a b s t r a c tThis paper describes a new methodology for automatic location of the optic disc in retinal images, based on the combination of information taken from the blood vessel network with intensity data. The distribution of vessel orientations around an image point is quantified using the new concept of entropy of vascular directions. The robustness of the method for OD localization is improved by constraining the search for maximal values of entropy to image areas with high intensities. The method was able to obtain a valid location for the optic disc in 1357 out of the 1361 images of the four datasets.
The use of inductively coupled plasma-mass spectrometry (ICP-MS) in the study of gunshot residues (GSR) is relatively recent, and only a few studies have been published on the subject. In the present paper, this instrumental technique has been used to study the deposit pattern of the GSR around the bullet entrance hole, through the analysis of antimony (Sb), barium (Ba), and lead (Pb). The data obtained were used to establish a mathematical model for estimating the firing distance. Test shots using a 6.35-mm pistol were made against a target of cotton tissue, and the amounts of Sb, Ba, and Pb deposited in quadrangular pieces of the target, cut from 4 radial positions, were determined by ICP-MS. In these experimental conditions, it was possible to estimate the firing distance on the interval [20-80] cm. The best linear correlation between ln m and d, where m is the mass of Sb, Ba, or Pb in the samples, expressed in mug/g of target tissue, and d the firing distance, was obtained at radial distances between 3.5 cm and 4.5 cm from the entrance hole. The best regression curve which adjusted to the data was a linear multiple regression between the firing distance and the logarithm of the mass of each element: d = a + b(1)X(1) + b(2)X(2) + b(3)X(3), where X(1) = ln m (Sb), X(2) = ln m(Ba) and X(3) = ln m (Pb). The accuracy of firing distance estimation using only 1 or 2 elements was not significantly different from the one obtained with the 3 elements.
This paper presents a spatial characterization of the distribution at district level of the forest fire events that occurred in mainland Portugal between 1996 and 2015 and whose causes were investigated. We further examine the breakdown of the causes of these forest fires over this period. Results supported by relevant validated statistics show that of the total fire events recorded, 94.4% were identified as an effective occurrence, of which 22.2% had burned an area greater than 1 ha, and of these only 42.1% were investigated. False alarms or fires without a recorded burning area are more significant in the districts of Aveiro, Lisbon and Porto, the biggest municipalities. Of the fires whose causes were investigated, the largest number of recorded events were in NE regions (49.0%), followed by NW regions (41.7%), and finally in the rest of the country (9.3%). Taking into account the ratio between the investigated fires and the total number of fires and the behavior profile produced for cluster analysis, a different panorama is brought to light, with the center and south regions showing greater effort to investigate the fires. A thorough analysis of the causes and motivations of the ignition of these forest fire occurrences showed that human activity, either deliberate (20.4%) or negligent (29.9%), outweigh natural phenomena (0.6%). Reactivations (14.6%) and Unknown (34.5%) causes decreased as time passed, whereas negligent and deliberate causes increased. However, these results could change if the percentage of unknown information in relation to the origin of the forest fires is considerable. The outcome of this research will support an efficient management related to fire mitigation and suppression including establishing preventive actions to reduce the occurrence of forest fires and emphasize the need to improve the procedure for recording forest fire events in Portugal, especially in relation to identifying their cause.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.