Structure–Function Relationship of Retinal Ganglion Cells in Multiple Sclerosis

The retinal ganglion cells (RGC) may be considered an easily accessible pathophysiological site of degenerative processes in neurological diseases, such as the RGC damage detectable in multiple sclerosis (MS) patients with (HON) and without a history of optic neuritis (NON). We aimed to assess and interrelate RGC functional and structural damage in different retinal layers and retinal sites. We included 12 NON patients, 11 HON patients and 14 healthy controls for cross-sectional multifocal pattern electroretinography (mfPERG) and optical coherence tomography (OCT) measurements. Amplitude and peak times of the mfPERG were assessed. Macula and disc OCT scans were acquired to determine macular retinal layer and peripapillary retinal nerve fiber layer (pRNFL) thickness. In both HON and NON patients the foveal N2 amplitude of the mfPERG was reduced compared to controls. The parafoveal P1 peak time was significantly reduced in HON only. For OCT, parafoveal (pfGCL) and perifoveal (pGCL) ganglion cell layer thicknesses were decreased in HON vs. controls, while pRNFL in the papillomacular bundle sector (PMB) showed reductions in both NON and HON. As the mfPERG derived N2 originates from RGC axons, these findings suggest foveal axonal dysfunction not only in HON, but also in NON patients.     

CFD simulation of the effect of rain on the performance of horizontal wind turbines

Wind turbine power output is influenced by environmental conditions, including rain. Therefore, a better understanding of the effect of rain on the performance of wind turbines is necessary. Our coupled Lagrangian‐Eulerian multiphase computational fluid dynamics model was modified to more accurately simulate the momentum transfer during water film formation on the airfoils of a horizontal‐axis turbine and the performance loss caused by the rainwater film on the National Renewable Energy Laboratory (NREL) turbine performance. To obtain three‐dimensional numerical simulation of the wind turbine in manageable computational time, simplifying assumptions were made and the validity of these assumptions was verified by simulating the flow over the S809 airfoil of the NREL turbine. In a dry environment, simulation of turbine power output agreed well with NREL experimental data. Our multiphase model showed that the rain film accumulation and flow on the surface of the turbine airfoil reduces the power output of the turbine. © 2017 American Institute of Chemical Engineers AIChE J, 63: 5375–5383, 2017     

Passively recognising human activities through lifelogging

Lifelogging is the process of automatically recording aspects of one’s life in digital form. This includes visual lifelogging using wearable cameras such as the SenseCam and in recent years many interesting applications for this have emerged and are being actively researched. One of the most interesting of these, and possibly the most far-reaching, is using visual lifelogs as a memory prosthesis but there are also applications in job-specific activity recording, general lifestyle analysis and market analysis.In this work we describe a technique which allowed us to develop automatic classifiers for visual lifelogs to infer different lifestyle traits or characteristics. Their accuracy was validated on a set of 95 k manually annotated images and through one-on-one interviews with those who gathered the images. These automatic classifiers were then applied to a collection of over 3 million lifelog images collected by 33 individuals sporadically over a period of 3.5 years. From this collection we present a number of anecdotal observations to demonstrate the future potential of lifelogging to capture human behaviour. These anecdotes include: the eating habits of office workers; to the amount of time researchers spend outdoors through the year; to the observation that retired people in our study appear to spend quite a bit of time indoors eating with friends. We believe this work demonstrates the potential of lifelogging techniques to assist behavioural scientists in future.     

Everyday concept detection in visual lifelogs: validation,relationships and trends

The Microsoft SenseCam is a small lightweight wearable camera used to passively capture photos and other sensor readings from a user’s day-to-day activities. It captures on average 3,000 images in a typical day, equating to almost 1 million images per year. It can be used to aid memory by creating a personal multimedia lifelog, or visual recording of the wearer’s life. However the sheer volume of image data captured within a visual lifelog creates a number of challenges, particularly for locating relevant content. Within this work, we explore the applicability of semantic concept detection, a method often used within video retrieval, on the domain of visual lifelogs. Our concept detector models the correspondence between low-level visual features and high-level semantic concepts (such as indoors, outdoors, people, buildings, etc.) using supervised machine learning. By doing so it determines the probability of a concept’s presence. We apply detection of 27 everyday semantic concepts on a lifelog collection composed of 257,518 SenseCam images from 5 users. The results were evaluated on a subset of 95,907 images, to determine the accuracy for detection of each semantic concept. We conducted further analysis on the temporal consistency, co-occurance and relationships within the detected concepts to more extensively investigate the robustness of the detectors within this domain.     

The adsorption of bovine serum albumin by activated sludge

The rapid removal, from suspension, of between 2–% of bovine serum albumin (BSA) by BSA acclimated activated sludge was attributed to adsorption. The extent of adsorption varied with the substrate to biomass (s/b) ratio. The concentration of BSA adsorped was influenced by both the concentration of BSA and the concentration of activated sludge. The experimental data did not conform to the calssical adsorption equations of Langmuir (J. Am. chem. Soc.40, 1361–1403, 918) or Freundlich (Colloid and Capillary Chemistry, Methuen, London, 1926) but to a newly developed equation, the activated sludge adsorption equation (ASAE). This new equation was tested and proven by experimental data and by data obtained independently by Banerji et al. (J. Wat. Pollut. Control Fed.40, 161–173, 1968) who investigated starch removal by activated sludge. Following the development of the ASAE, it was found possible to express both the concentration of BSA adsorbed per unit weight activated sludge (m) and the concentration of BSA in equilibrium per unit weight activated sludge (C/b) as a function of the concentration of BSA added to the system per unit weight adsorbent (C_t). Thus adsorption could be expressed as a function of the substrate to biomass (s/b) ratio.     

Delineating the Tnt1 Insertion Landscape of the Model Legume Medicago truncatula cv. R108 at the Hi-C Resolution Using a Chromosome-Length Genome Assembly

Legumes are of great interest for sustainable agricultural production as they fix atmospheric nitrogen to improve the soil. Medicago truncatula is a well-established model legume, and extensive studies in fundamental molecular, physiological, and developmental biology have been undertaken to translate into trait improvements in economically important legume crops worldwide. However, M. truncatula reference genome was generated in the accession Jemalong A17, which is highly recalcitrant to transformation. M. truncatula R108 is more attractive for genetic studies due to its high transformation efficiency and Tnt1-insertion population resource for functional genomics. The need to perform accurate synteny analysis and comprehensive genome-scale comparisons necessitates a chromosome-length genome assembly for M. truncatula cv. R108. Here, we performed in situ Hi-C (48×) to anchor, order, orient scaffolds, and correct misjoins of contigs in a previously published genome assembly (R108 v1.0), resulting in an improved genome assembly containing eight chromosome-length scaffolds that span 97.62% of the sequenced bases in the input assembly. The long-range physical information data generated using Hi-C allowed us to obtain a chromosome-length ordering of the genome assembly, better validate previous draft misjoins, and provide further insights accurately predicting synteny between A17 and R108 regions corresponding to the known chromosome 4/8 translocation. Furthermore, mapping the Tnt1 insertion landscape on this reference assembly presents an important resource for M. truncatula functional genomics by supporting efficient mutant gene identification in Tnt1 insertion lines. Our data provide a much-needed foundational resource that supports functional and molecular research into the Leguminosae for sustainable agriculture and feeding the future.     

Magnesium alloy applications in automotive structures

The use of magnesium alloys in structural applications has great potential for the lightweighting of transportation vehicles. Research within the CAST Cooperative Research Centre has tackled some of the important issues related to the use of magnesium in structural applications. To this end, a new alloy with extrudability and properties similar to 6000 series aluminum alloys has been developed. Furthermore, a method of laser heating magnesium alloys before self-piercing riveting has enabled high-integrity joining between magnesium components or between magnesium and dissimilar metals. In this paper, new technologies and improved understanding of the deformation behavior of wrought magnesium alloys are discussed in light of key metallurgical features such as alloy composition, grain size, and work hardening rate. All are part of CAST Co-operative Research Centre.