962 resultados para Interacting particle systems


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A cascading failure is a failure in a system of interconnected parts, in which the breakdown of one element can lead to the subsequent collapse of the others. The aim of this paper is to introduce a simple combinatorial model for the study of cascading failures. In particular, having in mind particle systems and Markov random fields, we take into consideration a network of interacting urns displaced over a lattice. Every urn is Pólya-like and its reinforcement matrix is not only a function of time (time contagion) but also of the behavior of the neighboring urns (spatial contagion), and of a random component, which can represent either simple fate or the impact of exogenous factors. In this way a non-trivial dependence structure among the urns is built, and it is used to study default avalanches over the lattice. Thanks to its flexibility and its interesting probabilistic properties, the given construction may be used to model different phenomena characterized by cascading failures such as power grids and financial networks.

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The developments of models in Earth Sciences, e.g. for earthquake prediction and for the simulation of mantel convection, are fare from being finalized. Therefore there is a need for a modelling environment that allows scientist to implement and test new models in an easy but flexible way. After been verified, the models should be easy to apply within its scope, typically by setting input parameters through a GUI or web services. It should be possible to link certain parameters to external data sources, such as databases and other simulation codes. Moreover, as typically large-scale meshes have to be used to achieve appropriate resolutions, the computational efficiency of the underlying numerical methods is important. Conceptional this leads to a software system with three major layers: the application layer, the mathematical layer, and the numerical algorithm layer. The latter is implemented as a C/C++ library to solve a basic, computational intensive linear problem, such as a linear partial differential equation. The mathematical layer allows the model developer to define his model and to implement high level solution algorithms (e.g. Newton-Raphson scheme, Crank-Nicholson scheme) or choose these algorithms form an algorithm library. The kernels of the model are generic, typically linear, solvers provided through the numerical algorithm layer. Finally, to provide an easy-to-use application environment, a web interface is (semi-automatically) built to edit the XML input file for the modelling code. In the talk, we will discuss the advantages and disadvantages of this concept in more details. We will also present the modelling environment escript which is a prototype implementation toward such a software system in Python (see www.python.org). Key components of escript are the Data class and the PDE class. Objects of the Data class allow generating, holding, accessing, and manipulating data, in such a way that the actual, in the particular context best, representation is transparent to the user. They are also the key to establish connections with external data sources. PDE class objects are describing (linear) partial differential equation objects to be solved by a numerical library. The current implementation of escript has been linked to the finite element code Finley to solve general linear partial differential equations. We will give a few simple examples which will illustrate the usage escript. Moreover, we show the usage of escript together with Finley for the modelling of interacting fault systems and for the simulation of mantel convection.

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This thesis was focused on theoretical models of synchronization to cortical dynamics as measured by magnetoencephalography (MEG). Dynamical systems theory was used in both identifying relevant variables for brain coordination and also in devising methods for their quantification. We presented a method for studying interactions of linear and chaotic neuronal sources using MEG beamforming techniques. We showed that such sources can be accurately reconstructed in terms of their location, temporal dynamics and possible interactions. Synchronization in low-dimensional nonlinear systems was studied to explore specific correlates of functional integration and segregation. In the case of interacting dissimilar systems, relevant coordination phenomena involved generalized and phase synchronization, which were often intermittent. Spatially-extended systems were then studied. For locally-coupled dissimilar systems, as in the case of cortical columns, clustering behaviour occurred. Synchronized clusters emerged at different frequencies and their boundaries were marked through oscillation death. The macroscopic mean field revealed sharp spectral peaks at the frequencies of the clusters and broader spectral drops at their boundaries. These results question existing models of Event Related Synchronization and Desynchronization. We re-examined the concept of the steady-state evoked response following an AM stimulus. We showed that very little variability in the AM following response could be accounted by system noise. We presented a methodology for detecting local and global nonlinear interactions from MEG data in order to account for residual variability. We found crosshemispheric nonlinear interactions of ongoing cortical rhythms concurrent with the stimulus and interactions of these rhythms with the following AM responses. Finally, we hypothesized that holistic spatial stimuli would be accompanied by the emergence of clusters in primary visual cortex resulting in frequency-specific MEG oscillations. Indeed, we found different frequency distributions in induced gamma oscillations for different spatial stimuli, which was suggestive of temporal coding of these spatial stimuli. Further, we addressed the bursting character of these oscillations, which was suggestive of intermittent nonlinear dynamics. However, we did not observe the characteristic-3/2 power-law scaling in the distribution of interburst intervals. Further, this distribution was only seldom significantly different to the one obtained in surrogate data, where nonlinear structure was destroyed. In conclusion, the work presented in this thesis suggests that advances in dynamical systems theory in conjunction with developments in magnetoencephalography may facilitate a mapping between levels of description int he brain. this may potentially represent a major advancement in neuroscience.

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Small particles and their dynamics are of widespread interest due both to their unique properties and their ubiquity. Here, we investigate several classes of small particles: colloids, polymers, and liposomes. All these particles, due to their size on the order of microns, exhibit significant similarity in that they are large enough to be visualized in microscopes, but small enough to be significantly influenced by thermal (or Brownian) motion. Further, similar optical microscopy and experimental techniques are commonly employed to investigate all these particles. In this work, we develop single particle tracking techniques, which allow thorough characterization of individual particle dynamics, observing many behaviors which would be overlooked by methods which time or ensemble average. The various particle systems are also similar in that frequently, the signal-to-noise ratio represented a significant concern. In many cases, development of image analysis and particle tracking methods optimized to low signal-to-noise was critical to performing experimental observations. The simplest particles studied, in terms of their interaction potentials, were chemically homogeneous (though optically anisotropic) hard-sphere colloids. Using these spheres, we explored the comparatively underdeveloped conjunction of translation and rotation and particle hydrodynamics. Developing off this, the dynamics of clusters of spherical colloids were investigated, exploring how shape anisotropy influences the translation and rotation respectively. Transitioning away from uniform hard-sphere potentials, the interactions of amphiphilic colloidal particles were explored, observing the effects of hydrophilic and hydrophobic interactions upon pattern assembly and inter-particle dynamics. Interaction potentials were altered in a different fashion by working with suspensions of liposomes, which, while homogeneous, introduce the possibility of deformation. Even further degrees of freedom were introduced by observing the interaction of particles and then polymers within polymer suspensions or along lipid tubules. Throughout, while examination of the trajectories revealed that while by some measures, the averaged behaviors accorded with expectation, often closer examination made possible by single particle tracking revealed novel and unexpected phenomena.

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Consider the concept combination ‘pet human’. In word association experiments, human subjects produce the associate ‘slave’ in relation to this combination. The striking aspect of this associate is that it is not produced as an associate of ‘pet’, or ‘human’ in isolation. In other words, the associate ‘slave’ seems to be emergent. Such emergent associations sometimes have a creative character and cognitive science is largely silent about how we produce them. Departing from a dimensional model of human conceptual space, this article will explore concept combinations, and will argue that emergent associations are a result of abductive reasoning within conceptual space, that is, below the symbolic level of cognition. A tensor-based approach is used to model concept combinations allowing such combinations to be formalized as interacting quantum systems. Free association norm data is used to motivate the underlying basis of the conceptual space. It is shown by analogy how some concept combinations may behave like quantum-entangled (non-separable) particles. Two methods of analysis were presented for empirically validating the presence of non-separable concept combinations in human cognition. One method is based on quantum theory and another based on comparing a joint (true theoretic) probability distribution with another distribution based on a separability assumption using a chi-square goodness-of-fit test. Although these methods were inconclusive in relation to an empirical study of bi-ambiguous concept combinations, avenues for further refinement of these methods are identified.

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Compositionality is a frequently made assumption in linguistics, and yet many human subjects reveal highly non-compositional word associations when confronted with novel concept combinations. This article will show how a non-compositional account of concept combinations can be supplied by modelling them as interacting quantum systems.

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The overarching aim of this thesis was to investigate how processes of perception and action emerge under changing informational constraints during performance of multi-articular interceptive actions. Interceptive actions provide unique opportunities to study processes of perception and action in dynamic performance environments. The movement model used to exemplify the functionally coupled relationship between perception and action, from an ecological dynamics perspective, was cricket batting. Ecological dynamics conceptualises the human body as a complex system composed of many interacting sub-systems, and perceptual and motor system degrees of freedom, which leads to the emergence of patterns of behaviour under changing task constraints during performance. The series of studies reported in the Chapters of this doctoral thesis contributed to understanding of human behaviour by providing evidence of key properties of complex systems in human movement systems including self-organisation under constraints and meta-stability. Specifically, the studies: i) demonstrated how movement organisation (action) and visual strategies (perception) of dynamic human behaviour are constrained by changing ecological (especially informational) task constraints; (ii) provided evidence for the importance of representative design in experiments on perception and action; and iii), provided a principled theoretical framework to guide learning design in acquisition of skill in interceptive actions like cricket batting.

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We propose a new scheme for the use of constraints in setting up classical, Hamiltonian, relativistic, interacting particle theories. We show that it possesses both Poincaré invariance and invariance of world lines. We discuss the transition to the physical phase space and the nonrelativistic limit.

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NMR spectra of molecules oriented in thermotropic liquid crystalline media provide information on the molecular structure and order. The spins are generally strongly dipolar coupled and the spectral analyse require the tedious and time consuming numerical iterative calculations. The present study demonstrates the application of multiple quantum spin state selective detection of single quantum transitions for mimicking the homonuclear decoupling and the direct estimation of an element of ordering matrix. This information is utilized to estimate the nearly accurate starting dipolar couplings for iterative calculations. The studies on the spectra of strongly dipolar coupled five and six interacting spin systems are reported.

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The applicability of a formalism involving an exponential function of composition x1 in interpreting the thermodynamic properties of alloys has been studied. The excess integral and partial molar free energies of mixing are expressed as: $$\begin{gathered} \Delta F^{xs} = a_o x_1 (1 - x_1 )e^{bx_1 } \hfill \\ RTln\gamma _1 = a_o (1 - x_1 )^2 (1 + bx_1 )e^{bx_1 } \hfill \\ RTln\gamma _2 = a_o x_1^2 (1 - b + bx_1 )e^{bx_1 } \hfill \\ \end{gathered} $$ The equations are used in interpreting experimental data for several relatively weakly interacting binary systems. For the purpose of comparison, activity coefficients obtained by the subregular model and Krupkowski’s formalism have also been computed. The present equations may be considered to be convenient in describing the thermodynamic behavior of metallic solutions.

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Partikkelisysteemien segregaatio eli erottuminen on ilmiö, jossa tasalaatuisen jauheseoksen komponenteilla on taipumus erota toisistaan. Jauheen erottumistaipumus riippuu partikkelien ominaisuuksista, ympäröivistä olosuhteista ja partikkelien välisistä vuorovaikutuksista. Segregaatiomekanismeja on esitetty kirjallisuudessa valtava määrä ja pienetkin erot partikkelien välisissä ominaisuuksissa ja vuorovaikutuksissa voivat johtaa täysin eri segregaatiomekanismeihin. Segregaatioilmiö on lääketeollisuuden näkökulmasta hyvin keskeinen, eikä sitä tunneta vielä riittävän hyvin, jotta siltä osattaisiin systemaattisesti välttyä. Nykyinen segregaatiotutkimus perustuu suurelta osin yrityksen ja erehdyksen kautta tapahtuvaan oppimiseen. Todellisen segregaatioilmiön ymmärtämiseen tarvittaisiin innovatiivisia tutkimusmenetelmiä. Kokeellisen osan tarkoituksena oli kehittää ja perustestata menetelmä, jolla voidaan tutkia erilaisten partikkelisysteemien erottumiskäyttäytymistä, ja käyttää tätä menetelmää farmaseuttisten rae- ja pellettiseosten segregaation tutkimiseen. Tavoitteena oli todistaa kehitetyn Babel-laitteen toimintaperiaatteen soveltuvuus partikkelisysteemien erottumiskäyttäytymisen tutkimiseen, mutta suoritetut kokeet olivat lähinnä menetelmän ja laitteen testausta. Ongelmiksi muodostuivat Babel-laitteen asettamat rajoitukset, partikkelien sähköistyminen ja partikkelien väliset vuorovaikutukset. Käytetyt suoraviivaiset lähestymistavat eivät riittäneet segregaation aiheuttamiseen Babel-laitteella. Vertikaalisen ravistelun seurauksena syntynyt konvektiopyörre esti segregaation syntymisen. Johtopäätöksenä voidaan sanoa, että Babel-laite mittaa hyvin ja toistettavasti sekä se kykenee erottamaan erikokoiset partikkelit ja erilaiset kokojakaumat toisistaan. Laitteen kehittämistavoitteena olisi saada segregaatio paremmin näkyviin jauheseoksissa ravistelun seurauksena. Tällöin voitaisiin tehdä päätelmiä jauheseoksen erottumistaipumuksesta ja systeemissä vallitsevista erottumismekanismeista. Laitteen ja menetelmän jatkokehittäminen voisi tuottaa hyödyllistä lisätietoa, mikä edesauttaisi segregaation ymmärtämistä ilmiönä entistä paremmin

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Powders are essential materials in the pharmaceutical industry, being involved in majority of all drug manufacturing. Powder flow and particle size are central particle properties addressed by means of particle engineering. The aim of the thesis was to gain knowledge on powder processing with restricted liquid addition, with a primary focus on particle coating and early granule growth. Furthermore, characterisation of this kind of processes was performed. A thin coating layer of hydroxypropyl methylcellulose was applied on individual particles of ibuprofen in a fluidised bed top-spray process. The polymeric coating improved the flow properties of the powder. The improvement was strongly related to relative humidity, which can be seen as an indicator of a change in surface hydrophilicity caused by the coating. The ibuprofen used in the present study had a d50 of 40 μm and thus belongs to the Geldart group C powders, which can be considered as challenging materials in top-spray coating processes. Ibuprofen was similarly coated using a novel ultrasound-assisted coating method. The results were in line with those obtained from powders coated in the fluidised bed process mentioned above. It was found that the ultrasound-assisted method was capable of coating single particles with a simple and robust setup. Granule growth in a fluidised bed process was inhibited by feeding the liquid in pulses. The results showed that the length of the pulsing cycles is of importance, and can be used to adjust granule growth. Moreover, pulsed liquid feed was found to be of greater significance to granule growth in high inlet air relative humidity. Liquid feed pulsing can thus be used as a tool in particle size targeting in fluidised bed processes and in compensating for changes in relative humidity of the inlet air. The nozzle function of a two-fluid external mixing pneumatic nozzle, typical for small scale pharmaceutical fluidised bed processes, was studied in situ in an ongoing fluidised bed process with particle tracking velocimetry. It was found that the liquid droplets undergo coalescence as they proceed away from the nozzle head. The coalescence was expected to increase droplet speed, which was confirmed in the study. The spray turbulence was studied, and the results showed turbulence caused by the event of atomisation and by the oppositely directed fluidising air. It was concluded that particle tracking velocimetry is a suitable tool for in situ spray characterisation. The light transmission through dense particulate systems was found to carry information on particle size and packing density as expected based on the theory of light scattering by solids. It was possible to differentiate binary blends consisting of components with differences in optical properties. Light transmission showed potential as a rapid, simple and inexpensive tool in characterisation of particulate systems giving information on changes in particle systems, which could be utilised in basic process diagnostics.

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We explore the salient features of the `Kitaev ladder', a two-legged ladder version of the spin-1/2 Kitaev model on a honeycomb lattice, by mapping it to a one-dimensional fermionic p-wave superconducting system. We examine the connections between spin phases and topologically non-trivial phases of non-interacting fermionic systems, demonstrating the equivalence between the spontaneous breaking of global Z(2) symmetry in spin systems and the existence of isolated Majorana modes. In the Kitaev ladder, we investigate topological properties of the system in different sectors characterized by the presence or absence of a vortex in each plaquette of the ladder. We show that vortex patterns can yield a rich parameter space for tuning into topologically non-trivial phases. We introduce and employ a new topological invariant for explicitly determining the presence of zero energy Majorana modes at the boundaries of such phases. Finally, we discuss dynamic quenching between topologically non-trivial phases in the Kitaev ladder and, in particular, the post-quench dynamics governed by tuning through a quantum critical point.

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Hollow nanostructures are used for various applications including catalysis, sensing, and drug delivery. Methods based on the Kirkendall effect have been the most successful for obtaining hollow nanostructures of various multicomponent systems. The classical Kirkendall effect relies on the presence of a faster diffusing species in the core; the resultant imbalance in flux results in the formation of hollow structures. Here, an alternate non-Kirkendall mechanism that is operative for the formation of hollow single crystalline particles of intermetallic PtBi is demonstrated. The synthesis method involves sequential reduction of Pt and Bi salts in ethylene glycol under microwave irradiation. Detailed analysis of the reaction at various stages indicates that the formation of the intermetallic PtBi hollow nanoparticles occurs in steps. The mechanistic details are elucidated using control experiments. The use of microwave results in a very rapid synthesis of intermetallics PtBi that exhibits excellent electrocatalytic activity for formic acid oxidation reaction. The method presented can be extended to various multicomponent systems and is independent of the intrinsic diffusivities of the species involved.

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The fabrication of a mesoporous silica nanoparticle (MSN)-protamine hybrid system (MSN-PRM) is reported that selectively releases drugs in the presence of specific enzyme triggers present in the proximity of cancer cells. The enzyme trigger involved is a protease called trypsin, which is overexpressed in certain specific pathological conditions, such as inflammation and cancer. Overexpression of trypsin is known to be associated with invasion, metastasis, and growth in several cancers, such as leukemia, colon cancer, and colorectal cancer. The current system (MSN-PRM) consists of an MSN support in which mesopores are capped with an FDA-approved peptide drug protamine, which effectively blocks the outward diffusion of the drug molecules from the mesopores of the MSNs. On exposure to the enzyme trigger, the protamine cap disintegrates, opening up the molecular gates and releasing the entrapped drug molecules. The system exhibits minimal premature release in the absence of the trigger and selectively releases the encapsulated drugs in the presence of the proteases secreted by colorectal cancer cells. The ability of the MSN-PRM particles to deliver anticancer drugs to colorectal cancer cells has also been demonstrated. The hydrophobic drug is released into cancer cells subsequent to disintegration of the protamine cap, resulting in cell death. Drug-induced cell death in colorectal cancer cells is significantly enhanced when the hydrophobic drug that is known to degrade in aqueous environments is encapsulated in the MSN-PRM system in comparison to the free drug (P < 0.05). The system, which shows good biocompatibility and selective drug release, is a promising platform for cancer specific drug delivery.