Wormlike micelle formation and flow alignment of a pluronic block copolymer in aqueous solution

The self-assembly into wormlike micelles of a poly(ethylene oxide)-b-poly(propylene oxide)-b-poly(ethylene oxide) triblock copolymer Pluronic P84 in aqueous salt solution (2 M NaCl) has been studied by rheology, small-angle X-ray and neutron scattering (SAXS/SANS), and light scattering. Measurements of the flow curves by controlled stress rheometry indicated phase separation under flow. SAXS on solutions subjected to capillary flow showed alignment of micelles at intermediate shear rates, although loss of alignment was observed for high shear rates. For dilute solutions, SAXS and static light scattering data on unaligned samples could be superposed over three decades in scattering vector, providing unique information on the wormlike micelle structure over several length scales. SANS data provided information on even shorter length scales, in particular, concerning "blob" scattering from the micelle corona. The data could be modeled based on a system of semiflexible self-avoiding cylinders with a circular cross-section, as described by the wormlike chain model with excluded volume interactions. The micelle structure was compared at two temperatures close to the cloud point (47 degrees C). The micellar radius was found not to vary with temperature in this region, although the contour length increased with increasing temperature, whereas the Kuhn length decreased. These variations result in an increase of the low-concentration radius of gyration with increasing temperature. This was consistent with dynamic light scattering results, and, applying theoretical results from the literature, this is in agreement with an increase in endcap energy due to changes in hydration of the poly(ethylene oxide) blocks as the temperature is increased.

Attention through self-synchronisation in the spiking neuron stochastic diffusion network

The paper discusses ensemble behaviour in the Spiking Neuron Stochastic Diffusion Network, SNSDN, a novel network exploring biologically plausible information processing based on higher order temporal coding. SNSDN was proposed as an alternative solution to the binding problem [1]. SNSDN operation resembles Stochastic Diffusin on Search, SDS, a non-deterministic search algorithm able to rapidly locate the best instantiation of a target pattern within a noisy search space ([3], [5]). In SNSDN, relevant information is encoded in the length of interspike intervals. Although every neuron operates in its own time, ‘attention’ to a pattern in the search space results in self-synchronised activity of a large population of neurons. When multiple patterns are present in the search space, ‘switching of at- tention’ results in a change of the synchronous activity. The qualitative effect of attention on the synchronicity of spiking behaviour in both time and frequency domain will be discussed.

Advances in sequential data assimilation and numerical weather forecasting: an Ensemble Transform Kalman-Bucy Filter, a study on clustering in deterministic Ensemble Square Root Filters, and a test of a new time stepping scheme in an atmospheric model

This dissertation deals with aspects of sequential data assimilation (in particular ensemble Kalman filtering) and numerical weather forecasting. In the first part, the recently formulated Ensemble Kalman-Bucy (EnKBF) filter is revisited. It is shown that the previously used numerical integration scheme fails when the magnitude of the background error covariance grows beyond that of the observational error covariance in the forecast window. Therefore, we present a suitable integration scheme that handles the stiffening of the differential equations involved and doesn’t represent further computational expense. Moreover, a transform-based alternative to the EnKBF is developed: under this scheme, the operations are performed in the ensemble space instead of in the state space. Advantages of this formulation are explained. For the first time, the EnKBF is implemented in an atmospheric model. The second part of this work deals with ensemble clustering, a phenomenon that arises when performing data assimilation using of deterministic ensemble square root filters in highly nonlinear forecast models. Namely, an M-member ensemble detaches into an outlier and a cluster of M-1 members. Previous works may suggest that this issue represents a failure of EnSRFs; this work dispels that notion. It is shown that ensemble clustering can be reverted also due to nonlinear processes, in particular the alternation between nonlinear expansion and compression of the ensemble for different regions of the attractor. Some EnSRFs that use random rotations have been developed to overcome this issue; these formulations are analyzed and their advantages and disadvantages with respect to common EnSRFs are discussed. The third and last part contains the implementation of the Robert-Asselin-Williams (RAW) filter in an atmospheric model. The RAW filter is an improvement to the widely popular Robert-Asselin filter that successfully suppresses spurious computational waves while avoiding any distortion in the mean value of the function. Using statistical significance tests both at the local and field level, it is shown that the climatology of the SPEEDY model is not modified by the changed time stepping scheme; hence, no retuning of the parameterizations is required. It is found the accuracy of the medium-term forecasts is increased by using the RAW filter.

Do phytoplankton communities evolve through a self-regulatory abundance-diversity relationship?

A small group of phytoplankton species that produce toxic or allelopathic chemicals has a significant effect on plankton dynamics in marine ecosystems. The species of non-toxic phytoplankton, which are large in number, are affected by the toxin-allelopathy of those species. By analysis of the abundance data of marine phytoplankton collected from the North-West coast of the Bay of Bengal, an empirical relationship between the abundance of the potential toxin-producing species and the species diversity of the non-toxic phytoplankton is formulated. A change-point analysis demonstrates that the diversity of non-toxic phytoplankton increases with the increase of toxic species up to a certain level. However, for a massive increase of the toxin-producing species the diversity of phytoplankton at species level reduces gradually. Following the results, a deterministic relationship between the abundance of toxic phytoplankton and the diversity of non-toxic phytoplankton is developed. The abundance–diversity relationship develops a unimodal pathway through which the abundance of toxic species regulates the diversity of phytoplankton. These results contribute to the current understanding of the coexistence and biodiversity of phytoplankton, the top-down vs. bottom-up debate, and to that of abundance–diversity relationship in marine ecosystems.

A longitudinal analysis of self‐regulation and well-being: avoidance personal goals, avoidance coping, stress generation, and subjective well-being

We conducted 2 longitudinal meditational studies to test an integrative model of goals, stress and coping, and well‐being. Study 1 documented avoidance personal goals as an antecedent of life stressors and life stressors as a partial mediator of the relation between avoidance goals and longitudinal change in subjective well‐being (SWB). Study 2 fully replicated Study 1 and likewise validated avoidance goals as an antecedent of avoidance coping and avoidance coping as a partial mediator of the relation between avoidance goals and longitudinal change in SWB. It also showed that avoidance coping partially mediates the link between avoidance goals and life stressors and validated a sequential meditational model involving both avoidance coping and life stressors. The aforementioned results held when controlling for social desirability, basic traits, and general motivational dispositions. The findings are discussed with regard to the integration of various strands of research on self‐regulation. (PsycINFO Database Record (c) 2012 APA, all rights reserved)(journal abstract)

Bioactive films produced from self-assembling peptide amphiphiles as versatile substrates for tuning cell adhesion and tissue architecture in serum-free conditions

The development of versatile bioactive surfaces able to emulate in vivo conditions is of enormous importance to the future of cell and tissue therapy. Tuning cell behaviour on two-dimensional surfaces so that the cells perform as if they were in a natural three-dimensional tissue represents a significant challenge, but one that must be met if the early promise of cell and tissue therapy is to be fully realised. Due to the inherent complexities involved in the manufacture of biomimetic three-dimensional substrates, the scaling up of engineered tissue-based therapies may be simpler if based upon proven two-dimensional culture systems. In this work, we developed new coating materials composed of the self-assembling peptide amphiphiles (PAs) C16G3RGD (RGD) and C16G3RGDS (RGDS) shown to control cell adhesion and tissue architecture while avoiding the use of serum. When mixed with the C16ETTES diluent PA at 13 : 87 (mol mol-1) ratio at 1.25 times 10-3 M, the bioactive {PAs} were shown to support optimal adhesion, maximal proliferation, and prolonged viability of human corneal stromal fibroblasts ({hCSFs)}, while improving the cell phenotype. These {PAs} also provided stable adhesive coatings on highly-hydrophobic surfaces composed of striated polytetrafluoroethylene ({PTFE)}, significantly enhancing proliferation of aligned cells and increasing the complexity of the produced tissue. The thickness and structure of this highly-organised tissue were similar to those observed in vivo, comprising aligned newly-deposited extracellular matrix. As such, the developed coatings can constitute a versatile biomaterial for applications in cell biology, tissue engineering, and regenerative medicine requiring serum-free conditions.

On the spectra and pseudospectra of a class of non-self-adjoint random matrices and operators

In this paper we develop and apply methods for the spectral analysis of non-selfadjoint tridiagonal infinite and finite random matrices, and for the spectral analysis of analogous deterministic matrices which are pseudo-ergodic in the sense of E. B. Davies (Commun. Math. Phys. 216 (2001), 687–704). As a major application to illustrate our methods we focus on the “hopping sign model” introduced by J. Feinberg and A. Zee (Phys. Rev. E 59 (1999), 6433–6443), in which the main objects of study are random tridiagonal matrices which have zeros on the main diagonal and random ±1’s as the other entries. We explore the relationship between spectral sets in the finite and infinite matrix cases, and between the semi-infinite and bi-infinite matrix cases, for example showing that the numerical range and p-norm ε - pseudospectra (ε > 0, p ∈ [1,∞] ) of the random finite matrices converge almost surely to their infinite matrix counterparts, and that the finite matrix spectra are contained in the infinite matrix spectrum Σ. We also propose a sequence of inclusion sets for Σ which we show is convergent to Σ, with the nth element of the sequence computable by calculating smallest singular values of (large numbers of) n×n matrices. We propose similar convergent approximations for the 2-norm ε -pseudospectra of the infinite random matrices, these approximations sandwiching the infinite matrix pseudospectra from above and below.

Should system dynamics be described as a 'hard' or 'deterministic' systems approach?

This paper explores the criticism that system dynamics is a ‘hard’ or ‘deterministic’ systems approach. This criticism is seen to have four interpretations and each is addressed from the perspectives of social theory and systems science. Firstly, system dynamics is shown to offer not prophecies but Popperian predictions. Secondly, it is shown to involve the view that system structure only partially, not fully, determines human behaviour. Thirdly, the field's assumptions are shown not to constitute a grand content theory—though its structural theory and its attachment to the notion of causality in social systems are acknowledged. Finally, system dynamics is shown to be significantly different from systems engineering. The paper concludes that such confusions have arisen partially because of limited communication at the theoretical level from within the system dynamics community but also because of imperfect command of the available literature on the part of external commentators. Improved communication on theoretical issues is encouraged, though it is observed that system dynamics will continue to justify its assumptions primarily from the point of view of practical problem solving. The answer to the question in the paper's title is therefore: on balance, no.

Self-concept clarity and compulsive Internet use: the role of preference for virtual interactions and employment status in British and North-American samples

Background and Aims Compulsive Internet Use (CIU) describes a maladaptive relationship with the Internet characterised by loss of control and conflict. Although also affecting adults, most studies use teenage samples, and theoretical development on risk factors is scarce. According to Davis (2001), the social connectivity function of the Internet is key in identifying traits associated with CIU. Since Self-Concept Clarity (SCC) is strongly related to social anxiety, and virtual interactions allow “self-edition”, we hypothesized that individuals low in SCC could choose virtual interactions as safer alternative to satisfy their social needs. This could in turn increase the risk of CIU. Building on a previous study, we also expected CIU to be more harmful in the unemployed. Methods We collected samples from the UK (N = 532) and US (N = 502) with equal distribution of employed and unemployed individuals. We ran Measurement Invariance tests to confirm that the constructs were equivalent across countries. Subsequently, we conducted mediation and moderation analysis to test our hypothesis with Multigroup Confirmatory Factor Analysis. Results Measurement Invariance was confirmed. The relationship between SCC and CIU was partially mediated by preference of virtual interactions in both countries. This preference was significantly related to lower social support. Short term unemployment seemed to accentuate the negative impact of CIU on life satisfaction in both countries, although only marginally significantly in the US. The unemployed reported significantly lower levels of life satisfaction. Conclusion We demonstrated that SCC is a key vulnerability factor to CIU in adults, and confirmed the additional risks for the unemployed.