Integer‐valued functional data analysis for measles forecasting

Measles presents a unique and imminent challenge for epidemiologists and public health officials: the disease is highly contagious, yet vaccination rates are declining precipitously in many localities. Consequently, the risk of a measles outbreak continues to rise. To improve preparedness, we study historical measles data both prevaccine and postvaccine, and design new methodology to forecast measles counts with uncertainty quantification. We propose to model the disease counts as an integer‐valued functional time series: measles counts are a function of time‐of‐year and time‐ordered by year. The counts are modeled using a negative‐binomial distribution conditional on a real‐valued latent process, which accounts for the overdispersion observed in the data. The latent process is decomposed using an unknown basis expansion, which is learned from the data, with dynamic basis coefficients. The resulting framework provides enhanced capability to model complex seasonality, which varies dynamically from year‐to‐year, and offers improved multimonth‐ahead point forecasts and substantially tighter forecast intervals (with correct coverage) compared to existing forecasting models. Importantly, the fully Bayesian approach provides well‐calibrated and precise uncertainty quantification for epi‐relevant features, such as the future value and time of the peak measles count in a given year. An R package is available online.     

Observations of the Suspended Matter Distribution Dynamics in the Elbe Estuary from Time Series Aerial Photographs

Series of aerial photographs taken with an interval of 6 Minutes were used to study the dynamics of the suspended matter distribution in a 1 km section of the Elbe Estuary. The observations show heterogeneous distribution patterns which are different at each phase of the tidal cycle. The comparison with the bathymetry indicates that the distribution is mainly a function of the river bed topography, which modifies the local current structure. The surface distribution in the fairway region is especially determined by the ship traffic.     

采用数据挖掘技术对湖北省人类狂犬病开展生物信息学研究

狂犬病作为一种急性人畜共患疾病,其致死率接近100％.而湖北省作为我国中部狂犬病高发地之一,开展该省狂犬病的流行病学调查不仅有助于了解我国当前面临的狂犬病疫情风险,还能为当地及全国狂犬病防控工作提供有效的参考意见.首先运用描述性分析发现湖北省狂犬病发病人数随时间呈下降趋势,而狂犬病暴露人数则呈上升趋势,且近年来中西部地...     

Structural identifiability analysis of some highly structured families of statespace models using differential algebra

In this paper we identify biologically relevant families of models whose structural identifiability analysis could not be performed with available techniques directly. The models considered come from both the immunological and epidemiological literature.     

Comparison of parameters from rhythmometric models with multiple components on hybrid data

Population multiple components is a statistical tool useful for the analysis of time-dependent hybrid data. With a small number of parameters, it is possible to model and to predict the periodic behavior of a population. In this article, we propose two methods to compare among populations rhythmometric parameters obtained by multiple component analysis. The first is a parametric method based in the usual statistical techniques for comparison of mean vectors in multivariate normal populations. The method, through MANOVA analysis, allows comparison of the MESOR and amplitude-acrophase pair of each component among two or more populations. The second is a nonparametric method, based in bootstrap techniques, to compare parameters from two populations. This test allows one to compare the MESOR, the amplitude, and the acrophase of each fitted component, as well as the global amplitude, orthophase, and bathyphase estimated when all fitted components are harmonics of a fundamental period. The idea is to calculate a confidence interval for the difference of the parameters of interest. If this interval does not contain zero, it can be concluded that the parameters from the two models are different with high probability. An estimation of p-value for the corresponding test can also be calculated. Both methods are illustrated with an example, based on clinical data. The nonparametric test can also be applied to paired data, a special situation of great interest in practice. By the use of similar bootstrap techniques, we illustrate how to construct confidence intervals for any rhythmometric parameter estimated from population multiple components models, including the orthophase, bathyphase, and global amplitude. These tests for comparison of parameters among populations are a needed tool when modeling the nonsinusoidal rhythmic behavior of hybrid data by population multiple component analysis.     

Effects induced by mono- and divalent cations on protein regions responsible for thermal adaptation in β-glycosidase from<Emphasis Type="Italic"> Sulfolobus solfataricus</Emphasis>

The perturbation induced by mono- and divalent cations on the thermophilicity and thermostability of Solfolobus solfataricus -glycosidase, a hyperthermophilic tetrameric enzyme, has been investigated by spectroscopic and computational simulation methods to ascertain the Hofmeister effects on two strategic protein regions identified previously. Specifically, (1) an extra segment (83–124), present only in the sequence of hyperthermophilic glycosidases and recognized as an important thermostability determinant for the enzyme structure; and (2) a restricted area of the subunit interface responsible for the quaternary structure maintenance. Mono- and divalent cations inhibit to a different extent the -glycosidase activity, whose kinetic constants show an apparent competitive inhibition of the catalytic process that reflects the Hofmeister order. The thermostability is also affected by the nature and charge of the cations, reaching maximal effects for the case of Mg²⁺. Fourier transform infrared spectroscopy has revealed very small changes in the protein secondary structure in the presence of the investigated cations at 20 °C, while large effects on the protein melting temperatures are observed. Computational analysis of the enzyme structure has identified negative patches on the accessible surface of the two identified regions. Following the Hofmeister series, cations weaken the existing electrostatic network that links the extra segment to the remaining protein matrix. In particular, the perturbing action of cations could involve the ionic pair interactions E107–R245 and E109–R185, thus leading to a local destructuring of the extra segment as a possible starting event for thermal destabilization. A detailed investigation of the electrostatic network at the A–C intermolecular interface of Sgly after energy minimization suggests that cations could cause a strong attenuation of the ion pair interactions E474–K72 and D473–R402, with consequent partial dissociation of the tetrameric structure.Abbreviations Amide I amide I band in a ²H₂O medium - EM energy minimization - ONPG o-nitrophenyl--d-galactopyranoside - Sgly Escherichia coli expressed Sulfolobus solfataricus -glycosidase     

Measuring mast seeding behavior: relationships among population variation,individual variation and synchrony

Mast seeding, or masting, is the variable production of flowers, seeds, or fruit across years more or less synchronously by individuals within a population. A critical issue is the extent to which temporal variation in seed production over a collection of individuals can be viewed as arising from a combination of individual variation and synchrony among individuals. Studies of masting typically quantify such variation in terms of the coefficient of variation (CV). In this paper we examine mathematically how the population CV relates to the mean individual CV and synchrony, concluding that the relationship is a complex one which cannot isolate an overall measure of synchrony, and involves additional factors, principally the number of plants sampled and the mean productivity per plant. Our development suggests some simple approximate relationships of population CV to individual variability, synchrony and the number of individuals. These were found to fit quite well when applied to data from 59 studies which included seed production at the individual level.     

High yield regioselective monobenzyloxycarbonylation of secondary alcohols in glycopyranoside series

The regioselective monobenzyloxycarbonylation of secondary alcohols in methyl 6-O-(4-methoxytrityl)-alpha-D-manno-, gluco- and galactopyranoside has been achieved in high yields (74-85%) by using benzyl chloroformate in the presence of 4-dimethylaminopyridine and/or 1,4-diazabicyclo[2.2.2]octane.     

A two-stage model for multiple time series data of counts

We propose a two-stage model for time series data of counts from multiple locations. This method fits first-stage model(s) using the technique of iteratively weighted filtered least squares (IWFLS) to obtain location-specific intercepts and slopes, with possible lagged effects via polynomial distributed lag modeling. These slopes and/or intercepts are then taken to a second-stage mixed-effects meta-regression model in order to stabilize results from various locations. The representation of the models from the stages into a combined mixed-effects model, issues of inference and choices of the parameters in modeling the lag structure are discussed. We illustrate this proposed model via detailed analysis on the effect of air pollution on school absenteeism based on data from the Southern California Children's Health Study.