Optimal non-linear reinforcement schemes for stochastic automata

Two optimal non-linear reinforcement schemes—the Reward-Inaction and the Penalty-Inaction—for the two-state automaton functioning in a stationary random environment are considered. Very simple conditions of symmetry of the non-linear function figuring in the reinforcement scheme are shown to be necessary and sufficient for optimality. General expressions for the variance and rate of learning are derived. These schemes are compared with the already existing optimal linear schemes in the light of average variance and average rate of learning.

Equivalence conditions for classes of linear and non-linear distributed parameter systems

Equivalence of certain classes of second-order non-linear distributed parameter systems and corresponding linear third-order systems is established through a differential transformation technique. As linear systems are amenable to analysis through existing techniques, this study is expected to offer a method of tackling certain classes of non-linear problems which may otherwise prove to be formidable in nature.

Non-destructive discrimination of Bell states by NMR using a single ancilla qubit

Discrimination of Bell states plays an important role in a number of quantum computational protocols such as teleportation and secret sharing. However, most of the protocols dealing with Bell state discrimination in the literature either involve performing correlated measurements or destroying the entanglement of the system. Here, we demonstrate an NMR-based experimental realization of a protocol for Bell state discrimination, following a scheme proposed by Gupta et al (quant-ph/0504183v1, 23 April 2005), which does not destroy the Bell state under consideration. Using the proposed protocol, one can deterministically distinguish the Bell states, without performing a measurement using the entangled basis. State discrimination is performed through two independent measurements on one ancilla qubit, which leaves the Bell states unchanged.

Non-disruptive and null-deflection mass flow measurement by a pressure compensation technique

Accurate mass flow measurement is very important in various monitoring and control applications. This paper proposes a novel method of fluid flow measurement by compensating the pressure drop across the ends of measuring unit using a compensating pump. The pressure drop due to the flow is balanced by a feedback control loop. This is a null-deflection type of measurement. As the insertion of such a measuring unit does not affect the functioning of the systems, this is also a non-disruptive flow measurement method. The implementation and design of such a unit are discussed. The system is modeled and simulated using the bond graph technique and it is experimentally validated. (C) 2009 Elsevier Ltd. All rights reserved.

Worst inputs and a bound on the highest peak statistics of a class of non-linear systems

A method is developed by which the input leading to the highest possible response in an interval of time can be determined for a class of non-linear systems. The input, if deterministic, is constrained to have a known finite energy (or norm) in the interval under consideration. In the case of random inputs, the energy is constrained to have a known probability distribution function. The approach has applications when a system has to be put to maximum advantage by getting the largest possible output or when a system has to be designed to the highest maximum response with only the input energy or the energy distribution known. The method is also useful in arriving at a bound on the highest peak distribution of the response, when the excitation is a known random process.As an illustration the Duffing oscillator has been analysed and some numerical results have also been presented.

An approximate analysis of non-linear non-conservative systems subjected to step function excitation

This paper deals with the approximate analysis of the step response of non-linear nonconservative systems by the application of ultraspherical polynomials. From the differential equations for amplitude and phase, set up by the method of variation of parameters, the approximate solutions are obtained by a generalized averaging technique based on ultraspherical polynomial expansions. The Krylov-Bogoliubov results are given by a particular set of these polynomials. The method has been applied to study the step response of a cubic spring mass system in presence of viscous, material, quadratic, and mixed types of damping. The approximate results are compared with the digital and analogue computer solutions and a close agreement has been found between the analytical and the exact results.

Natural modes of a coupled non-linear system

The natural modes of a non-linear system with two degrees of freedom are investigated. The system, which may contain either hard or soft springs, is shown to possess three modes of vibration one of which does not have any counterpart in the linear theory. The stability analysis indicates the existence of seven different modal stability patterns depending on the values of two parameters of non-linearity.

Undamped Cooper pairs in a non-degenerate electron system

Following the reaction matrix technique and the Kanamori approximation. a condition is obtained for the occurence of undamped Cooper pairs in a non-degenerate electron system. Its relevance to induced superconductivity in systems with artificially populated (optically pumped) bands is pointed out.

Studies on non-specific interference due to serum in the avidin-biotin microELISA for monkey chorionic gonadotropin and a method for its elimination

A study has been carried out on the non-specific interference due to serum in the avidin biotin micro-ELISA for monkey chorionic gonadotropin. Results suggest that it is not due to any proteolytic activity in the serum, but immunoglobulin or associated factors interfering at the level of antigen-antibody interaction. This interference was eliminated by heating samples at 60°C for 30 min.

Transfers of Family Businesses to Non-Family Buyers - The Selling Business Family Perspective

This study focuses on business families and how they handle transitions such as business transfers. It also tries to shift the balance of research away from successions and towards business transfers as a key topic for family business researchers. In addition, it contributes to the family business research field by further highlighting the importance of the various different contributions in the family business from business family members other than the entrepreneurial founder. Based on interviews with both business family members and business brokers, it appears as important for business families who are selling their family business that it is managed in a similar way in the future regardless of the shift in ownership and management. It is also important that the employees can stay with the business. However, employees are seldom regarded as potential buyers of the family business; most preferably, from the point of view of business family members, this should be somebody who is similar to themselves. Business transfers can be lengthy processes, but once the family business is sold, previous owners most often want to leave the family business. This disengagement can be difficult for business family members if they have not managed to build up some other identity outside the family business environment. Money may compensate for the loss in the short run, but something else is needed in the long run, since the management of money is usually not perceived as that interesting. A family business transfer can have great influence on the members of the business family who is selling, and therefore it is suggested that personal due diligence could be of some help when planning the transfer. That tool can help business family members to analyse their own personal situation, but it may also make it easier to understand how the other business family members feel about the forthcoming change. Everyone is influenced in different ways during a family business transfer, and awareness of this fact may make it easier for the whole business family to adjust to their new environment.

Enzyme catalysed non-oxidative decarboxylation of aromatic acids II. Identification of active site residues of 2,3-dihydroxybenzoic acid decarboxylase from Aspergillus niger

In order to understand the mechanism of decarboxylation by 2,3-dihydroxybenzoic acid decarboxylase, chemical modification studies were carried out. Specific modification of the amino acid residues with diethylpyrocarbonate, N-bromosuccinimide and N-ethylmaleiimide revealed that at least one residue each of histidine, tryptophan and cysteine were essential for the activity. Various substrate analogs which were potential inhibitors significantly protected the enzyme against inactivation. The modification of residues at low concentration of the reagents and the protection experiments suggested that these amino acid residues might be present at the active site. Studies also suggested that the carboxyl and ortho-hydroxyl groups of the substrate are essential for interaction with the enzyme.

Estimation of signals in colored non gaussian noise based on Gaussian Mixture models

Non-Gaussianity of signals/noise often results in significant performance degradation for systems, which are designed using the Gaussian assumption. So non-Gaussian signals/noise require a different modelling and processing approach. In this paper, we discuss a new Bayesian estimation technique for non-Gaussian signals corrupted by colored non Gaussian noise. The method is based on using zero mean finite Gaussian Mixture Models (GMMs) for signal and noise. The estimation is done using an adaptive non-causal nonlinear filtering technique. The method involves deriving an estimator in terms of the GMM parameters, which are in turn estimated using the EM algorithm. The proposed filter is of finite length and offers computational feasibility. The simulations show that the proposed method gives a significant improvement compared to the linear filter for a wide variety of noise conditions, including impulsive noise. We also claim that the estimation of signal using the correlation with past and future samples leads to reduced mean squared error as compared to signal estimation based on past samples only.