Train‐the‐trainer: Methodology to learn the cognitive interview

Research has indicated that police may not receive enough training in interviewing cooperative witnesses, specifically in use of the cognitive interview (CI). Practically, for the CI to be effective in real‐world investigations, police investigators must be trained by law enforcement trainers. We conducted a three‐phase experiment to examine the feasibility of training experienced law enforcement trainers who would then train others to conduct the CI. We instructed Federal Bureau of Investigation and local law enforcement trainers about the CI (Phase I); law enforcement trainers from both agencies (n = 4, 100% male, mean age = 50 years) instructed university students (n = 25, 59% female, mean age = 21 years) to conduct either the CI or a standard law enforcement interview (Phase II); the student interviewers then interviewed other student witnesses (n = 50, 73% female, mean age = 22 years), who had watched a simulated crime (phase III). Compared with standard training, interviews conducted by those trained by CI‐trained instructors contained more information and at a higher accuracy rate and with fewer suggestive questions.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147804/1/jip1518_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147804/2/jip1518.pd

Submaximal Oxygen Uptake Kinetics, Functional Mobility, and Physical Activity in Older Adults with Heart Failure and Reduced Ejection Fraction

Background: Submaximal oxygen uptake measures are more feasible and may better predict clinical cardiac outcomes than maximal tests in older adults with heart failure (HF). We examined relationships between maximal oxygen uptake, submaximal oxygen kinetics, functional mobility, and physical activity in older adults with HF and reduced ejection fraction. Methods: Older adults with HF and reduced ejection fraction (n = 25, age 75 ± 7 years) were compared to 25 healthy age- and gender-matched controls. Assessments included a maximal treadmill test for peak oxygen uptake (VO2peak), oxygen uptake kinetics at onset of and on recovery from a submaximal treadmill test, functional mobility testing [Get Up and Go (GUG), Comfortable Gait Speed (CGS), Unipedal Stance (US)], and self-reported physical activity (PA). Results: Compared to controls, HF had worse performance on GUG, CGS, and US, greater delays in submaximal oxygen uptake kinetics, and lower PA. In controls, VO2peak was more strongly associated with functional mobility and PA than submaximal oxygen uptake kinetics. In HF patients, submaximal oxygen uptake kinetics were similarly associated with GUG and CGS as VO2peak, but weakly associated with PA. Conclusions: Based on their mobility performance, older HF patients with reduced ejection fraction are at risk for adverse functional outcomes. In this population, submaximal oxygen uptake measures may be equivalent to VO2 peak in predicting functional mobility, and in addition to being more feasible, may provide better insight into how aerobic function relates to mobility in older adults with HF

Finding community structure in networks using the eigenvectors of matrices

We consider the problem of detecting communities or modules in networks, groups of vertices with a higher-than-average density of edges connecting them. Previous work indicates that a robust approach to this problem is the maximization of the benefit function known as "modularity" over possible divisions of a network. Here we show that this maximization process can be written in terms of the eigenspectrum of a matrix we call the modularity matrix, which plays a role in community detection similar to that played by the graph Laplacian in graph partitioning calculations. This result leads us to a number of possible algorithms for detecting community structure, as well as several other results, including a spectral measure of bipartite structure in networks and a new centrality measure that identifies those vertices that occupy central positions within the communities to which they belong. The algorithms and measures proposed are illustrated with applications to a variety of real-world complex networks.Comment: 22 pages, 8 figures, minor corrections in this versio

Ice cloud formation potential by free tropospheric particles from long-range transport over the Northern Atlantic Ocean

Long-range transported free tropospheric particles can play a significant role on heterogeneous ice nucleation. Using optical and electron microscopy we examine the physicochemical characteristics of ice nucleating particles (INPs). Particles were collected on substrates from the free troposphere at the remote Pico Mountain Observatory in the Azores Islands, after long-range transport and aging over the Atlantic Ocean. We investigate four specific events to study the ice formation potential by the collected particles with different ages and transport patterns. We use single-particle analysis, as well as bulk analysis to characterize particle populations. Both analyses show substantial differences in particle composition between samples from the four events; in addition, single-particle microscopy analysis indicates that most particles are coated by organic material. The identified INPs contained mixtures of dust, aged sea salt and soot, and organic material acquired either at the source or during transport. The temperature and relative humidity (RH) at which ice formed, varied only by 5% between samples, despite differences in particle composition, sources, and transport patterns. We hypothesize that this small variation in the onset RH may be due to the coating material on the particles. This study underscores and motivates the need to further investigate how long-range transported and atmospherically aged free tropospheric particles impact ice cloud formatio

Extremal Optimization for Graph Partitioning

Extremal optimization is a new general-purpose method for approximating solutions to hard optimization problems. We study the method in detail by way of the NP-hard graph partitioning problem. We discuss the scaling behavior of extremal optimization, focusing on the convergence of the average run as a function of runtime and system size. The method has a single free parameter, which we determine numerically and justify using a simple argument. Our numerical results demonstrate that on random graphs, extremal optimization maintains consistent accuracy for increasing system sizes, with an approximation error decreasing over runtime roughly as a power law t^(-0.4). On geometrically structured graphs, the scaling of results from the average run suggests that these are far from optimal, with large fluctuations between individual trials. But when only the best runs are considered, results consistent with theoretical arguments are recovered.Comment: 34 pages, RevTex4, 1 table and 20 ps-figures included, related papers available at http://www.physics.emory.edu/faculty/boettcher