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- Mann, Koren K., et al.
(author)
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Tungsten
- 2022. - 5
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In: Handbook on the toxicology of metals. - : Elsevier. - 9780128229460 ; , s. 869-883
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Book chapter (peer-reviewed)abstract
- Tungsten is a rare element with a natural abundance thought to be around 1.5 parts per million. It is remarkable for its robust physical properties, making it useful for many industrial applications. Tungsten is the heaviest metal to have a known biological role as it is essential as a cofactor for oxidoreductases in some thermophilic prokaryotes. In animal models, ingested and inhaled tungsten is rapidly absorbed and excreted in the urine. The remaining tungsten in the body is distributed mainly to the spleen, kidney, and bone, with the highest tungsten accumulation in the bone. Tungsten metabolism closely resembles molybdenum in chemical properties. Occupational inhalation exposure to tungsten carbide dust has been linked to cases of pulmonary fibrosis, a hard metal disease, although the contribution of tungsten carbide versus cobalt coexposure is unclear. Small quantities of tungsten are present in food and water and trace quantities, related to industrial emissions, are found in the general atmosphere. Tungsten is also present in human serum, urine, and feces, with elimination approximately balancing intake of the metal in the few nonindustrially exposed subjects studied. Industrial, medical, and military uses of tungsten have been expanding rapidly; therefore, the potential for tungsten spreading into the environment is rapidly increasing.
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- Rowa, Per, et al.
(author)
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Automated Malaria Parasite Detection
- 1977
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Reports (other academic/artistic)abstract
- A system for malaria parasite detection in thin blood-smears is presented. Sample slides prepared with standard methods are accepted. A low-cost TV-camera mounted on an ordinary microscope with a computer controlled stage is used as a picture sensor. Frames, digitized in windows of 64 x 64 pixels are fed into a special purpose picture processor at normal frame rate (25 frames/sec). In the picture processor measurements are made on the images at high speed. The classification problem is split into different levels each having different characteristics such as different sampling density. Four classes, three of which are different types of malaria parasites, are recognized. As a whole the classification is best labelled as a sequential pattern recognition procedure.In its preliminary version the system has been run at a speed comparable to that of a human operator, that is l 500 cells per minute. A test on 80 000 cells gave 25 false negatives out of 283 parasites (9%) and 41 false positives (0.05%).
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