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Non-Stokesian dynamics of magnetic helical nanoswimmers under confinement

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arXiv 2023年

作者： Fazeli, Alireza Thakore, Vaibhav Ala-Nissila, Tapio Karttunen, Mikko Department of Mathematics Western University 1151 Richmond Street LondonONN6A 5B7 Canada Center for Advanced Materials and Biomaterials Research Western University 1151 Richmond Street LondonONN6A 5B7 Canada Multiscale Statistical and Quantum Physics Group Quantum Technology Finland Centre of Excellence Department of Applied Physics Aalto University P.O. Box 11000 Aalto EspooFI-00076 Finland Interdisciplinary Centre for Mathematical Modelling Department of Mathematical Sciences Loughborough University Loughborough LeicestershireLE11 3TU United Kingdom Department of Physics and Astronomy Western University 1151 Richmond Street LondonONN6A 5B7 Canada Department of Chemistry Western University 1151 Richmond Street LondonONN6A 3K7 Canada

Electromagnetically propelled helical nanoswimmers offer great potential for nanorobotic applications. Here, the effect of confinement on their propulsion is characterized using lattice-Boltzmann simulations. Two principal mechanisms give rise to their forward motion under confinement: 1) pure swimming, and 2) the thrust created by the differential pressure due to confinement. Under strong confinement, they face greater rotational drag, but display a faster propulsion for fixed driving frequency in agreement with experimental findings. This is due to the increased differential pressure created by the boundary walls when they are sufficiently close to each other and the particle. Two new analytical relations are presented: 1) for predicting the swimming speed of an unconfined particle as a function of its angular speed and geometrical properties, and 2) an empirical expression to accurately predict the propulsion speed of a confined swimmer as a function of the degree of confinement and its unconfined swimming speed. At low driving frequencies and degrees of confinement, the systems retain the expected linear behavior consistent with the predictions of the Stokes equation. However, as the driving frequency and/or the degree of confinement increase, their impact on propulsion leads to increasing deviations from the Stokesian regime and emergence of nonlinear behavior. Copyright © 2023, The Authors. All rights reserved.

关键词： Forecasting

Assessing the reliability of wind power operations under a changing climate with a non-Gaussian bias correction

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arXiv 2020年

作者： Zhang, Jiachen Crippa, Paola Genton, Marc G. Castruccio, Stefano Department of Applied and Computational Mathematics and Statistics University of Notre Dame United States Department of Civid and Environmental Engineering and Geoscience University of Notre Dame United States Statistics Program King Abdullah University of Science and Technology Saudi Arabia

Facing increasing societal and economic pressure, many countries have established strategies to develop renewable energy portfolios, whose penetration in the market can alleviate the dependence on fossil fuels. In the case of wind, there is a fundamental question related to the resilience, and hence profitability, of future wind farms to a changing climate, given that current wind turbines have lifespans of up to thirty years. In this work we develop a new non-Gaussian method to adjust assimilated observational data to simulations and to estimate future wind, predicated on a trans-Gaussian transformation and a cluster-wise minimization of the Kullback-Leibler divergence. Future winds abundance will be determined for Saudi Arabia, a country with a recently established plan to develop a portfolio of up to 16 GW of wind energy. Further, we estimate the change in profits over future decades using additional high-resolution simulations, an improved method for vertical wind extrapolation and power curves from a collection of popular wind turbines. We find an overall increase in daily profit of $272,000 for the wind energy market for the optimal locations for wind farming in the country. Copyright © 2020, The Authors. All rights reserved.

关键词： Wind power

A deep learning-based ODE solver for chemical kinetics

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arXiv 2020年

作者： Zhang, Tianhan Zhang, Yaoyu Weinan, E. Ju, Yiguang Department of Mechanical and Aerospace Engineering Princeton University PrincetonNJ08544 United States School of Mathematical Sciences Institute of Natural Sciences MOE-LSC Qing Yuan Research Institute Shanghai Jiao Tong University Shanghai200240 China Department of Mathematics Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

Developing efficient and accurate algorithms for chemistry integration is a challenging task due to its strong stiffness and high dimensionality. The current work presents a deep learning-based numerical method called DeepCombustion0.0 to solve stiff ordinary differential equation systems. The homogeneous autoignition of DME/air mixture, including 54 species, is adopted as an example to illustrate the validity and accuracy of the algorithm. The training and testing datasets cover a wide range of temperature, pressure, and mixture conditions between 750 – 1200 K, 30 – 50 atm, and equivalence ratio = 0.7 – 1.5. Both the first-stage low-temperature ignition (LTI) and the second-stage high-temperature ignition (HTI) are considered. The methodology highlights the importance of the adaptive data sampling techniques, power transform preprocessing, and binary deep neural network (DNN) design. By using the adaptive random samplings and appropriate power transforms, smooth submanifolds in the state vector phase space are observed, on which two three-layer DNNs can be appropriately trained. The neural networks are end-to-end, which predict temporal gradients of the state vectors directly. The results show that temporal evolutions predicted by DNN agree well with traditional numerical methods in all state vector dimensions, including temperature, pressure, and species concentrations. Besides, the ignition delay time differences are within 1%. At the same time, the CPU time is reduced by more than 20 times and 200 times compared with the HMTS and VODE method, respectively. The current work demonstrates the enormous potential of applying the deep learning algorithm in chemical kinetics and combustion modeling. © 2020, CC BY.

关键词： Numerical methods

Mathematical modeling and mechanisms of HIV latency for personalized anti latency therapies

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npj Systems Biology and Applications 2025年第1期11卷 1-11页

作者： Gianmarco Rasi Nicola Cotugno Paolo Palma Elena Emili Jessica M. Conway Research Unit of Clinical Immunology and Vaccinology Bambino Gesù Children’s Hospital IRCCS 00165 Rome Italy PhD Program in Immunology Molecular Medicine and Applied Biotechnology University of Rome “Tor Vergata” 00133 Rome Italy Department of Systems Medicine University of Rome “Tor Vergata” 00133 Roma Italy Department of Mathematics and Center for Infectious Disease Dynamics Pennsylvania State University University Park PA USA

Combination antiretroviral therapy controls human immunodeficiency virus-1 (HIV) but cannot eradicate latent proviruses in immune cells, which reactivate upon treatment interruption. Anti-latency therapies like “shock-and-kill” are being developed but are yet to succeed due to the complexity of latency mechanisms. This review discusses recent advances in understanding HIV latency via mathematical modeling, covering key regulatory factors and models to predict latency reversal, highlighting gaps to guide future therapeutic approaches.

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Phase equilibrium of water with hexagonal and cubic ice using the SCAN functional

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arXiv 2021年

作者： Piaggi, Pablo Miguel Panagiotopoulos, Athanassios Z. Debenedetti, Pablo G. Car, Roberto Department of Chemistry Princeton University PrincetonNJ08544 United States Department of Chemical and Biological Engineering Princeton University PrincetonNJ08544 United States Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States Department of Physics Princeton University PrincetonNJ08544 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

Machine learning models are rapidly becoming widely used to simulate complex physicochemical phenomena with ab initio accuracy. Here, we use one such model as well as direct density functional theory (DFT) calculations to investigate the phase equilibrium of water, hexagonal ice (Ih), and cubic ice (Ic), with an eye towards studying ice nucleation. The machine learning model is based on deep neural networks and has been trained on DFT data obtained using the SCAN exchange and correlation functional. We use this model to drive enhanced sampling simulations aimed at calculating a number of complex properties that are out of reach of DFT-driven simulations and then employ an appropriate reweighting procedure to compute the corresponding properties for the SCAN functional. This approach allows us to calculate the melting temperature of both ice polymorphs, the driving force for nucleation, the heat of fusion, the densities at the melting temperature, the relative stability of ice Ih and Ic, and other properties. We find a correct qualitative prediction of all properties of interest. In some cases, quantitative agreement with experiment is better than for state-of-the-art semiempirical potentials for water. Our results also show that SCAN correctly predicts that ice Ih is more stable than ice Ic. Copyright © 2021, The Authors. All rights reserved.

关键词： Ice

Bidirectional shooting method for extreme nonlinear optics

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Physical Review A 2019年第5期100卷 053818-053818页

作者： A. Hofstrand P. Jakobsen J. V. Moloney Program in Applied Mathematics University of Arizona Tucson Arizona 85721 USA College of Optical Sciences University of Arizona Tucson Arizona 85721 USA Department of Mathematics and Statistics University of Tromso 9037 Tromso Norway

In this paper we introduce a pseudospectral shooting method to model intense, ultrashort optical pulses incident on remote targets. The method naturally extends the unidirectional pulse propagation equation to include backward propagating radiation due to either nonlinear coupling with the “forward” field or reflections generated at material boundaries. The general applicability of the method is highlighted with several examples, including a full simulation of a pulse propagating through air across an ultrathin gold film coated on fused silica.

关键词： Nonlinear optics

Optical spin conductivity in ultracold quantum gases

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Physical Review Research 2022年第4期4卷 043014-043014页

作者： Yuta Sekino Hiroyuki Tajima Shun Uchino Quantum Hadron Physics Laboratory RIKEN Nishina Center (RNC) Wako Saitama 351-0198 Japan Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS) RIKEN Wako Saitama 351-0198 Japan RIKEN Cluster for Pioneering Research (CPR) Astrophysical Big Bang Laboratory (ABBL) Wako Saitama 351-0198 Japan Department of Mathematics and Physics Kochi University Kochi 780-8520 Japan Department of Physics Graduate School of Science The University of Tokyo Tokyo 113-0033 Japan Advanced Science Research Center Japan Atomic Energy Agency Tokai Ibaraki 319-1195 Japan Waseda Institute for Advanced Study Waseda University Shinjuku Tokyo 169-8050 Japan

We show that the optical spin conductivity, which is a small ac response of a bulk spin current and elusive in condensed matter systems, can be measured in ultracold atoms. We demonstrate that this conductivity contains rich information on quantum states by analyzing experimentally achievable systems such as a spin-12 superfluid Fermi gas, a spin-1 Bose-Einstein condensate, and a Tomonaga-Luttinger liquid. The obtained conductivity spectra, which are absent in the Drude conductivity, reflect quasiparticle excitations and non-Fermi-liquid properties. Accessible physical quantities include the superfluid gap and the contact for the superfluid Fermi gas, gapped and gapless spin excitations as well as quantum depletion for the Bose-Einstein condensate, and the spin part of the Tomonaga-Luttinger liquid parameter elusive in cold-atom experiments. Unlike its mass transport counterpart, the spin conductivity serves as a probe applicable to clean atomic gases without disorder or lattice potentials. Our formalism can be generalized to various systems such as spin-orbit-coupled and nonequilibrium systems.

关键词： Cold atoms & matter waves Fermi gases Fermionic condensates Spin current Spinor Bose-Einstein condensates Spintronics Ultracold gases

Differential gene expression in trabecular bone osteocytes is related to the local strain and strain gradient

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Scientific reports 2025年第1期15卷 18501页

作者： Meghana Machireddy Sarah Nano Lucas Debiase Jonathan Lewis Sara Cole Jun Li Glen L Niebur University of Notre Dame Bioengineering Graduate Program Notre Dame IN USA. Department of Aerospace and Mechanical Engineering Notre Dame IN USA. Notre Dame Integrated Imaging Facility Notre Dame IN USA. Department of Applied and Computational Mathematics and Statistics University of Notre Dame Notre Dame IN USA. University of Notre Dame Bioengineering Graduate Program Notre Dame IN USA. gniebur@nd.edu. Department of Aerospace and Mechanical Engineering Notre Dame IN USA. gniebur@nd.edu.

Osteocytes regulate the response of osteoclasts and osteoblasts to mechanical loading through signaling molecules, the levels of which are controlled by post-translational modification or degradation and by differential gene transcription and translation. The magnitude and mode of bone tissue deformation that elicits a transcriptional response in individual osteocytes in situ has been difficult to quantify. We measured SOST, Wnt11, TNF, and FRZB gene expression in osteocytes within loaded and unloaded control porcine trabecular bone explants using RNAScope® and compared the local tissue level strain and strain gradient-which we used as an indicator of potential poroelastic fluid flow-in the tissue surrounding osteocytes with high vs. low gene expression. The measured expression of all four genes differed between loaded and unloaded explants, on average, with the mean SOST expression level decreasing by 45%. In the loaded explants, gene expression was altered from baseline in about 30% of the osteocytes, and they were surrounded by tissue with higher strain and strain gradient than the 20 to 25% of osteocytes that remained near baseline expression. Both deviatoric strain and hydrostatic strain gradient were sensitive and specific predictors of the mechanobiological response for individual genes as well as combinations. SOST expression was highly related to elevated strain gradient, providing evidence that osteocytes respond to fluid flow in the lacunar-canalicular system.

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The ternary goldbach problem with two piatetski-shapiro primes and a prime with a missing digit

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arXiv 2020年

作者： Maier, Helmut Rassias, Michael Th Department of Mathematics University of Ulm Helmholtzstrasse 18 Ulm89081 Germany Institute of Mathematics University of Zurich ZurichCH-8057 Switzerland Moscow Institute of Physics and Technology 141700 Dolgoprudny Institutskiy per d. 9 Russia Institute for Advanced Study Program in Interdisciplinary Studies 1 Einstein Dr PrincetonNJ08540 United States

Let γ "98 ` 23logp10{9q p« 0.919 . . .q . log 10 Let γ ă γ0 ď 1, c0 "1{γ0 be fixed. Let also a0 P t0, 1, . . ., 9u. We prove on assumption of the Generalized Riemann Hypothesis that each sufficiently large odd integer N0 can be represented in the form N0 "p1 ` p2 ` p3, where the pi are of the form pi "rnci0 s, ni P N, for i "1, 2 and the decimal expansion of p3 does not contain the digit a0. The proof merges methods of J. Maynard from his paper on the infinitude of primes with restricted digits, results of A. Balog and J. Friedlander on Piatetski-Shapiro primes and the Hardy-Littlewood circle method in two variables. This is the first result on the ternary Goldbach problem with primes of mixed type which involves primes with missing *** Codes 11P32, 11N05, 11A63 Copyright © 2020, The Authors. All rights reserved.

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