Variable selection in nonlinear function-on-scalar regression

We develop a new method for variable selection in a nonlinear additive function-on-scalar regression (FOSR) model. Existing methods for variable selection in FOSR have focused on the linear effects of scalar predictors, which can be a restrictive assumption in the presence of multiple continuously measured covariates. We propose a computationally efficient approach for variable selection in existing linear FOSR using functional principal component scores of the functional response and extend this framework to a nonlinear additive function-on-scalar model. The proposed method provides a unified and flexible framework for variable selection in FOSR, allowing nonlinear effects of the covariates. Numerical analysis using simulation study illustrates the advantages of the proposed method over existing variable selection methods in FOSR even when the underlying covariate effects are all linear. The proposed procedure is demonstrated on accelerometer data from the 2003–2004 cohorts of the National Health and Nutrition Examination Survey (NHANES) in understanding the association between diurnal patterns of physical activity and demographic, lifestyle, and health characteristics of the participants.     

Functional data analysis with covariate-dependent mean and covariance structures

Functional data analysis has emerged as a powerful tool in response to the ever-increasing resources and efforts devoted to collecting information about response curves or anything that varies over a continuum. However, limited progress has been made with regard to linking the covariance structures of response curves to external covariates, as most functional models assume a common covariance structure. We propose a new functional regression model with covariate-dependent mean and covariance structures. Particularly, by allowing variances of random scores to be covariate-dependent, we identify eigenfunctions for each individual from the set of eigenfunctions that govern the variation patterns across all individuals, resulting in high interpretability and prediction power. We further propose a new penalized quasi-likelihood procedure that combines regularization and B-spline smoothing for model selection and estimation and establish the convergence rate and asymptotic normality of the proposed estimators. The utility of the developed method is demonstrated via simulations, as well as an analysis of the Avon Longitudinal Study of Parents and Children concerning parental effects on the growth curves of their offspring, which yields biologically interesting results.     

Insecticidal and Repellent Effects of the Essential Oils Extract from Zanthoxylum myriacanthum against Three Storage Pests

The co-storage of two or more Chinese herbal medicines can effectively prevent the herbs from the damage by pests. Thus, it is important to protect herbs and crops to study Chinese herbal medicines and their medicinal components against storage pests. This study aimed to assess the insecticidal activities and repellent effect of essential oils (EOs) extracted from fruits at different periods from Zanthoxylum myriacanthum Wall. ex Hook. f. (1 h, 2 h, 3–5 h and 5–7 h), and their major compounds against three kinds of pests (Tribolium castaneum, Lasioderma serricorne, and Liposcelis bostrychophila). The results of gas chromatography-mass spectrometer analysis revealed homomyrtenol (22.56 %, 28.01 %, 28.48 % and 28.41 %, respectively) and p-cymene (30.58 %, 13.95 %, 24.97 % and 6.85 %, respectively) were the common major compounds of the EOs at 1 h, 2 h, 3–5 h, and 5–7 h. m-Cymene contents in EOs of fruits, 1 h, 2 h and 3–5 h were 3.85 %, 0.95 %, 6.71 %, and 6.15 %, respectively. According to Principal component analysis (PCA), the composition of fruits′ EO was significantly different from other EOs due to the different collection times. The bio-assays showed that EOs and major compounds were toxic to all three pests, but the fumigation effect on L. bostrychophila was not noticeable. EOs extracted at different times had a repellent effect on the three pests at the highest concentration (78.63 nL/cm²), but the attractive effects of the EOs of 3–5 h, 5–7 h, and p-cymene were observed at the low concentrations (3.15, 0.63 and 0.13 nL/cm²). Our results suggest that Z. myriacanthum have the potential to be developed as biological insecticides.     

Corresponding patterns of geographic variation among populations ofSilene latifolia (=S. alba =S. pratensis) (Caryophyllaceae)

Morphological and biochemical data were analysed from 30 greenhouse-grown populations of EuropeanSilene latifolia. Six separate character sets (flavones, seed, pollen, capsules, male and female flower morphology) were used in the analyses. There was broad-scale congruence between trends of geographic variation in most character sets, with the populations being assigned to western (or southern and western) and eastern clusters. The eastern and western clusters abut along a transition zone that runs roughly from Belgium to the northern Balkans; this zone represents a region of relatively rapid change and contains populations intermediate between the eastern and western clusters. Variation in flower morphology was weak and discordant with variation in the other character sets. The origin and maintenance of the variation pattern is discussed in terms of migrational history and hybrid zones.     

Character selection in relation to the numerical taxonomy of some male Diaspididae (Homoptera: Coccoidea)

A quantitative comparison of the classifications of 24 species of male Diaspididae by principal component and principal coordinate analysis was extended to allow the comparison of classifications based on selected subsets of the 101 available characters. It was shown that subsets of 25–28 characters could be chosen numerically and used to construct classifications that resembled very closely the classification based on the reference set of characters. The conclusions are discussed in relation to other views on character-weighting and in relation to classifications of the Diaspididae based on traditional taxonomic characters provided by the females.     

The Bio3D packages for structural bioinformatics

Bio3D is a family of R packages for the analysis of biomolecular sequence, structure, and dynamics. Major functionality includes biomolecular database searching and retrieval, sequence and structure conservation analysis, ensemble normal mode analysis, protein structure and correlation network analysis, principal component, and related multivariate analysis methods. Here, we review recent package developments, including a new underlying segregation into separate packages for distinct analysis, and introduce a new method for structure analysis named ensemble difference distance matrix analysis (eDDM). The eDDM approach calculates and compares atomic distance matrices across large sets of homologous atomic structures to help identify the residue wise determinants underlying specific functional processes. An eDDM workflow is detailed along with an example application to a large protein family. As a new member of the Bio3D family, the Bio3D‐eddm package supports both experimental and theoretical simulation‐generated structures, is integrated with other methods for dissecting sequence‐structure–function relationships, and can be used in a highly automated and reproducible manner. Bio3D is distributed as an integrated set of platform independent open source R packages available from: http://thegrantlab.org/bio3d/ .     

草莓种苗壮苗指数模型的构建与质量评价

随着我国草莓栽培面积逐年增加,草莓种苗需求量越来越大,为了确保种苗育苗质量,亟需开展壮苗评价的研究。本研究以生长40 d的‘红颜’穴盘苗为对象,在测定地上部和地下部生长、鲜重、干重等16项指标的基础上,分别构建单项指标隶属函数,使用加权模糊评判法计算种苗综合评价指数;利用主成分分析筛选的关键指标组成多个壮苗指数模型,与种苗综合评价指数进行相关性分析后,确定最佳草莓壮苗指数模型并进行验证。结果表明: 随机选取的320株草莓种苗16项指标存在显著差异,综合评价指数为0.165～0.817,可作为壮苗指数模型构建和种苗质量评价的依据。主成分分析将16项指标划分为地上部相关指标、地下部相关指标和色素指标3个主成分,累计贡献率达到79.7%;从每个主成分中选择贡献值最大的3个指标随机组成27种壮苗指数模型,通过相关性分析筛选出与综合评价指数相关性最大的5个壮苗指数模型,其中“地上干重×根系表面积×叶绿素a”的相关性最高,用‘红颜’、‘香野’和‘甜查理’种苗验证相关系数均最大,分别为0.879、0.924和0.975,确定可作为草莓壮苗指数计算模型。以综合评价指数为种苗质量分级依据,可将种苗健壮程度分为3个等级:等级Ⅰ(综合评价指数≥0.5,壮苗指数≥4.0)为优质苗,等级Ⅱ(综合评价指数0.3～0.5,壮苗指数0.5～4.0)为合格苗,等级Ⅲ(综合评价指数≤0.3,壮苗指数≤0.5)为弱苗。研究结果可为草莓或其他种苗壮苗指数计算和种苗健壮程度评价提供理论依据与科学方法。