STORRE Community: This community contains the ePrints and eTheses produced by the Faculty's staff and students.

Molecular and functional characterization of a fads2 orthologue in the Amazonian teleost, Arapaima gigas

Sun, 01 Jan 2017 00:00:00 GMT

Title: Molecular and functional characterization of a fads2 orthologue in the Amazonian teleost, Arapaima gigas Authors: Lopes-Marques, Mónica; Ozório, Rodrigo; Amaral, Ricardo; Tocher, Douglas R; Monroig, Oscar; Costa, Castro Luıs Filipe Abstract: The Brazilian teleost Arapaima gigas is an iconic species of the Amazon. In recent years a significant effort has been put into the farming of arapaima to mitigate overfishing threats. However, little is known regarding the nutritional requirements of A. gigas in particular those for essential fatty acids including the long-chain polyunsaturated fatty acids (LC-PUFA) eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). The ability to biosynthesize LC-PUFA is dependent upon the gene repertoire of fatty acyl desaturases (Fads) and elongases (Elovl), as well as their fatty acid specificities. In the present study we characterized both molecularly and functionally an orthologue of the desaturase fatty acid desaturase 2 (fads2) from A. gigas. The isolated sequence displayed the typical desaturase features, a cytochrome b5-domain with the heme-binding motif, two transmembrane domains and three histidine-rich regions. Functional characterization of A. gigas fads2 showed that, similar to other teleosts, the A. gigas fads2 exhibited a predominant Δ6 activity complemented with some capacity for Δ8 desaturation. Given that A. gigas belongs to one of the oldest teleostei lineages, the Osteoglossomorpha, these findings offer a significant insight into the evolution LC-PUFA biosynthesis in teleosts.

Biologically Inspired Progressive Enhancement Target Detection from Heavy Cluttered SAR Images

Sat, 01 Oct 2016 00:00:00 GMT

Title: Biologically Inspired Progressive Enhancement Target Detection from Heavy Cluttered SAR Images Authors: Gao, Fei; Ma, Fei; Zhang, Yaotian; Wang, Jun; Sun, Jinping; Yang, Erfu; Hussain, Amir Abstract: High-resolution synthetic aperture radar (SAR) can provide a rich information source for target detection and greatly increase the types and number of target characteristics. How to efficiently extract the target of interest from large amounts of SAR images is the main research issue. Inspired by the biological visual systems, researchers have put forward a variety of biologically inspired visual models for target detection, such as classical saliency map and HMAX. But these methods only model the retina or visual cortex in the visual system, which limit their ability to extract and integrate targets characteristics; thus, their detection accuracy and efficiency can be easily disturbed in complex environment. Based on the analysis of retina and visual cortex in biological visual systems, a progressive enhancement detection method for SAR targets is proposed in this paper. The detection process is divided into RET, PVC, and AVC three stages which simulate the information processing chain of retina, primary and advanced visual cortex, respectively. RET stage is responsible for eliminating the redundant information of input SAR image, enhancing inputs’ features, and transforming them to excitation signals. PVC stage obtains primary features through the competition mechanism between the neurons and the combination of characteristics, and then completes the rough detection. In the AVC stage, the neurons with more receptive field compound more precise advanced features, completing the final fine detection. The experimental results obtained in this study show that the proposed approach has better detection results in comparison with the traditional methods in complex scenes.

A Neuro-Fuzzy Control System Based on Feature Extraction of Surface Electromyogram Signal for Solar-Powered Wheelchair

Sat, 01 Oct 2016 00:00:00 GMT

Title: A Neuro-Fuzzy Control System Based on Feature Extraction of Surface Electromyogram Signal for Solar-Powered Wheelchair Authors: Kaiser, M Shamim; Chowdhury, Zamshed Iqbal; Mamun, Shamim Al; Hussain, Amir; Mahmud, Mufti Abstract: This paper presents the design and implementation of a low-cost solar-powered wheelchair for physically challenged people. The signals necessary to maneuver the wheelchair are acquired from different muscles of the hand using surface electromyography (sEMG) technique. The raw sEMG signals are collected from the upper limb muscles which are then processed, characterized, and classified to extract necessary features for the generation of control signals to be used for the automated movement of the wheelchair. An artificial neural network-based classifier is constructed to classify the patterns and features extracted from the raw sEMG signals. The classification accuracy of the extracted parameters from the sEMG signals is found to be relatively high in comparison with the existing methods. The extracted parameters used to generate control signals that are then fed into a microcomputer-based control system (MiCS). A solar-powered wheelchair prototype is developed, and the above MiCS is introduced to control its maneuver using the sEMG signals. The prototype is then thoroughly tested with sEMG signals from patients of different age groups. Also, the life cycle cost analysis of the proposed wheelchair revealed that it is financially feasible and cost-effective.

Quantifying the roles of host movement and vector dispersal in the transmission of vector-borne diseases of livestock

Mon, 03 Apr 2017 00:00:00 GMT

Title: Quantifying the roles of host movement and vector dispersal in the transmission of vector-borne diseases of livestock Authors: Sumner, Tom; Orton, Richard; Green, Darren; Kao, Rowland R; Gubbins, Simon Abstract: The role of host movement in the spread of vector-borne diseases of livestock has been little studied. Here we develop a mathematical framework that allows us to disentangle and quantify the roles of vector dispersal and livestock movement in transmission between farms. We apply this framework to outbreaks of bluetongue virus (BTV) and Schmallenberg virus (SBV) in Great Britain, both of which are spread byCulicoidesbiting midges and have recently emerged in northern Europe. For BTV we estimate parameters by fitting the model to outbreak data using approximate Bayesian computation, while for SBV we use previously derived estimates. We find that around 90% of transmission of BTV between farms is a result of vector dispersal, while for SBV this proportion is 98%. This difference is a consequence of higher vector competence and shorter duration of viraemia for SBV compared with BTV. For both viruses we estimate that the mean number of secondary infections per infected farm is greater than one for vector dispersal, but below one for livestock movements. Although livestock movements account for a small proportion of transmission and cannot sustain an outbreak on their own, they play an important role in establishing new foci of infection. However, the impact of restricting livestock movements on the spread of both viruses depends critically on assumptions made about the distances over which vector dispersal occurs. If vector dispersal occurs primarily at a local scale (99% of transmission occurs <25 km), movement restrictions are predicted to be effective at reducing spread, but if dispersal occurs frequently over longer distances (99% of transmission occurs <50 km) they are not.