An exploration of the role duality experienced by HR professionals as both implementers and recipients of HR practices: evidence from the Indian railways

This study provides an innovative perspective on empirically assessing HR by focusing on the duality of HR professionals’ experiences as both implementers and recipients or internal customers of HR practices given that they are also employees of the organization. We hypothesize that HR professionals experience HR practices more favorably from an implementer perspective as compared to an internal customer perspective. These differences in experiences are likely to be influenced by HR professionals’ hierarchical position in the HR department. Our analyses of 1,271 HR professionals employed by Indian Railways revealed a number of differences between the two types of experience. Some practices (recruitment and selection, training, and employee welfare) were viewed more negatively from the implementer perspective, whereas others (compensation, benefits, and employment relations) were rated more negatively from the internal customer perspective. Those holding more senior HR positions reported more positive experiences of training and employment relations from an internal customer perspective. Overall our contributions draw on the attribution theory and concepts of intraorganizational power and voice, and have implications concerning the effectiveness of HR practices. © 2015 Wiley Periodicals, Inc.

A hierarchical Bayesian model for predicting the functional consequences of amino-acid polymorphisms

Genetic polymorphisms in deoxyribonucleic acid coding regions may have a phenotypic effect on the carrier, e.g. by influencing susceptibility to disease. Detection of deleterious mutations via association studies is hampered by the large number of candidate sites; therefore methods are needed to narrow down the search to the most promising sites. For this, a possible approach is to use structural and sequence-based information of the encoded protein to predict whether a mutation at a particular site is likely to disrupt the functionality of the protein itself. We propose a hierarchical Bayesian multivariate adaptive regression spline (BMARS) model for supervised learning in this context and assess its predictive performance by using data from mutagenesis experiments on lac repressor and lysozyme proteins. In these experiments, about 12 amino-acid substitutions were performed at each native amino-acid position and the effect on protein functionality was assessed. The training data thus consist of repeated observations at each position, which the hierarchical framework is needed to account for. The model is trained on the lac repressor data and tested on the lysozyme mutations and vice versa. In particular, we show that the hierarchical BMARS model, by allowing for the clustered nature of the data, yields lower out-of-sample misclassification rates compared with both a BMARS and a frequen-tist MARS model, a support vector machine classifier and an optimally pruned classification tree.

Hierarchical modeling of entangled polymers

We demonstrate that it is possible to link multi-chain molecular dynamics simulations with the tube model using a single chain slip-links model as a bridge. This hierarchical approach allows significant speed up of simulations, permitting us to span the time scales relevant for a comparison with the tube theory. Fitting the mean-square displacement of individual monomers in molecular dynamics simulations with the slip-spring model, we show that it is possible to predict the stress relaxation. Then, we analyze the stress relaxation from slip-spring simulations in the framework of the tube theory. In the absence of constraint release, we establish that the relaxation modulus can be decomposed as the sum of contributions from fast and longitudinal Rouse modes, and tube survival. Finally, we discuss some open questions regarding possible future directions that could be profitable in rendering the tube model quantitative, even for mildly entangled polymers

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Evaluating explanations about drug prescriptions: effects of varying the nature of information about side effects and its relative position in explanations

This study evaluates computer-generated written explanations about drug prescriptions that are based on an analysis of both patient and doctor informational needs. Three experiments examine the effects of varying the type of information given about the possible side effects of the medication, and the order of information within the explanation. Experiment 1 investigated the effects of these two factors on people's ratings of how good they consider the explanations to be and of their perceived likelihood of taking the medication, as well as on their memory for the information in the explanation. Experiment 2 further examined the effects of varying information about side effects by separating out the contribution of number and severity of side effects. It was found that participants in this study did not “like” explanations that described severe side effects, and also judged that they would be less likely to take the medication if given such explanations. Experiment 3 therefore investigated whether information about severe side effects could be presented in such a way as to increase judgements of how good explanations are thought to be, as well as the perceived likelihood of adherence. The results showed some benefits of providing additional explanatory information.

The seasonal forecast of electricity demand: A hierarchical Bayesian model with climatological weather generator

In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

A hierarchical distributed approach for mining molecular fragments

Recently, two approaches have been introduced that distribute the molecular fragment mining problem. The first approach applies a master/worker topology, the second approach, a completely distributed peer-to-peer system, solves the scalability problem due to the bottleneck at the master node. However, in many real world scenarios the participating computing nodes cannot communicate directly due to administrative policies such as security restrictions. Thus, potential computing power is not accessible to accelerate the mining run. To solve this shortcoming, this work introduces a hierarchical topology of computing resources, which distributes the management over several levels and adapts to the natural structure of those multi-domain architectures. The most important aspect is the load balancing scheme, which has been designed and optimized for the hierarchical structure. The approach allows dynamic aggregation of heterogenous computing resources and is applied to wide area network scenarios.

Molecular characterization of Iranian wheat stripe virus shows its taxonomic position as a distinct species in the genus Tenuivirus

The full lengths of three genome segments of Iranian wheat stripe virus (IWSV) were amplified by reverse transcription (RT) followed by polymerase chain reaction (PCR) using a primer complementary to tenuivirus conserved terminal sequences. The segments were sequenced and found to comprise 3469, 2337, and 1831 nt, respectively. The gene organization of these segments is similar to that of other known tenuiviruses, each displaying an ambisense coding strategy. IWSV segments, however, are different from those of other viruses with respect to the number of nucleotides and deduced amino acid sequence for each ORF. Depending on the segment, the first 16-22 nt at the 5' end and the first 16 nt at the 3' end are highly conserved among IWSV and rice hoja blanca virus (RHBV), rice stripe virus (RSV) and maize stripe virus ( MStV). In addition, the first 15-18 nt at the 5' end are complementary to the first 16-18 nt at the 3' end. Phylogenetic analyses showed close similarity and a common ancestor for IWSV, RHBV, and Echinochloa hoja blanca virus (EHBV). These findings confirm the position of IWSV as a distinct species in the genus Tenuivirus.

Phylogeny and the hierarchical organization of plant diversity

R. H. Whittaker's idea that plant diversity can be divided into a hierarchy of spatial components from alpha at the within-habitat scale through beta for the turnover of species between habitats to gamma along regional gradients implies the underlying existence of alpha, beta, and gamma niches. We explore the hypothesis that the evolution of a, (3, and gamma niches is also hierarchical, with traits that define the a niche being labile, while those defining a and 7 niches are conservative. At the a level we find support for the hypothesis in the lack of close significant phylogenetic relationship between meadow species that have similar a niches. In a second test, a niche overlap based on a variety of traits is compared between congeners and noncongeners in several communities; here, too, there is no evidence of a correlation between a niche and phylogeny. To test whether beta and gamma niches evolve conservatively, we reconstructed the evolution of relevant traits on evolutionary trees for 14 different clades. Tests against null models revealed a number of instances, including some in island radiations, in which habitat (beta niche) and elevational maximum (an aspect of the gamma niche) showed evolutionary conservatism.

Floral meristem indeterminacy depends on flower position and is facilitated by acarpellate gynoecium development in Impatiens balsamina

Floral meristems are generally determinate. Termination of their activity varies with species, occurring after carpel or ovule development, depending on the placentation type. In terminal flowering Impatiens balsamina (cv. Dwarf Bush Flowered) some flowers exhibit meristem indeterminacy; they produce organs from the placenta after ovule development. Here we provide a detailed description of gynoecium development in this line and explore the basis of the indeterminate nature of some of its floral meristems. We find that the placenta is sometimes established without complete carpel fusion. Proliferative growth derives from meristematic remnants of the placenta and is more common in the terminal inflorescence. RNA in situ hybridization reveals that IbLFY (Impatiens LFY homologue) is expressed in all meristem states, even in proliferating meristems. Expression of IbAG in axillary flowers is as expected in the meristem, stamens and carpels but absent from the proliferating meristem. We conclude that I. balsamina has cauline placentation. Incomplete suppression of inflorescence identity in flowers of the terminal inflorescence leads to floral meristem proliferation after ovule development in this species.