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Background Cell type-specific ribosome-pulldown has become an increasingly popular method for analysis of gene expression. It allows for expression analysis from intact tissues and monitoring of protein synthesis in vivo. However, while its utility has been assessed, technical aspects related to sequencing of these samples, often starting with a smaller amount of RNA, have not been reported. In this study, we evaluated the performance of five library prep protocols for ribosome-associated mRNAs when only 250 pg-4 ng of total RNA are used. Results We obtained total and RiboTag-IP RNA, in three biological replicates. We compared 5 methods of library preparation for Illumina Next Generation sequencing: NuGEN Ovation RNA-Seq system V2 Kit, TaKaRa SMARTer Stranded Total RNA-Seq Kit, TaKaRa SMART-Seq v4 Ultra Low Input RNA Kit, Illumina TruSeq RNA Library Prep Kit v2 and NEBNext® Ultra™ Directional RNA Library Prep Kit using slightly modified protocols each with 4 ng of total RNA. An additional set of samples was processed using the TruSeq kit with 70 ng, as a ‘gold standard’ control and the SMART-Seq v4 with 250 pg of total RNA. TruSeq-processed samples had the best metrics overall, with similar results for the 4 ng and 70 ng samples. The results of the SMART-Seq v4 processed samples were similar to TruSeq (Spearman correlation > 0.8) despite using lower amount of input RNA. All RiboTag-IP samples had an increase in the intronic reads compared with the corresponding whole tissue, suggesting that the IP captures some immature mRNAs. The SMARTer-processed samples had a higher representation of ribosomal and non-coding RNAs leading to lower representation of protein coding mRNA. The enrichment or depletion of IP samples compared to corresponding input RNA was similar across all kits except for SMARTer kit. Conclusion RiboTag-seq can be performed successfully with as little as 250 pg of total RNA when using the SMART-Seq v4 kit and 4 ng when using the modified protocols of other library preparation kits. The SMART-Seq v4 and TruSeq kits resulted in the highest quality libraries. RiboTag IP RNA contains some immature transcripts.

Purpose – Arguing that the print media act as a claims-making forum for the social construction and contestation of crises, the aim of this paper is to explore how the print media mediated two audits commissioned following a high-profile salary cap breach in the National Rugby League (NRL) in Australia. Design/methodology/approach – This paper draws upon critical discourse analysis to examine the media coverage of the two audits by the two major Australian media organisations, News Limited and Fairfax Media Limited. The analysis is based on a qualitative study complemented by quantitative techniques that explore critical incidents and representations in the daily press. Findings – The paper illustrates the way in which News Limited, the owner of the infringing club, mobilised its media platform to promote favourable viewpoints and interpretations and how these were challenged in the Fairfax press. Evidence of both coverage bias and statement bias in the treatment of the two audits is produced. Originality/value – This paper provides evidence that commercial interests of owner/publishers coloured media coverage of the two audits, which were central pillars of the crisis management strategy of News Limited and the NRL. Implications for the media's contribution to public accountability, accounting outputs and impression management, and the growing commercial diversification and reach of media outlets are considered.

Many estimation and inference problems arising from large-scale animal surveys are focused on developing an understanding of patterns in abundance or occurrence of a species based on spatially referenced count data. One fundamental challenge, then, is that it is generally not feasible to completely enumerate (\"census\") all individuals present in each sample unit. This observation bias may consist of several components, including spatial coverage bias (not all individuals in the population are exposed to sampling) and detection bias (exposed individuals may go undetected). Thus, observations are biased for the state variable (abundance, occupancy) that is the object of inference. Moreover, data are often sparse for most observation locations, requiring consideration of methods for spatially aggregating or otherwise combining sparse data among sample units. The development of methods that unify spatial statistical models with models accommodating non-detection is necessary to resolve important spatial inference problems based on animal survey data. In this paper, we develop a novel hierarchical spatial model for estimation of abundance and occurrence from survey data wherein detection is imperfect. Our application is focused on spatial inference problems in the Swiss Survey of Common Breeding Birds. The observation model for the survey data is specified conditional on the unknown quadrat population size, N(s). We augment the observation model with a spatial process model for N(s), describing the spatial variation in abundance of the species. The model includes explicit sources of variation in habitat structure (forest, elevation) and latent variation in the form of a correlated spatial process. This provides a model-based framework for combining the spatially referenced samples while at the same time yielding a unified treatment of estimation problems involving both abundance and occurrence. We provide a Bayesian framework for analysis and prediction based on the integrated likelihood, and we use the model to obtain estimates of abundance and occurrence maps for the European Jay (Garrulus glandarius), a widespread, elusive, forest bird. The naive national abundance estimate ignoring imperfect detection and incomplete quadrat coverage was 77 766 territories. Accounting for imperfect detection added approximately 18 000 territories, and adjusting for coverage bias added another 131 000 territories to yield a fully corrected estimate of the national total of about 227 000 territories. This is approximately three times as high as previous estimates that assume every territory is detected in each quadrat.

To estimate the coverage error for web surveys in Europe over time, we analyzed data from the Eurobarometer. The Eurobarometer collects data for the European Community across member and applicant states. Since 2005, the Eurobarometer has contained a straightforward question on Internet access. We compared respondents with and without Internet access and estimated coverage bias for demographic variables (sex, age, length of education) and sociopolitical variables (left-right position on a political scale, life satisfaction). Countries in Europe do differ in Internet penetration and resulting coverage bias. Over time, Internet penetration dramatically increases and coverage bias decreases, but the rate of change differs across countries. In addition, the countries’ development significantly affects the pace of these changes.

Cell-phone-only (CPO) households differ along key variables from non-CPO households, creating potential coverage biases in landline-only random-digit-dialing (RDD) surveys. Researchers have attempted to correct for this by weighting their data based on demographic differences. Previous research, however, has not examined CPO coverage biases in media-use surveys—an important oversight as cell phone use is itself a media choice. This article presents a secondary analysis of Pew’s 2012 media consumption survey and concludes that demographics alone are not adequate controls for the CPO bias in media-use surveys.

The continuously growing mobile-only population raises concerns regarding the representativeness of traditional landline telephone surveys. At this time, the mobile-only population differs significantly from general population, which leads to coverage bias when using fixed-line samples only for telephone surveys. However, in many European countries the mobile-only population is not the only source of coverage bias in telephone surveys. In addition, we have to consider coverage biases caused by considerable proportions of citizens without any telephone service. Since these two groups differ from the general population with respect to differential socio-demographic categories, in our view, the negative effects of mobile-only coverage error in traditional landline telephone surveys might in fact compensate—in part—for coverage bias caused by the no-phone population. To test this hypothesis of compensating coverage biases we calculated relative coverage biases caused by the mobile-only population and relative coverage biases caused by the no-phone population in 30 European countries for two socio-demographic variables in two points in time. Results are presented for four groups of countries that differ with respect to no-phone and mobile-only rates. Results suggest that—in general—mobile-only biases and no-phone biases do not compensate to a great extent, and thus the alarming mobile-only biases cannot be neglected when using telephone surveys in the estimation of population parameters. Nevertheless, there are several countries where the bias caused by the mobile-only population is far bigger than the joint bias caused by the mobile-only population and the no-phone population. This finding suggests that biases caused by the recent mobile-only population would be even more severe if the no-phone population did not exist.

In this paper, we advance a three-stage theory-building framework to assist scholars in addressing theoretical and coverage biases by means of the appropriate design of cross-domain theory-building research. In our discussion, we use an example from research in international entrepreneurship, which has been emerging as a cross-domain area for the entrepreneurship and international business research communities since the mid-1990s. Theoretical bias can stem from the situation where the conceptualisation of a phenomenon whose research is currently emerging and depends upon several of the established disciplines of social science and their sub-domains, is in fact dominated by the theoretical approaches of a single domain. As to the coverage bias, the somewhat novel research domain of international entrepreneurship provides us with a means to illustrate how research in an emerging domain tends to focus on positive growth only and rarely takes appropriately into account companies that fare less well; for instance, accounting for survivor bias would require that scholars carefully acknowledge firms that go out of business for one reason or another. Observations from a longitudinal, multiple-case study research on the de-internationalisation of small high-technology firms is used to exemplify the structure of our framework.

Online news media sites are emerging as the primary source of news for a large number of users. Due to a large number of stories being published in these media sites, users usually rely on news recommendation systems to find important news. In this work, we focus on automatically recommending news stories to all users of such media websites, where the selection is not influenced by a particular user’s news reading habit. When recommending news stories in such non-personalized manner, there are three basic metrics of interest—recency, importance (analogous to relevance in personalized recommendation) and diversity of the recommended news. Ideally, recommender systems should recommend the most important stories soon after they are published. However, the importance of a story only becomes evident as the story ages, thereby creating a tension between recency and importance. A systematic analysis of popular recommendation strategies in use today reveals that they lead to poor trade-offs between recency and importance in practice. So, in this paper, we propose a new recommendation strategy (called Highest Future-Impact) which attempts to optimize on both the axes. To implement our proposed strategy in practice, we propose two approaches to predict the future-impact of news stories, by using crowd-sourced popularity signals and by observing editorial selection in past news data. Finally, we propose approaches to inculcate diversity in recommended news which can maintain a balanced proportion of news from different news sections. Evaluations over real-world news datasets show that our implementations achieve good performance in recommending news stories.

We review objective Bayes procedures based on both parametric and predictive coverage probability bias and explore the extent to which such procedures contravene the likelihood principle in the case of a scalar parameter. The discussion encompasses choice of objective priors, objective posterior probability statements and objective predictive probability statements. We conclude with some remarks concerning the future development and implementation of objective priors based on small coverage probability bias.

Probability matching priors are priors for which the posterior probabilities of certain specified sets are exactly or approximately equal to their coverage probabilities. These priors arise as solutions of partial differential equations that may be difficult to solve, either analytically or numerically. Recently Levine & Casella (2003) presented an algorithm for the implementation of probability matching priors for an interest parameter in the presence of a single nuisance parameter. In this paper we develop a local implementation that is very much more easily computed. A local probability matching prior is a data-dependent approximation to a probability matching prior and is such that the asymptotic order of approximation of the frequentist coverage probability is not degraded. We illustrate the theory with a number of examples, including three discussed in Levine & Casella (2003).