990 resultados para Plant architecture


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X-ray diffraction studies on single crystals of a few viruses have led to the elucidation of their three dimensional structure at near atomic resolution. Both the tertiary structure of the coat protein subunit and the quaternary morganization of the icosahedral capsid in these viruses are remarkably similar. These studies have led to a critical re-examination of the structural principles in the architecture of isometric viruses and suggestions of alternative mechanisms of assembly. Apart from their role in the assembly of the virus particle, the coat proteins of certian viruses have been shown to inhibit the replication of the cognate RNA leading to cross-protection. The coat protein amino acid sequence and the genomic sequence of several spherical plant RNA viruses have been determined in the last decade. Experimental data on the mechanisms of uncoating, gene expression and replication of several classes of viruses have also become available. The function of the non-structural proteins of some viruses have been determined. This rapid progress has provided a wealth of information on several key steps in the life cycle of RNA viruses. The function of the viral coat protein, capsid architecture, assembly and disassembly and replication of isometric RNA plant viruses are discussed in the light of this accumulated knowledge.

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Physalis mottle tymovirus (previously named belladonna mottle virus, Iowa strain) RNA was cross-linked to its coat protein by exposure of the intact virus to ultraviolet light. The site of cross-linking of the coat protein with the RNA was identified as Lys-10 by sequencing the oligonucleotide-linked tryptic peptide obtained upon HPLC separation subsequent to enzymetic digestion of the cross-linked and dissociated virus. Three monoclonal antibodies PA3B2, PB5G9, and PF12C9, obtained using denatured coat protein as antigen, cross-reacted effectively with the intact virus indicating that the epitopes recognized by these monoclonals are on the surface of the virus. Using the peptides generated by digestion with CNBr, clostripain, V-8 protease, or trypsin and a recombinant protein lacking the N-terminal 21 residues expressed from a cDNA clone, it was shown that PA3B2 recognizes the sequence 22-36 on the coat protein while PB5G9 and PF12C9 recognize region 75-110. These results suggest that Lys-10 is one of the specific sites through which the RNA interacts in the intact virus. The polypeptide segment (region 22-36) following this buried portion as well as the epitope within the region 75-110 are exposed in the intact virus. These observations are consistent with the canonical β-barrel structure observed in certain other plant viruses.

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Sesbania mosaic virus (SMV) is a plant virus that infects Sesbania grandiflora plants in Andhra Pradesh, India. The amino acid sequence of the coat protein of SMV was determined using purified peptides generated by cleavage with trypsin, chymotrypsin, V8 protease and clostripain. The 230 residues so far determined were compared to the corresponding residues of southern bean mosaic virus (SBMV), the type member of sobemoviruses. The overall identity between the sequences is 61.7%. The amino terminal 64 residues, which constitute an independent domain (R-domain) known to interact with RNA, are conserved to a lower extent (52.5%). Comparison of the positively charged residues in this domain suggests that the RNA-protein interactions are considerably weaker in SMV. The residues that constitute the major domain of the coat protein, the surface domain (S-domain, residues 65-260), are better conserved (66.5%). The positively charged residues of this domain that face the nucleic acid are well conserved. The longest conserved stretch of residues (131-142) corresponds to the loop involved in intersubunit interactions between subunits related by the quasi 3-fold symmetry. A unique cation binding site located on the quasi 3-fold axis contributes to the stability of SMV. These differences are reflected in the increased stability of the SMV coat protein and its ability to be reconstituted with RNA at pH 7.5. A major epitope was identified using monoclonal antibodies to SMV in the segment 201-223 which contains an exposed helix in the capsid structure. This region is highly conserved between SMV and SBMV (70%) suggesting that it could represent the site of an important function such as vector recognition.

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The centralized paradigm of a single controller and a single plant upon which modern control theory is built is no longer applicable to modern cyber-physical systems of interest, such as the power-grid, software defined networks or automated highways systems, as these are all large-scale and spatially distributed. Both the scale and the distributed nature of these systems has motivated the decentralization of control schemes into local sub-controllers that measure, exchange and act on locally available subsets of the globally available system information. This decentralization of control logic leads to different decision makers acting on asymmetric information sets, introduces the need for coordination between them, and perhaps not surprisingly makes the resulting optimal control problem much harder to solve. In fact, shortly after such questions were posed, it was realized that seemingly simple decentralized optimal control problems are computationally intractable to solve, with the Wistenhausen counterexample being a famous instance of this phenomenon. Spurred on by this perhaps discouraging result, a concerted 40 year effort to identify tractable classes of distributed optimal control problems culminated in the notion of quadratic invariance, which loosely states that if sub-controllers can exchange information with each other at least as quickly as the effect of their control actions propagates through the plant, then the resulting distributed optimal control problem admits a convex formulation.

The identification of quadratic invariance as an appropriate means of "convexifying" distributed optimal control problems led to a renewed enthusiasm in the controller synthesis community, resulting in a rich set of results over the past decade. The contributions of this thesis can be seen as being a part of this broader family of results, with a particular focus on closing the gap between theory and practice by relaxing or removing assumptions made in the traditional distributed optimal control framework. Our contributions are to the foundational theory of distributed optimal control, and fall under three broad categories, namely controller synthesis, architecture design and system identification.

We begin by providing two novel controller synthesis algorithms. The first is a solution to the distributed H-infinity optimal control problem subject to delay constraints, and provides the only known exact characterization of delay-constrained distributed controllers satisfying an H-infinity norm bound. The second is an explicit dynamic programming solution to a two player LQR state-feedback problem with varying delays. Accommodating varying delays represents an important first step in combining distributed optimal control theory with the area of Networked Control Systems that considers lossy channels in the feedback loop. Our next set of results are concerned with controller architecture design. When designing controllers for large-scale systems, the architectural aspects of the controller such as the placement of actuators, sensors, and the communication links between them can no longer be taken as given -- indeed the task of designing this architecture is now as important as the design of the control laws themselves. To address this task, we formulate the Regularization for Design (RFD) framework, which is a unifying computationally tractable approach, based on the model matching framework and atomic norm regularization, for the simultaneous co-design of a structured optimal controller and the architecture needed to implement it. Our final result is a contribution to distributed system identification. Traditional system identification techniques such as subspace identification are not computationally scalable, and destroy rather than leverage any a priori information about the system's interconnection structure. We argue that in the context of system identification, an essential building block of any scalable algorithm is the ability to estimate local dynamics within a large interconnected system. To that end we propose a promising heuristic for identifying the dynamics of a subsystem that is still connected to a large system. We exploit the fact that the transfer function of the local dynamics is low-order, but full-rank, while the transfer function of the global dynamics is high-order, but low-rank, to formulate this separation task as a nuclear norm minimization problem. Finally, we conclude with a brief discussion of future research directions, with a particular emphasis on how to incorporate the results of this thesis, and those of optimal control theory in general, into a broader theory of dynamics, control and optimization in layered architectures.

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‘A free Ireland would drain the bogs, would harness the rivers, would plant the wastes, would nationalise the railways and the waterways, would improve agriculture, would protect fisheries, would foster industries, would promote commerce, and beautify the cities …’ (Padraig Pearse, ‘From a Hermitage’, 1913)

Somewhat unusually in his often romantic writings Padraig Pearse – poet, pedagogue and revolutionary – chose to describe the future of an independent Ireland in terms of infrastructure and technological processes. Terence Brown’s locating of this excerpt at the beginning his seminal work Ireland: A Social and Cultural History 1922-2002 highlights the simultaneous and interlinking construction of both a new physical and cultural landscape for an independent modern nation. Lacking any significant industrial complex, the construction of new infrastructures in Ireland was seen throughout the 20th century as a key element in the building of the new State, just as the adoption of an international style modernism in architecture was perceived as a way to escape the colonial past. For Paul N. Edwards modernity and infrastructure are intimately connected.

‘infrastructures simultaneously shape and are shaped – in other words, co-construct – the condition of modernity. By linking macro, meso, and micro scales of time, space and social organisation, they form the stable foundation of modern social worlds’ (2003: 186).
Simultaneously omnipresent and invisible – infra means beneath – Edwards also points out that infrastructure tends only to become apparent when it is either new or broken. Interpreting the meso scale as being that of the building, this session calls for papers that critically and analytically investigate aspects of the architectures of infrastructure in 20th-century Ireland. Like the territory they explore these papers may range across scales to oscillate between a concern for the artefact and its physical landscape, and the larger, often hidden systems and networks that co-define this architecture.

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In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

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In this paper a parallel implementation of an Adaprtive Generalized Predictive Control (AGPC) algorithm is presented. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

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The activated sludge process - the main biological technology usually applied to wastewater treatment plants (WWTP) - directly depends on live beings (microorganisms), and therefore on unforeseen changes produced by them. It could be possible to get a good plant operation if the supervisory control system is able to react to the changes and deviations in the system and can take the necessary actions to restore the system’s performance. These decisions are often based both on physical, chemical, microbiological principles (suitable to be modelled by conventional control algorithms) and on some knowledge (suitable to be modelled by knowledge-based systems). But one of the key problems in knowledge-based control systems design is the development of an architecture able to manage efficiently the different elements of the process (integrated architecture), to learn from previous cases (spec@c experimental knowledge) and to acquire the domain knowledge (general expert knowledge). These problems increase when the process belongs to an ill-structured domain and is composed of several complex operational units. Therefore, an integrated and distributed AI architecture seems to be a good choice. This paper proposes an integrated and distributed supervisory multi-level architecture for the supervision of WWTP, that overcomes some of the main troubles of classical control techniques and those of knowledge-based systems applied to real world systems