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In his book, "Identity and the Museum Visitor Experience," John Falk makes the case that by understanding the underlying motivations that drive a visitor, a museum can create an experience that reflects a person's identity and therefore satisfy their motivation for visiting. According to Falk, this level of personal connection increases meaningfulness to the visit. This, in turn, helps a museum develop and sustain a community of learners, and ultimately attendance and revenue. A network of nine cultural institutions in Denver utilized Falk's instrument to gain a "snap-shot" of what motivates museum-goers in one metropolitan community. The study, which employed the Falk Visitor Identity-Related Motivation Typology, and its results, is presented in this article. Further, Denver Zoo outlines how it has used the data from the Falk study to rethink and enhance staff professional development, program development and learning outcomes, and marketing. (Contains 12 notes.)

Parametric and nonparametric approaches to evaluate land-cover change detection using very high resolution (VHR) satellite imagery are applied to the analysis of the demolition of the Rocky Flats nuclear weapons facility located near Denver, CO. Both maximum-likelihood and neural network classifiers are used to validate a new parallel architecture which improves the accuracy when applied to VHR satellite imagery for the study of land-cover change between sequential satellite acquisitions. An enhancement of about 14% was found between the single-step classification and the new parallel architecture, confirming the advantage and the robust improvement obtained with this architecture regardless of the classification algorithm used. In this paper, we demonstrate and document the demolition and removal of hundreds of buildings taken down to bare soil between 2003 and 2005 at the Rocky Flats site. [ABSTRACT FROM AUTHOR]

The Study to Explore Early Development (SEED) is a multi-site case-control study designed to explore the relationship between autism spectrum disorder (ASD) phenotypes and etiologies. The goals of this paper are to (1) describe the SEED algorithm that uses the Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule (ADOS) to classify children with ASD, (2) examine psychometric properties of different ASD classification methods, including the SEED method that incorporates rules for resolving ADI-R and ADOS discordance, and (3) determine whether restricted interests and repetitive behaviors were noted for children who had instrument discordance resolved using ADI-R social and communication scores. Results support the utility of SEED criteria when well-defined groups of children are an important clinical or research outcome. [ABSTRACT FROM AUTHOR]

Takeoff and landing maneuvers can be particularly hazardous at airports surrounded by complex terrain. To address this situation, the Federal Aviation Administration has developed a precipitous terrain classification as a way to impose more restrictive terrain clearances in the vicinity of complex terrain and to mitigate possible altimeter errors and pilot control problems experienced while executing instrument approach procedures. The current precipitous point value (PPV) algorithm relies on the terrain characteristics within a local area of 2 n mi (3.7 km) in radius and is therefore static in time. In this work, we investigate the role of meteorological effects leading to potential aviation hazards over complex terrain, namely, turbulence, altimeter-setting errors, and density-altitude deviations. To that end, we combine observations with high-resolution numerical weather forecasts within a 28 3 28 region over the Rocky Mountains in Colorado containing three airports that are surrounded by precipitous terrain. Both available turbulence reports and model's turbulence forecasts show little correlation with the PPV algorithm for the region analyzed, indicating that the static terrain characteristics cannot generally be used to reliably capture hazardous low-level turbulence events. Altimeter-setting errors and densityaltitude effects are also found to be only very weakly correlated with the PPV algorithm. Altimeter-setting errors contribute to hazardous conditions mainly during cold seasons, driven by synoptic weather systems, whereas density-altitude effects are on the contrary predominantly present during the spring and summer months and follow a very well-marked diurnal evolution modulated by surface radiative effects. These findings demonstrate the effectiveness of high-resolution weather forecast information in determining aviation-relevant hazardous conditions over complex terrain. [ABSTRACT FROM AUTHOR]

The authors examined the implications of test differences for defining and diagnosing comprehension deficits using reading comprehension tests. They had 995 children complete the Gray Oral Reading Test–3, the Qualitative Reading Inventory–3, the Woodcock–Johnson Passage Comprehension–3, and the Peabody Individual Achievement Test and compared which children were identified by each test as being in the lowest 10%. Although a child who performs so poorly might be expected to do poorly on all tests, the authors found that the average overlap between tests in diagnosing comprehension difficulties was only 43%. Consistency in diagnosis was greater for younger children, when comprehension deficits are the result of weaker decoding skills, than for older children. Inconsistencies between tests were just as evident when identifying the top performers. The different children identified as having a comprehension deficit by each test were compared on four profile variables—word decoding skill, IQ, ADHD symptoms, and working memory skill—to understand the nature of the different deficits assessed by each test. Theoretical and practical implications of these test differences in defining and diagnosing comprehension deficits are discussed. [ABSTRACT FROM PUBLISHER]

In this article the authors consider the problem of identifying geographically homogeneous regions based on similarities in the temporal dynamics of weather patterns. The authors propose two disparity measures and apply them to cluster time series of observed monthly temperatures from locations across Colorado. The two disparity measures are based on state-space models, where the monthly temperature anomaly dynamics and seasonal variation are represented by latent processes. They find that the disparity measures produce clusters consistent with known atmospheric flow structures.