Delivering Justice in the Mail: 6 Postcards on the Dreyfus Affair

Essay on postcards related to the Dreyfus Affair

Analytical and Experimental Methods for Studying Novel Cavity Geometries in Quantum Dot Mode Locked Lasers

In this dissertation, the insights provided using analytical methods to predict and refine Quantum Dot Mode Locked Lasers (QDMLLs) for use in multiple applications are explored. Experimental investigation guided by theory greatly reduces the number of iterations to find solutions to technical problems. The fitness of the theory and methods used for prediction of QDMLL operation are demonstrated. Experimental cases for QDMLLs in high temperature and radioactive environments are presented. Further avenues of pursuit for achieving high repetition rates in optical sources are also proposed

Measured impact of crooked traceroute

Data collected using traceroute-based algorithms underpins research into the Internet’s router-level topology, though it is possible to infer false links from this data. One source of false inference is the combination of per-flow load-balancing, in which more than one path is active from a given source to destination, and classic traceroute, which varies the UDP destination port number or ICMP checksum of successive probe packets, which can cause per-flow load-balancers to treat successive packets as distinct flows and forward them along different paths. Consequently, successive probe packets can solicit responses from unconnected routers, leading to the inference of false links. This paper examines the inaccuracies induced from such false inferences, both on macroscopic and ISP topology mapping. We collected macroscopic topology data to 365k destinations, with techniques that both do and do not try to capture load balancing phenomena.We then use alias resolution techniques to infer if a measurement artifact of classic traceroute induces a false router-level link. This technique detected that 2.71% and 0.76% of the links in our UDP and ICMP graphs were falsely inferred due to the presence of load-balancing. We conclude that most per-flow load-balancing does not induce false links when macroscopic topology is inferred using classic traceroute. The effect of false links on ISP topology mapping is possibly much worse, because the degrees of a tier-1 ISP’s routers derived from classic traceroute were inflated by a median factor of 2.9 as compared to those inferred with Paris traceroute

Law, Politics, and Political Discourse in Sixteenth-Century Manorial Norfolk

This thesis interrogates the form and structure of the principle texts produced within the English legal system in the late sixteenth century. It examines the instruments of litigation in the sixteenth-century Duchy Chamber and Star Chamber - their bills of information and complaint, answers, demurrers, rejoinders, interrogatories, examinations and depositions - in order to demonstrate that they were structured according to an essentially Roman theory of forensic rhetoric. This forensic framework, it is argued, is evident in legal texts from the North Norfolk Manor of Gimingham. The thesis demonstrates how this classical inheritance is indicative of the influence of Renaissance thought and Humanism upon English law and illustrates one of the key means by which English law and English legal culture developed in the late sixteenth-century. This thesis makes an important critical methodological contribution to the historiography of social history. Methodologically, the thesis has been deeply influenced by the analytical concerns of intellectual history, particularly those of the Cambridge School of intellectual historians, but retained an evidentiary base that is almost exclusively a province social historians. This is unique in the scholarship. It writes a history of legal and political culture from the ground up, in order to excavate a larger context within which we might place individuals within the mass of ordinary people and thereby obtain a greater grasp the scope of early modern politics and civil society. This is demonstrated through the analysis of Gimingham’s legal and political culture, excavated through an examination of its litigation

multiplestressR: An R package to analyse factorial multiple stressor data using the additive and multiplicative null models

Globally, ecosystems are being affected by multiple simultaneous stressors (also termed drivers, factors, or perturbations). While the effects of single stressors are becoming increasingly well understood, there remains substantial uncertainty regarding how multiple stressors may interact to affect ecosystems. Accordingly, there is substantial interest in documenting how stressors combine to impact individuals through to entire communities. Indeed, understanding how stressors interact represents one of the grand challenges currently facing ecologists and conservationists. Popular methods used to classify stressor interactions comprise multiple steps, including complex mathematical equations. Accordingly, there is the potential for errors to occur at multiple points, any of which can result in erroneous conclusions being drawn. Furthermore, there are frequently minor methodological differences between studies which may limit, or even prevent, direct comparisons of their results from being made. Here, we introduce the multiplestressR R package, a statistical tool which addresses the above issues. The package allows researchers to easily conduct a rigorous analysis of their multiple stressor data and provides results which are simple to interpret. The multiplestressR package can implement either the additive or multiplicative null model using iterations of these tools which are commonplace within multiple stressor ecology. The multiplestressR package can classify interactions as being synergistic, antagonistic, reversal, or null and requires minimal experience in either R or statistics to implement. Additionally, we provide example R code which can be easily modified to analysis any given factorial multiple stressor dataset. Indeed, widespread use of this software will allow for an easier and more robust comparison of results. Ultimately, we hope that the multiplestressR package will provide a stronger understanding of how stressors combine to affect individuals, populations, communities, and ecosystems

Multivariate geometric anisotropic Cox processes

This paper introduces a new modeling and inference framework for multivariate and anisotropic point processes. Building on recent innovations in multivariate spatial statistics, we propose a new family of multivariate anisotropic random fields, and from them a family of anisotropic point processes. We give conditions that make the proposed models valid. We also propose a Palm likelihood-based inference method for this type of point process, circumventing issues of likelihood tractability. Finally we illustrate the utility of the proposed modeling framework by analyzing spatial ecological observations of plants and trees in the Barro Colorado Island data

High diversity of microplankton surrounds deep-water coral reef in the Norwegian Sea

Coral reefs that exist in the depths of the oceans are surrounded by Eukarya, Archaea and bacterial communities that may play an important role in the nutrition and health of the reef. The first interdomain community structure of planktonic organisms in seawater from a deep-water coral reef is described. Community profiling and analysis of ribosomal RNA gene sequences from a coral reef system at 350 m depth in the Norwegian Sea revealed a rich diversity of Eukarya and Bacteria and a moderate diversity of Archaea. Most sequences affiliated with marine microplankton from deep-sea to cold-surface regions, with many sequences being similar to those described in studies of mesopelagic and oxygen minimum zones. Dominant phylotypes belonged to the Alveolata (group I, II, dinoflagellates), Stramenopiles (silicoflagellates), Alphaproteobacteria (Pelagibacter ubique), Gammaproteobacteria (ARCTIC96BD-19), Bacteroidetes (Flavobacteria) and mesophilic Crenarchaeota (Nitrosopumilus maritimus). Several rare and novel members of the community fell into distinct phylogenetic groups. The inferred function of dominant community members suggested autotrophs that utilise light, ammonium or sulphide, and lifestyles based on host associations. The high diversity reflected a microplankton community structure, which is significantly different from that of microplankton collected at the same depth at a pelagic station away from reefs

A user-friendly guide to using distance measures to compare time series in ecology

Time series are a critical component of ecological analysis, used to track changes in biotic and abiotic variables. Information can be extracted from the properties of time series for tasks such as classification (e.g., assigning species to individual bird calls); clustering (e.g., clustering similar responses in population dynamics to abrupt changes in the environment or management interventions); prediction (e.g., accuracy of model predictions to original time series data); and anomaly detection (e.g., detecting possible catastrophic events from population time series). These common tasks in ecological research all rely on the notion of (dis-) similarity, which can be determined using distance measures. A plethora of distance measures have been described, predominantly in the computer and information sciences, but many have not been introduced to ecologists. Furthermore, little is known about how to select appropriate distance measures for time-series-related tasks. Therefore, many potential applications remain unexplored. Here, we describe 16 properties of distance measures that are likely to be of importance to a variety of ecological questions involving time series. We then test 42 distance measures for each property and use the results to develop an objective method to select appropriate distance measures for any task and ecological dataset. We demonstrate our selection method by applying it to a set of real-world data on breeding bird populations in the UK and discuss other potential applications for distance measures, along with associated technical issues common in ecology. Our real-world population trends exhibit a common challenge for time series comparisons: a high level of stochasticity. We demonstrate two different ways of overcoming this challenge, first by selecting distance measures with properties that make them well suited to comparing noisy time series and second by applying a smoothing algorithm before selecting appropriate distance measures. In both cases, the distance measures chosen through our selection method are not only fit-for-purpose but are consistent in their rankings of the population trends. The results of our study should lead to an improved understanding of, and greater scope for, the use of distance measures for comparing ecological time series and help us answer new ecological questions