Receding horizon control using modified iterative dynamic programming and neural network models

The basic idea of the contribution is to replace a mathematical model of the process by an equivalent neural network (NN) that mimics the phenomenological model and it is used as a process predictor in the modified iterative dynamic programming control (IDP) algoritlun. IDP is a very useful teclmique for solving unconstrained and constrained dynamic optimisation problems. The original IDP method is developed for continuous systems within state space formulation. The modified algoritlun uses a learned NN as a process predictor. The algoritlun modifications resulting from this type of the models include several important issues that arise from the use of discrete-time and input-output model formulations. Moreover, there are also some significant problems that are not to be overlooked stemming from the receding horizon implementation of the method. The contribution discusses all these issues. The benefits of the proposed approach are small number of iterations required to converge to global optimum, ability to handle multivariable constrained systems and significant time reduction compared to the original IDP method.     

On solving optimal control problems with free initial condition using iterative dynamic programming

For solving optimal control problems where the initial conditions of some of the state variables are not specified, a procedure based on iterative dynamic programming (IDP) is presented. In this procedure, the free initial conditions are taken to be additional control variables for the first time stage only; then the search for the optimal initial conditions and also the optimal control policy is carried out simultaneously using IDP. The procedure is straightforward, and as illustrated with two nonlinear optimal control problems, for each case the optimum performance index is readily obtained.     

Bang‐Bang solution of nonlinear time‐optimal control problems using a semi‐exhaustivesearch

At times, the objective is to seek a bang‐bang control policy for nonlinear time‐optimal control problems. The usefulness of iterative dynamic programming (IDP) has been shown in the literature for solving such problems. However, the convergence to the optimal solution has been obtained from about 50% of the guessed values near the optimum. In this paper, we present a semiexhaustive search method for seeking such solutions and a comparison is made with the IDP. The results show that the convergence can be obtained from a significantly higher number of guessed values chosen over a much wider region around the optimum.     

A Three-section Algorithm of Dynamic Programming Based on Three-stage Decomposition System Model for Grade Transition Trajectory Optimization Problems

This paper introduces a practical solving scheme of gradetransition trajectory optimization (GTTO) problems under typical certificate-checking–updating framework. Due to complicated kinetics of polymer...     

Insight into the Binding and Hydrolytic Preferences of hNudt16 Based on Nucleotide Diphosphate Substrates

Nudt16 is a member of the NUDIX family of hydrolases that show specificity towards substrates consisting of a nucleoside diphosphate linked to another moiety X. Several substrates for hNudt16 and various possible biological functions have been reported. However, some of these reports contradict each other and studies comparing the substrate specificity of the hNudt16 protein are limited. Therefore, we quantitatively compared the affinity of hNudt16 towards a set of previously published substrates, as well as identified novel potential substrates. Here, we show that hNudt16 has the highest affinity towards IDP and GppG, with K_d below 100 nM. Other tested ligands exhibited a weaker affinity of several orders of magnitude. Among the investigated compounds, only IDP, GppG, m⁷GppG, AppA, dpCoA, and NADH were hydrolyzed by hNudt16 with a strong substrate preference for inosine or guanosine containing compounds. A new identified substrate for hNudt16, GppG, which binds the enzyme with an affinity comparable to that of IDP, suggests another potential regulatory role of this protein. Molecular docking of hNudt16-ligand binding inside the hNudt16 pocket revealed two binding modes for representative substrates. Nucleobase stabilization by Π stacking interactions with His24 has been associated with strong binding of hNudt16 substrates.     

A Lumenal Loop Associated with Catalytic Asymmetry in Plant Vacuolar H+-Translocating Pyrophosphatase

Membrane-integral inorganic pyrophosphatases (mPPases) couple pyrophosphate hydrolysis with H⁺ and Na⁺ pumping in plants and microbes. mPPases are homodimeric transporters with two catalytic sites facing the cytoplasm and demonstrating highly different substrate-binding affinities and activities. The structural aspects of the functional asymmetry are still poorly understood because the structure of the physiologically relevant dimer form with only one active site occupied by the substrate is unknown. We addressed this issue by molecular dynamics (MD) simulations of the H⁺-transporting mPPase of Vigna radiata, starting from its crystal structure containing a close substrate analog (imidodiphosphate, IDP) in both active sites. The MD simulations revealed pre-existing subunit asymmetry, which increased upon IDP binding to one subunit and persisted in the fully occupied dimer. The most significant asymmetrical change caused by IDP binding is a ‘rigid body’-like displacement of the lumenal loop connecting α-helices 2 and 3 in the partner subunit and opening its exit channel for water. This highly conserved 14–19-residue loop is found only in plant vacuolar mPPases and may have a regulatory function, such as pH sensing in the vacuole. Our data define the structural link between the loop and active sites and are consistent with the published structural and functional data.     

Optimal reaction conditions for the minimization of energy consumption and by‐product formation in a poly(ethylene terephthalate) process

We determined the optimal reaction conditions to minimize the energy cost and the quantities of by‐products for a poly(ethylene terephthalate) process by using the iterative dynamic programming (IDP) algorithm. Here, we employed a sequence of three reactor models: the semibatch transesterification reactor model, the semibatch prepolymerization reactor model, and the rotating‐disc‐type polycondensation reactor model. We selectively chose or developed the reactor models by incorporating experimentally verified kinetic models reported in the literature. We established the model for the entire reactor system by connecting the three reactor models in series and by resolving some joint problems arising when different types of reactor models were interconnected. On the basis of the simulation results of the reactor system, we scrutinized the cause and effect between the reaction conditions and the final quality of the polymer product. Here, we set up the optimization strategy by using IDP on the basis of the integrated reactor model, and the process variables with significant influence on the properties of polymer were selected as control variables with the help of a simulation study. With this method, we could refine the reaction conditions at the end of each iteration step by contracting the spectra of control regions, and the iteration process finally stopped when the profile of the optimal trajectory converged. We also took the constraints on the control variables into account to guarantee polymer quality and to suppress side reactions. Constituting six different strategies by setting weighting vectors differently, we examined the differences in optimal trajectories, the trend of optimality, and the quality of the final polymer product. For each of the strategies, we conducted the optimization to examine whether the number‐average degree of polymerization approached the desired value. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 993–1008, 2002     

Further developments in the new approach to boundary condition iteration in optimal control

In solving the boundary value problem resulting from the use of Pontryagin's maximum principle, a transformation matrix is used to relate the sensitivity of the final state to the initial state. This avoids the need to solve the (n × n) differential equation to give the transition matrix, and yields very rapid convergence to the optimum. To ensure convergence, iterative dynamic programming (IDP) is used for a number of passes to yield good starting conditions for this boundary condition iteration procedure. Clipping technique is used to handle constraints on control. Five optimal control problems are used to illustrate and to test the procedure.     

Iminodipropionic acid as the leaving group for DNA polymerization by HIV-1 reverse transcriptase

Previous studies have demonstrated that some selected amino monoacids and amino diacids can function as leaving groups in the polymerase‐catalyzed incorporation of deoxynucleotides into DNA. Among these, the iminodiacetic acid phosphoramidate of deoxyadenosine monophosphate (IDA‐dAMP) represents an interesting example, as it could overcome some of the problems observed when using L ‐aspartic acid as the leaving group, that is, poor chain elongation. We have now synthesized and evaluated a series of IDA‐dAMP analogues that bear either an extended aliphatic chain in the amino acid function, or a phosphonic acid moiety (substituting for the carboxylic acid function). Among these compounds, the nucleotide with an iminodipropionic acid leaving group (IDP‐dAMP) was identified as the best substrate; the excellent single incorporation (91 % conversion to a P+1 strand at 50 μM ) was at a substrate concentration ten times lower than that used for IDA‐dAMP). This nucleotide also presented improved kinetics and elongation capability compared to IDA‐dAMP. The analogues with T, G, and C base moieties were also investigated for their incorporation ability with HIV‐1 RT. The incorporation efficiency was found to decrease in the order A>T>G>C. The properties of the iminodipropionic acid as the leaving group surpass those of previously evaluated leaving groups; this acid will be a prime candidate for in vivo testing.     

迭代动态规划在系统最优化中的应用

<正>过程系统优化是化工过程设计、操作及控制的一个重要课题,很多情况下,其所涉及到的连续系统是以非常复杂的非线性微分方程组来表示的;而对于这种非线性的多维系统,有效地寻找其     

Density functional theory for the study of the multimode Jahn-Teller effect

The Jahn-Teller (JT) theorem states that in a molecule with a degenerate electronic state, a structural distortion must occur that lowers the symmetry, removes the degeneracy and lowers the energy. The multideterminental-DFT method performed to calculate the JT parameters for JT active molecules is described. Within the harmonic approximation the JT distortion can be analyzed as a linear combination of all totally symmetric normal modes in any of the low symmetry minimum energy conformation, which allows the intrinsic distortion path (IDP) to be calculated, exactly from the high symmetry point to the low symmetry configuration. Results obtained by the approach described here give direct insight into the coupling of electronic structure and nuclear movements.     

Heterocyclic compounds as releasers of the fright reaction in the giant danioDanio malabaricus (Jerdon) (Cyprinidae,Ostariophysi, Pisces)

Fifty-nine pteridine, purine, and pyrimidine derivatives were tested with schools of the giant danioDanio malabaricus (Jerdon). The fright reaction was elicited by three pteridine derivatives: 2,6-diamino-4-oxodihydropteridine, isoxanthopterin, and 6-acetonyliso-xanthopterin. A minor effect could not be excluded for three purine derivatives: I-5-MP, IDP, and ITP.     

Evaluation of the parameters used in iterative dynamic programming

To apply iterative dynamic programming (IDP) to optimal control problems having a very large number of control variables the use of randomly chosen values for control at each grid point is required. To gain insight into the effect of the number of allowable values for control, the region contraction factor, and the number of grid points for the state vector to be used, computational results are presented for two nonlinear systems, one of which possesses numerous local optima. The reliability of obtaining the global optimum for the bifunctional catalyst blend optimization problem was found to be somewhat higher by using randomly chosen values for control rather than by choosing the control values over a uniform distribution. The global optimum is obtained even when a small number of allowable values for control at each grid point and a small number of grid points for the states are used. There is a wide range of the region contraction factor for which rapid convergence to the optimum is obtained. Also the number of grid points for the state can be very small without adversely affecting convergence to the optimum.     

Intrinsically disordered proteins: from sequence and conformational properties toward drug discovery

Structural disorder of functional proteins under physiological conditions is widespread within eukaryotic proteomes. The lack of stable tertiary and secondary structure offers a variety of functional advantages to intrinsically disordered proteins (IDPs): their malleability of interaction with different partners, specific but low-affinity binding, and their fine modulation by post-translational modifications. IDPs are therefore central players in key processes such as cell-cycle control and signal-transduction pathways, and impairment of their function is associated with many disease states such as cancer and neurodegenerative disorders. Fascinating progress in the experimental characterization of IDPs has been made in the last decade, especially in NMR spectroscopy and small-angle X-ray scattering as well as in single-molecule techniques. It has been accompanied by the development of powerful computational tools to translate experimental results in explicit ensemble representations of IDPs. With the aid of bioinformatics tools, these advances have paved the way to targeting IDP interactions in rational drug-discovery projects.     

Effects of four isocyanates and four plasticizers on the thermomechanical and tensile properties of hydroxyl-terminated polybutadiene elastomers and the effect of solid particle filling

The aim of this study is to analyze effect of four different isocyanates and four different plasticizers in hydroxyl-terminated polybutadiene (HTPB) based elastomers by quantitative analysis of the shape of the loss factor (tan δ), tensile strength, deformation frequency shift of the maximum temperatures of loss moduli G" and of tan δ. The first part of the study shows intensities of the tan δ curves with the four isocyanates follow the order HDI > IPDI > H12MDI > Desmodur™ E305. By molecular modeling of the isocyanates and the corresponding polyurethane parts the influence of molecular geometry on tan δ are discussed. The second part of the study analyzes HTPB-IPDI elastomers with the four different plasticizers DOA, DOS, DOZ, and IDP. The IDP provides lowest T_g at about −83°C, while the others provide at about −78°C. In the third part, aluminum (Al-18 μm) and ammonium perchlorate (AP-200 μm) are added to HTPB-IPDI+DOA to analyze the effect of particle size, wt% content and particle type on the shape and intensity of the tan δ curves. From the frequency shift of the two maximum temperatures one receives activation energies Eaf. Their average values without and with plasticizer are with tan δ 178 and 165 kJ/mol and with G" 274 and 248 kJ/mol, respectively.     

Binding Mode Characterization of Osteopontin on Hydroxyapatite by Solution NMR Spectroscopy

Extracellular matrix glycoproteins play a major role in bone mineralization and modulation of osteogenesis. Among these, the intrinsically disordered protein osteopontin (OPN) is associated with the inhibition of formation, growth and proliferation of the bone mineral hydroxyapatite (HAP). Furthermore, post-translational modifications like phosphorylation can alter conformations and interaction properties of intrinsically disordered proteins (IDPs). Therefore, the actual interaction of OPN with a HAP surface on an atomic level and how this interaction is affected by phosphorylation is of great interest. Here, we study the interaction of full-length OPN on the surface of suspended HAP nanoparticles by solution NMR spectroscopy. We report the binding modes of this IDP and provide evidence for the influence of hyperphosphorylation on the binding character and an explanation for the differing roles in biomineralization. Our study moreover presents an easy and suitable option to measure interaction of nanoparticles in a stable suspension with full-length proteins.     

The Hydrophilic Loop of Arabidopsis PIN1 Auxin Efflux Carrier Harbors Hallmarks of an Intrinsically Disordered Protein

Much of plant development depends on cell-to-cell redistribution of the plant hormone auxin, which is facilitated by the plasma membrane (PM) localized PIN FORMED (PIN) proteins. Auxin export activity, developmental roles, subcellular trafficking, and polarity of PINs have been well studied, but their structure remains elusive besides a rough outline that they contain two groups of 5 alpha-helices connected by a large hydrophilic loop (HL). Here, we focus on the PIN1 HL as we could produce it in sufficient quantities for biochemical investigations to provide insights into its secondary structure. Circular dichroism (CD) studies revealed its nature as an intrinsically disordered protein (IDP), manifested by the increase of structure content upon thermal melting. Consistent with IDPs serving as interaction platforms, PIN1 loops homodimerize. PIN1 HL cytoplasmic overexpression in Arabidopsis disrupts early endocytic trafficking of PIN1 and PIN2 and causes defects in the cotyledon vasculature formation. In summary, we demonstrate that PIN1 HL has an intrinsically disordered nature, which must be considered to gain further structural insights. Some secondary structures may form transiently during pairing with known and yet-to-be-discovered interactors.