Download Domestic Animals Images [REPACK]

All awesome entries. Congratulations to those who ranked. Thank you for the mention of my images.

The cat was a feral living at a local wetlands.

The dogs belong to a friend, I thought a nice image of her dogs would be a great way to repay her kindness.

The Peacock was at a local zoo.

The Imaging Anatomy web site is a basic atlas of normal imaging anatomy of domestic animals. It is designed as an aid for veterinary students beginning their study of diagnostic imaging. It is not meant to be a comprehensive reference of imaging anatomy. It is also not meant to present the range of variation across breeds of the domestic animals. The site is the result of the work of Gerald J. Pijanowski, DVM, PhD and Steve Kneller, DVM, MS, DACVR, along with the design wizardry of Nancy Oliver of the Design Group. The overlays used to highlight various structures on each image are the result of the hard work of Seth Kramer, Class of 2011. Thanks to the research of Seth Kramer, the color palate used should accomodate the common forms of color blindness. Any errors, omissions or other mistakes are the responsibilty of the creators. Your comments and suggestions are invited. Please e-mail them to designgroup@vetmed.illinois.edu.

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A competitive learning vector quantization artificial neural network (ANN) was trained to identify third-stage parasitic strongyle larvae from domestic animals on the basis of quantitative data obtained from processed digital images of larvae. For this reason, various quantitative features obtained from processed digital images of larvae were tested as to whether they are variant or invariant to the shape taken by the motile larvae during image recording. A total of 255 images of 57 individual larvae in various shapes belonging to five genera were recorded. Following image processing, 16 features were measured, of which seven were selected as invariant to larva shape. By trial and error, two of those features, 'area' and 'perimeter', along with the quantitative features used in conventional identification, 'overall body length', 'width' and 'extension of sheath' (tip of larva to tip of sheath), were used as an effective training data set for the ANN. This ANN coupled with an image analysis facility and a knowledge relational database became the basis for developing a computer-based larva identification system whose overall identification performance was 91.9%. The advantages of this system are its speed and objectivity. The objectivity of the system is based on the fact that it is not subject to inter- and intra-observer variability arising from the user's profile of competency in interpreting subjective and non-quantifiable descriptions. The limitations of the system are that it cannot handle raw images but only data extracted from images, its performance depends on the reliability of the input vectors used as training data for the ANN, and its use is restricted only to well-equipped laboratories due to its requirement for expensive instrumentation.

Identifier: domesticanimalsf00stor (find matches)

Title: The domestic animals : from the latest and best authorities. Illustrated

Year: 1860 (1860s)

Authors: Storke, Elliot G., 1811-1879

Subjects: Horses Domestic animals

Publisher: Auburn, N.Y. : Auburn publish. Co.

Contributing Library: Webster Family Library of Veterinary Medicine

Digitizing Sponsor: Tufts University

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hort-horn class; not, indeed, the high bred Duiham short-horn,but a large capacious animal, possessing several of its qualities, andgiving a large quantity of milk, with as much aptitude to fatten as isconsistent with the production of milk, and hence is selected by thedairymen of large towns, and especially of London, for the supply ofmilk for a given period, and then to be fatted on distillers refuse, andother waste matters which a town will afford, and thus o-ive a doublepay to the dairyman. The Yorkshire cow is of much larger size than either of those wehave been considering; and, when fat, will weigh from eight to elevenhundred pounds. Her head is fine, and somewhat small; there is aserene placidity of eye, which shows a mild and gentle disposition, tend-ing alike to produce fat and milk. The horns are small and white, themuzzle without black spots; the breast deep and prominent, but thatand the shoulders thin ; the neck somewhat narrow, but full below the6* 106 DOMESTIC ANIMALS.

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CATTLE. 107 shoulders, and without any loose skin ; the barrel somewhat round ; thebelly capacious; milk-vein large; back perfectly straight; rump wide,and flat as a table; tail small, and set on so that there is almost astraight line from the tail to the head. The prevailing color is roan, orred or white; and sometimes white, with the tips of the ears red. Thethighs are thin; but the legs are straight and somewhat short. Theudder is very large and muscular, projecting forward, well filled up be-hind, and so broad as to give the cow the appearance of a waddle inher walking. Indeed, her qualities are not inappropriately described insome doggerel lines often quoted; and t^vo of the verses we shall ven-ture to give, as most aptly descriptive of the Yorkshire cow Shes broad in her ribs, and long in her rump,A straight and flat back without ever a hump;Shes wide in lier hips, and cahii in lier eyes;Shes fine in her slioulders, and thin in her tliighs Shes hght in her neck, and small in her

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Management strategies and the use of advanced technologies are equally important for determining the sample number and sampling frame for successful field sampling for animal disease prevalence studies. The quality of the biological samples collected in the field has a direct bearing on the integrity of the data generated, prevalence estimates and subsequent policy decisions on disease control. Hence, compromising the quality of biological samples collected in the field could potentially undermine the priority setting principles in disease control strategies. Biological samples collected from domestic animals in the field are precious materials and require meticulous planning for sample collection, sample storage in the field, transportation, and storage in the laboratory. Poorly managed field sampling has a significant detrimental impact on the sample quality and quantity and directly affects the accuracy of disease prevalence data. A bad choice of sampling tools, containers, storage and transport all have a negative impact on the integrity of the sample and consequently have an impact on the outcome. Over the last two years, as part of our one health animal sampling work in India, we have observed challenges and opportunities in the field sampling of animals for disease prevalence studies. This paper aims to provide information on management practices and technologies for efficient biological sample collection from the field and ensure that good quality samples are available for testing.

The first step in the animal disease prevalence study in a population is the determination of a statistically defined random sample number and sampling frame. Execution of the sampling plan in the field requires liaison with local veterinarians and village heads, meticulous planning of sample collection, sample storage in the field, and careful transportation, labeling, and storage in the laboratory. Biological sample collection from domestic animals in the field can be performed with ease and efficiency with proper management practices and advanced technological tools. Management practices and use of advanced technologies are equally important as the determination of sample number and sampling frame for efficient field sampling for animal disease prevalence. Management practices with regional touch considering the local cultural, socioeconomic, and political conditions in mind are a vital part of any animal and human disease prevalence studies. The quality of the biological samples collected in the field has a direct bearing on the integrity of the data generated, prevalence estimates and subsequent policy decisions on disease control. Hence, compromising the quality of biological samples collected in the field could potentially undermine the priority setting principles in disease control (Migliavaca et al. 2020). In India, regulatory approvals such as the Institutional Animal Ethics Committee (IAEC) and Committee for the Purpose of Control and Supervision of Experiments on Animals (CPCSEA) are required for performing animal experimentation in field conditions. For handling hazardous microorganisms, Institutional Bio-Safety Committee (IBSC) approval was necessary (Race and Hammond 2008). Prior to sampling, regulatory approvals had to be acquired.

Sampling of animals in field conditions and data collection can be greatly improved using advanced technologies, viz. GPS instrument, voice recorders, online data collection forms, muzzle printing device, handheld label printers, temperature and motion data loggers and digital cameras. e24fc04721