Examining macro-level correlates of farm equipment theft : a test of routine activity theory and social disorganization theory.

This dissertation explores the potential for routine activity theory and social disorganization theory to explain incidence of farm equipment theft at the county level. Relatively few attempts have been made to discern the factors that contribute to such theft. Most are relatively dated, and all focus upon the relationship between victimization risk and the characteristics of individual farms. Accordingly, the current study represents the first attempt to examine the influence of macro-level processes and characteristics upon the problem. Data are gathered for 306 counties housed within four Southeastern States. Counts of farm equipment theft are collected from the 2011-2012 iterations of the National Incident Based Reporting System, and attributed to the county in which they occurred. The routine activity measures employed are based upon the findings of micro-level studies, and drawn primarily from the 2007 version of the Census of Agriculture. Social disorganization measures are created in line with past attempts to explore the applicability of the theory to crime problems outside of metropolitan areas. These measures are derived from the 2010 version of the United States Census. Negative binomial regression analysis suggests that both theories have applicability to our understanding of farm equipment theft incidence. Agricultural characteristics aggregated to the county level appear to condition the number of opportunities available to motivated offenders. Moreover, counties featuring structural characteristics conducive to disorganization appear to experience higher incidence of theft than those that would be considered “more organized.” Based upon these findings, implications for each theoretical framework are addressed. In addition, policy implications are covered, with a specific focus upon strategies designed to reduce opportunities for theft and improve levels of informal social control in rural areas. The dissertation concludes with a brief discussion of limitations associated with the study, directions for future research, and concluding remarks

An Exploratory Look at Thefts from Construction Sites

Theft of construction equipment, materials, and tools from construction sites results in approximately one billion dollars in direct annual losses to the U.S. construction industry per year. A better understanding of theft characteristics is vital to reducing this figure. This study analyzes over 15,000 incidents from the National Incident-Based Reporting System (NIBRS) to understand characteristics such as theft prevalence, average monetary losses, and recovery rates. The study finds that contractors lost an average of about $6,000 per incident. Trucks are the most expensive theft targets, with an average loss of about$42,000 per incident, and also the most likely item to be recovered (55% of the time). However, recovery rate across all targets was less than 7%. The results of this study provide the most accurate and extensive statistics to date on construction theft characteristics. The study also identifies best practices to reduce thefts such as the use of survellience systems. Further, the use of advanced marking and tracking systems to safeguard expensive equipment and vehicles and aid their recoveries are discussed. The findings are expected to aid contractors and law enforcement agencies in formulating methods for reducing thefts of construction items and improving the likelihood of their recoveries

Development and Validation of a Complete GATE Model of the Siemens Inveon Trimodal Imaging Platform

This article presents and validates a newly developed GATE model of the Siemens Inveon trimodal imaging platform. Fully incorporating the positron emission tomography (PET), single-photon emission computed tomography (SPECT), and computed tomography (CT) data acquisition subsystems, this model enables feasibility studies of new imaging applications, the development of reconstruction and correction algorithms, and the creation of a baseline against which experimental results for real data can be compared. Model validation was based on comparing simulation results against both empirical and published data. The PET modality was validated using the NEMA NU-4 standard. Validations of SPECT and CT modalities were based on assessment of model accuracy compared to published and empirical data on the platform. Validation results show good agreement between simulation and empirical data of approximately ± 5%

GATE Validation of Standard Dual Energy Corrections in Small Animal SPECT-CT

<div><p>This paper addresses ¹²³I and ¹²⁵I dual isotope SPECT imaging, which can be challenging because of spectrum overlap in the low energy spectrums of these isotopes. We first quantify the contribution of low-energy photons from each isotope using GATE-based Monte Carlo simulations for the MOBY mouse phantom. We then describe and analyze a simple, but effective method that uses the ratio of detected low and high energy ¹²³I activity to separate the mixed low energy ¹²³I and ¹²⁵I activities. Performance is compared with correction methods used in conventional tissue biodistribution techniques. The results indicate that the spectrum overlap effects can be significantly reduced, if not entirely eliminated, when attenuation and scatter is either absent or corrected for using standard methods. In particular, we show that relative activity levels of the two isotopes can be accurately estimated for a wide range of organs and provide quantitative validation that standard methods for spectrum overlap correction provide reasonable estimates for reasonable corrections in small-animal SPECT/CT imaging.</p></div

Relative estimation error for three different imaging conditions: Ideal (no scatter medium), scatter and attenuation medium without corrections, and scatter and attenuation medium with corrections.

<p>Relative estimation error for three different imaging conditions: Ideal (no scatter medium), scatter and attenuation medium without corrections, and scatter and attenuation medium with corrections.</p

Illustrations of model components.

<p>a). GATE model of Siemens Inveon SPECT system configured with two MGP collimators. b). MWB collimator. c). MOBY attenuation phantom.</p

Stacked bar plots of energy ratios and relative activity measurements.

<p>a). Low-to-high energy ratio e123 under different imaging conditions. b). Total ¹²³I activity in both high and low-energy windows.</p

Energy spectra of ¹²³I and ¹²⁵I for the MGP collimator.

<p>Energy spectra of ¹²³I and ¹²⁵I for the MGP collimator.</p

Estimated low-to-high energy (e123) ratios for selected organs in different sized mice.

<p>Estimated low-to-high energy (e123) ratios for selected organs in different sized mice.</p

Comparison of real and simulated data.

<p>The top row shows real data for the uncorrected low energy window, high energy window, and the corrected low energy window. The bottom row shows the same information but for the simulated MOBY phantom data.</p