Let S be the set of n coins,in which there are m counterfeit coins, heavier (or lighter) than the normals. How many weighings do we need to find the m fakes by a balance? Denote by g_m(n) the least number of weighings...Let S be the set of n coins,in which there are m counterfeit coins, heavier (or lighter) than the normals. How many weighings do we need to find the m fakes by a balance? Denote by g_m(n) the least number of weighings we need.展开更多
An authentication-secrecy code based on the rational normal curves over finite fields was constructed,whose probabilities of successful deception achieve their information-theoretic bounds.The set of encoding rules fo...An authentication-secrecy code based on the rational normal curves over finite fields was constructed,whose probabilities of successful deception achieve their information-theoretic bounds.The set of encoding rules for this code is a representation system for cosets of a certain subgroup in the projective transformation group.A special case is studied,i.e.the rational normal curves are the conies over finite fields.The representation system for the cosets which determines the set of encoding rules will be given.展开更多
Aims More data are needed about how genetic variation(GV)and envi-ronmental factors influence phenotypic variation within the natural populations of long-lived species with broad geographic distribu-tions.To fill this...Aims More data are needed about how genetic variation(GV)and envi-ronmental factors influence phenotypic variation within the natural populations of long-lived species with broad geographic distribu-tions.To fill this gap,we examined the correlations among envi-ronmental factors and phenotypic variation within and among 13 natural populations of Pinus tabulaeformis consisting of four demo-graphically distinct groups within the entire distributional range.Methods Using the Akaike’s information Criterion(AiC)model,we measured 12 morphological traits and constructed alternative candidate models for the relationships between each morphological trait and key climatic variables and genetic groups.We then compared the AiC weight for each candidate model to identify the best approximating model for ecogeographical variation of P.tabulaeformis.The partitioning of vari-ance was assessed subsequently by evaluating the independent vari-ables of the selected best models using partial redundancy analysis.Important Findings Significant phenotypic variation of the morphological traits was observed both within individual populations and among populations.Variation partition analyses showed that most of the phenotypic variation was co-determined by both GV and climatic factors.GV accounted for the largest proportion of reproductive trait variation,whereas local key climatic factors(i.e.actual evapotranspiration,AET)accounted for the largest proportion of phenotypic variation in the remaining investigated traits.Our results indicate that both genetic divergence and key environmental factors affect the phenotypic variation observed among populations of this species,and that reproductive and vegetative traits adaptively respond differently with respect to local environmental conditions.This partitioning of factors can inform those making predictions about phenotypic variation in response to future changes in climatic conditions(particularly those affecting AET).展开更多
Introduction:Incorporating information on animal behavior in resource-based predictive modeling(e.g.,occurrence mapping)can elucidate the relationship between process and spatial pattern and depict habitat in terms of...Introduction:Incorporating information on animal behavior in resource-based predictive modeling(e.g.,occurrence mapping)can elucidate the relationship between process and spatial pattern and depict habitat in terms of its structure as well as its function.In this paper,we assigned location data on brood-rearing greater sage-grouse(Centrocercus urophasianus)to either within-patch(encamped)or between-patch(traveling)behavioral modes by estimating a movement-based relative displacement index.Objectives were to estimate and validate spatially explicit models of within-versus between-patch resource selection for application in habitat management and compare these models to a non-behaviorally adjusted model.Results:A single model,the vegetation and water resources model,was most plausible for both the encamped and traveling modes,including the non-behaviorally adjusted model.When encamped,sage-grouse selected for taller shrubs,avoided bare ground,and were closer to mesic areas.Traveling sage-grouse selected for greater litter cover and herbaceous vegetation.Preference for proximity to mesic areas was common to both encamped and traveling modes and to the non-behaviorally adjusted model.The non-behaviorally adjusted map was similar to the encamped model and validated well.However,we observed different selection patterns during traveling that could have been masked had behavioral state not been accounted for.Conclusions:Characterizing habitat that structured between-patch movement broadens our understanding of the habitat needs of brood-rearing sage-grouse,and the combined raster surface offers a reliable habitat management tool that is readily amenable to application by GIS users in efforts to focus sustainable landscape management.展开更多
文摘Let S be the set of n coins,in which there are m counterfeit coins, heavier (or lighter) than the normals. How many weighings do we need to find the m fakes by a balance? Denote by g_m(n) the least number of weighings we need.
基金Project supported by the National Natural Science Foundation of China and the Natural Science Foundation of Guangdong Province.
文摘An authentication-secrecy code based on the rational normal curves over finite fields was constructed,whose probabilities of successful deception achieve their information-theoretic bounds.The set of encoding rules for this code is a representation system for cosets of a certain subgroup in the projective transformation group.A special case is studied,i.e.the rational normal curves are the conies over finite fields.The representation system for the cosets which determines the set of encoding rules will be given.
基金Program from Chinese National Basic Research Program(2014CB954203)grants from the National Natural Science Foundation of China(31322010,31270753,31000286)the National Youth Top-notch Talent Support Program to J.D.and Fundamental Research Funds for Central Universities(lzujbky-2012-k23).
文摘Aims More data are needed about how genetic variation(GV)and envi-ronmental factors influence phenotypic variation within the natural populations of long-lived species with broad geographic distribu-tions.To fill this gap,we examined the correlations among envi-ronmental factors and phenotypic variation within and among 13 natural populations of Pinus tabulaeformis consisting of four demo-graphically distinct groups within the entire distributional range.Methods Using the Akaike’s information Criterion(AiC)model,we measured 12 morphological traits and constructed alternative candidate models for the relationships between each morphological trait and key climatic variables and genetic groups.We then compared the AiC weight for each candidate model to identify the best approximating model for ecogeographical variation of P.tabulaeformis.The partitioning of vari-ance was assessed subsequently by evaluating the independent vari-ables of the selected best models using partial redundancy analysis.Important Findings Significant phenotypic variation of the morphological traits was observed both within individual populations and among populations.Variation partition analyses showed that most of the phenotypic variation was co-determined by both GV and climatic factors.GV accounted for the largest proportion of reproductive trait variation,whereas local key climatic factors(i.e.actual evapotranspiration,AET)accounted for the largest proportion of phenotypic variation in the remaining investigated traits.Our results indicate that both genetic divergence and key environmental factors affect the phenotypic variation observed among populations of this species,and that reproductive and vegetative traits adaptively respond differently with respect to local environmental conditions.This partitioning of factors can inform those making predictions about phenotypic variation in response to future changes in climatic conditions(particularly those affecting AET).
文摘Introduction:Incorporating information on animal behavior in resource-based predictive modeling(e.g.,occurrence mapping)can elucidate the relationship between process and spatial pattern and depict habitat in terms of its structure as well as its function.In this paper,we assigned location data on brood-rearing greater sage-grouse(Centrocercus urophasianus)to either within-patch(encamped)or between-patch(traveling)behavioral modes by estimating a movement-based relative displacement index.Objectives were to estimate and validate spatially explicit models of within-versus between-patch resource selection for application in habitat management and compare these models to a non-behaviorally adjusted model.Results:A single model,the vegetation and water resources model,was most plausible for both the encamped and traveling modes,including the non-behaviorally adjusted model.When encamped,sage-grouse selected for taller shrubs,avoided bare ground,and were closer to mesic areas.Traveling sage-grouse selected for greater litter cover and herbaceous vegetation.Preference for proximity to mesic areas was common to both encamped and traveling modes and to the non-behaviorally adjusted model.The non-behaviorally adjusted map was similar to the encamped model and validated well.However,we observed different selection patterns during traveling that could have been masked had behavioral state not been accounted for.Conclusions:Characterizing habitat that structured between-patch movement broadens our understanding of the habitat needs of brood-rearing sage-grouse,and the combined raster surface offers a reliable habitat management tool that is readily amenable to application by GIS users in efforts to focus sustainable landscape management.
