While interval-valued picture fuzzy sets(IvPFSs)provide a powerful tool for modeling uncertainty and ambiguity in various fields,existing divergence measures for IvPFSs remain limited and often produce counterintuitiv...While interval-valued picture fuzzy sets(IvPFSs)provide a powerful tool for modeling uncertainty and ambiguity in various fields,existing divergence measures for IvPFSs remain limited and often produce counterintuitive results.To address these shortcomings,this paper introduces two novel divergencemeasures for IvPFSs,inspired by the Jensen-Shannon divergence.The fundamental properties of the proposed measures-non-degeneracy,symmetry,triangular inequality,and boundedness-are rigorously proven.Comparative analyses with existing measures are conducted through specific cases and numerical examples,clearly demonstrating the advantages of our approach.Furthermore,we apply the new divergence measures to develop an enhanced interval-valued picture fuzzy TOPSIS method for risk assessment in construction projects,showing the practical applicability and effectiveness of our contributions.展开更多
A Bayesian network reconstruction method based on norm minimization is proposed to address the sparsity and iterative divergence issues in network reconstruction caused by noise and missing values.This method achieves...A Bayesian network reconstruction method based on norm minimization is proposed to address the sparsity and iterative divergence issues in network reconstruction caused by noise and missing values.This method achieves precise adjustment of the network structure by constructing a preliminary random network model and introducing small-world network characteristics and combines L1 norm minimization regularization techniques to control model complexity and optimize the inference process of variable dependencies.In the experiment of game network reconstruction,when the success rate of the L1 norm minimization model’s existence connection reconstruction reaches 100%,the minimum data required is about 40%,while the minimum data required for a sparse Bayesian learning network is about 45%.In terms of operational efficiency,the running time for minimizing the L1 normis basically maintained at 1.0 s,while the success rate of connection reconstruction increases significantly with an increase in data volume,reaching a maximum of 13.2 s.Meanwhile,in the case of a signal-to-noise ratio of 10 dB,the L1 model achieves a 100% success rate in the reconstruction of existing connections,while the sparse Bayesian network had the highest success rate of 90% in the reconstruction of non-existent connections.In the analysis of actual cases,the maximum lift and drop track of the research method is 0.08 m.The mean square error is 5.74 cm^(2).The results indicate that this norm minimization-based method has good performance in data efficiency and model stability,effectively reducing the impact of outliers on the reconstruction results to more accurately reflect the actual situation.展开更多
Objective:With Persicaria capitata as test materials,we compared and analyzed the chloroplast(cp)genome characteristics as well as their phylogenetic relationships and evolutionary history with related species of Pers...Objective:With Persicaria capitata as test materials,we compared and analyzed the chloroplast(cp)genome characteristics as well as their phylogenetic relationships and evolutionary history with related species of Persicaria nepalensis,Persicaria japonica,Persicaria chinensis,Persicaria filiformis,Persicaria perfoliata,Persicaria pubescens,Persicaria hnydropiper.Methods:The Illumina HiSeq high-throughput sequencing platform was used for the first time for P.capitata cp genome sequencing.NOVOPlasty and CpGAVAS2 were used for assembly and annotation,and Codon W,DnaSP,and MISA were used to conduct a series of comparative genomic analyses between the plant and seven species of the same genus.A phylogenetic tree was constructed using the maximum likelihood(ML)and neighbor-joining(NJ)methods,and divergence time was estimated using BEAST.Results:The total length of P.capitata cp genome was 158,821 bp,with a guanine and cytosine(GC)content of 38.0%,exhibiting a typical circular tetrad structure.The genome contains 127 annotated genes,including 82 protein-coding and 45 tRNA-encoding genes.The cp genome harbors simple sequence repeat(SSR)loci primarily composed of A/T.The conserved species structure of this genus is reinforced by the expansion and contraction of the inverted repeat(IR)region.The non-coding regions of the cp genomes exhibited significant differences among the genera.Six different mutation hotspots(psbK-psbI,atpI-rps2,petN-psbD,atpB-rbcL,cemA-petA,ndhI-ndhA-ycf1)were screened from the non-coding regions of genes with high nucleotide variability(pI).These hotspots were expected to define the phylogenetic species of Persicaria.Furthermore,phylogenetic analysis of Polygonaceae plants showed that P.capitata was more closely related to P.chinensis than P.nepalensis.Analysis of divergence time indicated that Polygonaceae originated in the Late Cretaceous(~180 Ma)and began to differentiate during the Middle Miocene.Persicaria differentiated~66.44 million years ago,during the Miocene.Conclusions:Our findings will serve as a scientific basis for further research on species identification and evolution,population genetics,and phylogenetic analysis of P.capitata.Further,we provide valuable information for understanding the origin and evolution of Persicaria in Polygonaceae and estimating the differentiation time of Persicaria and its population.展开更多
Uncertainty and ambiguity are pervasive in real-world intelligent systems,necessitating advanced mathematical frameworks for effective modeling and analysis.Fermatean fuzzy sets(FFSs),as a recent extension of classica...Uncertainty and ambiguity are pervasive in real-world intelligent systems,necessitating advanced mathematical frameworks for effective modeling and analysis.Fermatean fuzzy sets(FFSs),as a recent extension of classical fuzzy theory,provide enhanced flexibility for representing complex uncertainty.In this paper,we propose a unified parametric divergence operator for FFSs,which comprehensively captures the interplay among membership,nonmembership,and hesitation degrees.The proposed operator is rigorously analyzed with respect to key mathematical properties,including non-negativity,non-degeneracy,and symmetry.Notably,several well-known divergence operators,such as Jensen-Shannon divergence,Hellinger distance,andχ2-divergence,are shown to be special cases within our unified framework.Extensive experiments on pattern classification,hierarchical clustering,and multiattribute decision-making tasks demonstrate the competitive performance and stability of the proposed operator.These results confirm both the theoretical significance and practical value of our method for advanced fuzzy information processing in machine learning and intelligent decision-making.展开更多
This study introduces a novel distance measure(DM)for(p,q,r)-spherical fuzzy sets((p,q,to improve decision-making in complex and uncertain environments.Many existing distance measures eitherr)-SFSs)fail to satisfy ess...This study introduces a novel distance measure(DM)for(p,q,r)-spherical fuzzy sets((p,q,to improve decision-making in complex and uncertain environments.Many existing distance measures eitherr)-SFSs)fail to satisfy essential axiomatic properties or produce unintuitive outcomes.To address these limitations,we propose a new three-dimensional divergence-based DM that ensures mathematical consistency,enhances the discrimination of information,and adheres to the axiomatic framework of distance theory.Building on this foundation,we construct a multi-criteria decision-making(MCDM)model that utilizes the proposed DM to evaluate and rank alternatives effectively.The applicability and robustness of the model are validated through a practical case study,demonstrating that it leads to more rational,consistent,and reliable decision outcomes compared to existing approaches.展开更多
As a practicing anatomic pathologist specialized in urologic pathology,a vast difference may be observed between what pathologists designate as neuroendocrine(or small cell)carcinoma of the prostate,and what clinician...As a practicing anatomic pathologist specialized in urologic pathology,a vast difference may be observed between what pathologists designate as neuroendocrine(or small cell)carcinoma of the prostate,and what clinicians or basic scientists define as such.展开更多
Lignified stone cells are a unique feature of pear fruit,significantly affecting fruit texture.Even though some research efforts have already been made,the stone cell formation mechanism is complex,with many aspects y...Lignified stone cells are a unique feature of pear fruit,significantly affecting fruit texture.Even though some research efforts have already been made,the stone cell formation mechanism is complex,with many aspects yet to be elucidated.Here,through a genome-wide association analysis of stone cell traits,we identified PbrMADS1,a member of the SEPALLATA3(SEP3)subfamily,as a candidate gene specifically expressed in stone cells during early fruit development.Functional studies confirmed that PbrMADS1 promotes stone cell formation;however,it does not directly activate lignin-related genes.Instead,Pbr MADS1 interacts with PbrMYB169,enhancing PbrMYB169's binding to AC elements and amplifying downstream gene activation.Notably,homologous MADS1 and MYB169 proteins from closely related species such as apple and loquat do not form a similar complex.Sequence analysis revealed that the protein sequence of PbrMADS1 contains methionine(M)at the 63rdamino acid position,while apple and loquat homologs carry threonine(T)at the same site.Substituting M with T(PbrMADS1^(M63T))weakened its interaction with Pbr MYB169 and impaired its function in regulating stone cell formation.This study offers new insights into MADS gene-mediated stone cell formation and highlights functional divergence within the SEP3 subfamily among apple tribe species of the Rosaceae family.展开更多
We prove that for any p perfect set of positive measure and for it＇s any density point x0 one can construct a measurable function f（x）, bounded on [0,1）, such that each measurable and bounded function, which coinc...We prove that for any p perfect set of positive measure and for it＇s any density point x0 one can construct a measurable function f（x）, bounded on [0,1）, such that each measurable and bounded function, which coincides with f（x） on the set p has diverging Fourier-Walsh series on the point xo.展开更多
基金the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Small Research Project under grant number RGP1/141/46.
文摘While interval-valued picture fuzzy sets(IvPFSs)provide a powerful tool for modeling uncertainty and ambiguity in various fields,existing divergence measures for IvPFSs remain limited and often produce counterintuitive results.To address these shortcomings,this paper introduces two novel divergencemeasures for IvPFSs,inspired by the Jensen-Shannon divergence.The fundamental properties of the proposed measures-non-degeneracy,symmetry,triangular inequality,and boundedness-are rigorously proven.Comparative analyses with existing measures are conducted through specific cases and numerical examples,clearly demonstrating the advantages of our approach.Furthermore,we apply the new divergence measures to develop an enhanced interval-valued picture fuzzy TOPSIS method for risk assessment in construction projects,showing the practical applicability and effectiveness of our contributions.
基金supported by the Scientific and Technological Developing Scheme of Jilin Province,China(No.20240101371JC)the National Natural Science Foundation of China(No.62107008).
文摘A Bayesian network reconstruction method based on norm minimization is proposed to address the sparsity and iterative divergence issues in network reconstruction caused by noise and missing values.This method achieves precise adjustment of the network structure by constructing a preliminary random network model and introducing small-world network characteristics and combines L1 norm minimization regularization techniques to control model complexity and optimize the inference process of variable dependencies.In the experiment of game network reconstruction,when the success rate of the L1 norm minimization model’s existence connection reconstruction reaches 100%,the minimum data required is about 40%,while the minimum data required for a sparse Bayesian learning network is about 45%.In terms of operational efficiency,the running time for minimizing the L1 normis basically maintained at 1.0 s,while the success rate of connection reconstruction increases significantly with an increase in data volume,reaching a maximum of 13.2 s.Meanwhile,in the case of a signal-to-noise ratio of 10 dB,the L1 model achieves a 100% success rate in the reconstruction of existing connections,while the sparse Bayesian network had the highest success rate of 90% in the reconstruction of non-existent connections.In the analysis of actual cases,the maximum lift and drop track of the research method is 0.08 m.The mean square error is 5.74 cm^(2).The results indicate that this norm minimization-based method has good performance in data efficiency and model stability,effectively reducing the impact of outliers on the reconstruction results to more accurately reflect the actual situation.
基金supported by the National Natural Science Foundation of China(82060913).
文摘Objective:With Persicaria capitata as test materials,we compared and analyzed the chloroplast(cp)genome characteristics as well as their phylogenetic relationships and evolutionary history with related species of Persicaria nepalensis,Persicaria japonica,Persicaria chinensis,Persicaria filiformis,Persicaria perfoliata,Persicaria pubescens,Persicaria hnydropiper.Methods:The Illumina HiSeq high-throughput sequencing platform was used for the first time for P.capitata cp genome sequencing.NOVOPlasty and CpGAVAS2 were used for assembly and annotation,and Codon W,DnaSP,and MISA were used to conduct a series of comparative genomic analyses between the plant and seven species of the same genus.A phylogenetic tree was constructed using the maximum likelihood(ML)and neighbor-joining(NJ)methods,and divergence time was estimated using BEAST.Results:The total length of P.capitata cp genome was 158,821 bp,with a guanine and cytosine(GC)content of 38.0%,exhibiting a typical circular tetrad structure.The genome contains 127 annotated genes,including 82 protein-coding and 45 tRNA-encoding genes.The cp genome harbors simple sequence repeat(SSR)loci primarily composed of A/T.The conserved species structure of this genus is reinforced by the expansion and contraction of the inverted repeat(IR)region.The non-coding regions of the cp genomes exhibited significant differences among the genera.Six different mutation hotspots(psbK-psbI,atpI-rps2,petN-psbD,atpB-rbcL,cemA-petA,ndhI-ndhA-ycf1)were screened from the non-coding regions of genes with high nucleotide variability(pI).These hotspots were expected to define the phylogenetic species of Persicaria.Furthermore,phylogenetic analysis of Polygonaceae plants showed that P.capitata was more closely related to P.chinensis than P.nepalensis.Analysis of divergence time indicated that Polygonaceae originated in the Late Cretaceous(~180 Ma)and began to differentiate during the Middle Miocene.Persicaria differentiated~66.44 million years ago,during the Miocene.Conclusions:Our findings will serve as a scientific basis for further research on species identification and evolution,population genetics,and phylogenetic analysis of P.capitata.Further,we provide valuable information for understanding the origin and evolution of Persicaria in Polygonaceae and estimating the differentiation time of Persicaria and its population.
文摘Uncertainty and ambiguity are pervasive in real-world intelligent systems,necessitating advanced mathematical frameworks for effective modeling and analysis.Fermatean fuzzy sets(FFSs),as a recent extension of classical fuzzy theory,provide enhanced flexibility for representing complex uncertainty.In this paper,we propose a unified parametric divergence operator for FFSs,which comprehensively captures the interplay among membership,nonmembership,and hesitation degrees.The proposed operator is rigorously analyzed with respect to key mathematical properties,including non-negativity,non-degeneracy,and symmetry.Notably,several well-known divergence operators,such as Jensen-Shannon divergence,Hellinger distance,andχ2-divergence,are shown to be special cases within our unified framework.Extensive experiments on pattern classification,hierarchical clustering,and multiattribute decision-making tasks demonstrate the competitive performance and stability of the proposed operator.These results confirm both the theoretical significance and practical value of our method for advanced fuzzy information processing in machine learning and intelligent decision-making.
文摘This study introduces a novel distance measure(DM)for(p,q,r)-spherical fuzzy sets((p,q,to improve decision-making in complex and uncertain environments.Many existing distance measures eitherr)-SFSs)fail to satisfy essential axiomatic properties or produce unintuitive outcomes.To address these limitations,we propose a new three-dimensional divergence-based DM that ensures mathematical consistency,enhances the discrimination of information,and adheres to the axiomatic framework of distance theory.Building on this foundation,we construct a multi-criteria decision-making(MCDM)model that utilizes the proposed DM to evaluate and rank alternatives effectively.The applicability and robustness of the model are validated through a practical case study,demonstrating that it leads to more rational,consistent,and reliable decision outcomes compared to existing approaches.
文摘As a practicing anatomic pathologist specialized in urologic pathology,a vast difference may be observed between what pathologists designate as neuroendocrine(or small cell)carcinoma of the prostate,and what clinicians or basic scientists define as such.
基金funded by the National Science Foundation of China(U24A20415,32230097,32472689)the Earmarked Fund for China Agriculture Research System(CARS-28)+2 种基金the National Science Foundation of Shandong Province(ZR2024QC064)the Advanced Talents Research Foundation of Shandong Agricultural Universitythe“First Class Discipline”Construction Project of Shandong Agricultural University。
文摘Lignified stone cells are a unique feature of pear fruit,significantly affecting fruit texture.Even though some research efforts have already been made,the stone cell formation mechanism is complex,with many aspects yet to be elucidated.Here,through a genome-wide association analysis of stone cell traits,we identified PbrMADS1,a member of the SEPALLATA3(SEP3)subfamily,as a candidate gene specifically expressed in stone cells during early fruit development.Functional studies confirmed that PbrMADS1 promotes stone cell formation;however,it does not directly activate lignin-related genes.Instead,Pbr MADS1 interacts with PbrMYB169,enhancing PbrMYB169's binding to AC elements and amplifying downstream gene activation.Notably,homologous MADS1 and MYB169 proteins from closely related species such as apple and loquat do not form a similar complex.Sequence analysis revealed that the protein sequence of PbrMADS1 contains methionine(M)at the 63rdamino acid position,while apple and loquat homologs carry threonine(T)at the same site.Substituting M with T(PbrMADS1^(M63T))weakened its interaction with Pbr MYB169 and impaired its function in regulating stone cell formation.This study offers new insights into MADS gene-mediated stone cell formation and highlights functional divergence within the SEP3 subfamily among apple tribe species of the Rosaceae family.
文摘We prove that for any p perfect set of positive measure and for it＇s any density point x0 one can construct a measurable function f（x）, bounded on [0,1）, such that each measurable and bounded function, which coincides with f（x） on the set p has diverging Fourier-Walsh series on the point xo.
