Early bursts of body size and shape evolution are rare in comparative data

George Gaylord Simpson famously postulated that much of life's diversity originated as adaptive radiations-more or less simultaneous divergences of numerous lines from a single ancestral adaptive type. However, identifying adaptive radiations has proven difficult due to a lack of broad-scale comparative datasets. Here, we use phylogenetic comparative data on body size and shape in a diversity of animal clades to test a key model of adaptive radiation, in which initially rapid morphological evolution is followed by relative stasis. We compared the fit of this model to both single selective peak and random walk models. We found little support for the early-burst model of adaptive radiation, whereas both other models, particularly that of selective peaks, were commonly supported. In addition, we found that the net rate of morphological evolution varied inversely with clade age. The youngest clades appear to evolve most rapidly because long-term change typically does not attain the amount of divergence predicted from rates measured over short time scales. Across our entire analysis, the dominant pattern was one of constraints shaping evolution continually through time rather than rapid evolution followed by stasis. We suggest that the classical model of adaptive radiation, where morphological evolution is initially rapid and slows through time, may be rare in comparative data.

Increasing Utilization of US Electric Grids via Smart Technologies: Integration of Load Management, Real Time Pricing, Renewables, EVs and Smart Grid Sensors

Electric power grids throughout the world suffer from serious inefficiencies associated with under-utilization due to demand patterns, engineering design and load following approaches in use today. These grids consume much of the world’s energy and represent a large carbon footprint. From material utilization perspectives significant hardware is manufactured and installed for this infrastructure often to be used at less than 20-40% of its operational capacity for most of its lifetime. These inefficiencies lead engineers to require additional grid support and conventional generation capacity additions when renewable technologies (such as solar and wind) and electric vehicles are to be added to the utility demand/supply mix. Using actual data from the PJM [PJM 2009] the work shows that consumer load management, real time price signals, sensors and intelligent demand/supply control offer a compelling path forward to increase the efficient utilization and carbon footprint reduction of the world’s grids. Underutilization factors from many distribution companies indicate that distribution feeders are often operated at only 70-80% of their peak capacity for a few hours per year, and on average are loaded to less than 30-40% of their capability. By creating strong societal connections between consumers and energy providers technology can radically change this situation. Intelligent deployment of smart sensors, smart electric vehicles, consumer-based load management technology very high saturations of intermittent renewable energy supplies can be effectively controlled and dispatched to increase the levels of utilization of existing utility distribution, substation, transmission, and generation equipment. The strengthening of these technology, society and consumer relationships requires rapid dissemination of knowledge (real time prices, costs & benefit sharing, demand response requirements) in order to incentivize behaviors that can increase the effective use of technological equipment that represents one of the largest capital assets modern society has created.

Provenance signature of a forearc basin modified by spreading ridge subduction: Detrital zircon geochronology and detrital modes from the Paleogene Arkose Ridge Formation, southern Alaska

Upper Paleocene–Eocene boulder conglomerate, cross-stratified sandstone, and laminated carbonaceous mudstone of the Arkose Ridge Formation exposed in the southern Talkeetna Mountains record fluvial-lacustrine deposition proximal to the volcanic arc in a forearc basin modified by Paleogene spreading ridge subduction beneath southern Alaska. U-Pb ages of detrital zircon grains and modal analyses were obtained from stratigraphic sections spanning the 2,000 m thick Arkose Ridge Formation in order to constrain the lithology, age, and location of sediment sources that provided detritus. Detrital modes from 24 conglomerate beds and 54 sandstone thin sections aredominated by plutonic and volcanic clasts and plagioclase feldspar with minor quartz, schist, hornblende, argillite, and metabasalt. Westernmost sandstone and conglomerate strata contain <5% volcanic clasts whereas easternmost sandstone and conglomerate strata contain 40 to >80% volcanic clasts. Temporally, eastern sandstones andconglomerates exhibit an upsection increase in volcanic detritus from <40 to >80% volcanic clasts. U-Pb ages from >1400 detrital zircons in 15 sandstone samples reveal three main populations: late Paleocene–Eocene (60-48 Ma; 16% of all grains), Late Cretaceous–early Paleocene (85–60 Ma; 62%) and Jurassic–Early Cretaceous (200–100 Ma; 12%). A plot of U/Th vs U-Pb ages shows that >97% of zircons are <200 Ma and>99% of zircons have <10 U/Th ratios, consistent with mainly igneous source terranes. Strata show increased enrichment in late Paleocene–Eocene detrital zircons from <2% in the west to >25% in the east. In eastern sections, this younger age population increases temporally from 0% in the lower 50 m of the section to >40% in samples collected >740 m above the base. Integration of the compositional and detrital geochronologic data suggests: (1) Detritus was eroded mainly from igneous sources exposed directly north of the Arkose Ridge Formation strata, mainly Jurassic–Paleocene plutons and Paleocene–Eocenevolcanic centers. Subordinate metamorphic detritus was eroded from western Mesozoic low-grade metamorphic sources. Subordinate sedimentary detritus was eroded from eastern Mesozoic sedimentary sources. (2) Eastern deposystems received higher proportions of juvenile volcanic detritus through time, consistent with construction of adjacent slab-window volcanic centers during Arkose Ridge Formation deposition. (3)Western deposystems transported detritus from Jurassic–Paleocene arc plutons that flank the northwestern basin margin. (4) Metasedimentary strata of the Chugach accretionaryprism, exposed 20-50 km south of the Arkose Ridge Formation, did not contribute abundant detritus. Conventional provenance models predict reduced input of volcanic detritus to forearc basins during exhumation of the volcanic edifice and increasing exposure ofsubvolcanic plutons (Dickinson, 1995; Ingersoll and Eastmond, 2007). In the forearc strata of these conventional models, sandstone modal analyses record progressive increases upsection in quartz and feldspar concomitant with decreases in lithic grains, mainly volcanic lithics. Additionally, as the arc massif denudes through time, theyoungest detrital U-Pb zircon age populations become significantly older than the age of forearc deposition as the arc migrates inboard or ceases magmatism. Westernmost strata of the Arkose Ridge Formation are consistent with this conventional model. However, easternmost strata of the Arkose Ridge Formation contain sandstone modes that record an upsection increase in lithic grains accompanied by a decrease in quartz and feldspar, and detrital zircon age populations that closely match the age of deposition. This deviation from the conventional model is due to the proximity of the easternmost strata to adjacent juvenile volcanic rocks emplaced by slab-window volcanic processes. Provenance data from the Arkose Ridge Formation show that forearc basins modified by spreading ridge subduction may record upsection increases in non-arc, syndepositional volcanic detritusdue to contemporaneous accumulation of thick volcanic sequences at slab-window volcanic centers. This change may occur locally at the same time that other regions of the forearc continue to receive increasing amounts of plutonic detritus as the remnant arc denudes, resulting in complex lateral variations in forearc basin petrofacies and chronofacies.

Application of 3D documentation and geometric reconstruction methods in traffic accident analysis: with high resolution surface scanning, radiological MSCT/MRI scanning and real data based animation

The examination of traffic accidents is daily routine in forensic medicine. An important question in the analysis of the victims of traffic accidents, for example in collisions between motor vehicles and pedestrians or cyclists, is the situation of the impact. Apart from forensic medical examinations (external examination and autopsy), three-dimensional technologies and methods are gaining importance in forensic investigations. Besides the post-mortem multi-slice computed tomography (MSCT) and magnetic resonance imaging (MRI) for the documentation and analysis of internal findings, highly precise 3D surface scanning is employed for the documentation of the external body findings and of injury-inflicting instruments. The correlation of injuries of the body to the injury-inflicting object and the accident mechanism are of great importance. The applied methods include documentation of the external and internal body and the involved vehicles and inflicting tools as well as the analysis of the acquired data. The body surface and the accident vehicles with their damages were digitized by 3D surface scanning. For the internal findings of the body, post-mortem MSCT and MRI were used. The analysis included the processing of the obtained data to 3D models, determination of the driving direction of the vehicle, correlation of injuries to the vehicle damages, geometric determination of the impact situation and evaluation of further findings of the accident. In the following article, the benefits of the 3D documentation and computer-assisted, drawn-to-scale 3D comparisons of the relevant injuries with the damages to the vehicle in the analysis of the course of accidents, especially with regard to the impact situation, are shown on two examined cases.

On Time Series Analysis of Public Health and Biomedical Data

A time series is a sequence of observations made over time. Examples in public health include daily ozone concentrations, weekly admissions to an emergency department or annual expenditures on health care in the United States. Time series models are used to describe the dependence of the response at each time on predictor variables including covariates and possibly previous values in the series. Time series methods are necessary to account for the correlation among repeated responses over time. This paper gives an overview of time series ideas and methods used in public health research.

Connectionism as metaphor: Towards an integrated, unified conception of self-system and individual difference

Comments on an article by Kashima et al. (see record 2007-10111-001). In their target article Kashima and colleagues try to show how a connectionist model conceptualization of the self is best suited to capture the self's temporal and socio-culturally contextualized nature. They propose a new model and to support this model, the authors conduct computer simulations of psychological phenomena whose importance for the self has long been clear, even if not formally modeled, such as imitation, and learning of sequence and narrative. As explicated when we advocated connectionist models as a metaphor for self in Mischel and Morf (2003), we fully endorse the utility of such a metaphor, as these models have some of the processing characteristics necessary for capturing key aspects and functions of a dynamic cognitive-affective self-system. As elaborated in that chapter, we see as their principal strength that connectionist models can take account of multiple simultaneous processes without invoking a single central control. All outputs reflect a distributed pattern of activation across a large number of simple processing units, the nature of which depends on (and changes with) the connection weights between the links and the satisfaction of mutual constraints across these links (Rummelhart & McClelland, 1986). This allows a simple account for why certain input features will at times predominate, while others take over on other occasions. (PsycINFO Database Record (c) 2008 APA, all rights reserved)

Climate-induced interannual variability of marine primary and export production in three global coupled climate carbon cycle models

Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP) and export production (EP) of particulate organic carbon (POC). Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR) are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation). Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006) with stronger stratification (higher sea surface temperature; SST) being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL) also reproduces the inverse relationship between stratification (SST) and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.

Book Review of “Human Behaviour and the Social Environment: Models, Metaphors, and Maps for Applying Theoretical Perspectives to Practice”. 640 pages, Thomson Brooks/Cole, 2007, by James A. Forte

This voluminous book which draws on almost 1000 references provides an important theoretical base for practice. After an informative introduction about models, maps and metaphors, Forte provides an impressive presentation of several perspectives for use in practice; applied ecological theory, applied system theory, applied biology, applied cognitive science, applied psychodynamic theory, applied behaviourism, applied symbolic interactionism, applied social role theory, applied economic theory, and applied critical theory. Finally he completes his book with a chapter on “Multi theory practice and routes to integration.”

Curricular Integration of Simulations in Neuroscience - Instructional and Technical Perspectives

In recent years interactive media and tools, like scientific simulations and simulation environments or dynamic data visualizations, became established methods in the neural and cognitive sciences. Hence, university teachers of neural and cognitive sciences are faced with the challenge to integrate these media into the neuroscientific curriculum. Especially simulations and dynamic visualizations offer great opportunities for teachers and learners, since they are both illustrative and explorable. However, simulations bear instructional problems: they are abstract, demand some computer skills and conceptual knowledge about what simulations intend to explain. By following two central questions this article provides an overview on possible approaches to be applied in neuroscience education and opens perspectives for their curricular integration: (i) How can complex scientific media be transformed for educational use in an efficient and (for students on all levels) comprehensible manner and (ii) by what technical infrastructure can this transformation be supported? Exemplified by educational simulations for the neurosciences and their application in courses, answers to these questions are proposed a) by introducing a specific educational simulation approach for the neurosciences b) by introducing an e-learning environment for simulations, and c) by providing examples of curricular integration on different levels which might help academic teachers to integrate newly created or existing interactive educational resources in their courses.

Integration of WSNs into enterprise systems based on semantic physical business entities

Internet of Things based systems are anticipated to gain widespread use in industrial applications. Standardization efforts, like 6L0WPAN and the Constrained Application Protocol (CoAP) have made the integration of wireless sensor nodes possible using Internet technology and web-like access to data (RESTful service access). While there are still some open issues, the interoperability problem in the lower layers can now be considered solved from an enterprise software vendors' point of view. One possible next step towards integration of real-world objects into enterprise systems and solving the corresponding interoperability problems at higher levels is to use semantic web technologies. We introduce an abstraction of real-world objects, called Semantic Physical Business Entities (SPBE), using Linked Data principles. We show that this abstraction nicely fits into enterprise systems, as SPBEs allow a business object centric view on real-world objects, instead of a pure device centric view. The interdependencies between how currently services in an enterprise system are used and how this can be done in a semantic real-world aware enterprise system are outlined, arguing for the need of semantic services and semantic knowledge repositories. We introduce a lightweight query language, which we use to perform a quantitative analysis of our approach to demonstrate its feasibility.

Role of diuretics, blockers, and statins in increasing the risk of diabetes in patients with impaired glucose tolerance: reanalysis of data from the NAVIGATOR study

OBJECTIVE To examine the degree to which use of β blockers, statins, and diuretics in patients with impaired glucose tolerance and other cardiovascular risk factors is associated with new onset diabetes. DESIGN Reanalysis of data from the Nateglinide and Valsartan in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR) trial. SETTING NAVIGATOR trial. PARTICIPANTS Patients who at baseline (enrolment) were treatment naïve to β blockers (n=5640), diuretics (n=6346), statins (n=6146), and calcium channel blockers (n=6294). Use of calcium channel blocker was used as a metabolically neutral control. MAIN OUTCOME MEASURES Development of new onset diabetes diagnosed by standard plasma glucose level in all participants and confirmed with glucose tolerance testing within 12 weeks after the increased glucose value was recorded. The relation between each treatment and new onset diabetes was evaluated using marginal structural models for causal inference, to account for time dependent confounding in treatment assignment. RESULTS During the median five years of follow-up, β blockers were started in 915 (16.2%) patients, diuretics in 1316 (20.7%), statins in 1353 (22.0%), and calcium channel blockers in 1171 (18.6%). After adjusting for baseline characteristics and time varying confounders, diuretics and statins were both associated with an increased risk of new onset diabetes (hazard ratio 1.23, 95% confidence interval 1.06 to 1.44, and 1.32, 1.14 to 1.48, respectively), whereas β blockers and calcium channel blockers were not associated with new onset diabetes (1.10, 0.92 to 1.31, and 0.95, 0.79 to 1.13, respectively). CONCLUSIONS Among people with impaired glucose tolerance and other cardiovascular risk factors and with serial glucose measurements, diuretics and statins were associated with an increased risk of new onset diabetes, whereas the effect of β blockers was non-significant.