Fully renewable limonene-derived polycarbonate as a high-performance alkyd resin

Limonene-derived polycarbonate-based alkyd resins (ARs) have been prepared by copolymerization of limonene dioxide with CO2, catalysed by a β-diiminate zinc–bis(trimethylsilyl)amido complex, and subsequent chemical modification with soybean oil fatty acids using triphenylethylphosphonium bromide as the catalyst. This quantitative partial modification was realized via epoxy–carboxylic acid chemistry, affording ARs with higher oil lengths, lower polydispersities and higher glass transition temperatures (Tg) in comparison to a conventional polyester AR based on phthalic acid, multifunctional polyol pentaerythritol and soybean fatty acid. The novel limonene polycarbonate AR and the conventional polyester AR were evaluated as coatings and both the physical drying (without the presence of the oxidative drying accelerator Borchi® Oxy Coat) and chemical curing (with Borchi® Oxy Coat) processes of these coatings were monitored by measuring the König hardness and complex modulus development with time. A better performance was obtained for the alkyd paint containing polycarbonates modified with fatty acids (FA-PCs), which showed a faster chemical drying, a higher König hardness and a higher Tg in coating evaluation, demonstrating that the fully renewable FA-PCs are promising resins for alkyd paint applications

Deep level investigation of InGaAs on InP layer

Deep level traps in lattice-matched In0.47Ga0.53As epitaxial layers grown by MBE on InP substrates have been studied by Deep Level Transient Spectroscopy (DLTS) on Al2O3/InGaAs Metal-Oxide-Semiconductor (MOS) capacitors. The impact of different surface passivation steps and a post-gate-deposition Forming Gas Annealing (FGA) has been studied. It is shown that spectra are dominated by a near mid gap electron trap in the depletion region, with activation energy in the range 0.37 eV to 0.42 eV. At the same time, a broad background distribution of interface states is found as well, which is significantly reduced by the FGA. Detailed carrier trapping studies have been carried out to identify the origin of the grown-in electron traps, which are shown to be of point defect behavior

Drivers of lichen species richness at multiple spatial scales in temperate forests

Only few studies analysing lichen diversity have simultaneously considered interactions among drivers that operate at different spatial and temporal scales. Aims: The aims of this study were to evaluate the relative importance of host tree, and local, landscape and historical factors in explaining lichen diversity in managed temperate forests, and to test the potential interactions among factors acting at different spatial scales. Methods: Thirty-five stands were selected in the Őrség region, western Hungary. Linear models and multi-model inference within an information-theory framework were used to evaluate the role of different variables on lichen species richness. Results: Drivers at multiple spatial scales contributed to shaping lichen species richness both at the tree and plot levels. Tree level species richness was related to both tree and plot level factors. With increasing relative diffuse light lichen species richness increased; this effect was stronger on higher than on lower part of the trunks. At the plot-scale, species richness was affected by local drivers. Landscape and historical factors had no or only marginal effect. Conclusions: Lichen conservation in temperate managed forests could be improved if the complex interactions among host tree quality and availability, micro-climatic conditions, and management were taken into consideration

Increasing atmospheric [CO2] from glacial through future levels affects drought tolerance via impacts on leaves, xylem and their integrated function

This is the peer reviewed version of the following article: Medeiros, J. S. and Ward, J. K. (2013), Increasing atmospheric [CO2] from glacial to future concentrations affects drought tolerance via impacts on leaves, xylem and their integrated function. New Phytol, 199: 738–748. doi:10.1111/nph.12318, which has been published in final form at http://doi.org/10.1111/nph.12318. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Changes in atmospheric carbon dioxide concentration ([CO2]) affect plant carbon/water trade-offs, with implications for drought tolerance. Leaf-level studies often indicate that drought tolerance may increase with rising [CO2], but integrated leaf and xylem responses are not well understood in this respect. In addition, the influence of low [CO2] of the last glacial period on drought tolerance and xylem properties is not well understood. We investigated the interactive effects of a broad range of [CO2] and plant water potentials on leaf function, xylem structure and function and the integration of leaf and xylem function in Phaseolus vulgaris. Elevated [CO2] decreased vessel implosion strength, reduced conduit specific hydraulic conductance, and compromised leaf specific xylem hydraulic conductance under moderate drought. By contrast, at glacial [CO2], transpiration was maintained under moderate drought via greater conduit specific and leaf specific hydraulic conductance in association with increased vessel implosion strength. Our study involving the integration of leaf and xylem responses suggests that increasing [CO2] does not improve drought tolerance. We show that under glacial conditions changes in leaf and xylem properties could increase drought tolerance, while under future conditions greater productivity may only occur when higher water use can be accommodated

Genetic Loci Associated With Fluoride Resistance in Streptococcus mutans

The prolonged exposure of the cariogenic bacterial species Streptococcus mutans to high concentrations of fluoride leads to the development of fluoride resistance in this species. Previous studies confirmed the involvement of a mutation in a single chromosomal region in the occurrence of fluoride resistance. The involvement of multiple genomic mutations has not been verified. The aim of this study is to identify multiple genetic loci associated with fluoride resistance in S. mutans. The previously published whole genome sequences of two fluoride-resistant S. mutans strains (UA159-FR and C180-2FR) and their corresponding wild-type strains (UA159 and C180-2) were analyzed to locate shared chromosomal mutations in fluoride-resistant strains. Both fluoride-resistant strains were isolated in laboratory by culturing their mother strains in media with high concentrations of fluoride. The corresponding gene expression and enzyme activities were accordingly validated. Mutations were identified in two glycolytic enzymes, namely pyruvate kinase and enolase. Pyruvate kinase was deactivated in fluoride-resistant strain C180-2FR. Enolase was less inhibited by fluoride in fluoride-resistant strain UA159-FR than in its wild-type strain. Mutations in the promoter mutp constitutively increased the promoter activity and up-regulated the expression of the downstream fluoride antiporters in fluoride-resistant strains. Mutations in the intergenic region glpFp led to lower expression of glpF, encoding a glycerol uptake facilitator protein, in fluoride-resistant strains than in wild-type strains. Our results revealed that there is overlap of chromosomal regions with mutations among different fluoride-resistant S. mutans strains. They provide novel candidates for the study of the mechanisms of fluoride resistance

Investigating the role of prior and observation error correlations in improving a model forecast of forest carbon balance using Four Dimensional Variational data assimilation

Efforts to implement variational data assimilation routines with functional ecology models and land surface models have been limited, with sequential and Markov chain Monte Carlo data assimilation methods being prevalent. When data assimilation has been used with models of carbon balance, prior or “background” errors (in the initial state and parameter values) and observation errors have largely been treated as independent and uncorrelated. Correlations between background errors have long been known to be a key aspect of data assimilation in numerical weather prediction. More recently, it has been shown that accounting for correlated observation errors in the assimilation algorithm can considerably improve data assimilation results and forecasts. In this paper we implement a Four-Dimensional Variational data assimilation (4D-Var) scheme with a simple model of forest carbon balance, for joint parameter and state estimation and assimilate daily observations of Net Ecosystem CO2 Exchange (NEE) taken at the Alice Holt forest CO2 flux site in Hampshire, UK. We then investigate the effect of specifying correlations between parameter and state variables in background error statistics and the effect of specifying correlations in time between observation errors. The idea of including these correlations in time is new and has not been previously explored in carbon balance model data assimilation. In data assimilation, background and observation error statistics are often described by the background error covariance matrix and the observation error covariance matrix. We outline novel methods for creating correlated versions of these matrices, using a set of previously postulated dynamical constraints to include correlations in the background error statistics and a Gaussian correlation function to include time correlations in the observation error statistics. The methods used in this paper will allow the inclusion of time correlations between many different observation types in the assimilation algorithm, meaning that previously neglected information can be accounted for. In our experiments we assimilate a single year of NEE observations and then run a forecast for the next 14 years. We compare the results using our new correlated background and observation error covariance matrices and those using diagonal covariance matrices. We find that using the new correlated matrices reduces the root mean square error in the 14 year forecast of daily NEE by 44% decreasing from 4.22 gCm−2 day−1 to 2.38 gCm−2 day−

A global apparent polar wander path for the last 320 Ma calculated from site-level paleomagnetic data

Apparent polar wander paths (APWPs) calculated from paleomagnetic data describe the motion of tectonic plates relative to the Earth's rotation axis through geological time, providing a quantitative paleogeographic framework for studying the evolution of Earth's interior, surface, and atmosphere. Previous APWPs were typically calculated from collections of paleomagnetic poles, with each pole computed from collections of paleomagnetic sites, and each site representing a spot reading of the paleomagnetic field. It was recently shown that the choice of how sites are distributed over poles strongly determines the confidence region around APWPs and possibly the APWP itself, and that the number of paleomagnetic data used to compute a single paleomagnetic pole varies widely and is essentially arbitrary. Here, we use a recently proposed method to overcome this problem and provide a new global APWP for the last 320 million years that is calculated from simulated site-level paleomagnetic data instead of from paleopoles, in which spatial and temporal uncertainties of the original datasets are incorporated. We provide an updated global paleomagnetic database scrutinized against quantitative, stringent quality criteria, and use an updated global plate motion model. The new global APWP follows the same trend as the most recent pole-based APWP but has smaller uncertainties. This demonstrates that the first-order geometry of the global APWP is robust and reproducible. Moreover, we find that previously identified peaks in APW rate disappear when calculating the APWP from site-level data and correcting for a temporal bias in the underlying data. Finally, we show that a higher-resolution global APWP frame may be determined for time intervals with high data density, but that this is not yet feasible for the entire 320–0 Ma time span. Calculating polar wander from site-level data provides opportunities to significantly improve the quality and resolution of the global APWP by collecting large and well-dated paleomagnetic datasets from stable plate interiors, which may contribute to solving detailed Earth scientific problems that rely on a paleomagnetic reference frame