Ku-band interferometry

Construction of Ku band radio interferometer and preliminary observation

Evolution of Network Architecture in a Granular Material Under Compression

As a granular material is compressed, the particles and forces within the system arrange to form complex and heterogeneous collective structures. Force chains are a prime example of such structures, and are thought to constrain bulk properties such as mechanical stability and acoustic transmission. However, capturing and characterizing the evolving nature of the intrinsic inhomogeneity and mesoscale architecture of granular systems can be challenging. A growing body of work has shown that graph theoretic approaches may provide a useful foundation for tackling these problems. Here, we extend the current approaches by utilizing multilayer networks as a framework for directly quantifying the progression of mesoscale architecture in a compressed granular system. We examine a quasi-two-dimensional aggregate of photoelastic disks, subject to biaxial compressions through a series of small, quasistatic steps. Treating particles as network nodes and interparticle forces as network edges, we construct a multilayer network for the system by linking together the series of static force networks that exist at each strain step. We then extract the inherent mesoscale structure from the system by using a generalization of community detection methods to multilayer networks, and we define quantitative measures to characterize the changes in this structure throughout the compression process. We separately consider the network of normal and tangential forces, and find that they display a different progression throughout compression. To test the sensitivity of the network model to particle properties, we examine whether the method can distinguish a subsystem of low-friction particles within a bath of higher-friction particles. We find that this can be achieved by considering the network of tangential forces, and that the community structure is better able to separate the subsystem than a purely local measure of interparticle forces alone. The results discussed throughout this study suggest that these network science techniques may provide a direct way to compare and classify data from systems under different external conditions or with different physical makeup

K-Space at TRECVID 2008

In this paper we describe K-Space’s participation in TRECVid 2008 in the interactive search task. For 2008 the K-Space group performed one of the largest interactive video information retrieval experiments conducted in a laboratory setting. We had three institutions participating in a multi-site multi-system experiment. In total 36 users participated, 12 each from Dublin City University (DCU, Ireland), University of Glasgow (GU, Scotland) and Centrum Wiskunde and Informatica (CWI, the Netherlands). Three user interfaces were developed, two from DCU which were also used in 2007 as well as an interface from GU. All interfaces leveraged the same search service. Using a latin squares arrangement, each user conducted 12 topics, leading in total to 6 runs per site, 18 in total. We officially submitted for evaluation 3 of these runs to NIST with an additional expert run using a 4th system. Our submitted runs performed around the median. In this paper we will present an overview of the search system utilized, the experimental setup and a preliminary analysis of our results

Learning to Detect Objects from Eye-Tracking Data

One of the bottlenecks in computer vision, especially in object detection, is the need for a large amount of training data. Typically, this is acquired by manually annotating images by hand. In this study, we explore the possibility of using eye-trackers to provide training data for supervised machine learning. We have created a new large scale eye-tracking dataset, collecting fixation data for 6270 images from the Pascal VOC 2012 database. This represents 10 of the 20 classes included in the Pascal database. Each image was viewed by 5 observers, and a total of over 178k fixations have been collected. While previous attempts at using fixation data in computer vision were based on a free-viewing paradigm, we used a visual search task in order to increase the proportion of fixations on the target object. Furthermore, we divided the dataset into five pairs of semantically similar classes (cat/dog, bicycle/motorbike, horse/cow, boat/aeroplane and sofa/diningtable), with the observer having to decide which class each image belonged to. This kept the observer's task simple, while decreasing the chance of them using the scene gist to identify the target parafoveally. In order to alleviate the central bias in scene viewing, the images were presented to the observers with a random offset. The goal of our project is to use the eye-tracking information in order to detect and localise the attended objects. Our model so far, based on features representing the location of the fixations and an appearance model of the attended regions, can successfully predict the location of the target objects in over half of images

Dietary Habits, Menstrual Health, Body Composition, and Eating Disorder Risk Among Collegiate Volleyball Players: A Descriptive Study

Volleyball is typically considered a non-aesthetic sport. However, the revealing nature of volleyball uniforms may place additional pressure on female volleyball players to be thin and increase the risk of disordered eating. The purpose of this study was to provide descriptive data concerning the body composition, nutritional habits, eating disorder risk, and menstrual health of collegiate volleyball players. Female collegiate volleyball players (N = 14) completed a 7-day food record, menstrual health questionnaire, and EAT-26 survey. Participant body composition was determined using a 3 site skinfold test and the Bod Pod®. Half (50%) of participants were deemed “At-Risk” (AR) for disordered eating according to EAT-26 results, while the other half were consider “Not At- Risk” (NR). Participants consumed inadequate calories (1928 + 476) meeting only 69.35% of their predicted energy expenditure (2780.66 + 148.88). Additionally, all participants were below the recommended CHO intake range of 6-10g/kg/day for athletes (3.49 + 0.89g/CHO/kg/day) and the recommended intake range of 1.2-1.7 g/kg/day for protein for athletes (1.17 + 0.35). Body fat percentage using the Bod Pod® (22.76 + 6.25%) was similar to values reported by other studies. Seven of the participants were currently using oral contraceptives (OC). Menstrual dysfunction was reported by 3 participants not using OC. Of those using OC, 3 reported irregular menses as the reason for taking OC. No significant difference existed in macronutrient and energy intake, prevalence of menstrual dysfunction, or body composition between AR and NR groups. In conclusion, the current study suggests that collegiate female volleyball players’ diets tend to be inadequate in calories, protein, and carbohydrates, placing them at risk for subsequent medical ailments including menstrual dysfunction

Computer supported argument maps as a policy memory

This paper investigates to what extent Computer Supported Argument Visualisation can be designed to encourage debate and deliberation by citizens on public issues. Such argument maps use icons and arrows to represent the structure of a series of related viewpoints, reducing the amount of text necessary to convey the ideas, thereby clarifying the issue under consideration. Argument maps have the potential to provide a readily accessible medium by which citizens can follow and join in public debates on policy issues. In this paper we describe our approach, type of maps we have chosen to use and then demonstrate the potential of a collection of maps to form a ‘policy memory’ to support policy development. Our case study is the development of the ‘Smoking in Public Places’ policy in the Scottish Parliament. Our overall aim is to engage citizens in democratic decision-making leading to better policy-making and a more engaged citizenry

Transient hyperckemia in the setting of neuromyelitis optica (NMO)

INTRODUCTION: Neuromyelitis optica (NMO) is characterized by inflammatory demyelinating lesions of the spinal cord and optic nerves from an autoimmune response against water channel aquaporin-4 (AQP4). We report 2 patients with transient hyperCKemia associated with NMO suggesting possible skeletal muscle damage. METHODS: Patient 1 was a 72-year-old man who presented with muscle soreness and elevated serum creatine kinase (CK) preceding an initial attack of NMO. Patient 2 was a 25-year-old woman with an established diagnosis of NMO who presented with diffuse myalgias, proximal upper extremity weakness, and hyperCKemia. Muscle biopsies were obtained for histopathologic evaluation, protein gel electrophoresis, immunofluorescence, and complement staining. RESULTS: In both patients the muscle showed only mild variation in fiber diameter. There were no inflammatory changes or muscle fiber necrosis, though there was reduced AQP4 expression and deposition of activated complement. CONCLUSIONS: Complement-mediated sarcolemmal injury may lead to hyperCKemia in NMO