Hyperferritinemia -cataract syndrome: Long-term ophthalmic observations in an Italian family

Background Hyperferritinemia-cataract syndrome (HCS) is a rare Mendelian condition characterized by bilateral cataract and high levels of serum ferritin in the absence of iron overload. Methods HCS was diagnosed in three adult siblings. In two of them it was possible to assess lens changes initially in 1995 and again in 2013. Serum ferritin, iron, transferrin concentrations and transferrin saturation percentage were also measured, and the Iron Responsive Element (IRE) region of the L-ferritin gene (FTL) was studied. Results Serum ferritin concentrations were considerably elevated while serum iron, transferrin and transferrin saturation levels were within the normal range in each sibling. Cataract changes in our patients were consistent with those previously reported in the literature. Progression of the cataract, an aspect of few studies in this syndrome, appeared to be quite limited in extent. The heterozygous +32G to T (-168G>T) substitution in the IRE of the FTL gene was detected in this family. Conclusions Ophthalmic and biochemical studies together with genetic testing confirmed HCS in three family members. Although the disorder has been extensively described in recent years, little is known regarding cataract evolution over time. In our cases, lens evaluations encompassed many years, identified bilateral cataract of typical morphology and supported the hypothesis that this unique clinical feature of the disease tends to be slowly progressive in nature, at least in adults.

Instrument for simultaneous assessment of tear film surface quality and subjective vision

To develop and test a custom-built instrument to simultaneously assess tear film surface quality (TFSQ) and subjective vision score (SVS).

Open source computer-vision based guidance system for UAVs on-board decision making

The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.

A Distributed Robotic Vision Service

Robotic vision is limited by line of sight and onboard camera capabilities. Robots can acquire video or images from remote cameras, but processing additional data has a computational burden. This paper applies the Distributed Robotic Vision Service, DRVS, to robot path planning using data outside line-of-sight of the robot. DRVS implements a distributed visual object detection service to distributes the computation to remote camera nodes with processing capabilities. Robots request task-specific object detection from DRVS by specifying a geographic region of interest and object type. The remote camera nodes perform the visual processing and send the high-level object information to the robot. Additionally, DRVS relieves robots of sensor discovery by dynamically distributing object detection requests to remote camera nodes. Tested over two different indoor path planning tasks DRVS showed dramatic reduction in mobile robot compute load and wireless network utilization.

Conditions of Compromise and Failure (The Dickensian Aspect)

‘Conditions of Compromise and Failure (The Dickensian Aspect)' acts as a re-enactment of the common trope of television detective dramas. A result of the artist’s repeated immersions in the television program ‘The Wire’, the work forms a node-map of all the named characters featured on the show. While each coloured thread represents and connects together the Byzantine narrative between all of the characters, the sheer mass of connections obfuscates any clear reading at all.

Deploying speaker verification techniques to vision-based RPA detect and avoid

Detect and Avoid (DAA) technology is widely acknowledged as a critical enabler for unsegregated Remote Piloted Aircraft (RPA) operations, particularly Beyond Visual Line of Sight (BVLOS). Image-based DAA, in the visible spectrum, is a promising technological option for addressing the challenges DAA presents. Two impediments to progress for this approach are the scarcity of available video footage to train and test algorithms, in conjunction with testing regimes and specifications which facilitate repeatable, statistically valid, performance assessment. This paper includes three key contributions undertaken to address these impediments. In the first instance, we detail our progress towards the creation of a large hybrid collision and near-collision encounter database. Second, we explore the suitability of techniques employed by the biometric research community (Speaker Verification and Language Identification), for DAA performance optimisation and assessment. These techniques include Detection Error Trade-off (DET) curves, Equal Error Rates (EER), and the Detection Cost Function (DCF). Finally, the hybrid database and the speech-based techniques are combined and employed in the assessment of a contemporary, image based DAA system. This system includes stabilisation, morphological filtering and a Hidden Markov Model (HMM) temporal filter.