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arXiv 2024年

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. © 2024, CC BY-NC-ND.

关键词： Large datasets

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Pore size estimation in axon-mimicking microfibres with diffusion-relaxation MRI

arXiv

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arXiv 2023年

作者： Canales-Rodríguez, Erick J. Pizzolato, Marco Zhou, Feng-Lei Barakovic, Muhamed Thiran, Jean-Philippe Jones, Derek K. Parker, Geoffrey J.M. Dyrby, Tim B. Lausanne Switzerland Centre for Functional and Diagnostic Imaging and Research Copenhagen University Hospital Amager and Hvidovre Copenhagen Denmark Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby Denmark Centre for Medical Image Computing Department of Medical Physics and Biomedical Engineering University College London London United Kingdom MicroPhantoms Limited Cambridge United Kingdom Basel Department of Biomedical Engineering University Hospital Basel University of Basel Basel Switzerland Radiology Department Centre Hospitalier Universitaire Vaudois University of Lausanne Lausanne Switzerland EPFL Lausanne Switzerland Cardiff University Brain Research Imaging Centre Cardiff University Wales Cardiff United Kingdom Department of Neuroinflammation Queen Square Institute of Neurology University College London London United Kingdom Bioxydyn Limited Manchester United Kingdom

Purpose: This study aims to evaluate two distinct approaches for fibre radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfibre phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approach and a T2-based pore size estimation technique. Theory and Methods: A general diffusion-relaxation theoretical model for the spherical mean signal from water molecules within a distribution of cylinders with varying radii was introduced, encompassing the evaluated models as particular cases. Additionally, a new numerical approach was presented for estimating effective radii (i.e., MRI-visible mean radii) from the ground truth radii distributions, not reliant on previous theoretical approximations and adaptable to various acquisition sequences. The ground truth radii were obtained from Scanning Electron Microscope images. Results: Both methods show a linear relationship between effective radii estimated from MRI data and ground-truth radii distributions, though some discrepancies were observed. The spherical mean power-law method overestimated fibre radii. Conversely, the T2-based method exhibited higher sensitivity to smaller fibre radii but faced limitations in accurately estimating the radius in one particular phantom, possibly due to material-specific relaxation changes. Conclusion: The study demonstrates the feasibility of both techniques to predict pore sizes of hollow microfibres. The T2-based technique, unlike the spherical mean power-law method, does not demand ultra-high diffusion gradients but requires calibration with known radius distributions. This research contributes to the ongoing development and evaluation of neuroimaging techniques for fibre radius estimation, highlights the advantages and limitations of both methods and provides datasets for reproducible research. © 2023, CC BY.

关键词： Diffusion

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Radiation and gyrotactic microorganisms in Walter-B nanofluid flow over a stretching sheet

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Journal of Radiation Research and applied Sciences 2025年第3期18卷

作者： Muhammad Shaheen Hakeem Ullah Mehreen Fiza Aasim Ullah Jan Ali Akgül A.S. Hendy Samira Elaissi Ilyas Khan Mohsen Bakhori N.F.M. Noor Department of Mathematics Abdul Wali Khan University Mardan 23200 Khyber Pakhtunkhwa Pakistan Department of Mathematics and Statistics Bacha Khan University Charsadda Khyber Pakhtunkhwa Pakistan Department of Electronics and Communication Engineering Saveetha School of Engineering SIMATS Chennai Tamilnadu India Siirt University Art and Science Faculty Department of Mathematics 56100 Siirt Turkey Applied Science Research Center Applied Science Private University Amman 11937 Jordan Department of Computational Mathematics and Computer Science Institute of Natural Sciences and Mathematics Ural Federal University 19 Mira St. Yekaterinburg 620002 Russia Department of Mechanics and Mathematics Western Caspian University Baku 1001 Azerbaijan Department of Physics College of Sciences Princes Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia Department of Mathematics College of Science Al-Zulfi Majmaah University Al-Majmaah 11952 Saudi Arabia Department of Medical Equipment Technology College of Applied Medical Science Majmaah University Majmaah 11952 Saudi Arabia Institute of Mathematical Sciences Faculty of Science Universiti Malaya 50603 Kuala Lumpur Malaysia

The present study investigates the flow characteristics of both homogeneous and heterogeneous Walter-B nanofluids induced by a stretching sheet. Special attention is given to the effects of melting and magnetic fields on the flow behavior. The distribution of motile microorganisms is modeled using a microbial conservation equation, incorporating key parameters such as the Lewis number, Peclet number, and the microorganism difference parameter. The influence of thermal radiation and the heterogeneous reaction parameter is also considered. To facilitate the analysis, the governing partial differential equations are transformed into a set of ordinary differential equations using similarity transformations. A convergent series solution is then obtained through the application of the Homotopy Analysis Method (HAM). The study further explores the effects of various physical parameters, including the Prandtl number, magnetic field intensity, radiation, thermophoresis, Brownian motion, bioconvection, Peclet number, and the microorganism difference parameter. Results indicate that the velocity field decreases with an increase in the magnetic parameter, while the temperature profile diminishes with higher values of the radiation parameter. Furthermore, the concentration of microorganisms is observed to decline with increasing Lewis number.

关键词： Walter-B Homogeneous and heterogeneous reaction Radiation Bioconvection Melting phenomena

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Synthesis of Fe₃O₄-NH₂-APTES@rGO@SiO₂ core–shell magnetic microspheres for efficient aqueous phenol photocatalytic degradation

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Results in Physics 2024年 62卷

作者： Ur Rehman, Ghani Tahir, Muhammad Goh, P.S. Baba Basha, D. Ismail, A.F. Alhazmi, Hadil Abdul Wahab, Roswanira Samavati, Alireza Khan, Ilyas Department of Chemistry Faculty of Science Universiti Teknologi Malaysia Johor Skudai 81310 UTM Malaysia Chemical and Petroleum Engineering Department United Arab Emirates University P.O. Box 15551 Al Ain United Arab Emirates Department of information systems college of computer and information sciences Majmaah University Al Majmaah -11952 Saudi Arabia Department of Mathematical Sciences College of Science Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia Advanced Membrane Technology Research Centre (AMTEC) Universiti Teknologi Malaysia Johor Bahru Skudai 81310 Malaysia Department of Mathematics College of Science Al-Zulﬁ Majmaah University Al-Majmaah Saudi Arabia Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman Jordan

This study aims to synthesize a ternary Fe3O4-NH2-APTES@rGO@SiO2 core–shell magnetic microspheres by modified Stöber technique to photodegrade aqueous phenol under UV-C light effectively. Results of the X-ray di... 详细信息

This study aims to synthesize a ternary Fe₃O₄-NH₂-APTES@rGO@SiO₂ core–shell magnetic microspheres by modified Stöber technique to photodegrade aqueous phenol under UV-C light effectively. Results of the X-ray diffractogram of the as-synthesized Fe₃O₄-NH₂-APTES@rGO@SiO₂ core–shell magnetic microspheres showed the nanoparticles having an average size of 126.00 nm, comparable to 150.00 nm seen in the FESEM micrograph. These sizes were supported by the EDX and FTIR results which verified the presence of Fe₃O₄, rGO, and SiO₂, and the TEM micrograph revealed them to be spherically shaped. Also, the thermally more stable microspheres than the pure individual components and binary nanocomposites were evident in their corresponding TGA ***, the photoluminescence spectra of the Fe₃O₄-NH₂-APTES@rGO@SiO₂ microspheres supported their higher photodegrading ability as a consequence of an extended e^-/h⁺ recombination rate. The microspheres were more effective in photo-catalytically degrading the highest amount of aqueous phenol (∼89 %) than Fe₃O₄-NH₂-APTES@rGO (∼74 %), Fe₃O₄-NH₂-APTES@SiO₂ (∼78 %), and pure Fe₃O₄ (∼62 %), under an optimized condition of 0.2 g/350 mL catalyst loading and 50 ppm of initial phenol concentration. The enhanced photoactivity was ascribed to the high stability and specific surface of SiO₂, the synergistic influence of Fe₃O₄, and the rGO sheet's rapid electron transport·H₂O₂ enhanced phenol degradation to 94 %. © 2024

关键词： Fe3O4-NH2-APTES@rGO@SiO2 microsphere Modified Stöber method Phenol Photodegradation

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Random pulse sequences for qubit noise spectroscopy

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Physical Review applied 2025年第5期23卷 054090-054090页

作者： Kaixin Huang Demitry Farfurnik Alireza Seif Mohammad Hafezi Yi-Kai Liu Joint Quantum Institute (JQI) NIST/University of Maryland College Park Maryland 20742 USA Joint Center for Quantum Information and Computer Science (QuICS) NIST/University of Maryland College Park Maryland 20742 USA Department of Electrical and Computer Engineering and Department of Physics North Carolina State University Raleigh North Carolina 27695 USA Pritzker School of Molecular Engineering University of Chicago Chicago Illinois 60637 USA Applied and Computational Mathematics Division National Institute of Standards and Technology (NIST) Gaithersburg Maryland 20899 USA

Qubit noise spectroscopy is an important tool for the experimental investigation of open quantum systems. However, conventional techniques for noise spectroscopy are time-consuming, because they require measurements of the noise spectral density at many different frequencies. Here we describe an alternative approach to noise spectroscopy, which requires fewer resources, and relies on direct measurement of arbitrary linear functionals of the noise spectral density. This method uses random pulse sequences with carefully controlled correlations, which are chosen using algorithms for phase retrieval. These measurements allow us to reconstruct sparse noise spectra via compressed sensing. Our simulations of the performance of the random pulse sequences on a realistic physical system, self-assembled quantum dots, reveal a speedup of an order of magnitude in extracting the noise spectrum, compared to conventional dynamical decoupling approaches.

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Fixed Point Technique: Stability Analysis of Quadratic Functional Equation in Various Quasi-Banach Spaces

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Journal of mathematics 2025年第1期2025卷

作者： Kandhasamy Tamilvanan Faruk Özger S. A. Mohiuddine Naeem Ahmad Masho Jima Kabeto Department of Mathematics Faculty of Science & Humanities R.M.K. Engineering College Kavaraipettai Tiruvallur 601206 Tamil Nadu India rmkec.ac.in Department of Computer Engineering Iğdır University Iğdır 76000 Türkiye Department of General Required Courses Mathematics The Applied College King Abdulaziz University Jeddah 21589 Saudi Arabia kau.edu.sa Operator Theory and Applications Research Group Department of Mathematics Faculty of Science King Abdulaziz University Jeddah 21589 Saudi Arabia kau.edu.sa Department of Mathematics College of Science Jouf University Sakaka 72388 Saudi Arabia ju.edu.sa Department of Mathematics College of Natural Sciences Jimma University P. O. Box 378 Jimma Ethiopia ju.edu.et

In this present work, we derive the solution of a quadratic functional equation and investigate the Ulam stability of this equation in Banach spaces using fixed point and direct techniques. Mainly, we examine the stability results in quasi- β -Banach spaces and quasi-fuzzy β -Banach spaces by means of direct method as well as quasi-Banach spaces by means of alternative fixed point theorem in the sense of generalized b -metric spaces. To further establish the instability of a single case, an appropriate counterexample is also provided.

关键词： 39B32 39B82 46S40 fixed point quasi-fuzzy β-Banach space quasi-Banach space

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Enhanced heat transfer in nanofluid flow via prabhakar fractional models for solar thermal systems

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Journal of Radiation Research and applied Sciences 2025年第3期18卷

作者： Shajar Abbas Ghada Ragheb Elnaggar Ahmad Shafique Ioan-Lucian Popa S. Saleem Muhammad Ramzan Mumtaz Ahmad Centre for Advanced Studies in Pure and Applied Mathematics Bahauddin Zakariya University Multan Pakistan AS (Ayub Shah) Institute of Mathematics and Research Centre Multan Pakistan Industrial and Systems Engineering Department College of Engineering Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia Department of Computing Mathematics and Electronics “1 Decembrie 1918” University of Alba Iulia 15 510009 Alba Iulia Romania Faculty of Mathematics and Computer Science Transilvania University of Brasov Iuliu Maniu Street 50 500091 Brasov Romania Department of Mathematics College of Science King Khalid University Abha 61413 Saudi Arabia Center for Artificial Intelligence (CAI) King Khalid University Abha 61421 Saudi Arabia Department of Mathematics University of Sargodha Sargodha Pakistan

This study presents a comprehensive thermal analysis of non-Newtonian nanofluid flow influenced by solar thermal radiation, with direct applications in industrial engineering, renewable energy systems, and thermal management. The objective is to evaluate the performance of a second-grade nanofluid in a parabolic trough solar collector (PTSC), focusing on the impacts of chemical reaction, mass and heat transport. The model assumes a copper–PVA-water nanofluid infused with gyrotactic microorganisms to enhance thermal conductivity and bioconvection. The dimensionless governing equations for velocity, temperature, concentration, and bioconvection are formulated using Fourier's and Fick's laws and calculated analytically via the Laplace integral transform. Results reveal that a 10 % increase in nanoparticle volume fraction leads to a 15 % improvement in temperature distribution, while the electric field parameter increases fluid velocity by 12 %. Aditionally, increase in bioconvection Lewis and Peclet numbers significantly reduce microorganism concentration by approximately 20 %. The study demonstrates that fractional-order models offer better control of transport mechanisms and that second-grade nanofluids improve heat transfer efficiency. These findings highlights the promise of of such fluids in solar thermal systems, industrial engineering processes, and energy-efficient system design.

关键词： Solar radiation Prabhakar derivative Gyrotactic microorganisms Laplace integral transform

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Correction to: Fractional-order chaotic oscillator-based Aquila optimization algorithm for maximization of the chaotic with Lorentz oscillator

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Neural Computing and Applications 2023年第2期36卷 1045-1045页

作者： Cavlak, Yakup Ateş, Abdullah Abualigah, Laith Elaziz, Mohammed Abd Engineering Faculty Computer Engineering Department Inonu University Malatya Turkey Computer Science Department Prince Hussein Bin Abdullah Faculty for Information Technology Al Al-Bayt University Mafraq Jordan College of Engineering Yuan Ze University Taoyuan Taiwan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman Jordan Department of Mathematics Faculty of Science Zagazig University Zagazig Egypt Faculty of Computer Science and Engineering Galala University Suez Egypt Artificial Intelligence Research Center (AIRC) College of Engineering and Information Technology Ajman University Ajman UAE Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

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Dynamic regulation of resource transport induces criticality in interdependent networks of excitable units

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Physical Review E 2020年第2期101卷 022303-022303页

作者： Yogesh S. Virkar Juan G. Restrepo Woodrow L. Shew Edward Ott Department of Computer Science University of Colorado at Boulder Boulder Colorado 80309 USA Department of Applied Mathematics University of Colorado at Boulder Boulder Colorado 80309 USA Department of Physics University of Arkansas Fayetteville Arkansas 72701 USA Departments of Electrical and Computer Engineering and of Physics University of Maryland College Park Maryland 20742 USA

Various functions of a network of excitable units can be enhanced if the network is in the “critical regime,” where excitations are, on average, neither damped nor amplified. An important question is how can such networks self-organize to operate in the critical regime. Previously, it was shown that regulation via resource transport on a secondary network can robustly maintain the primary network dynamics in a balanced state where activity doesn't grow or decay. Here we show that this internetwork regulation process robustly produces a power-law distribution of activity avalanches, as observed in experiments, over ranges of model parameters spanning orders of magnitude. We also show that the resource transport over the secondary network protects the system against the destabilizing effect of local variations in parameters and heterogeneity in network structure. For homogeneous networks, we derive a reduced three-dimensional map which reproduces the behavior of the full system.

关键词： Collective behavior in networks Critical phenomena Network diffusion Neuronal dynamics Neuronal networks Transport in networks 3-dimensional systems Brain network Collective dynamics Erdos-Renyi graph Multilayer & multiplex networks

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Extending the limit of molecular dynamics with ab initio accuracy to 10 billion atoms

arXiv

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arXiv 2022年

作者： Guo, Zhuoqiang Lu, Denghui Yan, Yujin Hu, Siyu Liu, Rongrong Tan, Guangming Sun, Ninghui Jiang, Wanrun Liu, Lijun Chen, Yixiao Zhang, Linfeng Chen, Mohan Wang, Han Jia, Weile Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China State Key Laboratory of Computer Architecture ICT Chinese Academy of Sciences Beijing China HEDPS CAPT College of Engineering Peking University Beijing China AI for Science Institute Beijing China Osaka University Osaka Japan Princeton University Princeton United States DP Technology Beijing China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing China

High-performance computing, together with a neural network model trained from data generated with first-principles methods, has greatly boosted applications of ab initio molecular dynamics in terms of spatial and temporal scales on modern supercomputers. Previous state-of-the-art can achieve 1 − 2 nanoseconds molecular dynamics simulation per day for 100-million atoms on the entire Summit supercomputer. In this paper, we have significantly reduced the memory footprint and computational time by a comprehensive approach with both algorithmic and system innovations. The neural network model is compressed by model tabulation, kernel fusion, and redundancy removal. Then optimizations such as acceleration of customized kernel, tabulation of activation function, MPI+OpenMP parallelization are implemented on GPU and ARM architectures. Testing results of the copper system show that the optimized code can scale up to the entire machine of both Fugaku and Summit, and the corresponding system size can be extended by a factor of 134 to an © 2022, CC BY-NC-SA.

关键词： Supercomputers

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