53 research outputs found

    Assessing the value of enrofloxacin and carprofen combination treatment in southern white rhinoceros (Ceratotherium simum) through the use of pharmacokinetic modelling

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    Over the past decade, the poaching of white rhinoceros (Ceratotherium simum) has increased dramatically. More than 7000 animals have been killed and approximately 200 animals annually survive the poaching attempts with life threatening injuries, which require immediate medical attention. Despite their need for veterinary care, knowledge on the treatment of white rhinoceros is scarce. Approved drugs are non-existent and dosages need to be extrapolated arbitrarily from other species. In order to successfully treat injured poaching victims and to increase their chance of survival, potentially effective drugs and corresponding dosages need to be assessed. For this study, we evaluated the pharmacokinetic and pharmacodynamic properties of enrofloxacin in combination with carprofen, administered to immobilised rhinoceros. From the pharmacokinetic evaluation, intravenous enrofloxacin (12.5 mg/kg) was characterised by an AUC, Cl and t1/2 (Gmean ± SD) of 64.5 ± 14.44 μg*h/mL, 0.19 ± 0.04 L/h*kg and 12.41 ± 2.62 hours, respectively. Of these, the unexpected finding was the extremely long half-life of elimination, which was significantly longer than that of the horse and of any other mammalian species. Subsequent pharmacodynamics modelling showed that daily intravenous application could be useful and could be achieved by means of a light butorphanol sedation, followed by the enrofloxacin administration through an indwelling catheter. To further evaluate if the intravenous priming dose could be maintained by subsequent oral dosing, animals in phase two of the study were treated with a second dose of enrofloxacin in the feed following immobilisation. The oral treatment was deemed inappropriate, as the oral bioavailability of 33.30 ± 38.33% was surprisingly low. Intramuscular carprofen (1 mg/kg), was characterised by an AUC, Cl and t1/2 of 904.61 ± 110.78 μg*h/ml, 0.0011 ± 0.0001 L/h*kg and 105.71 ± 15.67 hours, respectively. As for enrofloxacin, the major finding was the considerably long half-life, which was the longest reported in any species this far. Based on the changes in plasma thromboxane concentration, we surmise that the drug would have an anti-inflammatory effect for a minimum of 48 hours. To gain a better understanding of the prolonged half-life of elimination, two in silico studies were undertaken. For the first study, allometric pharmacokinetic modelling was conducted with enrofloxacin to ascertain if the slower metabolism evident in the rhino could be attributed to the size of the species. Despite the goodness of fit of different models, none were predictive of the actual pharmacokinetic parameters. This leads to the conclusion that the slower metabolism resulted from metabolic constraints as opposed to size-related slower metabolism. To provide insight into the metabolic constrains in the rhino and to ascertain if the rhino genome coded for the enzymes described in the horse, a species closest related to the rhinoceros, the published rhino genome was evaluated using BLAST algorithms. The white rhino nucleotide sequences were 90.74% identical to the equine sequences, which represents the highest degree of similarity amongst all evaluated species sequences. Even though all CYP450 families present in the horse coud be identified in the white rhino, the horse genome contained additional gene sequences for a larger number of iso-enzymes, which were not present in the rhino. Thus, the difference in the metabolic capacity cannot be directly attributed to an absolute deficiency of a CYP enzyme family. However, with the difference possibly being the absence of specific isoenzymes in the rhino, this could suggest that the horse is a more efficient metabolizer. Based on the results of this study, we believe that carprofen shows good promise as an analgesic for use in rhinoceros. While enrofloxacin should be effective, its use is rather limited due to the frequently required intravenous administration. The subsequent in silico modelling suggested that the rhino may exhibit metabolic constraints, which may result from their lower number of isoenzymes. The latter assumption does however require further evaluation.Companion Animal Clinical StudiesPhDUnrestricte

    An evaluation of the factors affecting ‘poacher’ detection with drones and the efficacy of machine-learning for detection

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    Drones are being increasingly used in conservation to tackle the illegal poaching of animals. An important aspect of using drones for this purpose is establishing the technological and the environmental factors that increase the chances of success when detecting poachers. Recent studies focused on investigating these factors, and this research builds upon this as well as exploring the efficacy of machine-learning for automated detection. In an experimental setting with voluntary test subjects, various factors were tested for their effect on detection probability: camera type (visible spectrum, RGB, and thermal infrared, TIR), time of day, camera angle, canopy density, and walking/stationary test subjects. The drone footage was analysed both manually by volunteers and through automated detection software. A generalised linear model with a logit link function was used to statistically analyse the data for both types of analysis. The findings concluded that using a TIR camera improved detection probability, particularly at dawn and with a 90° camera angle. An oblique angle was more effective during RGB flights, and walking/stationary test subjects did not influence detection with both cameras. Probability of detection decreased with increasing vegetation cover. Machine-learning software had a successful detection probability of 0.558, however, it produced nearly five times more false positives than manual analysis. Manual analysis, however, produced 2.5 times more false negatives than automated detection. Despite manual analysis producing more true positive detections than automated detection in this study, the automated software gives promising, successful results, and the advantages of automated methods over manual analysis make it a promising tool with the potential to be successfully incorporated into anti-poaching strategies

    A Comprehensive Review of AI-enabled Unmanned Aerial Vehicle: Trends, Vision , and Challenges

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    In recent years, the combination of artificial intelligence (AI) and unmanned aerial vehicles (UAVs) has brought about advancements in various areas. This comprehensive analysis explores the changing landscape of AI-powered UAVs and friendly computing in their applications. It covers emerging trends, futuristic visions, and the inherent challenges that come with this relationship. The study examines how AI plays a role in enabling navigation, detecting and tracking objects, monitoring wildlife, enhancing precision agriculture, facilitating rescue operations, conducting surveillance activities, and establishing communication among UAVs using environmentally conscious computing techniques. By delving into the interaction between AI and UAVs, this analysis highlights the potential for these technologies to revolutionise industries such as agriculture, surveillance practices, disaster management strategies, and more. While envisioning possibilities, it also takes a look at ethical considerations, safety concerns, regulatory frameworks to be established, and the responsible deployment of AI-enhanced UAV systems. By consolidating insights from research endeavours in this field, this review provides an understanding of the evolving landscape of AI-powered UAVs while setting the stage for further exploration in this transformative domain

    Noninvasive Technologies for Primate Conservation in the 21st Century

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    Observing and quantifying primate behavior in the wild is challenging. Human presence affects primate behavior and habituation of new, especially terrestrial, individuals is a time-intensive process that carries with it ethical and health concerns, especially during the recent pandemic when primates are at even greater risk than usual. As a result, wildlife researchers, including primatologists, have increasingly turned to new technologies to answer questions and provide important data related to primate conservation. Tools and methods should be chosen carefully to maximize and improve the data that will be used to answer the research questions. We review here the role of four indirect methods—camera traps, acoustic monitoring, drones, and portable field labs—and improvements in machine learning that offer rapid, reliable means of combing through large datasets that these methods generate. We describe key applications and limitations of each tool in primate conservation, and where we anticipate primate conservation technology moving forward in the coming years

    An Evaluation of the Factors Affecting 'Poacher' Detection with Drones and the Efficacy of Machine-Learning for Detection.

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    Drones are being increasingly used in conservation to tackle the illegal poaching of animals. An important aspect of using drones for this purpose is establishing the technological and the environmental factors that increase the chances of success when detecting poachers. Recent studies focused on investigating these factors, and this research builds upon this as well as exploring the efficacy of machine-learning for automated detection. In an experimental setting with voluntary test subjects, various factors were tested for their effect on detection probability: camera type (visible spectrum, RGB, and thermal infrared, TIR), time of day, camera angle, canopy density, and walking/stationary test subjects. The drone footage was analysed both manually by volunteers and through automated detection software. A generalised linear model with a logit link function was used to statistically analyse the data for both types of analysis. The findings concluded that using a TIR camera improved detection probability, particularly at dawn and with a 90° camera angle. An oblique angle was more effective during RGB flights, and walking/stationary test subjects did not influence detection with both cameras. Probability of detection decreased with increasing vegetation cover. Machine-learning software had a successful detection probability of 0.558, however, it produced nearly five times more false positives than manual analysis. Manual analysis, however, produced 2.5 times more false negatives than automated detection. Despite manual analysis producing more true positive detections than automated detection in this study, the automated software gives promising, successful results, and the advantages of automated methods over manual analysis make it a promising tool with the potential to be successfully incorporated into anti-poaching strategies

    Wildlife Population Monitoring

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    Wildlife management is about finding the balance between conservation of endangered species and mitigating the impacts of overabundant wildlife on humans and the environment. This book deals with the monitoring of fauna, related diseases, and interactions with humans. It is intended to assist and support the professional worker in wildlife management

    Forecasting: theory and practice

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    Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases.info:eu-repo/semantics/publishedVersio
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