Broad-Band Coupling of High-Q Resonant Loads

Considering the method of broad-band coupling a series resonant RLC load to a resistive source using a uniform quarter-wave transmission-line inverter, it is shown that the 3-dB bandwidth of the network insertion loss reckoned with respect to a 0-dB loss attains a maximum for a particular value of the center frequency insertion loss in the range 0-3 dB. The center frequency Ioss and the corresponding value of the maximum 3-dB bandwidth are calculated for various loads and the results graphically presented.

Q-band beam waveguide

A report of the design, development ana periom~ance characteristics of a Q-band (8 nim) confoal. mned, aielectric lens beam waveguide is presented.

Q-Band beam wave-guide

Consideration is given to a 25-foot long Q-band (8 mm) confocal, zoned dielectric lens beam waveguide. Numerical expressions for the axial and radial fields are presented. The experimental set-up consisted of uniformly spaced zoned dielectric lenses, a transmitting horn and a receiving horn. It was found that: (1) the wave beam is reiterated when confocal, zoned dielectric lenses act as phase transformers in place of smooth surfaced transformers in beam waveguides; (2) the axial field is oscillatory near the source and the oscillation persists for about 25 cm from the source; (3) the oscillation disappears after one lens is used; (4) higher order modes with higher attenuation rates die out faster than fundamental modes; (5) phase transformers do not alter beam modes; (6) without any lens the beam cross-section broadens significantly in the Z-direction; (7) with one lens the beam exhibits the reiteration phenomenon; and (8) inserting a second lens on the axial and cross-sectional field distribution shows further the reiteration principle.

Clan-based evolutionary approach for solving control problems

This paper presents a dan-based evolutionary approach for solving control problems. Three selected control problems, viz. linear-quadratic, harvest, and push-cart problems, are solved using the proposed approach. Results are compared with those of the evolutionary programming (EP) approach. In most of the cases, the proposed approach is successful in obtaining (near) optimal solutions for these selected problems.

A vector measure for the intelligence of a question-answering (Q-A) system

The problem of quantification of intelligence of humans, and of intelligent systems, has been a challenging and controversial topic. IQ tests have been traditionally used to quantify human intelligence based on results of test designed by psychologists. It is in general very difficult to quantify intelligence. In this paper the authors consider a simple question-answering (Q-A) system and use this to quantify intelligence. The authors quantify intelligence as a vector with three components. The components consist of a measure of knowledge in asking questions, effectiveness of questions asked, and correctness of deduction. The authors formalize these parameters and have conducted experiments on humans to measure these parameters

High-Q, Ag-doped 123 resonator on unbuffered sapphire substrate

The microwave performance of an Ag-doped YBa2Cu3O7-x, thin-film X-band microstrip resonator on unbuffered sapphire substrate is reported. Q-values of 2400 and 1200 have been obtained al 15R and 77K, respectively, which correspond to R(s) values of 330 mu Omega and 680 mu Omega.

Two-timescale Q-learning Algorithms with an Application to Routing in Networks

We propose two variants of the Q-learning algorithm that (both) use two timescales. One of these updates Q-values of all feasible state-action pairs at each instant while the other updates Q-values of states with actions chosen according to the ‘current ’ randomized policy updates. A sketch of convergence of the algorithms is shown. Finally, numerical experiments using the proposed algorithms for routing on different network topologies are presented and performance comparisons with the regular Q-learning algorithm are shown.

Voltage stability : some reflections on Q-V characteristics of loads

Considering voltage stability as a static viability problem, this paper takes a particular concern of Q-V characteristics and reflects on certain notions that do not seem to have been explicitly mentioned or derived in the existing documented literature. The equations of Q-V characteristics are rederived in exactness, some salient points on the curve are discovered and analysed. The results of the analysis are illustrated through a case study

A touch of history and a peep into the future of the lipid-quinone known as coenzyme Q and ubiquinone

Coenzyme Q (ubiquinone), a fully substituted benzoquinone with polyprenyl side chain, participates in many cellular redox activities. Paradoxically it was discovered only in 1957, albeit being ubiquitous. It required a person, F. L. Crane, a place, Enzyme Institute, Madison, USA, and a time when D. E. Green was directing vigorous research on mitochondria. Located at the transition of 2-electron flavoproteins and 1-electron cytochrome carriers, it facilitates electron transfer through the elegant Q-cycle in mitochondria to reduce O-2 to H2O, and to H2O2, now a significant signal-transducing agent, as a minor activity in shunt pathway (animals) and alternative oxidase (plants). The ability to form Q-radical by losing an electron and a proton was ingeniously used by Mitchell to explain the formation of the proton gradient, considered the core of energy transduction, and also in acidification in vacuoles. Known to be a mobile membrane constituent (microsomes, plasma membrane and Golgi apparatus), allowing it to reach multiple sites, coenzyme Q is expected to have other activities. Coenzyme Q protects circulating lipoproteins being a better lipid antioxidant than even vitamin E. Binding to proteins such as QPS, QPN, QPC and uncoupling protein in mitochondria, QA and QB in the reaction centre in R. sphaeroides, and disulfide bond-forming protein in E. coli (possibly also in Golgi), coenzyme Q acquires selective functions. A characteristic of orally dosed coenzyme Q is its exclusive absorption into the liver, but not the other tissues. This enrichment of Q is accompanied by significant decrease of blood pressure and of serum cholesterol. Inhibition of formation of mevalonate, the common precursor in the branched isoprene pathway, by the minor product, coenzyme Q, decreases the major product, cholesterol. Relaxation of contracted arterial smooth muscle by a side-chain truncated product of coenzyme Q explains its effect of decreasing blood pressure. Extensive clinical studies carried out on oral supplements of coenzyine Q, initially by K. Folkers and Y. Yamamura and followed many others, revealed a large number of beneficial effects, significantly in cardiovascular diseases. Such a variety of effects by this lipid quinone cannot depend on redox activity alone. The fat-soluble vitamins (A, D, E and K) that bear structural relationship with coenzyme Q are known to be active in their polar forms. A vignette of modified forms of coenzyme Q taking active role in its multiple effects is emerging.

q-Gaussian based Smoothed Functional Algorithms for Stochastic Optimization

The q-Gaussian distribution results from maximizing certain generalizations of Shannon entropy under some constraints. The importance of q-Gaussian distributions stems from the fact that they exhibit power-law behavior, and also generalize Gaussian distributions. In this paper, we propose a Smoothed Functional (SF) scheme for gradient estimation using q-Gaussian distribution, and also propose an algorithm for optimization based on the above scheme. Convergence results of the algorithm are presented. Performance of the proposed algorithm is shown by simulation results on a queuing model.

A novel Q-learning algorithm with function approximation for constrained Markov decision processes

We present a novel multi-timescale Q-learning algorithm for average cost control in a Markov decision process subject to multiple inequality constraints. We formulate a relaxed version of this problem through the Lagrange multiplier method. Our algorithm is different from Q-learning in that it updates two parameters - a Q-value parameter and a policy parameter. The Q-value parameter is updated on a slower time scale as compared to the policy parameter. Whereas Q-learning with function approximation can diverge in some cases, our algorithm is seen to be convergent as a result of the aforementioned timescale separation. We show the results of experiments on a problem of constrained routing in a multistage queueing network. Our algorithm is seen to exhibit good performance and the various inequality constraints are seen to be satisfied upon convergence of the algorithm.