bluuebunny/crossref_metadata_2025 huggingface dataset:
Hierarchical Interaction Models
Authors: Edwards David
Published: December 2018

Lauritzen and Wermuth have proposed a class of models for mixed qualitative and continuous data, defined by two properties: that the continuous variables are normally distributed given the qualitative variables and that a set of conditional independence relations hold between specified pairs of variables. These models, called graphical association models, include graphical log-linear models for contingency tables and covariance selection models for correlation matrices. The present paper examines an extension to this class called hierarchical interaction models. A compact form for model representation is described and an estimation algorithm is given. Some properties of the models concerning marginalization and conditioning are examined. The class includes and generalizes hierarchical log-linear models, standard fixed effect analysis of variance (ANOVA), multivariate ANOVA and multivariate regression models. Two applications are given.
Balanced Design of Bootstrap Simulations
Authors: Graham R. L. , Hinkley D. V. , John P. W. M. , Shi S.
Published: December 2018

Davison et al. (1986) have shown that finite bootstrap simulations can be improved by forcing balance in the aggregate of simulated data sets. Their methods yield first-order balance, which principally affects bootstrap estimation of bias. Here we extend the methodology to second-order balance, which principally affects bootstrap estimation of variance. The particular techniques involve Latin square and balanced incomplete block designs. Numerical examples are given to illustrate both the positive and the negative features of the balanced simulations.
Robust Bayesian Analysis with ϵ-Contaminations Partially Known
Authors: Moreno E. , Cano J. A.
Published: December 2018

Prior distributions of the form π=(1−ϵ)π0+ϵq,π0 being the base elicited prior, q being contamination and ϵ reflecting the amount of error in π0 that is deemed possible, are considered. It is assumed that π0 is completely specified and that only some quantiles of q are known. As π varies over this class, the ranges of the posterior mean and of the posterior probabilities of an arbitrary set are determined. Some examples including hypotheses testing related to a bivariate normal likelihood are given.
Recursive Order Estimation of Autoregressions Without Bounding the Model Set
Authors: Hemerly E. M. , Davis M. H. A.
Published: December 2018

In a recent paper, we proved that Rissanen's 'predictive least squares' (PLS) criterion for model selection provides strongly consistent order estimates for autoregressive (AR) processes, i.e. the PLS order estimate p̂(n) based on the first n data points converges almost surely to p  0 as n → ∞ when the data are generated by an AR process of order p  0, and p  0 is known to belong to the finite model set M = {1, 2, ..., K}, K < ∞. In the present paper we strengthen this result by showing that strong consistency is maintained even if K is allowed to increase with rate O((log n)γ), for any γ<12, thus removing the need to specify an a priori upper bound.
One-Step Bootstrapping for Smooth Iterative Procedures
Authors: Schucany William R. , Wang Suojin
Published: December 2018

Resampling techniques have the potential to provide useful information about the sampling distribution of estimators of many population characteristics. Ambitious schemes such as the bootstrap and iterated bootstrap imply a substantial increase in computational effort. For some iterative procedures, such as generalized least squares or the EM algorithm, it is possible to avoid fully iterating each bootstrap replication to convergence. By analysing expansions of the defining equation, we can extract asymptotically correct bootstrap estimates from a single step for each replication. In this paper we demonstrate the large sample validity of this computationally efficient approach and illustrate its small sample applicability. Whether or not the adjustment represents an adequate replacement for full iteration depends on the nature of the problem and the desired accuracy for the bootstrap quantiles. If subsequent iterations are adjusted, then greater enhancement of the rate is achieved and the practical increase in accuracy is significant.
A Likelihood Paradox
Authors: Goldstein M. , Howard J. V.
Published: December 2018

The Fraser–Monette–Ng example, strengthened by Joshi, is simplified and further strengthened. The claim by Joshi that it gives a counter-example to the likelihood principle, and that this counter-example also covers the case of a finite parameter space, is disputed.
Practical Use of Higher Order Asymptotics for Multiparameter Exponential Families
Authors: Pierce Donald A. , Peters Dawn
Published: December 2018

Recently developed asymptotics based on saddlepoint methods provide important practical methods for multiparameter exponential families, especially in generalized linear models. The aim here is to clarify and explore these. Attention is restricted to tests and confidence intervals regarding a single parametric function which can be represented as a natural parameter of a full rank exponential family. Excellent approximations to exact conditional inferences are often available, in terms of simple adjustments to the signed square root of the likelihood ratio statistic. The focus is on distinguishing between two aspects of the adjustments: one reducing effects of nuisance parameter estimation and the other adjusting for little information regarding the parameter of interest. Numerical results are given for some Poisson and multinomial models.
Bivariate Threshold Methods for Extremes
Authors: Joe Harry , Smith Richard L. , Weissman Ishay
Published: December 2018

An extension of the threshold method for extreme values is developed, to consider the joint distribution of extremes of two variables. The methodology is based on the point process representation of bivariate extremes. Both parametric and nonparametric models are considered. The simplest case to handle is that in which both marginal distributions are known. For the more realistic case in which the marginal distributions are unknown, a mixed parametric-nonparametric method is proposed. The techniques are illustrated with data on sulphate and nitrate levels taken from a major study of acid rain.
Single-Factor Analysis by Minimum Message Length Estimation
Authors: Wallace C. S. , Freeman P. R.
Published: December 2018

The minimum message length (MML) technique is applied to the problem of estimating the parameters of a multivariate Gaussian model in which the correlation structure is modelled by a single common factor. Implicit estimator equations are derived and compared with those obtained from a maximum likelihood (ML) analysis. Unlike ML, the MML estimators remain consistent when used to estimate both the factor loadings and the factor scores. Tests on simulated data show the MML estimates to be on average more accurate than the ML estimates when the former exist. If the data show little evidence for a factor, the MML estimate collapses. It is shown that the condition for the existence of an MML estimate is essentially that the log-likelihood ratio in favour of the factor model exceeds the value expected under the null (no-factor) hypotheses.
A Characterization of Exponential Distributions Through Conditional Independence
Authors: Liang Ta Chen , Balakrishnan N.
Published: December 2018

Let Y  1, Y  2, . . ., Yn be mutually independent non-negative random variables having an absolutely continuous distribution function Fi(y) over its support [0, ∞) and the corresponding density function f  i(y) > 0 for y > 0. Let A denote the event that Yi – Y  i+1 > 0 for all i = 1, 2, . . ., n – 1. Then we show that, conditional on the event A, Yi – Y  i+1 and Y  i+1 are independent for all i = 1, 2,. . ., k if and only if Yi (i = 1, 2, . . ., k) are exponentially distributed random variables, where 1 ≤ k ≤ n – 1. We note that the k exponential distributions can have different scale parameters.
The Use of a Canonical Form in the Construction of Locally Optimal Designs for Non-Linear Problems
Authors: Ford I. , Torsney B. , Wu C. F. J.
Published: December 2018

Optimal experimental designs for non-linear problems depend on the values of the underlying unknown parameters in the model. For various reasons there is interest in providing explicit formulae for the optimal designs as a function of the unknown parameters. This paper shows that, for a certain class of generalized linear models, the problem can be reduced to a canonical form. This simplifies the underlying problem and designs are constructed for several contexts with a single variable using geometric and other arguments.
Distribution Estimation Using Concomitants of Order Statistics, with Application to Monte Carlo Simulation for the Bootstrap
Authors: Do Kim-Anh , Hall Peter
Published: December 2018

We show that a simulation method suggested by Efron for approximating bootstrap distributions is closely related to techniques based on concomitants of order statistics and develop its asymptotic properties from that viewpoint. We prove that the method produces Monte Carlo approximations with variance and mean-squared error decreasing like B−  1  n−  1/2, where B denotes the number of simulations and n equals the sample size. Therefore Efron's method can be a competitor with techniques such as balanced resampling, importance resampling and antithetic resampling, where variance and mean-squared error decrease like B  −1 with no significant contribution from sample size. However, Efron's method has drawbacks, one being that performance in the tails is not as good as performance towards the centre of the distribution. In this respect, importance resampling has distinct advantages.
A Note on Adjusted Profile Likelihoods in Non-Linear Regression
Authors: Macaskill G. T.
Published: December 2018

The problem of partial non-linear regression is used to provide an example of McCullagh and Tibshirani's profile likelihood adjustment for more than one parameter of interest, where for one linear nuisance parameter an expression for the adjusted profile likelihood can be derived.
Downdating the Moore-Penrose Generalized Inverse for Cross-Validation of Centred Least Squares Prediction
Authors: Dunne T. T. , Stone M.
Published: December 2018

Given a p × p symmetric matrix B and a p-vector c outside the range of B, a simple expression is formulated for the action of the Moore-Penrose generalized inverse B  + on a vector b in the range of B, in terms of b, c and (B + cc‱)+. A special case of this formula gives a ‘downdating’ formula for the vector of least squares regression coefficients based on the Moore-Penrose inverse of the centred sum of squares and products matrix. The formula is analogous to that given by A. Albert for uncentred least squares fitting. An explicit downdating formula for the Moore-Penrose inverse B  + itself is derived, and then more general downdating expressions for the inverse and the vector B  +  b when the p-vector c is replaced by a matrix array C of such vectors outside the range of B.
Multidimensional Density Estimation by Tomography
Authors: O'Sullivan Finbarr , Pawitan Yudi
Published: December 2018

The paper explores the application of the filtered backprojection algorithm of computerized tomography to statistical smoothing of multidimensional densities. The method makes use of automated one-dimensional density smoothers to obtain an automated smoothed multidimensional density. No structural assumptions such as additivity or log-additivity are used. An important computational aspect of this method is its inherently parallel structure. We demonstrate linear speed-up on a parallel computer architecture. Various practical details are discussed together with some illustrative two-dimensional examples. Asymptotic mean error characteristics of the method are shown to match those of more familiar multivariate kernel-, near-neighbour- and spline-type smoothing techniques.
Robust Likelihood Calculation for Time Series
Authors: Taplin Ross H.
Published: December 2018

We propose a computationally efficient method for calculating the likelihoods of a time series under many submodels, each of which assumes a patch of outliers or level shifts. We assume a state space representation of the time series model with a Bayesian-type treatment of anomalies. The calculations form the basis for an efficient and robust estimation procedure. The method is also applicable to linear regression with correlated errors and is illustrated with two examples.
Prediction Rules for Exponential Family State Space Models
Authors: Grunwald Gary K. , Guttorp Peter , Raftery Adrian E.
Published: December 2018

We state and prove a simple and general expression for the marginal mean in an exponential family state space model with conjugate state density. We then discuss implications of this result on the choice of parameterization of the observation density, on the interpretation of the predictive density for steady models and on exponentially weighted moving average and trend-free forecasting.
Estimation in Generalized Mixed Models
Authors: McGilchrist C. A.
Published: December 2018

Regression models containing fixed and random effects may have a response variable which is not normally distributed. The generalized mixed model includes both discrete and continuous response variables and is developed here for problems in which the regression variables enter linearly into the model. Best linear unbiased predictor methods are extended to maximum likelihood and residual maximum likelihood estimation procedures. Applications in modelling discrete response variables and in survival analysis are discussed.
Grouping Corrections for Circular Goodness-Of-Fit Tests
Authors: Brown B. M.
Published: December 2018

Simple corrections are outlined for the application to grouped seasonal data of Watson's and Maag's tests. These tests are circular or seasonal analogues of one-sample and k- (≥2) sample tests, of Cramér–von Mises type, and have several natural advantages over their competitors. The provision of simple grouping corrections may enhance the use of these tests, which otherwise have very good features. The corresponding grouping corrections are also presented for conventional, i.e. non-circular, Cramér–von Mises types of test.
A Note on Posterior Moments for a Normal Mean with Double-Exponential Prior
Authors: Mitchell Ann F. S.
Published: December 2018

General results on the behaviour of the posterior mean and variance of the mean of a normal distribution with known variance using a double-exponential prior are derived and complement the conjectures and particular examples given by Pericchi and Smith (1992) and Pericchi and Walley (1991).
A New Index of Fit Based on Mixture Methods for the Analysis of Contingency Tables
Authors: Rudas Tamás , Clogg Clifford C. , Lindsay Bruce G.
Published: December 2018

A framework based on mixture methods is proposed for evaluating goodness of fit in the analysis of contingency tables. For a given model H applied to a contingency table P, we consider the two-point mixture P = (1 – π)π  1 + ππ  2, with π the mixing proportion (0 ≤ π ≤ 1) and π  1 and π  2 the tables of probabilities for each latent class or component. In the unstructured approach recommended here, the mixture model applies H to π  1 but does not impose any restrictions on π  2. A contingency table P can generally be represented as such a two-point mixture for an interval of π-values. We define our index of lack of fit, π*, to be the smallest such π, i.e. π* is the fraction of the population that cannot be described by model H. This approach can be contrasted with the structured approach that applies model H to both  π  1 and π  2 and leads to conventional latent class models when H is the hypothesis of independence. The case where H is the hypothesis of row–column independence and P is a two-way contingency table is covered in detail, but the procedure is quite general.
Transformations to Reduce Boundary Bias in Kernel Density Estimation
Authors: Marron J. S. , Ruppert D.
Published: December 2018

We consider kernel estimation of a univariate density whose support is a compact interval. If the density is non-zero at either boundary, then the usual kernel estimator can be seriously biased. ‘Reflection’ at a boundary removes some bias, but unless the first derivative of the density is 0 at the boundary the estimator with reflection can still be much more severely biased at the boundary than in the interior. We propose to transform the data to a density that has its first derivative equal to 0 at both boundaries. The density of the transformed data is estimated, and an estimate of the density of the original data is obtained by a change of variables. The transformation is selected from a parametric family, which is allowed to be quite general in our theoretical study. We propose algorithms where the transformation is either a quartic polynomial, a β cumulative density function (CDF) or a linear combination of a polynomial and a β CDF. The last two types of transformation are designed to accommodate possible poles at the boundaries. The first two algorithms are tested on simulated data and compared with an adjusted kernel method of Rice. We find that our proposal performs similarly to Rice's for densities with one-sided derivatives at the boundaries. Unlike Rice's method, our proposal is guaranteed to produce non-negative estimates. This can be a distinct advantage when the density is 0 at either boundary. Our algorithm for densities with poles outperforms the Rice adjustment when the density has a pole at a boundary.
Randomization for a Balanced Superimposition of One Youden Square on Another
Authors: Bailey R. A. , Preece D. A. , Rowley C. A.
Published: December 2018

Some experimentation, particularly on trees in orchards, requires the superimposition of a new set of treatments on an existing experiment, on the assumption that the effects of the new treatments do not interact with those of the old. Different approaches to the randomization of such new treatments were considered by Preece, Bailey and Patterson, who investigated in detail the case when one Latin square is superimposed on another to produce a Graeco-Latin square. For non-orthogonal superimpositions the theory is in general much more complicated. However, this paper shows that fairly simple randomization results are obtainable for certain balanced superimpositions of one Youden square on another (i) when each Youden square is of size (t – 1) × t and (ii) when each Youden square is of size k × t, where t is a prime power of the form 4s – 1 and k = 2s – 1 or k = 2s. In each case, t is the number of treatments in each Youden square. The valid randomization procedure obtained for the second case is unlike any previously known randomization procedure and is unlikely to be acceptable in practice; it is, however, an excellent indication of the difficulties that arise when randomization is attempted in unusual circumstances.
Robustifying Model Fitting
Authors: Windham Michael P.
Published: December 2018

A robust method for fitting a model from a parametric family is fundamental to effective statistical analysis. A procedure is given for robustifying any model fitting process by using weights from the family from which the model is to be chosen. The weighting reduces the influence of information that is not compatible with the model family, while maintaining the basic structure of a familiar model fitting process. The procedure produces a parametric family of model fitting functions. The value of the parameter determines the degree to which the weighting influences the robustified model fit. A mechanism for determining an appropriate value for the parameter is described.
On Assessing Goodness of Fit of Generalized Linear Models to Sparse Data
Authors: Farrington C. P.
Published: December 2018

Approximations to the first three moments of Pearson's statistic are obtained for non-canonical generalized linear models, extending the results of McCullagh. A first-order modification to Pearson's statistic is proposed which induces local orthogonality with the regression parameters, resulting in substantial simplifications and increased power. Accurate and easily computed approximations to the moments of the modified Pearson statistic conditional on the estimated regression parameters are obtained for testing goodness of fit to sparse data. Both the Pearson statistic and its modification are shown to be asymptotically independent of the regression parameters. Simulation studies and examples are given.
Principal Differential Analysis: Data Reduction by Differential Operators
Authors: Ramsay J. O.
Published: December 2018

Functional data are observations that are either themselves functions or are naturally representable as functions. When these functions can be considered smooth, it is natural to use their derivatives in exploring their variation. Principal differential analysis (PDA) identifies a linear differential operator L = w  0  I+w  1  D + . . . + w  m-1  D  m-1 + D  m that comes as close as possible to annihilating a sample of functions. Convenient procedures for estimating the m weighting functions w  j are developed. The estimated differential operator L is analogous to the projection operator used as the data annihilator in principal components analysis and thus can be viewed as a type of data reduction or exploration tool. The corresponding linear differential equation may also have a useful substantive interpretation. Modelling and regularization features can also be incorporated into PDA.
A Conditional Likelihood Approach to Residual Maximum Likelihood Estimation in Generalized Linear Models
Authors: Smyth Gordon K. , Verbyla Arünas P.
Published: December 2018

Residual maximum likelihood (REML) estimation is often preferred to maximum likelihood estimation as a method of estimating covariance parameters in linear models because it takes account of the loss of degrees of freedom in estimating the mean and produces unbiased estimating equations for the variance parameters. In this paper it is shown that REML has an exact conditional likelihood interpretation, where the conditioning is on an appropriate sufficient statistic to remove dependence on the nuisance parameters. This interpretation clarifies the motivation for REML and generalizes directly to non-normal models in which there is a low dimensional sufficient statistic for the fitted values. The conditional likelihood is shown to be well defined and to satisfy the properties of a likelihood function, even though this is not generally true when conditioning on statistics which depend on parameters of interest. Using the conditional likelihood representation, the concept of REML is extended to generalized linear models with varying dispersion and canonical link. Explicit calculation of the conditional likelihood is given for the one-way lay-out. A saddlepoint approximation for the conditional likelihood is also derived.
Associations of body fat and skeletal muscle with hypertension
Authors: Han Thang S. , Al‐Gindan Yasmin Y. , Govan Lindsay , Hankey Catherine R. , Lean Michael E. J.
Published: December 2018

Hypertension is known to be associated with obesity, while its relationship to skeletal muscle, SM (SM; a marker of general health and body function), remains uncertain. We analyzed population‐based data of 22 591 men (mean age: 51.6 ± 16.9 years) and 27 845 nonpregnant women (50.6 ± 16.9 years) from Scottish Health Surveys (2003, 2008‐2011) and Health Surveys for England (2003‐2006, 2008‐2013) including 2595 non‐insulin‐ and 536 insulin‐treated diabetic patients. Compared with normotensive individuals (no hypertension history with normal systolic [SBP < 140 mm Hg] and diastolic blood pressure [DBP < 90 mm Hg]), percent body fat (BF%) was significantly higher and percent SM lower (P < 0.001) in undetected (no hypertension history with raised SBP ≥ 140 and/or DBP ≥ 90 mm Hg), controlled (hypertension history with normal BP), uncontrolled (hypertension history with raised BP), and untreated hypertension. The prevalences of hypertension within BF% quintiles were 11.8%, 24.8%, 41.4%, 56.8%, and 71.6% and SM% quintiles were 67.5%, 53.3%, 39.5%, 27.4%, and 18.5%. Compared to referent groups (lowest BF% quintile or highest SM% quintile), odds ratio (age, sex, smoking, ethnicity, country, survey year, and diabetes adjusted) for having all types of hypertension in the highest BF% quintile was 5.5 (95% confidence interval = 5.0‐5.9) and lowest SM% quintile was 2.3 (2.2‐2.5). Compared with those without diabetes, individuals with diabetes had a 2.3‐fold‐2.6‐fold greater risk of hypertension, independent of confounding factors and BF% or SM%. The associations of hypertension with BF% were higher than those with body mass index (BMI). In conclusion, both BF and SM should be considered when analyzing results from health surveys, rather than relying on BMI which does not discriminate between the two.
Prebiotic edible coatings with biopreservatives: Quality and safety of fresh apple cubes
Authors: Bambace María F. , Alvarez María V. , Moreira María R.
Published: December 2018

Apple fiber (2g/L) was incorporated along with vanillin (2.5g/L) and geraniol (0.6mL/L) into gellan coatings and their effects on the microbiological, physicochemical, nutritional and sensory quality of fresh‐cut apple (12 days at 5±1 °C) were studied. Also, the impact of coatings on the evolution of Escherichia coli O157:H7 and Listeria innocua inoculated on apples was evaluated. Geraniol enhanced antioxidant properties of apples and allowed growth rate reduction of native microbiota. Vanillin minimized color changes, improved firmness, reduced yeasts/molds growth and prolonged sensory shelf‐life by 4 days. Moreover, both biopreservatives exerted initial bactericidal effects on E. coli and geraniol reduced E. coli counts. Also, a bacteriostatic effect against L. innocua was found during the first 4 days. Therefore, these functional coatings might be good alternatives for enhancing quality and assuring safety of apples cubes. Vanillin showed the greatest potential to be applied technologically for improving the overall quality of apple cubes.

Practical applications

The use of natural and functional coatings to enhance the quality of minimally processed fruits constitutes a novel technological alternative to respond to the growing rejection of consumers of foods that contain chemical preservatives that could damage their health. Apple fiber enriched‐gellan coatings added with vanillin provide a safe product with high nutritional quality and a prolonged shelf life.
Quality‐of‐life predictors for men undergoing infertility treatment in Japan
Authors: Asazawa Kyoko , Jitsuzaki Mina , Mori Akiko , Ichikawa Tomohiko , Shinozaki Katsuko , Porter Sarah E.
Published: December 2018

Aim

To dentify the predictors of the quality of life (QOL) of infertile men who are undergoing infertility treatments in Japan and to create a QOL prediction model, with the main variables aimed at providing more adequate support to male patients.

Methods

This cross‐sectional study used the quantitative data that were collected from 321 returned self‐report questionnaires that had been distributed to the men of 411 couples who were undergoing fertility treatment. The following four scales were used to measure the main outcomes: FertiQoL, psychological distress, spousal support, and workplace support. The data were analyzed by descriptive statistics, multiple regression analyses, and structural equation modeling.

Results

The number of returned questionnaires was 321 (78.1%). The QOL that was measured by FertiQoL was significantly lower in those men who were diagnosed with male factor infertility than in the other male patients. The two significant predictors of QOL were: spousal support and the infertility period. The structural equation modeling revealed that the same factors were related to QOL.

Conclusions

Male factor infertility, less spousal support, and a longer period of infertility were associated with a poorer QOL of those men who were undergoing infertility treatment. These results suggest that focusing on infertility causes, the length of the infertility period, and the couples’ partnership during treatment is needed to provide full support to men who have been diagnosed with infertility.
The Reception of Immigrants and Refugees in Western Countries: The Challenges of Our Time
Authors: Jetten Jolanda , Esses Victoria M.
Published: December 2018

In a rapidly changing world, the challenges of migration, as well as its potential benefits, are hotly debated. Recent years have seen new challenges as a result of unprecedented levels of migration, instability following the Global Financial Crisis, economic and security concerns surrounding immigration, and negative portrayals of immigrants by some Western leaders. These developments make it all the more important to understand the psychological processes underpinning attitudes toward immigrants and refugees, support for particular immigration policies and responses to changing policies, the role of portrayals of immigrants in the media, and the consequences of immigration attitudes and policies. This special issue brings together researchers interested in the topic of immigration from a psychological perspective, with a focus on understanding the reception of immigrants and refugees in Western countries. In this introductory article, we outline the background to this special issue and briefly describe each article included.
Introduction to the Special Issue on Patient‐Centric Healthcare Management in the Age of Analytics
Authors: Bretthauer Kurt M. , Savin Sergei
Published: December 2018

Operations management provides many exciting opportunities for improving the delivery of healthcare services. Much of the existing literature has focused on the efficient and cost effective delivery of good‐quality care. Recently, there has been a growing demand for a more direct consideration of the wants, needs, and preferences of individual patients. This drive for patient‐centric care coincides with and is fed by a dramatic explosion in the availability of data and analytics tools. The 12 papers in this special issue build on these important themes, focusing on data‐driven, patient‐focused approaches to care provision.
A Scenario Analysis of Future Hong Kong Age and Labour Force Profiles and its Implications
Authors: Lloyd Chris J. , Kwok Raymond , Yip Paul S. F.
Published: December 2018

The consequences of reduced fertility and mortality on the age distribution are an issue for most developed countries, but especially for the ‘Asian tiger’ economies. We use functional data analysis forecasting techniques to project the population of Hong Kong. Our projections include error estimates that allow for forecasting error as well as exogenous variations of fertility and migration numbers. We separate out the effects of pure demographic shifts from projected behavioural changes in labour force participation. This enables us to look at the kinds of changes in labour force participation that would be required to offset the aging effects that we estimate.
Soil information management and knowledge sharing in Victoria, Australia—user perspectives
Authors: Imhof Mark P. , Heemskerk Gemma E. , Cox Matthew T.
Published: December 2018

For twenty‐one years, soil information and knowledge in Victoria, Australia has been shared via the Victorian Resources Online (VRO) website. VRO has been the primary online repository for soil and landscape information generated from land resource assessment studies, field days, training workshops, and the visualization and animation of soil and landscape processes. User surveys and qualitative feedback have highlighted the value of online soil information to users, with many considering it a useful “tool of trade,” particularly those involved in agricultural research, extension, planning and education. An extensive series of “Healthy Soils” training workshops (2007–2010) focused on topics such as “soil types and structure,” “soil chemical testing,” “soil biology,” “soil erosion” and “organic matter.” Evaluation has demonstrated their usefulness and relevance, with learning outcomes achieved by >80% of overall participants, many of whom planned to make better management decisions and change management practices on‐farm. The information and knowledge generated through the series of workshops remains a valuable online resource. The development of more sophisticated knowledge visualization tools, such as animations, has broadened the potential audience for soil‐related information. Analytical profiling of VRO users in recent years has highlighted it as a source of information and knowledge for a local, national and international audience. This supports the notion that increasing access to public‐sector data and information provides significant benefits. Lessons learnt from enduring programs such as VRO can inform future information and knowledge management initiatives.
Re‐programming of gene expression in the CS8 rice line over‐expressing ADPglucose pyrophosphorylase induces a suppressor of starch biosynthesis
Authors: Cakir Bilal , Tian Li , Crofts Naoko , Chou Hong‐Li , Koper Kaan , Ng Chun‐Yeung , Tuncel Aytug , Gargouri Mahmoud , Hwang Seon‐Kap , Fujita Naoko , Okita Thomas W.
Published: December 2018

The CS8 transgenic rice (Oryza sativa L.) lines expressing an up‐regulated glgC gene produced higher levels of ADPglucose (ADPglc), the substrate for starch synthases. However, the increase in grain weight was much less than the increase in ADPglc levels suggesting one or more downstream rate‐limiting steps. Endosperm starch levels were not further enhanced in double transgenic plants expressing both glgC and the maize brittle‐1 gene, the latter responsible for transport of ADPglc into the amyloplast. These studies demonstrate that critical processes within the amyloplast stroma restrict maximum carbon flow into starch. RNA‐seq analysis showed extensive re‐programming of gene expression in the CS8 with 2073 genes up‐regulated and 140 down‐regulated. One conspicuous gene, up‐regulated ~15‐fold, coded for a biochemically uncharacterized starch binding domain‐containing protein (SBDCP1) possessing a plastid transit peptide. Confocal microscopy and transmission electron microscopy analysis confirmed that SBDCP1 was located in the amyloplasts. Reciprocal immunoprecipitation and pull‐down assays indicated an interaction between SBDCP1 and starch synthase IIIa (SSIIIa), which was down‐regulated at the protein level in the CS8 line. Furthermore, binding by SBDCP1 inhibited SSIIIa starch polymerization activity in a non‐competitive manner. Surprisingly, artificial microRNA gene suppression of SBDCP1 restored protein expression levels of SSIIIa in the CS8 line resulting in starch with lower amylose content and increased amylopectin chains with a higher degree of polymerization. Collectively, our results support the involvement of additional non‐enzymatic factors such as SBDCP in starch biosynthesis.
Effects of Inlet Disturbances on Fan Stability
Authors: Lee Kuen-Bae , Wilson Mark , Vahdati Mehdi
Published: December 2018

This paper investigates the effects of inlet disturbance caused by crosswind on a fan blade operation and addresses the possible aerodynamic instabilities, which can arise for such a fan-intake system. The work is carried out by using a three-dimensional unsteady computational fluid dynamics (CFD) model (AU3D), and for a modern low-speed fan rig for which extensive measured data is available. The computational domain includes the fan with outlet guide vanes for the bypass flow, engine-section stators for the core, and a symmetric intake upstream of the fan (a whole low-pressure domain). The unsteady full annulus simulations under crosswind are performed to analyze the effects of inlet disturbances on the operation of this blade. It was observed that, for sufficiently high amplitudes of crosswind, the intake lip separates, and results in a significant loss of stall margin. Moreover, even in the absence of lip separation, the blade can still stall prematurely due to nonhomogeneous flow caused by the two contra-rotating trailing vortices. In the second phase of this study, the effects of fan loading on the suppression of flow separation in the intake, and the consequent stall margin of the fan blade, were explored. The results indicated that, as the fan speed increases, it becomes more capable of reducing the inlet distortion levels, and consequently, the loss in stall margin decreases.
What now for human genome editing?
Authors: Cohen Jon
Published: December 2018

Claimed creation of CRISPR-edited babies triggers calls for international oversight.
Uncertainty boosts Brexit jitters for U.K. scientists
Authors: Stokstad Erik
Published: December 2018

Political turmoil in Parliament threatens a disastrous crash out of the European Union.
Universal flu vaccine is ‘an alchemist's dream’
Authors: Cohen Jon
Published: December 2018

The rapidly changing virus and a complex immune response stymie vaccine developers.
Taking aim
Authors: Wadman Meredith
Published: December 2018

After her own violent childhood, emergency physician Rebecca Cunningham is jump-starting research to prevent gun deaths in kids.
Animals and the zoogeochemistry of the carbon cycle
Authors: Schmitz Oswald J. , Wilmers Christopher C. , Leroux Shawn J. , Doughty Christopher E. , Atwood Trisha B. , Galetti Mauro , Davies Andrew B. , Goetz Scott J.
Published: December 2018

Animals count

Flux across the carbon cycle is generally characterized by contributions from plants, microbes, and abiotic systems. Animals, however, move vast amounts of carbon, both through ecosystem webs and across the landscape. Schmitz
et al.
review the different contributions that animal populations make to carbon cycling and discuss approaches that allow for better monitoring of these contributions.

Science
, this issue p.
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Cellular RNA Helicase DHX9 Interacts with the Essential Epstein-Barr Virus (EBV) Protein SM and Restricts EBV Lytic Replication
Authors: Fu Wenmin , Verma Dinesh , Burton Ashlee , Swaminathan Sankar
Published: December 2018

This study identifies an interaction between Epstein-Barr virus (EBV) SM protein and cellular helicase DHX9, exploring the roles that this interaction plays in viral infection and host defenses. Whereas most previous studies established DHX9 as a proviral factor, we demonstrate that DHX9 may act as an inhibitor of EBV virion production. DHX9 enhanced innate antiviral pathways active against EBV and was needed for maximal expression of several interferon-induced genes. We show that SM binds to and colocalizes DHX9 and may counteract the antiviral function of DHX9. These data indicate that DHX9 possesses antiviral activity and that SM may suppress the antiviral functions of DHX9 through this association. Our study presents a novel host-pathogen interaction between EBV and the host cell.
Listeria monocytogenes: cell biology of invasion and intracellular growth
Authors: Pizarro-Cerdá Javier , Cossart Pascale
Published: December 2018

The Gram-positive pathogenListeria monocytogenesis able to promote its entry into a diverse range of mammalian host cells by triggering plasma membrane remodeling, leading to bacterial engulfment. Upon cell invasion,L. monocytogenesdisrupts its internalization vacuole and translocates to the cytoplasm, where bacterial replication takes place. Subsequently,L. monocytogenesuses an actin-based motility system that allows bacterial cytoplasmic movement and cell-to-cell spread.L. monocytogenestherefore subverts host cell receptors, organelles and the cytoskeleton at different infection steps, manipulating diverse cellular functions that include ion transport, membrane trafficking, post-translational modifications, phosphoinositide production, innate immune responses as well as gene expression and DNA stability.
Clinical phenotyping of newly diagnosed type 2 diabetes in Yemen
Authors: Gunaid Abdallah Ahmed , Al-Kebsi Mohammed Mohammed , Bamashmus Mahfouth Abdalla , Al-Akily Saleh Ahmed , Al-Radaei Ahmed Nasser
Published: December 2018

Objective

To identify clinical phenotypes of type 2 diabetes (T2D) among adults presenting with a first diagnosis of diabetes.

Research design and methods

A total of 500 consecutive patients were subject to clinical assessment and laboratory investigations. We used data-driven cluster analysis to identify phenotypes of T2D based on clinical variables and Homeostasis Model Assessment (HOMA2) of insulin sensitivity and beta-cell function estimated from paired fasting blood glucose and specific insulin levels.

Results

The cluster analysis identified three statistically different clusters: cluster 1 (high insulin resistance and high beta-cell function group), which included patients with low insulin sensitivity and high beta-cell function; cluster 2 (low insulin resistance and low beta-cell function group), which included patients with high insulin sensitivity but very low beta-cell function; and cluster 3 (high insulin resistance and low beta-cell function group), which included patients with low insulin sensitivity and low beta-cell function. Insulin sensitivity, defined as median HOMA2-S, was progressively increasing from cluster 1 (35.4) to cluster 3 (40.9), to cluster 2 (76) (p<0.001). On the contrary, beta-cell function, defined as median HOMA2-β, was progressively declining from cluster 1 (78.3) to cluster 3 (30), to cluster 2 (22.3) (p<0.001). Clinical and biomarker variables associated with insulin resistance like obesity, abdominal adiposity, fatty liver, and high serum triglycerides were mainly seen in clusters 1 and 3. The highest median hemoglobin A1c value was noted in cluster 2 (88 mmol/mol) and the lowest in cluster 1.

Conclusion

Cluster analysis of newly diagnosed T2D in adults has identified three phenotypes based on clinical variables central to the development of diabetes and on specific clinical variables of each phenotype.
Operationalising a conceptual framework for a contiguous hospitalisation episode to study associations between surgical timing and death after first hip fracture: a Canadian observational study
Authors: Sheehan Katie Jane , Levy Adrian R , Sobolev Boris , Guy Pierre , Tang Michael , Kuramoto Lisa , Sutherland Jason M , Beaupre Lauren , Morin Suzanne N , Harvey Edward , Bradley Nick
Published: December 2018

Objective

We describe steps to operationalise a published conceptual framework for a contiguous hospitalisation episode using acute care hospital discharge abstracts. We then quantified the degree of bias induced by a first abstract episode, which does not account for hospital transfers.

Design

Retrospective observational study.

Setting

All acute care hospitals in nine Canadian provinces.

Participants

We retrieved acute hospitalisation discharge abstracts for 189 448 patients aged 65 years and older admitted to acute care with hip fracture between 2003 and 2013.

Primary and secondary outcome measures

The percentage of patients treated surgically, delayed to surgery (defined as two or more days after admission) and dying, between contiguous hospitalisation episodes and the first abstract episodes of care.

Results

Using contiguous hospitalisation episodes, 91.6% underwent surgery, 35.7% were delayed two or more days after admission and 6.7% died postoperatively, whereas, using the first abstract only, these percentages were 83.7%, 32.5% and 6.5%, respectively.

Conclusion

We demonstrate that not accounting for hospital transfers when evaluating the association between surgical timing and death underestimates reporting of the percentage of patients treated surgically and delayed to surgery by 9%, and the percentage who die after surgery by 3%. Researchers must be aware of this potential and avoidable bias as, depending on the purpose of the study, erroneous inferences may be drawn.
Study on Rural Eco-Governance in the Context of New-Type Urbanization
Authors: YU Fawen
Published: December 2018

During the process of new-type urbanization, industrial enterprises, as they move to the vast rural areas, have also brought pollution there. Rural eco-governance tackles not only the damage to natural resources and environment, industrial pollution, agricultural non-point source pollution and pollution caused by poultry and livestock raising, but also the aggravation of rural living environment. At present, governments at all levels usually focus solely on urban environment building and eco-governance in rural areas, as a result, is rarely aware of, insufficient in capital input, weak in technical and institutional support. To improve rural eco-governance substantially, governments at all levels should attach equal importance to rural and new urban ecological development and take effective measures in the following aspects: (1) improving top-level design and reinforce the leading position of the green development concept; (2) increasing capital input and improve rural eco-governance facilities; (3) making technological innovations and integration to support rural eco-governance; and (4) creating new governance mechanisms to enhance rural eco-governance.
Passages
Authors: Groce Alex
Published: December 2018

Confucius'2 Analects is the oldest guide to applied software engineering research and practice in existence. You don't believe me? Fine. We'll use random sampling to demonstrate. I have Ezra Pound's peculiar, but engaging, translation to hand, and can write a small program to generate five random samples easily, since the Analects has twenty books, and each book has approximately twenty "items." I've sorted the resulting samples for our convenience.
BeginToReason
Authors: Fowler Megan , Schwab Tim
Published: December 2018

Computer science (CS) students often evaluate the behavior of the code they write by running it on specific inputs, studying the outputs, and then inductively reasoning to a more general understanding of the code. This is a good starting point in the student's career, but successful graduates must be able to reason deductively about the code they create and encounter. They must be able to reason about the code on all inputs, without running the code. This paper describes an online system named "BeginToReason" that is designed to introduce symbolic reasoning, and the results of its use. Eighty students across six lab sections completed a written assessment while working with the BeginToReason System. The objective was to observe student understanding of the purpose of presented code both before and after completing a lesson using the BeginToReason System. Keywords: Symbolic reasoning, reasoning tool, online system, verification engine
Reasoning About Reference Behavior with RESOLVE
Authors: Sun Yu-Shan
Published: December 2018

As an alternative to reasoning about references explicitly and ACM SIGSOFT Software Engineering Notes Page 18 July 2018 Volume 43 Number 3 routinely as needed for Java-like programs, this paper summarizes the RESOLVE approach in reasoning via reference-hiding data abstractions for the majority of programs and only reasoning about references when they are unavoidable. Furthermore, this paper raises discussion topics for reasoning about various implementation classifications and to explore when there is a need to be concerned about establishing the frame property