Reversible thermal transition of polydiacetylene based on KTTKS collagen sequence

Here we explore the physico-chemical properties of a peptide amphiphile obtained by chemical conjugation of the collagenstimulating peptide KTTKS with 10,12-pentacosadiynoic acid which photopolymerizes as a stable and extended polydiacetylene. We investigate the self-assembly of this new polymer and rationalize its peculiar behavior in terms of a thermal conformational transition. Surprisingly, this polymer shows a thermal transition associated with a non-cooperative increase in b-sheet content at high temperature.

Surface chemistry of glycine on Pt{111} in different aqueous environments

Adsorption of glycine on Ptf111g under UHV conditions and in different aqueous environments was studied by XPS (UHV and ambient pressure) and NEXAFS. Under UHV conditions, glycine adsorbs in its neutral molecular state up to about 0.15 ML. Further deposition leads to the formation of an additional zwitterionic species, which is in direct contact with the substrate surface, followed by the growth of multilayers, which also consist of zwitterions. The neutral surface species is most stable and decomposes at 360 K through a multi-step process which includes the formation of methylamine and carbon monoxide. When glycine and water are co-adsorbed in UHV at low temperatures (< 170 K) inter-layer diffusion is inhibited and the surface composition depends on the adsorption sequence. Water adsorbed on top of a glycine layer does not lead to significant changes in its chemical state. When glycine is adsorbed on top of a pre-adsorbed chemisorbed water layer or thick ice layer, however, it is found in its zwitterionic state, even at low coverage. No difference is seen in the chemical state of glycine when the layers are exposed to ambient water vapor pressure up to 0.2 Torr at temperatures above 300 K. Also the decomposition temperature stays the same, 360 K, irrespective of the water vapor pressure. Only the reaction path of the decomposition products is affected by ambient water vapor.

A low-order model investigation of the analysis of gravity waves in the ensemble Kalman filter.

The behavior of the ensemble Kalman filter (EnKF) is examined in the context of a model that exhibits a nonlinear chaotic (slow) vortical mode coupled to a linear (fast) gravity wave of a given amplitude and frequency. It is shown that accurate recovery of both modes is enhanced when covariances between fast and slow normal-mode variables (which reflect the slaving relations inherent in balanced dynamics) are modeled correctly. More ensemble members are needed to recover the fast, linear gravity wave than the slow, vortical motion. Although the EnKF tends to diverge in the analysis of the gravity wave, the filter divergence is stable and does not lead to a great loss of accuracy. Consequently, provided the ensemble is large enough and observations are made that reflect both time scales, the EnKF is able to recover both time scales more accurately than optimal interpolation (OI), which uses a static error covariance matrix. For OI it is also found to be problematic to observe the state at a frequency that is a subharmonic of the gravity wave frequency, a problem that is in part overcome by the EnKF.However, error in themodeled gravity wave parameters can be detrimental to the performance of the EnKF and remove its implied advantages, suggesting that a modified algorithm or a method for accounting for model error is needed.

Ensemble transform Kalman-Bucy filters

Two recent works have adapted the Kalman–Bucy filter into an ensemble setting. In the first formulation, the ensemble of perturbations is updated by the solution of an ordinary differential equation (ODE) in pseudo-time, while the mean is updated as in the standard Kalman filter. In the second formulation, the full ensemble is updated in the analysis step as the solution of single set of ODEs in pseudo-time. Neither requires matrix inversions except for the frequently diagonal observation error covariance. We analyse the behaviour of the ODEs involved in these formulations. We demonstrate that they stiffen for large magnitudes of the ratio of background error to observational error variance, and that using the integration scheme proposed in both formulations can lead to failure. A numerical integration scheme that is both stable and is not computationally expensive is proposed. We develop transform-based alternatives for these Bucy-type approaches so that the integrations are computed in ensemble space where the variables are weights (of dimension equal to the ensemble size) rather than model variables. Finally, the performance of our ensemble transform Kalman–Bucy implementations is evaluated using three models: the 3-variable Lorenz 1963 model, the 40-variable Lorenz 1996 model, and a medium complexity atmospheric general circulation model known as SPEEDY. The results from all three models are encouraging and warrant further exploration of these assimilation techniques.

IS capabilities for supporting post crisis regulatory compliance

The financial crisis of 2007-2009, has precipitated large scale regulatory change. Financial organizations are faced with implementing new regulations of considerable breadth and depth. Firms are faced with engaging in complex and costly change management programs at a time when profits are diminished. Furthermore, investors are becoming increasingly focused on compliance are seeking to ensure that organizations can demonstrate robust compliance practices as part of their due diligence process .The role of IS in underpinning stable, is paramount. IS allows the stable and consistent controls for meeting regulations in order to ensure long term effective compliance. Consequently, our study explores the IS capabilities which support the post crisis regulatory landscape. We identify eight key capabilities: Managing Internal Controls, Measuring Monitoring and Reporting Transactions, IS Development and Procurement, Managing Third Parties, Sharing and Selecting Best Practice, IS Leadership, Data Management and Enabling Cultural Change.

Do autocratic states trade less?

Does the political regime of a country influence its involvement in international trade? A theoretical model that predicts that autocracies trade less than democracies is developed, and the predictions of the model are tested empirically using a panel of more than 130 countries for 1962–2000. In contrast to the existing literature, data on the regime type of individual countries are used rather than information about the congruence of the regime type of pairs of trading countries. In line with the model, autocracies are found to import substantially less than democracies, even after controlling for official trade policies. This finding is very stable and does not depend on a particular setup or estimation technique.

A case study of sea breeze blocking regulated by sea surface temperature along the English south coast

The sensitivity of sea breeze structure to sea surface temperature (SST) and coastal orography is investigated in convection-permitting Met Office Unified Model simulations of a case study along the south coast of England. Changes in SST of 1 K are shown to significantly modify the structure of the sea breeze immediately offshore. On the day of the case study, the sea breeze was partially blocked by coastal orography, particularly within Lyme Bay. The extent to which the flow is blocked depends strongly on the static stability of the marine boundary layer. In experiments with colder SST, the marine boundary layer is more stable, and the degree of blocking is more pronounced. Although a colder SST would also imply a larger land–sea temperature contrast and hence a stronger onshore wind – an effect which alone would discourage blocking – the increased static stability exerts a dominant control over whether blocking takes place. The implications of prescribing fixed SST from climatology in numerical weather prediction model forecasts of the sea breeze are discussed.

Age differences in brain activity during emotion processing: reflections of age-Related decline or increased emotion regulation?

Despite the fact that physical health and cognitive abilities decline with aging, the ability to regulate emotion remains stable and in some aspects improves across the adult life span. Older adults also show a positivity effect in their attention and memory, with diminished processing of negative stimuli relative to positive stimuli compared with younger adults. The current paper reviews functional magnetic resonance imaging studies investigating age-related differences in emotional processing and discusses how this evidence relates to two opposing theoretical accounts of older adults’ positivity effect. The aging-brain model [Cacioppo et al. in: Social Neuroscience: Toward Understanding the Underpinnings of the Social Mind. New York, Oxford University Press, 2011] proposes that older adults’ positivity effect is a consequence of age-related decline in the amygdala, whereas the cognitive control hypothesis [Kryla-Lighthall and Mather in: Handbook of Theories of Aging, ed 2. New York, Springer, 2009; Mather and Carstensen: Trends Cogn Sci 2005;9:496–502; Mather and Knight: Psychol Aging 2005;20:554–570] argues that the positivity effect is a result of older adults’ greater focus on regulating emotion. Based on evidence for structural and functional preservation of the amygdala in older adults and findings that older adults show greater prefrontal cortex activity than younger adults while engaging in emotion-processing tasks, we argue that the cognitive control hypothesis is a more likely explanation for older adults’ positivity effect than the aging-brain model.

In the mood: the dynamics of collective sentiments on Twitter

We study the relationship between the sentiment levels of Twitter users and the evolving network structure that the users created by @-mentioning each other. We use a large dataset of tweets to which we apply three sentiment scoring algorithms, including the open source SentiStrength program. Specifically we make three contributions. Firstly we find that people who have potentially the largest communication reach (according to a dynamic centrality measure) use sentiment differently than the average user: for example they use positive sentiment more often and negative sentiment less often. Secondly we find that when we follow structurally stable Twitter communities over a period of months, their sentiment levels are also stable, and sudden changes in community sentiment from one day to the next can in most cases be traced to external events affecting the community. Thirdly, based on our findings, we create and calibrate a simple agent-based model that is capable of reproducing measures of emotive response comparable to those obtained from our empirical dataset.