Evolution of stress deficit and changing rates of seismicity in cellular automaton models of earthquake faults

We investigate the internal dynamics of two cellular automaton models with heterogeneous strength fields and differing nearest neighbour laws. One model is a crack-like automaton, transferring ail stress from a rupture zone to the surroundings. The other automaton is a partial stress drop automaton, transferring only a fraction of the stress within a rupture zone to the surroundings. To study evolution of stress, the mean spectral density. f(k(r)) of a stress deficit held is: examined prior to, and immediately following ruptures in both models. Both models display a power-law relationship between f(k(r)) and spatial wavenumber (k(r)) of the form f(k(r)) similar tok(r)(-beta). In the crack model, the evolution of stress deficit is consistent with cyclic approach to, and retreat from a critical state in which large events occur. The approach to criticality is driven by tectonic loading. Short-range stress transfer in the model does not affect the approach to criticality of broad regions in the model. The evolution of stress deficit in the partial stress drop model is consistent with small fluctuations about a mean state of high stress, behaviour indicative of a self-organised critical system. Despite statistics similar to natural earthquakes these simplified models lack a physical basis. physically motivated models of earthquakes also display dynamical complexity similar to that of a critical point system. Studies of dynamical complexity in physical models of earthquakes may lead to advancement towards a physical theory for earthquakes.

Stochastic structure and individual-tree growth models

The majority of past and current individual-tree growth modelling methodologies have failed to characterise and incorporate structured stochastic components. Rather, they have relied on deterministic predictions or have added an unstructured random component to predictions. In particular, spatial stochastic structure has been neglected, despite being present in most applications of individual-tree growth models. Spatial stochastic structure (also called spatial dependence or spatial autocorrelation) eventuates when spatial influences such as competition and micro-site effects are not fully captured in models. Temporal stochastic structure (also called temporal dependence or temporal autocorrelation) eventuates when a sequence of measurements is taken on an individual-tree over time, and variables explaining temporal variation in these measurements are not included in the model. Nested stochastic structure eventuates when measurements are combined across sampling units and differences among the sampling units are not fully captured in the model. This review examines spatial, temporal, and nested stochastic structure and instances where each has been characterised in the forest biometry and statistical literature. Methodologies for incorporating stochastic structure in growth model estimation and prediction are described. Benefits from incorporation of stochastic structure include valid statistical inference, improved estimation efficiency, and more realistic and theoretically sound predictions. It is proposed in this review that individual-tree modelling methodologies need to characterise and include structured stochasticity. Possibilities for future research are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

Prior calcium channel blockade and short-term survival following acute myocardial infarction

There is concern over the safety of calcium channel blockers (CCBs) in acute coronary disease. We sought to determine if patients taking calcium channel blockers (CCBs) at the time of admission with acute myocardial infarction (AMI) had a higher case-fatality compared with those taking beta-blockers or neither medication. Clinical and drug treatment variables at the time of hospital admission predictive of survival at 28 days were examined in a community-based registry of patients aged under 65 years admitted to hospital for suspected AMI in Perth, Australia, between 1984 and 1993. Among 7766 patients, 1291 (16.6%) were taking a CCB and 1259 (16.2%) a betablocker alone at hospital admission. Patients taking CCBs had a worse clinical profile than those taking a beta-blocker alone or neither drug (control group), and a higher unadjusted 28-day mortality (17.6% versus 9.3% and 11.1% respectively, both P < 0.001). There was no significant heterogeneity with respect to mortality between nifedipine, diltiazem, or verapamil when used alone, or with a beta-blocker. After adjustment for factors predictive of death at 28 days, patients taking a CCB were found not to have an excess chance of death compared with the control group (odds ratio [OR] 1.06, 95% confidence interval [CI]; 0.87, 1.30), whereas those taking a beta-blocker alone had a lower odds of death (OR 0.75, 95% CI; 0.59, 0.94). These results indicate that established calcium channel blockade is not associated with an excess risk of death following AMI once other differences between patients are taken into account, but neither does it have the survival advantage seen with prior beta-blocker therapy.

Long-term disability after first-ever stroke and related prognostic factors in the Perth Community Stroke Study, 1989-1990

Background and Purpose-Few reliable estimates of the long-term functional outcome after stroke are available. This population-based study aimed to describe disability, dependency, and related independent prognostic factors at 5 years after,a first-ever stroke in patients in Perth, Western Australia. Methods-All individuals with a suspected acute stroke who were resident in a geographically defined region (population, 138 708) of Perth, Western Australia, were registered prospectively and assessed according to standardized diagnostic criteria over a period of 18 months in 1989 to 1990. Patients were followed up prospectively at 4 and 12 months and 5 years after the index event. Results-There were 370 cases of first-ever stroke, and 277 patients survived to 30 days. Of these early survivors, 152 (55%) were alive at 5 years, and among those who were neither institutionalized (n=146) nor disabled (n=129) at the time of their stroke, 21 (14%) were institutionalized in a nursing home, and 47 (36%) were disabled. The most important predictors of death or disability at 5 years were increasing age, baseline disability defined by a Barthel Index score of <20/20 (odds ratio [OR], 6.3; 95% confidence interval [CI], 2.7 to 14), moderate hemiparesis (OR, 2.7. 95% CI, 1.1 to 6.2), severe hemiparesis (OR, 4.5; 95% CI, 1.1 to 19), and recurrent stroke (OR, 9.4; 95% CI, 3.0 to 30). A low level of activity before the stroke was a significant predictor of institutionalization, and subsequent recurrent stroke was a consistent, independent predictor of institutionalization, disability, and death or institutionalization, increasing the odds of each of these 3 adverse outcomes by 5- to 15-fold. Conclusions-Among 30-day survivors of first-ever stroke, about half survive 5 years; of survivors, one third remain disabled, and I in 7 are in permanent institutional care. The major modifiable predictors of poor long-term outcome are a low level of activity before the stroke and subsequent recurrent stroke. Efforts to increase physical activity among the elderly and to prevent recurrent stroke in survivors of a first stroke are likely to reduce the long-term burden of cerebrovascular disease.

Long-term quantification of the release of monomers from dental resin composites and a resin-modified glass ionomer cement

This study quantified the release of monomers from polymerized specimens of four commercially available resin composites and one glass ionomer cement immersed in water:ethanol solutions. Individual standard curves were prepared from five monomers: (1) triethylene glycol dimethacrylate (TEGDMA), (2) 2-hydroxy-ethyl methacrylate (HEMA), (3) urethane dimethacrylate (UDMA), (4) bisphenol A glycidyl dimethacrylate (BISGMA), and (5) bisphenol A. The concentration of the monomers was determined at Days 1, 7, 30, and 90 with the use of electrospray ionization/mass spectrometry. Data were expressed in mean mumol per mm(2) surface area of specimen and analyzed with Scheffe's test (P < 0.05). The following monomers were found in water: monomers (1) and (2) from Delton sealant, monomer (5) from ScotchBond Multipurpose Adhesive and Delton sealant, monomer (3) from Definite and monomer (4) from Fuji II LC, ScotchBond Multipurpose Adhesive, Synergy and Definite. All these monomers increased in concentration over time, with the exception of monomer (1) from Delton sealant. Monomers (3) and (5) were found in extracts of materials despite their absence from the manufacturer's published composition. All monomers were released in significantly higher concentrations in water:ethanol solutions than in water. The greatest release of monomers occurred in the first day. The effect of the measured concentrations of monomers (1-5) on human genes, cells, or tissues needs to be considered with the use of a biological model. (C) 2002 Wiley Periodicals, Inc.

Prediction of promiscuous peptides that bind HLA class I molecules

Promiscuous T-cell epitopes make ideal targets for vaccine development. We report here a computational system, multipred, for the prediction of peptide binding to the HLA-A2 supertype. It combines a novel representation of peptide/MHC interactions with a hidden Markov model as the prediction algorithm. multipred is both sensitive and specific, and demonstrates high accuracy of peptide-binding predictions for HLA-A*0201, *0204, and *0205 alleles, good accuracy for *0206 allele, and marginal accuracy for *0203 allele. multipred replaces earlier requirements for individual prediction models for each HLA allelic variant and simplifies computational aspects of peptide-binding prediction. Preliminary testing indicates that multipred can predict peptide binding to HLA-A2 supertype molecules with high accuracy, including those allelic variants for which no experimental binding data are currently available.

Methods for prediction of peptide binding to MHC molecules: A comparative study

Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.

Mortality and recurrent cardiac events after coronary artery bypass graft: long term outcomes in a population study

Objective: To determine 30 day mortality, long term survival, and recurrent cardiac events after coronary artery bypass graft (CABG) in a population. Design: Follow up study of patients prospectively entered on to a cardiothoracic surgical database. Record linkages were used to obtain data on readmissions and deaths. Patients: 8910 patients undergoing isolated first CABG between 1980 and 1993 in Western Australia. Main outcome measures: 30 day and long term survival, readmission for cardiac event (acute myocardial infarction, unstable angina, percutaneous transluminal coronary angioplasty or reoperative CABG). Results: There were 3072 deaths to mid 1999. 30 day and long term survival were significantly better in patients treated in the first five years than during the following decade. The age of the patients, proportion of female patients, and number of grafts increased over time. An urgent procedure (odds ratio 3.3), older age (9% per year) and female sex (odds ratio 1.5) were associated with increased risk for 30 day mortality, while age (7% per year) and a recent myocardial infarction (odds ratio 1.16) influenced long term survival. Internal mammary artery grafts were followed by better short and long term survival, though there was an obvious selection bias in favour of younger male patients. Conclusions: This study shows worsening crude mortality at 30 days after CABG from the mid 1980s, associated with the inclusion of higher risk patients. Older age, an acute myocardial infarction in the year before surgery, and the use of sephenous vein grafts only were associated with poorer long term survival and greater risk of a recurrent cardiac event. Female sex predicted recurrent events but not long term survival.

Long-term survival of women with breast cancer in New South Wales

Several long-term studies of breast cancer survival have shown continued excess mortality from breast cancer up to 20-40 years following treatment. The purpose of this report was to investigate temporal trends in long-term survival from breast cancer in all New South Wales (NSW) women. Breast cancer cases incident in 1972-1996 (54,228) were derived from the NSW Central Cancer Registry a population-based registry which began in 1972. All cases of breast cancer not known to be dead were matched against death records. The expected survival for NSW women was derived from published annual life tables. Relative survival analysis compared the survival of cancer cases with the age, sex and period matched mortality of the total population. Cases were considered alive at the end of 1996, except when known to be dead. Proportional hazards regression was employed to model survival on age, period and degree of spread at diagnosis. Survival at 5, 10, 15, 20 and 25 years of follow-up was 76 per cent, 65 per cent, 60 per cent, 57 per cent and 56 per cent. The annual hazard rate for excess mortality was 4.3 per cent in year 1, maximal at 6.5 per cent in year 3, declining to 4.7 per cent in year 5, 2.7 per cent in year 10, 1.4 per cent in year 15, 1.0 per cent for years 16-20, and 0.4 per cent for years 20-25 of follow-up. Relative survival was highest in 40-49 year-olds. Cases diagnosed most recently (1992-1996) had the highest survival, compared with cases diagnosed in previous periods. Five-year survival improved over time, especially from the late 1980s for women in the screening age group (50-69 years). Survival was highest for those with localised cancer at diagnosis: 88.4 per cent, 79.1 per cent, 74.6 per cent, 72.7 per cent and 72.8 per cent at 5, 10, 15, 20 and 25 years follow-up (excluding those aged greater than or equal to 70 years). There was no significant difference between the survival of the breast cancer cases and the general population at 20-25 years follow-up. Degree of spread was less predictive of survival 5-20 years after diagnosis, compared with 0-5 years after diagnosis, and was not significant at 20-25 years of follow-up. Relative survival from breast cancer in NSW women continues to decrease to 25 years after diagnosis, but there is little excess mortality after 15 years follow-up, especially for those with localised cancer at diagnosis, and the minimal excess mortality at 20-25 years of follow-up is not statistically significant. (C) 2002 Elsevier Science Ltd. All rights reserved.

Prediction of carbon monoxide in fires by conditional moment closure

Carbon monoxide is the chief killer in fires. Dangerous levels of CO can occur when reacting combustion gases are quenched by heat transfer, or by mixing of the fire plume in a cooled under- or overventilated upper layer. In this paper, carbon monoxide predictions for enclosure fires are modeled by the conditional moment closure (CMC) method and are compared with laboratory data. The modeled fire situation is a buoyant, turbulent, diffusion flame burning under a hood. The fire plume entrains fresh air, and the postflame gases are cooled considerably under the hood by conduction and radiation, emulating conditions which occur in enclosure fires and lead to the freezing of CO burnout. Predictions of CO in the cooled layer are presented in the context of a complete computational fluid dynamics solution of velocity, temperature, and major species concentrations. A range of underhood equivalence ratios, from rich to lean, are investigated. The CMC method predicts CO in very good agreement with data. In particular, CMC is able to correctly predict CO concentrations in lean cooled gases, showing its capability in conditions where reaction rates change considerably.