A uniform white-noise model for fixed-point roundoff errors in digital systems

Fixed-point roundoff noise in digital implementation of linear systems arises due to overflow, quantization of coefficients and input signals, and arithmetical errors. In uniform white-noise models, the last two types of roundoff errors are regarded as uniformly distributed independent random vectors on cubes of suitable size. For input signal quantization errors, the heuristic model is justified by a quantization theorem, which cannot be directly applied to arithmetical errors due to the complicated input-dependence of errors. The complete uniform white-noise model is shown to be valid in the sense of weak convergence of probabilistic measures as the lattice step tends to zero if the matrices of realization of the system in the state space satisfy certain nonresonance conditions and the finite-dimensional distributions of the input signal are absolutely continuous.

Polyspecific malaria antibodies present at the time of infection inhibit the development of immunity to malaria but antibodies specific for the malaria merozoite surface protein, MSP1, facilitate immunity

Serum taken from mice immune to malaria as a result of infection and drug cure, or from mice immunized with a recombinant form of the merozoite surface protein, MSP1, can provide passive protection of recipient mice against the lethal parasite, Plasmodium yoelii YM. However, recipients of MSP1-immune serum go on to develop long-term immunity, whereas recipients of serum from mice naturally immune to malaria rapidly lose their resistance to infection. We demonstrate that 'infection/cure' serum suppresses the development of both antibody and cell-mediated parasite-specific responses in recipients, whereas these develop in recipients of MSP1-specific antibodies. These data have profound implications for our understanding of the development of malaria immunity in babies who passively acquire antibodies from their mothers.

Finite difference time domain (FDTD) method for modeling the effect of switched gradients on the human body in MRI

Numerical modeling of the eddy currents induced in the human body by the pulsed field gradients in MRI presents a difficult computational problem. It requires an efficient and accurate computational method for high spatial resolution analyses with a relatively low input frequency. In this article, a new technique is described which allows the finite difference time domain (FDTD) method to be efficiently applied over a very large frequency range, including low frequencies. This is not the case in conventional FDTD-based methods. A method of implementing streamline gradients in FDTD is presented, as well as comparative analyses which show that the correct source injection in the FDTD simulation plays a crucial rule in obtaining accurate solutions. In particular, making use of the derivative of the input source waveform is shown to provide distinct benefits in accuracy over direct source injection. In the method, no alterations to the properties of either the source or the transmission media are required. The method is essentially frequency independent and the source injection method has been verified against examples with analytical solutions. Results are presented showing the spatial distribution of gradient-induced electric fields and eddy currents in a complete body model.

Control of ovulation with a GnRH agonist after superstimulation of follicular growth in buffalo: fertilization and embryo recovery

The potential to use a GnRH agonist bioimplant and injection of exogenous LH to control the time of ovulation in a multiple ovulation and embryo transfer (MOET) protocol was examined in buffalo. Mixed-parity buffalo (Bubalus bubalis; 4-15-year-old; 529 13 kg LW) were randomly assigned to one of five groups (n = 6): Group 1, conventional MOET protocol; Group 2, conventional MOET with 12 It delay in injection of PGF(2alpha); Group 3, implanted with GnRH agonist to block the pre-ovulatory surge release of LH; Group 4, implanted with GnRH agonist and injected with exogenous LH (Lutropin(R), 25 mg) 24 h after 4 days of superstimulation with FSH; Group 5, implanted with GnRH agonist and injected with LH 36 h after superstimulation with FSH. Ovarian follicular growth in all buffaloes was stimulated by treatment with FSH (Folltropin-V(R), 200 mg) administered over 4 days, and was monitored by ovarian ultrasonography. At the time of estrus, the number of follicles greater than or equal to8 mm. was greater (P < 0.05) for buffaloes in Group 2 (12.8) than for buffaloes in Groups 1 (8.5), 3 (7.3), 4 (6.1) and 5 (6.8), which did not differ. All buffaloes were mated by AI after spontaneous (Groups 1-3) or induced (Groups 4 and 5) ovulation. The respective number of buffalo that ovulated, number of corpora lutea, ovulation rate (%), and embryos + oocytes recovered were: Group 1 (2, 1.8 +/- 1.6, 18.0 +/- 13.6, 0.2 +/- 0.2); Group 2 (4, 6.1 +/- 2.9, 40.5 +/- 17.5, 3.7 +/- 2.1); Group 3 (0, 0, 0, 0); Group 4 (6, 4.3 +/- 1.2, 69.3 +/- 14.2, 2.0 +/- 0.9); and Group 5 (1, 2.5 +/- 2.5, 15.5 +/- 15.5, 2.1 +/- 2.1). All buffaloes in Group 4 ovulated after injection of LH and had a relatively high ovulation rate (69%) and embryo recovery (46%). It has been shown that the GnRH agonist-LH protocol can be used to improve the efficiency of MOET in buffalo. (C) 2002 Elsevier Science Inc. All rights reserved.

Long-range automaton models of earthquakes: Power-law accelerations, correlation evolution, and mode-switching

We introduce a conceptual model for the in-plane physics of an earthquake fault. The model employs cellular automaton techniques to simulate tectonic loading, earthquake rupture, and strain redistribution. The impact of a hypothetical crustal elastodynamic Green's function is approximated by a long-range strain redistribution law with a r(-p) dependance. We investigate the influence of the effective elastodynamic interaction range upon the dynamical behaviour of the model by conducting experiments with different values of the exponent (p). The results indicate that this model has two distinct, stable modes of behaviour. The first mode produces a characteristic earthquake distribution with moderate to large events preceeded by an interval of time in which the rate of energy release accelerates. A correlation function analysis reveals that accelerating sequences are associated with a systematic, global evolution of strain energy correlations within the system. The second stable mode produces Gutenberg-Richter statistics, with near-linear energy release and no significant global correlation evolution. A model with effectively short-range interactions preferentially displays Gutenberg-Richter behaviour. However, models with long-range interactions appear to switch between the characteristic and GR modes. As the range of elastodynamic interactions is increased, characteristic behaviour begins to dominate GR behaviour. These models demonstrate that evolution of strain energy correlations may occur within systems with a fixed elastodynamic interaction range. Supposing that similar mode-switching dynamical behaviour occurs within earthquake faults then intermediate-term forecasting of large earthquakes may be feasible for some earthquakes but not for others, in alignment with certain empirical seismological observations. Further numerical investigation of dynamical models of this type may lead to advances in earthquake forecasting research and theoretical seismology.

Evolution of additive and nonadditive genetic variance in development time along a cline in Drosophila serrata

Latitudinal clines provide natural systems that may allow the effect of natural selection on the genetic variance to be determined. Ten clinal populations of Drosophila serrata collected from the eastern coast of Australia were used to examine clinal patterns in the trait mean and genetic variance of the life-history trait egg-to-adult development time. Development time significantly lengthened from tropical areas to temperate areas. The additive genetic variance for development time in each population was not associated with latitude but was associated with the population mean development time. Additive genetic variance tended to be larger in populations with more extreme development times and appeared to be consistent with allele frequency change. In contrast, the nonadditive genetic variance was not associated with the population mean but was associated with latitude. Levels of nonadditive genetic variance were greatest in the region of the cline where the gradient in the change in mean was greatest, consistent with Barton's (1999) conjecture that the generation of linkage disequilibrium may become an important component of the genetic variance in systems with a spatially varying optimum.

Structure of the gut contents of Trichogramma australicum Girault (Hymenoptera : Trichogrammatidae) larvae fixed in situ in eggs of its host Helicoverpa armigera (Hubner) (Lepidoptera : Noctuidae)

Trichogramma australicum larvae develop most rapidly in younger eggs of its host, the pest lepidopteran Helicoverpa armigera . To establish how the developmental stage of the host affects the diet of T. australicum , larvae were fixed in situ in eggs of H. armigera of different ages and the structure of the egg contents and parasitoid gut contents examined histologically. Larvae feeding on newly laid host eggs contain primarily yolk particles in their gut, while larvae feeding on older hosts contain necrotic cells and yolk particles. The gut of T. australicum larvae does not contain organised tissue remnants, indicating that larvae feed primarily by sucking food into their pharynx and feed best on a mixture of particulate semisolids in a liquid matrix. Secretory structures of T. australicum larvae that could be involved in modifying the host environment were examined. The hindgut is modified to form an anal vesicle with a number of attributes suggesting that it may be a specialised secretory structure. The paired salivary glands open to the exterior via a common duct.

The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

A new method for analysing the equilibrium and time-dependent behaviour of Markovian models

Many large-scale stochastic systems, such as telecommunications networks, can be modelled using a continuous-time Markov chain. However, it is frequently the case that a satisfactory analysis of their time-dependent, or even equilibrium, behaviour is impossible. In this paper, we propose a new method of analyzing Markovian models, whereby the existing transition structure is replaced by a more amenable one. Using rates of transition given by the equilibrium expected rates of the corresponding transitions of the original chain, we are able to approximate its behaviour. We present two formulations of the idea of expected rates. The first provides a method for analysing time-dependent behaviour, while the second provides a highly accurate means of analysing equilibrium behaviour. We shall illustrate our approach with reference to a variety of models, giving particular attention to queueing and loss networks. (C) 2003 Elsevier Ltd. All rights reserved.

The variety of variables in automated real-time refinement

The refinement calculus is a well-established theory for deriving program code from specifications. Recent research has extended the theory to handle timing requirements, as well as functional ones, and we have developed an interactive programming tool based on these extensions. Through a number of case studies completed using the tool, this paper explains how the tool helps the programmer by supporting the many forms of variables needed in the theory. These include simple state variables as in the untimed calculus, trace variables that model the evolution of properties over time, auxiliary variables that exist only to support formal reasoning, subroutine parameters, and variables shared between parallel processes.