982 resultados para Complex number


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Distributed Space-Time Block Codes (DSTBCs) from Complex Orthogonal Designs (CODs) (both square and non-square CODs other than the Alamouti design) are known to lose their single-symbol ML decodable (SSD) property when used in two-hop wireless relay networks using the amplify and forward protocol. For such a network, a new class of high rate, training-symbol embedded (TSE) SSD DSTBCs are proposed from TSE-CODs. The constructed codes include the training symbols within the structure of the code which is shown to be the key point to obtain high rate along with the SSD property. TSE-CODs are shown to offer full-diversity for arbitrary complex constellations. Non-square TSE-CODs are shown to provide better rates (in symbols per channel use) compared to the known SSD DSTBCs for relay networks when the number of relays is less than 10. Importantly, the proposed DSTBCs do not contain zeros in their codewords and as a result, antennas of the relay nodes do not undergo a sequence of switch on and off transitions within every codeword use. Hence, the proposed DSTBCs eliminate the antenna switching problem.

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Two drug-drug co-crystals of the anti-tuberculosis drugs isoniazid (INH), pyrazinamide (PYR) and 4-aminosalicylic acid (PAS) are reported. The first is the 1 : 1 molecular complex of INH and PAS. The second is the monohydrate of the 1 : 1 complex of PYR and PAS. The crystal structures of both co-crystals are characterized by a number of hydrogen bonded synthons. Hydrogen bonding of the COOH center dot center dot center dot N-pyridine type is found in both cases. In the INH : PAS co-crystal, there are two symmetry independent COOH center dot center dot center dot center dot N-pyridine hydrogen bonds. In one of these, the H-atom is located on the carboxylic group and is indicative of a co-crystal. In the second case, partial proton transfer occurs across the hydrogen bond, and the extent of proton transfer depends on the temperature. This is more indicative of a salt. Drug-drug co-crystals may have some bearing in the treatment of tuberculosis.

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NMR spectra of molecules oriented in liquid-crystalline matrix provide information on the structure and orientation of the molecules. Thermotropic liquid crystals used as an orienting media result in the spectra of spins that are generally strongly coupled. The number of allowed transitions increases rapidly with the increase in the number of interacting spins. Furthermore, the number of single quantum transitions required for analysis is highly redundant. In the present study, we have demonstrated that it is possible to separate the subspectra of a homonuclear dipolar coupled spin system on the basis of the spin states of the coupled heteronuclei by multiple quantum (MQ)−single quantum (SQ) correlation experiments. This significantly reduces the number of redundant transitions, thereby simplifying the analysis of the complex spectrum. The methodology has been demonstrated on the doubly 13C labeled acetonitrile aligned in the liquid-crystal matrix and has been applied to analyze the complex spectrum of an oriented six spin system.

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Let I be an m-primary ideal of a Noetherian local ring (R, m) of positive dimension. The coefficient e(1)(I) of the Hilbert polynomial of an I-admissible filtration I is called the Chern number of I. A formula for the Chern number has been derived involving the Euler characteristic of subcomplexes of a Koszul complex. Specific formulas for the Chern number have been given in local rings of dimension at most two. These have been used to provide new and unified proofs of several results about e(1)(I).

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The poly (l-lysine)-based SPL7013 dendrimer with naphthalene disulphonate surface groups blocks the entry of HIV-1 into target cells and is in clinical trials for development as a topical microbicide. Its mechanism of action against R5 HIV-1, the HIV-1 variant implicated in transmission across individuals, remains poorly understood. Using docking and fully atomistic MD simulations, we find that SPL7013 binds tightly to R5 gp120 in the gp120-CD4 complex but weakly to gp120 alone. Further, the binding, although to multiple regions of gp120, does not occlude the CD4 binding site on gp120, suggesting that SPL7013 does not prevent the binding of R5 gp120 to CD4. Using MD simulations to compute binding energies of several docked structures, we find that SPL7013 binding to gp120 significantly weakens the gp120-CD4 complex. Finally, we use steered molecular dynamics (SMD) to study the kinetics of the dissociation of the gp120-CD4 complex in the absence of the dendrimer and with the dendrimer bound in each of the several stable configurations to gp120. We find that SPL7013 significantly lowers the force required to rupture the gp120-CD4 complex and accelerates its dissociation. Taken together, our findings suggest that SPL7013 compromises the stability of the R5 gp120-CD4 complex, potentially preventing the accrual of the requisite number of gp120-CD4 complexes across the virus-cell interface, thereby blocking virus entry.

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In this paper we introduce a weighted complex networks model to investigate and recognize structures of patterns. The regular treating in pattern recognition models is to describe each pattern as a high-dimensional vector which however is insufficient to express the structural information. Thus, a number of methods are developed to extract the structural information, such as different feature extraction algorithms used in pre-processing steps, or the local receptive fields in convolutional networks. In our model, each pattern is attributed to a weighted complex network, whose topology represents the structure of that pattern. Based upon the training samples, we get several prototypal complex networks which could stand for the general structural characteristics of patterns in different categories. We use these prototypal networks to recognize the unknown patterns. It is an attempt to use complex networks in pattern recognition, and our result shows the potential for real-world pattern recognition. A spatial parameter is introduced to get the optimal recognition accuracy, and it remains constant insensitive to the amount of training samples. We have discussed the interesting properties of the prototypal networks. An approximate linear relation is found between the strength and color of vertexes, in which we could compare the structural difference between each category. We have visualized these prototypal networks to show that their topology indeed represents the common characteristics of patterns. We have also shown that the asymmetric strength distribution in these prototypal networks brings high robustness for recognition. Our study may cast a light on understanding the mechanism of the biologic neuronal systems in object recognition as well.

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The study of complex networks has attracted the attention of the scientific community for many obvious reasons. A vast number of systems, from the brain to ecosystems, power grid, and the Internet, can be represented as large complex networks, i.e, assemblies of many interacting components with nontrivial topological properties. The link between these components can describe a global behaviour such as the Internet traffic, electricity supply service, market trend, etc. One of the most relevant topological feature of graphs representing these complex systems is community structure which aims to identify the modules and, possibly, their hierarchical organization, by only using the information encoded in the graph topology. Deciphering network community structure is not only important in order to characterize the graph topologically, but gives some information both on the formation of the network and on its functionality.

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Lionfish (Pterois volitans/miles complex) are venomous coral reef fishes from the Indian and western Pacific oceans that are now found in the western Atlantic Ocean. Adult lionfish have been observed from Miami, Florida to Cape Hatteras, North Carolina, and juvenile lionfish have been observed off North Carolina, New York, and Bermuda. The large number of adults observed and the occurrence of juveniles indicate that lionfish are established and reproducing along the southeast United States coast. Introductions of marine species occur in many ways. Ballast water discharge, a very common method of introduction for marine invertebrates, is responsible for many freshwater fish introductions. In contrast, most marine fish introductions result from intentional stocking for fishery purposes. Lionfish, however, likely were introduced via unintentional or intentional aquarium releases, and the introduction of lionfish into United States waters should lead to an assessment of the threat posed by the aquarium trade as a vector for fish introductions. Currently, no management actions are being taken to limit the effect of lionfish on the southeast United States continental shelf ecosystem. Further, only limited funds have been made available for research. Nevertheless, the extent of the introduction has been documented and a forecast of the maximum potential spread of lionfish is being developed. Under a scenario of no management actions and limited research, three predictions are made: ● With no action, the lionfish population will continue to grow along the southeast United States shelf. ● Effects on the marine ecosystem of the southeast United States will become more noticeable as the lionfish population grows. ● There will be incidents of lionfish envenomations of divers and/or fishers along the east coast of the United States. Removing lionfish from the southeast United States continental shelf ecosystem would be expensive and likely impossible. A bounty could be established that would encourage the removal of fish and provide specimens for research. However, the bounty would need to be lower than the price of fish in the aquarium trade (~$25-$50 each) to ensure that captured specimens were from the wild. Such a low bounty may not provide enough incentive for capturing lionfish in the wild. Further, such action would only increase the interaction between the public and lionfish, increasing the risk of lionfish envenomations. As the introduction of lionfish is very likely irreversible, future actions should focus on five areas. 1) The population of lionfish should be tracked. 2) Research should be conducted so that scientists can make better predictions regarding the status of the invasion and the effects on native species, ecosystem function, and ecosystem services. 3) Outreach and education efforts must be increased, both specifically toward lionfish and more generally toward the aquarium trade as a method of fish introductions. 4) Additional regulation should be considered to reduce the frequency of marine fish introduction into U.S. waters. However, the issue is more complicated than simply limiting the import of non-native species, and these complexities need to be considered simultaneously. 5) Health care providers along the east coast of the United States need to be notified that a venomous fish is now resident along the southeast United States. The introduction and spread of lionfish illustrates the difficulty inherent in managing introduced species in marine systems. Introduced species often spread via natural mechanisms after the initial introduction. Efforts to control the introduction of marine fish will fail if managers do not consider the natural dispersal of a species following an introduction. Thus, management strategies limiting marine fish introductions need to be applied over the scale of natural ecological dispersal to be effective, pointing to the need for a regional management approach defined by natural processes not by political boundaries. The introduction and success of lionfish along the east coast should change the long-held perception that marine fish invasions are a minimal threat to marine ecosystems. Research is needed to determine the effects of specific invasive fish species in specific ecosystems. More broadly, a cohesive plan is needed to manage, mitigate and minimize the effects of marine invasive fish species on ecosystems that are already compromised by other human activities. Presently, the magnitude of marine fish introductions as a stressor on marine ecosystems cannot be quantified, but can no longer be dismissed as negligible. (PDF contains 31 pages)

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This is an Author's Accepted Manuscript of an article published in “Emergence: Complexity and Organization”, 15 (2), pp. 14-22 (2013), copyright Taylor & Francis.

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This is the first part of direct numerical simulation (DNS) of double-diffusive convection in a slim rectangular enclosure with horizontal temperature and concentration gradients. We consider the case with the thermal Rayleigh number of 10^5, the Pradtle number of 1, the Lewis number of 2, the buoyancy ratio of composition to temperature being in the range of [0,1], and height-to-width aspect ration of 4. A new 7th order upwind compact scheme was developed for approximation of convective terms, and a three-stage third-order Runge-Kutta method was employed for time advancement. Our DNS suggests that with the buoyancy ratio increasing form 0 to 1, the flow of transition is a complex series changing fromthe steady to periodic, chaotic, periodic, quasi-periodic, and finally back to periodic. There are two types of periodic flow, one is simple periodic flow with single fundamental frequency (FF), and another is complex periodic flow with multiple FFs. This process is illustrated by using time-velocity histories, Fourier frequency spectrum analysis and the phase-space rajectories.

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The dissertation is concerned with the mathematical study of various network problems. First, three real-world networks are considered: (i) the human brain network (ii) communication networks, (iii) electric power networks. Although these networks perform very different tasks, they share similar mathematical foundations. The high-level goal is to analyze and/or synthesis each of these systems from a “control and optimization” point of view. After studying these three real-world networks, two abstract network problems are also explored, which are motivated by power systems. The first one is “flow optimization over a flow network” and the second one is “nonlinear optimization over a generalized weighted graph”. The results derived in this dissertation are summarized below.

Brain Networks: Neuroimaging data reveals the coordinated activity of spatially distinct brain regions, which may be represented mathematically as a network of nodes (brain regions) and links (interdependencies). To obtain the brain connectivity network, the graphs associated with the correlation matrix and the inverse covariance matrix—describing marginal and conditional dependencies between brain regions—have been proposed in the literature. A question arises as to whether any of these graphs provides useful information about the brain connectivity. Due to the electrical properties of the brain, this problem will be investigated in the context of electrical circuits. First, we consider an electric circuit model and show that the inverse covariance matrix of the node voltages reveals the topology of the circuit. Second, we study the problem of finding the topology of the circuit based on only measurement. In this case, by assuming that the circuit is hidden inside a black box and only the nodal signals are available for measurement, the aim is to find the topology of the circuit when a limited number of samples are available. For this purpose, we deploy the graphical lasso technique to estimate a sparse inverse covariance matrix. It is shown that the graphical lasso may find most of the circuit topology if the exact covariance matrix is well-conditioned. However, it may fail to work well when this matrix is ill-conditioned. To deal with ill-conditioned matrices, we propose a small modification to the graphical lasso algorithm and demonstrate its performance. Finally, the technique developed in this work will be applied to the resting-state fMRI data of a number of healthy subjects.

Communication Networks: Congestion control techniques aim to adjust the transmission rates of competing users in the Internet in such a way that the network resources are shared efficiently. Despite the progress in the analysis and synthesis of the Internet congestion control, almost all existing fluid models of congestion control assume that every link in the path of a flow observes the original source rate. To address this issue, a more accurate model is derived in this work for the behavior of the network under an arbitrary congestion controller, which takes into account of the effect of buffering (queueing) on data flows. Using this model, it is proved that the well-known Internet congestion control algorithms may no longer be stable for the common pricing schemes, unless a sufficient condition is satisfied. It is also shown that these algorithms are guaranteed to be stable if a new pricing mechanism is used.

Electrical Power Networks: Optimal power flow (OPF) has been one of the most studied problems for power systems since its introduction by Carpentier in 1962. This problem is concerned with finding an optimal operating point of a power network minimizing the total power generation cost subject to network and physical constraints. It is well known that OPF is computationally hard to solve due to the nonlinear interrelation among the optimization variables. The objective is to identify a large class of networks over which every OPF problem can be solved in polynomial time. To this end, a convex relaxation is proposed, which solves the OPF problem exactly for every radial network and every meshed network with a sufficient number of phase shifters, provided power over-delivery is allowed. The concept of “power over-delivery” is equivalent to relaxing the power balance equations to inequality constraints.

Flow Networks: In this part of the dissertation, the minimum-cost flow problem over an arbitrary flow network is considered. In this problem, each node is associated with some possibly unknown injection, each line has two unknown flows at its ends related to each other via a nonlinear function, and all injections and flows need to satisfy certain box constraints. This problem, named generalized network flow (GNF), is highly non-convex due to its nonlinear equality constraints. Under the assumption of monotonicity and convexity of the flow and cost functions, a convex relaxation is proposed, which always finds the optimal injections. A primary application of this work is in the OPF problem. The results of this work on GNF prove that the relaxation on power balance equations (i.e., load over-delivery) is not needed in practice under a very mild angle assumption.

Generalized Weighted Graphs: Motivated by power optimizations, this part aims to find a global optimization technique for a nonlinear optimization defined over a generalized weighted graph. Every edge of this type of graph is associated with a weight set corresponding to the known parameters of the optimization (e.g., the coefficients). The motivation behind this problem is to investigate how the (hidden) structure of a given real/complex valued optimization makes the problem easy to solve, and indeed the generalized weighted graph is introduced to capture the structure of an optimization. Various sufficient conditions are derived, which relate the polynomial-time solvability of different classes of optimization problems to weak properties of the generalized weighted graph such as its topology and the sign definiteness of its weight sets. As an application, it is proved that a broad class of real and complex optimizations over power networks are polynomial-time solvable due to the passivity of transmission lines and transformers.

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Threefold symmetric Fe phosphine complexes have been used to model the structural and functional aspects of biological N2 fixation by nitrogenases. Low-valent bridging Fe-S-Fe complexes in the formal oxidation states Fe(II)Fe(II), Fe(II)/Fe(I), and Fe(I)/Fe(I) have been synthesized which display rich spectroscopic and magnetic behavior. A series of cationic tris-phosphine borane (TPB) ligated Fe complexes have been synthesized and been shown to bind a variety of nitrogenous ligands including N2H4, NH3, and NH2-. These complexes are all high spin S = 3/2 and display EPR and magnetic characteristics typical of this spin state. Furthermore, a sequential protonation and reduction sequence of a terminal amide results in loss of NH3 and uptake of N2. These stoichiometric transformations represent the final steps in potential N2 fixation schemes.

Treatment of an anionic FeN2 complex with excess acid also results in the formation of some NH3, suggesting the possibility of a catalytic cycle for the conversion of N2 to NH3 mediated by Fe. Indeed, use of excess acid and reductant results in the formation of seven equivalents of NH3 per Fe center, demonstrating Fe mediated catalytic N2 fixation with acids and protons for the first time. Numerous control experiments indicate that this catalysis is likely being mediated by a molecular species.

A number of other phosphine ligated Fe complexes have also been tested for catalysis and suggest that a hemi-labile Fe-B interaction may be critical for catalysis. Additionally, various conditions for the catalysis have been investigated. These studies further support the assignment of a molecular species and delineate some of the conditions required for catalysis.

Finally, combined spectroscopic studies have been performed on a putative intermediate for catalysis. These studies converge on an assignment of this new species as a hydrazido(2-) complex. Such species have been known on group 6 metals for some time, but this represents the first characterization of this ligand on Fe. Further spectroscopic studies suggest that this species is present in catalytic mixtures, which suggests that the first steps of a distal mechanism for N2 fixation are feasible in this system.

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The solution behavior of linear polymer chains is well understood, having been the subject of intense study throughout the previous century. As plastics have become ubiquitous in everyday life, polymer science has grown into a major field of study. The conformation of a polymer in solution depends on the molecular architecture and its interactions with the surroundings. Developments in synthetic techniques have led to the creation of precision-tailored polymeric materials with varied topologies and functionalities. In order to design materials with the desired properties, it is imperative to understand the relationships between polymer architecture and their conformation and behavior. To meet that need, this thesis investigates the conformation and self-assembly of three architecturally complex macromolecular systems with rich and varied behaviors driven by the resolution of intramolecular conflicts. First we describe the development of a robust and facile synthetic approach to reproducible bottlebrush polymers (Chapter 2). The method was used to produce homologous series of bottlebrush polymers with polynorbornene backbones, which revealed the effect of side-chain and backbone length on the overall conformation in both good and theta solvent conditions (Chapter 3). The side-chain conformation was obtained from a series of SANS experiments and determined to be indistinguishable from the behavior of free linear polymer chains. Using deuterium-labeled bottlebrushes, we were able for the first time to directly observe the backbone conformation of a bottlebrush polymer which showed self-avoiding walk behavior. Secondly, a series of SANS experiments was conducted on a homologous series of Side Group Liquid Crystalline Polymers (SGLCPs) in a perdeuterated small molecule liquid crystal (5CB). Monodomain, aligned, dilute samples of SGLCP-b-PS block copolymers were seen to self-assemble into complex micellar structures with mutually orthogonally oriented anisotropies at different length scales (Chapter 4). Finally, we present the results from the first scattering experiments on a set of fuel-soluble, associating telechelic polymers. We observed the formation of supramolecular aggregates in dilute (≤0.5wt%) solutions of telechelic polymers and determined that the choice of solvent has a significant effect on the strength of association and the size of the supramolecules (Chapter 5). A method was developed for the direct estimation of supramolecular aggregation number from SANS data. The insight into structure-property relationships obtained from this work will enable the more targeted development of these molecular architectures for their respective applications.

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This dissertation studies long-term behavior of random Riccati recursions and mathematical epidemic model. Riccati recursions are derived from Kalman filtering. The error covariance matrix of Kalman filtering satisfies Riccati recursions. Convergence condition of time-invariant Riccati recursions are well-studied by researchers. We focus on time-varying case, and assume that regressor matrix is random and identical and independently distributed according to given distribution whose probability distribution function is continuous, supported on whole space, and decaying faster than any polynomial. We study the geometric convergence of the probability distribution. We also study the global dynamics of the epidemic spread over complex networks for various models. For instance, in the discrete-time Markov chain model, each node is either healthy or infected at any given time. In this setting, the number of the state increases exponentially as the size of the network increases. The Markov chain has a unique stationary distribution where all the nodes are healthy with probability 1. Since the probability distribution of Markov chain defined on finite state converges to the stationary distribution, this Markov chain model concludes that epidemic disease dies out after long enough time. To analyze the Markov chain model, we study nonlinear epidemic model whose state at any given time is the vector obtained from the marginal probability of infection of each node in the network at that time. Convergence to the origin in the epidemic map implies the extinction of epidemics. The nonlinear model is upper-bounded by linearizing the model at the origin. As a result, the origin is the globally stable unique fixed point of the nonlinear model if the linear upper bound is stable. The nonlinear model has a second fixed point when the linear upper bound is unstable. We work on stability analysis of the second fixed point for both discrete-time and continuous-time models. Returning back to the Markov chain model, we claim that the stability of linear upper bound for nonlinear model is strongly related with the extinction time of the Markov chain. We show that stable linear upper bound is sufficient condition of fast extinction and the probability of survival is bounded by nonlinear epidemic map.

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The Caranx hippos species complex comprises three extant species: crevalle jack (Caranx hippos) (Linnaeus, 1766) from both the western and eastern Atlantic oceans; Pacific crevalle jack (Caranx caninus) Günther, 1868 from the eastern Pacific Ocean; and longfin crevalle jack (Caranx fischeri) new species, from the eastern Atlantic, including the Mediterranean Sea and Ascension Island. Adults of all three species are superficially similar with a black blotch on the lower half of the pectoral fin, a black spot on the upper margin of opercle, one or two pairs of enlarged symphyseal canines on the lower jaw, and a similar pattern of breast squamation. Each species has a different pattern of hyperostotic bone development and anal-fin color. The two sympatric eastern Atlantic species also differ from each other in number of dorsal-and anal-fin rays, and in large adults of C. fischeri the lobes of these fins are longer and the body is deeper. Caranx hippos from opposite sides of the Atlantic are virtually indistinguishable externally but differ consistently in the expression of hyperostosis of the first dorsalfin pterygiophore. The fossil species Caranx carangopsis Steindachner 1859 appears to have been based on composite material of Trachurus sp. and a fourth species of the Caranx hippos complex. Patterns of hyperostotic bone development are compared in the nine (of 15 total) species of Caranx sensu stricto that exhibit hyperostosis.