Peptide models for the bacteriorhodopsin chromophore. Retinylidene-lysine systems containing aspartic acid and serine residues

The retinylidene Schiff base derivative of seven lysine containing peptides have been prepared in order to investigate solvent and neighboring group effects, on the absorption maximum of the protonated Schiff base chromophore. The peptides studied are Boc-Aib-Lys-Aib-OMe (1), Boc-Ala-Aib-Lys-OMe (2), Boc-Ala-Aib-Lys-Aib-OMe (3), Boc-Aib-Asp-Aib-Aib-Lys-Aib-OMe (4), Boc-Aib-Asp-Aib-Ala-Aib-Lys-Aib-OMe (5), Boc-Lys-Val-Gly-Phe-OMe (6) and Boc-Ser-Ala-Lys-Val-Gly-Phe-OMe (7). In all cases protonation shifts the absorption maxima to the red by 3150–8450 cm-1. For peptides 1–3 the protonation shifts are significantly larger in nonhydrogen bonding solvents like CHCl3 or CH2Cl2 as compared to hydrogen bonding solvents like CH3OH. The presence of a proximal Asp residue in 4 and 5 results in pronounced blue shift of the absorption maximum of the protonated Schiff base in CHCl3, relative to peptides lacking this residue. Peptides 6 and 7 represent small segments of the bacteriorhodopsin sequence in the vicinity of Lys-216. The presence of Ser reduces the magnitude of the protonation shift.

On probability-based inference under data missing by design

Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.

Modeling multi-stakeholder multi-objective decisions during public participation in major infrastructure and construction projects: A decision rule approach

Major infrastructure and construction (MIC) projects are those with significant traffic or environmental impact, of strategic and regional significance and high sensitivity. The decision making process of schemes of this type is becoming ever more complicated, especially with the increasing number of stakeholders involved and their growing tendency to defend their own varied interests. Failing to address and meet the concerns and expectations of stakeholders may result in project failures. To avoid this necessitates a systematic participatory approach to facilitate decision-making. Though numerous decision models have been established in previous studies (e.g. ELECTRE methods, the analytic hierarchy process and analytic network process) their applicability in the decision process during stakeholder participation in contemporary MIC projects is still uncertain. To resolve this, the decision rule approach is employed for modeling multi-stakeholder multi-objective project decisions. Through this, the result is obtained naturally according to the “rules” accepted by any stakeholder involved. In this sense, consensus is more likely to be achieved since the process is more convincing and the result is easier to be accepted by all concerned. Appropriate “rules”, comprehensive enough to address multiple objectives while straightforward enough to be understood by multiple stakeholders, are set for resolving conflict and facilitating consensus during the project decision process. The West Kowloon Cultural District (WKCD) project is used as a demonstration case and a focus group meeting is conducted in order to confirm the validity of the model established. The results indicate that the model is objective, reliable and practical enough to cope with real world problems. Finally, a suggested future research agenda is provided.

Queuing Models for Estimating Aircraft Fleet Availability

The availability of a small fleet of aircraft in a flying-base, repair-depot combination is modeled and studied. First, a deterministic flow model relates parameters of interest and represents the state-of-the art in the planning of such systems. Second, a cyclic queue model shows the effect of the principal uncertainties in operation and repair and shows the consequent decrease in the availability of aircraft at the flying-base. Several options such as increasing fleet size, investments in additional repair facilities, or building reliability and maintainability into the individual aircraft during its life-cycle are open for increasing the availability. A life-cycle cost criterion brings out some of these features. Numerical results confirm Rose's prediction that there exists a minimal cost combination of end products and repair-depot capability to achieve a prescribed operational availability.

Evaluation of k-epsilon and RNG turbulence models for confined swirling and non-swirling flow

In a very recent study [1] the Renormalisation Group (RNG) turbulence model was used to obtain flow predictions in a strongly swirling quarl burner, and was found to perform well in predicting certain features that are not well captured using less sophisticated models of turbulence. The implication is that the RNG approach should provide an economical and reliable tool for the prediction of swirling flows in combustor and furnace geometries commonly encountered in technological applications. To test this hypothesis the present work considers flow in a model furnace for which experimental data is available [2]. The essential features of the flow which differentiate it from the previous study [1] are that the annular air jet entry is relatively narrow and the base wall of the cylindrical furnace is at 90 degrees to the inlet pipe. For swirl numbers of order 1 the resulting flow is highly complex with significant inner and outer recirculation regions. The RNG and standard k-epsilon models are used to model the flow for both swirling and non-swirling entry jets and the results compared with experimental data [2]. Near wall viscous effects are accounted for in both models via the standard wall function formulation [3]. For the RNG model, additional computations with grid placement extending well inside the near wall viscous-affected sublayer are performed in order to assess the low Reynolds number capabilities of the model.

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA)problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max-min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.

NUVIEW:software for display and interactive manipulation of nucleic acid models

The NUVIEW software package allows skeletal models of any double helical nucleic acid molecule to be displayed out a graphics monitor and to apply various rotations, translations and scaling transformations interactively, through the keyboard. The skeletal model is generated by connecting any pair of representative points, one from each of the bases in the basepair. In addition to the above mentioned manipulations, the base residues can be identified by using a locator and the distance between any pair of residues can be obtained. A sequence based color coded display allows easy identification of sequence repeats, such as runs of Adenines. The real time interactive manipulation of such skeletal models for large DNA/RNA double helices, can be used to trace the path of the nucleic acid chain in three dimensions and hence get a better idea of its topology, location of linear or curved regions, distances between far off regions in the sequence etc. A physical picture of these features will assist in understanding the relationship between base sequence, structure and biological function in nucleic acids.

Fuzzy waste load allocation model: a multiobjective approach

Fuzzy Waste Load Allocation Model (FWLAM), developed in an earlier study, derives the optimal fractional levels, for the base flow conditions, considering the goals of the Pollution Control Agency (PCA) and dischargers. The Modified Fuzzy Waste Load Allocation Model (MFWLAM) developed subsequently is a stochastic model and considers the moments (mean, variance and skewness) of water quality indicators, incorporating uncertainty due to randomness of input variables along with uncertainty due to imprecision. The risk of low water quality is reduced significantly by using this modified model, but inclusion of new constraints leads to a low value of acceptability level, A, interpreted as the maximized minimum satisfaction in the system. To improve this value, a new model, which is a combination Of FWLAM and MFWLAM, is presented, allowing for some violations in the constraints of MFWLAM. This combined model is a multiobjective optimization model having the objectives, maximization of acceptability level and minimization of violation of constraints. Fuzzy multiobjective programming, goal programming and fuzzy goal programming are used to find the solutions. For the optimization model, Probabilistic Global Search Lausanne (PGSL) is used as a nonlinear optimization tool. The methodology is applied to a case study of the Tunga-Bhadra river system in south India. The model results in a compromised solution of a higher value of acceptability level as compared to MFWLAM, with a satisfactory value of risk. Thus the goal of risk minimization is achieved with a comparatively better value of acceptability level.

Fuzzy-logic-based health monitoring and residual-life prediction for composite helicopter rotor

A health-monitoring and life-estimation strategy for composite rotor blades is developed in this work. The cross-sectional stiffness reduction obtained by physics-based models is expressed as a function of the life of the structure using a recent phenomenological damage model. This stiffness reduction is further used to study the behavior of measurable system parameters such as blade deflections, loads, and strains of a composite rotor blade in static analysis and forward flight. The simulated measurements are obtained using an aeroelastic analysis of the composite rotor blade based on the finite element in space and time with physics-based damage modes that are then linked to the life consumption of the blade. The model-based measurements are contaminated with noise to simulate real data. Genetic fuzzy systems are developed for global online prediction of physical damage and life consumption using displacement- and force-based measurement deviations between damaged and undamaged conditions. Furthermore, local online prediction of physical damage and life consumption is done using strains measured along the blade length. It is observed that the life consumption in the matrix-cracking zone is about 12-15% and life consumption in debonding/delamination zone is about 45-55% of the total life of the blade. It is also observed that the success rate of the genetic fuzzy systems depends upon the number of measurements, type of measurements and training, and the testing noise level. The genetic fuzzy systems work quite well with noisy data and are recommended for online structural health monitoring of composite helicopter rotor blades.

Iron(III) Schiff base complexes of arginine and lysine as netropsin mimics showing AT-selective DNA binding and photonuclease activity

Iron(III) complexes [Fe(L)(2)]Cl (1-3), where L is monoanionic N-salicylidene-arginine (sal-argH for 1), hydroxynaphthylidene-arginine (nap-argH for 2) and N-salicylidene-lysine (sal-lysH for 3), were prepared and their DNA binding and photo-induced DNA cleavage activity studied. Complex 3 as its hexafluorophosphate salt [Fe(sal-lysH)(2)](PF6)center dot 6H(2)O (3a) was structurally characterized by single crystal Xray crystallography. The crystals belonged to the triclinic space group P-1. The complex has two tridentate ligands in FeN2O4 coordination geometry with two pendant cationic amine moieties. Complexes 1 and 2 with two pendant cationic guanidinium moieties are the structural models for the antitumor antibiotics netropsin. The complexes are stable and soluble in water. They showed quasi-reversible Fe(III)/Fe(II) redox couple near 0.6 V in H2O-0.1 M KCl. The high-spin 3d(5)-iron(III) complexes with mu(eff) value of similar to 5.9 mu(B) displayed ligand-to-metal charge transfer electronic band near 500 mm in Tris-HCl buffer. The complexes show binding to Calf Thymus (CT) DNA. Complex 2 showed better binding propensity to the synthetic oligomer poly(dA)center dot poly(dT) than to CT-DNA or poly(dG)center dot poly(dC). All the complexes displayed chemical nuclease activity in the presence of 3-mercaptopropionic acid as a reducing agent and cleaved supercoiled pUC19 DNA to its nicked circular form. They exhibited photo-induced DNA cleavage activity in UV-A light and visible light via a mechanistic pathway that involves the formation of reactive hydroxyl radical species. (C) 2010 Elsevier Inc. All rights reserved.

Uplink Power Control and Base Station Association in Multichannel Cellular Networks

A combined base station association and power control problem is studied for the uplink of multichannel multicell cellular networks, in which each channel is used by exactly one cell (i.e., base station). A distributed association and power update algorithm is proposed and shown to converge to a Nash equilibrium of a noncooperative game. We consider network models with discrete mobiles (yielding an atomic congestion game), as well as a continuum of mobiles (yielding a population game). We find that the equilibria need not be Pareto efficient, nor need they be system optimal. To address the lack of system optimality, we propose pricing mechanisms. It is shown that these mechanisms can be implemented in a distributed fashion.

Seismic response of reinforced soil retaining wall models: Influence of backfill relative density

This paper presents the results of shaking table tests on model reinforced soil retaining walls in the laboratory. The influence of backfill relative density on the seismic response was studied through a series of laboratory model tests on retaining walls. Construction of model retaining walls in the laminar box mounted on shaking table, instrumentation and results from the shaking table tests are described in detail. Three types of walls: wrap- and rigid-faced reinforced soil walls and unreinforced rigid-faced walls constructed to different densities were tested for a relatively small excitation. Wrap-faced walls are further tested for higher base excitation at different frequencies and relative densities. It is observed from these tests that the effect of backfill density on the seismic performance of reinforced retaining walls is pronounced only at very low relative density and at the higher base excitation. The walls constructed with higher backfill relative density showed lesser face deformations and more acceleration amplifications compared to the walls constructed with lower densities when tested at higher base excitation. The response of wrap- and rigid-faced retaining walls is not much affected by the backfill relative density when tested at smaller base excitation. The effects of facing rigidity were evaluated to a limited extent. Displacements in wrap-faced walls are many times higher compared to rigid-faced walls. The results obtained from this study are helpful in understanding the relative performance of reinforced soil retaining walls constructed to when subjected to smaller and higher base excitation for the range of relative density employed in the testing program. (C) 2007 Elsevier Ltd. All rights reserved.

Seismic response of wrap-faced reinforced soil-retaining wall models using shaking table tests

This paper presents the results of shaking table tests on geotextile-reinforced wrap-faced soil-retaining walls. Construction of model retaining walls in a laminar box mounted on a shaking table, instrumentation, and results from the shaking table tests are discussed in detail. The base motion parameters, surcharge pressure and number of reinforcing layers are varied in different model tests. It is observed from these tests that the response of the wrap-faced soil-retaining walls is significantly affected by the base acceleration levels, frequency of shaking, quantity of reinforcement and magnitude of surcharge pressure on the crest. The effects of these different parameters on acceleration response at different elevations of the retaining wall, horizontal soil pressures and face deformations are also presented. The results obtained from this study are helpful in understanding the relative performance of reinforced soil-retaining walls under different test conditions used in the experiments.

Two-agent cooperative search using game models with endurance-time constraints

In this article, the problem of two Unmanned Aerial Vehicles (UAVs) cooperatively searching an unknown region is addressed. The search region is discretized into hexagonal cells and each cell is assumed to possess an uncertainty value. The UAVs have to cooperatively search these cells taking limited endurance, sensor and communication range constraints into account. Due to limited endurance, the UAVs need to return to the base station for refuelling and also need to select a base station when multiple base stations are present. This article proposes a route planning algorithm that takes endurance time constraints into account and uses game theoretical strategies to reduce the uncertainty. The route planning algorithm selects only those cells that ensure the agent will return to any one of the available bases. A set of paths are formed using these cells which the game theoretical strategies use to select a path that yields maximum uncertainty reduction. We explore non-cooperative Nash, cooperative and security strategies from game theory to enhance the search effectiveness. Monte-Carlo simulations are carried out which show the superiority of the game theoretical strategies over greedy strategy for different look ahead step length paths. Within the game theoretical strategies, non-cooperative Nash and cooperative strategy perform similarly in an ideal case, but Nash strategy performs better than the cooperative strategy when the perceived information is different. We also propose a heuristic based on partitioning of the search space into sectors to reduce computational overhead without performance degradation.

An ab-initio study of the proton affinity of conjugated schiff-base and related nitrogen compounds: an analysis of the triggering site of bacteriorhodopsin

The chemical groups which take part in the proton transfer reaction in bacteriorhodopsin have been studied by ab initio quantum chemical methods. The various factors such as conjugation with a linear system, electron delocalization of the guanidine type, cis-trans isomerism, geometry distortion and hydrogen bonding with charged groups can influence the properties of a given chemical group. Several systems are studied at 4-31G and STO-3G levels. Some of the Schiff-base analogues and guanidine type molecules are characterized by their molecular orbital diagrams, energy levels and the nature of charge distribution. Also, the effects of the above-mentioned factors on proton affinity are studied. It is hoped that the values thus obtained can be helpful in evaluating various structural models for proton transfer.