Sparse identification of nonlinear dynamics(SINDy)has made significant progress in data-driven dynamics modeling.However,determining appropriate hyperparameters and addressing the time-consuming symbolic regression pr...Sparse identification of nonlinear dynamics(SINDy)has made significant progress in data-driven dynamics modeling.However,determining appropriate hyperparameters and addressing the time-consuming symbolic regression process remain substantial challenges.This study proposes the adaptive backward stepwise selection of fast SINDy(ABSS-FSINDy),which integrates statistical learning-based estimation and technical advancements to significantly reduce simulation time.This approach not only provides insights into the conditions under which SINDy performs optimally but also highlights potential failure points,particularly in the context of backward stepwise selection(BSS).By decoding predefined features into textual expressions,ABSS-FSINDy significantly reduces the simulation time compared with conventional symbolic regression methods.We validate the proposed method through a series of numerical experiments involving both planar/spatial dynamics and high-dimensional chaotic systems,including Lotka-Volterra,hyperchaotic Rossler,coupled Lorenz,and Lorenz 96 benchmark systems.The experimental results demonstrate that ABSS-FSINDy autonomously determines optimal hyperparameters within the SINDy framework,overcoming the curse of dimensionality in high-dimensional simulations.This improvement is substantial across both lowand high-dimensional systems,yielding efficiency gains of one to three orders of magnitude.For instance,in a 20D dynamical system,the simulation time is reduced from 107.63 s to just 0.093 s,resulting in a 3-order-of-magnitude improvement in simulation efficiency.This advancement broadens the applicability of SINDy for the identification and reconstruction of high-dimensional dynamical systems.展开更多
Papaya(Carica papaya)is a promising model system for genetic and genomic studies of fruit traits and sex determination in tropical trees and fruits.However,the genomic basis of the artificial selection for key fruit t...Papaya(Carica papaya)is a promising model system for genetic and genomic studies of fruit traits and sex determination in tropical trees and fruits.However,the genomic basis of the artificial selection for key fruit traits and commercially crucial hermaphroditism remains poorly understood.In this study,we assembled the genomes for two phenotypically divergent hermaphroditic cultivars,including their haplotype-phased sex-determining regions(SDRs).Population genomic analyses of wild,common-type(for vegetable use),and fruit-type(for fresh consumption)papayas revealed a clear domestication history and geographic spread model.By combining genome-wide association study(GWAS),selection scan,and functional validation,we revealed a stepwise selection targeting CpPUP11 and Cp/CMT during domestication and improvement to reshape fruit size,and artificial selection on CpMAPK1,CpCOX,CpCIN,and CpUBE3 during the improvement process to increase fruit sweetness and vitamin C content.Furthermore,we demonstrated the independent origins of two hermaphroditic lineages through polyphyletic selection from wild male populations,resulting in two distinct hermaphrodite-specific Yh regions(HSY1 and HSY3).This transition was driven by selection targeting male-biased genes,which exhibited stable dominance in their methylation and transcription.Notably,we identified a hermaphrodite-specific,selectively fixed 13-bp insertion in the male-biased gene CpPGLP1A(HSY3-TR-13bp),which is strongly associated with the male-to-hermaphrodite transition.Collectively,our study provides novel insights into the genomic architecture of papaya domestication,revealing a trajectory of stepwise selection reshaping fruit traits and male-biased selection driving the emergence of a novel hermaphroditic sexual system.展开更多
Fast stepwise procedures of selection of variables by using AIC and BIC criteria are proposed inthis paper. We shall use a short name 'FSP' for these new procedures. FSP are similar to the well-known stepwise ...Fast stepwise procedures of selection of variables by using AIC and BIC criteria are proposed inthis paper. We shall use a short name 'FSP' for these new procedures. FSP are similar to the well-known stepwise regression procedures in computing steps. But FSP have two advantages. One of theseadvantages is that FSP are definitely convergent with a faster rate in finite computing steps. Anotheradvantage is that ESP can be used for large number of candidate variables. In this paper we alsoshow some asymptotic properties of FSP, and some simulation results.展开更多
基金Project supported by the National Natural Science Foundation of China(Nos.12172291,12472357,and 12232015)the Shaanxi Province Outstanding Youth Fund Project(No.2024JC-JCQN-05)the 111 Project(No.BP0719007)。
文摘Sparse identification of nonlinear dynamics(SINDy)has made significant progress in data-driven dynamics modeling.However,determining appropriate hyperparameters and addressing the time-consuming symbolic regression process remain substantial challenges.This study proposes the adaptive backward stepwise selection of fast SINDy(ABSS-FSINDy),which integrates statistical learning-based estimation and technical advancements to significantly reduce simulation time.This approach not only provides insights into the conditions under which SINDy performs optimally but also highlights potential failure points,particularly in the context of backward stepwise selection(BSS).By decoding predefined features into textual expressions,ABSS-FSINDy significantly reduces the simulation time compared with conventional symbolic regression methods.We validate the proposed method through a series of numerical experiments involving both planar/spatial dynamics and high-dimensional chaotic systems,including Lotka-Volterra,hyperchaotic Rossler,coupled Lorenz,and Lorenz 96 benchmark systems.The experimental results demonstrate that ABSS-FSINDy autonomously determines optimal hyperparameters within the SINDy framework,overcoming the curse of dimensionality in high-dimensional simulations.This improvement is substantial across both lowand high-dimensional systems,yielding efficiency gains of one to three orders of magnitude.For instance,in a 20D dynamical system,the simulation time is reduced from 107.63 s to just 0.093 s,resulting in a 3-order-of-magnitude improvement in simulation efficiency.This advancement broadens the applicability of SINDy for the identification and reconstruction of high-dimensional dynamical systems.
基金supported by the Key Research and Development Project of Hainan Province(ZDYF2025XDNY120 to H.Z.)the Project of State Key Laboratory of Tropical Crop Breeding(No.NKLTCBCXTD16 to C.J.)+3 种基金the National Natural Science Foundation of China(32472698 to C.J.)the Central Public-interest Scientific Institution Basal Research Fund for Chinese Academy of Tropical Agricultural Sciences(1630052020007 to C.J.)the Social Public-interest Scientific Institution Reform Special Fund(1630052024002 to C.J.)the Hainan Province Science and Technology Special Fund(ZDYF2022XDNY257 and ZDYF2024XDNY179 to R.J.).
文摘Papaya(Carica papaya)is a promising model system for genetic and genomic studies of fruit traits and sex determination in tropical trees and fruits.However,the genomic basis of the artificial selection for key fruit traits and commercially crucial hermaphroditism remains poorly understood.In this study,we assembled the genomes for two phenotypically divergent hermaphroditic cultivars,including their haplotype-phased sex-determining regions(SDRs).Population genomic analyses of wild,common-type(for vegetable use),and fruit-type(for fresh consumption)papayas revealed a clear domestication history and geographic spread model.By combining genome-wide association study(GWAS),selection scan,and functional validation,we revealed a stepwise selection targeting CpPUP11 and Cp/CMT during domestication and improvement to reshape fruit size,and artificial selection on CpMAPK1,CpCOX,CpCIN,and CpUBE3 during the improvement process to increase fruit sweetness and vitamin C content.Furthermore,we demonstrated the independent origins of two hermaphroditic lineages through polyphyletic selection from wild male populations,resulting in two distinct hermaphrodite-specific Yh regions(HSY1 and HSY3).This transition was driven by selection targeting male-biased genes,which exhibited stable dominance in their methylation and transcription.Notably,we identified a hermaphrodite-specific,selectively fixed 13-bp insertion in the male-biased gene CpPGLP1A(HSY3-TR-13bp),which is strongly associated with the male-to-hermaphrodite transition.Collectively,our study provides novel insights into the genomic architecture of papaya domestication,revealing a trajectory of stepwise selection reshaping fruit traits and male-biased selection driving the emergence of a novel hermaphroditic sexual system.
文摘Fast stepwise procedures of selection of variables by using AIC and BIC criteria are proposed inthis paper. We shall use a short name 'FSP' for these new procedures. FSP are similar to the well-known stepwise regression procedures in computing steps. But FSP have two advantages. One of theseadvantages is that FSP are definitely convergent with a faster rate in finite computing steps. Anotheradvantage is that ESP can be used for large number of candidate variables. In this paper we alsoshow some asymptotic properties of FSP, and some simulation results.
