Comparison of BR and QR Eigenvalue Algorithms for Power System Small Signal Stability Analysis

The BR algorithm is a novel and efficient method to find all eigenvalues of upper Hessenberg matrices and has never been applied to eigenanalysis for power system small signal stability. This paper analyzes differences between the BR and the QR algorithms with performance comparison in terms of CPU time based on stopping criteria and storage requirement. The BR algorithm utilizes accelerating strategies to improve its performance when computing eigenvalues of narrowly banded, nearly tridiagonal upper Hessenberg matrices. These strategies significantly reduce the computation time at a reasonable level of precision. Compared with the QR algorithm, the BR algorithm requires fewer iteration steps and less storage space without depriving of appropriate precision in solving eigenvalue problems of large-scale power systems. Numerical examples demonstrate the efficiency of the BR algorithm in pursuing eigenanalysis tasks of 39-, 68-, 115-, 300-, and 600-bus systems. Experiment results suggest that the BR algorithm is a more efficient algorithm for large-scale power system small signal stability eigenanalysis.

Folding, calcium binding, and structural characterization of a concatemer of the first and second ligand-binding modules of the low-density lipoprotein receptor

The ligand-binding domain of the low-density lipoprotein (LDL) receptor is comprised of seven tandemly repeated ligand-binding modules, each being approximately 40 amino acids long and containing six conserved cysteine residues. We have expressed and characterized a concatemer of the first two modules (LB1 and LB2) of the human LDL receptor. Oxidative folding of the recombinant concatemer (rLB(1-2)), in the presence of calcium ions, gave a single dominant isomer with six disulfide bonds. Peptic cleavage of the short Linker region that connects the last cysteine residue of LB1 and the first cysteine residue of LB2 yielded two discrete fragments, thus excluding the presence of intermodule disulfide bonds. The N-terminal module, LB1, reacted with a conformation-specific monoclonal antibody (IgG-C7) made to LB1 in the native LDL receptor. From this, we concluded that the first module was correctly folded, with the same set of disulfide bonds as LB1 of the LDL receptor. The disulfide bond connections of LB2 were identified from mass spectral analysis of fragments formed by digestion of the C-terminal peptic fragment with elastase. These data showed that the disulfide bonds of LB2 connected Cys(I) and Cys(III), Cys(II) and Cys(V), and Cys(IV) and Cys(VI). This pattern is identical to that found for recombinant LB1 and LB2. The concatemer has two high-affinity calcium-binding sites, one per module. An analysis of the secondary chemical shifts of C alpha protons shows that the conformations of LB1 and LB2 in the concatemer are very similar to those of the individual modules, with no evidence for strong interactions between the two modules.

Comparative analysis of dendritic cell density and total number in commonly transplanted organs: morphometric estimation in normal mice

Dendritic cells (DC) are considered to be the major cell type responsible for induction of primary immune responses. While they have been shown to play a critical role in eliciting allosensitization via the direct pathway, there is evidence that maturational and/or activational heterogeneity between DC in different donor organs may be crucial to allograft outcome. Despite such an important perceived role for DC, no accurate estimates of their number in commonly transplanted organs have been reported. Therefore, leukocytes and DC were visualized and enumerated in cryostat sections of normal mouse (C57BL/10, B10.BR, C3H) liver, heart, kidney and pancreas by immunohistochemistry (CD45 and MHC class II staining, respectively). Total immunopositive cell number and MHC class II+ cell density (C57BL/10 mice only) were estimated using established morphometric techniques - the fractionator and disector principles, respectively. Liver contained considerably more leukocytes (similar to 5-20 x 10(6)) and DC (similar to 1-3 x 10(6)) than the other organs examined (pancreas: similar to 0.6 x 10(6) and similar to 0.35 x 10(6): heart: similar to 0.8 x 10(6) and similar to 0.4 x 10(6); kidney similar to 1.2 x 10(6) and 0.65 x 10(6), respectively). In liver, DC comprised a lower proportion of all leukocytes (similar to 15-25%) than in the other parenchymal organs examined (similar to 40-60%). Comparatively, DC density in C57BL/10 mice was heart > kidney > pancreas much greater than liver (similar to 6.6 x 10(6), 5 x 10(6), 4.5 x 10(6) and 1.1 x 10(6) cells/cm(3), respectively). When compared to previously published data on allograft survival, the results indicate that the absolute number of MHC class II+ DC present in a donor organ is a poor predictor of graft outcome. Survival of solid organ allografts is more closely related to the density of the donor DC network within the graft. (C) 2000 Elsevier Science B.V. All rights reserved.

Commentary: Using the convection-dispersion model and transit time density functions in the analysis of organ distribution kinetics

The convection-dispersion model and its extended form have been used to describe solute disposition in organs and to predict hepatic availabilities. A range of empirical transit-time density functions has also been used for a similar purpose. The use of the dispersion model with mixed boundary conditions and transit-time density functions has been queried recently by Hisaka and Sugiyanaa in this journal. We suggest that, consistent with soil science and chemical engineering literature, the mixed boundary conditions are appropriate providing concentrations are defined in terms of flux to ensure continuity at the boundaries and mass balance. It is suggested that the use of the inverse Gaussian or other functions as empirical transit-time densities is independent of any boundary condition consideration. The mixed boundary condition solutions of the convection-dispersion model are the easiest to use when linear kinetics applies. In contrast, the closed conditions are easier to apply in a numerical analysis of nonlinear disposition of solutes in organs. We therefore argue that the use of hepatic elimination models should be based on pragmatic considerations, giving emphasis to using the simplest or easiest solution that will give a sufficiently accurate prediction of hepatic pharmacokinetics for a particular application. (C) 2000 Wiley-Liss Inc. and the American Pharmaceutical Association J Pharm Sci 89:1579-1586, 2000.

An Economic Analysis of the Legal Concept of Trustees' Power of Investment

Authorised trustee status is a legal concept which has economic implications; one of the major implications is that it assists in the direction of investment funds into particular securities and areas of the economy. The concept of authorised trustee status, while attempting to achieve specific outcomes for the beneficiaries of trusts cannot be relied upon to secure these results. Economic analysis of the role of the trustee maintains that this role is one of portfolio manager; a role which is complex but which is explicable in terms of definable procedures and practices. The role of trustee as portfolio manager is one which requires greater financial knowledge than can be assumed is possessed by all trustees. The trustee as portfolio manager is required to maintain a review of decisions make under powers to invest trust assets. A solution to the problem of authorised trustee status is proposed. The solution takes two parts: the first is the adoption of the prudent person approach but with the codification of duties of the trustee and the explicit listing of the factors that a trustee should consider in using the investment powers. The second part of the proposed solution is to link the investment powers of trustees to the best practice features of securities advisers who are now licensed by a regulatory body, the Australian Securities and Investment Commission.

A comparison of low-storage strategies for spectral analysis in dissipative systems: filter diagonalisation in the Lanczos representation and harmonic inversion of the Chebychev-order-domain autocorrelation function

We compare the performance of two different low-storage filter diagonalisation (LSFD) strategies in the calculation of complex resonance energies of the HO2, radical. The first is carried out within a complex-symmetric Lanczos subspace representation [H. Zhang, S.C. Smith, Phys. Chem. Chem. Phys. 3 (2001) 2281]. The second involves harmonic inversion of a real autocorrelation function obtained via a damped Chebychev recursion [V.A. Mandelshtam, H.S. Taylor, J. Chem. Phys. 107 (1997) 6756]. We find that while the Chebychev approach has the advantage of utilizing real algebra in the time-consuming process of generating the vector recursion, the Lanczos, method (using complex vectors) requires fewer iterations, especially for low-energy part of the spectrum. The overall efficiency in calculating resonances for these two methods is comparable for this challenging system. (C) 2001 Elsevier Science B.V. All rights reserved.

Power of the joint segregation analysis method for testing mixed major-gene and polygene inheritance models of quantitative traits

Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.

Size and power properties of the AH test of evolutionary change

We investigate the size and power properties of the AH test of evolutionary change. This involves examining whether the size results are sensitive to both the number of individual frequencies estimated and the spectral shape adopted under the null hypothesis. The power tests examine whether the test has good power to detect shifts in both spectral position (variance) and spectral shape (autocovariance structure).

Density functional theory analysis of the influence of pore wall heterogeneity on adsorption in carbons

Density functional theory for adsorption in carbons is adapted here to incorporate a random distribution of pore wall thickness in the solid, and it is shown that the mean pore wall thickness is intimately related to the pore size distribution characteristics. For typical carbons the pore walls are estimated to comprise only about two graphene layers, and application of the modified density functional theory approach shows that the commonly used assumption of infinitely thick walls can severely affect the results for adsorption in small pores under both supercritical and subcritical conditions. Under supercritical conditions the Henry's law coefficient is overpredicted by as much as a factor of 2, while under subcritical conditions pore wall heterogeneity appears to modify transitions in small pores into a sequence of smaller ones corresponding to pores with different wall thicknesses. The results suggest the need to improve current pore size distrubution analysis methods to allow for pore wall heterogeneity. The density functional theory is further extended here to allow for interpore adsorbate interactions, and it appears that these interaction are negligible for small molecules such as nitrogen but significant for more strongly interacting heavier molecules such as butane, for which the traditional independent pore model may not be adequate.

Linkage and Association Analysis of Radiation Damage Repair Genes XRCC3 and XRCC5 with Nevus Density in Adolescent Twins

Previous studies have shown that a deficiency in DNA damage repair is associated with increased cancer risk, and exposure to UV radiation is a major risk factor for the development of malignant melanoma. High density of common nevi (moles) is a major risk factor for cutaneous melanoma. A nevus may result from a mutation in a single UV-exposed melanocyte which failed to repair DNA damage in one or more critical genes. XRCC3 and XRCC5 may have an effect on nevus count through their function as components of DNA repair processes that may be involved directly or indirectly in the repair of DNA damage due to UV radiation. This study aims to test the hypothesis that the frequency of flat or raised moles is associated with polymorphism at or near these DNA repair genes, and that certain alleles are associated with less efficient DNA repair, and greater nevus density. Twins were recruited from schools in south eastern Queensland and were examined close to their 12th birthday. Nurses examined each individual and counted all moles on the entire body surface. A 10cM genome scan of 274 families (642 individuals) was performed and microsatellite polymorphisms in XRCC3 and adjacent to XRCC5 were also typed. Linkage and association of nevus count to these loci were tested simultaneously using a structural-equation modeling approach implemented in MX. There is weak evidence for linkage of XRCC5 to a QTL influencing raised mole count, and also weak association. There is also weak evidence for association between flat mole count and XRCC3. No tests were significant after correction for testing multiple alleles, nor were any of the tests for total association significant. If variation in XRCC3 or XRCC5 influences UV sensitivity, and indirectly affects nevus density, then the effects are small.

Adsorption of supercritical fluids in non-porous and porous carbons: analysis of adsorbed phase volume and density

In this paper, we revisit the surface mass excess in adsorption studies and investigate the role of the volume of the adsorbed phase and its density in the analysis of supercritical gas adsorption in non-porous as well as microporous solids. For many supercritical fluids tested (krypton, argon, nitrogen, methane) on many different carbonaceous solids, it is found that the volume of the adsorbed phase is confined mostly to a geometrical volume having a thickness of up to a few molecular diameters. At high pressure the adsorbed phase density is also found to be very close to but never equal or greater than the liquid phase density. (C) 2003 Elsevier Science Ltd. All rights reserved.

Application of density functional theory to analysis of energetic heterogeneity and pore size distribution of activated carbons

A new approach based on the nonlocal density functional theory to determine pore size distribution (PSD) of activated carbons and energetic heterogeneity of the pore wall is proposed. The energetic heterogeneity is modeled with an energy distribution function (EDF), describing the distribution of solid-fluid potential well depth (this distribution is a Dirac delta function for an energetic homogeneous surface). The approach allows simultaneous determining of the PSD (assuming slit shape) and EDF from nitrogen or argon isotherms at their respective boiling points by using a set of local isotherms calculated for a range of pore widths and solid-fluid potential well depths. It is found that the structure of the pore wall surface significantly differs from that of graphitized carbon black. This could be attributed to defects in the crystalline structure of the surface, active oxide centers, finite size of the pore walls (in either wall thickness or pore length), and so forth. Those factors depend on the precursor and the process of carbonization and activation and hence provide a fingerprint for each adsorbent. The approach allows very accurate correlation of the experimental adsorption isotherm and leads to PSDs that are simpler and more realistic than those obtained with the original nonlocal density functional theory.

Exposing extinction risk analysis to pathogens: Is disease just another form of density dependence?

In the United States and several other countries., the development of population viability analyses (PVA) is a legal requirement of any species survival plan developed for threatened and endangered species. Despite the importance of pathogens in natural populations, little attention has been given to host-pathogen dynamics in PVA. To study the effect of infectious pathogens on extinction risk estimates generated from PVA, we review and synthesize the relevance of host-pathogen dynamics in analyses of extinction risk. We then develop a stochastic, density-dependent host-parasite model to investigate the effects of disease on the persistence of endangered populations. We show that this model converges on a Ricker model of density dependence under a suite of limiting assumptions, including. a high probability that epidemics will arrive and occur. Using this modeling framework, we then quantify: (1) dynamic differences between time series generated by disease and Ricker processes with the same parameters; (2) observed probabilities of quasi-extinction for populations exposed to disease or self-limitation; and (3) bias in probabilities of quasi-extinction estimated by density-independent PVAs when populations experience either form of density dependence. Our results suggest two generalities about the relationships among disease, PVA, and the management of endangered species. First, disease more strongly increases variability in host abundance and, thus, the probability of quasi-extinction, than does self-limitation. This result stems from the fact that the effects and the probability of occurrence of disease are both density dependent. Second, estimates of quasi-extinction are more often overly optimistic for populations experiencing disease than for those subject to self-limitation. Thus, although the results of density-independent PVAs may be relatively robust to some particular assumptions about density dependence, they are less robust when endangered populations are known to be susceptible to disease. If potential management actions involve manipulating pathogens, then it may be useful to. model disease explicitly.