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arXiv 2023年

作者： Mohammed, Mozzamil Brännström, Åke Landi, Pietro Dieckmann, Ulf Institute for Chemistry and Biology of the Marine Environment University of Oldenburg Oldenburg Germany Advancing Systems Analysis Program International Institute for Applied Systems Analysis Laxenburg Austria Department of Mathematics and Mathematical Statistics Umeå University Umeå Sweden Applied Mathematics Division Department of Mathematical Sciences Stellenbosch University Stellenbosch South Africa Okinawa Onna904-0495 Japan

Plant-frugivore interactions play a central role for plant persistence and spatial distribution by promoting the long-range dispersal of seeds by frugivores. However, plant-frugivore interactions are increasingly being threatened by anthropogenic activities. An important anthropogenic threat that could expose plant-frugivore systems to extinction risk is fruit harvesting. Here, we develop an individual-based and a pair-approximation model of plant-frugivore-human interactions to elucidate the effects of human harvesting of fruits on plant establishment, persistence, and spatial distribution. Our results show that frugivores strongly affect global density of plants and gradually shift their spatial distribution from aggregated to random, depending on the attack rate and dispersal efficiency of frugivores. We find that, in the absence of frugivores, plants experiencing intense fruit harvesting cannot persist even if their fecundity is high. In the presence of frugivores, fruit harvesting profoundly affects the global dispersal of seeds and thus changes the spatial distributions of plants from random to aggregated, potentially causing plant extinction. Our results demonstrate that sufficiently efficient frugivores mitigate the negative impact of fruit harvesting on plant populations and enable plant establishment precluded by harvesting. Taken together, these results draw attention to previously underappreciated impacts of fruit harvesting in plant-frugivore-human interactions. Copyright © 2023, The Authors. All rights reserved.

关键词： Spatial distribution

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Temporal and phenological profiles of open and dense Caatinga using remote sensing:response to precipitation and its irregularities

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Journal of Forestry Research 2021年第3期32卷 1067-1076页

作者： Janisson Batista de Jesus Tatiana Mora Kuplich íkaro Daniel de Carvalho Barreto Cristiano Niederauer da Rosa Fernando Luis Hillebrand Postgraduate Program in Remote Sensing Federal University of Rio Grande Do SulAv.Bento GoncalvesCEP 91501-970Porto AlegreRio Grande do Sul 9500Brazil National Institute for Space Research(INPE)Southern Regional Centre(CRS) CEP 97105-970Santa MariaRio Grande do SulBrazil Postgraduate Program in Applied Biometrics and Statistics Rural Federal University of PernambucoDom Manuel de Medeiross/nDois IrmaosCEP 52171-900RecifePernambucoBrazil

Caatinga is a typical biome of Brazil's semiarid regions and subject to climate *** is needed on the relation of its features to climate *** study analyzed the infl uence of rainfall and its irregularities in open and dense woody Caatinga *** curves were generated by means of Normalized Difference Vegetation Index(NDVI)time profiles in the Grota do Angico Conservation Unit study area in Sergipe *** data from 2000 to 2018 were collected and phenological curves generated using various estimate methods that produced the following variables:[start of season,end of season,peak of season position,length of season,mean growing season and maximum seasonal].Rainfall showed a standard intra-annual behavior,with inter-annual variations related to irregularities infl uencing Caatinga *** Caatinga vegetation had higher values of NDVI in all periods,even in anomalous years compared to open Caatinga,in addition to having longer leaf coverage over the year,with an anticipated start and a more extended seasonal *** analysis of the rainfall regime made it possible to assess its infl uence on the Caatinga and phenological profiles proved to be fundamental to understand periods of physiological change of open and dense *** results indicate that dense Caatinga maintains physiological activity longer,which may be associated with greater moisture maintenance in a semiarid *** addition,because it has a greater leaf cover for longer periods,the soil may be preserved and maintain its characteristics longer,reducing the effects of *** results may be associated with the type of forest management and conservation in this *** total or partial suppression of individual remnants of Caatinga should be avoided,since the most open areas have lower photosynthetic capacity,affected to a considerable extent from the effects of adverse climatic ***,open Caatinga has a reduced cap

关键词： Semiarid Tropical dry forest NDVI MODIS Phenopix

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Classical and Quantum Phase Transitions in Multiscale Media: Universality and Critical Exponents in the Fractional Ising Model

arXiv

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arXiv 2025年

作者： Lewis, Joshua M. Carr, Lincoln D. Quantum Engineering Program Colorado School of Mines 1523 Illinois St. GoldenCO80401 United States Department of Physics Colorado School of Mines 1523 Illinois St. GoldenCO80401 United States Department of Applied Mathematics and Statistics Colorado School of Mines 1523 Illinois St. GoldenCO80401 United States

Until now multiscale quantum problems have appeared to be out of reach at the many-body level relevant to strongly correlated materials and current quantum information devices. In fact, they can be modeled with q-th order fractional derivatives, as we demonstrate in this work, treating classical and quantum phase transitions in a fractional Ising model for 0 D of the system tied geometrically to the anomalous dimension η. We discover that for classical systems, HD is precisely equal to the fractional order q. In contrast, for quantum systems, HD deviates from this direct equivalence, scaling more gradually, driven by additional degrees of freedom introduced by quantum fluctuations. These results reveal how fractional derivatives fundamentally modify the fractal geometry of many-body interactions, directly influencing the universal symmetries of the system and overcoming traditional dimensional restrictions on phase transitions. Specifically, we find that for q © 2025, CC BY.

关键词： Degrees of freedom (mechanics)

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Langevin Equations in the Small-Mass Limit: Higher-Order Approximations

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Annales Henri Poincare 2020年第6期21卷 1765-1811页

作者： Birrell, Jeremiah Wehr, Jan Department of Mathematics and Statistics University of Massachusetts Amherst Amherst 01003 MA United States Department of Mathematics and Program in Applied Mathematics University of Arizona Tucson 8572 AZ United States

We study the small-mass (overdamped) limit of Langevin equations for a particle in a potential and/or magnetic field with matrix-valued and state-dependent drift and diffusion. We utilize a bootstrapping argument to derive a hierarchy of approximate equations for the position degrees of freedom that are able to achieve accuracy of order m^ℓ ^/ ² over compact time intervals for any ℓ∈ Z⁺. This generalizes prior derivations of the homogenized equation for the position degrees of freedom in the m→ 0 limit, which result in order m^{1 / 2} approximations. Our results cover bounded forces, for which we prove convergence in L^p norms and unbounded forces, in which case we prove convergence in probability. © 2020, Springer Nature Switzerland AG.

关键词： 60H10 82C31

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Investigation of factors regarding the effects of COVID-19 pandemic on college students’ depression by quantum annealer

arXiv

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arXiv 2023年

作者： Choi, Junggu Kim, Kion Park, Soohyun Hur, Juyoen Yang, Hyunjung Kim, Younghoon Lee, Hakbae Han, Sanghoon Yonsei Graduate program in Cognitive Science Yonsei University Seoul03722 Korea Republic of Korea Quantum Computing© Seoul06164 Korea Republic of Department of Psychology Yonsei University Seoul03722 Korea Republic of University College Yonsei University Seoul03722 Korea Republic of Deparment of Applied Statistics Yonsei University Seoul03722 Korea Republic of Department of Statistics and Data science Yonsei University Seoul03722 Korea Republic of

Diverse cases regarding the impact, with its related factors, of the COVID-19 pandemic on mental health have been reported in previous studies. College student groups have been frequently selected as the target population in previous studies because they are easily affected by pandemics. In this study, multivariable datasets were collected from 751 college students based on the complex relationships between various mental health factors. We utilized quantum annealing (QA)-based feature selection algorithms that were executed by commercial D-Wave quantum computers to determine the changes in the relative importance of the associated factors before and after the pandemic. Multivariable linear regression (MLR) and XGBoost models were also applied to validate the QA-based algorithms. Based on the experimental results, we confirm that QA-based algorithms have comparable capabilities in factor analysis research to the MLR models that have been widely used in previous studies. Furthermore, the performance of the QA-based algorithms was validated through the important factor results from the algorithms. Pandemic-related factors (e.g., confidence in the social system) and psychological factors (e.g., decision-making in uncertain situations) were more important in post-pandemic conditions. We believe that our study will serve as a reference for researchers studying similar topics. Copyright © 2023, The Authors. All rights reserved.

关键词： Multiple linear regression

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Effect of cholesterol on plasma membrane and motility of Piau ( Leporinus obtusidens ) sperm

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Cryobiology 2022年 109卷 61-62页

作者： Elenice A. Moraes Illa Carla S. Carvalho Elizabeth Maria S. Moreira Virginia Renata T. Oliveir Karine V. Antunes Guilherme R. Moreira Rozzano Antonio C.R. Figueiredo Research Center for Pigs Native and Wild Species Federal University of Sao Francisco Valley Petrolina Brazil Biometrics and Applied Statistics Program Rural Federal University of Pernambuco Recife Brazil Regional Superintendence of the Sao Francisco and Parnaiba Valley Development Company Petrolina Brazil

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

arXiv

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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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Forecasting high-frequency spatio-temporal wind power with dimensionally reduced echo state networks

arXiv

引用

arXiv 2021年

作者： Huang, Huang Castruccio, Stefano Genton, Marc G. Statistics Program King Abdullah University of Science and Technology Thuwal 23955-6900 Saudi Arabia Department of Applied and Computational Mathematics and Statistics University of Notre Dame Notre DameIN46556 United States

Fast and accurate hourly forecasts of wind speed and power are crucial in quan-tifying and planning the energy budget in the electric grid. Modeling wind at a high resolution brings forth considerable challenges given its turbulent and highly nonlin-ear dynamics. In developing countries, where wind farms over a large domain are currently under construction or consideration, this is even more challenging given the necessity of modeling wind over space as well. In this work, we propose a machine learning approach to model the nonlinear hourly wind dynamics in Saudi Arabia with a domain-specific choice of knots to reduce the spatial dimensionality. Our re-sults show that for locations highlighted as wind abundant by a previous work, our approach results in an 11% improvement in the two-hour-ahead forecasted power against operational standards in the wind energy sector, yielding a saving of nearly one million US dollars over a year under current market prices in Saudi Arabia. © 2021, CC BY.

关键词： Wind power

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Learning High-Dimensional McKean-Vlasov Forward-Backward Stochastic Differential Equations with General Distribution Dependence

arXiv

引用

arXiv 2022年

作者： Han, Jiequn Hu, Ruimeng Long, Jihao Center for Computational Mathematics Flatiron Institute New YorkNY10010 United States Department of Mathematics Department of Statistics and Applied Probability University of California Santa BarbaraCA93106-3080 United States The Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544-1000 United States

One of the core problems in mean-field control and mean-field games is to solve the corresponding McKean-Vlasov forward-backward stochastic differential equations (MV-FBSDEs). Most existing methods are tailored to special cases in which the mean-field interaction only depends on expectation or other moments and thus is inadequate to solve problems when the mean-field interaction has full distribution dependence. In this paper, we propose a novel deep learning method for computing MV-FBSDEs with a general form of mean-field interactions. Specifically, built on fictitious play, we recast the problem into repeatedly solving standard FBSDEs with explicit coefficient functions. These coefficient functions are used to approximate the MV-FBSDEs’ model coefficients with full distribution dependence, and are updated by solving another supervising learning problem using training data simulated from the last iteration’s FBSDE solutions. We use deep neural networks to solve standard BSDEs and approximate coefficient functions in order to solve high-dimensional MV-FBSDEs. Under proper assumptions on the learned functions, we prove that the convergence of the proposed method is free of the curse of dimensionality (CoD) by using a class of integral probability metrics (IPMs) previously developed in [Han, Hu and Long, arXiv:2104.12036]. The proved theorem shows the advantage of the method in high dimensions. We present the numerical performance in high-dimensional MV-FBSDE problems, including a mean-field game example of the well-known Cucker-Smale model whose cost depends on the full distribution of the forward *** Codes 65C30, 68T07, 49N80, 68Q25 © 2022, CC BY.

关键词： Stochastic systems

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Evaluating COVID-19 Surveillance Testing Strategies at Colorado School of Mines: A Stochastic Modeling Approach

arXiv

引用

arXiv 2024年

作者： Albrecht, Laura Leiderman, Karin Sindi, Suzanne S. Nychka, Douglas Applied Mathematics and Statistics Department Colorado School of Mines GoldenCO United States Mathematics Department University of North Carolina Chapel Hill Chapel HillNC United States UNC Blood Research Center University of North Carolina Chapel Hill Chapel HillNC United States Computational Medicine Program University of North Carolina Chapel Hill Chapel HillNC United States Department of Applied Mathematics University of California Merced MercedCA United States

This study introduces a stochastic model of COVID-19 transmission tailored to the Colorado School of Mines campus and evaluates surveillance testing strategies within a university context. Enhancing the conventional SEIR framework with stochastic transitions, our model accounts for the unique characteristics of disease spread in a residential college, including specific states for testing, quarantine, and isolation. Employing an approximate Bayesian computation (ABC) method for parameter estimation, we navigate the complexities inherent in stochastic models, enabling an accurate fit of the model with the campus case data. We then studied our model under the estimated parameters to evaluate the efficacy of different testing policies that could be implemented on a university campus. This framework not only advances understanding of COVID-19 dynamics on the Mines campus but serves as a blueprint for comparable settings, providing insights for informed strategies against infectious diseases. © 2024, CC BY.

关键词： COVID-19

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