THE RETAIL PRICE EFFECT OF THE KENTUCKY AND TENNESSEE MILK MARKETING LAWS

Retail prices of milk in Kentucky and Tennessee are compared following the abolishment of Kentucky's Milk Marketing Law. Data and comparisons are also presented from the six adjacent states having no milk marketing law.Demand and Price Analysis,

Evaluation of existing and new methods of tracking glacier terminus change

ACKNOWLEDGEMENTS The authors thank two anonymous reviewers for constructive comments that helped to improve the manuscript. This research was financially supported by J.M.L.’s PhD funding from UK Natural Environment Research Council grant No. NE/I528742/1.Peer reviewedPublisher PD

What do Bayesian methods offer population forecasters?

The Bayesian approach has a number of attractive properties for probabilistic forecasting. In this paper, we apply Bayesian time series models to obtain future population estimates with uncertainty for England and Wales. To account for heterogeneity found in the historical data, we add parameters to represent the stochastic volatility in the error terms. Uncertainty in model choice is incorporated through Bayesian model averaging techniques. The resulting predictive distributions from Bayesian forecasting models have two main advantages over those obtained using traditional stochastic models. Firstly, data and uncertainties in the parameters and model choice are explicitly included using probability distributions. As a result, more realistic probabilistic population forecasts can be obtained. Second, Bayesian models formally allow the incorporation of expert opinion, including uncertainty, into the forecast. Our results are discussed in relation to classical time series methods and existing cohort component projections. This paper demonstrates the flexibility of the Bayesian approach to simple population forecasting and provides insights into further developments of more complicated population models that include, for example, components of demographic change

Integrated Modelling of European Migration: Background, specification and results

The aims of this paper are to present the background and specification of the Integrated Modelling of European Migration (IMEM) model. Currently, international migration data are collected by individual countries with separate collection systems and designs. This creates problems when attempting to understand or predict population movements between countries as the reported data are inconsistent in terms of their availability, definitions and quality. Rather than wait for countries to harmonise their migration data collection and reporting systems, we propose a model to overcome the limitations of the various data sources. In particular, we propose a Bayesian model for harmonising and correcting the inadequacies in the available data and for estimating the completely missing flows. The focus is on estimating recent international migration flows amongst countries in the European Union (EU) and European Free Trade Association (EFTA) from 2002 to 2008, using data collected by Eurostat and other national and international institutions. We also include additional information provided by experts on the effects of undercount, measurement and accuracy. The methodology is integrated and capable of providing a synthetic data base with measures of uncertainty for international migration flows and other model parameters.

Augmenting migration statistics with expert knowledge

International migration statistics vary considerably from one country to another in terms of measurement, quality and coverage. Furthermore, immigration tend to be captured more accurately than emigration. In this paper, we first describe the need to augment reported flows of international migration with knowledge gained from experts on the measurement of migration statistics, obtained from a multi-stage Delphi survey. Second, we present our methodology for translating this information into prior distributions for input into the Integrated Modelling of European Migration (IMEM) model, which is designed to estimate migration flows amongst countries in the European Union (EU) and European Free Trade Association (EFTA), by using recent data collected by Eurostat and other national and international institutions. The IMEM model is capable of providing a synthetic data base with measures of uncertainty for international migration flows and other model parameters.

Terminus-driven retreat of a major southwest Greenland tidewater glacier during the early 19th century : insights from glacier reconstructions and numerical modelling

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Greenland tidewater glacier advanced rapidly during era of Norse Settlement

ACKNOWLEDGMENTS We thank the Greenland Institute of Natural Resources for providing logistical support in Nuuk. Martin Blicher, Thomas Juul-Pedersen, and Johanne Vad are thanked for their research and field assistance. We acknowledge the support of the National Museum of Greenland for permission to undertake excavations near Norse ruin sites (permit 2015/03). Project funding was provided by the Leverhulme Trust Research Project grant 2014-093, and J.M. Lea was supported by funding from the Quaternary Research Association, British Society for Geomorphology, and a UK Research and Innovation (UKRI) Future Leaders Fellowship (MR/S017232/1). We thank two anonymous reviewers and the editor for constructive comments, which helped to substantially improve this paper. D.M. Pearce would like to dedicate this paper to her father Richard M. Pearce.Peer reviewedPostprin

Hypermethylation of CpG islands and shores around specific microRNAs and mirtrons is associated with the phenotype and presence of bladder cancer

PURPOSE To analyze the role and translational potential for hypermethylation of CpG islands and shores in the regulation of small RNAs within urothelial cell carcinoma (UCC). To examine microRNAs (miR) and mirtrons, a new class of RNA located within gene introns and processed in a Drosha-independent manner. EXPERIMENTAL DESIGN The methylation status of 865 small RNAs was evaluated in normal and malignant cell lines by using 5-azacytidine and microarrays. Bisulfite sequencing was used for CpG regions around selected RNAs. Prognostic and diagnostic associations for epigenetically regulated RNAs were examined by using material from 359 patients, including 216 tumors and 121 urinary samples (68 cases and 53 controls). Functional analyses examined the effect of silencing susceptible RNAs in normal urothelial cells. RESULTS Exonic/UTR-located miRs and mirtons are most susceptible to epigenetic regulation. We identified 4 mirtrons and 16 miRs with CpG hypermethylation across 35 regions in normal and malignant urothelium. For several miRs, hypermethylation was more frequent and dense in CpG shores than islands (e.g., miRs-9/149/210/212/328/503/1224/1227/1229), and was associated with tumor grade, stage, and prognosis (e.g., miR-1224 multivariate analysis OR = 2.5; 95% CI, 1.3-5.0; P = 0.006). The urinary expression of epigenetically silenced RNAs (miRs-152/328/1224) was associated with the presence of UCC (concordance index, 0.86; 95% CI, 0.80-0.93; ANOVA P < 0.016). CONCLUSIONS Hypermethylation of mirtrons and miRs is common in UCC. Mirtrons appear particularly susceptible to epigenetic regulation. Aberrant hypermethylation of small RNAs is associated with the presence and behavior of UCC, suggesting potential roles as diagnostic and prognostic biomarkers