Conservation laws for Z(N) symmetric quantum spin models and their exact ground state energies

We derive an infinite set of conserved charges for some Z(N) symmetric quantum spin models by constructing their Lax pairs. These models correspond to the Potts model, Ashkin-Teller model and the particular set of self-dual Z(N) models solved by Fateev and Zamolodchikov [6]. The exact ground state energy for this last family of hamiltonians is also presented. © 1986.

On the stability of the extracellular hemoglobin of Glossoscolex paulistus, in two iron oxidation states, in the presence of urea

The stability of the Glossoscolex paulistus hemoglobin (HbGp), in two iron oxidation states (and three forms), as monitored by optical absorption, fluorescence emission and circular dichroism (CD) spectroscopies, in the presence of the chaotropic agent urea, is studied. HbGp oligomeric dissociation, denaturation and iron oxidation are observed. CD data show that the cyanomet-HbGp is more stable than the oxy-form. Oxy- and cyanomet-HbGp show good fits on the basis of a two state model with critical urea concentrations at 220-222 nm of 5.1 +/- 0.2 and 6.1 +/- 0.1 mol/L, respectively. The three-state model was able to reveal a subtle second transition at lower urea concentration (1.0-2.0 mol/L) associated to partial oligomeric dissociation. The intermediate state for oxy- and cyanomet-HbGp is very similar to the native state. For met-HbGp, a different equilibrium, in the presence of urea, is observed. A sharp transition at 1.95 +/- 0.05 mol/L of denaturant is observed, associated to oligomeric dissociation and hemichrome formation. In this case, analysis by a three-state model reveals the great similarity between the intermediate and the unfolded states. Analysis of spectroscopic data, by two-state and three-state models, reveals consistency of obtained thermodynamic parameters for HbGp urea denaturation. (C) 2012 Elsevier Inc. All rights reserved.

Closed-loop stable model predictive control of integrating systems with dead time

Model predictive control (MPC) applications in the process industry usually deal with process systems that show time delays (dead times) between the system inputs and outputs. Also, in many industrial applications of MPC, integrating outputs resulting from liquid level control or recycle streams need to be considered as controlled outputs. Conventional MPC packages can be applied to time-delay systems but stability of the closed loop system will depend on the tuning parameters of the controller and cannot be guaranteed even in the nominal case. In this work, a state space model based on the analytical step response model is extended to the case of integrating time systems with time delays. This model is applied to the development of two versions of a nominally stable MPC, which is designed to the practical scenario in which one has targets for some of the inputs and/or outputs that may be unreachable and zone control (or interval tracking) for the remaining outputs. The controller is tested through simulation of a multivariable industrial reactor system. (C) 2012 Elsevier Ltd. All rights reserved.

Substructuring approache in state space models for dynamic system parameters identification

In the recent decade, the request for structural health monitoring expertise increased exponentially in the United States. The aging issues that most of the transportation structures are experiencing can put in serious jeopardy the economic system of a region as well as of a country. At the same time, the monitoring of structures is a central topic of discussion in Europe, where the preservation of historical buildings has been addressed over the last four centuries. More recently, various concerns arose about security performance of civil structures after tragic events such the 9/11 or the 2011 Japan earthquake: engineers looks for a design able to resist exceptional loadings due to earthquakes, hurricanes and terrorist attacks. After events of such a kind, the assessment of the remaining life of the structure is at least as important as the initial performance design. Consequently, it appears very clear that the introduction of reliable and accessible damage assessment techniques is crucial for the localization of issues and for a correct and immediate rehabilitation. The System Identification is a branch of the more general Control Theory. In Civil Engineering, this field addresses the techniques needed to find mechanical characteristics as the stiffness or the mass starting from the signals captured by sensors. The objective of the Dynamic Structural Identification (DSI) is to define, starting from experimental measurements, the modal fundamental parameters of a generic structure in order to characterize, via a mathematical model, the dynamic behavior. The knowledge of these parameters is helpful in the Model Updating procedure, that permits to define corrected theoretical models through experimental validation. The main aim of this technique is to minimize the differences between the theoretical model results and in situ measurements of dynamic data. Therefore, the new model becomes a very effective control practice when it comes to rehabilitation of structures or damage assessment. The instrumentation of a whole structure is an unfeasible procedure sometimes because of the high cost involved or, sometimes, because it’s not possible to physically reach each point of the structure. Therefore, numerous scholars have been trying to address this problem. In general two are the main involved methods. Since the limited number of sensors, in a first case, it’s possible to gather time histories only for some locations, then to move the instruments to another location and replay the procedure. Otherwise, if the number of sensors is enough and the structure does not present a complicate geometry, it’s usually sufficient to detect only the principal first modes. This two problems are well presented in the works of Balsamo [1] for the application to a simple system and Jun [2] for the analysis of system with a limited number of sensors. Once the system identification has been carried, it is possible to access the actual system characteristics. A frequent practice is to create an updated FEM model and assess whether the structure fulfills or not the requested functions. Once again the objective of this work is to present a general methodology to analyze big structure using a limited number of instrumentation and at the same time, obtaining the most information about an identified structure without recalling methodologies of difficult interpretation. A general framework of the state space identification procedure via OKID/ERA algorithm is developed and implemented in Matlab. Then, some simple examples are proposed to highlight the principal characteristics and advantage of this methodology. A new algebraic manipulation for a prolific use of substructuring results is developed and implemented.

Rainfall spatial predictions: a two-part model and its assessment

Spatial prediction of hourly rainfall via radar calibration is addressed. The change of support problem (COSP), arising when the spatial supports of different data sources do not coincide, is faced in a non-Gaussian setting; in fact, hourly rainfall in Emilia-Romagna region, in Italy, is characterized by abundance of zero values and right-skeweness of the distribution of positive amounts. Rain gauge direct measurements on sparsely distributed locations and hourly cumulated radar grids are provided by the ARPA-SIMC Emilia-Romagna. We propose a three-stage Bayesian hierarchical model for radar calibration, exploiting rain gauges as reference measure. Rain probability and amounts are modeled via linear relationships with radar in the log scale; spatial correlated Gaussian effects capture the residual information. We employ a probit link for rainfall probability and Gamma distribution for rainfall positive amounts; the two steps are joined via a two-part semicontinuous model. Three model specifications differently addressing COSP are presented; in particular, a stochastic weighting of all radar pixels, driven by a latent Gaussian process defined on the grid, is employed. Estimation is performed via MCMC procedures implemented in C, linked to R software. Communication and evaluation of probabilistic, point and interval predictions is investigated. A non-randomized PIT histogram is proposed for correctly assessing calibration and coverage of two-part semicontinuous models. Predictions obtained with the different model specifications are evaluated via graphical tools (Reliability Plot, Sharpness Histogram, PIT Histogram, Brier Score Plot and Quantile Decomposition Plot), proper scoring rules (Brier Score, Continuous Rank Probability Score) and consistent scoring functions (Root Mean Square Error and Mean Absolute Error addressing the predictive mean and median, respectively). Calibration is reached and the inclusion of neighbouring information slightly improves predictions. All specifications outperform a benchmark model with incorrelated effects, confirming the relevance of spatial correlation for modeling rainfall probability and accumulation.

A feasibility study on model-based evaluation of kidney perfusion measured by means of FAIR prepared true-FISP arterial spin labeling (ASL) on a 3-T MR scanner

RATIONALE AND OBJECTIVES: A feasibility study on measuring kidney perfusion by a contrast-free magnetic resonance (MR) imaging technique is presented. MATERIALS AND METHODS: A flow-sensitive alternating inversion recovery (FAIR) prepared true fast imaging with steady-state precession (TrueFISP) arterial spin labeling sequence was used on a 3.0-T MR-scanner. The basis for quantification is a two-compartment exchange model proposed by Parkes that corrects for diverse assumptions in single-compartment standard models. RESULTS: Eleven healthy volunteers (mean age, 42.3 years; range 24-55) were examined. The calculated mean renal blood flow values for the exchange model (109 +/- 5 [medulla] and 245 +/- 11 [cortex] ml/min - 100 g) are in good agreement with the literature. Most important, the two-compartment exchange model exhibits a stabilizing effect on the evaluation of perfusion values if the finite permeability of the vessel wall and the venous outflow (fast solution) are considered: the values for the one-compartment standard model were 93 +/- 18 (medulla) and 208 +/- 37 (cortex) ml/min - 100 g. CONCLUSION: This improvement will increase the accuracy of contrast-free imaging of kidney perfusion in treatment renovascular disease.

Exploring the origins of topological frustration: Design of a minimally frustrated model of fragment B of protein A

Topological frustration in an energetically unfrustrated off-lattice model of the helical protein fragment B of protein A from Staphylococcus aureus was investigated. This Gō-type model exhibited thermodynamic and kinetic signatures of a well-designed two-state folder with concurrent collapse and folding transitions and single exponential kinetics at the transition temperature. Topological frustration is determined in the absence of energetic frustration by the distribution of Fersht φ values. Topologically unfrustrated systems present a unimodal distribution sharply peaked at intermediate φ, whereas highly frustrated systems display a bimodal distribution peaked at low and high φ values. The distribution of φ values in protein A was determined both thermodynamically and kinetically. Both methods yielded a unimodal distribution centered at φ = 0.3 with tails extending to low and high φ values, indicating the presence of a small amount of topological frustration. The contacts with high φ values were located in the turn regions between helices I and II and II and III, intimating that these hairpins are in large part required in the transition state. Our results are in good agreement with all-atom simulations of protein A, as well as lattice simulations of a three- letter code 27-mer (which can be compared with a 60-residue helical protein). The relatively broad unimodal distribution of φ values obtained from the all-atom simulations and that from the minimalist model for the same native fold suggest that the structure of the transition state ensemble is determined mostly by the protein topology and not energetic frustration.

Transition-state structure as a unifying basis in protein-folding mechanisms: Contact order, chain topology, stability, and the extended nucleus mechanism

I attempt to reconcile apparently conflicting factors and mechanisms that have been proposed to determine the rate constant for two-state folding of small proteins, on the basis of general features of the structures of transition states. Φ-Value analysis implies a transition state for folding that resembles an expanded and distorted native structure, which is built around an extended nucleus. The nucleus is composed predominantly of elements of partly or well-formed native secondary structure that are stabilized by local and long-range tertiary interactions. These long-range interactions give rise to connecting loops, frequently containing the native loops that are poorly structured. I derive an equation that relates differences in the contact order of a protein to changes in the length of linking loops, which, in turn, is directly related to the unfavorable free energy of the loops in the transition state. Kinetic data on loop extension mutants of CI2 and α-spectrin SH3 domain fit the equation qualitatively. The rate of folding depends primarily on the interactions that directly stabilize the nucleus, especially those in native-like secondary structure and those resulting from the entropy loss from the connecting loops, which vary with contact order. This partitioning of energy accounts for the success of some algorithms that predict folding rates, because they use these principles either explicitly or implicitly. The extended nucleus model thus unifies the observations of rate depending on both stability and topology.

Solid-state synthesis and mechanical unfolding of polymers of T4 lysozyme

Recent advances in single molecule manipulation methods offer a novel approach to investigating the protein folding problem. These studies usually are done on molecules that are naturally organized as linear arrays of globular domains. To extend these techniques to study proteins that normally exist as monomers, we have developed a method of synthesizing polymers of protein molecules in the solid state. By introducing cysteines at locations where bacteriophage T4 lysozyme molecules contact each other in a crystal and taking advantage of the alignment provided by the lattice, we have obtained polymers of defined polarity up to 25 molecules long that retain enzymatic activity. These polymers then were manipulated mechanically by using a modified scanning force microscope to characterize the force-induced reversible unfolding of the individual lysozyme molecules. This approach should be general and adaptable to many other proteins with known crystal structures. For T4 lysozyme, the force required to unfold the monomers was 64 ± 16 pN at the pulling speed used. Refolding occurred within 1 sec of relaxation with an efficiency close to 100%. Analysis of the force versus extension curves suggests that the mechanical unfolding transition follows a two-state model. The unfolding forces determined in 1 M guanidine hydrochloride indicate that in these conditions the activation barrier for unfolding is reduced by 2 kcal/mol.

A statistical mechanical model for β-hairpin kinetics

Understanding the mechanism of protein secondary structure formation is an essential part of the protein-folding puzzle. Here, we describe a simple statistical mechanical model for the formation of a β-hairpin, the minimal structural element of the antiparallel β-pleated sheet. The model accurately describes the thermodynamic and kinetic behavior of a 16-residue, β-hairpin-forming peptide, successfully explaining its two-state behavior and apparent negative activation energy for folding. The model classifies structures according to their backbone conformation, defined by 15 pairs of dihedral angles, and is further simplified by considering only the 120 structures with contiguous stretches of native pairs of backbone dihedral angles. This single sequence approximation is tested by comparison with a more complete model that includes the 215 possible conformations and 15 × 215 possible kinetic transitions. Finally, we use the model to predict the equilibrium unfolding curves and kinetics for several variants of the β-hairpin peptide.

The "allosteric three-site model" of elongation cannot be confirmed in a well-defined ribosome system from Escherichia coli.

For the functional role of the ribosomal tRNA exit (E) site, two different models have been proposed. It has been suggested that transient E-site binding of the tRNA leaving the peptidyl (P) site promotes elongation factor G (EF-G)-dependent translocation by lowering the energetic barrier of tRNA release [Lill, R., Robertson, J. M. & Wintermeyer, W. (1989) EMBO J. 8, 3933-3938]. The alternative "allosteric three-site model" [Nierhaus, K.H. (1990) Biochemistry 29, 4997-5008] features stable, codon-dependent tRNA binding to the E site and postulates a coupling between E and aminoacyl (A) sites that regulates the tRNA binding affinity of the two sites in an anticooperative manner. Extending our testing of the two conflicting models, we have performed translocation experiments with fully active ribosomes programmed with heteropolymeric mRNA. The results confirm that the deacylated tRNA released from the P site is bound to the E site in a kinetically labile fashion, and that the affinity of binding, i.e., the occupancy of the E site, is increased by Mg2+ or polyamines. At conditions of high E-site occupancy in the posttranslocation complex, filling the A site with aminoacyl-tRNA had no influence on the E site, i.e., there was no detectable anticooperative coupling between the two sites, provided that second-round translocation was avoided by removing EF-G. On the basis of these results, which are entirely consistent with our previous results, we consider the allosteric three-site model of elongation untenable. Rather, as proposed earlier, the E site-bound state of the leaving tRNA is a transient intermediate and, as such, is a mechanistic feature of the classic two-state model of the elongating ribosome.

Kinetic model for selective cultivation of microfungi in a microscreen process for food processing wastewater treatment and biomass production

The research was aimed at developing a technology to combine the production of useful microfungi with the treatment of wastewater from food processing. A recycle bioreactor equipped with a micro-screen was developed as a wastewater treatment system on a laboratory scale to contain a Rhizopus culture and maintain its dominance under non-aseptic conditions. Competitive growth of bacteria was observed, but this was minimised by manipulation of the solids retention time and the hydraulic retention time. Removal of about 90% of the waste organic material (as BOD) from the wastewater was achieved simultaneously. Since essentially all fungi are retained behind the 100 mum aperture screen, the solids retention time could be controlled by the rate of harvesting. The hydraulic retention time was employed to control the bacterial growth as the bacteria were washed through the screen at a short HRT. A steady state model was developed to determine these two parameters. This model predicts the effluent quality. Experimental work is still needed to determine the growth characteristics of the selected fungal species under optimum conditions (pH and temperature).

The Bazhanov-Stroganov model from 3D approach

We apply a three-dimensional approach to describe a new parametrization of the L-operators for the two-dimensional Bazhanov-Stroganov (BS) integrable spin model related to the chiral Potts model. This parametrization is based on the solution of the associated classical discrete integrable system. Using a three-dimensional vertex satisfying a modified tetrahedron equation, we construct an operator which generalizes the BS quantum intertwining matrix S. This operator describes the isospectral deformations of the integrable BS model.

Solvable model for distribution networks on random graphs

We propose a simple model that captures the salient properties of distribution networks, and study the possible occurrence of blackouts, i.e., sudden failings of large portions of such networks. The model is defined on a random graph of finite connectivity. The nodes of the graph represent hubs of the network, while the edges of the graph represent the links of the distribution network. Both, the nodes and the edges carry dynamical two state variables representing the functioning or dysfunctional state of the node or link in question. We describe a dynamical process in which the breakdown of a link or node is triggered when the level of maintenance it receives falls below a given threshold. This form of dynamics can lead to situations of catastrophic breakdown, if levels of maintenance are themselves dependent on the functioning of the net, once maintenance levels locally fall below a critical threshold due to fluctuations. We formulate conditions under which such systems can be analyzed in terms of thermodynamic equilibrium techniques, and under these conditions derive a phase diagram characterizing the collective behavior of the system, given its model parameters. The phase diagram is confirmed qualitatively and quantitatively by simulations on explicit realizations of the graph, thus confirming the validity of our approach. © 2007 The American Physical Society.

Extracting protein-protein interactions from MEDLINE using the hidden vector state model

A major challenge in text mining for biomedicine is automatically extracting protein-protein interactions from the vast amount of biomedical literature. We have constructed an information extraction system based on the Hidden Vector State (HVS) model for protein-protein interactions. The HVS model can be trained using only lightly annotated data whilst simultaneously retaining sufficient ability to capture the hierarchical structure. When applied in extracting protein-protein interactions, we found that it performed better than other established statistical methods and achieved 61.5% in F-score with balanced recall and precision values. Moreover, the statistical nature of the pure data-driven HVS model makes it intrinsically robust and it can be easily adapted to other domains.