Adjoint operator approach to shape design for internal incompressible flows

The problem of determining the profile of a channel or duct that provides the maximum static pressure rise is solved. Incompressible, laminar flow governed by the steady state Navier-Stokes equations is assumed. Recent advances in computational resources and algorithms have made it possible to solve the direct problem of determining such a flow through a body of known geometry. It is possible to obtain a set of adjoint equations, the solution to which permits the calculation of the direction and relative magnitude of change in the diffuser profile that leads to a higher pressure rise. The solution to the adjoint problem can be shown to represent an artificially constructed flow. This interpretation provides a means to construct numerical solutions to the adjoint equations that do not compromise the fully viscous nature of the problem. The algorithmic and computational aspects of solving the adjoint equations are addressed. The form of these set of equations is similar but not identical to the Navier-Stokes equations. In particular some issues related to boundary conditions and stability are discussed

Foundations of Quantum Discord

This paper summarizes the basics of the notion of quantum discord and how it relates to other types of correlations in quantum physics. We take the fundamental information theoretic approach and illustrate our exposition with a number of simple examples.Comment: 3 pages, special issue edited by Diogo de Oliveira Soares Pinto et a

Development and evaluation of superconducting circuit elements

An approach to the application of high Tc ceramic superconductors to practical circuit elements was developed and demonstrated. This method, known as the rigid-conductor process (RCP), involves the combination of a pre-formed, sintered, and tested superconductor material with an appropriate, rigid substrate via an epoxy adhesive which also serves to encapsulate the element from the ambient environment. Emphasis was on the practical means to achieve functional, reliable, and reproducible components. Although all of the work described in this report involved a YBa2Cu3Osub(7-x) high Tc superconductor material, the techniques developed and conclusions reached are equally applicable to other high Tc materials

Studies of uncontrolled air traffic patterns, phase 1

The general aviation air traffic flow patterns at uncontrolled airports are investigated and analyzed and traffic pattern concepts are developed to minimize the midair collision hazard in uncontrolled airspace. An analytical approach to evaluate midair collision hazard probability as a function of traffic densities is established which is basically independent of path structure. Two methods of generating space-time interrelationships between terminal area aircraft are presented; one is a deterministic model to generate pseudorandom aircraft tracks, the other is a statistical model in preliminary form. Some hazard measures are presented for selected traffic densities. It is concluded that the probability of encountering a hazard should be minimized independently of any other considerations and that the number of encounters involving visible-avoidable aircraft should be maximized at the expense of encounters in other categories

Invariant quantum discord in qubit-qutrit systems under local dephasing

We investigate the dynamics of quantum discord and entanglement for a class of mixed qubit-qutrit states assuming that only the qutrit is under the action of a dephasing channel. We demonstrate that even though the entanglement in the qubit-qutrit state disappears in a finite time interval, partial coherence left in the system enables quantum discord to remain invariant throughout the whole time evolution

A Simple and Sensitive HPTLC Method for Simultaneous Determination of Metformin Hydrochloride and Sitagliptin Phosphate in Tablet Dosage Form

A simple, rapid, and precise high-performance thin-layer chromatographic (HPTLC) method for simultaneous estimation of two antidiabetic drugs, metformin hydrochloride and sitagliptin phosphate, in tablet dosage form has been developed and validated. Chromatography was performed on silica gel 60 F254 plates with butanol : water : glacial acetic acid (6 : 2 : 2, v/v/v) as mobile phase. This system gave a good resolution for metformin hydrochloride ( value of 0.35 ± 0.01) and sitagliptin phosphate ( value of 0.75 ± 0.01). Detection and quantification were carried out at 227 nm. The linear regression data for the calibration plot showed a good relationship with and 0.9991 for metformin hydrochloride and sitagliptin phosphate, respectively. The method was validated for precision and recovery. The limits of detection and quantification were 13.05 and 39.56 ng/μL for metformin hydrochloride and 2.65 and 8.03 ng/μL for sitagliptin phosphate, respectively. The amounts of the drugs in the marketed formulation were 99.86% and 98.91% for metformin hydrochloride and sitagliptin phosphate, respectively

Entropy Based Feature Selection For Multi-Relational Naïve Bayesian Classifier

Current industries data’s are stored in relation structures. In usual approach to mine these data, we often use to join several relations to form a single relation using foreign key links, which is known as flatten. Flatten may cause troubles such as time consuming, data redundancy and statistical skew on data. Hence, the critical issues arise that how to mine data directly on numerous relations. The solution of the given issue is the approach called multi-relational data mining (MRDM). Other issues are irrelevant or redundant attributes in a relation may not make contribution to classification accuracy. Thus, feature selection is an essential data pre- processing step in multi-relational data mining. By filtering out irrelevant or redundant features from relations for data mining, we improve classification accuracy, achieve good time performance, and improve comprehensibility of the models. We had proposed the entropy based feature selection method for Multi-relational Naïve Bayesian Classifier. We have use method InfoDist and Pearson’s Correlation parameters, which will be used to filter out irrelevant and redundant features from the multi-relational database and will enhance classification accuracy. We analyzed our algorithm over PKDD financial dataset and achieved the better accuracy compare to the existing features selection methods