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Vaccine efficacy and SARS-CoV-2 control in California and *** the session 2020e2026:A modeling study

Infectious Disease Modelling 2022年第1期7卷 62-81页

作者： Md Shahriar Mahmud Md Kamrujjaman Md Mashih Ibn Yasin Adan Md Alamgir Hossain Md Mizanur Rahman Md Shahidul Islam Muhammad Mohebujjaman Md Mamun Molla Department of Computer Science and Engineering State University of BangladeshDhaka1205Bangladesh Department of Mathematics University of DhakaDhaka1000Bangladesh Department of Mathematics and Statistics University of CalgaryCalgaryABCanada Computational Biology Research Lab(CBRL) Department of PharmacyJagannath UniversityDhaka1100Bangladesh Hitotsubashi Institute for Advanced Study Hitotsubashi UniversityNaka KunitachiTokyo186-8601Japan Department of Mathematics and Physics Texas A&M International UniversityLaredoTX78041USA Department of Mathematics&Physics North South UniversityDhaka1229Bangladesh Center for Applied Scientific Computing(CASC) North South UniversityDhaka1229Bangladesh

Background:Besides maintaining health precautions,vaccination has been the only prevention from SARS-CoV-2,though no clinically proved 100%effective vaccine has been developed till *** this stage,to withhold the debris of this pandemic-experts need to know the impact of the vaccine efficacy rates,the threshold level of vaccine effectiveness and how long this pandemic may extent with vaccines that have different efficacy *** this article,a mathematical model study has been done on the importance of vaccination and vaccine efficiency rate during an ongoing ***:We simulated a five compartment mathematical model to analyze the pandemic scenario in both California,and whole *** considered four vaccines,Pfizer(95%),Moderna(94%),AstraZeneca(79%),and Johnson&Johnson(72%),which are being used rigorously to control the SARS-CoV-2 pandemic,in addition with two special cases:a vaccine with 100%efficacy rate and no vaccine under ***-CoV-2 related data of California,and *** used in this ***:Both the infection and death rates are very high in *** model suggests that the pandemic situation in California will be under control in the last quartile of the year 2023 if vaccination program is continued with the Pfizer *** this time,six waves may happen from the beginning of the immunization where the case fatality and recovery rates will be 1.697%and 98.30%,***,according to the considered model,this period might be extended to the mid of 2024 when vaccines with lower efficacy rates are *** the other hand,the daily cases and deaths in the *** be under control at the end of 2026 with multiple *** the number of susceptible people will fall down to none in the beginning of 2027,there is less chance to stop the vaccination program if vaccinated with a vaccine other than a 100%effective vaccine or Pfizer,and at that case vaccination program must run till the mid of *** to this s

关键词： Vaccine Model California Control measurement SARS-CoV-2

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Sequential Markov Chain Monte Carlo for Lagrangian Data Assimilation with Applications to Unknown Data Locations

arXiv

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arXiv 2023年

作者： Ruzayqat, Hamza Beskos, Alexandros Crisan, Dan Jasra, Ajay Kantas, Nikolas Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Statistical Science University College London LondonWC1E 6BT United Kingdom Department of Mathematics Imperial College London LondonSW7 2AZ United Kingdom

We consider a class of high-dimensional spatial filtering problems, where the spatial locations of observations are unknown and driven by the partially observed hidden signal. This problem is exceptionally challenging as not only is high-dimensional, but the model for the signal yields longer-range time dependencies through the observation locations. Motivated by this model we revisit a lesser-known and provably convergent computational methodology from [4, 11, 28] that uses sequential Markov Chain Monte Carlo (MCMC) chains. We extend this methodology for data filtering problems with unknown observation locations. We benchmark our algorithms on Linear Gaussian state space models against competing ensemble methods and demonstrate a significant improvement in both execution speed and accuracy. Finally, we implement a realistic case study on a high-dimensional rotating shallow water model (of about 104 - 105 dimensions) with real and synthetic data. The data is provided by the National Oceanic and Atmospheric Administration (NOAA) and contains observations from ocean drifters in a domain of the Atlantic Ocean restricted to the longitude and latitude intervals [-51◦,-41◦], [17◦,27◦] *** Codes 62M20, 60G35, 60J20, 94A12, 93E11, 65C40 © 2023, CC BY.

关键词： Location

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EHands: Quantum Protocol for Polynomial Computation on Real-Valued Encoded States

arXiv

引用

arXiv 2025年

作者： Balewski, Jan Amankwah, Mercy G. Bethel, E. Wes Perciano, Talita Van Beeumen, Roel National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Department of Mathematics Applied Mathematics and Statistics Case Western Reserve University ClevelandOH44106 United States Computer Science Department San Francisco State University San FranciscoCA94132 United States Scientific Data Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

The novel constructive EHands protocol defines a universal set of quantum operations for multivariable polynomial transformations on quantum processors by introducing four basic subcircuits—multiplication, addition, negation, and parity flip—and by using expectation-value encoding (EVEN) to represent real numbers in quantum states. These elementary arithmetic operations can be systematically composed to compute degree-d polynomials, Pd(x), on a QPU. The resulting quantum circuit structure closely mirrors the stepwise evaluation of polynomials on a classical calculator, providing an intuitive and efficient approach to polynomial computation on quantum hardware. By enabling direct, predictable polynomial and nonlinear data transformations on a QPU, our method reduces dependence on classical post-processing in hybrid quantum-classical algorithms, enabling advancements in many quantum algorithms. The EHands quantum circuits are compact enough to deliver meaningful and accurate results on today’s noisy quantum processors. We present a detailed implementation of P4(x) and report experimental results for polynomial approximations of common functions, obtained using IBM’s Heron-class quantum processors and an ideal Qiskit simulator. Copyright © 2025, The Authors. All rights reserved.

关键词： Polynomial approximation

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Some hybrid Riemannian conjugate gradient methods with restart strategy

Franklin Open

引用

Franklin Open 2025年 10卷

作者： Salihu, Nasiru Kumam, Poom Salisu, Sani Khammahawong, Konrawut Center of Excellence in Theoretical and Computational Science (TaCS-CoE) Fixed Point Research Laboratory Fixed Point Theory and Applications Research Group Faculty of Science King Mongkut's University of Technology Thonburi (KMUTT) Bangkok 10140 Thailand Department of Mathematics Faculty of Sciences Modibbo Adama University Yola 652105 Nigeria KMUTT-Fixed Point Research Laboratory Room SCL 802 Science Laboratory Building Department of Mathematics Faculty of Science King Mongkut's University of Technology Thonburi (KMUTT) Bangkok 10140 Thailand Department of Mathematics Faculty of Natural and Applied Sciences Sule Lamido University Kafin Hausa Jigawa Nigeria Applied Mathematics for Science and Engineering Research Unit (AMSERU) Department of Mathematics and Computer Science Faculty of Science and Technology Rajamangala University of Technology Thanyaburi (RMUTT) Pathum Thani 12110 Thailand

Hybrid nonlinear conjugate gradient (CG) methods are known to be efficient and have less memory requirement for solving optimization problems in Euclidean spaces. The formulations strategically switch between two or more CG parameters to enhance their general structures. In this work, some hybrid Riemannian CG methods are presented, which are sufficiently descent irrespective of the line search technique employed and converges globally using scaled version of the nonexpensive condition. Finally, the numerical experiments are performed to confirm the strength of the schemes by considering some Riemannian optimization problems. The numerical results obtained when compared to some classical Riemannian CG methods indicated the efficiency of the proposed hybrid Riemannian CG methods. © 2025 The Authors

关键词： Global convergence Retraction Riemannian conjugate gradient method Riemannian optimization Riemannian wolfe conditions Vector transport

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Trumpets: Injective flows for inference and inverse problems

arXiv

引用

arXiv 2021年

作者： Kothari, Konik Khorashadizadeh, AmirEhsan de Hoop, Maarten Dokmanić, Ivan Coordinated Science Laboratory University of Illinois at Urbana-Champaign United States Department of Mathematics and Computer Science University of Basel Switzerland Computational and Applied Mathematics Rice University

We propose injective generative models called TRUMPETs that generalize invertible normalizing flows. The proposed generators progressively increase dimension from a low-dimensional latent space. We demonstrate that TRUMPETs can be trained orders of magnitudes faster than standard flows while yielding samples of comparable or better quality. They retain many of the advantages of the standard flows such as training based on maximum likelihood and a fast, exact inverse of the generator. Since TRUMPETs are injective and have fast inverses, they can be effectively used for downstream Bayesian inference. To wit, we use TRUMPET priors for maximum a posteriori estimation in the context of image reconstruction from compressive measurements, outperforming competitive baselines in terms of reconstruction quality and speed. We then propose an efficient method for posterior characterization and uncertainty quantification with TRUMPETs by taking advantage of the low-dimensional latent space. © 2021, CC BY-NC-SA.

关键词： Image reconstruction

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Anisotropic, multiband, and strong-coupling superconductivity of the Pb0.64Bi0.36 alloy

arXiv

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arXiv 2024年

作者： Gutowska, Sylwia Górnicka, Karolina Wójcik, Pawel Klimczuk, Tomasz Wiendlocha, Bartlomiej University of Vienna Faculty of Physics Center for Computational Materials Science Kolingasse 14-16 ViennaA-1090 Austria AGH University of Krakow Faculty of Physics and Applied Computer Science Aleja Mickiewicza 30 Krakow30-059 Poland Materials Science and Technology Division Oak Ridge National Laboratory Oak RidgeTN United States Faculty of Applied Physics and Mathematics and Advanced Materials Centre Gdansk University of Technology ul. Narutowicza 11/12 Gdansk80-233 Poland

This paper presents theoretical and experimental studies on the superconductivity of Pb0.64Bi0.36 alloy, which is a prototype of strongly coupled superconductors and exhibits one of the strongest coupling under ambient pressure among the materials studied so far. The critical temperature, the specific heat in the superconducting state, and the magnetic critical fields are experimentally determined. Deviations from the single-gap s-wave BCS-like behavior are observed. The electronic structure, phonons and electron-phonon interactions are analyzed in relation to the metallic Pb, explaining why the Pb-Bi alloy exhibits such a large value of the electron-phonon coupling parameter λ 2. Superconductivity is studied using the isotropic Eliashberg formalism as well as the anisotropic density functional theory for superconductors. We find that while Pb is a two-gap superconductor with well-defined separate superconducting gaps, in the Pb-Bi alloy an overlapped three-gap-like structure is formed with a strong anisotropy. Furthermore, the chemical disorder, inherent to this alloy, leads to strong electron scattering, which is found to reduce the critical temperature. © 2024, CC BY.

关键词： Anisotropy

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A Coupled CS-DSG3/BEM Method for Hydroelastic Analysis of Pontoon-Type VLFS with Arbitrary Plan Shape 3rd

A Coupled CS-DSG3/BEM Method for Hydroelastic Analysis of Po...

引用

3rd International Conference on Sustainable Civil Engineering and Architecture, ICSCEA 2023

作者： Luong, Van Hai Nguyen, H.P. Nguyen-Thoi, T. 268 Ly Thuong Kiet Street District 10 Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Linh Trung Ward Thu Duc District Ho Chi Minh City Viet Nam School of Civil Engineering The University of Queensland St LuciaQLD4072 Australia Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Viet Nam Faculty of Mechanical-Electrical and Computer Engineering Van Lang University Ho Chi Minh City Viet Nam

ISBN: (纸本)9789819974337

The cell-based smoothed discrete shear gap method (CS-DSG3) was introduced for analysing Mindlin plates. This method employs three-node triangular elements and can produce solutions with high accuracy. This research aims to combine CS-DSG3 with the Boundary Element Method (BEM) to perform hydroelastic analyses on pontoon-type Very Large Floating Structures (VLFS) with varying plan shapes. In this study, the VLFS is conceptualized as a Mindlin plate resting on an ideal fluid. The structural and fluid domains are discretized using three-node triangular elements. The structural equation is formulated using CS-DSG3, while the water equation is established using BEM. The hydroelastic analysis is conducted within the frequency domain. To validate the accuracy of the CS-DSG3/BEM approach, its results are compared with available published solutions. The proposed method is then employed in parametric investigations involving various VLFS plan shapes to explore how the shape influences hydroelastic responses. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Boundary element method

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Fast Universal Entangling Gate for Superconducting Quantum computers

SSRN

引用

SSRN 2024年

作者： AbuGhanem, Muhammad Homid, Ali H. Obada, A.S.-F. Hendy, Ahmed S. Eleuch, Hichem Faculty of Science Ain Shams University Cairo11566 Egypt Zewail City of Science Technology and Innovation Giza12678 Egypt Mathematics Department Faculty of Science Al-Azhar University Assiut71524 Egypt Mathematics Department Faculty of Science Al-Azher University Nassr City Cairo11884 Egypt Department of Computational Mathematics and Computer Science Institute of Natural Sciences and Mathematics Ural Federal University Yekaterinburg Russia Department of Mathematics Faculty of Science Benha University Benha Egypt Department of Applied Physics and Astronomy University of Sharjah Sharjah27272 United Arab Emirates College of Arts and Sciences Abu Dhabi University Abu Dhabi59911 United Arab Emirates Institute for Quantum Science and Engineering Texas A&M University College StationTX77843 United States

Universal quantum gates are crucial for efficient algorithm execution on quantum computers, offering rapid and fault-tolerant manipulations. This paper presents a theoretical framework for realizing a novel entangling universal quantum gate within the circuit quantum electrodynamics (circuit QED) architecture. Our approach involves positioning two SQUIDs qubits within a resonant single-mode microwave cavity field, enabling the implementation of the SQSCZ gate, a fusion of the square root of SWAP ($\sqrt{SWAP}$) and the square root of controlled-Z ($\sqrt{CZ}$) gates. This gate serves as a fundamental building block for constructing universal quantum gates including the controlled-NOT gates. Moreover, the SQSCZ gate operates unitarily, ensuring logical reversibility, and exhibits an entangling power (EP) of 1.5/9. Quantitative analysis reveals an average gate fidelity of $60\%$. To delve deeper into the gate's performance, we conducted quantum process tomography (QPT) analysis by repeating the quantum experiment 11,000 times for each measurement basis on an IBM Quantum's quantum simulator. This rigorous approach yielded a remarkable process fidelity of $96.065616\%$. These findings offer promising implications for future research and applications. © 2024, The Authors. All rights reserved.

关键词： Qubits

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Bayesian Parameter Inference for Partially Observed SDEs driven by Fractional Brownian Motion

arXiv

引用

arXiv 2022年

作者： Maama, Mohamed Jasra, Ajay Ombao, Hernando Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

In this paper we consider Bayesian parameter inference for partially observed fractional Brownian motion (fBM) models. The approach we follow is to time-discretize the hidden process and then to design Markov chain Monte Carlo (MCMC) algorithms to sample from the posterior density on the parameters given data. We rely on a novel representation of the time discretization, which seeks to sample from an approximation of the posterior and then corrects via importance sampling;the approximation reduces the time (in terms of total observation time T) by O(T). This method is extended by using a multilevel MCMC method which can reduce the computational cost to achieve a given mean square error (MSE) versus using a single time discretization. Our methods are illustrated on simulated and real data. Copyright © 2022, The Authors. All rights reserved.

关键词： Mean square error

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Day-Ahead Forecasting of Solar Irradiance & PV Power Output Through Statistical Machine Learning Methods

Day-Ahead Forecasting of Solar Irradiance & PV Power Output ...

引用

Saudi Arabia Smart Grid Conference (SASG)

作者： Yiannis Kamarianakis Yannis Pantazis Evangelia Kalligiannaki Theodoros D. Katsaounis Konstantinos Kotsovos Issam Gereige Marwan Abdullah Aqil Jamal Athanasios Tzavaras Data Science Group Institute of Applied and Computational Mathematics Foundation for Research and Technology-Hellas Greece Dept. of Mathematics and Applied Mathematics University of Crete Greece Carbon Management Division Saudi Aramco R&D Center Dhahran Saudi Arabia Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

Energy production from solar photovoltaic (PV) plants is unpredictable, mainly due to the stochastic formation and movement of clouds or aerosol - dust particles which scatter or disperse solar radiation. Accurate forecasts of PV output are essential to Distribution and Transportation System Operators as they assist efficient solar energy trading and management of electricity grids. This work evaluates an autoregressive, computationally-light KNN-regression scheme (TSFKNN) for hourly, day-ahead forecasts of solar irradiance and energy yield of various PV technologies. The model is being tested and validated using data measured in Thuwal, Saudi Arabia. The available measured records span a 60-month period. The developed forecasting models are designed for online systems and provide increased levels of accuracy and low computational cost. Several parametric and nonparametric specifications, coupled with conventional versus outlier-robust estimation procedures are tested, in order to derive an optimal month-specific daily profile (MDP). Current results demonstrate that including intraday variability to the monthly-based irradiance models achieve improved predictive accuracy between 10% and 25% on average.

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