Birth and rapid subcellular adaptation of a hominoid-specific CDC14 protein

Gene duplication was prevalent during hominoid evolution, yet little is known about the functional fate of new ape gene copies. We characterized the CDC14B cell cycle gene and the functional evolution of its hominoid-specific daughter gene, CDC14Bretro. We found that CDC14B encodes four different splice isoforms that show different subcellular localizations (nucleus or microtubule-associated) and functional properties. A microtubular CDC14B variant spawned CDC14Bretro through retroposition in the hominoid ancestor 18-25 million years ago (Mya). CDC14Bretro evolved brain-/testis-specific expression after the duplication event and experienced a short period of intense positive selection in the African ape ancestor 7-12 Mya. Using resurrected ancestral protein variants, we demonstrate that by virtue of amino acid substitutions in distinct protein regions during this time, the subcellular localization of CDC14Bretro progressively shifted from the association with microtubules (stabilizing them) to an association with the endoplasmic reticulum. CDC14Bretro evolution represents a paradigm example of rapid, selectively driven subcellular relocalization, thus revealing a novel mode for the emergence of new gene function

The prediction of speed and incline in outdoor running in humans using accelerometry.

PURPOSE: To explore whether triaxial accelerometric measurements can be utilized to accurately assess speed and incline of running in free-living conditions. METHODS: Body accelerations during running were recorded at the lower back and at the heel by a portable data logger in 20 human subjects, 10 men, and 10 women. After parameterizing body accelerations, two neural networks were designed to recognize each running pattern and calculate speed and incline. Each subject ran 18 times on outdoor roads at various speeds and inclines; 12 runs were used to calibrate the neural networks whereas the 6 other runs were used to validate the model. RESULTS: A small difference between the estimated and the actual values was observed: the square root of the mean square error (RMSE) was 0.12 m x s(-1) for speed and 0.014 radiant (rad) (or 1.4% in absolute value) for incline. Multiple regression analysis allowed accurate prediction of speed (RMSE = 0.14 m x s(-1)) but not of incline (RMSE = 0.026 rad or 2.6% slope). CONCLUSION: Triaxial accelerometric measurements allows an accurate estimation of speed of running and incline of terrain (the latter with more uncertainty). This will permit the validation of the energetic results generated on the treadmill as applied to more physiological unconstrained running conditions.

Assessing High-Speed Internet Access in the State of Iowa: Sixth Assessment, January 2008

This Assessment gauges the availability of highspeed Internet access to both rural and non-rural Iowans. The Board continues to evaluate the progress in the deployment of high-speed Internet access through this Sixth Assessment, including information related to Internet speeds available to consumers and pricing of high-speed Internet services. Comparison of this Assessment with the earlier efforts is critical if a clear perspective on the developing availability of high-speed Internet access to all residents of the State of Iowa is desired.

Spatio-temporal Brain Dynamics Mediating Post-error Behavioral Adjustments.

Optimal behavior relies on flexible adaptation to environmental requirements, notably based on the detection of errors. The impact of error detection on subsequent behavior typically manifests as a slowing down of RTs following errors. Precisely how errors impact the processing of subsequent stimuli and in turn shape behavior remains unresolved. To address these questions, we used an auditory spatial go/no-go task where continual feedback informed participants of whether they were too slow. We contrasted auditory-evoked potentials to left-lateralized go and right no-go stimuli as a function of performance on the preceding go stimuli, generating a 2 × 2 design with "preceding performance" (fast hit [FH], slow hit [SH]) and stimulus type (go, no-go) as within-subject factors. SH trials yielded SH trials on the following trials more often than did FHs, supporting our assumption that SHs engaged effects similar to errors. Electrophysiologically, auditory-evoked potentials modulated topographically as a function of preceding performance 80-110 msec poststimulus onset and then as a function of stimulus type at 110-140 msec, indicative of changes in the underlying brain networks. Source estimations revealed a stronger activity of prefrontal regions to stimuli after successful than error trials, followed by a stronger response of parietal areas to the no-go than go stimuli. We interpret these results in terms of a shift from a fast automatic to a slow controlled form of inhibitory control induced by the detection of errors, manifesting during low-level integration of task-relevant features of subsequent stimuli, which in turn influences response speed.

Critères de sélection et d'adaptation d'un instrument de mesure pour la recherche clinique

The goal of this paper is to provide clinicians and researchers, who may not be experts in psychometrics, with a guide for the selection and adaptation of an instrument for clinical research. Issues related to the concept to be measured, the targeted clientele, the selection criteria for the instrument (algorithm), the strategies for translation and adaptation, as well as potential bias related to the administration of an instrument are reviewed and discussed.

Calcium homeostasis in the central nervous system: adaptation to neurodegeneration.

Here we review the results of our recent studies on neurodegeneration together with data on cerebral calcium precipitation in animal models and humans. A model that integrates the diversity of mechanisms involved in neurodegeneration is presented and discussed based on the functional relevance of calcium precipitation.

Speed Limit Questions? Here’s Your Answer, February 8, 2010

Iowa’s speed regulations are based on the same basic speed law that is used in all 50 states: “Any person driving a motor vehicle on a highway shall drive the same at a careful and prudent speed not greater than nor less than is reasonable and proper, having due regard to the traffic, surface, and width of the highway and of any other conditions then existing, and no person shall drive any vehicle upon a highway at a speed greater than will permit the person to bring it to a stop within the assured clear distance ahead, such driver having the right to assume, however, that all persons using said highway will observe the law.” Statutory limits are based on the concept that uniform categories of highways can be traveled safely at certain preset maximum speeds under ideal conditions. Whether the speed limit is posted or unposted, drivers should reduce their speed below these values in poor weather, heavy traffic, and under other potentially hazardous conditions.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

Leaf area of common bean genotypes during early pod filling as related to plant adaptation to limited phosphorus supply

Low phosphorus supply markedly limits leaf growth and genotypes able to maintain adequate leaf area at low P could adapt better to limited-P conditions. This work aimed to investigate the relationship between leaf area production of common bean (Phaseolus vulgaris) genotypes during early pod filling and plant adaptation to limited P supply. Twenty-four genotypes, comprised of the four growth habits in the species and two weedy accessions, were grown at two P level applied to the soil (20 and 80 mg kg-1) in 4 kg pots and harvested at two growth stages (pod setting and early pod filling). High P level markedly increased the leaf number and leaf size (leaf area per leaf), slightly increased specific leaf area but did not affect the net assimilation rate. At low P level most genotypic variation for plant dry mass was associated with leaf size, whereas at high P level this variation was associated primarily with the number of leaves and secondarily with leaf size, specific leaf area playing a minor role at both P level. Determinate bush genotypes presented a smaller leaf area, fewer but larger leaves with higher specific leaf area and lower net assimilation rate. Climbing genotypes showed numerous leaves, smaller and thicker leaves with a higher net assimilation rate. Indeterminate bush and indeterminate prostrate genotypes presented the highest leaf area, achieved through intermediate leaf number, leaf size and specific leaf area. The latter groups were better adapted to limited P. It is concluded that improved growth at low P during early pod filling was associated with common bean genotypes able to maintain leaf expansion through leaves with greater individual leaf area.

Report of the Workshop on Intelligent Compaction for Soils and HMA, April 2-4, 2008

This document summarizes the discussion and findings of a workshop on intelligent compaction for soils and hot-mix asphalt held in West Des Moines, Iowa, on April 2–4, 2008. The objective of the meeting was to provide a collaborative exchange of ideas for developing research initiatives that accelerate implementation of intelligent compaction (IC) technologies for soil, aggregates, and hot mix asphalt. Technical presentations, working breakout sessions, a panel discussion, and a group implementation strategy session comprised the workshop activities. About 100 attendees representing state departments of transportation, Federal Highway Administration, contractors, equipment manufacturers, and researchers participated in the workshop.

Report of the Workshop on Intelligent Construction for Earthworks, April 14-16, 2008

This document summarizes the discussion and findings of a workshop on intelligent technologies for earthwork construction held in West Des Moines, Iowa, on April 14–16, 2009. This meeting follows a similar workshop conducted in 2008. The objective of the meeting was to provide a focused discussion on identifying research and implementation needs/strategies to advance intelligent compaction and automated machine guidance technologies. Technical presentations, interactive working breakout sessions, and a panel discussion comprised the workshop. About 100 attendees representing state departments of transportation, Federal Highway Administration, contractors, equipment manufacturers, and researchers participated in the workshop.