Optimal reactive power flow via the modified barrier Lagrangian function approach

A new approach called the Modified Barrier Lagrangian Function (MBLF) to solve the Optimal Reactive Power Flow problem is presented. In this approach, the inequality constraints are treated by the Modified Barrier Function (MBF) method, which has a finite convergence property: i.e. the optimal solution in the MBF method can actually be in the bound of the feasible set. Hence, the inequality constraints can be precisely equal to zero. Another property of the MBF method is that the barrier parameter does not need to be driven to zero to attain the solution. Therefore, the conditioning of the involved Hessian matrix is greatly enhanced. In order to show this, a comparative analysis of the numeric conditioning of the Hessian matrix of the MBLF approach, by the decomposition in singular values, is carried out. The feasibility of the proposed approach is also demonstrated with comparative tests to Interior Point Method (IPM) using various IEEE test systems and two networks derived from Brazilian generation/transmission system. The results show that the MBLF method is computationally more attractive than the IPM in terms of speed, number of iterations and numerical conditioning. (C) 2011 Elsevier B.V. All rights reserved.

Scrupocellaria (Bryozoa: Cheilostomata) from the Queensland coast, with the description of three new species

Among the Scrupocellaria species previously reported from Queensland, three are here redescribed - S. cervicornis, S. curvata and S. diadema; two other species, S. frondis and S. sinuosa, are recorded from the area for the first time; three new species, S. hamata n. sp., S. prolata n. sp. and S. peltata n. sp., are also described, and the remainder are discussed. The need for the re-examination of specimens assigned to this genus is highlighted. The geographic range of some Scrupocellaria species is far more limited than once thought.

A new Pennsylvanian Oriocrassatellinae from Brazil and the distribution of the genus Oriocrassatella in space and time

Oriocrassatella Etheridge Jr., 1907 is a long range crassatellid bivalve genus well recognized in shallow waters of epeiric seas throughout the upper part of Paleozoic. The first occurrences of this genus are recorded in the sedimentary successions of the Gondwana, both in Australia and South America. However, the geographic and age distribution of Oriocrassatella in Late Mississippian deposits of Australia and Argentina may indicate an earliest Visean or even a pre-Visean origin for the genus. Following its origin in Early Carboniferous a complex paleobiogeographic history from Southern to Northern Hemisphere took place in the Permian. During its initial dispersal phase from Late Carboniferous to the Early Permian the genus thrived in cold water environments associated to the Late Paleozoic Gondwana glaciation. Shallow-water bottoms of the warm waters of the central Gondwana fringe and Laurussia were colonized by Oriocrassatella only during Early Permian times when the genus became cosmopolitan. A new species of this genus is described herein, Oriocrassatella piauiensis n. sp., recorded from the Piaui Formation, Pennsylvanian of the Parnaiba Basin. This new species may represent an early adaptation to warm waters. However, based on available data, species of this genus seem to have adapted definitely to warm water environments probably related the Late Pennsylvanian interglacial phases. In these phases, climatic barrier were interrupted allowing the faunal interchange and larval dispersion following a South to North migration route through the eastern margins of Gondwana and the eastern Paleotethys.

A new simple class of superpotentials in SUSY quantum mechanics

In this work, we introduce the class of quantum mechanics superpotentials W(x) = g epsilon(x)x(2n) and study in detail the cases n = 0 and 1. The n = 0 superpotential is shown to lead to the known problem of two supersymmetrically related Dirac delta potentials (well and barrier). The n = 1 case results in the potentials V+/-(x) = g(2)x(4) +/- 2g|x|. For V-, we present the exact ground-state solution and study the excited states by a variational technique. Starting from the ground state of V- and using logarithmic perturbation theory, we study the ground states of V+ and also of V(x) = g(2)x(4) and compare the result obtained in this new way with other results for this last potential in the literature.

New molecular targets for PET and SPECT imaging in neurodegenerative diseases

The pathophysiology of neurodegenerative diseases (ND) such as Alzheimer's disease (AD) and Parkinson's disease (PD) has not yet been completely elucidated. However, in the past few years, there have been great knowledge advances about intra-and extracellular proteins that may display impaired function or expression in AD, PD and other ND, such as amyloid beta (AB), alpha-synuclein, tau protein and neuroinfiammatory markers. Recent developments in the imaging techniques of positron emission tomography (PET) and single photon emission computed tomography (SPECT) now allow the non-invasive tracking of such molecular targets of known relevance to ND in vivo. This article summarizes recent findings of PET and SPECT studies using these novel methods, and discusses their potential role in the field of drug development for ND as well as future clinical applications in regard to differential diagnosis of ND and monitoring of disease progression.

A fragment-based approach for the in silico prediction of blood-brain barrier permeation

Blood-brain barrier (BBB) permeation is an essential property for drugs that act in the central nervous system (CNS) for the treatment of human diseases, such as epilepsy, depression, Alzheimer's disease, Parkinson disease, schizophrenia, among others. In the present work, quantitative structure-property relationship (QSPR) studies were conducted for the development and validation of in silico models for the prediction of BBB permeation. The data set used has substantial chemical diversity and a relatively wide distribution of property values. The generated QSPR models showed good statistical parameters and were successfully employed for the prediction of a test set containing 48 compounds. The predictive models presented herein are useful in the identification, selection and design of new drug candidates having improved pharmacokinetic properties.