Modeling expert problem solving in a game of chance: a Yahtzee© case study

Although developments on software agents have led to useful applications in automation of routine tasks such as electronic mail filtering, there is a scarcity of research that empirically evaluates the performance of a software agent versus that of a human reasoner, whose problem-solving capabilities the agent embodies. In the context of a game of a chance, namely Yahtzee©, we identified strategies deployed by expert human reasoners and developed a decision tree for agent development. This paper describes the computer implementation of the Yahtzee game as well as the software agent. It also presents a comparison of the performance of humans versus an automated agent. Results indicate that, in this context, the software agent embodies human expertise at a high level of fidelity.     

On the pH dependence of protein stability

This paper treats the free energy contribution of ionizable groups to protein stability. A method is presented for the calculation of the pH dependence of the denaturation free energy of a protein, which yields results that can be compared directly to experiment. The first step in the treatment is the determination of the average charges of all the ionizable groups in both the folded and unfolded protein. An expression due to Tanford then relates the pH dependence of the unfolding free energy to the difference in net charge between the two states. In order to determine absolute rather than relative unfolding free energies, it is necessary to calculate the total contribution of ionizable groups to protein stability at some reference pH. This is accomplished through a statistical mechanical treatment similar to the one used previously in the calculation of pKas. The treatment itself is rigorous but it suffers from uncertainties in the pKa calculations. Nevertheless, the overall shape of experimentally observed plots of denaturation free energy as a function of pH are reasonably well reproduced by the calculations. A number of general conclusions that arise from the analysis are: (1) knowledge of titration curves and/or effective pKa values of ionizable groups in proteins is sufficient to calculate the pH dependence of the denaturation free energy with respect to some reference pH value. However, in order to calculate the absolute contribution of ionizable groups to protein stability, it is necessary to also know the intrinsic pKa of each group. This is defined as the pKa of a group in a hypothetical state of the protein where all other groups are neutral. (2) Due to desolvation effects, ionizable groups destabilize proteins, although the effect is strongly dependent on pH. There are however, strongly stabilizing pairwise Coulombic interactions on the surface of proteins. (3) Plots of stability versus pH should not be interpreted in terms of a group whose pKa corresponds to the titration midpoint, but rather to a group with different pKas (that correspond approximately to the titration end points) in each state. (4) Any residual structure in the GuHCl-denatured state of proteins appears to have little effect on the pH dependence of stability. (5) pH-dependent unfolding, for example to the "molten globule" state, appears due to individual groups with anomalous pKas whose locations on the protein surface may determine the nature of the unfolded state.     

Rational Approach to Shear Design in Fiber-Reinforced Polymer-Prestressed Concrete Structures

The use of plasticity-based shear design methods for fiber-reinforced polymer (FRP) reinforced and prestressed concrete, as they are used at present, is inappropriate in the long term. In particular, the use of a plasticity-based truss model for shear behavior seems to be unsound, as reliance is placed on a predominantly elastic zone to redistribute stresses. A better approach to shear design would be to employ a model incorporating force equilibrium and compatibility of strains so that the elastic properties of the FRP could be included rationally. This would help to develop a real understanding and form a basis on which new guides and codes could be founded. In tandem with a more rational analytical approach, new configurations and types of FRP reinforcement need to be developed and researched so that these materials can be used more efficiently. An analytical approach to investigate the shear response of FRP-reinforced and -prestressed concrete has been developed, based on equilibrium and compatibility across a shear discontinuity. The analytical model presented here was developed in conjunction with an experimental program. Correlation between the analytical and experimental results is good and more accurate than the current guideline provisions for concrete beams containing FRP reinforcement.     

Parameter Sensitivity and Predictive Uncertainty in a New Water Quality Model, Q2

A new dynamic model of water quality, Q2, has recently been developed, capable of simulating large branched river systems. This paper describes the application of a generalized sensitivity analysis (GSA) to Q2 for single reaches of the River Thames in southern England. Focusing on the simulation of dissolved oxygen (DO) (since this may be regarded as a proxy for the overall health of a river); the GSA is used to identify key parameters controlling model behavior and provide a probabilistic procedure for model calibration. It is shown that, in the River Thames at least, it is more important to obtain high quality forcing functions than to obtain improved parameter estimates once approximate values have been estimated. Furthermore, there is a need to ensure reasonable simulation of a range of water quality determinands, since a focus only on DO increases predictive uncertainty in the DO simulations. The Q2 model has been applied here to the River Thames, but it has a broad utility for evaluating other systems in Europe and around the world.     

Quantitative assessment of vegetation structural attributes from aerial photography

Cover of vegetation understorey and overstorey was determined from aerial photography at 1:25 000 and 1:40 000 scales by a grid sampling technique. Models were developed relating values of aerial cover to field cover as determined by intensive field measurement. The influence of photo-scale, photo colour, the angle of the image, shadow, the hiatus between aerial and field sampling, crown width, crown height, proportion of dead trees, drought prior to aerial sampling, land type, previously cleared vegetation and incline on explanatory models was also examined. The only variables that could be clearly interpreted as influencing the models were vegetation height, photo-scale and land type. Only the latter two variables are useful for predictive models. The smaller the scale of photography the greater the exaggeration of the aerial image of tree crowns. This probable result of photo graininess would be most significant when tree crowns are small, an inverse surrogate of tree height. Two-phase models were developed for predicting basal area and biomass from aerial cover. In most instances models were successful for predicting overstorey and understorey cover and for predicting total basal area and biomass. The technique offers a powerful and cost-effective method of assessing vegetation change over long time periods in a way that no other technique can duplicate.     

Assessing the Effects of Acute Amyloid β Oligomer Exposure in the Rat

Alzheimer’s disease (AD) is the most common form of dementia, yet there are no therapeutic treatments that can either cure or delay its onset. Currently, the pathogenesis of AD is still uncertain, especially with respect to how the disease develops from a normal healthy brain. Amyloid β oligomers (AβO) are highly neurotoxic proteins and are considered potential initiators to the pathogenesis of AD. Rat brains were exposed to AβO via bilateral intracerebroventricular injections. Rats were then euthanized at either 1, 3, 7 or 21-days post surgery. Rat behavioural testing was performed using the Morris water maze and open field tests. Post-mortem brain tissue was immunolabelled for Aβ, microglia, and cholinergic neurons. Rats exposed to AβO showed deficits in spatial learning and anxiety-like behaviour. Acute positive staining for Aβ was only observed in the corpus callosum surrounding the lateral ventricles. AβO exposed rat brains also showed a delayed increase in activated microglia within the corpus callosum and a decreased number of cholinergic neurons within the basal forebrain. Acute exposure to AβO resulted in mild learning and memory impairments with co-concomitant white matter pathology within the corpus callosum and cholinergic cell loss within the basal forebrain. Results suggest that acute exposure to AβO in the rat may be a useful tool in assessing the early phases for the pathogenesis of AD.     

A yeast surface display platform for plant hormone receptors: Toward directed evolution of new biosensors

Small-molecule biosensors have major applications in biotechnology and medicine but remain difficult to engineer. Plant hormone receptors represent an attractive platform for engineering such biosensors because their chemically induced dimerization architectures naturally decouple small-molecule sensing and sensor actuation. Rapid biosensor engineering will require quantitative high-throughput screening methods. Here we develop a yeast surface display (YSD) platform for the PYR1/HAB1 abscisic acid sensor of Arabidopsis thaliana. We extensively optimized PYR1 surface display, HAB1 purification, and binding reaction conditions. Our system reproduces previous results with wild-type and engineered receptors, and a mathematical analysis of the PYR1/HAB1 system allows us to infer all binding constants. Critically, we find that a previously engineered PYR1 receptor with altered ligand specificity binds HAB1 with identical affinity, suggesting that substantial reengineering of the PYR1 binding pocket does not compromise sensor actuation. This YSD platform for A. thaliana PYR1/HAB1 will facilitate future biosensor engineering efforts.     

Isolation and characterization of the Saccharomyces cerevisiae DPP1 gene encoding diacylglycerol pyrophosphate phosphatase

Diacylglycerol pyrophosphate (DGPP) is involved in a putative novel lipid signaling pathway. DGPP phosphatase (DGPP phosphohydrolase) is a membrane-associated 34-kDa enzyme from Saccharomyces cerevisiae which catalyzes the dephosphorylation of DGPP to yield phosphatidate (PA) and then catalyzes the dephosphorylation of PA to yield diacylglycerol. Amino acid sequence information derived from DGPP phosphatase was used to identify and isolate the DPP1 (diacylglycerol pyrophosphate phosphatase) gene encoding the enzyme. Multicopy plasmids containing the DPP1 gene directed a 10-fold overexpression of DGPP phosphatase activity in S. cerevisiae. The heterologous expression of the S. cerevisiae DPP1 gene in Sf-9 insect cells resulted in a 500-fold overexpression of DGPP phosphatase activity over that expressed in wild-type S. cerevisiae. DGPP phosphatase possesses a Mg2+-independent PA phosphatase activity, and its expression correlated with the overexpression of DGPP phosphatase activity in S. cerevisiae and in insect cells. DGPP phosphatase was predicted to be an integral membrane protein with six transmembrane-spanning domains. The enzyme contains a novel phosphatase sequence motif found in a superfamily of phosphatases. A dpp1Delta mutant was constructed by deletion of the chromosomal copy of the DPP1 gene. The dpp1Delta mutant was viable and did not exhibit any obvious growth defects. The mutant was devoid of DGPP phosphatase activity and accumulated (4-fold) DGPP. Analysis of the mutant showed that the DPP1 gene was not responsible for all of the Mg2+-independent PA phosphatase activity in S. cerevisiae.