Marlice van der merwe biography sample
Cattle breeding, trypanosomosis prevalence and drug resistance in Northern Togo.
PubMed
Tchamdja, E; Kulo, A E; Vitouley, H S; Batawui, K; Bankolé, A A; Adomefa, K; Cecchi, G; Hoppenheit, A; Clausen, P H; De Deken, R; Van Den Abbeele, J; Marcotty, T; Delespaux, V
2017-03-15
AfricanAnimalTrypanosomosis (AAT) is a major disease of cattle in Togo and its control is essentially based on chemotherapy. However, because of excessive use of trypanocides during the past decades, chemo-resistance in the parasites has developed. In order to assess the current situation of AAT and resistance to trypanocidal drugs in Northern Togo, a study was conducted on cattle from December 2012 to August 2013 in the regions of Kara and Savanes. An initial cross-sectional survey was carried out in 40 villages using the Haematocrit Centrifugation Technique (HCT). Out of these, 5 villages with a trypanosome prevalence of >10% were selected for a block treatment study (BT) with diminazene diaceturate (DA: 3.5mg/kg for a 14-day follow-up) and isometamidium chloride (ISM: 0.5mg/kg for a 28-day follow-up). Positive blood samples collected during the parasitological surveys and an equivalent number of negatives were further analyzed by PCR-RFLP for trypanosome species confirmation and molecular diagnosis of resistance to DA in Trypanosoma congolense. The results from 1883 bovine blood samples confirmed a high overall trypanosome prevalence of 10.8% in Northern Togo. PCR-RFLP revealed that T. congolense is the dominant pathogenic trypanosome species (50.5%) followed by T. vivax (27.3%), and T. brucei (16.2%). The BT showed varying levels of treatment failures ranging from 0 to 30% and from 0 to 50% for DA and for ISM respectively, suggesting the existence of resistant trypanosome populations in the study area. Our results show that AAT still represents a major obstacle to the development of cattle husbandry in Northern Togo. In areas of high AAT risk, a community-based integrated strategy com Sir Bent Skovmand (January 25, 1945— February 6, 2007) was a Danish plant scientist and conservationist. Time Magazine wrote in 1991 that Skovmand, "'while not exactly a household name,' had had 'more to do with the welfare of the world's five billion people than many heads of state.'"Skovmand was born in Frederiksberg, Denmark. After serving in the Danish Army, Skovmand attended the University of Minnesota in the US as part of the Minnesota Agricultural Student Trainee international exchange program. He graduated in 1971 with a major in biological and physical sciences in agriculture, and then earned his masters in 1973 and doctorate in 1976 both in Plant Pathology from the University of Minnesota After completing his doctorate, he joined the International Maize and Wheat Improvement Center in El Batán, Mexico, where he studied older seed strains and genetic variation among widespread strains. He also worked with governments and farmers across the world to increase the use of the advanced crops being developed.He was awarded the Knight's Cross of the Order of the Dannebrog in 2003.Continuing his work on preserving the genetic diversity among wheats, barleys, and oats, he was appointed the director of the Nordic Gene Bank, based in Alnarp, Sweden, in 2003, and founded the Svalbard International Seed Vault. The Seed Vault, also called the "Doomsday Vault", is supported by the Global Crop Diversity Trust and aims to preserve "the raw material of agriculture" to make it available for breeding and research even in the advent of disaster, war, or climate change. The Vault was scheduled to open in late 2008.Skovmand was opposed to patenting individual genes, describing it as "like copyrighting each and every word in Hamlet, and saying no one can use any word used in Hamlet without paying the author". He routinely released his catalogs of agricultural information on CDs, which he gave away for free, never attempting to patent the work. In his work with the International Leandra Brickson Artificial intelligence (AI) and machine learning (ML) present revolutionary opportunities to enhance our understanding of animal behavior and conservation strategies. Using elephants, a crucial species in Africa and Asia’s protected areas, as our focal point, we delve into the role of AI and ML in their conservation. Given the increasing amounts of data gathered from a variety of sensors like cameras, microphones, geophones, drones, and satellites, the challenge lies in managing and interpreting this vast data. New AI and ML techniques offer solutions to streamline this process, helping us extract vital information that might otherwise be overlooked. This paper focuses on the different AI-driven monitoring methods and their potential for improving elephant conservation. Collaborative efforts between AI experts and ecological researchers are essential in leveraging these innovative technologies for enhanced wildlife conservation, setting a precedent for numerous other species. Elephants hold significant intrinsic, biological, ecological, and human cultural value. They possess unique genetic and physiological features [1], exhibit high-levels of individual cognitive and emotional intelligence [2, 3, 4], maintain complex social behaviors and structures [5, 6, 7, 8, 9], serve as keystone species in their respective ecosystems [10, 11, 12], are highly valued by their local communities [13] and serve as flagship species for animal conservation [14]. Unfortunately, the three extant species of elephants, African Savannah elephants (Loxodonta africa .Elephants and Algorithms: A Review of the Current and Future Role of AI in Elephant Monitoring
Colossal Biosciences, Dallas, TX, USApublications@colossal.comLibby Zhang
Fritz Vollrath
University of Oxford, Oxford, United KingdomSave the Elephants, Nairobi, KenyaIain Douglas-Hamilton
Alexander J. Titus
International Computer Science Institute, Berkeley, CA, USAAbstract
1 Introduction