998 resultados para News detection
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Weekly newsletter for the State of Iowa Alcoholic Beverages Division
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Weekly newsletter for the State of Iowa Alcoholic Beverages Division
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Weekly newsletter for the State of Iowa Alcoholic Beverages Division
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Newsletter for Economic Development.
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Abstract. Terrestrial laser scanning (TLS) is one of the most promising surveying techniques for rockslope characteriza- tion and monitoring. Landslide and rockfall movements can be detected by means of comparison of sequential scans. One of the most pressing challenges of natural hazards is com- bined temporal and spatial prediction of rockfall. An outdoor experiment was performed to ascertain whether the TLS in- strumental error is small enough to enable detection of pre- cursory displacements of millimetric magnitude. This con- sists of a known displacement of three objects relative to a stable surface. Results show that millimetric changes cannot be detected by the analysis of the unprocessed datasets. Dis- placement measurement are improved considerably by ap- plying Nearest Neighbour (NN) averaging, which reduces the error (1σ ) up to a factor of 6. This technique was ap- plied to displacements prior to the April 2007 rockfall event at Castellfollit de la Roca, Spain. The maximum precursory displacement measured was 45 mm, approximately 2.5 times the standard deviation of the model comparison, hampering the distinction between actual displacement and instrumen- tal error using conventional methodologies. Encouragingly, the precursory displacement was clearly detected by apply- ing the NN averaging method. These results show that mil- limetric displacements prior to failure can be detected using TLS.
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Newsletter for Information Technology Department
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Newsletter for Information Technology Department
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Newsletter for Information Technology Department
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Newsletter for Information Technology Department
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Newsletter for Information Technology Department
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Newsletter for Information Technology Department
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Newsletter for Information Technology Department
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Arsenic contamination of natural waters is a worldwide concern, as the drinking water supplies for large populations can have high concentrations of arsenic. Traditional techniques to detect arsenic in natural water samples can be costly and time-consuming; therefore, robust and inexpensive methods to detect arsenic in water are highly desirable. Additionally, methods for detecting arsenic in the field have been greatly sought after. This article focuses on the use of bacteria-based assays as an emerging method that is both robust and inexpensive for the detection of arsenic in groundwater both in the field and in the laboratory. The arsenic detection elements in bacteria-based bioassays are biosensor-reporter strains; genetically modified strains of, e.g., Escherichia coli, Bacillus subtilis, Staphylococcus aureus, and Rhodopseudomonas palustris. In response to the presence of arsenic, such bacteria produce a reporter protein, the amount or activity of which is measured in the bioassay. Some of these bacterial biosensor-reporters have been successfully utilized for comparative in-field analyses through the use of simple solution-based assays, but future methods may concentrate on miniaturization using fiberoptics or microfluidics platforms. Additionally, there are other potential emerging bioassays for the detection of arsenic in natural waters including nematodes and clams.
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Newsletter for Iowa Department of Transportation
