First observation of yrast band in odd-odd162Lu

High spin states of the odd-odd¹⁶²Lu nucleus have been studied via¹⁴⁷Sm(¹⁹F,4nγ)¹⁶²Lu reaction at 95 MeV beam energy. Level scheme for yrast band based onπ[h_11/2 v[i_13/2] quasiparticle configuration was established up to I ^π = (23^?) for the first time. This band shows the signature inversion in energy before backbending generally appeared in this mass region. It is stressed that the signature splitting in¹⁶²Lu is larger than that in the¹⁶⁰Tm nucleus.     

A class of polynomial variable metric algorithms for linear optimization

In the paper, the behaviour of interior point algorithms is analyzed by using a variable metric method approach. A class of polynomial variable metric algorithms is given achieving O ((n/β)L) iterations for solving a canonical form linear optimization problem with respect to a wide class of Riemannian metrics, wheren is the number of dimensions and β a fixed value. It is shown that the vector fields of several interior point algorithms for linear optimization is the negative Riemannian gradient vector field of a linear a potential or a logarithmic barrier function for suitable Riemannian metrics. Research Partially supported by the Hungarian National Research Foundation, Grant Nos. OTKA-T016413 and OTKA-2116.     

Optimization for pattern classification using biased random search techniques

We demonstrate how optimization problems arise in the field of pattern classification, in particular in using piecewise-linear classification and classification based on an optimal linear separator. We motivate the need in this area for a general purpose optimization approach. We discuss ALOPEX, a biased random search approach, from the point of view of this need. While ALOPEX itself failed to fulfil our need, a newly-introduced generalization of it (iterated ALOPEX) was found to be appropriate for the optimization problems of our particular concern. We conclude the paper with a brief critical evaluation of this approach as compared to our original aims.     

Bifurcations in the growth process of a vortex sheet in rotating superfluid

Vortex-sheet growth is considered. Broken symmetry bifurcations are found in the growth process. The collective elasticity theory for a well-developed vortex sheet is presented, which is similar to that of smectic liquid crystals. The bifurcations in the limit of a much folded vortex sheet correspond to the Helfrich instability in smectics and cholesterics.     

Application of enzyme-field effect transistor sensor arrays as detectors in a flow-injection analysis system for simultaneous monitoring of medium components. Part II. Monitoring of cultivation processes

Glucose, maltose, sucrose, lactose, ethanol and urea concentrations were monitored simultaneously during the cultivation of Escherichia coli and Saccharomyces cerevisiae by means of enzyme field effect transistors (EnFETs) applying glucose dehydrogenase (GDH), maltase (MAL)/GDH, invertase (INV)/GDH, β-galactosidase (β-GAL)/galactosedehydrogenase (GALDH), alcoholdehydrogenase (ADH)/aldehydedehydrogenase (ALDH), and urease. These enzymes were (co)immobilized on the pH sensitive gates of an eight-FET array. The FET array was integrated in a commercial FIA system.     

Low-order modeling and dynamic characterization of rapid thermal processing

A low-order model of rapid thermal processing (RTP) of semiconductor wafers is derived. The first-principles nonlinear model describes the static and dynamic thermal behavior of a wafer with approximate spatial temperature uniformity undergoing rapid heating and cooling in a multilamp RTP chamber. The model is verified experimentally for a range of operating temperatures from 400° C to 900° C and pressures of 1 Torr and 1 atmosphere in an inert N₂ environment. Theoretical predictions suggest model validity over a still wider range of operating conditions. One advantage of the low-order model over previous high-order and statistical models is that the proposed model contains a small number of fundamental parameters and functions that, if necessary, are easily identifiable. Furthermore, because of reduced computational complexity, the low-order model can be used in real-time predictive applications including signal processing and process control design. In studying and verifying the model, the dynamic behavior of a semiconductor wafer undergoing rapid temperature changes is characterized. Close comparison between theory and experiment in terms of the wafer eigenvalue and dc gain is demonstrated; the strong nonlinear effects of temperature are shown. Convective heat transfer losses are also examined and are shown to increase with radial position on the wafer.