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In this paper, I outline the drawbacks with the two main behavioral approaches to animal behavior problems and argue that each alone is insufficient to underpin a field of clinical animal behavior. Applied ethology offers an interest in an animal’s spontaneous behavior in natural contexts, understood within an ecological and evolutionary context, but lacks an awareness of mechanisms that can be manipulated to modify the behavior of individual animals. Behaviorism in the form of Applied Behavior Analysis offers a toolkit of techniques for modifying the behavior of individual animals, but has seldom been applied to non-human species, and often overlooks phylogenetic aspects of behavior. Notwithstanding the historical animosities between the two fields of animal behavior they are philosophically highly compatible – both being empiricist schools stemming ultimately from Darwin’s insights. Though each individually is incomplete, I argue that an integrated approach that synthesizes the strengths of each holds great promise in helping the many animals who need our assistance to survive and thrive in human-dominated environments.
The relative importance of adaptation and individual ontogenetic experience in dogs' high levels of behavioral compatibility with humans has been a topic of intense scientific attention over the past two decades. Salomons et al. Current Biology, 31, 3137-3144, (2021) recently presented a particularly rich data set of observations on both wolf and dog puppies that has the potential to contribute substantially to this debate. In their study subjecting wolf and dog puppies to batteries of tests, including the ability to follow human pointing gestures, Salomons et al. (2021) reported that dogs, but not wolves, have a specialized innate capacity for cooperation with humans. However, upon reanalyzing this data set, we reach a different conclusion-namely, that when controlling adequately for various environmental factors, wolves and dogs perform similarly in their cooperation with humans.
Journal article.
Journal article.
This study addresses the problem of particle image segmentation by measuring the similarity between a sampled region and an adjacent region, based on Bhattacharyya distance and an image feature extraction technique that uses distribution of local binary patterns and pattern contrasts. A boundary smoothing process is developed to improve the accuracy of the segmentation. The novel particle image segmentation algorithm is tested using four different cases of particle image velocimetry (PIV) images. The obtained experimental results of segmentations provide partitioning of the objects within 10 percent error rate. Ground-truth segmentation data, which are manually segmented image from each case, are used to calculate the error rate of the segmentations.
Here, this research extends that exploratory work in an effort to determine if hfg of aqueous nanofluids can be manipulated, i.e., increased or decreased, by the addition of graphite or silver nanoparticles. Our results to date indicate that hfg can be substantially impacted, by up to ± 30% depending on the type of nanoparticle. Moreover, this dissertation reports further experiments with changing surface area based on volume fraction (0.005% to 2%) and various nanoparticle sizes to investigate the mechanisms for hfg modification in aqueous graphite and silver nanofluids. This research also investigates thermophysical properties, i.e., density and surface tension in aqueous nanofluids to support the experimental results of hfg based on the Clausius - Clapeyron equation. This theoretical investigation agrees well with the experimental results. Furthermore, this research investigates the hfg change of aqueous nanofluids with nanoscale studies in terms of melting of silver nanoparticles and hydrophobic interactions of graphite nanofluid. As a result, the entropy change due to those mechanisms could be a main cause of the changes of hfg in silver and graphite nanofluids.
Finally, applying the latent heat results of graphite and silver nanofluids to an actual solar thermal system to identify enhanced performance with a Rankine cycle is suggested to show that the tunable latent heat of vaporization in nanofluilds could be beneficial for real-world solar thermal applications with improved efficiency.