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This book examines despotism and deceit in the Graeco-Roman world from historical and literary perspectives, over a range of historical periods including classical Athens, the Hellenistic kingdoms, late republican and early imperial Rome, late antiquity, and Byzantium.

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Geochemistry, Geophysics, Geosystems 16 (2015): 925–946, doi:10.1002/2014GC005692. ; Grain size is an important control on mantle viscosity and permeability, but is difficult or impossible to measure in situ. We construct a two-dimensional, single phase model for the steady state mean grain size beneath a mid-ocean ridge. The mantle rheology is modeled as a composite of diffusion creep, dislocation creep, dislocation accommodated grain boundary sliding, and a plastic stress limiter. The mean grain size is calculated by the paleowattmeter relationship of Austin and Evans (2007). We investigate the sensitivity of our model to global variations in grain growth exponent, potential temperature, spreading-rate, and mantle hydration. We interpret the mean grain-size field in terms of its permeability to melt transport. The permeability structure due to mean grain size may be approximated as a high permeability region beneath a low permeability region. The transition between high and low permeability regions occurs across a boundary that is steeply inclined toward the ridge axis. We hypothesize that such a permeability structure generated from the variability of the mean grain size may focus melt toward the ridge axis, analogous to Sparks and Parmentier (1991)-type focusing. This focusing may, in turn, constrain the region where significant melt fractions are observed by seismic or magnetotelluric surveys. This interpretation of melt focusing via the grain-size permeability structure is consistent with MT observation of the asthenosphere beneath the East Pacific Rise. ; European Research Council under the European Union's Seventh Framework Programme . Grant Number: FP7/2007–2013

ABSTRACT
ObjectivesDataSHIELD (www.datashield.ac.uk) was born of the requirement in the biomedical and social sciences to co-analyse individual patient data (microdata) from different sources, without disclosing identity or sensitive information. Under DataSHIELD, raw data never leaves the data provider and no microdata or disclosive information can be seen by the researcher. The analysis is taken to the data - not the data to the analysis.
Text data can be very disclosive in the biomedical domain (patient records, GP letters etc). Similar, but different, issues are present in other domains - text could be copyrighted, or have a large IP value, making sharing impractical.
ApproachBy treating text in an analogous way to individual patient data we assessed if DataSHIELD could be adapted and implemented for text analysis, and circumvent the key obstacles that currently prevent it.
ResultsUsing open digitised text data held by the British Library, a DataSHIELD proof-of-concept infrastructure and prototype DataSHIELD functions for free text analysis were developed.
ConclusionsWhilst it is possible to analyse free text within a DataSHIELD infrastructure, the challenge is creating generalised and resilient anti-disclosure methods for free text analysis. There are a range of biomedical and health sciences applications for DataSHIELD methods of privacy protected analysis of free text including analysis of electronic health records and analysis of qualitative data e.g. from social media.

The manner in which the key managers of entrepreneurial firms perceive the environment of the firm has important implications for decisions regarding organizational structure, processes and performance. Entrepreneurial behavior has traditionally been characterized as one type of strategic response to uncertain environments. This research takes a unique position in exploring how the entrepreneurial orientation of the firm's key manager may in fact influence managerial perceptions of the environment. Utilizing survey data drawn from more than 800 key managers in three countries this study proposes and tests a model of perceived uncertainty. The results suggest that the greater the entrepreneurial orientation of the key manager the more likely he or she is to characterize the environment of the firm as uncertain. Although this relationship holds true in general the results also suggest that there are strong differences in the relationship across countries and industries and that certain firm characteristics have a potential impact on managerial perceptions.

ABSTRACT
ObjectivesIn several disciplines such as in biomedicine and social sciences the analysis of individual-level data or the co-analysis of data from different studies requires the pooling and the sharing of those data. However, sharing and combining sensitive individual-level data is often prohibited by ethico-legal constraints and other barriers such as the control maintenance and the huge sample sizes. The graphical illustration of microdata is also often forbidden as can potentially be unsecured on the identification of sensitive information. For example the plot of a standard scatterplot is disclosive as can explicitly specify the exact values of two measurements for each single individual.
ApproachDataSHIELD (www.datashield.ac.uk) is a novel approach that allows the analysis of sensitive individual-level data and the co-analysis of such data from several studies simultaneously without physically pooling the data.
ResultsDataSHIELD functionality consists of several functions that provide the flexibility of performing data analysis through different statistical techniques. A part of this environment includes a number of graphical-related functions for the graphical illustration of the statistical properties and relationships between different variables. We overview the graphical functions in DataSHIELD (ds.histogram, ds.heatmapPlot, ds.contourPlot) and demonstrate a number of new functions including ds.scatterPlot and ds.boxPlot developed based on the application of different computational approaches like the k-Nearest Neighbours algorithm and ensuring privacy protected analysis.
ConclusionDataSHIELD graphical functionality has certain methodological features for the representation of the relationships between different variables preserving their statistical properties and assuring the data privacy protection. These graphical approaches can be used or enhanced for application in various areas where confidentiality and information sensitivity is considered, for example in longitudinal data and survival analysis, in epidemiological studies, in geospatial analysis and several others.

Although it is generally acknowledged that fire-induced heterogeneity is important for maintaining diverse species assemblages in northern Australian savannas, scant relevant data are currently available to examine this proposition. The study takes advantage of a singular, detailed, bidecadal fire history assembled annually for Kakadu National Park to explore relationships between fire-induced heterogeneity and other terrain features. Three patch-based heterogeneity indices were calculated from assembled fire-history data for the central 1-ha cell of a 5 × 5 cell (25 ha) window; that is, at a spatial scale relevant to the home ranges of many small- to medium-sized native mammals. Two of these indices were first calculated separately for each year, employing different metrics based on the extent of burning occurring in the 5 × 5 cell array, and then averaged for each of four consecutive five-year periods and over all years. The third index was calculated as the sum of the coefficients of variation for four fire-regime variability parameters determined likewise for five- and 20-year periods. Assembled data illustrate that (1) fire-induced heterogeneity in Kakadu increased in each successive five-year period from 1981, and (2) when modelled with independent terrain coverages, significant relationships were obtained for all three heterogeneity indices with terrain roughness, distance to roads, and distance to drainage lines.

This report describes the results of the Scottish Official Control Monitoring Programmes delivered by the Centre for Environment, Fisheries and Aquaculture Science (Cefas) and partners for the period 1st January to 31st December 2018. The programmes were delivered on behalf of Food Standards Scotland (FSS), the competent authority in Scotland for food safety and were aimed at delivering the testing required for the statutory monitoring of biotoxins, E.coli and chemical contaminants in shellfish and for the identification and enumeration of potentially harmful algal species in selected shellfish harvesting areas, as described in EC Regulations 854/2004, 882/2004, 1881/2006 and 2074/2005. The co-ordination of the programme, its logistics, toxin analyses and the majority of E. coli analyses were conducted by Cefas, whilst phytoplankton analyses were performed by SAMS Research Services Ltd. (SRSL) in Oban, chemical contaminants analyses by Fera Science Ltd (Fera) in York and E. coli analyses for Shetland only by SSQC Ltd in Scalloway. These laboratories were contracted by Cefas under the scope of the 'Shellfish Partnership'. An overview of these programmes and their results are presented in the following sections of this report: • Section 1: Toxin and phytoplankton monitoring programme • Section 2: E. coli monitoring programme • Section 3: Chemical contaminants monitoring programme The Shellfish Partnership has been responsible for the delivery of these programmes since 2012. Until now, the results of each annual programme have been reported separately. At the request of FSS, the 2018 results have been combined into one single annual report. A total of 3,975 shellfish samples and 1,305 water samples were collected for the purpose of the 2018 Scottish official control monitoring programmes. Samples collected between the 1st of January and 31st of March were collected by officers operating on behalf of several contractors appointed directly by FSS. Since the 1st of April 2018, sampling officers from Hall Mark Meat Hygiene (HMMH) have collected or arranged collection for all samples from all geographic locations, under a new contract arrangement with Cefas. Only 0.5% of the biotoxin samples, 0.7% of the water samples and 2.1% of E. coli samples were rejected as unsuitable for analysis on arrival at the laboratories. All chemical contaminants samples were suitable. All analyses followed the approved methods layed out in EU legislation and specified by FSS for the purpose of this programme. All methods were accredited to ISO17025:2005 standards at the testing laboratories. Amnesic shellfish poisoning toxins (ASP) were monitored in 794 samples, lipophilic toxins (LT) in 1,858 samples and paralytic shellfish poisoning toxins (PSP) in 1,161 samples. 1,951 samples were tested for E. coli, 20 for heavy metals (lead, cadmium and mercury), 28 for PAHs and 13 for dioxins and PCBs. All results were reported to FSS' specifications and met the required FSS turnaround times. Specifically: • 96.5% of all toxin results were reported within 1 working day of sample eceipt, 99.9% within 2 working days; • 100% of phytoplankton results were reported within 3 days of sample receipt; • 100% of E. coli actionable results ('outwith') were reported within 3 working days of onset of analysis; • 100% of E. coli non-actionable results were reported within 5 working days of onset of analysis; • Chemical contaminant report produced by end May 2018. The results of the monitoring programme are presented in each section of this report. In summary: • 254 samples breached the maximum permitted limits (MPL) for lipophilic toxins (OA/DTX/PTX group only) (see section 1.2); • 21 samples breached the MPL for PSP toxins (see section 1.3); • No sample breached the MPL for ASP toxins (see section 1.4); • Outwith E. coli results were reported in 6% of the 1,946 analyses undertaken (see Table 19 for details); • All chemical contaminants results were below the regulatory maximum limits (see section 3).

<b><i>Background:</i></b> DataSHIELD (Data Aggregation Through Anonymous Summary-statistics from Harmonised Individual levEL Databases) has been proposed to facilitate the co-analysis of individual-level data from multiple studies without physically sharing the data. In a previous paper, we investigated whether DataSHIELD could protect participant confidentiality in accordance with UK law. In this follow-up paper, we investigate whether DataSHIELD addresses a broader range of ethics-related data-sharing concerns. <b><i>Methods:</i></b> Ethics-related data-sharing concerns of Institutional Review Boards, ethics experts, international research consortia and research participants were identified through a literature search and systematically examined at a multidisciplinary workshop to determine whether DataSHIELD proposes mechanisms which can address these concerns. <b><i>Results:</i></b> DataSHIELD addresses several ethics-related data-sharing concerns related to privacy, confidentiality, and the protection of the research participant's rights while sharing data and after the data have been shared. The data remain entirely under the direct management of the study that collected them. Data processing commands are strictly supervised, and the data are queried in a protected environment. Issues related to the return of individual research results when data are shared are eliminated; the responsibility for return remains at the study of origin. <b><i>Conclusion:</i></b> DataSHIELD can provide an innovative and robust solution for addressing commonly encountered ethics-related data-sharing concerns.