The role of beach state and the timing of pre-storm surveys in determining the accuracy of storm impact assessments

Dune erosion principally occurs when water level exceeds the elevation of the beach and predicting erosion is progressively becoming more important for management as coastal populations increase, sea level rises, and storms become more powerful. This study assesses storm impacts using a simple model from Stockdon et al. (2007) configured with oceanographic information from the ADCIRC + SWAN model and frequently collected beach profiles. We applied that model to barrier islands in North Carolina including: Core Banks with a more dissipative beach morphology and Shackleford Banks and Onslow Beach with intermediate beach morphologies. The study periods captured 10 events where wave collision with the dunes and/or overwash were either predicted or observed, including large multiple-day events caused by hurricanes and smaller events caused by onshore winds and high tide. Comparing model output with a time series of beach photographs shows the predictive power and sensitivity of the model was consistently high at the Core Banks Site with its wide and low-gradient beach, high-elevation dunes (2.58 m), and high resistance to overwash. Model predictive power and sensitivity was lowest at the Shackleford Banks Site because frequent and large changes to beach slope and intermediate dune elevation (0.54–1.25 m) caused small variations of modeled total water level to either overpredict or underpredict storm impacts. In addition, storm impacts were always overpredicted during hurricanes at the Shackleford Banks Site, which was likely due to storm waves decreasing the beach slope from what was measured prior to the event and used as model input. Like Shackleford Banks, the beach slope of the Onslow Beach Site was steep and variable, but the low-elevation dunes (0.24–0.28 m) made resistance to overwash low and the predictive power and sensitivity of the model higher than at the Shackleford Banks Site. Results suggest that storm impacts and the associated potential for dune erosion is predicted more accurately at beaches where the threshold for overwash is high or low because total water level during most events will commonly fall short of or exceed the overwash threshold, respectively. The accuracy of predicting the storm impact regime is sensitive to beach slope. The slope of intermediate beaches is more variable than dissipative beaches and requires frequent measurement if it is to be represented accurately in the model, but this can be impractical and costly even using the latest drone-surveying methods. To maximize the accuracy of predicting storm impacts, intermediate beach morphology should be constrained by surveying at seasonal or yearly time scales and used as input to numerical models that estimate beach slope over short time scales (hours during an event or daily), configured with the latest wave and water-level forecasts

Resonant X ray photoelectron spectroscopy identification of atomic contributions to valence states

Valence electronic structure is crucial for understanding and predicting reactivity. Valence non resonant Xray photoelectron spectroscopy NRXPS provides a direct method for probing the overall valence electronic structure. However, it is often difficult to separate the varying contributions to NRXPS; for example, contributions of solutes in solvents or functional groups in complex molecules. In this work we show that valence resonant X ray photoelectron spectroscopy RXPS is a vital tool for obtaining atomic contributions to valence states. We combine RXPS with NRXPS and density functional theory calculations to demonstrate the validity of using RXPS to identify atomic contributions for a range of solutes both neutral and ionic and solvents both molecular solvents and ionic liquids . Furthermore, the one electron picture of RXPS holds for all of the closed shell molecules ions studied, although the situation for an open shell metal complex is more complicated. Factors needed to obtain a strong RXPS signal are investigated in order to predict the types of systems RXPS will work best for; a balance of element electronegativity and bonding type is found to be important. Additionally, the dependence of RXPS spectra on both varying solvation environment and varying local covalent bonding is probed. We find that RXPS is a promising fingerprint method for identifying species in solution, due to the spectral shape having a strong dependence on local covalency but a weak dependence on solvation environmen

Oscillatory networks of high-level mental alignment::A perspective-taking MEG study

Mentally imagining another's perspective is a high-level social process, reliant on manipulating internal representations of the self in an embodied manner. Recently Wang et al. (2016) showed that theta-band (3–7 Hz) brain oscillations within the right temporo-parietal junction (rTPJ) and brain regions coding for motor/body schema contribute to the process of perspective-taking. Using a similar paradigm, we set out to unravel the extended functional brain network in detail. Increasing the angle between self and other perspective was accompanied by longer reaction times and increases in theta power within rTPJ, right lateral prefrontal cortex (PFC) and right anterior cingulate cortex (ACC). Using Granger-causality, we showed that lateral PFC and ACC exert top-down influence over rTPJ, indicative of executive control processes required for managing conflicts between self and other perspectives. Finally, we quantified patterns of whole-brain phase coupling in relation to the rTPJ. Results suggest that rTPJ increases its theta-band phase synchrony with brain regions involved in mentalizing and regions coding for motor/body schema; whilst decreasing synchrony to visual regions. Implications for neurocognitive models are discussed, and it is proposed that rTPJ acts as a ‘hub’ to route bottom-up visual information to internal representations of the self during perspective-taking, co-ordinated by theta-band oscillations

Measurement of the Probability of Gluon Splitting into Charmed Quarks in Hadronic Z Decays

We have measured the probability, n(g->cc~), of a gluon splitting into a charm-quark pair using 1.7 million hadronic Z decays collected by the L3 detector. Two independent methods have been applied to events with a three-jet topology. One method relies on tagging charmed hadrons by identifying a lepton in the lowest energy jet. The other method uses a neural network based on global event shape parameters. Combining both methods, we measure n(g->cc~)= [2.45 +/- 0.29 +/- 0.53]%

Paleobiology of titanosaurs: reproduction, development, histology, pneumaticity, locomotion and neuroanatomy from the South American fossil record

Fil: García, Rodolfo A.. Instituto de Investigación en Paleobiología y Geología. Museo Provincial Carlos Ameghino. Cipolletti; ArgentinaFil: Salgado, Leonardo. Instituto de Investigación en Paleobiología y Geología. General Roca. Río Negro; ArgentinaFil: Fernández, Mariela. Inibioma-Centro Regional Universitario Bariloche. Bariloche. Río Negro; ArgentinaFil: Cerda, Ignacio A.. Instituto de Investigación en Paleobiología y Geología. Museo Provincial Carlos Ameghino. Cipolletti; ArgentinaFil: Carabajal, Ariana Paulina. Museo Carmen Funes. Plaza Huincul. Neuquén; ArgentinaFil: Otero, Alejandro. Museo de La Plata. Universidad Nacional de La Plata; ArgentinaFil: Coria, Rodolfo A.. Instituto de Paleobiología y Geología. Universidad Nacional de Río Negro. Neuquén; ArgentinaFil: Fiorelli, Lucas E.. Centro Regional de Investigaciones Científicas y Transferencia Tecnológica. Anillaco. La Rioja; Argentin

Brain oscillations and connectivity in autism spectrum disorders (ASD):new approaches to methodology, measurement and modelling

Although atypical social behaviour remains a key characterisation of ASD, the presence ofsensory and perceptual abnormalities has been given a more central role in recentclassification changes. An understanding of the origins of such aberrations could thus prove afruitful focus for ASD research. Early neurocognitive models of ASD suggested that thestudy of high frequency activity in the brain as a measure of cortical connectivity mightprovide the key to understanding the neural correlates of sensory and perceptual deviations inASD. As our review shows, the findings from subsequent research have been inconsistent,with a lack of agreement about the nature of any high frequency disturbances in ASD brains.Based on the application of new techniques using more sophisticated measures of brainsynchronisation, direction of information flow, and invoking the coupling between high andlow frequency bands, we propose a framework which could reconcile apparently conflictingfindings in this area and would be consistent both with emerging neurocognitive models ofautism and with the heterogeneity of the condition

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives