We report the development of a new methodology for analyzing CYLEX tests streak images. In these tests, the displacement of the wall of an explosive filled cylinder is obtained by backlighting the cylinder. The profile is imaged through a slit and streaked across a film record as the cylinder is detonated. A critical step in processing this data is the spatial calibration of the film and extraction of the profile of the cylinder from the image. Historically this has been a tedious task as it was performed by eye with the assistance of an optical comparator. Recently we developed an algorithm which automates the data calibration and extraction process of digitized streak records utilizing the Shen‐Castan edge detection algorithm and the image processing capabilities found in the IGOR PRO software. The new processing methodology greatly increases the resolution of the data, removes human subjectivity, and reduces analysis time from hours to seconds. The higher resolution of the new method has enabled much greater accuracy in measuring early‐time (<15 µs) expansion. With the aid of CTH hydrocode calculations, new fitting functions were developed to model both the early and late‐time expansion data. These functions contain physically meaningful fitting parameters and include terms which mimic the intensity and time scales of the shock and gas induced expansion of the cylinder independently. We demonstrate the methodology and hydrocode calculations on a recent CYLEX test series aimed at examining the effects of a plastic liner on high‐purity oxygen‐free copper cylinders filled with a high explosive.
An important question in cancer evolution concerns which traits make a cell likely to successfully metastasize. Cell motility phenotypes, mediated by cell shape change, are strong candidates. We experimentally evolved breast cancer cells in vitro for metastatic capability, using selective regimes designed to simulate stages of metastasis, then quantified their motility behaviours using computer vision. All evolved lines showed changes to motility phenotypes, and we have identified a previously unknown density-dependent motility phenotype only seen in cells selected for colonization of decellularized lung tissue. These cells increase their rate of morphological change with an increase in migration speed when local cell density is high. However, when the local cell density is low, we find the opposite relationship: the rate of morphological change decreases with an increase in migration speed. Neither the ancestral population, nor cells selected for their ability to escape or invade extracellular matrix-like environments, displays this dynamic behavioural switch. Our results suggest that cells capable of distant-site colonization may be characterized by dynamic morphological phenotypes and the capacity to respond to the local social environment.
Platelets mediate arterial thrombosis, a leading cause of myocardial infarction and stroke. During injury, platelets adhere and spread over exposed subendothelial matrix substrates of the damaged blood vessel wall. The mechanisms which govern platelet activation and their interaction with a range of substrates are therefore regularly investigated using platelet spreading assays. These assays often use differential interference contrast (DIC) microscopy to assess platelet morphology and analysis performed using manual annotation. Here, a convolutional neural network (CNN) allowed fully automated analysis of platelet spreading assays captured by DIC microscopy. The CNN was trained using 120 generalised training images. Increasing the number of training images increases the mean average precision of the CNN. The CNN performance was compared to six manual annotators. Significant variation was observed between annotators, highlighting bias when manual analysis is performed. The CNN effectively analysed platelet morphology when platelets spread over a range of substrates (CRP-XL, vWF and fibrinogen), in the presence and absence of inhibitors (dasatinib, ibrutinib and PRT-060318) and agonist (thrombin), with results consistent in quantifying spread platelet area which is comparable to published literature. The application of a CNN enables, for the first time, automated analysis of platelet spreading assays captured by DIC microscopy.
Abstract. The cylinder test (aka cylinder expansion or Cylex test) is a standard way to measure the Gurney velocity and determine the JWL coefficients of an explosive and has been utilized by the explosives community for many years. More recently, early time shock information has been found to be useful in examining the early pressure-time history during the expansion of the cylinder. Work in the area of nanoenergetics has prompted Air Force researchers to develop a miniaturized version of the Cylex test, for materials with a sufficiently small critical diameter, to reduce the cost and quantity of material required for the test. This paper discusses the development of a half-inch diameter version of the Cylex test. A measurement systems analysis of the new miniaturized and the standard one-inch test has been performed using the liquid explosive PLX (nitromethane sensitized with ethylene diamine). The resulting velocity and displacement profiles obtained from the streak records were compared to Photo Doppler Velocimetry (PDV) measurements as well as CTH hydrocode simulations. Measurements of the Gurney value for both diameter tests were in agreement and yielded a similar level of variability of 1%-4%.
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