Health Service Use Predictors Among Trauma Survivors: A Critical Review.

This article had 2 aims: (a) to comprehensively review and synthesize the literature on predictors of health service utilization in survivors of traumatic events and posttraumatic stress disorder (PTSD) patients and (b) to discuss methodological issues in examining service utilization in this population. PsycINFO was searched for relevant articles published through April 2004. Included studies had to primarily sample trauma survivors or PTSD patients and statistically explore health service use determinants. Although some findings conflicted across studies, increased mental health service use was generally related to being female, having a previous trauma history, and having a PTSD diagnosis. Increased medical service use was found among those with a PTSD diagnosis. Methodological recommendations are made for future health service use studies. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Creating and Rendering Convolution Surfaces

Implicit surfaces obtained by convolution of multi-dimensional primitives with some potential function, are a generalisation of popular implicit surface models: blobs, metaballs and soft objects. These models differ in their choice of potential function but agree upon the use of underlying modelling primitives, namely, points. In this paper a method is described for modelling and rendering implicit surfaces built upon an expanded set of skeletal primitives: points, line segments, polygons, arcs and planes. An analytical solution to the convolution is described. This solution offers a more accurate and robust representation of the resultant implicit surface than previous methods. An algorithm for ray-tracing the surfaces formed through convolution of any combination of these primitives is also outlined.     

Direct Segmentation of Algebraic Models for Reverse Engineering

In Reverse Engineering a physical object is digitally reconstructed from a set of boundary points. In the segmentation phase these points are grouped into subsets to facilitate consecutive steps as surface fitting. In this paper we present a segmentation method with subsequent classification of simple algebraic surfaces. Our method is direct in the sense that it operates directly on the point set in contrast to other approaches that are based on a triangulation of the data set. The segmentation process involves a fast algorithm for k-nearest neighbors search and an estimation of first and second order surface properties. The first order segmentation, that is based on normal vectors, provides an initial subdivision of the surface and detects sharp edges as well as flat or highly curved areas. One of the main features of our method is to proceed by alternating the steps of segmentation and normal vector estimation. The second order segmentation subdivides the surface according to principal curvatures and provides a sufficient foundation for the classification of simple algebraic surfaces. If the boundary of the original object contains such surfaces the segmentation is optimized based on the result of a surface fitting procedure.     

Memory and Emotions for the September 11, 2001, Terrorist Attacks in Patients With Alzheimer's Disease, Patients With Mild Cognitive Impairment, and Healthy Older Adults.

National traumatic events can produce extremely vivid memories. Using a questionnaire administered during telephone interviews, the authors investigated emotional responses to, and memory for. the September 11, 2001, terrorist attacks in patients with Alzheimer's disease (AD), patients with mild cognitive impairment (MCI), and healthy older adults in the initial weeks following the event and again 3-4 months later. There were several notable findings. First, patients with AD showed less memory than patients with MCI and older adults. Second, patients with AD, but not patients with MCI or older adults, appeared to retain more memory for personal versus factual information. Third, patients with AD and older adults did not differ in the intensity of their reported emotional responses to the attacks, whereas patients with MCI reported relatively less intense emotional responses. Last, distortions of memory for personal information were frequent for all participants but were more common in patients with AD. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Wave propagation in delaminated beam

The wave propagation model investigated herein is based on the known fact that material discontinuities affect the propagation of elastic waves in solids. The change in certain material characteristics, such as a local change in stiffness or inertia caused by a crack or the presence of material damage, will affect the propagation of transmitted elastic waves and will modify the received signal. Wave frequencies associated with the highest detection sensitivity depend, among other things, on the type of structure, the type of material, and the type of damage. This paper presents a method of wave propagation, which can be further used to detect small delaminations in beam-like structures. The considered beam is modelled by spectral finite elements.     

A Dynamic Interaction Between Machine Learning and the Philosophy of Science

The relationship between machine learning and the philosophy of science can be classed as a dynamic interaction: a mutually beneficial connection between two autonomous fields that changes direction over time. I discuss the nature of this interaction and give a case study highlighting interactions between research on Bayesian networks in machine learning and research on causality and probability in the philosophy of science.     

Constraint Lingo: towards high‐level constraint programming

Logic programming requires that the programmer convert a problem into a set of constraints based on predicates. Choosing the predicates and introducing appropriate constraints can be intricate and error prone. If the problem domain is structured enough, we can let the programmer express the problem in terms of more abstract, higher‐level constraints. A compiler can then convert the higher‐level program into a logic‐programming formalism. The compiler writer can experiment with alternative low‐level representations of the higher‐level constraints in order to achieve a high‐quality translation. The programmer can then take advantage of both a reduction in complexity and an improvement in runtime speed for all problems within the domain. We apply this analysis to the domain of tabular constraint‐satisfaction problems. Examples of such problems include logic puzzles solvable on a hatch grid and combinatorial problems such as graph coloring and independent sets. The proper abstractions for these problems are rows, columns, entries, and their interactions. We present a higher‐level language, Constraint Lingo, dedicated to problems in this domain. We also describe how we translate programs from Constraint Lingo into lower‐level logic formalisms such as the logic of propositional schemata. These translations require that we choose among competing lower‐level representations in order to produce efficient results. The overall effectiveness of our approach depends on the appropriateness of Constraint Lingo, our ability to translate Constraint Lingo programs into high‐quality representations in logic formalisms, and the efficiency with which logic engines can compute answer sets. We comment on our computational experience with these tools in solving both graph problems and logic puzzles. Copyright © 2004 John Wiley & Sons, Ltd.     

Three-dimensional reconstruction of aqueous channels in human trabecular meshwork using light microscopy and confocal microscopy

Conventional two-dimensional imaging of the trabecular meshwork (TM) provides limited information about the size, shape, and interconnection of the aqueous channels within the meshwork. Understanding the three-dimensional (3-D) relationships of the channels within this tissue may give insight into its normal function and possible changes present in the eye disease glaucoma. The purpose of our study was to compare laser scanning confocal microscopy with standard 1 μm Araldite-embeddedhistologic sections for 3-D analysis of the trabecular meshwork. In addition, the study was done to determine whether computerized 3-D reconstruction could isolate the fluid spaces of the trabecular meshwork and determine the size of interconnections between the fluid spaces. Confocal microscopy appears comparable to 1 μm Araldite-embedded tissue sections and has the advantage of inherent registration of the serial tissue sections. Three-dimensional reconstruction allowed the isolation of the fluid spaces within the trabecular meshwork and revealed the presence of numerous interconnections between larger fluid spaces. The distribution of these interconnections was randomly arranged, with no predilection for specific regions within the trabecular meshwork. This distribution of constrictions and “expansion chambers” may provide a clue to the mechanism by which subtle histologic changes are associated with increased ocular pressure in glaucoma.     

Selecting and conserving lands for biodiversity: The role of remote sensing

A major focus of conservation is on protecting areas to ensure the persistence of biological diversity. Because such areas may be large, not easily accessible, subject to change, and sensitive to the surrounding landscape, remote sensing can be a valuable tool in establishing and managing protected areas. We describe three case studies to illustrate how remote sensing can contribute to setting priorities for conservation actions, monitoring the status of conservation targets, and evaluating the effectiveness of conservation strategies. In the Connecticut River watershed, remote sensing has been used to assess flood regimes and identify key areas of floodplain forests and their context for conservation planning. At Eglin Air Force Base in Florida, remote sensing has provided information to assess the effectiveness of management strategies to restore fire to the longleaf pine sandhills ecosystem, control invasive species, and prioritize annual prescribed burns. In eastern US forests, remote sensing is being used to evaluate the ecological condition and changes at properties where direct access would be difficult.As the resolution and capacities of remote-sensing technology continue to develop, however, several issues are becoming increasingly important. It is essential that the spatial and temporal resolution of remote-sensing data be matched to the relevant scales of biodiversity, major threats, and management actions. Data layers must be compatible, both in scale and in measurement properties, and key patterns must be distinguished from irrelevant detail, especially at the finer scales of application in local management. Combining remote sensing with ground surveys can expand the array of information used in management and contribute to the ecological interpretation of remote-sensing data. Because conservation funds are always limited, remote sensing also must be cost effective. This requires balancing the wealth of detail afforded by ever-finer resolution of remote-sensing data with what is actually needed to implement sound conservation and management. Remote sensing is a valuable tool, but it is not a panacea for all of the challenges of conservation monitoring and management.