Dissertations / Theses on the topic 'Information dynamics'

Presented is a study of quantum entanglement from the perspective of the theory of quantum information dynamics. We consider pairwise entanglement and present an analytical development using joint ladder operators, the sum of two single-particle fermionic ladder operators. This approach allows us to write down analytical representations of quantum algorithms and to explore quantum entanglement as it is manifested in a system of qubits.;We present a topological representation of quantum logic that views entangled qubit spacetime histories (or qubit world lines) as a generalized braid, referred to as a super-braid. The crossing of world lines may be either classical or quantum mechanical in nature, and in the latter case most conveniently expressed with our analytical expressions for entangling quantum gates. at a quantum mechanical crossing, independent world lines can become entangled. We present quantum skein relations that allow complicated superbraids to be recursively reduced to alternate classical histories. If the superbraid is closed, then one can decompose the resulting superlink into an entangled superposition of classical links. Also, one can compute a superlink invariant, for example the Jones polynomial for the square root of a knot.;We present measurement-based quantum computing based on our joint number operators. We take expectation values of the joint number operators to determine kinetic-level variables describing the quantum information dynamics in the qubit system at the mesoscopic scale. We explore the issue of reversibility in quantum maps at this scale using a quantum Boltzmann equation. We then present an example of quantum information processing using a qubit system comprised of nuclear spins. We also discuss quantum propositions cast in terms of joint number operators.;We review the well known dynamical equations governing superfluidity, with a focus on self-consistent dynamics supporting quantum vortices in a Bose-Einstein condensate (BEC). Furthermore, we review the mutual vortex-vortex interaction and the consequent Kelvin wave instability. We derive an effective equation of motion for a Fermi condensate that is the basis of our qubit representation of superfluidity.;We then present our quantum lattice gas representation of a superfluid. We explore aspects of our model with two qubits per point, referred to as a Q2 model, particularly its usefulness for carrying out practical quantum fluid simulations. We find that it is perhaps the simplest yet most comprehensive model of superfluid dynamics. as a prime application of Q2, we explore the power-law regions in the energy spectrum of a condensate in the low-temperature limit. We achieved the largest quantum simulations to date of a BEC and, for the first time, Kolmogorov scaling in superfluids, a flow regime heretofore only obtainably by classical turbulence models.;Finally, we address the subject of turbulence regarding information conservation on the small scales (both mesoscopic and microscopic) underlying the flow dynamics on the large hydrodynamic (macroscopic) scale. We present a hydrodynamic-level momentum equation, in the form of a Navier-Stokes equation, as the basis for the energy spectrum of quantum turbulence at large scales. Quantum turbulence, in particular the representation of fluid eddies in terms of a coherent structure of polarized quantum vortices, offers a unique window into the heretofore intractable subject of energy cascades.

Theoretical models of the exchange rate are developed where information on the model is not fully available to agents. It is an application of Benjamin Friedman's (1979) theme that full rational expectations may be a possibility only in the long-run, even for completely rational individuals. The thesis attempts to develop the theory of exchange rate behaviour by considering some neglected informational issues. The three substantive chapters each consider specific aspects of relevance to the determination of the exchange rate from an asset market view of perfect capital mobility. These are the possible current account inter-relationship, the persistence of interest rate differentials between the two currencies and the subjectivity of and the regress in beliefs across a decentralised market. Generally, limited information on the model will give rise to erroneous beliefs, on the one hand, and encourage the acquistion of information and the revision of beliefs, on the other. Erroneous beliefs will cause correlations between variables, which may not normally occur inside full rational expectations. The revision of beliefs will bring a particular source of non-stationarity to the data. And the stability of certain learning forms may require limitations on the degree of capital mobility. These conclusions would suggest that any empirical work on modelling the exchange rate may gain from relaxing certain a priori restrictions, which properly belong to models with stronger assumptions on the availability of information.

The passage of time is unrelenting. Time is an omnipresent feature of our existence, serving as a context to frame change driven by events and phenomena in our personal lives and social constructs. Accordingly, various elements of time are woven throughout information itself, and information behaviours such as creation, seeking and utilisation. Time plays a central role in many aspects of information retrieval (IR). It can not only distinguish the interpretation of information, but also profoundly influence the intentions and expectations of users' information seeking activity. Many time-based patterns and trends - namely temporal dynamics - are evident in streams of information behaviour by individuals and crowds. A temporal dynamic refers to a periodic regularity, or, a one-off or irregular past, present or future of a particular element (e.g., word, topic or query popularity) - driven by predictable and unpredictable time-based events and phenomena. Several challenges and opportunities related to temporal dynamics are apparent throughout IR. This thesis explores temporal dynamics from the perspective of query popularity and meaning, and word use and relationships over time. More specifically, the thesis posits that temporal dynamics provide tacit meaning and structure of information and information seeking. As such, temporal dynamics are a ‘two-way street’ since they must be supported, but also conversely, can be exploited to improve time-aware IR effectiveness. Real-time temporal dynamics in information seeking must be supported for consistent user satisfaction over time. Uncertainty about what the user expects is a perennial problem for IR systems, further confounded by changes over time. To alleviate this issue, IR systems can: (i) assist the user to submit an effective query (e.g., error-free and descriptive), and (ii) better anticipate what the user is most likely to want in relevance ranking. I first explore methods to help users formulate queries through time-aware query auto-completion, which can suggest both recent and always popular queries. I propose and evaluate novel approaches for time-sensitive query auto-completion, and demonstrate state-of-the-art performance of up to 9.2% improvement above the hard baseline. Notably, I find results are reflected across diverse search scenarios in different languages, confirming the pervasive and language agnostic nature of temporal dynamics. Furthermore, I explore the impact of temporal dynamics on the motives behind users' information seeking, and thus how relevance itself is subject to temporal dynamics. I find that temporal dynamics have a dramatic impact on what users expect over time for a considerable proportion of queries. In particular, I find the most likely meaning of ambiguous queries is affected over short and long-term periods (e.g., hours to months) by several periodic and one-off event temporal dynamics. Additionally, I find that for event-driven multi-faceted queries, relevance can often be inferred by modelling the temporal dynamics of changes in related information. In addition to real-time temporal dynamics, previously observed temporal dynamics offer a complementary opportunity as a tacit dimension which can be exploited to inform more effective IR systems. IR approaches are typically based on methods which characterise the nature of information through the statistical distributions of words and phrases. In this thesis I look to model and exploit the temporal dimension of the collection, characterised by temporal dynamics, in these established IR approaches. I explore how the temporal dynamic similarity of word and phrase use in a collection can be exploited to infer temporal semantic relationships between the terms. I propose an approach to uncover a query topic's "chronotype" terms -- that is, its most distinctive and temporally interdependent terms, based on a mix of temporal and non-temporal evidence. I find exploiting chronotype terms in temporal query expansion leads to significantly improved retrieval performance in several time-based collections. Temporal dynamics provide both a challenge and an opportunity for IR systems. Overall, the findings presented in this thesis demonstrate that temporal dynamics can be used to derive tacit structure and meaning of information and information behaviour, which is then valuable for improving IR. Hence, time-aware IR systems which take temporal dynamics into account can better satisfy users consistently by anticipating changing user expectations, and maximising retrieval effectiveness over time.

En aquesta tesi he investigat diversos camps de la biologia que podrien englobar-se en la disciplina general dels sistemes no lineals de replicadors. Els treballs presentats en aquesta tesis investiguen diversos fenomens dinàmics i processos evolutius per virus de RNA, pels anomenats hipercicles i per models generals de replicadors antagonistes. Específicament he investigat les anomenades quasiespècies, utilitzades per a modelitzar poblacions de RNA. Els treballs sobre hipercicles exploren diversos fenomens previs a l'origen de la vida i a l'aparició de la primera cèl.lula vivent. Mitjançant models ecològics com també utilitzant diferents eines computacionals he estudiat l'anomenada hipòtesi de la Reina Roja per entitats replicadores simples amb mutació. Aquests estudis tenen un interès en el contexte de l'evolució prebiòtica i l'ecologia teòrica.
In this thesis I have investigated several fields of biology that can be classified in the general subject of replicator nonlinear systems. The works presented in the thesis investigate several dynamical phenomena and evolutionary processes for RNA viruses, for hypercycles and for general models on antagonistic replicator dynamics. I have specifically investigated the dynamics of so-called quasispecies, used for the modelization of RNA populations. The works on hypercycles explore several phenomena related to previous events to the origin of life and to the appearance of the first living cell. By means of some ecologically-based mathematical models as well as of some computational models we also investigate the so-called Red Queen hypothesis for small, replicating-mutating entities. These studies are of interest in the context of prebiotic evolution and theoretical ecology.

En aquesta tesi he investigat diversos camps de la biologia que podrien englobar-se en la disciplina general dels sistemes no lineals de replicadors. Els treballs presentats en aquesta tesis investiguen diversos fenomens dinàmics i processos evolutius per virus de RNA, pels anomenats hipercicles i per models generals de replicadors antagonistes. Específicament he investigat les anomenades quasiespècies, utilitzades per a modelitzar poblacions de RNA. Els treballs sobre hipercicles exploren diversos fenomens previs a l'origen de la vida i a l'aparició de la primera cèl.lula vivent. Mitjançant models ecològics com també utilitzant diferents eines computacionals he estudiat l'anomenada hipòtesi de la Reina Roja per entitats replicadores simples amb mutació. Aquests estudis tenen un interès en el contexte de l'evolució prebiòtica i l'ecologia teòrica.
In this thesis I have investigated several fields of biology that can be classified in the general subject of replicator nonlinear systems. The works presented in the thesis investigate several dynamical phenomena and evolutionary processes for RNA viruses, for hypercycles and for general models on antagonistic replicator dynamics. I have specifically investigated the dynamics of so-called quasispecies, used for the modelization of RNA populations. The works on hypercycles explore several phenomena related to previous events to the origin of life and to the appearance of the first living cell. By means of some ecologically-based mathematical models as well as of some computational models we also investigate the so-called Red Queen hypothesis for small, replicating-mutating entities. These studies are of interest in the context of prebiotic evolution and theoretical ecology.

The study of complex systems has intensified in recent years. Researchers from many different disciplines have realised that the study of systems possessing a large number of degrees of freedom interacting in a non-linear way can offer insights into problems in engineering, biology, economics and many other fields besides. Among the themes in complexity, we focus here the issues of congestion and congestion emergence in the context of urban networks, with particular reference to the effects of dissemination of information about the system’s status. This topic is of great relevance today, due to the increasing availability of real-time information about traffic conditions and the large diffusion of personal devices that allow travellers to access such information. Through the analysis of a few simple models of information propagation in urban environment, we uncover that, contrarily to the naïve expectation, complete information is often detrimental to the global performance of the urban traffic network. Indeed, global or long-range dissemination induces correlations in the systems that become a source for spatial disorder, making the system more prone to the emergence of congested states and pushing it away from its Wardrop equilibrium. The models we study range from simple flow models on network to complete agent-based simulations on real-world networks with interacting agents and dynamical information. We then analyse real data, coming from London’s network of traffic detectors. We confirm that the heterogeneity in the distribution of traffic flow and occupancies across the network reduces its performances, consistently with the results obtained for the information propagation models. In addition, we find a rich phenomenology strikingly similar to the one found in critical self-organised systems. Indeed, we measure power-law correlation functions and 1/f power spectra, hinting to long spatial and temporal effects in the traffic flow, and confirm this result through the community detection analysis of the detectors’ correlation network, which showing that the whole urban area behaves as a single large chunk. We conclude discussing the origin of these features and how they can be used to improve the network performances.

Neural information processing by trains of action potentials is studied in the context of weakly electric fish electroreceptor neurons. A simple but accurate dynamical model for the firing activity of these neurons is presented and compared with experimental results. Dynamical analysis of the model reveals the mechanism by which it reproduces features present in experimental data, such as relative refractoriness and bursting behaviour. Approximations necessary for application of information theory to neural spike trains are presented and different measures are compared. Finally, the consequences of spike patterning caused by relative refractoriness and bursting on information transfer are investigated. It is found that relative refractoriness can increase information transfer while bursting provides a non-linear mechanism for encoding information that might be more efficient than firing of isolated spikes.

Biometric identification systems based on Keystroke Dynamics have been around for almost forty years now. There has always been a lot of interest in identifying individuals using their physiological or behavioral traits. Keystroke Dynamics focuses on the particular way a person types on a keyboard. The objective of the proposed research is to determine how well the identity of users can be established when using this biometric trait and when contextual information is also taken into account. The proposed research focuses on free text. Users were never told what to type, how or when. This particular field of Keystroke Dynamics has not been as thoroughly studied as the fixed text alternative where a plethora of methods have been tried. The proposed methods focus on the hypothesis that the position of a particular letter, or combination of letters, in a word is of high importance. Other studies have not taken into account if these letter combinations had occurred at the beginning, the middle, or the end of a word. A template of the user will be built using the context of the written words and the latency between successive keystrokes. Other features, like word length, minimum number of needed words to consider a session valid, frequency of words, model building parameters, as well as age group and gender have also been studied to determine those that better help ascertain the identity of an individual. The results of the proposed research should help determine if using Keystroke Dynamics and the proposed methodology are enough to identify users from the content they type with a good enough level of certainty. From this moment, it could be used as a method to ensure that a user is not supplanted, in authentication schemes, or even to help determine the authorship of different parts of a document written by more than one user.
Els sistemes d’identificació biomètrica basades en la cadència de tecleig fa gairebé quaranta anys que s’estudien. Hi ha hagut molt interès en identificar les persones a partir de les seves característiques fisiològiques o de comportament. La cadència de tecleig és la manera en la que una persona escriu en un teclat. L’objectiu de la recerca proposada és determinar com de bé es pot arribar a identificar un individu mitjançant aquesta característica biomètrica i quan també es prenen en consideració dades contextuals. Aquesta recerca es basa en text lliure. Als usuaris mai se’ls va dir què, quan o com havien d’escriure. Aquest camp de la cadència de tecleig no ha estat tan estudiat com l’alternativa de text fix on un gran ventall de mètodes s’han provat. Els mètodes d’identificació proposats es basen en la hipòtesi que la posició d’una lletra, o combinació de lletres teclejades, en una paraula és de gran importància. Altres estudis no prenen en consideració aquesta informació, és a dir, si la combinació de lletres s’ha produït al principi, al mig o al final de la paraula. Es crearà una empremta de l’usuari tenint en compte el context de les lletres en les paraules escrites i les latències entre pulsacions successives. Altres característiques com la mida de les paraules, el nombre mínim de paraules necessari per considerar una sessió vàlida, la freqüència de mots, els paràmetres de construcció dels models, així com el grup d’edat i el gènere també s’han estudiat per determinar quines són les que millor ajuden a identificar un individu. Els resultats de la recerca proposada haurien de permetre determinar si l’ús de la cadència de tecleig i els mètodes proposats són suficients per identificar els usuaris a partir del contingut que generen, sempre amb un cert marge d’error. En cas afirmatiu es podria introduir la tècnica proposada com un mètode més per assegurar que un usuari no és suplantat, en sistemes d’autenticació, o fins i tot per ajudar a determinar l’autoria de diferents parts d’un document que ha estat escrit per més d’un usuari.

The representation of stimuli within the human brain is a core, unresolved issue in Neuroscience. Invasive methods of investigation are not generally suitable for. use on healthy human subjects and so the main methods of investigation have been those using non-invasive imaging techniques including Magnetoencephalography (MEG). This thesis examines the analysis of MEG data using a spatial filtering approach known as beamforming.

The hypothesis in this paper is that the existence of retail markets may not necessarily be determined by spatial factors and increasing return in transportation (or increasing returns in retailing), but can be explained by the rational behaviour of firms operating in a stochastic environment. It is shown that demand uncertainty can serve as an independent source of retail trade. Consequently, the ability of firms to process information and predict demand (i.e., to decrease demand uncertainty) may affect the characteristics of retail markets. The results indicate that risk-averse firms always devote resources to demand forecasting; producers are better off trading with retailers than with final consumers; and the volume of output supplied through retail markets is greater than it would be if producers traded directly with consumers (thus benefiting social welfare). Furthermore, the paper shows that technological progress in data-processing, which allows for cheaper and better predictions of market demand, increases the number of firms operationg in retail markets. (authors' abstract)
Series: Discussion Papers of the Institute for Economic Geography and GIScience

Networks (or graphs) have become ubiquitous as data from diverse disciplines can naturally be mapped to graph structures. The problem of extracting meaningful information from large scale graph data in an efficient and effective way has become crucial and challenging with several important applications and towards this end, graph mining and analysis methods constitute prominent tools. This dissertation contributes models, tools and observations to problems that arise in the area of mining social and information networks. We built upon computationally efficient graph mining methods in order to: (i) design models for analyzing the structure and dynamics of real-world networks towards unraveling properties that can further be used in practical applications; (ii) develop algorithmic tools for large-scale analytics on data with inherent (e. G. , social networks) or without inherent (e. G. , text) graph structure. In particular, for the former point we show how to model the engagement dynamics of large social networks and how to assess their vulnerability with respect to user departures from the network. In both cases, by unraveling the dynamics of real social networks, regularities and patterns about their structure and formation can be identified; such knowledge can further be used in various applications including churn prediction, anomaly detection and building robust social networking systems. For the latter, we examine how to identify influential users in complex networks, having direct applications to epidemic control and viral marketing and how to utilize graph mining techniques in order to enhance text analytics tasks and in particular the one of text categorization.

La dissémination d'information explore les chemins pris par l'information qui est transmise dans un réseau social, afin de comprendre et modéliser les relations entre les utilisateurs de ce réseau, ce qui permet une meilleur compréhension des relations humaines et leurs dynamique. Même si la priorité de ce travail soit théorique, en envisageant des aspects psychologiques et sociologiques des réseaux sociaux, les modèles de dissémination d'information sont aussi à la base de plusieurs applications concrètes, comme la maximisation d'influence, la prédication de liens, la découverte des noeuds influents, la détection des communautés, la détection des tendances, etc. Cette thèse est donc basée sur ces deux facettes de la dissémination d'information: nous développons d'abord des cadres théoriques mathématiquement solides pour étudier les relations entre les personnes et l'information, et dans un deuxième moment nous créons des outils responsables pour une exploration plus cohérente des liens cachés dans ces relations. Les outils théoriques développés ici sont les modèles de dynamique d'opinions et de dissémination d'information, où nous étudions le flot d'informations des utilisateurs dans les réseaux sociaux, et les outils pratiques développés ici sont un nouveau algorithme de détection de communautés et un nouveau algorithme de détection de tendances dans les réseaux sociaux
Our aim in this Ph. D. thesis is to study the diffusion of information as well as the opinion dynamics of users in social networks. Information diffusion models explore the paths taken by information being transmitted through a social network in order to understand and analyze the relationships between users in such network, leading to a better comprehension of human relations and dynamics. This thesis is based on both sides of information diffusion: first by developing mathematical theories and models to study the relationships between people and information, and in a second time by creating tools to better exploit the hidden patterns in these relationships. The theoretical tools developed in this thesis are opinion dynamics models and information diffusion models, where we study the information flow from users in social networks, and the practical tools developed in this thesis are a novel community detection algorithm and a novel trend detection algorithm. We start by introducing an opinion dynamics model in which agents interact with each other about several distinct opinions/contents. In our framework, agents do not exchange all their opinions with each other, they communicate about randomly chosen opinions at each time. We show, using stochastic approximation algorithms, that under mild assumptions this opinion dynamics algorithm converges as time increases, whose behavior is ruled by how users choose the opinions to broadcast at each time. We develop next a community detection algorithm which is a direct application of this opinion dynamics model: when agents broadcast the content they appreciate the most. Communities are thus formed, where they are defined as groups of users that appreciate mostly the same content. This algorithm, which is distributed by nature, has the remarkable property that the discovered communities can be studied from a solid mathematical standpoint. In addition to the theoretical advantage over heuristic community detection methods, the presented algorithm is able to accommodate weighted networks, parametric and nonparametric versions, with the discovery of overlapping communities a byproduct with no mathematical overhead. In a second part, we define a general framework to model information diffusion in social networks. The proposed framework takes into consideration not only the hidden interactions between users, but as well the interactions between contents and multiple social networks. It also accommodates dynamic networks and various temporal effects of the diffusion. This framework can be combined with topic modeling, for which several estimation techniques are derived, which are based on nonnegative tensor factorization techniques. Together with a dimensionality reduction argument, this techniques discover, in addition, the latent community structure of the users in the social networks. At last, we use one instance of the previous framework to develop a trend detection algorithm designed to find trendy topics in a social network. We take into consideration the interaction between users and topics, we formally define trendiness and derive trend indices for each topic being disseminated in the social network. These indices take into consideration the distance between the real broadcast intensity and the maximum expected broadcast intensity and the social network topology. The proposed trend detection algorithm uses stochastic control techniques in order calculate the trend indices, is fast and aggregates all the information of the broadcasts into a simple one-dimensional process, thus reducing its complexity and the quantity of necessary data to the detection. To the best of our knowledge, this is the first trend detection algorithm that is based solely on the individual performances of topics

We propose cells generate large transmembrane ion gradients to form information circuits that detect, process, and respond to environmental perturbations or signals. In this model, the specialized gates of transmembrane ion channels function as information detectors that communicate to the cell through rapid and (usually) local pulses of ions. Information in the ion "puffs" is received and processed by the cell through resulting changes in charge density and/or mobile cation (and/or anion) concentrations alter the localization and function of peripheral membrane proteins. The subsequent changes in protein binding to the membrane or activation of K+, Ca2+ or Mg2+ -dependent enzymes then constitute a cellular response to the perturbation. To test this hypothesis we analyzed ion-based signal transmission as a communication channel operating with coded inputs and decoded outputs. By minimizing the Kullback-Leibler cross entropy H-KL(p||q) between concentrations of the ion species inside p(i)(t) i = 1,.,N , and outside q(i)(t) the cell membrane, we find signal transmission through transmembrane ion flow forms an optimal Shannon information channel that minimizes information loss and maximizes transmission speed. We demonstrate the ion dynamics in neuronal action potentials described by Hodgkin and Huxley (including the equations themselves) represent a special case of these general information principles.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2000.
Includes bibliographical references (p. 61-64).
Supply chains are nonlinear dynamic systems, the control of which is complicated by long, variable delays in product and information flows. In this thesis, we present a novel framework for improving the visibility of information in supply chains by reducing the delays in information flow. We first analyze the growth and evolution of production and operations management software over the past three decades, and the current trends in their development, coupled with recent advances in radio frequency technology, wireless communications, data representation methods, and the internet. Information visibility is identified as one of the key elements for successful implementation of any such software. We analyze the dynamics of a supply chain under different scenarios of information visibility and forecasting decisions with the help of simulations. Possible improvements in supply chain costs are identified, provided information visibility. We propose a framework to achieve information visibility in the supply chain using radio frequency tags, tag readers, product identification codes, an object description language, and the internet.
by Yogesh V. Joshi.
S.M.

"From the point of view of information technology the past decade can be designated the “decade of ERP”. A global movement of implementing integrated systems for optimising the fulfilment of orders has dominated both investments from large and medium corporations and the focus of research and educational institutions. The results of these implementations sometimes have been dramatic: Significant improvements of throughput time, and at the same time clear decreases in inventory. Organisations have become like machines. Interesting material - though not in all aspects consistent - on the improvement of productivity is collected in (Potthof, 1998). Unfortunately, and strangely enough, only little research has been done in the consequences of ERP systems on the flexibility and adaptability of organisations."

From the point of view of information technology the past decade can be designated the “decade of ERP”. A global movement of implementing integrated systems for optimising the fulfilment of orders has dominated both investments from large and medium corporations and the focus of research and educational institutions. The results of these implementations sometimes have been dramatic: Significant improvements of throughput time, and at the same time clear decreases in inventory. Organisations have become like machines. Interesting material - though not in all aspects consistent - on the improvement of productivity is collected in (Potthof, 1998). Unfortunately, and strangely enough, only little research has been done in the consequences of ERP systems on the flexibility and adaptability of organisations.

The neural net computer simulations which will be presented here are based on the acceptance of a set of assumptions that for the last twenty years have been expressed in the fields of information processing, neurophysiology and cognitive sciences. First of all, neural networks and their dynamical behaviors in terms of attractors is the natural way adopted by the brain to encode information. Any information item to be stored in the neural net should be coded in some way or another in one of the dynamical attractors of the brain and retrieved by stimulating the net so as to trap its dynamics in the desired item's basin of attraction. The second view shared by neural net researchers is to base the learning of the synaptic matrix on a local Hebbian mechanism. The last assumption is the presence of chaos and the benefit gained by its presence. Chaos, although very simply produced, inherently possesses an infinite amount of cyclic regimes that can be exploited for coding information. Moreover, the network randomly wanders around these unstable regimes in a spontaneous way, thus rapidly proposing alternative responses to external stimuli and being able to easily switch from one of these potential attractors to another in response to any coming stimulus.

In this thesis, it is shown experimentally that the more information is to be stored in robust cyclic attractors, the more chaos appears as a regime in the back, erratically itinerating among brief appearances of these attractors. Chaos does not appear to be the cause but the consequence of the learning. However, it appears as an helpful consequence that widens the net's encoding capacity. To learn the information to be stored, an unsupervised Hebbian learning algorithm is introduced. By leaving the semantics of the attractors to be associated with the feeding data unprescribed, promising results have been obtained in term of storing capacity.
Doctorat en sciences appliquées
info:eu-repo/semantics/nonPublished

Nowadays, the global supply chain system needs to respond promptly to changes in customer demand and adapt quickly to advancements in technology. Supply chain management becomes an integral approach which links together producers, distributors and customers in collaborative management of the whole system. The variability in orders or inventories in supply chain systems is generally thought to be caused by exogenous random factors such as uncertainties in customer demand or lead time. Studies have shown, however, that orders or inventories may exhibit significant variability, even if customer demand and lead time are deterministic. Most researchers have concentrated on the effects of the ordering policy on supply chain behaviour, while not many have paid attention to the influences of applying different forecasting to supply chain planning. This thesis presents an analysis of the behaviour of a model of a centralised supply chain. The research was conducted within the manufacturing sector and involved the breathing equipment manufacturer Draeger Safety, UK. The modelling process was embedded in the organization and was focused on the client's needs. A simplified model of the Draeger Safety, UK centralised supply chain was developed and validated. The dynamics of the supply chain under the influence of various factors: demand pattern, ordering policy, demand-information sharing, and lead time were observed. Simulation and analysis were performed using system dynamics, non-linear dynamics and control theory. The findings suggest that destructive oscillations of inventory could be generated by internal decision making practices. To reduce the variation in the supply chain system, the adjustment parameters for both inventory and supply line discrepancies should be more comparable in magnitude. Counter- intuitively, in certain fields of decision, sharing demand information can do more harm than good. The linear forecasting ARMA (autoregression and moving average) model and the nonlinear forecasting model Wavelet Neural Network were applied as the supply chain forecasting methods. The performance was tested against supply chain costs. A management microworld was developed, allowing managers to experiment with different decision policies and learn how the supply chain performs.

For analysing financial time series two main opposing viewpoints exist, either capital markets are completely stochastic and therefore prices follow a random walk, or they are deterministic and consequently predictable. For each of these views a great variety of tools exist with which it can be tried to confirm the hypotheses. Unfortunately, these methods are not well suited for dealing with data characterised in part by both paradigms. This thesis investigates these two approaches in order to model the behaviour of financial time series. In the deterministic framework methods are used to characterise the dimensionality of embedded financial data. The stochastic approach includes here an estimation of the unconditioned and conditional return distributions using parametric, non- and semi-parametric density estimation techniques. Finally, it will be shown how elements from these two approaches could be combined to achieve a more realistic model for financial time series.

The Hardwood Industry in United States has been challenged by low-cost competition from overseas. Although cost reduction strategies have had minimal success, the proximity of industry to the domestic market has large implications on a more customer-focused strategy. The problem arises that individual companies and supply chains evolved based on the principles of economies of size and not on the flexibility to adapt to customer needs and changing resource constraints. An increased rate at which material and information flows through the hardwood supply chains is the key to the industriesâ ability to be customer-focused. Information systems may offer benefits for the industry, but changes in material flow of a company or supply chain cannot necessarily be predicted when implementing information systems. It was hypothesized that by understanding the dynamics between information flow and material flow throughout the supply chain, performance improvement would be possible through more effective release and use of information. A case study analysis of a hardwood supply chain was utilized to identify the effect of increased information flow on the material flow of the supply chain. Value Stream Mapping was utilized to benchmark the current state of lead times of information flow and material flow. System Dynamics was utilized to understand the relationships between the information flow and the material flow. Finally, simulations were performed to identify the specific effects on material flow as increased information flow is released through different information strategies. The study showed that increased information flow between supply chain members increased material flow through the supply chain. For a case study supply chain, an increase in information flow, through advanced knowledge of customer demand by a supplier, was found to reduce the inventory buffers throughout the supply chain by up to 38 percent and increase the total material flow through the supply chain by 10 percent. In addition to the increased information flow caused by the advanced knowledge of demand (18 percent), information flow would increase (by an additional 7 percent) based on the reductions in buffer inventory within each company of the supply chain.
Ph. D.

Oscillatory neural activity is closely related to cognition and behaviour, with synchronisation mechanisms playing a key role in the integration and functional organization of different cortical areas. Nevertheless, its informational content and relationship with behaviour - and hence cognition - are still to be fully understood. This thesis is concerned with better understanding the role of neuronal oscillations and information dynamics towards the generation of embodied cognitive behaviours and with investigating the efficacy of such systems as practical robot controllers. To this end, we develop a novel model based on the Kuramoto model of coupled phase oscillators and perform three minimally cognitive evolutionary robotics experiments. The analyses focus both on a behavioural level description, investigating the robot's trajectories, and on a mechanism level description, exploring the variables' dynamics and the information transfer properties within and between the agent's body and the environment. The first experiment demonstrates that in an active categorical perception task under normal and inverted vision, networks with a definite, but not too strong, propensity for synchronisation are more able to reconfigure, to organise themselves functionally, and to adapt to different behavioural conditions. The second experiment relates assembly constitution and phase reorganisation dynamics to performance in supervised and unsupervised learning tasks. We demonstrate that assembly dynamics facilitate the evolutionary process, can account for varying degrees of stimuli modulation of the sensorimotor interactions, and can contribute to solving different tasks leaving aside other plasticity mechanisms. The third experiment explores an associative learning task considering a more realistic connectivity pattern between neurons. We demonstrate that networks with travelling waves as a default solution perform poorly compared to networks that are normally synchronised in the absence of stimuli. Overall, this thesis shows that neural synchronisation dynamics, when suitably flexible and reconfigurable, produce an asymmetric flow of information and can generate minimally cognitive embodied behaviours.

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2007.
Includes bibliographical references (p. 166-169).
As companies are increasingly relying on information technologies (IT) to help maintain their existing and develop new competitive advantages, investing effectively in IT is becoming more and more important. One of the biggest challenges facing an enterprise IT organization is how to select a project portfolio that is best aligned with the business strategies and to deliver highest value using limited IT resources. In this research paper, I examined in detail a recently proposed IT governance framework, designed a System Dynamics model based on this framework, and developed a simulation application to investigate constructs, relationships and scenarios suggested by the framework. My research identified and examined several levers through which IT managers can achieve better alignment with business goals and more efficient use of IT resources. I examined alternative IT governance regimes (combinations of rules and policies for selecting among opportunities and retaining existing systems) in terms of their effects on efficiency, feature satisfaction, and cost of the resulting legacy asset base. By choosing the right combination of relatively straightforward selection and retention policies, IT managers can steer their legacy assets toward a desired efficiency or satisfaction goal in concert with company strategies.
by Bin Zhou.
S.M.

A travers cette étude, se présente une perspective dynamique de l'annotation sémantique. Cette perspective considère le passage du temps et les flux permanents de documents qui font croître les collections et étendre leurs systèmes d'annotation. Nous apportons également une vision de la qualité des systèmes d'annotations basée sur la notion d'accès à l'information et de cohérence. Dans notre vision de la qualité, l'information de vocabulaire d'annotation est la complexité à parcourir par un utilisateur à la recherche d'un certain sujet.Pour répondre au problème de la dynamique dans l'annotation sémantique, cette thèse propose une architecture modulaire pour l'annotation sémantique dynamique. Cette architecture modélise les activités impliquées dans le processus d'annotation sémantique en modules abstraits avec des considérations particulières en fonction de la tâche spécifique.Comme cas d'étude, nous prenons l’annotation de blogs. Nous rassemblâmes un corpus contenant jusqu'à 10 ans de billets de blog annotés avec des catégories et des tags et analysé les habitudes d'annotation observées. Nous explorons la suggestion automatique de tags et de catégories afin de mesurer l'impact de la dynamique dans le système d'annotation. Certaines stratégies pour faire face à cet impact ont été évaluées pour caractériser l'importance de l'âge des exemples.Enfin, nous proposons un cadre de trois mesures de qualité et une méthode interactive pour récupérer la qualité d'un système d'indexation basé sur des annotations sémantiques appuyée par les métriques. Les mesures ont été évaluées au fil du temps pour observer la dégradation de la qualité de l'indexation. Une série d'exemples étudiés sont présentés pour observer la performance des mesures visant à guider la restructuration du système d'annotation de l'indexation
The information is growing and evolving everyday and in every human activity. Documents of different modalities store our information. The dynamic nature of information is given by a flow of documents. The huge and ever-growing document collections opens the need for organizing, relating and searching for information in an efficient way. Although full-text search tools have been developed, people continue to categorize documents, often using automatic classification tools. These annotations categories can be considered as a semantic indexing: classifying newspaper articles or blog posts allows journalists or readers to quickly find documents that have been published in the past in relation to a given topic. However, the quality of an index based on semantic annotation often deteriorates with time due to the dynamics of the information it describes: some categories are misused or forgotten by indexers, others become obsolete or too general to be useful. Through this study we introduce a dynamic perspective of semantic annotation. This perspective considers the passage of time and the permanent flow of documents that makes the collections grow and their annotation systems to extend and evolve. We also bring a vision of the quality of annotations systems based on the notion of information access. Traditionally, the quality of the annotation is considered in terms of semantic adequacy between the contents of the documents and the annotation terms describe them. In our vision, the quality of annotation vocabulary depends on the amount and complexity of information to be navigated by a user while searching for a certain topic. To address the problem of the dynamics in semantic annotation, this work proposes a modular architecture for dynamic semantic annotation. This architecture models the activities involved in the semantic annotation process in abstract modules dedicated to the different tasks that users have to perform. As a case of study we took blogging annotation. We gathered a corpus containing up to 10 years of annotated blog posts with categories and tags and we analyzed the annotation habits. By testing automatic tag and category strategies, we measure the impact of the dynamics in the annotation system. We propose some strategies to control this impact, which helps to evaluate the obsolescence of examples. Finally we propose a framework relying on three quality metrics and an interactive method to recover the quality of an indexing system based on semantic annotation. The metrics are evaluated over time to observe the degradation in indexing quality. A series of studied examples are presented to observe the performance of the measures to guide the restructuring of the indexing annotation system

Small and Medium Enterprises (SMEs) in the United Kingdom (UK) have almost universally adopted information and communications technology (lCT). So, they are subject to information security threats. Fortunately, there are readily available information security and identity theft resources offering advice and guidance. However, most resources do not specifically address SMEs. This research reviews the relevant information system (IS), information security and SME ICT characteristics literature. The overall aim is to contribute to the understanding of contemporary information security dynamics. Quantitative and qualitative approaches are used to ascertain the nature ofcontemporary respondent information security issues. This research reveals limited SME-oriented IS and information security literature. Respondent§had limited awareness about their information security risks. They had failed to take the appropriate organisational and technical steps to mitigate their risks. Respondents were found to be at risk from a range ofinformation security threats. The contributions ofthis research are two theories explaining aspects of contemporary information sec~ty dynamics amongst respondents. One theory presents constructs to exploit SME information security weaknesses, whilst the other theory presents SME information security improvement constructs. From the improvement theory and identified information security resources, a more concrete recommendations road map with a hierarchy of implementation levels is developed. The road map was packaged and successfully piloted on an SME.

Companies increasingly rely on external partners when starting their innovation initiatives. Emergent innovation ecosystems of heterogeneous actors proved to be successful in leveraging combined competence for the creation of the new ventures. However, constantly changing environment of simultaneous competition and cooperation – coopetition, presents a challenge for the ecosystem management. Drawing on the network orchestration and coopetition research, I analyze management practices and coopetition dynamics in the digital creative industry in Northern Sweden. Based on the analysis, I offer two main contributions. First, I provide a detailed account of innovation ecosystem orchestration within the digital creative industry, including its chronological evolution and the challenges related to it. Second, the application of coopetition notion to the innovation ecosystem context brings forward tensions that should be further scrutinized in order to develop better management practices for such innovation networks.

Manufacturing supply chains are invariably dynamic and complicated in nature. Hence, steady state models are not sufficient for analyzing and designing supply chains. Models of supply chains must accurately capture their dynamic behavior, which is determined by the structure of the organization, and the policies adopted by management. System dynamics modeling provides a powerful framework for this purpose. The use of system dynamics models in supply chain management has thus far been limited to explaining phenomenon like the bullwhip effect, and for policy development. We provide a structured approach for policy design, which doesnâ t rely on any simulation experiments. Further, we study the impact that information network design has on the response of supply chains. We use a combinatorial approach to develop guidelines for information network design. Further, we examine the possibility of utilizing a PID information feedback structure to enhance the responsiveness of the supply chain. Lastly, we propose a combined feedback feed-forward information structure to enable a supply chain to rapidly respond to disturbances whose effects are known. The goal of this dissertation is to provide a structured approach for the design of information network structure, and operating policy.
Ph. D.

Living beings strive to survive and reproduce. To do so they need to monitor and adapt to a dynamic environment, taking advantage of the opportunities and dodging the threats that they may encounter. This thesis is devoted to analyse, using a mathematical and computational approach, a variety of mechanisms of anticipation, adaptation, and resistance to changes in the external conditions. To do so, we have studied regulatory systems across different scales. First, we analysed the genetic circuit that controls the galactose utilization by Saccharomyces cerevisiae, which is composed by a small set of genes, with the goal of establishing the tools to explore the epistatic interactions of mutations within this system. Second, we propose a framework to understand how cellular regulatory networks, composed by hundreds or thousands of elements, can process time-dependent information in a state-dependent manner. Finally, we discovered and characterised the mechanism of growth oscillations in biofilms of Bacillus subtilis cells. We found that these oscillations are caused by the metabolic co-dependence between distant groups of cells, and are crucial to ensure the resistance of the colony to external aggressions.
Els éssers vius malden per sobreviure i reproduir-se. Per aconseguir-ho necessiten monitoritzar i adaptar-se a un ambient dinàmic, aprofitant les oportunitats i esquivant les amenaces que els sobrevenen. L’objectiu d’aquesta tesis ha estat analitzar, mitjançant eines matemàtiques i computacionals, alguns dels mecanismes cel lulars d’anticipació, adaptació i resistència a canvis en el medi. Per fer-ho hem estudiat sistemes de regulació en diferents escales. En primer lloc, hem analitzat el circuit genètic, format per uns pocs gens, que controla el consum de galactosa per part de Saccharomyces cerevisiae, i hem desenvolupat les eines necessàries per explorar les interaccions epistàtiques entre mutacions dins aquest sistema. En segon lloc, proposem un marc teòric per explicar com les xarxes de regulació cel lular, que consten de centenars o milers d’elements, poden processar informació temporal codificant-la en la seva pròpia dinàmica. Finalment, hem descobert i caracteritzat el mecanisme d’oscil lacions en el creixement de biofilms de Bacillus subtilis. Aquestes oscil lacions són conseqüència de l’acoblament metabòlic entre regions distants del biofilm, i juguen un paper crucial per assegurar la resistència de la colònia a agressions externes.

1. The Force Field Accuracy Problem. The utility and applicability of MD simulations to model biomolecular systems goes only as far as its ability to sufficiently sample the conformational space and the correct description of the potential in terms of the force field functional form and parameter set. Clearly, the force field defines the shape of the conformational space for a given set of atomic positions and also the accessibility of energy minima. When simulating systems at equilibrium, especially quite stable systems such as DNA, the force fields strive to generate ensembles that reproduce well real systems and this does not have to come as a big trade-off with sampling power. In recent years it has become the business of computer engineers and software developers to address the issue of achieving long and biologically relevant time scales. Convergence and reproducibility of atomistic DNA simulations with state-of-the-art force fields such as our parmbsc1 has been convincingly demonstrated. It also seems that until a significant revolution, where milliseconds of simulation become routine, current sampling ranges completely cover the internal structures and dynamics of B-DNAs at this time scale. The growing confidence has allowed many researchers to use MD for very detailed studies on the sequence-dependent nature of DNA oligomers and on the complex arsenal of mechanisms that govern its behavior. In any such studies careful validation of results is necessary since it is not yet entirely clear how well and to what degree are sequence effects reproduced in MD. The fact that the latest-generation of force fields agree very well between themselves and that they fit with the sparse experimental data is surely very encouraging, but it will be some time until small differences in sequence geometries can be validated. Our own extensive validation of the parmbsc1 force field, as well as a large number of other works that have, since its publication, either specifically set out to assess its performance, or have just applied it with success, speak of a very stable parametrization able to deal with a wide range of DNAs. It is worth to mention that in special conditions small improvements might be necessary, which could be achieved with the inclusion of polarization terms. However, up to date, no force field has been able to model polarization without eventually destabilizing the system and this at a huge cost (a factor of 10) to calculation speed. To sum up, based on the remarkable performance of parmbsc1, we and other groups can employ it with confidence in the detailed study of DNA dynamics and we expect that the number of supporting results will only increase. 2. 2. Sequence-dependence and polymorphisms of B-DNA. So what is it that we actually learn from analyzing the conformation variability of DNA over its sequence space at the tetramer level? It is well established that different bps have different preferences regarding their internal geometries, and to some extent, Calladine’s set of heuristic rules is able to make sense of these differences. At the bps level, some sequences are extremely stable, such as ApT, and some sequences, such as CpG, have a bi-stable equilibrium and they convert between different arrangements of their internal geometries. There are cases where this frustration can be explained by their charge distribution, bulkiness or the strength of their stacking and h-bonding interactions, but in many cases in requires a more holistic view, taking higher-level sequence effects into account. In multi-microsecond MD simulations, intra-base-pair parameters are always unimodal since alternative states that might be accessed through base opening are not sampled in at this time scale. However, their ensemble averages show sizeable differences according to the change in sequence. Inter- base-pair parameters can be bimodal, but only in certain tetranulceotide combinations that make up about 5% of cases. This can be explained considering that the central bps of a particular combination of four nucleotides has a structural preference that is in conflict with those of its neighboring steps. In order to minimize the energy cost and satisfy as best as possible all conformational requirements, a more flexible bps will populate several states, usually a maximum of two. Optimization of geometries between several bps generally involve backbone rearrangements, with the sugar-phosphate acting as a hinge that allows consecutive bps to coordinate in a complex choreography often involving other factors, such as subtle changes in the solvent environment environment. In B-DNA the most important backbone transition is the BI/BII, which can be related to the base chemistry through the sequence-dependent relative strength of unconventional h-bonds that stabilize BII conformations. In a tetramer model of B-DNA, the backbone transitions of different tetramers are translated into motions along different internal degrees of freedom, depending on the sequence. Therefore, we are able now to build a picture of the interconnected conformational space of DNA as an overlap of tetranucleotide sequences with transferable structural descriptors. It is still a matter of speculation how these properties might be exploited by proteins and other binders for biological function. 3. Information transfer through the DNA. There are however a few special cases where the tetramer model does not seem to be sufficient. The CTAG is one such case that demonstrates that for a highly flexible and polymorphic tetramer, long-range sequence composition can have a notable effect on the structural properties of the central bps. Analyzing the mechanism behind this long-range communication through the DNA has meant more than anything else an opportunity to understand rare events of sequence modulation that might be a lot more general in cases of larger, induced distortions on the helix. In CTAG we could observe sequence influence not only from the hexamer level, but even from beyond, and the data points to a complex mechanism of information transfer across DNA through coordinated backbone movements. In performing biological function, DNA is often mistakenly viewed as an inert lattice onto which proteins assemble to replicate or transcribe genes. However, experiments demonstrate that information transfer in the DNA can happen even over long distances and can produce allosteric effects upon ligand binding. Without question, the binding of proteins or small molecules to the DNA can produce coupled conformational changes that may affect a neighboring binding site and increase its affinity for the secondary binding protein. Such changes need not alter ensemble averages and only potentiate modifications in the shape of the energy well at the secondary binding site. As seen from the dynamic information provided by an MD trajectory, maybe in more than one case of protein couples, DNA acts as a wire transmitting pulses of information originated at the primary binding site that travel to distant regions. We show that MD methods can provide reasonable explanations for cooperative binding phenomena on the DNA and open for the first time the possibility of the “allostery without conformational change” in the recruitment of proteins of the DNA scaffold. From a thermodynamic point of view, this type of cooperative binding seems to be entropy-driven. Thus, the first binding event freezes some of the degrees of freedom around it’s own binding region, but also reduces the entropy cost associated to the second binding.
1. Problema de exactitud del campo de fuerza La utilidad y aplicabilidad de las simulaciones de DM para modelar sistemas biomoleculares depende de su capacidad para muestrear suficientemente el espacio conformacional y la descripción correcta del potencial en términos de la forma funcional del campo de fuerza y el conjunto de parámetros. Claramente, el campo de fuerza define la forma del espacio conformacional para un conjunto dado de posiciones atómicas y también el acceso a los mínimos energéticos. Al simular sistemas en equilibrio, especialmente en sistemas bastante estables como el ADN, los campos de fuerza se esfuerzan por generar conjuntos que reproducen sistemas reales y no tiene por qué ser una gran desventaja con el poder de muestreo. En los últimos años, se ha convertido en tarea de los ingenieros informáticos y los desarrolladores de software abordar el problema de lograr escalas de tiempo largas y biológicamente relevantes. La convergencia y reproducibilidad de simulaciones de ADN atomístico con campos de fuerza de última generación, como nuestro parmbsc1, se ha demostrado de forma convincente. También parece que hasta llegar a una revolución significativa, donde los milisegundos de simulación se vuelven rutinarios, los rangos de muestreo actuales cubren por completo las estructuras internas y la dinámica de los ADN-B en esta escala de tiempo. La creciente confianza ha permitido a muchos investigadores utilizar DM para estudios muy detallados sobre la naturaleza dependiente de la secuencia de oligómeros de ADN y sobre el complejo arsenal de mecanismos que rigen su comportamiento. En cualquiera de estos estudios es necesaria una validación cuidadosa de los resultados ya que aún no está del todo claro qué tan bien y en qué grado se reproducen los efectos de secuencia en DM. El hecho de que la última generación de campos de fuerza coincida muy bien entre sí y que se ajusten a los escasos datos experimentales es seguramente muy alentador, pero pasará algún tiempo hasta que se puedan validar pequeñas diferencias en las geometrías de las secuencias. Nuestra propia validación extensiva del campo de fuerza parmbsc1, así como una gran cantidad de otros trabajos que, desde su publicación, se han establecido específicamente para evaluar su rendimiento, o simplemente lo han aplicado con éxito, hablan de una parametrización muy estable capaz de tratar con una amplia gama de ADN. Vale la pena mencionar que en condiciones especiales podrían ser necesarias pequeñas mejoras, lo que podría lograrse con la inclusión de términos de polarización. Sin embargo, hasta la fecha, ningún campo de fuerza ha sido capaz de modelar la polarización sin desestabilizar finalmente el sistema y esto a un costo enorme (un factor de 10) a la velocidad de cálculo. En resumen, con base en el notable desempeño de parmbsc1, nosotros y otros grupos podemos emplearlo con confianza en el estudio detallado de la dinámica del ADN y esperamos que el número de resultados de soporte solo aumente. 2. Dependencia de la secuencia y polimorfismos del ADN-B. Entonces, ¿qué es lo que realmente aprendemos al analizar la variabilidad de conformación del ADN sobre su espacio de secuencia a nivel de los tetrámeros? Está bien establecido que diferentes bps tienen diferentes preferencias con respecto a sus geometrías internas, y hasta cierto punto, el conjunto de reglas heurísticas de Calladine es capaz de dar sentido a estas diferencias. A nivel de bps, algunas secuencias son extremadamente estables, como ApT, y algunas secuencias, como CpG, tienen un equilibrio biestable y convierten entre diferentes disposiciones de sus geometrías internas. Hay casos en que esta frustración puede explicarse por la distribución de cargas, el volumen o la fuerza de sus interacciones de apilamiento y los puentes de hidrógeno, pero en muchos casos requiere una visión más integral, teniendo en cuenta los efectos de secuencia de más alto nivel. En simulaciones de DM de multi-microsegundos, los parámetros de pares intra-base son siempre unimodales ya que los estados alternativos a los que se puede acceder a través de la apertura de la base no se muestrean en esta escala de tiempo. Sin embargo, sus promedios de conjunto muestran diferencias considerables de acuerdo con el cambio en la secuencia. Los parámetros de pares de bases pueden ser bimodales, pero solo en ciertas combinaciones de tetranulceótidos que constituyen aproximadamente el 5% de los casos. Esto puede explicarse teniendo en cuenta que el bps central de una combinación particular de cuatro nucleótidos tiene una preferencia estructural que está en conflicto con la de sus pasos vecinos. Con el fin de minimizar el costo de energía y satisfacer de la mejor manera posible todos los requisitos conformacionales, un bps más flexible poblará varios estados, generalmente un máximo de dos. La optimización de las geometrías entre varios bps generalmente implica reorganizaciones de la red troncal, con el azúcar fosfato actuando como una bisagra que permite la coordinación consecutiva de bps en una coreografía compleja que a menudo involucra otros factores, tales como cambios sutiles en el entorno del solvente. En los ADN-B, la transición principal más importante es BI/BII, que se puede relacionar con la química a través de la fuerza relativa dependiente de la secuencia de puentes de hidrógeno no convencionales que estabilizan las conformaciones BII. En un modelo de tetrámero de ADN-B, las transiciones de la cadena principal de diferentes tetrámeros se traducen en movimientos a lo largo de diferentes grados internos de libertad, dependiendo de la secuencia. Por lo tanto, ahora podemos construir una imagen del espacio conformacional interconectado del ADN como una superposición de secuencias de tetranucleótidos con descriptores estructurales transferibles. Todavía es una cuestión de especulación cómo estas propiedades podrían ser explotadas por proteínas y otras moléculas que se unen al ADN para diferentes funciones biológicas. 3. Transferencia de información a través del ADN. Sin embargo, hay algunos casos especiales en los que el modelo de tetrámero no parece ser suficiente. El CTAG es uno de esos casos que demuestra que, para un tetrámero altamente flexible y polimórfico, la composición de la secuencia de largo alcance puede tener un efecto notable sobre las propiedades estructurales del bps central. Analizar el mecanismo detrás de esta comunicación de largo alcance a través del ADN ha significado más que nada una oportunidad para comprender los raros eventos de modulación de secuencia que podrían ser mucho más generales en casos de distorsiones mayores e inducidas en la hélice. En CTAG pudimos observar la influencia de la secuencia no solo desde el nivel del hexámero, sino incluso más allá, y los datos apuntan a un complejo mecanismo de transferencia de información a través del ADN mediante movimientos coordinados de la cadena principal. En la realización de la función biológica, el ADN a menudo se considera erróneamente como un retículo inerte sobre el cual las proteínas se ensamblan para replicar o transcribir genes. Sin embargo, los experimentos demuestran que la transferencia de información en el ADN puede ocurrir incluso a largas distancias y puede producir efectos alostéricos sobre la unión al ligando. Sin lugar a duda, la unión de proteínas o moléculas pequeñas al ADN puede producir cambios conformacionales acoplados que pueden afectar a un sitio de unión vecino y aumentar su afinidad por la proteína de unión secundaria. Tales cambios no necesitan alterar los promedios del conjunto y solo potencian modificaciones en la forma del pozo de energía en el sitio de unión secundario. Como se ve a partir de la información dinámica proporcionada por una trayectoria de DM, tal vez en más de un caso de parejas de proteínas, el ADN actúa como un cable que transmite pulsos de información originados en el sitio primario de unión que viajan a regiones distantes. Mostramos que los métodos de DM pueden proporcionar explicaciones razonables para los fenómenos de unión cooperativa en el ADN y abren por primera vez la posibilidad de la "alostería sin cambio conformacional" en el reclutamiento de proteínas al ADN. Desde un punto de vista termodinámico, este tipo de enlace cooperativo parece estar impulsado por la entropía. Por lo tanto, el primer evento vinculante congela algunos de los grados de libertad alrededor de su propia región de unión, pero también reduce el costo de entropía asociado al segundo enlace.

Thesis (Ph. D.)--University of California, San Diego, 2009.
Title from first page of PDF file (viewed July 14, 2009). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references.

This thesis investigates the relationships between surveillance, acts of resistance to surveillance and their respective roles in the contemporary social order. The context for this investigation is the contemporary ‘information society’. This is characterised by globally networked information and communication technologies, and is represented most plainly by one medium in particular: the Internet. The Internet has historically been a contested domain; it represents, for some, the cornerstone of civil liberties yet at the same time it is highly regulated and susceptible to control. The significant social, cultural, economic and political impacts of the Internet include the proliferation of techniques of digital surveillance. However, while the Internet has facilitated the growth of these practices, it has also created new opportunities for resistance to surveillance. By attending to the social dynamics and mechanics of resistance, we can generate more nuanced and subtle understandings of the ways in which social control is being performed. A framework of nodal governance steers this research. Consequently, this study locates these dynamics within three specific sites: online civil society, the regulatory process and the media. These cases demonstrate how a range of social actors, across a variety of settings, are implicated in the dynamics of digital surveillance and resistance. An innovative, multi-strategy approach to the fieldwork, including computational social science methods, captures these emergent dynamics as they are played out. The analysis of the data is guided by a theoretical preoccupation with control that serves to illustrate its plural and fluid character. Central to this are social and technological networks as forms of organisation and communication that facilitate surveillance and resistance. The thesis concludes that contemporary social control is an inherently socio-technical process, shaped primarily by dynamics of digital surveillance and resistance.

This paper examines the challenges involved in understanding group dynamics when utilizing online teaching platforms, such as WebCT. When the student cohort involved is studying professionally oriented technical subjects, people who have prior knowledge of this professional area may exhibit be-haviors which overwhelm other students. In traditional face-to-face tutorial and workshop environments, teachers are able to interact with students, ensuring that they have a comfortable environment in which to contribute and learn. This may involve bringing them out of themselves when they appear intimidated and re-directing them when they threaten to dominate. Teachers can interpret body language and use their own body language and facial expressions as well as verbal comment to maintain a student-centered learning environment. It is much more difficult to influence the dynamics of online discussion. Our ex-perience at Curtin has shown that the potential for intimidation of students leading to their non-participation is stronger than in the classroom, especially when prior professional knowledge and experi-ence is involved. This outcome is opposite to expectations of web communication, usually believed to be an environment where people can overcome the constraints of their personality and participate in discus-sion more easily. Reasons this may occur will be examined together with techniques for ensuring that students are afforded an equitable learning environment.