Dataset Information

Ballistic research techniques: visualizing gunshot wounding patterns.

ABSTRACT: There are difficulties associated with mapping gunshot wound (GSW) patterns within opaque models. Depending on the damage measurement parameters required, there are multiple techniques that can provide methods of "seeing" the GSW pattern within an opaque model. The aim of this paper was to test several of these techniques within a cadaveric animal limb model to determine the most effective. The techniques of interest were flash X-ray, ultrasound, physical dissection, and computed-tomography (CT). Fallow deer hind limbs were chosen for the model with four limbs used for each technique tested. Quarantined 7.62?×?39 mm ammunition was used for each shot, and each limb was only shot once, on an outdoor range with shots impacting at muzzle velocity. Flash X-ray provided evidence of yaw within the limb during the projectile's flight; ultrasound though able to visualise the GSW track, was too subjective and was abandoned; dissection proved too unreliable due to the tissue being cadaveric so also too subjective; and lastly, CT with contrast provided excellent imaging in multiple viewing planes and 3D image reconstruction; this allowed versatile measurement of the GSW pattern to collect dimensions of damage as required. Of the different techniques examined in this study, CT with contrast proved the most effective to allow precise GSW pattern analysis within a cadaveric animal limb model. These findings may be beneficial to others wishing to undertake further ballistic study both within clinical and forensic fields.

SUBMITTER: Stevenson T

PROVIDER: S-EPMC7181419 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Ballistic research techniques: visualizing gunshot wounding patterns.

Stevenson Tom T Carr Debra J DJ Harrison Karl K Critchley Richard R Gibb Iain E IE Stapley Sarah A SA

International journal of legal medicine 20200214 3

There are difficulties associated with mapping gunshot wound (GSW) patterns within opaque models. Depending on the damage measurement parameters required, there are multiple techniques that can provide methods of "seeing" the GSW pattern within an opaque model. The aim of this paper was to test several of these techniques within a cadaveric animal limb model to determine the most effective. The techniques of interest were flash X-ray, ultrasound, physical dissection, and computed-tomography (CT) ...[more]

PMID: 32060625

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Project description:Sensor technologies allow ethologists to continuously monitor the behaviors of large numbers of animals over extended periods of time. This creates new opportunities to study livestock behavior in commercial settings, but also new methodological challenges. Densely sampled behavioral data from large heterogeneous groups can contain a range of complex patterns and stochastic structures that may be difficult to visualize using conventional exploratory data analysis techniques. The goal of this research was to assess the efficacy of unsupervised machine learning tools in recovering complex behavioral patterns from such datasets to better inform subsequent statistical modeling. This methodological case study was carried out using records on milking order, or the sequence in which cows arrange themselves as they enter the milking parlor. Data was collected over a 6-month period from a closed group of 200 mixed-parity Holstein cattle on an organic dairy. Cows at the front and rear of the queue proved more consistent in their entry position than animals at the center of the queue, a systematic pattern of heterogeneity more clearly visualized using entropy estimates, a scale and distribution-free alternative to variance robust to outliers. Dimension reduction techniques were then used to visualize relationships between cows. No evidence of social cohesion was recovered, but Diffusion Map embeddings proved more adept than PCA at revealing the underlying linear geometry of this data. Median parlor entry positions from the pre- and post-pasture subperiods were highly correlated (R = 0.91), suggesting a surprising degree of temporal stationarity. Data Mechanics visualizations, however, revealed heterogeneous non-stationary among subgroups of animals in the center of the group and herd-level temporal outliers. A repeated measures model recovered inconsistent evidence of a relationships between entry position and cow attributes. Mutual conditional entropy tests, a permutation-based approach to assessing bivariate correlations robust to non-independence, confirmed a significant but non-linear association with peak milk yield, but revealed the age effect to be potentially confounded by health status. Finally, queueing records were related back to behaviors recorded via ear tag accelerometers using linear models and mutual conditional entropy tests. Both approaches recovered consistent evidence of differences in home pen behaviors across subsections of the queue.

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Ballistic research techniques: visualizing gunshot wounding patterns.

Publications

Ballistic research techniques: visualizing gunshot wounding patterns.

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