Computer simulations of soft particles in flow

Understanding the dynamics of blood cells is a crucial element to discover biological mechanisms, to develop new efficient drugs, design sophisticated microfluidic devices, for diagnostics. In this work, we focus on the dynamics of red blood cells in microvascular flow. Microvascular blood flow resistance has a strong impact on cardiovascular function and tissue perfusion. The flow resistance in microcirculation is governed by flow behavior of blood through a complex network of vessels, where the distribution of red blood cells across vessel cross-sections may be significantly distorted at vessel bifurcations and junctions. We investigate the development of blood flow and its resistance starting from a dispersed configuration of red blood cells in simulations for different hematocrits, flow rates, vessel diameters, and aggregation interactions between red blood cells. Initially dispersed red blood cells migrate toward the vessel center leading to the formation of a cell-free layer near the wall and to a decrease of the flow resistance. The development of cell-free layer appears to be nearly universal when scaled with a characteristic shear rate of the flow, which allows an estimation of the length of a vessel required for full flow development, $l_c \approx 25D$, with vessel diameter $D$. Thus, the potential effect of red blood cell dispersion at vessel bifurcations and junctions on the flow resistance may be significant in vessels which are shorter or comparable to the length $l_c$. The presence of aggregation interactions between red blood cells lead in general to a reduction of blood flow resistance. The development of the cell-free layer thickness looks similar for both cases with and without aggregation interactions. Although, attractive interactions result in a larger cell-free layer plateau values. However, because the aggregation forces are short-ranged at high enough shear rates ($\bar{\dot{\gamma}} \gtrsim 50~\text{s}^{-1}$) aggregation of red blood cells does not bring a significant change to the blood flow properties. Also, we develop a simple theoretical model which is able to describe the converged cell-free-layer thickness with respect to flow rate assuming steady-state flow. The model is based on the balance between a lift force on red blood cells due to cell-wall hydrodynamic interactions and shear-induced effective pressure due to cell-cell interactions in flow. We expect that these results can also be used to better understand the flow behavior of other suspensions of deformable particles such as vesicles, capsules, and cells. Finally, we investigate segregation phenomena in blood as a two-component suspension under Poiseuille flow, consisting of red blood cells and target cells. The spatial distribution of particles in blood flow is very important. For example, in case of nanoparticle drug delivery, the particles need to come closer to microvessel walls, in order to adhere and bring the drug to a target position within the microvasculature. Here we consider that segregation can be described as a competition between shear-induced diffusion and the lift force that pushes every soft particle in a flow away from the wall. In order to investigate the segregation, on one hand, we have 2D DPD simulations of red blood cells and target cell of different sizes, on the other hand the Fokker-Planck equation for steady state. For the equation we measure force profile, particle distribution and diffusion constant across the channel. We compare simulation results with those from the Fokker-Planck equation and find a very good correspondence between the two approaches. Moreover, we investigate the diffusion behavior of target particles for different hematocrit values and shear rates. Our simulation results indicate that diffusion constant increases with increasing hematocrit and depends linearly on shear rate. The third part of the study describes development of a simulation model of complex vascular geometries. The development of the model is important to reproduce vascular systems of small pieces of tissues which might be gotten from MRI or microscope images. The simulation model of the complex vascular systems might be divided into three parts: modeling the geometry, developing in- and outflow boundary conditions, and simulation domain decomposition for an efficient computation. We have found that for the in- and outflow boundary conditions it is better to use the SDPD fluid than DPD one because of the density fluctuations along the channel of the latter. During the flow in a straight channel, it is difficult to control the density of the DPD fluid. However, the SDPD fluid has not that shortcoming even in more complex channels with many branches and in- and outflows because the force acting on particles is calculated also depending on the local density of the fluid.

(Quantum-) critical dynamics of magnetoelectric materials

In this thesis the critical dynamics of several magnetoelectric compounds at their phase transition were examined. Mostly measurements of the dielectric properties in the frequency range of below 1 Hz up to 5 GHz were employed to evaluate the critical exponents for both magnetic field and temperature-dependent measurements. Most of the materials that are part of this work show anomalous behavior, especially at very low temperatures where quantum fluctuations are of the order of or even dominate those induced thermally. This anomalous behavior manifests in different forms. In Dy2Ti2O7 we demonstrate the existence of electric dipoles on magnetic monopoles. Here the dynamics at the critical endpoint located at 0.36K and in a magnetic field of 1T parallel to the [111] direction are of special interest. At this critical endpoint the expected critical slowing down of the dynamics could not only not be observed but instead the opposite, critical speeding-up by several orders of magnitude, could be demonstrated. Furthermore, we show that the phase diagram of Dy2Ti2O7 in this field direction can be reproduced solely from the dynamical properties, for example the resonance frequency of the observed relaxation that is connected to the monopole movement. Away from this point of the phase diagram the dynamics are slowing-down with reduction of temperature as one would expect. Additional measurements on Y2Ti2O7, a structurally identical but non-magnetic material, show only slowing down with reduction of temperature and no additional features. A possible explanation for the observed critical speeding-up is a coherent movement of magnetic monopoles close to the critical field that increases the resonance frequency by reducing the damping of the process. LiCuVO4 on the other hand behaves normally at its phase transition as long as the temperature is higher than 0.4 K. In this temperature regime the dynamics show critical slowing-down analogous to classical ferroelectric materials. This analogy extends also towards higher frequencies where the permittivity displays a ‘dispersion’ minimum that is temperature-dependent but of the order of 2 GHz. Below 0.4K the observed behavior changes drastically. Here we found no longer relaxational behavior but instead an excitation with very low energy. This low energy excitation was predicted by theory and is caused by nearly gapless soliton excitations within the 1D Cu2+ chains of LiCuVO4. Finally, in TbMnO3 the dynamics of the phase transition into the multiferroic phase was observed at roughly 27 K, a much higher temperature compared to the other materials. Here the expected critical slowing-down was observed, even though in low-frequency measurements this transition into the ferroelectric phase is overshadowed by the so-called c-axis relaxation. Therefore, only frequencies above 1MHz could be used to determine the critical exponents for both temperatureand magnetic-field-dependent measurements. This was done for both the peak frequency as well as the relaxation strength. In TbMnO3 an electromagnetic soft-mode with small optical weight causes the observed fluctuations, similar to the case of multiferroic MnWO4.

Ionisation and discharge in cloud-forming atmospheres of brown dwarfs and extrasolar planets

Brown dwarfs and giant gas extrasolar planets have cold atmospheres with rich chemical compositions from which mineral cloud particles form. Their properties, like particle sizes and material composition, vary with height, and the mineral cloud particles are charged due to triboelectric processes in such dynamic atmospheres. The dynamics of the atmospheric gas is driven by the irradiating host star and/or by the rotation of the objects that changes during its lifetime. Thermal gas ionisation in these ultra-cool but dense atmospheres allows electrostatic interactions and magnetic coupling of a substantial atmosphere volume. Combined with a strong magnetic field , a chromosphere and aurorae might form as suggested by radio and x-ray observations of brown dwarfs. Non-equilibrium processes like cosmic ray ionisation and discharge processes in clouds will increase the local pool of free electrons in the gas. Cosmic rays and lighting discharges also alter the composition of the local atmospheric gas such that tracer molecules might be identified. Cosmic rays affect the atmosphere through air showers in a certain volume which was modelled with a 3D Monte Carlo radiative transfer code to be able to visualise their spacial extent. Given a certain degree of thermal ionisation of the atmospheric gas, we suggest that electron attachment to charge mineral cloud particles is too inefficient to cause an electrostatic disruption of the cloud particles. Cloud particles will therefore not be destroyed by Coulomb explosion for the local temperature in the collisional dominated brown dwarf and giant gas planet atmospheres. However, the cloud particles are destroyed electrostatically in regions with strong gas ionisation. The potential size of such cloud holes would, however, be too small and might occur too far inside the cloud to mimic the effect of, e.g. magnetic field induced star spots.

Multipartite entanglement in harmonic oscillators subjected to dissipative quantum dynamics

Una detallada descripción de la dinámica de bajas energías del entrelazamiento multipartito es proporcionada para sistemas armónicos en una gran variedad de escenarios disipativos. Sin hacer ninguna aproximación central, esta descripción yace principalmente sobre un conjunto razonable de hipótesis acerca del entorno e interacción entorno-sistema, ambas consistente con un análisis lineal de la dinámica disipativa. En la primera parte se deriva un criterio de inseparabilidad capaz de detectar el entrelazamiento k-partito de una extensa clase de estados gausianos y no-gausianos en sistemas de variable continua. Este criterio se emplea para monitorizar la dinámica transitiva del entrelazamiento, mostrando que los estados no-gausianos pueden ser tan robustos frente a los efectos disipativos como los gausianos. Especial atención se dedicada a la dinámica estacionaria del entrelazamiento entre tres osciladores interaccionando con el mismo entorno o diferentes entornos a distintas temperaturas. Este estudio contribuye a dilucidar el papel de las correlaciones cuánticas en el comportamiento de la corrientes energéticas.

Analysis of Molecular Dynamics Simulations of Protein Folding

Microsecond long Molecular Dynamics (MD) trajectories of biomolecular processes are now possible due to advances in computer technology. Soon, trajectories long enough to probe dynamics over many milliseconds will become available. Since these timescales match the physiological timescales over which many small proteins fold, all atom MD simulations of protein folding are now becoming popular. To distill features of such large folding trajectories, we must develop methods that can both compress trajectory data to enable visualization, and that can yield themselves to further analysis, such as the finding of collective coordinates and reduction of the dynamics. Conventionally, clustering has been the most popular MD trajectory analysis technique, followed by principal component analysis (PCA). Simple clustering used in MD trajectory analysis suffers from various serious drawbacks, namely, (i) it is not data driven, (ii) it is unstable to noise and change in cutoff parameters, and (iii) since it does not take into account interrelationships amongst data points, the separation of data into clusters can often be artificial. Usually, partitions generated by clustering techniques are validated visually, but such validation is not possible for MD trajectories of protein folding, as the underlying structural transitions are not well understood. Rigorous cluster validation techniques may be adapted, but it is more crucial to reduce the dimensions in which MD trajectories reside, while still preserving their salient features. PCA has often been used for dimension reduction and while it is computationally inexpensive, being a linear method, it does not achieve good data compression. In this thesis, I propose a different method, a nonmetric multidimensional scaling (nMDS) technique, which achieves superior data compression by virtue of being nonlinear, and also provides a clear insight into the structural processes underlying MD trajectories. I illustrate the capabilities of nMDS by analyzing three complete villin headpiece folding and six norleucine mutant (NLE) folding trajectories simulated by Freddolino and Schulten [1]. Using these trajectories, I make comparisons between nMDS, PCA and clustering to demonstrate the superiority of nMDS. The three villin headpiece trajectories showed great structural heterogeneity. Apart from a few trivial features like early formation of secondary structure, no commonalities between trajectories were found. There were no units of residues or atoms found moving in concert across the trajectories. A flipping transition, corresponding to the flipping of helix 1 relative to the plane formed by helices 2 and 3 was observed towards the end of the folding process in all trajectories, when nearly all native contacts had been formed. However, the transition occurred through a different series of steps in all trajectories, indicating that it may not be a common transition in villin folding. The trajectories showed competition between local structure formation/hydrophobic collapse and global structure formation in all trajectories. Our analysis on the NLE trajectories confirms the notion that a tight hydrophobic core inhibits correct 3-D rearrangement. Only one of the six NLE trajectories folded, and it showed no flipping transition. All the other trajectories get trapped in hydrophobically collapsed states. The NLE residues were found to be buried deeply into the core, compared to the corresponding lysines in the villin headpiece, thereby making the core tighter and harder to undo for 3-D rearrangement. Our results suggest that the NLE may not be a fast folder as experiments suggest. The tightness of the hydrophobic core may be a very important factor in the folding of larger proteins. It is likely that chaperones like GroEL act to undo the tight hydrophobic core of proteins, after most secondary structure elements have been formed, so that global rearrangement is easier. I conclude by presenting facts about chaperone-protein complexes and propose further directions for the study of protein folding.

Effect of boiling on deposition of metallic colloids

In this study the relationship between heterogeneous nucleate boiling surfaces and deposition of suspended metallic colloidal particles, popularly known as crud or corrosion products in process industries, on those heterogeneous sites is investigated. Various researchers have reported that hematite is a major constituent of crud which makes it the primary material of interest; however the models developed in this work are irrespective of material choice. Qualitative hypotheses on the deposition process under boiling as proposed by previous researchers have been tested, which fail to provide explanations for several physical mechanisms observed and analyzed. In this study a quantitative model of deposition rate has been developed on the basis of bubble dynamics and colloid-surface interaction potential. Boiling from a heating surface aids in aggregation of the metallic particulates viz. nano-particles, crud particulate, etc. suspended in a liquid, which helps in transporting them to heating surfaces. Consequently, clusters of particles deposit onto the heating surfaces due to various interactive forces, resulting in formation of porous or impervious layers. The deposit layer grows or recedes depending upon variations in interparticle and surface forces, fluid shear, fluid chemistry, etc. This deposit layer in turn affects the rate of bubble generation, formation of porous chimneys, critical heat flux (CHF) of surfaces, activation and deactivation of nucleation sites on the heating surfaces. Several problems are posed due to the effect of boiling on colloidal deposition, which range from research initiatives involving nano-fluids as a heat transfer medium to industrial applications such as light water nuclear reactors. In this study, it is attempted to integrate colloid and surface science with vapor bubble dynamics, boiling heat transfer and evaporation rate. Pool boiling experiments with dilute metallic colloids have been conducted to investigate several parameters impacting the system. The experimental data available in the literature is obtained by flow experiments, which do not help in correlating boiling mechanism with the deposition amount or structure. With the help of experimental evidences and analysis, previously proposed hypothesis for particle transport to the contact line due to hydrophobicity has been challenged. The experimental observations suggest that deposition occurs around the bubble surface contact line and extends underneath area of the bubble microlayer as well. During the evaporation the concentration gradient of a non-volatile species is created, which induces osmotic pressure. The osmotic pressure developed inside the microlayer draws more particles inside the microlayer region or towards contact line. The colloidal escape time is slower than the evaporation time, which leads to the aggregation of particles in the evaporating micro-layer. These aggregated particles deposit onto or are removed from the heating surface, depending upon their total interaction potential. Interaction potential has been computed with the help of surface charge and van der Waals potential for the materials in aqueous solutions. Based upon the interaction-force boundary layer thickness, which is governed by debye radius (or ionic concentration and pH), a simplified quantitative model for the attachment kinetics is proposed. This attachment kinetics model gives reasonable results in predicting attachment rate against data reported by previous researchers. The attachment kinetics study has been done for different pH levels and particle sizes for hematite particles. Quantification of colloidal transport under boiling scenarios is done with the help of overall average evaporation rates because generally waiting times for bubbles at the same position is much larger than growth times. In other words, from a larger measurable scale perspective, frequency of bubbles dictates the rate of collection of particles rather than evaporation rate during micro-layer evaporation of one bubble. The combination of attachment kinetics and colloidal transport kinetics has been used to make a consolidated model for prediction of the amount of deposition and is validated with the help of high fidelity experimental data. In an attempt to understand and explain boiling characteristics, high speed visualization of bubble dynamics from a single artificial large cavity and multiple naturally occurring cavities is conducted. A bubble growth and departure dynamics model is developed for artificial active sites and is validated with the experimental data. The variation of bubble departure diameter with wall temperature is analyzed with experimental results and shows coherence with earlier studies. However, deposit traces after boiling experiments show that bubble contact diameter is essential to predict bubble departure dynamics, which has been ignored previously by various researchers. The relationship between porosity of colloid deposits and bubbles under the influence of Jakob number, sub-cooling and particle size has been developed. This also can be further utilized in variational wettability of the surface. Designing porous surfaces can having vast range of applications varying from high wettability, such as high critical heat flux boilers, to low wettability, such as efficient condensers.

Oceans of energy? The non-linear trajectory of the emerging wave energy technology

This paper addresses the construction and structuring of a technological niche – i.e. a protected space where promising but still underperforming technologies are stabilized and articulated with societal needs – and discusses the processes that influence niche development and may enable niche breakout. In theoretical terms the paper is grounded on the multi-level approach to sustainability transitions, and particularly on the niche literature. But it also attempts to address the limitations of this literature in what concerns the spatial dimension of niche development. It is argued that technological niches can transcend the narrow territorial boundaries to which they are often confined, and encompass communities and actions that span several spatial levels, without losing some territorial embeddedness. It is further proposed that these features shape the niche trajectory and, therefore, need to be explicitly considered by the niche theoretical framework. To address this problem the paper builds on and extends the socio-cognitive perspective to technology development, introducing a further dimension – space – which broadens the concept of technological niche and permits to better capture the complexity of niche behaviour. This extended framework is applied to the case of an emerging renewable energy technology – wave energy - which exhibits a particularly slow and non-linear development trajectory. The empirical analysis starts by examining how an “overall niche space” in wave energy was spatially constructed over time. Then it investigates in greater detail the niche development processes that took place in Portugal, a country that was among the pioneers in the field, and whose actors have been, from very early stages, engaged in the activities conducted at various spatial levels. Through this combined analysis, the paper seeks to understand whether and how niche development is shaped by processes taking place at different spatial levels. More specifically it investigates the interplay between territorial and relational elements in niche development, and how these different dynamics influence the performance of the niche processes and impact on the overall niche trajectory. The results confirm the niche multi-spatial dynamics, showing that it is shaped by the interplay between a niche relational space constructed by actors’ actions and interactions on/across levels, and the territorial effects introduced by these actors’ embeddedness in particular geographical and institutional settings. They contribute to a more precise understanding of the processes that can accelerate or slow down the trajectory of a technological niche. In addition, the results shed some light into the niche activities conducted in/originating from a specific territorial setting - Portugal - offering some insights into the behaviour of key actors and its implications for the positioning of the country in the emerging field, which can be relevant for the formulation of strategies and policies for this area.

The interplay between neuronal activity and actin dynamics mimic the setting of an LTD synaptic tag

Persistent forms of plasticity, such as long-term depression (LTD), are dependent on the interplay between activity-dependent synaptic tags and the capture of plasticity-related proteins. We propose that the synaptic tag represents a structural alteration that turns synapses permissive to change. We found that modulation of actin dynamics has different roles in the induction and maintenance of LTD. Inhibition of either actin depolymerisation or polymerization blocks LTD induction whereas only the inhibition of actin depolymerisation blocks LTD maintenance. Interestingly, we found that actin depolymerisation and CaMKII activation are involved in LTD synaptic-tagging and capture. Moreover, inhibition of actin polymerisation mimics the setting of a synaptic tag, in an activity-dependent manner, allowing the expression of LTD in non-stimulated synapses. Suspending synaptic activation also restricts the time window of synaptic capture, which can be restored by inhibiting actin polymerization. Our results support our hypothesis that modulation of the actin cytoskeleton provides an input-specific signal for synaptic protein capture.

Centre-of-mass motion in multi-particle Schrodinger-Newton dynamics

We investigate the implication of the nonlinear and non-local multi-particle Schrodinger-Newton equation for the motion of the mass centre of an extended multi-particle object, giving self-contained and comprehensible derivations. In particular, we discuss two opposite limiting cases. In the first case, the width of the centre-of-mass wave packet is assumed much larger than the actual extent of the object, in the second case it is assumed much smaller. Both cases result in nonlinear deviations from ordinary free Schrodinger evolution for the centre of mass. On a general conceptual level we include some discussion in order to clarify the physical basis and intention for studying the Schrodinger-Newton equation.

Computational modelling of non-equilibrium condensing steam flows in low-pressure steam turbines

The steam turbines play a significant role in global power generation. Especially, research on low pressure (LP) steam turbine stages is of special importance for steam turbine man- ufactures, vendors, power plant owners and the scientific community due to their lower efficiency than the high pressure steam turbine stages. Because of condensation, the last stages of LP turbine experience irreversible thermodynamic losses, aerodynamic losses and erosion in turbine blades. Additionally, an LP steam turbine requires maintenance due to moisture generation, and therefore, it is also affecting on the turbine reliability. Therefore, the design of energy efficient LP steam turbines requires a comprehensive analysis of condensation phenomena and corresponding losses occurring in the steam tur- bine either by experiments or with numerical simulations. The aim of the present work is to apply computational fluid dynamics (CFD) to enhance the existing knowledge and understanding of condensing steam flows and loss mechanisms that occur due to the irre- versible heat and mass transfer during the condensation process in an LP steam turbine. Throughout this work, two commercial CFD codes were used to model non-equilibrium condensing steam flows. The Eulerian-Eulerian approach was utilised in which the mix- ture of vapour and liquid phases was solved by Reynolds-averaged Navier-Stokes equa- tions. The nucleation process was modelled with the classical nucleation theory, and two different droplet growth models were used to predict the droplet growth rate. The flow turbulence was solved by employing the standard k-ε and the shear stress transport k-ω turbulence models. Further, both models were modified and implemented in the CFD codes. The thermodynamic properties of vapour and liquid phases were evaluated with real gas models. In this thesis, various topics, namely the influence of real gas properties, turbulence mod- elling, unsteadiness and the blade trailing edge shape on wet-steam flows, are studied with different convergent-divergent nozzles, turbine stator cascade and 3D turbine stator-rotor stage. The simulated results of this study were evaluated and discussed together with the available experimental data in the literature. The grid independence study revealed that an adequate grid size is required to capture correct trends of condensation phenomena in LP turbine flows. The study shows that accurate real gas properties are important for the precise modelling of non-equilibrium condensing steam flows. The turbulence modelling revealed that the flow expansion and subsequently the rate of formation of liquid droplet nuclei and its growth process were affected by the turbulence modelling. The losses were rather sensitive to turbulence modelling as well. Based on the presented results, it could be observed that the correct computational prediction of wet-steam flows in the LP turbine requires the turbulence to be modelled accurately. The trailing edge shape of the LP turbine blades influenced the liquid droplet formulation, distribution and sizes, and loss generation. The study shows that the semicircular trailing edge shape predicted the smallest droplet sizes. The square trailing edge shape estimated greater losses. The analysis of steady and unsteady calculations of wet-steam flow exhibited that in unsteady simulations, the interaction of wakes in the rotor blade row affected the flow field. The flow unsteadiness influenced the nucleation and droplet growth processes due to the fluctuation in the Wilson point.

Variational ensemble Kalman filtering applied to data assimilation problems in computational fluid dynamics

One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.

Liquid film dynamics in horizontal and tilted tubes: dry spots and sliding drops

Using a model derived from lubrication theory, we consider the evolution of a thin viscous film coating the interior or exterior of a cylindrical tube. The flow is driven by surface tension and gravity and the liquid is assumed to wet the cylinder perfectly. When the tube is horizontal, we use large-time simulations to describe the bifurcation structure of the capillary equilibria appearing at low Bond number. We identify a new film configuration in which an isolated dry patch appears at the top of the tube and demonstrate hysteresis in the transition between rivulets and annular collars as the tube length is varied. For a tube tilted to the vertical, we show how a long initially uniform rivulet can break up first into isolated drops and then annular collars, which subsequently merge. We also show that the speed at which a localized drop moves down the base of a tilted tube is non-monotonic in tilt angle.

Production and carbonate dynamics of Halimeda incrassata (Ellis)Lamouroux altered by Thalassia testudinum Banks and Soland ex König

Ocean acidification poses a serious threat to a broad suite of calcifying organisms. Scleractinian corals and cal- careous algae that occupy shallow, tropical waters are vulnerable to global changes in ocean chemistry be- cause they already are subject to stressful and variable carbon dynamics at the local scale. For example, net heterotrophy increases carbon dioxide concentrations, and pH varies with diurnal fluctuations in photosyn- thesis and respiration. Few researchers, however, have investigated the possibility that carbon dioxide con- sumption during photosynthesis by non-calcifying photoautotrophs, such as seagrasses, can ameliorate deleterious effects of ocean acidi fi cation on sympatric calcareous algae. Naturally occurring variations in the density of seagrasses and associated calcareous algae provide an ecologically relevant test of the hypoth- esis that diel fl uctuations in water chemistry driven by cycles of photosynthesis and respiration within seagrass beds create microenvironments that enhance macroalgal calci fi cation. In Grape Tree Bay off Little Cayman Island BWI, we quanti fi ed net production and characterized calci fi cation for thalli of the calcareous green alga Halimeda incrassata growing within beds of Thalassia testudinum with varying shoot densities. Re- sults indicated that individual H . incrassata thalli were ~6% more calci fi ed in dense seagrass beds. On an areal basis, however, far more calcium carbonate was produced by H . incrassata in areas where seagrasses were less dense due to higher rates of production. In addition, diel pH regimes in vegetated and unvegetated areas within the lagoon were not signi fi cantly different, suggesting a high degree of water exchange and mixing throughout the lagoon. These results suggest that, especially in well-mixed lagoons, carbonate pro- duction by calcareous algae may be more related to biotic interactions between seagrasses and calcareous algae than to seagrass-mediated changes in local water chemistry.

Neural representations of social and non-social uncertainty in human decision making

The social landscape is filled with an intricate web of species-specific desired objects and course of actions. Humans are highly social animals and, as they navigate this landscape, they need to produce adapted decision-making behaviour. Traditionally social and non-social neural mechanisms affecting choice have been investigated using different approaches. Recently, in an effort to unite these findings, two main theories have been proposed to explain how the brain might encode social and non-social motivational decision-making: the extended common currency and the social valuation specific schema (Ruff & Fehr 2014). One way to test these theories is to directly compare neural activity related to social and non-social decision outcomes within the same experimental setting. Here we address this issue by focusing on the neural substrates of social and non-social forms of uncertainty. Using functional magnetic resonance imaging (fMRI) we directly compared the neural representations of reward and risk prediction and errors (RePE and RiPE) in social and non- social situations using gambling games. We used a trust betting game to vary uncertainty along a social dimension (trustworthiness), and a card game (Preuschoff et al. 2006) to vary uncertainty along a non-social dimension (pure risk). The trust game was designed to maintain the same structure of the card game. In a first study, we exposed a divide between subcortical and cortical regions when comparing the way these regions process social and non-social forms of uncertainty during outcome anticipation. Activity in subcortical regions reflected social and non-social RePE, while activity in cortical regions correlated with social RePE and non-social RiPE. The second study focused on outcome delivery and integrated the concept of RiPE in non-social settings with that of fairness and monetary utility maximisation in social settings. In particular these results corroborate recent models of anterior insula function (Singer et al. 2009; Seth 2013), and expose a possible neural mechanism that weights fairness and uncertainty but not monetary utility. The third study focused on functionally defined regions of the early visual cortex (V1) showing how activity in these areas, traditionally considered only visual, might reflect motivational prediction errors in addition to known perceptual prediction mechanisms (den Ouden et al 2012). On the whole, while our results do not support unilaterally one or the other theory modeling the underlying neural dynamics of social and non-social forms of decision making, they provide a working framework where both general mechanisms might coexist.