Improved wetland remote sensing in Yellowstone National Park using classification trees to combine TM imagery and ancillary environmental data

The U.S. Fish and Wildlife Service uses the term palustrine wetland to describe vegetated wetlands traditionally identified as marsh, bog, fen, swamp, or wet meadow. Landsat TM imagery was combined with image texture and ancillary environmental data to model probabilities of palustrine wetland occurrence in Yellowstone National Park using classification trees. Model training and test locations were identified from National Wetlands Inventory maps, and classification trees were built for seven years spanning a range of annual precipitation. At a coarse level, palustrine wetland was separated from upland. At a finer level, five palustrine wetland types were discriminated: aquatic bed (PAB), emergent (PEM), forested (PFO), scrub-shrub (PSS), and unconsolidated shore (PUS). TM-derived variables alone were relatively accurate at separating wetland from upland, but model error rates dropped incrementally as image texture, DEM-derived terrain variables, and other ancillary GIS layers were added. For classification trees making use of all available predictors, average overall test error rates were 7.8% for palustrine wetland/upland models and 17.0% for palustrine wetland type models, with consistent accuracies across years. However, models were prone to wetland over-prediction. While the predominant PEM class was classified with omission and commission error rates less than 14%, we had difficulty identifying the PAB and PSS classes. Ancillary vegetation information greatly improved PSS classification and moderately improved PFO discrimination. Association with geothermal areas distinguished PUS wetlands. Wetland over-prediction was exacerbated by class imbalance in likely combination with spatial and spectral limitations of the TM sensor. Wetland probability surfaces may be more informative than hard classification, and appear to respond to climate-driven wetland variability. The developed method is portable, relatively easy to implement, and should be applicable in other settings and over larger extents.     

The impact of misregistration on SRTM and DEM image differences

Image differences between Shuttle Radar Topography Mission (SRTM) data and other Digital Elevation Models (DEMs) are often performed for either accuracy assessment or for estimating vegetation height across the landscape. It has been widely assumed that the effect of sub-pixel misregistration between the two models on resultant image differences is negligible, yet this has not previously been tested in detail. The aim of this study was to determine the impact that various levels of misregistration have on image differences between SRTM and DEMs. First, very accurate image co-registration was performed at two study sites between higher resolution DEMs and SRTM data, and then image differences (SRTM–DEM) were performed after various levels of misregistration were systematically introduced into the SRTM data. It was found that: (1) misregistration caused an erroneous and dominant correlation between elevation difference and aspect across the landscape; (2) the direction of the misregistration defined the direction of this erroneous and systematic elevation difference; (3) for sub-pixel misregistration the error due solely to misregistration was greater than, or equal to the true difference between the two models for substantial proportions of the landscape (e.g., greater than 33% of the area for a half-pixel misregistration); and (4) the strength of the erroneous relationship with aspect was enhanced by steeper terrain. Spatial comparisons of DEMs were found to be sensitive to even sub-pixel misregistration between the two models, which resulted in a strong erroneous correlation with aspect. This misregistration induced correlation with aspect is not likely specific to SRTM data only; we expect it to be a generic relationship present in any DEM image difference analysis.     

Artefacts au cours de la préparation de coupes de grains d'amidon. Etude par microscopie photonique et électronique

Artefacts During the Preparation of Sections of Starch Granules. Studies under Light and Electron Microscope. Dark bands which are usually observed in ultrathin sections of starch granules, „coloured”︁ or not, have been considered by some authors as marking the presence of protidic substances, by others as artefacts of sectioning, on account of the diversity of their shapes and the frequency of their appearance. Examinations under light microscope show that this phenomenon appears effectively, during the sectioning of the inclusion block, when the ultrathin section of starch comes into contact with the surface of water in the collecting tank and then swells. The examination under electron microscope of ultrathin sections shadowed with gold, allows us to show that these dark bands are the consequence of surface folding of the cut starch grains. The measurements of electron density show that there are folds like S or double folds like S, and that electron transmission across the sample follows a logarithmic rule. A discussion leads to think that these artefacts are the consequence of a defective permeation of starch with the inclusion material and the result of starch water affinity. We must definitely leave out that dark bands should be a manifestation of protidic material.     

Microscopic Effects of Ultrasound on the Structure of Potato Starch Preliminary Study

This preliminary study has related the nature of rupture in starch grains, induced by ultrasound, to the ambient atmosphere, the concentration of the suspension, the frequency and the time of irradiation. It has been tentatively concluded that principally mechanical effects have been induced under conditions that would promote vaporous cavitation (280 KHz, 15 W/cm²). In an atmosphere of hydrogen, many deep conical pits are produced. In an atmosphere of air or oxygen, deep pitting is somewhat less pronounced than in hydrogen but injury to other parts of the surface is greater. Virtually no effect is produced in vacuo, and under carbon dioxide the effect is very weak. The extent of damage increases with time of radiation and decreases with increasing concentration of starch in the suspension. It is suggested that damage produced by ultrasound indicates a primarily radial structure of submicroscopic units in the starch grain. Explanations proposed for the effects observed must be tested in further experiments.     

Spanish Content on Hospital Websites: An Analysis of U.S. Hospitals' in Concentrated Latino Communities

This study explores the nature and extent of Spanish language translation of hospital websites. A quantitative content analysis of 121 U.S. hospital websites located in Hispanic communities was conducted. Results indicate that a significant number of U.S. hospitals fail on their websites to offer equal content for Spanish language users. The study also examines several factors potentially associated with the incidence of website translation. First, organizational factors such as hospital size, ownership type and formal statements of diversity commitment are investigated. Second, demographic factors such as county population size and Hispanic population size are also considered. Hispanics' use of the Internet, the digital divide, culture's impact on Internet use, and eHealth provide a background for discussion of the findings.     

Crosslinking effect on polydimethylsiloxane elastic modulus measured by custom‐built compression instrument

A macroscopic compression test utilizing a simple custom‐built instrument was employed to measure polydimethylsiloxane (PDMS) elastic modulus. PDMS samples with varying crosslinking density were prepared with the elastomer base to the curing agent ratio ranging from 5 : 1 to 33 : 1. The PDMS network elastic modulus varied linearly with the amount of crosslinker, ranging from 0.57 MPa to 3.7 MPa for the samples tested. PDMS elastic modulus in MPa can be expressed as 20 MPa/PDMS base to curing agent ratio. This article describes a simple method for measuring elastic properties of soft polymeric materials. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 41050.     

Cover Picture: Length‐Dependent Uptake of DNA‐Wrapped Single‐Walled Carbon Nanotubes (Adv. Mater. 7/2007)

Well‐defined length fractions of DNA‐wrapped single‐walled carbon nanotubes (SWNTs) of below 200 nm are taken up preferentially by IMR‐90 human lung fibroblasts, while longer DNA wrapped SWNTs are excluded from the cell interior (inset), report Matt Becker and coworkers on p. 939. The cover image construct includes overlaid images of the labeled cell membrane, the nuclei (blue), and the fluorescently labeled DNA wrapped SWNTs (red) that have gained access to the cell interior.     

Neuroticism and depressive symptoms among spouse caregivers: Do health behaviors mediate this relationship?

This study examined the mediating role of health behaviors in the relationship between neuroticism and depressive symptoms among spouse caregivers. Path analysis was used to test a model of the caregiver stress process among 233 caregivers of people with dementia. Results indicate that neuroticism has a significant direct effect on depressive symptoms and also indirectly influences depressive symptoms through health behaviors and perceived stress. When individual health behaviors were examined in the path model, only physical activity served a significant mediating role. These findings suggest that neuroticism may lead to depressive symptoms among caregivers partly through declines in physical activity. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Perceptron-based learning algorithms

A key task for connectionist research is the development and analysis of learning algorithms. An examination is made of several supervised learning algorithms for single-cell and network models. The heart of these algorithms is the pocket algorithm, a modification of perceptron learning that makes perceptron learning well-behaved with nonseparable training data, even if the data are noisy and contradictory. Features of these algorithms include speed algorithms fast enough to handle large sets of training data; network scaling properties, i.e. network methods scale up almost as well as single-cell models when the number of inputs is increased; analytic tractability, i.e. upper bounds on classification error are derivable; online learning, i.e. some variants can learn continually, without referring to previous data; and winner-take-all groups or choice groups, i.e. algorithms can be adapted to select one out of a number of possible classifications. These learning algorithms are suitable for applications in machine learning, pattern recognition, and connectionist expert systems.     

Problematic aspects of diagnosing premenstrual phase dysphoria: Recommendations for psychological research and practice.

A gender-specific psychiatric diagnosis, named after an aspect of normal menstrual cycle physiology ("Late Luteal Phase" Dysphoric Disorder, or LLPD), is currently being considered for full diagnostic status in the upcoming catalog of psychiatric disorders, the DSM-IV. Psychologists have had surprisingly little voice in the ongoing debate about LLPD, despite the severe methodological difficulties involved in establishing reliability and validity for the proposed diagnosis. To stimulate research contributions by psychologists, we discuss the risks for over- and underdiagnosis, identify gaps in knowledge, and highlight specific empirical questions that require attention if the debate is to be informed by assessments with demonstrated and acceptable levels of reliability and validity. (PsycINFO Database Record (c) 2010 APA, all rights reserved)