Epidemiological studies on camel trypanosomosis (surra) and its control and economic impact in Somaliland

Surra is a disease caused by the pathogenic trypanosome, Trypanosoma evansi, and is distributed throughout Africa, Asia and South America. The study outlined in this thesis was conducted to determine the epidemiology of trypanosomosis in camels, its economic impact on camels raised under a traditional pastoral production system and potential vectors that could transmit the disease between camels in Somaliland. Prior to this study there was limited information on the distribution and impact of surra in camels in Somaliland, although field reports indicated significant losses of production and consequently impact on the livelihood of pastoralists. In this study 2,575 camels were sampled from 144 herds and tested with the CATT/T. evansi. The animal level test seroprevalence observed was 26.4% (95% CI 24.8, 28.2) (real prevalence after adjusting for test sensitivity and specificity was 38.2%; 95% CI: 36.0, 40.0). The seroprevalence varied significantly between regions (p < 0.05) with a higher level (37.2%) in Sahil than in Awdal (19.3%) or Waqoyi Galbed (17.4%). A susceptible-infectious-subclinical (SIC) model was constructed in order to determine criteria for successful disease control by mass and targeted chemotherapy. This was used to simulate and estimate the economic benefits of four different control options against surra in camels. Adopting biannual treatment of all camels, monthly targeted treatment of clinically sick camels or biannual targeted treatment of seropositive camels was estimated to result in a benefit of US$141,431, 170,577 and 114,625 per village (80 camels) for a five year period in the study area, respectively. The prevalence after five years of control was predicted to be 7.4, 6.4 and 6.7$404,630 (20159 camels studied) if no treatment was administered. The greatest loss was associated with decreased milk yield (US$314,630). As part of this research Nzi and biconical traps were set to trap tabanids responsible for transmitting trypanosomosis. Three genera of tabanids were trapped (Philoliche, Tabanus and Haematopota) and these flies were recognised as potential vectors of trypanosomosis in camels. Philoliche species were the most widely distributed and abundant biting flies in the area. The activity of the biting flies differed throughout the day, with the highest activity observed in the middle of the day and the lowest in the afternoon. There was a significant difference between the alighting sites of biting flies on camels, with the lower body and belly of camels being the preferred sites compared to the upper body (head, neck and hump). In this study on average 0.87 ± 0.34 flies of the Philoliche genus alighted on the lower body and belly of camels in the middle of the day. The results of this study strongly support the need for implementation of surveillance and control programs for trypanosomosis in camel herds in Somaliland

Machine Learning for Biometrics

Biometrics aims at reliable and robust identification of humans from their personal traits, mainly for security and authentication purposes, but also for identifying and tracking the users of smarter applications. Frequently considered modalities are fingerprint, face, iris, palmprint and voice, but there are many other possible biometrics, including gait, ear image, retina, DNA, and even behaviours. This chapter presents a survey of machine learning methods used for biometrics applications, and identifies relevant research issues. We focus on three areas of interest: offline methods for biometric template construction and recognition, information fusion methods for integrating multiple biometrics to obtain robust results, and methods for dealing with temporal information. By introducing exemplary and influential machine learning approaches in the context of specific biometrics applications, we hope to provide the reader with the means to create novel machine learning solutions to challenging biometrics problems

Technoscience Art: A Bridge between Neuroesthetics and Art History?

One of the recent and exciting developments in mainstream art history is its confrontation with the cognitive sciences and neurology. This study is based on the problems these disciplines face before they can contribute to each other. We inspect several critical issues resulting from this encounter, especially in the context of the recently developing field of neuroesthetics. We argue that it is the language barrier between the disciplines, rather than any fundamental conceptual divison, that causes the lack of understanding on both sides. Shared terms in arts and neuroscience are elusive, and the different connotations of extant terms in these separate disciplines must be addressed. We propose technoscience art as a ground where joint terminology may be developed, an audience familiar to the concerns of both sides can be formed, and a new generation of scientifically-knowledgeable artists and scientists can interact for their mutual benefit

Registration of 3D Face Scans with Average Face Models

The accuracy of a 3D face recognition system depends on a correct registration that aligns the facial surfaces and makes a comparison possible. The best results obtained so far use a costly one-to-all registration approach, which requires the registration of each facial surface to all faces in the gallery. We explore the approach of registering the new facial surface to an average face model (AFM), which automatically establishes correspondence to the pre-registered gallery faces. We propose a new algorithm for constructing an AFM, and show that it works better than a recent approach. Extending the single-AFM approach, we propose to employ category-specific alternative AFMs for registration, and evaluate the effect on subsequent classification. We perform simulations with multiple AFMs that correspond to different clusters in the face shape space and compare these with gender and morphology based groupings. We show that the automatic clustering approach separates the faces into gender and morphology groups, consistent with the other race effect reported in the psychology literature. We inspect thin-plate spline and iterative closest point based registration schemes under manual or automatic landmark detection prior to registration. Finally, we describe and analyse a regular re-sampling method that significantly increases the accuracy of registration

New Flame Retardant and Antimicrobial Paints Based on Epoxy Paint Incorporated by Hexachlorocylodiphosphazane Derivatives for Protective Coating

Flame retardants can be incorporated into polymeric material either as additives or as reactive materials. Additive type flame retardants are widely used by means of blending them with a specific polymeric material. In this particular research, hexachlorocylodiphosphazane derivatives type (I-II) were synthesized for use as flame retardant and antimicrobial additives with epoxy varnish. These additives are physically incorporated into the epoxy varnish formula. Experimental coatings were manufactured on a laboratory scale and applied by brush on wood and steel panels. The fire retardant ability of each coating type was characterized using the limiting oxygen index (LOI) test. The mechanical properties of these flame retardants were also examined to evaluate the drawbacks of the additives. Results of the LOI indicated that coating with these compounds containing chlorine, nitrogen and phosphorus exhibit a very good retardant effect, when blended with epoxy varnish comparing with the blanket sample which not contain on the hexachlorocylodiphosphazane derivative as a additives. The hexachlorocylodiphosphazane derivative also exhibit mild results as preservative against microbiological attack. The mechanical properties of the painted dry films were investigated acordinting to ASTM