Terentius Poeta

Edited volume, reassessing Terence as a playwright of its own right, containing cutting-edge contributions on textual criticism, edition, language, metre, and aesthetics of Terence.

From the sun to the Earth: The 13 May 2005 coronal mass ejection

We report the results of a multi-instrument, multi-technique, coordinated study of the solar eruptive event of 13 May 2005. We discuss the resultant Earth-directed (halo) coronal mass ejection (CME), and the effects on the terrestrial space environment and upper Earth atmosphere. The interplanetary CME (ICME) impacted the Earth’s magnetosphere and caused the most-intense geomagnetic storm of 2005 with a Disturbed Storm Time (Dst) index reaching −263 nT at its peak. The terrestrial environment responded to the storm on a global scale. We have combined observations and measurements from coronal and interplanetary remote-sensing instruments, interplanetary and near-Earth in-situ measurements, remote-sensing observations and in-situ measurements of the terrestrial magnetosphere and ionosphere, along with coronal and heliospheric modelling. These analyses are used to trace the origin, development, propagation, terrestrial impact, and subsequent consequences of this event to obtain the most comprehensive view of a geo-effective solar eruption to date. This particular event is also part of a NASA-sponsored Living With a Star (LWS) study and an on-going US NSF-sponsored Solar, Heliospheric, and INterplanetary Environment (SHINE) community investigation.

GIS in the cloud: implementing a web map service on Google App Engine

Many producers of geographic information are now disseminating their data using open web service protocols, notably those published by the Open Geospatial Consortium. There are many challenges inherent in running robust and reliable services at reasonable cost. Cloud computing provides a new kind of scalable infrastructure that could address many of these challenges. In this study we implement a Web Map Service for raster imagery within the Google App Engine environment. We discuss the challenges of developing GIS applications within this framework and the performance characteristics of the implementation. Results show that the application scales well to multiple simultaneous users and performance will be adequate for many applications, although concerns remain over issues such as latency spikes. We discuss the feasibility of implementing services within the free usage quotas of Google App Engine and the possibility of extending the approaches in this paper to other GIS applications.

In vitro fermentation of carbohydrates by porcine faecal inocula and their influence on Salmonella Typhimurium growth in batch culture systems

The aim of this study was to evaluate in vitro the influence of fermentable carbohydrates on the activity of porcine microbiota and survival of Salmonella Typhimurium in a batch culture system simulating the porcine hindgut. The carbohydrates tested were xylooligosaccharides, a mixture of fructooligosaccharides/inulin (FIN), fructooligosaccharides (FOS), gentiooligosaccharides (GEO) and lactulose (LAC). These ingredients stimulated the growth of selected Bifidobacterium and Lactobacillus species in pure cultures. In batch cultures, the carbohydrates influenced some fermentation parameters. For example, GEO and FIN significantly increased lactic acids compared with the control (no added carbohydrate). With the exception of LAC, the test carbohydrates increased the production of short-chain fatty acid (SCFA) and modified SCFA profiles. Quantitative analysis of bacterial populations by FISH revealed increased counts of the Bifidobacterium group compared with control and, with exception of FOS, increased Lactobacillus, Leuconostoc and Weissella spp. counts. Salmonella numbers were the lowest during the fermentation of LAC. This work has looked at carbohydrate metabolism by porcine microbiota in a pH-controlled batch fermentation system. It provides an initial model to analyse interactions with pathogens.

Preminger and Peckinpah: seeing and shaping widescreen worlds

This chapter develops a comparative analysis of sequences from the films of two directors who made eloquent use of widescreen formats but who seem to be in all other respects wholly contrasting figures. The article includes a historiographical element in grounding the argument in the critical history of widescreen aesthetics and the directors’ work. It moves from a close analysis of three sequences, and an exploration of strategies in the use of the widescreen frame, to broader questions of style and its interpretation, narration, point of view and epistemology. The article connects with other work on Preminger, and on the critical history of mise-en-scène, while extending this through the comparative analysis of two figures from different Hollywood contexts and characterised by very different approaches.

Proof of concept of automated mapping of weeds in arable fields

The project investigated whether it would be possible to remove the main technical hindrance to precision application of herbicides to arable crops in the UK, namely creating geo-referenced weed maps for each field. The ultimate goal is an information system so that agronomists and farmers can plan precision weed control and create spraying maps. The project focussed on black-grass in wheat, but research was also carried out on barley and beans and on wild-oats, barren brome, rye-grass, cleavers and thistles which form stable patches in arable fields. Farmers may also make special efforts to control them. Using cameras mounted on farm machinery, the project explored the feasibility of automating the process of mapping black-grass in fields. Geo-referenced images were captured from June to December 2009, using sprayers, a tractor, combine harvesters and on foot. Cameras were mounted on the sprayer boom, on windows or on top of tractor and combine cabs and images were captured with a range of vibration levels and at speeds up to 20 km h-1. For acceptability to farmers, it was important that every image containing black-grass was classified as containing black-grass; false negatives are highly undesirable. The software algorithms recorded no false negatives in sample images analysed to date, although some black-grass heads were unclassified and there were also false positives. The density of black-grass heads per unit area estimated by machine vision increased as a linear function of the actual density with a mean detection rate of 47% of black-grass heads in sample images at T3 within a density range of 13 to 1230 heads m-2. A final part of the project was to create geo-referenced weed maps using software written in previous HGCA-funded projects and two examples show that geo-location by machine vision compares well with manually-mapped weed patches. The consortium therefore demonstrated for the first time the feasibility of using a GPS-linked computer-controlled camera system mounted on farm machinery (tractor, sprayer or combine) to geo-reference black-grass in winter wheat between black-grass head emergence and seed shedding.

Final report on research project PS2010, proof of concept of automated mapping of weeds in arable fields

Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).

Ballet

The video Ballet engages with recent histories of rural filmmaking, linking everyday farming movements with the aesthetics of dance. Starting point for this new work is a series of archival films from the collection of the Museum of English Rural Life (MERL), which provide warnings of contagion and nuclear catastrophe, describing procedure and instruction in the case of emergency. These films present a unique vision of rural labour and collective staged action, where extras, rural background actors, are performing 'normality' prior to potential disruption of an imminent crisis. Szuper Gallery's video deconstructs the movements of extras in these rural propaganda films. It features a large cast of dancers and non-dancers in a spectacular rural setting performing a new choreography to a dramatic sound score.

Ballet

This solo exhibition featured Ballet, a filmed performance and video installation by Szuper Gallery and an installation of original archive films. Ballet engages with recent histories of rural filmmaking, with movement and dance, linking everyday farming movements with the aesthetics of dance. The starting point for this new work was a series of archival films from the MERL collection, which were made for British farmers as a means both for information and for propaganda, to provide warnings of contagion and nuclear catastrophe, describing procedure and instruction in the case of emergency. Gestural performances and movements of background actors observed in those films were re-scripted into a new choreography of movement for camera to form a playful assemblage.

Fast regridding of large, complex geospatial datasets

In the earth sciences, data are commonly cast on complex grids in order to model irregular domains such as coastlines, or to evenly distribute grid points over the globe. It is common for a scientist to wish to re-cast such data onto a grid that is more amenable to manipulation, visualization, or comparison with other data sources. The complexity of the grids presents a significant technical difficulty to the regridding process. In particular, the regridding of complex grids may suffer from severe performance issues, in the worst case scaling with the product of the sizes of the source and destination grids. We present a mechanism for the fast regridding of such datasets, based upon the construction of a spatial index that allows fast searching of the source grid. We discover that the most efficient spatial index under test (in terms of memory usage and query time) is a simple look-up table. A kd-tree implementation was found to be faster to build and to give similar query performance at the expense of a larger memory footprint. Using our approach, we demonstrate that regridding of complex data may proceed at speeds sufficient to permit regridding on-the-fly in an interactive visualization application, or in a Web Map Service implementation. For large datasets with complex grids the new mechanism is shown to significantly outperform algorithms used in many scientific visualization packages.

The Matrix

Review and critical reflection on 'The Matrix', in relation to questions of genre, aesthetics, representation, and cultural and industrial contexts.

Transformers

Review and critical reflection on 'Transformers' as an example of the contemporary blockbuster, exploring questions of genre, aesthetics, representation, and cultural and industrial contexts.