An historical perspective on the development of the thermodynamic equation of seawater - 2010

Oceanography is concerned with understanding the mechanisms controlling the movement of seawater and its contents. A fundamental tool in this process is the characterization of the thermophysical properties of seawater as functions of measured temperature and electrical conductivity, the latter used as a proxy for the concentration of dissolved matter in seawater. For many years a collection of algorithms denoted the Equation of State 1980 (EOS-80) has been the internationally accepted standard for calculating such properties. However, modern measurement technology now allows routine observations of temperature and electrical conductivity to be made to at least one order of magnitude more accurately than the uncertainty in this standard. Recently, a new standard has been developed, the Thermodynamical Equation of Seawater 2010 (TEOS-10). This new standard is thermodynamically consistent, valid over a wider range of temperature and salinity, and includes a mechanism to account for composition variations in seawater. Here we review the scientific development of this standard, and describe the literature involved in its development, which includes many of the articles in this special issue.

Global-scale climate impact functions: the relationship between climate forcing and impact

Although there is a strong policy interest in the impacts of climate change corresponding to different degrees of climate change, there is so far little consistent empirical evidence of the relationship between climate forcing and impact. This is because the vast majority of impact assessments use emissions-based scenarios with associated socio-economic assumptions, and it is not feasible to infer impacts at other temperature changes by interpolation. This paper presents an assessment of the global-scale impacts of climate change in 2050 corresponding to defined increases in global mean temperature, using spatially-explicit impacts models representing impacts in the water resources, river flooding, coastal, agriculture, ecosystem and built environment sectors. Pattern-scaling is used to construct climate scenarios associated with specific changes in global mean surface temperature, and a relationship between temperature and sea level used to construct sea level rise scenarios. Climate scenarios are constructed from 21 climate models to give an indication of the uncertainty between forcing and response. The analysis shows that there is considerable uncertainty in the impacts associated with a given increase in global mean temperature, due largely to uncertainty in the projected regional change in precipitation. This has important policy implications. There is evidence for some sectors of a non-linear relationship between global mean temperature change and impact, due to the changing relative importance of temperature and precipitation change. In the socio-economic sectors considered here, the relationships are reasonably consistent between socio-economic scenarios if impacts are expressed in proportional terms, but there can be large differences in absolute terms. There are a number of caveats with the approach, including the use of pattern-scaling to construct scenarios, the use of one impacts model per sector, and the sensitivity of the shape of the relationships between forcing and response to the definition of the impact indicator.

The impacts of climate change on river flood risk at the global scale

This paper presents an assessment of the implications of climate change for global river flood risk. It is based on the estimation of flood frequency relationships at a grid resolution of 0.5 × 0.5°, using a global hydrological model with climate scenarios derived from 21 climate models, together with projections of future population. Four indicators of the flood hazard are calculated; change in the magnitude and return period of flood peaks, flood-prone population and cropland exposed to substantial change in flood frequency, and a generalised measure of regional flood risk based on combining frequency curves with generic flood damage functions. Under one climate model, emissions and socioeconomic scenario (HadCM3 and SRES A1b), in 2050 the current 100-year flood would occur at least twice as frequently across 40 % of the globe, approximately 450 million flood-prone people and 430 thousand km2 of flood-prone cropland would be exposed to a doubling of flood frequency, and global flood risk would increase by approximately 187 % over the risk in 2050 in the absence of climate change. There is strong regional variability (most adverse impacts would be in Asia), and considerable variability between climate models. In 2050, the range in increased exposure across 21 climate models under SRES A1b is 31–450 million people and 59 to 430 thousand km2 of cropland, and the change in risk varies between −9 and +376 %. The paper presents impacts by region, and also presents relationships between change in global mean surface temperature and impacts on the global flood hazard. There are a number of caveats with the analysis; it is based on one global hydrological model only, the climate scenarios are constructed using pattern-scaling, and the precise impacts are sensitive to some of the assumptions in the definition and application.

A radial basis function network classifier to maximise leave-one-out mutual information

tWe develop an orthogonal forward selection (OFS) approach to construct radial basis function (RBF)network classifiers for two-class problems. Our approach integrates several concepts in probabilisticmodelling, including cross validation, mutual information and Bayesian hyperparameter fitting. At eachstage of the OFS procedure, one model term is selected by maximising the leave-one-out mutual infor-mation (LOOMI) between the classifier’s predicted class labels and the true class labels. We derive theformula of LOOMI within the OFS framework so that the LOOMI can be evaluated efficiently for modelterm selection. Furthermore, a Bayesian procedure of hyperparameter fitting is also integrated into theeach stage of the OFS to infer the l2-norm based local regularisation parameter from the data. Since eachforward stage is effectively fitting of a one-variable model, this task is very fast. The classifier construc-tion procedure is automatically terminated without the need of using additional stopping criterion toyield very sparse RBF classifiers with excellent classification generalisation performance, which is par-ticular useful for the noisy data sets with highly overlapping class distribution. A number of benchmarkexamples are employed to demonstrate the effectiveness of our proposed approach.

On the barrier properties of the cornea: a microscopy study of the penetration of fluorescently labeled nanoparticles, polymers, and sodium fluorescein

Overcoming the natural defensive barrier functions of the eye remains one of the greatest challenges of ocular drug delivery. Cornea is a chemical and mechanical barrier preventing the passage of any foreign bodies including drugs into the eye, but the factors limiting penetration of permeants and nanoparticulate drug delivery systems through the cornea are still not fully understood. In this study, we investigate these barrier properties of the cornea using thiolated and PEGylated (750 and 5000 Da) nanoparticles, sodium fluorescein, and two linear polymers (dextran and polyethylene glycol). Experiments used intact bovine cornea in addition to bovine cornea de-epithelialized or tissues pretreated with cyclodextrin. It was shown that corneal epithelium is the major barrier for permeation; pretreatment of the cornea with β-cyclodextrin provides higher permeation of low molecular weight compounds, such as sodium fluorescein, but does not enhance penetration of nanoparticles and larger molecules. Studying penetration of thiolated and PEGylated (750 and 5000 Da) nanoparticles into the de-epithelialized ocular tissue revealed that interactions between corneal surface and thiol groups of nanoparticles were more significant determinants of penetration than particle size (for the sizes used here). PEGylation with polyethylene glycol of a higher molecular weight (5000 Da) allows penetration of nanoparticles into the stroma, which proceeds gradually, after an initial 1 h lag phase.

Regimes of conformational transitions of a diblock polyampholyte

The conformational properties of symmetric flexible diblock polyampholytes are investigated by scaling theory and molecular dynamics simulations. The electrostatically driven coil-globule transition of a symmetric diblock polyampholyte is found to consist of three regimes identified with increasing electrostatic interaction strength. In the first (folding) regime the electrostatic attraction causes the chain to fold through the overlap of the two blocks, while each block is slightly stretched by self-repulsion. The second (weak association or scrambled egg) regime is the classical collapse of the chain into a globule dominated by the fluctuation-induced attractions between oppositely charged sections of the chain. The structure of the formed globule can be represented as a dense packing of the charged chain sections (electrostatic attraction blobs). The third (strong association or ion binding) regime starts with direct binding of oppositely charged monomers (dipole formation), followed by a cascade of multipole formation (quadrupole, hexapole, octupole, etc.), leading to multiplets analogous to those found in ionomers. The existence of the multiplet cascade has also been confirmed in the simulations of solutions of short polymers with only one single charge (either positive or negative) in the middle of each chain. We use scaling theory to estimate the average chain size and the electrostatic correlation length as functions of the chain length, strength of electrostatic interactions, charge fraction, and solvent quality. The theoretically predicted scaling laws of these conformational properties are in very good agreement with our simulation results.

Nuclear Factor-kappaB controls the reaggregation of 3D neurosphere cultures in vitro

The approach of reaggregation involves the regeneration and self-renewal of histotypical 3D spheres from isolated tissue kept in suspension culture. Reaggregated spheres can be used as tumour, genetic, biohybrid and neurosphere models. In addition the functional superiority of 3D aggregates over conventional 2D cultures developed the use of neurospheres for brain engineering of CNS diseases. Thus 3D aggregate cultures created enormous interest in mechanisms that regulate the formation of multicellular aggregates in vitro. Here we analyzed mechanisms guiding the development of 3D neurosphere cultures. Adult neural stem cells can be cultured as self-adherent clusters, called neurospheres. Neurospheres are characterised as heterogeneous clusters containing unequal stem cell sub-types. Tumour necrosis factor-alpha (TNF-alpha is one of the crucial inflammatory cytokines with multiple actions on several cell types. TNF-alpha strongly activates the canonical Nuclear Factor Kappa-B (NF- kappaB) pathway. In order to investigate further functions of TNF in neural stem cells (NSCs) we tested the hypothesis that TNF is able to modulate the motility and/or migratory behaviour of SVZ derived adult neural stem cells. We observed a significantly faster sphere formation in TNF treated cultures than in untreated controls. The very fast aggregation of isolated NSCs (<2h) is a commonly observed phenomenon, though the mechanisms of 3D neurosphere formation remain largely unclear. Here we demonstrate for the first time, increased aggregation and enhanced motility of isolated NSCs in response to the TNF-stimulus. Moreover, this phenomenon is largely dependent on activated transcription factor NF-kappaB. Both, the pharmacological blockade of NF-kappaB pathway by pyrrolidine dithiocarbamate (PDTC) or Bay11-7082 and genetic blockade by expression of a transdominant-negative super-repressor IkappaB-AA1 led to decreased aggregation.

Effects of dense code-switching on executive control

Bilingualism is reported to re-structure executive control networks, but it remains unknown which aspects of the bilingual experience cause this modulation. This study explores the impact of three code-switching types on executive functions: (1) alternation of languages, (2) insertion of lexicon of one language into grammar of another, (3) dense code-switching with co-activation of lexicon and grammar. Current models hypothesise that they challenge different aspects of the executive system because they vary in the extent and scope of language separation. Two groups of German-English bilinguals differing in dense code-switching frequency participated in a flanker task under conditions varying in degree of trial-mixing and resulting demands to conflict-monitoring. Bilinguals engaging in more dense code-switching showed inhibitory advantages in the condition requiring most conflict-monitoring. Moreover, dense code-switching frequency correlated positively with monitoring skills. This suggests that the management of co-activated languages during dense code-switching engages conflict-monitoring and that the consolidation processes taking place within co-activated linguistic systems involve local inhibition. Code-switching types requiring greater degrees of language separation may involve more global forms of inhibition. This study shows that dense code-switching is a key experience shaping bilinguals’ executive functioning and highlights the importance of controlling for participants’ code-switching habits in bilingualism research.