Relevant bibliographies by topics / Network thermodynamics

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Network thermodynamics'

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Published: 1 March 2025

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Journal articles on the topic "Network thermodynamics"

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Wampler, Taylor, and Andre C. Barato. "Skewness and kurtosis in stochastic thermodynamics." Journal of Physics A: Mathematical and Theoretical 55, no. 1 (December 9, 2021): 014002. http://dx.doi.org/10.1088/1751-8121/ac3b0c.

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Abstract The thermodynamic uncertainty relation is a prominent result in stochastic thermodynamics that provides a bound on the fluctuations of any thermodynamic flux, also known as current, in terms of the average rate of entropy production. Such fluctuations are quantified by the second moment of the probability distribution of the current. The role of higher order standardized moments such as skewness and kurtosis remains largely unexplored. We analyze the skewness and kurtosis associated with the first passage time of thermodynamic currents within the framework of stochastic thermodynamics. We develop a method to evaluate higher order standardized moments associated with the first passage time of any current. For systems with a unicyclic network of states, we conjecture upper and lower bounds on skewness and kurtosis associated with entropy production. These bounds depend on the number of states and the thermodynamic force that drives the system out of equilibrium. We show that these bounds for skewness and kurtosis do not hold for multicyclic networks. We discuss the application of our results to infer an underlying network of states.
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Tasnim, Farita, and David H. Wolpert. "Stochastic Thermodynamics of Multiple Co-Evolving Systems—Beyond Multipartite Processes." Entropy 25, no. 7 (July 17, 2023): 1078. http://dx.doi.org/10.3390/e25071078.

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Many dynamical systems consist of multiple, co-evolving subsystems (i.e., they have multiple degrees of freedom). Often, the dynamics of one or more of these subsystems will not directly depend on the state of some other subsystems, resulting in a network of dependencies governing the dynamics. How does this dependency network affect the full system’s thermodynamics? Prior studies on the stochastic thermodynamics of multipartite processes have addressed this question by assuming that, in addition to the constraints of the dependency network, only one subsystem is allowed to change state at a time. However, in many real systems, such as chemical reaction networks or electronic circuits, multiple subsystems can—or must—change state together. Here, we investigate the thermodynamics of such composite processes, in which multiple subsystems are allowed to change state simultaneously. We first present new, strictly positive lower bounds on entropy production in composite processes. We then present thermodynamic uncertainty relations for information flows in composite processes. We end with strengthened speed limits for composite processes.
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Borlenghi, Simone, and Anna Delin. "Stochastic Thermodynamics of Oscillators’ Networks." Entropy 20, no. 12 (December 19, 2018): 992. http://dx.doi.org/10.3390/e20120992.

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We apply the stochastic thermodynamics formalism to describe the dynamics of systems of complex Langevin and Fokker-Planck equations. We provide in particular a simple and general recipe to calculate thermodynamical currents, dissipated and propagating heat for networks of nonlinear oscillators. By using the Hodge decomposition of thermodynamical forces and fluxes, we derive a formula for entropy production that generalises the notion of non-potential forces and makes transparent the breaking of detailed balance and of time reversal symmetry for states arbitrarily far from equilibrium. Our formalism is then applied to describe the off-equilibrium thermodynamics of a few examples, notably a continuum ferromagnet, a network of classical spin-oscillators and the Frenkel-Kontorova model of nano friction.
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Lewis, Edwin R. "Network thermodynamics revisited." Biosystems 34, no. 1-3 (1995): 47–63. http://dx.doi.org/10.1016/0303-2647(94)01456-h.

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Šesták, Jaroslav. "Studies in network thermodynamics." Thermochimica Acta 108 (November 1986): 393. http://dx.doi.org/10.1016/0040-6031(86)85106-1.

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Matsoukas, Themis. "Thermodynamics Beyond Molecules: Statistical Thermodynamics of Probability Distributions." Entropy 21, no. 9 (September 13, 2019): 890. http://dx.doi.org/10.3390/e21090890.

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Statistical thermodynamics has a universal appeal that extends beyond molecular systems, and yet, as its tools are being transplanted to fields outside physics, the fundamental question, what is thermodynamics, has remained unanswered. We answer this question here. Generalized statistical thermodynamics is a variational calculus of probability distributions. It is independent of physical hypotheses but provides the means to incorporate our knowledge, assumptions and physical models about a stochastic processes that gives rise to the probability in question. We derive the familiar calculus of thermodynamics via a probabilistic argument that makes no reference to physics. At the heart of the theory is a space of distributions and a special functional that assigns probabilities to this space. The maximization of this functional generates the mathematical network of thermodynamic relationship. We obtain statistical mechanics as a special case and make contact with Information Theory and Bayesian inference.
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Du, Bin, Daniel C. Zielinski, Jonathan M. Monk, and Bernhard O. Palsson. "Thermodynamic favorability and pathway yield as evolutionary tradeoffs in biosynthetic pathway choice." Proceedings of the National Academy of Sciences 115, no. 44 (October 11, 2018): 11339–44. http://dx.doi.org/10.1073/pnas.1805367115.

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The structure of the metabolic network contains myriad organism-specific variations across the tree of life, but the selection basis for pathway choices in different organisms is not well understood. Here, we examined the metabolic capabilities with respect to cofactor use and pathway thermodynamics of all sequenced organisms in the Kyoto Encyclopedia of Genes and Genomes Database. We found that (i) many biomass precursors have alternate synthesis routes that vary substantially in thermodynamic favorability and energy cost, creating tradeoffs that may be subject to selection pressure; (ii) alternative pathways in amino acid synthesis are characteristically distinguished by the use of biosynthetically unnecessary acyl-CoA cleavage; (iii) distinct choices preferring thermodynamic-favorable or cofactor-use–efficient pathways exist widely among organisms; (iv) cofactor-use–efficient pathways tend to have a greater yield advantage under anaerobic conditions specifically; and (v) lysine biosynthesis in particular exhibits temperature-dependent thermodynamics and corresponding differential pathway choice by thermophiles. These findings present a view on the evolution of metabolic network structure that highlights a key role of pathway thermodynamics and cofactor use in determining organism pathway choices.
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Reichl, L. E. "Book review:Studies in network thermodynamics." Journal of Statistical Physics 50, no. 1-2 (January 1988): 465. http://dx.doi.org/10.1007/bf01023005.

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Zhang, Mingjin, Peng Zhang, Yuhan Zhang, Minghai Yang, Xiaofeng Li, Xiaogang Dong, and Luchang Yang. "SAR-to-Optical Image Translation via an Interpretable Network." Remote Sensing 16, no. 2 (January 8, 2024): 242. http://dx.doi.org/10.3390/rs16020242.

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Synthetic aperture radar (SAR) is prevalent in the remote sensing field but is difficult to interpret by human visual perception. Recently, SAR-to-optical (S2O) image conversion methods have provided a prospective solution. However, since there is a substantial domain difference between optical and SAR images, they suffer from low image quality and geometric distortion in the produced optical images. Motivated by the analogy between pixels during the S2O image translation and molecules in a heat field, a thermodynamics-inspired network for SAR-to-optical image translation (S2O-TDN) is proposed in this paper. Specifically, we design a third-order finite difference (TFD) residual structure in light of the TFD equation of thermodynamics, which allows us to efficiently extract inter-domain invariant features and facilitate the learning of nonlinear translation mapping. In addition, we exploit the first law of thermodynamics (FLT) to devise an FLT-guided branch that promotes the state transition of the feature values from an unstable diffusion state to a stable one, aiming to regularize the feature diffusion and preserve image structures during S2O image translation. S2O-TDN follows an explicit design principle derived from thermodynamic theory and enjoys the advantage of explainability. Experiments on the public SEN1-2 dataset show the advantages of the proposed S2O-TDN over the current methods with more delicate textures and higher quantitative results.
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Keegan, Michael, Hava T. Siegelmann, Edward A. Rietman, Giannoula Lakka Klement, and Jack A. Tuszynski. "Gibbs Free Energy, a Thermodynamic Measure of Protein–Protein Interactions, Correlates with Neurologic Disability." BioMedInformatics 1, no. 3 (December 14, 2021): 201–10. http://dx.doi.org/10.3390/biomedinformatics1030013.

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Modern network science has been used to reveal new and often fundamental aspects of brain network organization in physiological as well as pathological conditions. As a consequence, these discoveries, which relate to network hierarchy, hubs and network interactions, have begun to change the paradigms of neurodegenerative disorders. In this paper, we explore the use of thermodynamics for protein–protein network interactions in Alzheimer’s disease (AD), Parkinson’s disease (PD), multiple sclerosis (MS), traumatic brain injury and epilepsy. To assess the validity of using network interactions in neurological diseases, we investigated the relationship between network thermodynamics and molecular systems biology for these neurological disorders. In order to uncover whether there was a correlation between network organization and biological outcomes, we used publicly available RNA transcription data from individual patients with these neurological conditions, and correlated these molecular profiles with their respective individual disability scores. We found a linear correlation (Pearson correlation of −0.828) between disease disability (a clinically validated measurement of a person’s functional status) and Gibbs free energy (a thermodynamic measure of protein–protein interactions). In other words, we found an inverse relationship between disease disability and thermodynamic energy. Because a larger degree of disability correlated with a larger negative drop in Gibbs free energy in a linear disability-dependent fashion, it could be presumed that the progression of neuropathology such as is seen in Alzheimer’s disease could potentially be prevented by therapeutically correcting the changes in Gibbs free energy.
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Dissertations / Theses on the topic "Network thermodynamics"

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Squadrani, Lorenzo. "Deep neural networks and thermodynamics." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020.

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Deep learning is the most effective and used approach to artificial intelligence, and yet it is far from being properly understood. The understanding of it is the way to go to further improve its effectiveness and in the best case to gain some understanding of the "natural" intelligence. We attempt a step in this direction with the aim of physics. We describe a convolutional neural network for image classification (trained on CIFAR-10) within the descriptive framework of Thermodynamics. In particular we define and study the temperature of each component of the network. Our results provides a new point of view on deep learning models, which may be a starting point towards a better understanding of artificial intelligence.
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Pierantozzi, Mariano. "Mathematical modeling for Thermodynamics: Thermophysical Properties and Equation of State." Doctoral thesis, Università Politecnica delle Marche, 2015. http://hdl.handle.net/11566/242931.

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Nelle moderne società multiculturali e multidisciplinari, sempre di più si devono adottare delle prospettive più ampie possibili. In questa tesi, si è tentato di adottare un metodo multidisciplinare che coinvolgesse non solo la matematica e la fisica, ma anche la chimica, la statistica, e più in generale l’ingegneria. Gli aspetti toccati sono quelli delle proprietà termofisiche della materia e delle equazioni di stato dei gas (EOS). Le proprietà termofisiche analizzate sono: tensione superficiale, conduttività termica, viscosità, dei liquidi e dei gas ed il secondo coefficiente del viriale. Dopo la raccolta dei dati sperimentali, essi sono stati analizzati con varie tecniche statistiche che trasformassero i dati grezzi in dati più attendibili. Dopo lo studio delle equazioni della letteratura si è proceduto con uno studio di sensibilità dei dati per vedere quali proprietà fisiche avessero maggiore impatto sulle proprietà studiate. Infine si è cercata un’equazione che potesse rappresentare nel migliore modo possibile i dati sperimentali. Si sono sempre preferite equazioni scalate ad equazioni puramente empiriche, in modo da avere non solo l’aderenza ai dati sperimentali, ma anche il rispetto dell’aspetto chimico-fisico. Dall’analisi dei residui, confrontandoci con le migliori equazioni in letteratura, i nostri risultati sono sempre stati migliori, tanto che hanno avuto dignità di pubblicazione nelle maggiori riviste del settore. Discorso a parte per le EOS. Analizzando la letteratura, ciò che subito è saltato all’occhio è che cercare la migliore equazione possibile è impossibile! Oppure come dice Martin parafrasando una frase della favola Biancaneve: “Specchio specchio delle mie brame, qual è la più bella del reame?” Abbiamo scelto la modifica dell’equazione Carnahan-Starling-De Santis. Tramite tecniche di minimizzazione multi obiettivo si sono migliorate le performance di tal equazione proprio intorno al punto critico. Questi sono gli aspetti principali toccati in questo lavoro di tesi, che di là dai risultati, pur buoni ottenuti, mi ha aperto il mondo della ricerca.
Abstract In the modern multicultural and multidisciplinary society, always adopting more and more wider prospective than before. In this thesis, we try to adopt a multidisciplinary method, which involves Mathematics, Physics, but also Chemistry, Statistics, and in general the scientific engineering. The aspects explained are thermo physical properties, and Equations of State (EOS) of gases. Regarding thermo physical properties have been analysed Surface Tension, Thermal Conductivity, Viscosity, and the second virial coefficient. On this arguments, the work had been subdivided between the gathering of experimental data, the analysing of data with statistical techniques transforming them to more reliable data than row. The second step was to collect the equations of literature. Then we went ahead studying the sensibility of data to find out which physical properties could have bigger impact to property examined. At the end, we looked for an equation that could represent experimental data in a better way. We always preferred the scaled equations that respect chemical and physical aspects, to the empirical ones. Comparing our results with better equations in literature, our results are always better, in fact all of the have been published in the best international journals on this subject. A separate discussion is that of EOS. Analyzing the previous literature, the first thing that came to our minds was that to find the best possible equation is impossible. Or as Martin wrote copying words of the famous fables Snow White: “Mirror mirror on the wall, who is the fairest of them all?”. We choose to modify The Carnahan-Starling-De Santis (CSD) equation of state, a parametrich equation with good results in the calculation of Vapor Liquid Equilibrium. Due to multi objective minimization techniques the performance of CSD has been improved. These are the principals aspect brought to light in this research, which apart from the results, with good results has opened to me the world of research.
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Ozaki, Hiroto. "Study of Network Structures and Rheological Properties of Physical Gels." Kyoto University, 2017. http://hdl.handle.net/2433/227633.

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Loutchko, Dimitri. "A Theoretical Study of the Tryptophan Synthase Enzyme Reaction Network." Doctoral thesis, Humboldt-Universität zu Berlin, 2018. http://dx.doi.org/10.18452/19384.

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Das Enzym Tryptophan Synthase ist ein ausgezeichnetes Beispiel einer molekularen Fabrik auf der Nanoskala mit zwei katalytischen Zentren. Der katalytische Zyklus des Moleküls beruht zudem auf zahlreichen allosterischen Wechselwirkungen sowie der Übertragung des Intermediats Indol durch einen intramolekularen Tunnel. In dieser Arbeit wird das erste kinetische Modell eines einzelnen Tryptophan Synthase Moleküls konstruiert und analysiert. Simulationen zeigen starke Korrelationen zwischen den Zuständen der Katalysezentren sowie die Ausbildung von Synchronisation. Mit stochastischer Thermodynamik wird die experimentell unzugängliche Reaktionskonstante für die Rückübertragung des Indols aus Messdaten rekonstuiert. Methoden, die den Informationsaustausch in bipartiten Markovnetzwerken charakterisieren, werden auf beliebige Markovnetzwerke verallgemeinert und auf das Modell angewendet. Der abschließende Teil befasst sich mit chemischen Reaktionsnetzwerken von Metaboliten und Enzymen. Es werden algebraische Modelle (Halbgruppen) konstruiert, welche aufeinanderfolgende und simultane katalytische Funktionen von Enzymen und von Unternetzwerken erfassen. Diese Funktionen werden genutzt, um eine natürliche Dynamikum sowie hinreichende und notwendige Bedingungen für seine Selbsterhaltung zu formulieren. Anschließend werden die algebraischen Modelle dazu genutzt, um eine Korrespondenz zwischen Halbgruppenkongruenzen und Skalenübergängen auf den Reaktionsnetzwerken herzustellen. Insbesondere wird eine Art von Kongruenzen erörtert, welche dem Ausspuren der globalen Struktur des Netzwerkes unter vollständiger Beibehaltung seiner lokalen Komponenten entspicht. Während klassische Techniken eine bestimmte lokale Komponente fixieren und sämtliche Informationen über ihre Umgebung ausspuren, sind bei dem algebraischen Verfahren alle lokalen Komponenten zugleich sichtbar und eine Verknüpfung von Funktionen aus verschiedenen Komponenten ist problemlos möglich.
The channeling enzyme tryptophan synthase provides a paradigmatic example of a chemical nanomachine with two distinct catalytic subunits. It catalyzes the biosynthesis of tryptophan, whereby the catalytic activity in a subunit is enhanced or inhibited depending on the state of the other subunit, gates control the accessibility of the reactive sites and the intermediate product indole is directly channeled within the protein. The first single-molecule kinetic model of the enzyme is constructed. Simulations reveal strong correlations in the states of the active centers and the emergent synchronization. Thermodynamic data is used to calculate the rate constant for the reverse indole channeling. Using the fully reversible single-molecule model, the stochastic thermodynamics of the enzyme is closely examined. The current methods describing information exchange in bipartite systems are extended to arbitrary Markov networks and applied to the kinetic model. They allow the characterization of the information exchange between the subunits resulting from allosteric cross-regulations and channeling. The final part of this work is focused on chemical reaction networks of metabolites and enzymes. Algebraic semigroup models are constructed based on a formalism that emphasizes the catalytic function of reactants within the network. A correspondence between coarse-graining procedures and semigroup congruences respecting the functional structure is established. A family of congruences that leads to a rather unusual coarse-graining is analyzed: The network is covered with local patches in a way that the local information on the network is fully retained, but the environment of each patch is not resolved. Whereas classical coarse-graining procedures would fix a particular patch and delete information about the environment, the algebraic approach keeps the structure of all local patches and allows the interaction of functions within distinct patches.
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Hui, Qing. "Nonlinear dynamical systems and control for large-scale, hybrid, and network systems." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/24635.

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Thesis (Ph.D.)--Aerospace Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Haddad, Wassim; Committee Member: Feron, Eric; Committee Member: JVR, Prasad; Committee Member: Taylor, David; Committee Member: Tsiotras, Panagiotis
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Grondin, Yohann. "Biological networks : a thermodynamical approach." Thesis, University of Leicester, 2006. http://hdl.handle.net/2381/30584.

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Many real systems can be represented by networks, that is a set of nodes connected to each other. The study of these systems as such has proven extremely useful as it gives access to a series of parameters that characterise their non-trivial architecture. This architecture is the product of many factors from the evolutionary mechanisms that shape the system during its growth to the functional dynamics on a shorter time scale. Gaining knowledge on the architecture is then of importance but faces many challenges in particular in the study of biological networks. The first challenge is in terms of the method used to generate networks as we need to adopt an approach that, we expect, would allow us to understand those constraints and forces that shape the network. The second challenge is that of understanding the relationship between the architecture of the system and its dynamics and functionality. The third challenge is to get access using suitable techniques to the network architecture from expression data, such as mRNA abundances, for example. We first show in this thesis that it is possible to generate networks from a thermodynamical viewpoint. This approach allows us to relate the architecture of network to some constraints. Furthermore, we show that some information on the structure resides in the non-randomness of the links between nodes. If we were to draw an analogy with traditional thermodynamics, networks could be modelled in a first approximation as perfect gases. On a dynamical network of our design, we show a dependence of the architecture on the distribution of the level of expression of the nodes. Surprisingly, the distribution of the periods of those networks is a power-law and independent of the underlying architecture of the system. By comparing the data obtained from our model to experimental mRNA data we found a correlation between the degree of connectivity of genes and their level of abundance. Finally, we show how we can apply a method used traditionally in image reconstruction to inference of networks.
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Kotjabasakis, E. "Design of flexible heat exchanger networks." Thesis, University of Manchester, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.235140.

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Design for process flexibility is an industrially important topic so it is not surprising that it is attracting much research work. Given the size of the problem it is also not surprising that workers have concentrated on heat exchanger networks, which can be considered to be a self-contained sub-problem. Unfortunately, recent research has suffered from a number of major drawbacks. Problem formulation has often been unrealistic. Proposed procedures tend to be 'clinical' rather than practical. Academic research has often been conducted without proper consideration of the industrial environment. Very few research results have been tested on full scale industrial problems. In this thesis a new problem formulation and new solution techniques are presented. They have been designed to fulfil the needs of industry. In problem formulation it is recognised that the specification of flexibility is primarily an economic problem. The amount of flexibility industry will demand is a function of how much it costs. The methodology developed here allows both, the flexibility cost and the existing trade-off between flexibility needs, capital costs and energy costs to be fully evaluated. Flexibility problem formulation is mainly based on Multiple Base Cases. Different plant operating scenarios are set and a design found that is able to satisfy each case. This is a formulation that has found a wide acceptance in industry. To be industrially practical, process design techniques must be intelligible to the non-specialist. The techniques developed here are simple and straightforward and give insight. Two new design techniques have been developed. The first of these is 'Downstream Paths'. These are used to identify and evolve the network structures that permit cost effective flexibility. The second technique is 'Sensitivity Tables'. These can be used to analyse the performance of a given structure. In addition they determine the cost effective modification to elements of the structure which provide the specified flexibility needs. The technique is rapid, simple to apply and easy to repeat. Consequently, many scenarios can be screened without much effort and a cost profile developed in order to evaluate the cost trade-off described above. The approach proposed in this thesis, involving the new problem formulation and solution techniques, has been applied to a number of case studies of industrial scale. These case studies have covered problems as diverse as catalyst deactivation, fouling, and plant debottlenecking. One major spin-off from the work is a new approach to the design of heat exchanger networks subjected to fouling. Large potential savings have been identified.
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Garcia, Cantu Ros Anselmo. "Thermodynamic and kinetic aspects of interaction networks." Doctoral thesis, Universite Libre de Bruxelles, 2007. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210420.

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In view of the fact that a same complex phenomenon can be approached by different conceptual frameworks, it is natural to inquire on the possibility to find connections between different types of quantities, such as topological, dynamical, statistical or thermodynamical, characterizing the same system. The present work is built on the idea that this line of approach can provide interesting insights on possible universal principles governing complex phenomena. In Chapter I we introduce concepts and tools of dynamical systems and thermodynamics as applied in macroscopic scale description as well as, for a later use, a number of selected representative models. In Chapter II we briefly present the elements of the theory of Markov processes describing a large class of stochastic process and also introduce some important concepts on the probabilistic description of deterministic systems. This chapter ends with a thermodynamic formulation accounting for the evolution of the entropy under the effect of stochastic fluctuations. In Chapter III, after introducing the main concepts and recent advances in network theory, we provide a connection between dynamical systems and network theory, which shows how universal structural properties of evolving networks can arise from deterministic dynamics. More specifically, we show explicitly the relation between the connectivity patterns of these networks and the indicators of the underlying dynamics, such as the local Lyapunov exponents. Our analysis is applied to representative models of chaotic maps, chaotic flows and is finally extended to stochastic processes. In Chapter IV we address the inverse problem, namely, processes whose dynamics is determined, in part, by the structure of the network in which they are embedded. In particular, we focus on systems of particles diffusing on a lattice and reacting instantaneously upon encountering each other. We study the role of the topology, the degree of synchronicity of motion and the reaction mechanism on the efficiency of the process. This lead us to identify a common generic mechanism responsible for the behavior of the efficiency, as a function of the control parameters. Finally, in Chapter V we study the connection between the topology and the thermodynamic properties of reaction networks, with focus on the entropy production and the system’s efficiency at nonequilibrium steady states. We also explore the connection between dynamic and thermodynamic properties of nonlinear feedbacks, as well as the response properties of reaction networks against both deterministic and stochastic external perturbations. We address networks of varying topologies, from regular lattices to complex structures./Le présent travail s’inscrit dans le domaine de recherche sur les systèmes complexes. Différentes approches, basées des systèmes dynamiques, de la thermodynamique des systèmes hors d’équilibre, de la physique statistique et, plus récemment, de la théorie des réseaux, sont combinés afin d’explorer des liens entre différentes types de grandeurs qui caractérisent certaines classes de comportements complexes. Dans le Chapitre I nous introduisons les principaux concepts et outils de systèmes dynamiques et de thermodynamique. Dans le Chapitre II nous présentons premièrement des éléments de la théorie de processus de Markov, ainsi que les concepts à la base de la description probabiliste des systèmes déterministes. Nous finissons le chapitre en proposant une formulation thermodynamique qui décrit l’évolution de l’entropie hors d’équilibre, soumis à l’influence de fluctuations stochastiques. Dans le Chapitre III nous introduisons les concepts de base en théorie des réseaux, ainsi qu’un résumé générale des progrès récents dans le domaine. Nous établissons ensuite une connexion entre la théorie des systèmes dynamiques et la théorie de réseaux. Celle-ci permet d’approfondir la compréhension des mécanismes responsables de l’émergence des propriétés structurelles dans des réseaux crées par des lois dynamiques déterministes. En particulier, nous mettons en évidence la relation entre des motifs de connectivité de ce type de réseaux et des indicateurs de la dynamique sous-jacente, tel que des exposant de Lyapounov locaux. Notre analyse est illustrée par des applications et des flots chaotiques et étendue à des processus stochastiques. Dans le Chapitre IV nous étudions le problème complémentaire, à savoir, celui de processus dont la dynamique est déterminée, en partie, par la structure du réseau dans lequel elle se déroule. Plus précisément, nous nous concentrons sur le cas de systèmes de particules réactives, diffusent au travers d’un réseau et réagissant instantanément lorsqu’un rencontre se produit entre elles. Nous étudions le rôle de la topologie, du degré de synchronicité des mouvements et aussi celui du mécanisme de réaction sur l’efficacité du processus. Dans les différents modèles étudiés, nous identifions un mécanisme générique commun, responsable du comportement de l’efficacité comme fonction des paramètres de contrôle. Enfin, dans le Chapitre V nous abordons la connexion entre la topologie et les propriétés thermodynamiques des réseaux de réactions, en analysant le comportement local et global de la production d’entropie et l’efficacité du système dans des état stationnaires de non-équilibre. Nous explorons aussi la connexion entre la dynamique et les propriétés de boucles de rétroaction non linéaires, ainsi que les propriétés de réponse des réseaux de réaction à des perturbations stochastiques et déterministes externes. Nous considérons le cas de réseaux à caractère régulier aussi bien que celui de réseaux complexes.


Doctorat en Sciences
info:eu-repo/semantics/nonPublished

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Honorato-Zimmer, Ricardo. "On a thermodynamic approach to biomolecular interaction networks." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28904.

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We explore the direct and inverse problem of thermodynamics in the context of rule-based modelling. The direct problem can be concisely stated as obtaining a set of rewriting rules and their rates from the description of the energy landscape such that their asymptotic behaviour when t → ∞ coincide. To tackle this problem, we describe an energy function as a finite set of connected patterns P and an energy cost function e which associates real values to each of these energy patterns. We use a finite set of reversible graph rewriting rules G to define the qualitative dynamics by showing which transformations are possible. Given G and P, we construct a finite set of rules Gp which i) has the same qualitative transition system as G and ii) when equipped with rates according to e, defines a continuous-time Markov chain that has detailed balance with respect to the invariant probability distribution determined by the energy function. The construction relies on a technique for rule refinement described in earlier work and allows us to represent thermodynamically consistent models of biochemical interaction networks in a concise manner. The inverse problem, on the other hand, is to i) check whether a rule-based model has an energy function that describes its asymptotic behaviour and if so ii) obtain the energy function from the graph rewriting rules and their rates. Although this problem is known to be undecidable in the general case, we find two suitable subsets of Kappa, our rule-based modelling framework of choice, were this question can be answer positively and the form of their energy functions described analytically.
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Jones, Paul Simon. "Targeting and design for heat exchanger networks under multiple base case operation." Thesis, University of Manchester, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.292518.

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Books on the topic "Network thermodynamics"

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Peusner, Leonardo. Studies in network thermodynamics. Amsterdam: Elsevier, 1986.

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Germany) Minisymposium on Thermodynamics of Surfaces (1995 Berlin. Thermodynamics of surfaces: Minisymposium, May 11-13, 1995 : European Thermodynamics Network, thermodynamics of complex systems. Berlin: Technische Universität Berlin, 1996.

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Peusner, L. The principles of network thermodynamics: Theory and biophysical applications. Lincoln, Mass: Entropy Ltd., 1987.

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Piotrowska, Ewa. Zastępcza sieć cieplna wymiennika ciepła pracującego w stanach przejściowych: The equivalent thermal network for heat exchanger working in the transient states. Warszawa: Wydawnictwo SGGW, 2013.

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Meeting, American Society of Mechanical Engineers Winter. Network thermodynamics, heat and mass transfer in biotechnology: Presented at the Winter Annual Meeting of the American Society of Mechanical Engineers, Boston, Massachusetts, December 13-18, 1987 : sponsored by the Bioengineering Division, ASME, the Heat Transfer Division, ASME. New York: American Society of Mechanical Engineers, 1987.

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American Society of Mechanical Engineers. Winter Meeting. Network thermodynamics, heat and mass transfer in biotechnology: Presented at the Winter Annual Meeting of the American Society of Mechanical Engineers, Boston, Massachusetts, December 13-18, 1987. New York, N.Y. (345 E. 47th St., New York 10017): ASME, 1987.

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Bejan, Adrian, and Giuseppe Grazzini, eds. Shape and Thermodynamics. Florence: Firenze University Press, 2008. http://dx.doi.org/10.36253/978-88-8453-836-9.

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Shape and Thermodynamics is a two-day international Workshop focused on the Constructal Theory of generation of configuration in nature and engineering. From the early developments related to tree configurations for the cooling of electronics, today Constructal theory is being applied to conceptual design of transportation net-works, river basins, living bodies, building materials and many other flow systems. Constructal theory is also enriching thermo-dynamics, from basic theory to design and optimization. This theory approaches design "as science", with the generation of configuration regarded as a phenomenon of all physics, based on principle (the Constructal law). For example, Constructal Theory contributes to the evolution of fuel cells, in the design of cooling channels, the optimal feeding of reactants, etc. Important applications are also found in the design of heat exchangers, district heating networks, etc. The growing scientific literature on Constructal Theory has an important Italian component, although further dissemination is timely. Moreover, the relation with other thermodynamic research areas deserves to be explored. Website: Shape and Thermodinamics
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Ito, Sosuke. Information Thermodynamics on Causal Networks and its Application to Biochemical Signal Transduction. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1664-6.

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Müller, Berndt. Neural networks: An introduction. 2nd ed. Berlin: Springer-Verlag, 1991.

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Müller, Berndt. Neural networks: An introduction. 2nd ed. Berlin: Springer, 1995.

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Book chapters on the topic "Network thermodynamics"

1

Imai, Y. "Graded Modelling of Exocrine Secretion Using Network Thermodynamics." In Epithelial Secretion of Water and Electrolytes, 129–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-75033-5_9.

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Gordon, Manfred. "Thermodynamics of Casein Gels and the Universality of Network Theories." In Integration of Fundamental Polymer Science and Technology, 167–76. Dordrecht: Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4185-4_22.

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Haddad, Wassim M. "The Role of Systems Biology, Neuroscience, and Thermodynamics in Network Control and Learning." In Handbook of Reinforcement Learning and Control, 763–817. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-60990-0_25.

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Doty, David, Trent A. Rogers, David Soloveichik, Chris Thachuk, and Damien Woods. "Thermodynamic Binding Networks." In Lecture Notes in Computer Science, 249–66. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66799-7_16.

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Feinberg, Martin. "Quasi-Thermodynamic Kinetic Systems." In Foundations of Chemical Reaction Network Theory, 273–91. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-03858-8_13.

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Utracki, L. A. "Thermodynamics and Kinetics of Phase Separation." In Interpenetrating Polymer Networks, 77–123. Washington, DC: American Chemical Society, 1994. http://dx.doi.org/10.1021/ba-1994-0239.ch003.

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Ito, Sosuke. "Information Thermodynamics on Causal Networks." In Information Thermodynamics on Causal Networks and its Application to Biochemical Signal Transduction, 61–82. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1664-6_6.

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Rostiashvili, V. G., and T. A. Vilgis. "Statistical Thermodynamics of Polymeric Networks." In Encyclopedia of Polymeric Nanomaterials, 1–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-36199-9_308-1.

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Rostiashvili, V. G., and T. A. Vilgis. "Statistical Thermodynamics of Polymeric Networks." In Encyclopedia of Polymeric Nanomaterials, 2254–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-29648-2_308.

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Ye, Cheng, Andrea Torsello, Richard C. Wilson, and Edwin R. Hancock. "Thermodynamics of Time Evolving Networks." In Graph-Based Representations in Pattern Recognition, 315–24. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18224-7_31.

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Conference papers on the topic "Network thermodynamics"

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Pavlović, Marina Simović, Maja Pagnacco, Bojana Bokić, Darko Vasiljević, Marija Radmilović-Rađenović, Branislav Rađenović, and Branko Kolarić. "Breaking Barriers: Molding Thermodynamics by Geometry of Nanostructures." In 2024 24th International Conference on Transparent Optical Networks (ICTON), 1–4. IEEE, 2024. http://dx.doi.org/10.1109/icton62926.2024.10648049.

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Zitelli, Mario. "A Thermodynamic Study of Low-power Modal Multiplexed Systems." In 2024 24th International Conference on Transparent Optical Networks (ICTON), 1–3. IEEE, 2024. http://dx.doi.org/10.1109/icton62926.2024.10647332.

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Kiritsis, E., and T. Taylor. "Thermodynamics of D-brane probes." In European Network on Physics beyond the Standard Model. Trieste, Italy: Sissa Medialab, 1999. http://dx.doi.org/10.22323/1.002.0027.

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Taliaferro, Matthew E., and Samuel R. Darr. "Modeling Internal Launch Vehicle Fluid Flow and Thermodynamics, Part 1: Thermodynamic Tank Network Solver." In AIAA SCITECH 2024 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2024. http://dx.doi.org/10.2514/6.2024-2293.

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Gaymann, Audrey, Giorgio Schiaffini, Michela Massini, Francesco Montomoli, and Alessandro Corsini. "Neural network topology for wind turbine analysis." In European Conference on Turbomachinery Fluid Dynamics and Thermodynamics. European Turbomachinery Society, 2019. http://dx.doi.org/10.29008/etc2019-174.

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Pothineni, Dinesh, Pratik Mishra, and Aadil Rasheed. "Social thermodynamics: Modelling communication dynamics in social network." In 2012 International Conference on Future Generation Communication Technology (FGCT). IEEE, 2012. http://dx.doi.org/10.1109/fgct.2012.6476582.

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Berg, Jordan M., D. H. S. Maithripala, Qing Hui, and Wassim M. Haddad. "Thermodynamics-based network systems control by thermal analogy." In 2012 IEEE 51st Annual Conference on Decision and Control (CDC). IEEE, 2012. http://dx.doi.org/10.1109/cdc.2012.6426012.

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Chen, Ruijun. "The Network Locating Principle in Flexible Circuit Board Assembly." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-10305.

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This paper focuses on developing the Network Locating Principle for fixturing tooling design in flexible circuit board assembly. From a viewpoint of Thermodynamics, a flexible circuit board populated with electronic components on the first side is a closed thermodynamic system. It experiences deformation energy change, assembly load work, and heat transfer during an isothermal assembly process on the second side, such as solder paste deposit printing and electronic component placement processes. Based on the First and Second Laws of Thermodynamics and Energy Equation of Thermoelastic Theory, a fixturing analysis is developed to investigate the deformation energy change, and furthermore the theoretical fixturing solution is derived to minimize the assembly load work during the isothermal assembly processes. To this end, the Network Locating Principle is proposed to guide fixturing tooling design for the isothermal assembly processes on the second side. Effectiveness of the Network Locating Principle is verified in numerical and experimental studies of flip chip placement processes on a thin flexible circuit.
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Layton, Astrid, John Reap, and Bert Bras. "A Correlation Between Thermal Efficiency and Biological Network Cyclicity." In ASME 2011 5th International Conference on Energy Sustainability. ASMEDC, 2011. http://dx.doi.org/10.1115/es2011-54787.

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This article investigates a correlation between the thermal efficiency of ideal power cycles and a structural measure of the degree of interactions in networks known as cyclicity. Efficient design of networks that reuse materials and energy motivates the work. Corporate “take-back” plans, multi-company industrial symbioses and public recycling programs recover products, components and materials using partially closed loop networks. As resources become scarcer and more expensive, the prevalence of these networks is likely to increase, and the importance of designing efficient networks grows. Multiple structural and material flow metrics that one might use to aid network design exist. One novel approach to network design involves patterning industrial networks on ecological ones. This latter idea lays at the heart of industrial symbiosis efforts. However, neither the materials metric approach nor the bioinspired ecological patterns approach stands upon a strong theoretical base. As a test of both approaches, this work uses a structural cycling metric, cyclicity, previously used to quantify patterns in ecosystems, to quantify energy flow in ideal thermodynamic cycles. The objective is not to learn about thermodynamic cycles. Rather, the intent of the comparison is to reveal whether trends in network structure as given by cyclicity relate to the fundamental laws of thermodynamics. Familiar ideal power cycles are first redrawn as energy flow networks. Cyclicity values are then calculated for these networks. A comparison shows that thermal efficiency increases with increasing cyclicity for fixed source and sink temperatures within a cycle. This results from the practice of adding cyclical energy paths (i.e. a regenerator) to an ideal power cycle, to increase thermal efficiency. The remainder of the article comments on the potential ramifications of this finding for the design of cycling industrial networks.
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Iwai, Takuya, Daichi Kominami, Masayuki Murata, and Tetsuya Yomo. "Thermodynamics-Based Entropy Adjustment for Robust Self-Organized Network Controls." In 2014 IEEE 38th Annual Computer Software and Applications Conference (COMPSAC). IEEE, 2014. http://dx.doi.org/10.1109/compsac.2014.48.

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Reports on the topic "Network thermodynamics"

1

Haddad, Wassim M. Complexity, Robustness, and Network Thermodynamics in Large-Scale and Multiagent Systems: A Hybrid Control Approach. Fort Belvoir, VA: Defense Technical Information Center, January 2012. http://dx.doi.org/10.21236/ada565203.

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Tse, David, Piyush Gupta, and Devavrat Shah. Thermodynamics of Large-Scale Heterogeneous Wireless Networks. Fort Belvoir, VA: Defense Technical Information Center, March 2014. http://dx.doi.org/10.21236/ada601231.

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Steele, W. V., R. D. Chirico, S. E. Knipmeyer, and A. Nguyen. The thermodynamic properties of 2-aminobiphenyl (an intermediate in the carbazole/hydrogen reaction network). Office of Scientific and Technical Information (OSTI), December 1990. http://dx.doi.org/10.2172/6307021.

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Haddad, Wassim M., and Quirino Balzano. A Network Thermodynamic Framework for the Analysis and Control Design of Large-Scale Dynamical Systems. Fort Belvoir, VA: Defense Technical Information Center, March 2006. http://dx.doi.org/10.21236/ada448643.

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Perdigão, Rui A. P. Strengthening Multi-Hazard Resilience with Quantum Aerospace Systems Intelligence. Synergistic Manifolds, January 2024. http://dx.doi.org/10.46337/240301.

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The present work further enhances and deploys our Quantum Aerospace Systems Intelligence technologies (DOI: 10.46337/quasi.230901) onto Multi-Hazard risk assessment and action, from sensing and prediction to modelling, decision support and active response, towards strengthening its fundamental knowledge, awareness and resilience in the face of multi-domain challenges. Moreover, it introduces our updated post-quantum aerospace engineering ecosystem for empowering active system dynamic capabilities to mitigate or even counter multi-hazard threats from space, leveraging our high energy technological physics solutions acting across coevolutionary space-times. These developments are further articulated with our latest Synergistic Nonlinear Quantum Wave Intelligence Networks suite of technologies (DOI: 10.46337/240118), vastly extending the operational capabilities of novel quantum and post-quantum systems to critically adverse thermodynamic conditions e.g. those pertaining situational action across real-world environmental and security theaters of operation.
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McKinley, James P., and Jonathan Istok. Stability of U(VI) and Tc(VII) Reducing Microbial Communities to Environmental Perturbation: Development and Testing of a Thermodynamic Network Model. Office of Scientific and Technical Information (OSTI), June 2005. http://dx.doi.org/10.2172/893451.

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McKinley, James P., Chongxuan Liu, Jack Istok, and Lee Krumholz. Stability of U(VI)- and Tc(VII) reducing microbial communities to environmental perturbation: a thermodynamic network model and intermediate-scale experiments. Office of Scientific and Technical Information (OSTI), June 2006. http://dx.doi.org/10.2172/895882.

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Perdigão, Rui A. P. Neuro-Quantum Cyber-Physical Intelligence (NQCPI). Synergistic Manifolds, October 2024. http://dx.doi.org/10.46337/241024.

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Neuro-Quantum Cyber-Physical Intelligence (NQCPI) is hereby introduced, entailing a novel framework for nonlinear natural-based neural post-quantum information physics, along with novel advances in far-from-equilibrium thermodynamics and evolutionary cognition in post-quantum neurobiochemistry for next-generation information physical systems intelligence. NQCPI harnesses and operates with the higher-order nonlinear nature of previously elusive quantum behaviour, including in open chaotic dissipative systems in thermodynamically and magneto-electrodynamically disruptive conditions, such as in natural biological and environmental systems, thereby paving new pathways for post-quantum information technologies, including new paradigms for information encoding, encryption, transmission and security elusive to SoA post-quantum approaches. NQCPI further harnesses and operates with novel quantum properties including new classes of high-order emergence and entanglement structures, new neuro-quantum physical properties, with higher-order post-quantum-proof improvements in security, storage and relaying of information. It further empowers new capabilities to disarm security protocols of adversarial powers including those already at SoA quantum and post-quantum levels. This new technology is implemented into a novel coevolutionary system-of-systems seamlessly operating across classical, quantum, post-quantum cryptographic and key distribution approaches, thereby generalising them with added value whilst ensuring backward compatibility for seamless articulation with legacy and SoA protocols. Having demonstrated disruptive added value relative to post-quantum security, NQCPI is also tested and implemented in other quantum technological developments, ranging from sensing to communication and computation, in articulation with QITES (Quantum Information Technologies in the Earth Sciences), QuASI (Quantum Aerospace Systems Intelligence), AIPSI (Augmented Information Physical Systems Intelligence), and Synergistic Nonlinear Quantum Wave Intelligence Networks (SyNQ-WIN), respectively from Perdigão (2020, 2023) and Perdigão and Hall (2023, 2024). Perdigão, R.A.P. (2020): QITES - Quantum Information Technologies in the Earth Sciences. https://doi.org/10.46337/qites.200628 Perdigão, R.A.P. (2023): QuASI - Quantum Aerospace Systems Intelligence. https://doi.org/10.46337/quasi.230901 Perdigão, R.A.P.; Hall, J. (2023): Augmented Information Physical Systems Intelligence (AIPSI). https://doi.org/10.46337/230414 Perdigão, R.A.P.; Hall, J. (2024): Synergistic Nonlinear Quantum Wave Intelligence Networks (SyNQ-WIN). https://doi.org/10.46337/240118
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