficulty arising from three-dimensional nonlinear terms in the MHD equations, and thus prove the initial-boundary value problem admits a unique global solution. Moreover the solution has the exponential decay-in-time around some rest state. Our two-layer energy structure enjoys two features: (1) the lower-order energy (functional) can not be controlled by the higher-order energy. (2) under the a priori smallness assumption of lower-order energy, we first close the higher-order energy estimates, and then further close the lower-energy estimates in turn. Copyright © 2021, The Authors. All rights reserved.

关键词： Initial value problems

Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI 41

学校读者我要写书评

暂无评论

Position: Bayesian Deep Learning is Needed in the Age of Lar...

41st International Conference on Machine Learning, ICML 2024

作者： Papamarkou, Theodore Skoularidou, Maria Palla, Konstantina Aitchison, Laurence Arbel, Julyan Dunson, David Filippone, Maurizio Fortuin, Vincent Hennig, Philipp Hernández-Lobato, José Miguel Hubin, Aliaksandr Immer, Alexander Karaletsos, Theofanis Khan, Mohammad Emtiyaz Kristiadi, Agustinus Li, Yingzhen Mandt, Stephan Nemeth, Christopher Osborne, Michael A. Rudner, Tim G.J. Rügamer, David Teh, Yee Whye Welling, Max Wilson, Andrew Gordon Zhang, Ruqi Department of Mathematics The University of Manchester Manchester United Kingdom Eric and Wendy Schmidt Center Broad Institute of MIT and Harvard Cambridge United States Spotify London United Kingdom Computational Neuroscience Unit University of Bristol Bristol United Kingdom Centre Inria de l'Université Grenoble Alpes Grenoble France Department of Statistical Science Duke University United States Statistics Program KAUST Saudi Arabia Helmholtz AI Munich Germany Department of Computer Science Technical University of Munich Munich Germany Munich Center for Machine Learning Munich Germany Tübingen AI Center University of Tübingen Tübingen Germany Department of Engineering University of Cambridge Cambridge United Kingdom Department of Mathematics University of Oslo Oslo Norway Bioinformatics and Applied Statistics Norwegian University of Life Sciences Ås Norway Department of Computer Science ETH Zurich Switzerland Chan Zuckerberg Initiative CA United States Center for Advanced Intelligence Project RIKEN Tokyo Japan Vector Institute Toronto Canada Department of Computing Imperial College London London United Kingdom Department of Computer Science UC Irvine Irvine United States Department of Mathematics and Statistics Lancaster University Lancaster United Kingdom Department of Engineering Science University of Oxford Oxford United Kingdom Center for Data Science New York University New York United States Department of Statistics LMU Munich Munich Germany DeepMind London United Kingdom Department of Statistics University of Oxford Oxford United Kingdom Informatics Institute University of Amsterdam Amsterdam Netherlands Courant Institute of Mathematical Sciences Center for Data Science Computer Science Department New York University New York United States Department of Computer Science Purdue University West Lafayette United States

In the current landscape of deep learning research, there is a predominant emphasis on achieving high predictive accuracy in supervised tasks involving large image and language datasets. However, a broader perspective reveals a multitude of overlooked metrics, tasks, and data types, such as uncertainty, active and continual learning, and scientific data, that demand attention. Bayesian deep learning (BDL) constitutes a promising avenue, offering advantages across these diverse settings. This paper posits that BDL can elevate the capabilities of deep learning. It revisits the strengths of BDL, acknowledges existing challenges, and highlights some exciting research avenues aimed at addressing these obstacles. Looking ahead, the discussion focuses on possible ways to combine large-scale foundation models with BDL to unlock their full potential. Copyright 2024 by the author(s)

关键词： Contrastive Learning

On inhibition of Rayleigh-Taylor instability by horizontal magnetic field in an inviscid MHD fluid with velocity damping

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Jiang, Fei Jiang, Song Zhao, Youyi College of Mathematics and Computer Science Fuzhou University Fuzhou350108 China Institute of Applied Physics and Computational Mathematics Beijing100088 China

It is still an open problem whether the inhibition phenomenon of Rayleigh-Taylor (RT) instability by horizontal magnetic field can be mathematically proved in a non-resistive magnetohydrodynamic (MHD) fluid in a two-dimensional (2D) horizontal slab domain, since it had been roughly verified by a 2D linearized motion equations in 2012 [43]. In this paper, we find that this inhibition phenomenon can be rigorously verified in the inhomogeneous, incompressible, inviscid case with velocity damping. More precisely, there exists a critical number mC such that if the strength |m| of horizontal magnetic field is bigger than mC, then the small perturbation solution around the magnetic RT equilibrium state is exponentially stable in time. Our result is also the first mathematical one based on the nonlinear motion equations for the proof of inhibition of flow instabilities by a horizontal magnetic field in a horizontal slab domain. In addition, we also provide a nonlinear instability result for the case |m| ϵ [0,mC). Our instability result presents that horizontal magnetic field can not inhibit the RT instability, if it's strength is to small. Copyright © 2021, The Authors. All rights reserved.

关键词： Damping

ON THE ROTHE-GALERKIN SPECTRAL DISCRETISATION FOR A CLASS OF VARIABLE FRACTIONAL-ORDER NONLINEAR WAVE EQUATIONS

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Bockstal, Karel V.A.N. Zaky, Mahmoud A. Hendy, Ahmed S. Ghent Analysis & PDE center Department of Mathematics: Analysis Logic and Discrete Mathematics Ghent University Krijgslaan 281 Ghent9000 Belgium Department of Mathematics and Statistics College of Science Imam Mohammad Ibn Saud Islamic University Riyadh Saudi Arabia Department of Applied Mathematics National Research Centre Giza Dokki12622 Egypt Department of Computational Mathematics and Computer Science Institute of Natural Sciences and Mathematics Ural Federal University 19 Mira St. Yekaterinburg620002 Russia Department of Mathematics Faculty of Science Benha University Benha13511 Egypt

In this contribution, a wave equation with a time-dependent variable-order fractional damping term and a nonlinear source is considered. Avoiding the circumstances of expressing the nonlinear variable-order fractional wave equations via closed-form expressions in terms of special functions, we investigate the existence and uniqueness of this problem with Rothe’s method. First, the weak formulation for the considered wave problem is proposed. Then, the uniqueness of a solution is established by employing Grönwall’s lemma. The Rothe scheme’s basic idea is to use Rothe functions to extend the solutions on single-time steps over the entire time frame. Inspired by that, we next introduce a uniform mesh time-discrete scheme based on a discrete convolution approximation in the backward sense. By applying some reasonable assumptions to the given data, we can predict a priori estimates for the time-discrete solution. Employing these estimates side by side with Rothe functions leads to proof of the solution’s existence over the whole time interval. Finally, the full discretisation of the problem is introduced by invoking Galerkin spectral techniques in the spatial direction, and numerical examples are *** Codes 35A01, 35A02, 35A15, 35R11, 65M12, 65M60, 33E12 Copyright © 2023, The Authors. All rights reserved.

关键词： Wave equations

CONVERGENCE SPEED AND APPROXIMATION ACCURACY OF NUMERICAL MCMC

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Cui, Tiangang Dong, Jing Jasra, Ajay Tong, Xin T. School of Mathematics Monash University Australia Graduate School of Business Columbia University United States Applied Mathematics and Computational Science Program Computer Electrical Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Saudi Arabia Department of Mathematics National University of Singapore Singapore

When implementing Markov Chain Monte Carlo (MCMC) algorithms, perturbation caused by numerical errors is sometimes inevitable. This paper studies how perturbation of MCMC affects the convergence speed and Monte Carlo estimation accuracy. Our results show that when the original Markov chain converges to stationarity fast enough and the perturbed transition kernel is a good approximation to the original transition kernel, the corresponding perturbed sampler has similar convergence speed and high approximation accuracy as well. We discuss two different analysis frameworks: ergodicity and spectral gap, both are widely used in the literature. Our results can be easily extended to obtain non-asymptotic error bounds for MCMC estimators. We also demonstrate how to apply our convergence and approximation results to the analysis of specific sampling algorithms, including Random walk Metropolis and Metropolis adjusted Langevin algorithm with perturbed target densities, and parallel tempering Monte Carlo with perturbed densities. Finally we present some simple numerical examples to verify our theoretical claims. Copyright © 2022, The Authors. All rights reserved.

关键词： Inverse problems

WEIGHTED CYLINDRIC PARTITIONS

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Bridges, Walter Uncu, Ali K. University of Cologne Department of Mathematics and Computer Science Weyertal 86-90 Cologne50931 Germany Johann Radon Institute for Computational and Applied Mathematics Austrian Academy of Science Altenbergerstraße 69 LinzA-4040 Austria University of Bath Faculty of Science Department of Computer Science BathBA2 7AY United Kingdom

Recently Corteel and Welsh outlined a technique for finding new sum-product identities by using functional relations between generating functions for cylindric partitions and a theorem of Borodin. Here, we extend this framework to include very general product-sides coming from work of Han and Xiong. In doing so, we are led to consider structures such as weighted cylindric partitions, symmetric cylindric partitions and weighted skew double shifted plane partitions. We prove some new identities and obtain new proofs of known identities, including the Göllnitz-Gordon and Little Göllnitz identities as well as some beautiful Schmidt-type identities of Andrews and *** Codes Primary 05A15, Secondary 05A17, 11B65, 11P81, 11P84 © 2022, CC0.

关键词： Algebra

A numerical method for solving elliptic equations on real closed algebraic curves and surfaces

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Hao, Wenrui Hauenstein, Jonathan D. Regan, Margaret H. Tang, Tingting Department of Mathematics Penn State University University ParkPA16802 United States Department of Applied and Computational Mathematics and Statistics University of Notre Dame Notre DameIN46556 United States Department of Mathematics and Computer Science College of the Holy Cross WorcesterMA01610 United States Department of Mathematics and Statistics San Diego State University San DiegoCA92182 United States

There are many numerical methods for solving partial different equations (PDEs) on manifolds such as classical implicit, finite difference, finite element, and isogeometric analysis methods which aim at improving the interoperability between finite element method and computer aided design (CAD) software. However, these approaches have difficulty when the domain has singularities since the solution at the singularity may be multivalued. This paper develops a novel numerical approach to solve elliptic PDEs on real, closed, connected, orientable, and almost smooth algebraic curves and surfaces. Our method integrates numerical algebraic geometry, differential geometry, and a finite difference scheme which is demonstrated on several examples. Copyright © 2023, The Authors. All rights reserved.

关键词： Numerical methods

Learning A Coarse-to-Fine Diffusion Transformer for Image Restoration

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Wang, Liyan Yang, Qinyu Wang, Cong Wang, Wei Pan, Jinshan Su, Zhixun School of Mathematical Sciences Dalian University of Technology Dalian China The Key Laboratory for Computational Mathematics and Data Intelligence of Liaoning Province The Liaoning Center for Applied Mathematics China The Department of Computing The Hong Kong Polytechnic University Hong Kong Dalian University of Technology Dalian China The School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China

Recent years have witnessed the remarkable performance of diffusion models in various vision tasks. However, for image restoration that aims to recover clear images with sharper details from given degraded observations, diffusion-based methods may fail to recover promising results due to inaccurate noise estimation. Moreover, simple constraining noises cannot effectively learn complex degradation information, which subsequently hinders the model capacity. To solve the above problems, we propose a coarse-to-fine diffusion Transformer (C2F-DFT) for image restoration. Specifically, our C2F-DFT contains diffusion self-attention (DFSA) and diffusion feed-forward network (DFN) within a new coarse-to-fine training scheme. The DFSA and DFN respectively capture the long-range diffusion dependencies and learn hierarchy diffusion representation to facilitate better restoration. In the coarse training stage, our C2FDFT estimates noises and then generates the final clean image by a sampling algorithm. To further improve the restoration quality, we propose a simple yet effective fine training scheme. It first exploits the coarse-trained diffusion model with fixed steps to generate restoration results, which then would be constrained with corresponding ground-truth ones to optimize the models to remedy the unsatisfactory results affected by inaccurate noise estimation. Extensive experiments show that C2F-DFT significantly outperforms diffusion-based restoration method IR-SDE and achieves competitive performance compared with Transformer-based state-of-the-art methods on 3 tasks, including image deraining, image deblurring, and real image denoising. Code is available at https://***/wlydlut/C2F-DFT. Copyright © 2023, The Authors. All rights reserved.

关键词： Image reconstruction