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We present a mathematical simplification for the evolutionary dynamics of a heritable trait within a two-sex population. This trait is assumed to control the timing of sex-specific life-history events, such as the age of sexual maturity and…

Populations and Evolution · Quantitative Biology 2019-07-04 M. H. Chan , K. Hawkes , P. S. Kim

Vertical farming allows for year-round cultivation of a variety of crops, overcoming environmental limitations and ensuring food security. This closed and highly controlled system allows the plants to grow in optimal conditions, so that…

Systems and Control · Electrical Eng. & Systems 2023-09-15 Annalena Daniels , Michael Fink , Marion Leibold , Dirk Wollherr , Senthold Asseng

We present an algorithm for the stochastic simulation of gene expression and heterogeneous population dynamics. The algorithm combines an exact method to simulate molecular-level fluctuations in single cells and a constant-number Monte…

Computational Physics · Physics 2016-08-24 Daniel A. Charlebois , Jukka Intosalmi , Dawn Fraser , Mads Kaern

The aim of this paper is two-fold. First, we propose a new computational method to investigate the particularities of evolution. Second, we apply this method to a model of gene regulatory networks (GRNs) and explore the evolution of…

Molecular Networks · Quantitative Biology 2022-01-21 Tadamune Kaneko , Macoto Kikuchi

Volatility is a key variable in option pricing, trading and hedging strategies. The purpose of this paper is to improve the accuracy of forecasting implied volatility using an extension of genetic programming (GP) by means of dynamic…

General Finance · Quantitative Finance 2020-07-15 Sana Ben Hamida , Wafa Abdelmalek , Fathi Abid

We propose and analyse a variant of the recently introduced kinetic based optimization method that incorporates ideas like survival-of-the-fittest and mutation strategies well-known from genetic algorithms. Thus, we provide a first attempt…

Optimization and Control · Mathematics 2024-07-18 Giacomo Albi , Federica Ferrarese , Claudia Totzeck

We show that neural networks trained by evolutionary reinforcement learning can enact efficient molecular self-assembly protocols. Presented with molecular simulation trajectories, networks learn to change temperature and chemical potential…

Statistical Mechanics · Physics 2020-06-01 Stephen Whitelam , Isaac Tamblyn

Phenotypes of individuals in a population of organisms are not fixed. Phenotypic fluctuations, which describe temporal variation of the phenotype of an individual or individual-to-individual variation across a population, are present in…

Populations and Evolution · Quantitative Biology 2018-08-15 Hong-Yan Shih , Harry Mickalide , David T. Fraebel , Nigel Goldenfeld , Seppe Kuehn

With climate change threatening agricultural productivity and global food demand increasing, it is important to better understand which farm management practices will maximize crop yields in various climatic conditions. To assess the…

Applications · Statistics 2022-04-12 Dan M. Kluger , Art B. Owen , David B. Lobell

We study optimal two-sector (vegetative and reproductive) allocation models of annual plants in temporally variable environments, that incorporate effects of density dependent lifetime variability and juvenile mortality in a fitness…

Populations and Evolution · Quantitative Biology 2022-06-24 Sergiy Koshkin , Zachary Zalles , Michael F. Tobin , Nicolas Toumbacaris , Cameron Spiess

A first step in exploring population structure in crop plants and other organisms is to define the number of subpopulations that exist for a given data set. The genetic marker data sets being generated have become increasingly large over…

Applications · Statistics 2014-01-09 Mark A. Newell , Dianne Cook , Heike Hofmann , Jean-Luc Jannink

Heterosis is the improved or increased function of any biological quality in a hybrid offspring. We have studied yet the largest maize SNP dataset for traits prediction. We develop linear and non-linear models which consider relationships…

Machine Learning · Statistics 2020-07-02 Binbin Shi , Xupeng Chen

Neural network models of real-world systems, such as industrial processes, made from sensor data must often rely on incomplete data. System states may not all be known, sensor data may be biased or noisy, and it is not often known which…

Neural and Evolutionary Computing · Computer Science 2007-06-08 Donald A. Sofge , David L. Elliott

Agricultural production requires careful management of inputs such as fungicides, insecticides, and herbicides to ensure a successful crop that is high-yielding, profitable, and of superior seed quality. Current state-of-the-art field crop…

Genomic Selection (GS) uses whole-genome information to predict crop phenotypes and accelerate breeding. Traditional GS methods, however, struggle with prediction accuracy for complex traits and large datasets. We propose DPCformer, a deep…

Machine Learning · Computer Science 2025-11-11 Pengcheng Deng , Kening Liu , Mengxi Zhou , Mingxi Li , Rui Yang , Chuzhe Cao , Maojun Wang , Zeyu Zhang

In this paper, we develop a mean-field model for simulating the microstructure evolution of crystalline materials during static recrystallization. The model considers a population of individual cells (i.e. grains and subgrains) growing in a…

Materials Science · Physics 2020-05-18 Arthur Després , Michael Greenwood , Chad Sinclair

Hybrid rice breeding crossbreeds different rice lines and cultivates the resulting hybrids in fields to select those with desirable agronomic traits, such as higher yields. Recently, genomic selection has emerged as an efficient way for…

Human-Computer Interaction · Computer Science 2025-07-17 Changjian Chen , Pengcheng Wang , Fei Lyu , Zhuo Tang , Li Yang , Long Wang , Yong Cai , Feng Yu , Kenli Li

Background: Acceleration of adaptation dynamics by stress-induced hypermutation has been found experimentally. Evolved evolvability is a prominent explanation. We investigate a more generally applicable explanation by a physical constraint.…

Biological Physics · Physics 2011-04-12 Lennart Hilbert

A hybrid Monte Carlo (HMC) approach is employed to quantify the influence of inelastic deformation on the microstructural evolution of polycrystalline materials. This approach couples a time explicit material point method (MPM) for…

Materials Science · Physics 2015-05-19 Liangzhe Zhang , Remi Dingreville , Timothy Bartel , Mark T. Lusk

The preservation of soil health is a critical challenge in the 21st century due to its significant impact on agriculture, human health, and biodiversity. We provide the first deep investigation of the predictive potential of machine…

Machine Learning · Statistics 2024-02-20 Rosa Aghdam , Xudong Tang , Shan Shan , Richard Lankau , Claudia Solís-Lemus