Potential structural materials and design concepts for light airplanes Final report

Potential structural materials and design concepts evaluated for light aircraft application

Potential Structural Materials and Design Concepts for Light Airplanes

Potential structural materials and design considerations for helicopters and light general aircraf

Transformation of stimulus correlations by the retina

Redundancies and correlations in the responses of sensory neurons seem to waste neural resources but can carry cues about structured stimuli and may help the brain to correct for response errors. To assess how the retina negotiates this tradeoff, we measured simultaneous responses from populations of ganglion cells presented with natural and artificial stimuli that varied greatly in correlation structure. We found that pairwise correlations in the retinal output remained similar across stimuli with widely different spatio-temporal correlations including white noise and natural movies. Meanwhile, purely spatial correlations tended to increase correlations in the retinal response. Responding to more correlated stimuli, ganglion cells had faster temporal kernels and tended to have stronger surrounds. These properties of individual cells, along with gain changes that opposed changes in effective contrast at the ganglion cell input, largely explained the similarity of pairwise correlations across stimuli where receptive field measurements were possible.Comment: author list corrected in metadat

Biophysical homoeostasis of leaf temperature: a neglected process for vegetation and land-surface modelling

Aim Leaf and air temperatures are seldom equal, but many vegetation models assume that they are. Land-surface models calculate canopy temperatures, but how well they do so is unknown. We encourage consideration of the leaf- and canopy-to-air temperature difference (ΔΤ) as a benchmark for land-surface modelling and an important feature of plant and ecosystem function. Location Tropical SW China. Time period 2013. Major Taxa studies Tropical trees. Methods We illustrate diurnal cycles of leaf- and canopy-to-air temperature difference (ΔΤ) with field measurements in a tropical dry woodland and with continuous monitoring data in a tropical seasonal forest. The Priestley–Taylor (PT) and Penman–Monteith (PM) approaches to evapotranspiration are used to provide insights into the interpretation and prediction of ΔT. Field measurements are also compared with land-surface model results obtained with the Joint U.K. Land Environment Simulator (JULES) set up for the conditions of the site. Results The ΔT followed a consistent diurnal cycle, with negative values at night (attributable to negative net radiation) becoming positive in the morning, reaching a plateau and becoming negative again when air temperature exceeded a ‘crossover’ in the 24–29 °C range. Daily time courses of ΔT could be approximated by either the PT or the PM model, but JULES tended to underestimate the magnitude of negative ΔT. Main conclusions Leaves with adequate water supply are partly buffered against air-temperature variations, through a passive biophysical mechanism. This is likely to be important for optimal leaf function, and land-surface and vegetation models should aim to reproduce it

Responses of leaf traits to climatic gradients: adaptive variation versus compositional shifts

Dynamic global vegetation models (DGVMs) typically rely on plant functional types (PFTs), which are assigned distinct environmental tolerances and replace one another progressively along environmental gradients. Fixed values of traits are assigned to each PFT; modelled trait variation along gradients is thus driven by PFT replacement. But empirical studies have revealed "universal" scaling relationships (quantitative trait variations with climate that are similar within and between species, PFTs and communities); and continuous, adaptive trait variation has been proposed to replace PFTs as the basis for next-generation DGVMs. Here we analyse quantitative leaf-trait variation on long temperature and moisture gradients in China with a view to understanding the relative importance of PFT replacement vs. continuous adaptive variation within PFTs. Leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC) and nitrogen content of dry matter were measured on all species at 80 sites ranging from temperate to tropical climates and from dense forests to deserts. Chlorophyll fluorescence traits and carbon, phosphorus and potassium contents were measured at 47 sites. Generalized linear models were used to relate log-transformed trait values to growing-season temperature and moisture indices, with or without PFT identity as a predictor, and to test for differences in trait responses among PFTs. Continuous trait variation was found to be ubiquitous. Responses to moisture availability were generally similar within and between PFTs, but biophysical traits (LA, SLA and LDMC) of forbs and grasses responded differently from woody plants. SLA and LDMC responses to temperature were dominated by the prevalence of evergreen PFTs with thick, dense leaves at the warm end of the gradient. Nutrient (N, P and K) responses to climate gradients were generally similar within all PFTs. Area-based nutrients generally declined with moisture; Narea and Karea declined with temperature, but Parea increased with temperature. Although the adaptive nature of many of these trait-climate relationships is understood qualitatively, a key challenge for modelling is to predict them quantitatively. Models must take into account that community-level responses to climatic gradients can be influenced by shifts in PFT composition, such as the replacement of deciduous by evergreen trees, which may run either parallel or counter to trait variation within PFTs. The importance of PFT shifts varies among traits, being important for biophysical traits but less so for physiological and chemical traits. Finally, models should take account of the diversity of trait values that is found in all sites and PFTs, representing the "pool" of variation that is locally available for the natural adaptation of ecosystem function to environmental change

Dynamic monitoring of the shelf life of Cobia (Rachycentron canadum): a study on the applicability of a smart photochromic indicator.

To ensure the marketing of fresh fish-based products, it is necessary to develop fast methods that assess its freshness in real time. This study therefore evaluated the applicability of a photochromic time?temperature indicator (TTI) to monitor the time and temperature history during the period of validity of the whole fish of the cobia specimen stored in ice. The TTI response was both visibly interpreted as well as adaptable to measurement using suitable equipment. The results showed that the smart indicator activated during 6 s of ultraviolet light showed a similar rate of deterioration of the analysed product visual response, proving to be a dynamic shelf life indicator that can assure consumers the ultimate quality point of the entire cobia easily, cheaply and accurately

Molecular weight effects on chain pull-out fracture of reinforced polymeric interfaces

Using Brownian dynamics, we simulate the fracture of polymer interfaces reinforced by diblock connector chains. We find that for short chains the interface fracture toughness depends linearly on the degree of polymerization $N$ of the connector chains, while for longer chains the dependence becomes $N^{3/2}$. Based on the geometry of initial chain configuration, we propose a scaling argument that accounts for both short and long chain limits and crossover between them.Comment: 5 pages, 3 figure

P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production

Terrestrial photosynthesis is the basis for vegetation growth and drives the land carbon cycle. Accurately simulating gross primary production (GPP, ecosystem-level apparent photosynthesis) is key for satellite monitoring and Earth System Model predictions under climate change. While robust models exist for describing leaf-level photosynthesis, predictions diverge due to uncertain photosynthetic traits and parameters which vary on multiple spatial and temporal scales. Here, we describe and evaluate a gross primary production (GPP, photosynthesis per unit ground area) model, the P-model, that combines the Farquhar-von Caemmerer-Berry model for C3 photosynthesis with an optimality principle for the carbon assimilation- transpiration trade-off, and predicts a multi-day average light use efficiency (LUE) for any climate and C3 vegetation type. The model is forced here with satellite data for the fraction of absorbed photosynthetically active radiation and site-specific meteorological data and is evaluated against GPP estimates from a globally distributed network of ecosystem flux measurements. Although the P-model requires relatively few inputs and prescribed parameters, the R2 for predicted versus observed GPP based on the full model setup is 0.75 (8-day mean, 131 sites) – better than some state-of-the-art satellite data-driven light use efficiency models. The R2 is reduced to 0.69 when not accounting for the reduction in quantum yield at low temperatures and effects of low soil moisture on LUE. The R2 for the P-model-predicted LUE is 0.37 (means by site) and 0.53 (means by vegetation type). The P-model provides a simple but powerful method for predicting – rather than prescribing light use efficiency and simulating terrestrial photosythesis across a wide range of conditions. The model is available as an R package (rpmodel)