On the axiomatic approach to the maximum entropy principle of inference

Recent axiomatic derivations of the maximum entropy principle from consistency conditions are critically examined. We show that proper application of consistency conditions alone allows a wider class of functionals, essentially of the form ∝ dx p(x)[p(x)/g(x)] s , for some real numbers, to be used for inductive inference and the commonly used form − ∝ dx p(x)ln[p(x)/g(x)] is only a particular case. The role of the prior densityg(x) is clarified. It is possible to regard it as a geometric factor, describing the coordinate system used and it does not represent information of the same kind as obtained by measurements on the system in the form of expectation values.

Principle of a Dual Current Source Converter for AC Motor Drives

The principle of operation of a dual current source converter is briefly explained. The combination of two single current source converters (SCSC) to form a ``dual (duplex) current source converter'' (DCSC) is proposed. The DCSC is shown to have the following merits: 1) it retains all the advantages of the SCSC; 2) it reduces the harmonic content of the current waveform considerably; and 3) since the load current is shared equally between two current source converters, ratings of the individual components employed in the circuit are considerably lowered. A DCSC can be an attractive choice for sophisticated large horsepower drives where a good performance of the drive rather than cost is a prime factor. An open-loop control scheme employing the DCSC for an ac motor drive has been successfully implemented in the laboratory. Oscillograms of the improved load current waveforms are shown.

The principle of microscopic reversibility in organic chemistry - a critique

The principle of microscopic reversibility is one of the few generalising principles used in organic chemistry which have their roots in the fundamental laws of thermodynamics. It has, therefore, been highly popular. However, although the principle has some important uses, its general application is not without pitfalls. The principle is easy to misunderstand and to misapply: indeed, some of its formulations are semantically dubious. The principle is most dangerous when used as a charm, for it is more subtle than some of its formulations suggest. But above all, the principle may not be used for deducing or disproving the mechanism of a reaction, except when the mechanism in the reverse direction is known independently. For, such use is, perhaps, the deadliest misapplication.

An absolute method for the determination of surface tension of liquids using pendent drop profiles

Drop formation at conical tips which is of relevance to metallurgists is investigated based on the principle of minimization of free energy using the variational approach. The dimensionless governing equations for drop profiles are computer solved using the fourth order Runge-Kutta method. For different cone angles, the theoretical plots of XT and ZT vs their ratio, are statistically analyzed, where XT and ZT are the dimensionless x and z coordinates of the drop profile at a plane at the conical tip, perpendicular to the axis of symmetry. Based on the mathematical description of these curves, an absolute method has been proposed for the determination of surface tension of liquids, which is shown to be preferable in comparison with the earlier pendent-drop profile methods.

Time dependence of effective slip on textured hydrophobic surfaces

In this paper, we present results on water flow past randomly textured hydrophobic surfaces with relatively large surface features of the order of 50 µm. Direct shear stress measurements are made on these surfaces in a channel configuration. The measurements indicate that the flow rates required to maintain a shear stress value vary substantially with water immersion time. At small times after filling the channel with water, the flow rates are up to 30% higher compared with the reference hydrophilic surface. With time, the flow rate gradually decreases and in a few hours reaches a value that is nearly the same as the hydrophilic case. Calculations of the effective slip lengths indicate that it varies from about 50 µm at small times to nearly zero or “no slip” after a few hours. Large effective slip lengths on such hydrophobic surfaces are known to be caused by trapped air pockets in the crevices of the surface. In order to understand the time dependent effective slip length, direct visualization of trapped air pockets is made in stationary water using the principle of total internal reflection of light at the water-air interface of the air pockets. These visualizations indicate that the number of bright spots corresponding to the air pockets decreases with time. This type of gradual disappearance of the trapped air pockets is possibly the reason for the decrease in effective slip length with time in the flow experiments. From the practical point of usage of such surfaces to reduce pressure drop, say, in microchannels, this time scale of the order of 1 h for the reduction in slip length would be very crucial. It would ultimately decide the time over which the surface can usefully provide pressure drop reductions. ©2009 American Institute of Physics

Flux balance analysis of biological systems: applications and challenges

Systems level modelling and simulations of biological processes are proving to be invaluable in obtaining a quantitative and dynamic perspective of various aspects of cellular function. In particular, constraint-based analyses of metabolic networks have gained considerable popularity for simulating cellular metabolism, of which flux balance analysis (FBA), is most widely used. Unlike mechanistic simulations that depend on accurate kinetic data, which are scarcely available, FBA is based on the principle of conservation of mass in a network, which utilizes the stoichiometric matrix and a biologically relevant objective function to identify optimal reaction flux distributions. FBA has been used to analyse genome-scale reconstructions of several organisms; it has also been used to analyse the effect of perturbations, such as gene deletions or drug inhibitions in silico. This article reviews the usefulness of FBA as a tool for gaining biological insights, advances in methodology enabling integration of regulatory information and thermodynamic constraints, and finally addresses the challenges that lie ahead. Various use scenarios and biological insights obtained from FBA, and applications in fields such metabolic engineering and drug target identification, are also discussed. Genome-scale constraint-based models have an immense potential for building and testing hypotheses, as well as to guide experimentation.

Swarm intelligence-based solver for parameter estimation of laboratory through-diffusion transport of contaminants

Theoretical approaches are of fundamental importance to predict the potential impact of waste disposal facilities on ground water contamination. Appropriate design parameters are generally estimated be fitting theoretical models to data gathered from field monitoring or laboratory experiments. Transient through-diffusion tests are generally conducted in the laboratory to estimate the mass transport parameters of the proposed barrier material. Thes parameters are usually estimated either by approximate eye-fitting calibration or by combining the solution of the direct problem with any available gradient-based techniques. In this work, an automated, gradient-free solver is developed to estimate the mass transport parameters of a transient through-diffusion model. The proposed inverse model uses a particle swarm optimization (PSO) algorithm that is based on the social behavior of animals searching for food sources. The finite difference numerical solution of the forward model is integrated with the PSO algorithm to solve the inverse problem of parameter estimation. The working principle of the new solver is demonstrated and mass transport parameters are estimated from laboratory through-diffusion experimental data. An inverse model based on the standard gradient-based technique is formulated to compare with the proposed solver. A detailed comparative study is carried out between conventional methods and the proposed solver. The present automated technique is found to be very efficient and robust. The mass transport parameters are obtained with great precision.

Analytical method for solving a set of inhomogeneous infinite simultaneous equations

It is shown that a method based on the principle of analytic continuation can be used to solve a set of inhomogeneous infinite simultaneous equations encountered in the analysis of surface acoustic wave propagation along the periodically perturbed surface of a piezoelectric medium.

Analytical method for solving a set of infinite simultaneous equations

It is shown that a method based on the principle of analytic continuation can be used to solve a set of infinite simultaneous equations encountered in solving for the electric field of a periodic electrode structure.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

An optimal dynamic inversion-based neuro-adaptive approach for treatment of chronic myelogenous leukemia

Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an innovative technique is presented to design an automatic drug administration strategy for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used to design the controller (medication dosage). First, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat the nominal model patients (patients who can be described by the mathematical model used here with the nominal parameter values) effectively. However, since the system parameters for a realistic model patient can be different from that of the nominal model patients, simulation studies for such patients indicate that the nominal controller is either inefficient or, worse, ineffective; i.e. the trajectory of the number of cancer cells either shows non-satisfactory transient behavior or it grows in an unstable manner. Hence, to make the drug dosage history more realistic and patient-specific, a model-following neuro-adaptive controller is augmented to the nominal controller. In this adaptive approach, a neural network trained online facilitates a new adaptive controller. The training process of the neural network is based on Lyapunov stability theory, which guarantees both stability of the cancer cell dynamics as well as boundedness of the network weights. From simulation studies, this adaptive control design approach is found to be very effective to treat the CML disease for realistic patients. Sufficient generality is retained in the mathematical developments so that the technique can be applied to other similar nonlinear control design problems as well.

Interaction of cationic amphiphilic drugs with lipid A: Implications for development of endotoxin antagonists

This report presents evidence for the interactions of several classes of cationic amphiphilic drugs including the phenothiazines, aminoquinolines, biguanides, and aromatic diamidines, with lipid A, the endotoxic principle of lipopolysaccharides. The interactions of the drugs were quantitatively assessed by fluorescence methods. The affinities of the drugs for lipid A parallel their endotoxin-antagonistic effects in the Limulus gelation assay. Dicationic compounds bind lipid A with greater affinity; the affinity of such molecules increases exponentially as a function of the distance between the basic moieties. The bis-amidine drug - pentamidine - examined in greater detail, binds lipid A with high affinity (apparent K-d: 0.12 mu M), and LPS, probably due to simultaneous interactions of the terminal amidine groups with the anionic phosphates on lipid A. The sequestration of endotoxin by pentamidine reduces its propensity to bind to cells, and the complex exhibits attenuated toxicity in biological assays. These results have implications in the development of therapeutic strategies against endotoxin-related disease states.

The change of complete symmetry of the crystals during the phase transitions in ferroelectrics and ferromagnetics

The extension of the superposition principle of the symmetries (P. Curie principle of symmetry) for the case of complete symmetry is given. The enumeration of all crystallographical groups of complete symmetry is presented, the number of elements having complete symmetry for each class of the crystals being indicated. The change of complete symmetry of the crystals under the phase transitions is obtained by superimposing the elements of complete symmetry of polar or axial vectors on the one hand, and the elements of complete symmetry of the crystals on the other. The tables of complete symmetry changes for the cubic, rhombic, monoclinic and triclinic crystals during the ferroelectric and ferromagnetic phase transitions are given.

A new method of producing local enhancement of buoyancy in liquid flows

We describe here a novel method of generating large volumetric heating in a liquid. The method uses the principle of ohmic heating of the liquid, rendered electrically conducting by suitable additives if necessary. Electrolysis is prevented by the use of high frequency alternating voltage and chemically treated electrodes. The technique is demonstrated by producing substantial heating in an initially neutral jet of water. Simple flow visualisation studies, made by adding dye to the jet, show marked changes in the growth and development of the jet with heat addition.