Autonomous monitoring of cliff nesting seabirds using computer vision

In this paper we describe a proposed system for automatic visual monitoring of seabird populations. Image sequences of cliff face nesting sites are captured using time-lapse digital photography. We are developing image processing software which is designed to automatically interpret these images, determine the number of birds present, and monitor activity. We focus primarily on the the development of low-level image processing techniques to support this goal. We first describe our existing work in video processing, and show how it is suitable for this problem domain. Image samples from a particular nest site are presented, and used to describe the associated challenges. We conclude by showing how we intend to develop our work to construct a distributed system capable of simultaneously monitoring a number of sites in the same locality

Automated visual surveillance of a population of nesting seabirds

Seabird populations are a valuable and accessible indicator of marine health: population changes have been linked with fish stock levels, climate change, and pollution. Understanding the development of particular colonies requires detailed data, but manual collection methods are labour intensive and error prone. Our work is concerned with development of computer vision algorithms to support autonomous visual monitoring of cliff-nesting nesting seabirds, and collection of behavioural data on a scale not feasible using manual methods. This work has been conducted at the University of Lincoln (UK), in collaboration with the Centre for Computational Ecology and Environmental Science (CEES) at Microsoft Research Cambridge. Our work has been ongoing for around 12 months, and focussed on robust image processing techniques capable of detecting and localising individual birds in image and video data. In our case, we are using data captured from a population of Common Guillemots (Uria aalge) resident on Skomer Island (UK) during the summer of 2010. This work represents a unique adaptation of computer vision technology, and we present a discussion of current and future technical challenges, processing techniques which we have developed, and some preliminary evaluation and results. In particular, we consider techniques based on feature based detection of birds and their body parts using gradient image features

Automatic nesting seabird detection based on boosted HOG-LBP descriptors

Seabird populations are considered an important and accessible indicator of the health of marine environments: variations have been linked with climate change and pollution 1. However, manual monitoring of large populations is labour-intensive, and requires significant investment of time and effort. In this paper, we propose a novel detection system for monitoring a specific population of Common Guillemots on Skomer Island, West Wales (UK). We incorporate two types of features, Histograms of Oriented Gradients (HOG) and Local Binary Pattern (LBP), to capture the edge/local shape information and the texture information of nesting seabirds. Optimal features are selected from a large HOG-LBP feature pool by boosting techniques, to calculate a compact representation suitable for the SVM classifier. A comparative study of two kinds of detectors, i.e., whole-body detector, head-beak detector, and their fusion is presented. When the proposed method is applied to the seabird detection, consistent and promising results are achieved. © 2011 IEEE

Cancer-Associated Fibroblast Mediated Inhibition of CD8+ Cytotoxic T Cell Accumulation in Tumours: Mechanisms and Therapeutic Opportunities

The tumour microenvironment (TME) is the complex environment in which various non-cancerous stromal cell populations co-exist, co-evolve and interact with tumour cells, having a profound impact on the progression of solid tumours. The TME is comprised of various extracellular matrix (ECM) proteins in addition to a variety of immune and stromal cells. These include tumour-associated macrophages, regulatory T cells (Tregs), myeloid-derived suppressor cells, as well as endothelial cells, pericytes and cancer-associated fibroblasts (CAFs). CAFs are the most abundant stromal cell population in many tumours and support cancer progression, metastasis and resistance to therapies through bidirectional signalling with both tumour cells and other cells within the TME. More recently, CAFs have been shown to also affect the anti-tumour immune response through direct and indirect interactions with immune cells. In this review, we specifically focus on the interactions between CAFs and cytotoxic CD8+ T cells, and on how these interactions affect T cell recruitment, infiltration and function in the tumour. We additionally provide insight into the therapeutic implications of targeting these interactions, particularly in the context of cancer immunotherapy.</jats:p

An Exploration of the Potential for Re-distributed Manufacturing to Contribute to a Sustainable , Resilient City

Re-distributed manufacturing (RDM), broadly described as manufacturing done at a smaller-scale and locally, could be beneficial to business and urban society through creating jobs, reducing the environmental impacts of production, and improving resilience to future disturbances. Consideration of RDM within a city-region requires the consideration of a wide range of issues – societal, technical, economic and environmental. This paper presents the results of a study into the potential for RDM to contribute to a sustainable, resilient city in the face of a range of expected future disturbances on the city and on manufacturing sectors. The study took an integrated assessment approach which incorporated the development of a conceptual framework; a ‘strawman’ causal loop diagram which was reviewed by participants in a workshop; and a stock and flow system dynamics model that represents our understanding about the structure and behaviour of urban manufacturing. Several key themes emerged: similarities between RDM and traditional manufacturing, availability of physical space for RDM to be done, achieving urban resilience through RDM by enabling responsiveness to disturbances, changes in environmental impacts from production, additions or losses in jobs, the competitiveness of local manufacturing, and skills and innovation for RDM technologies. Further work is recommended

Getting older and living longer with HIV: Findings from a pilot study conducted in Newham

Presentation given at UEL Research and Knowledge Exchange Conference 2012, held at the University of East London on 3 May 2012

Characterization of CMOS sensors for particle physics applications

This thesis summarizes work on the development of silicon sensor technologies for use in high energy physics experiments. This work has been focused on the characterization of passive strip sensors for hybrid devices as well as two novel monolithic active pixel sensors (MAPS) in the TowerJazz 180 nm CMOS imaging sensor process, MALTA and DECAL, for experiments at particle colliders. The MALTA sensor is part of a development towards a CMOS sensor based vertex detector system for use as a further upgrade by the ATLAS experiment, and the DECAL device is a more generic development suitable for use at either e$^+$e$^−$ or hadron colliders as an ultra high granularity electromagnetic calorimeter. The work has served to demonstrate the performance and identify shortcomings of the latest versions of these devices in the context of high energy particle physics experiments. Passive strip sensors for hybrids in the ATLAS Inner Tracker (ITk) were irradiated at the MC40 cyclotron in Birmingham and characterized. While the characterization results with devices irradiated at Birmingham were not conclusive, the sensor performance demonstrated at other facilities is within specifications, and the work has served as part of the commissioning of the irradiation facilities at Birmingham for sensor Quality Assurance during pre-production and production, and has highlighted issues to be resolved. Both monolithic pixel sensors, DECAL and MALTA, are the subject of ongoing developments to be included in future experiments. The very latest versions of MALTA were shown to be fully efficient after irradiation to 1×10$^{15}$ n$_{eq}$/cm$^2$ and nearly fully efficient at 2×$^{15}$ n$_{eq}$/cm$^2$, a significant improvement after having 78 % efficiency at 1×$^{15}$ n$_{eq}$/cm$^2$ in the original version of the device. Simulation for inclusion of calorimeter constructed from monolithic active pixel sensors (MAPS) in experiments shows promise to improve particle reconstruction with Particle Flow techniques. Measurements with the DECAL sensors have demonstrated the counting logic and digital configuration necessary for the proposed application in calorimetry. While both DECAL and MALTA would have to be subject to further design iteration for inclusion in experiments to improve the front-end, sensor, and readout characteristics, the demonstrated improvements show there is a clear path towards their final implementation

Remote Exploration: Understanding Martian Surface Processes

Earth and Mars share many similar physical features, including canyons, valleys, craters, volcanoes, ice, and gullies. My research focuses on two distinct projects. The first concentrates on the formation of gullies, which are channel networks generally formed on mid-latitude crater walls on Mars. Debated gully-forming processes include the melting of snowpacks, sublimation of accumulated carbon dioxide frost, melting of snow-rich dusty mantle material, and groundwater flows. Using High Resolution Imaging Science Experiment (HiRISE) images of gullies and working with Digital Elevation Models (DEMs) in ENVI, we are able to perform detailed studies of gully morphology, including volume calculations using slope, distance, and elevation. The second topic focuses on determining the mineral composition of Martian rocks. Using Raman spectroscopy, I am testing the mineral composition of igneous rocks and recording spectral peaks for key rock-forming minerals, such as olivine, plagioclase, potassium feldspar, quartz, and pyroxene. Raman spectroscopy is an inelastic light scattering technique that measures the change in energy of a photon. These samples and spectra will be used to help create an automated computer mineral identification algorithm that might be used on future Mars rover missions. Both projects contribute to scientific studies of remote exploration and understanding of the Martian surface

Panel #2: The Maine-Missouri Crisis and the Politics of Slavery

A panel that included three presentations: African Americans and the Political Consequences of Maine Statehood, Mary T. Freeman Doughface Pioneer: John Holmes of Maine, 1773-1843, Matthew Mason Fire Bell in the Night: The Establishment of a Slave Society in Jefferson\u27s Purchase, Diane Mutti Burk