Enriched behavioral prediction equation and its impact on structured learning and the dynamic calculus

This theoretical note describes an expansion of the behavioral prediction equation, in line with the greater complexity encountered in models of structured learning theory (R. B. Cattell, 1996a). This presents learning theory with a vector substitute for the simpler scalar quantities by which traditional Pavlovian-Skinnerian models have hitherto been represented. Structured learning can be demonstrated by vector changes across a range of intrapersonal psychological variables (ability, personality, motivation, and state constructs). Its use with motivational dynamic trait measures (R. B. Cattell, 1985) should reveal new theoretical possibilities for scientifically monitoring change processes (dynamic calculus model; R. B. Cattell, 1996b), such as encountered within psycho therapeutic settings (R. B. Cattell, 1987). The enhanced behavioral prediction equation suggests that static conceptualizations of personality structure such as the Big Five model are less than optimal.

HPLC measurement of harderoporphyrin in the harderian glands of rodents as a biomarker for sub-lethal or chronic arsenic exposure

An improved HPLC method has been established for the measurement of harderoporphyrin (HP) in the harderian gland of rats and mice. Groups of female Wistar rats were given a single oral dose of sodium arsenite at 0, 0.5 or 5.0 mg As(III)/kg body weight, or a slurry of arsenic-contaminated soil at equivalent dose rates and the animals were sacrificed 96 h after dosing. A group of C57BL/6J female mice were chronically exposed to drinking water containing 500 mug As(V)/I of sodium arsenate ad libitum for over 2 years. Porphyrins were measured in the harderian glands of rats and mice. Our results suggest that HP and the alteration of the porphyrin profile in the harderian glands of rodents is a highly sensitive biomarker for both single sub-lethal and chronic arsenic exposure. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

Prediction of coal ash fusion temperatures with the F*A*C*T thermodynamic computer package

This paper outlines research on the processes taking place within the coal mineral matter at high temperatures and development of the relationship between ash fusion temperatures (AFT) and phase equilibria of the coal ash slags. A new thermodynamic database for the Al-Ca-Fe-O-Si system developed by the author was used in conjunction with the thermodynamic computer package F*A*C*T for these purposes. In addition, high temperature experimental studies were undertaken that involved heat treatment and quenching of the ash cones followed by the analyses using different techniques. The study provided new information on the processes taking place during AFT test and demonstrated the validity of the AFTs predictions with F*A*C*T. Examples of practical applications of the AFT prediction method are given in the paper. The results of this study are important not only for the AFT predictions, but also in general for the application of phase equilibrium science to the characterisation of the coal mineral matter interactions at high temperature. (C) 2002 Elsevier Science Ltd. All rights reserved.

Rumors and stable-cause attribution in prediction and behavior

Two stock-market simulation experiments investigated the notion that rumors that invoke stable-cause attributions spawn illusory associations and less regressive predictions and behavior. In Study 1, illusory perceptions of association and stable causation (rumors caused price changes on the day after they appeared) existed despite rigorous conditions of nonassociation (price changes were unrelated to rumors). Predictions (recent price trends will continue) and trading behavior (departures from a strong buy-low-sell-high strategy) were both anti-regressive. In Study 2, stability of attribution was manipulated via a computerized tutorial. Participants taught to view price-changes as caused by stable forces predicted less regressively and departed more from buy-low-sell-high trading patterns than those taught to perceive changes as caused by unstable forces. Results inform a social cognitive and decision theoretic understanding of rumor by integrating it with causal attribution, covariation detection, and prediction theory. (C) 2002 Elsevier Science (USA). All rights reserved.

Interactions among endocrinology, seasonal reproductive cycles and the nesting biology of the female green sea turtle

We collected data on plasma levels of testosterone+5a-dihydrotestosterone (T+DHT) and corticosterone (CORT) from adult female green sea turtles (Chelonia mydas) from southern Queensland during distinct stages of their reproductive cycle. Those females capable of breeding in a given year had elevated plasma steroid levels (T+DHT 0.91 +/- 0.08; CORT 1.05 +/- 0.29 ng/ml), associated with follicular development, until courtship began in October. At the beginning of the nesting season in November plasma levels of 2 CORT were related to when the female first nested (r(2) = 0.06; F = 10.45; P = 0.01). However, they were not correlated with the number of clutches a female laid in that season (F = 3.65; P = 0.08). We repeatedly sampled 23 turtles over the nesting season and profiled changes in steroids immediately following oviposition of each clutch. Levels of T+DHT (range 0.41-0.58 ng/ml) and CORT (range 2.13-2.81 ng/ml) were similar through the early stages of the nesting season and inter-nesting period, and declined to near basal levels (T+DHT 0.37 +/- 0.03 and CORT 1.85 +/- ng/ml) following the last clutch for the season. Steroid hormone levels were also low (T+DHT 0.38 +/- 0.16; CORT 0.46 +/- 0.21 ng/ml) in four independent post-breeding (atretic) females; samples for these females were taken at a time when body condition was presumably at the lowest for the season. Subtle changes in the nesting environment, such as variation in nesting habitat or the time of night that nesting occurred, were associated with a small and slow CORT increase. We suggest CORT is increased in nesting females to assist in lipid transfer to prepare the ovarian follicles and/or the reproductive organs for ovulation.

The prediction of sharkskin instability observed during film blowing

The characteristics of sharkskin surface instability for linear low density polyethylene are studied as a function of film blowing processing conditions. By means of scanning electron microscopy and surface profilometry, is it found that for the standard industrial die geometry studied, sharkskin only occurs on the inside of the film bubble. Previous work suggests that this instability may be due to critical extensional stress levels at the exit of the die. Isothermal integral viscoelastic simulations of the annular extrusion process are reported, and confirm that the extensional stress at the die exit is large enough to cause local melt rupture. However the extensional stress level at the outer die wall predicts melt rupture of the outside bubble surface also, which contradicts the experimental findings. A significant temperature gradient is expected to exist across the die gap at the exit of the die, due to the external heating of the die and the low conductivity, of the polymer melt. It is shown that a gradient of 20 degreesC is required to cause sharkskin to only appear on the inner bubble surface.

Estimation of total body water from bioelectrical impedance analysis in patients with pancreatic cancer - agreement between three methods of prediction

Introduction Bioelectrical impedance analysis (BIA) is a useful field measure to estimate total body water (TBW). No prediction formulae have been developed or validated against a reference method in patients with pancreatic cancer. The aim of this study was to assess the agreement between three prediction equations for the estimation of TBW in cachectic patients with pancreatic cancer. Methods Resistance was measured at frequencies of 50 and 200 kHz in 18 outpatients (10 males and eight females, age 70.2 +/- 11.8 years) with pancreatic cancer from two tertiary Australian hospitals. Three published prediction formulae were used to calculate TBW - TBWs developed in surgical patients, TBWca-uw and TBWca-nw developed in underweight and normal weight patients with end-stage cancer. Results There was no significant difference in the TBW estimated by the three prediction equations - TBWs 32.9 +/- 8.3 L, TBWca-nw 36.3 +/- 7.4 L, TBWca-uw 34.6 +/- 7.6 L. At a population level, there is agreement between prediction of TBW in patients with pancreatic cancer estimated from the three equations. The best combination of low bias and narrow limits of agreement was observed when TBW was estimated from the equation developed in the underweight cancer patients relative to the normal weight cancer patients. When no established BIA prediction equation exists, practitioners should utilize an equation developed in a population with similar critical characteristics such as diagnosis, weight loss, body mass index and/or age. Conclusions Further research is required to determine the accuracy of the BIA prediction technique against a reference method in patients with pancreatic cancer.

Polyethylene flow prediction with a differential multi-mode Pom-Pom model

We report the first steps of a collaborative project between the University of Queensland, Polyflow, Michelin, SK Chemicals, and RMIT University; on simulation, validation and application of a recently introduced constitutive model designed to describe branched polymers. Whereas much progress has been made on predicting the complex flow behaviour of many - in particular linear - polymers, it sometimes appears difficult to predict simultaneously shear thinning and extensional strain hardening behaviour using traditional constitutive models. Recently a new viscoelastic model based on molecular topology, was proposed by McLeish and Larson (1998). We explore the predictive power of a differential multi-mode version of the pom-pom model for the flow behaviour of two commercial polymer melts: a (long-chain branched) low-density polyethylene (LDPE) and a (linear) high-density polyethylene (HDPE). The model responses are compared to elongational recovery experiments published by Langouche and Debbaut (1999), and start-up of simple shear flow, stress relaxation after simple and reverse step strain experiments carried out in our laboratory.

The effect of sodium chloride supplementation on the milk production of grazing Holstein Friesian cows during summer and autumn in a humid sub-tropical environment

Two studies were conducted to examine the effects of including NaCl at various rates in grain-based supplements for Friesian cows grazing established, dominant (>90%), rainfed kikuyu (Pennisetum clandestinum cv. Common) pastures during summer and autumn in a humid sub-tropical environment. In study 1 (19 January-27 March 1998), 48 cows (36 multiparous, 12 primiparous; 27-96 days postpartum) were allocated to one of four groups based on genetic merit, milk production, liveweight (LW) and days postpartum. They were fed (2.7 kg dry matter (DM) per cow, twice-a-day) one of four isoenergetic and isonitrogenous barley grain-based concentrates containing NaCl at concentrations (% as-fed) of either 0 (SC1), 1.1 (SC2), 2.2 (SC3) or 3.3 (SC4). Maximum temperature humidity index (THImax) was greater than or equal to78 during 50% of the experimental period. Concentrate NaCl content had no effect (P>0.05) on daily milk yield or LW change but daily yields of 4% fat corrected milk (FCM), fat and protein were higher (P0.05) among treatments at 7.6+/-1.24 kg DM per cow. In study 2 (18 January 1999-1 March 1999), 48 cows (32 pluriparous, 16 primiparous: 32-160 days postpartum) were fed (2.7 kg DM per cow twice-a-day) one of two isoenergetic and isonitrogenous barley grain-based concentrates containing NaCl at concentrations (% as-fed) of 0 (control) or 2.2 (HSC). THImax was greater than or equal to78 during 34% of days in the experimental period. Yields of milk, FCM, fat and protein were lower (P0.05) by concentrate NaCl content. These studies indicate that NaCl supplementation can be beneficial in terms of milk production during warm, humid conditions as opposed to milder conditions. (C) 2002 Elsevier Science B.V. All rights reserved.

Stress correlation function evolution in lattice solid elasto-dynamic models of shear and fracture zones and earthquake prediction

It has been argued that power-law time-to-failure fits for cumulative Benioff strain and an evolution in size-frequency statistics in the lead-up to large earthquakes are evidence that the crust behaves as a Critical Point (CP) system. If so, intermediate-term earthquake prediction is possible. However, this hypothesis has not been proven. If the crust does behave as a CP system, stress correlation lengths should grow in the lead-up to large events through the action of small to moderate ruptures and drop sharply once a large event occurs. However this evolution in stress correlation lengths cannot be observed directly. Here we show, using the lattice solid model to describe discontinuous elasto-dynamic systems subjected to shear and compression, that it is for possible correlation lengths to exhibit CP-type evolution. In the case of a granular system subjected to shear, this evolution occurs in the lead-up to the largest event and is accompanied by an increasing rate of moderate-sized events and power-law acceleration of Benioff strain release. In the case of an intact sample system subjected to compression, the evolution occurs only after a mature fracture system has developed. The results support the existence of a physical mechanism for intermediate-term earthquake forecasting and suggest this mechanism is fault-system dependent. This offers an explanation of why accelerating Benioff strain release is not observed prior to all large earthquakes. The results prove the existence of an underlying evolution in discontinuous elasto-dynamic, systems which is capable of providing a basis for forecasting catastrophic failure and earthquakes.

Load-unload response ratio and accelerating moment/energy release critical region scaling and earthquake prediction

The main idea of the Load-Unload Response Ratio (LURR) is that when a system is stable, its response to loading corresponds to its response to unloading, whereas when the system is approaching an unstable state, the response to loading and unloading becomes quite different. High LURR values and observations of Accelerating Moment/Energy Release (AMR/AER) prior to large earthquakes have led different research groups to suggest intermediate-term earthquake prediction is possible and imply that the LURR and AMR/AER observations may have a similar physical origin. To study this possibility, we conducted a retrospective examination of several Australian and Chinese earthquakes with magnitudes ranging from 5.0 to 7.9, including Australia's deadly Newcastle earthquake and the devastating Tangshan earthquake. Both LURR values and best-fit power-law time-to-failure functions were computed using data within a range of distances from the epicenter. Like the best-fit power-law fits in AMR/AER, the LURR value was optimal using data within a certain epicentral distance implying a critical region for LURR. Furthermore, LURR critical region size scales with mainshock magnitude and is similar to the AMR/AER critical region size. These results suggest a common physical origin for both the AMR/AER and LURR observations. Further research may provide clues that yield an understanding of this mechanism and help lead to a solid foundation for intermediate-term earthquake prediction.

Prediction of Golgi Type II membrane proteins based on their transmembrane domains

Motivation: A major issue in cell biology today is how distinct intracellular regions of the cell, like the Golgi Apparatus, maintain their unique composition of proteins and lipids. The cell differentially separates Golgi resident proteins from proteins that move through the organelle to other subcellular destinations. We set out to determine if we could distinguish these two types of transmembrane proteins using computational approaches. Results: A new method has been developed to predict Golgi membrane proteins based on their transmembrane domains. To establish the prediction procedure, we took the hydrophobicity values and frequencies of different residues within the transmembrane domains into consideration. A simple linear discriminant function was developed with a small number of parameters derived from a dataset of Type II transmembrane proteins of known localization. This can discriminate between proteins destined for Golgi apparatus or other locations (post-Golgi) with a success rate of 89.3% or 85.2%, respectively on our redundancy-reduced data sets.