Sequential asymmetric auctions with endogenous participation

In this paper we suggest a model of sequential auctions with endogenous participation where each bidder conjectures about the number of participants at each round. Then, after learning his value, each bidder decides whether or not to participate in the auction. In the calculation of his expected value, each bidder uses his conjectures about the number of participants for each possible subgroup. In equilibrium, the conjectured probability is compatible with the probability of staying in the auction. In our model, players face participation costs, bidders may buy as many objects as they wish and they are allowed to drop out at any round. Bidders can drop out at any time, but they cannot come back to the auction. In particular we can determine the number of participants and expected prices in equilibrium. We show that for any bidding strategy, there exists such a probability of staying in the auction. For the case of stochastically independent objects, we show that in equilibrium every bidder who decides to continue submits a bid that is equal to his value at each round. When objects are stochastically identical, we are able to show that expected prices are decreasing.

Simulated-annealing-based genetic algorithm for modeling the optical constants of solids

We propose a simulated-annealing-based genetic algorithm for solving model parameter estimation problems. The algorithm incorporates advantages of both genetic algorithms and simulated annealing. Tests on computer-generated synthetic data that closely resemble optical constants of a metal were performed to compare the efficiency of plain genetic algorithms against the simulated-annealing-based genetic algorithms. These tests assess the ability of the algorithms to and the global minimum and the accuracy of values obtained for model parameters. Finally, the algorithm with the best performance is used to fit the model dielectric function to data for platinum and aluminum. (C) 1997 Optical Society of America.

Concurreny based transition refinement for the verification of distributed algorithms

We suggest a new notion of behaviour preserving transition refinement based on partial order semantics. This notion is called transition refinement. We introduced transition refinement for elementary (low-level) Petri Nets earlier. For modelling and verifying complex distributed algorithms, high-level (Algebraic) Petri nets are usually used. In this paper, we define transition refinement for Algebraic Petri Nets. This notion is more powerful than transition refinement for elementary Petri nets because it corresponds to the simultaneous refinement of several transitions in an elementary Petri net. Transition refinement is particularly suitable for refinement steps that increase the degree of distribution of an algorithm, e.g. when synchronous communication is replaced by asynchronous message passing. We study how to prove that a replacement of a transition is a transition refinement.

Improved case management and continued government investment are needed for malaria eradication in Henan Province, China

A two-year study of malaria control began in Henan Province following cuts in government malaria spending in 1993. Cost data were collected from all government levels and on treatment-seeking (diagnosis, treatment) from 12,325 suspected malaria cases in two endemic counties. The cost burden was found to fall mainly on patients, but using government infrastructure. Good stewardship requires continuing government investment, to at least current levels, along with improved case management. In mainland China, vivax malaria is a significant factor in poverty and economic underdevelopment.

Algebraic Bethe ansatz for integrable extended Hubbard models arising from supersymmetric group solutions

Integrable extended Hubbard models arising from symmetric group solutions are examined in the framework of the graded quantum inverse scattering method. The Bethe ansatz equations for all these models are derived by using the algebraic Bethe ansatz method.

Generation of eigenstates using the phase-estimation algorithm

The phase estimation algorithm is so named because it allows an estimation of the eigenvalues associated with an operator. However, it has been proposed that the algorithm can also be used to generate eigenstates. Here we extend this proposal for small quantum systems, identifying the conditions under which the phase-estimation algorithm can successfully generate eigenstates. We then propose an implementation scheme based on an ion trap quantum computer. This scheme allows us to illustrate two simple examples, one in which the algorithm effectively generates eigenstates, and one in which it does not.

Genotype-by-management interactions for grain yield and grain protein concentration of wheat

The magnitude of genotype-by-management (G x M) interactions for grain yield and grain protein concentration was examined in a multi-environment trial (MET) involving a diverse set of 272 advanced breeding lines from the Queensland wheat breeding program. The MET was structured as a series of management-regimes imposed at 3 sites for 2 years. The management-regimes were generated at each site-year as separate trials in which planting time, N fertiliser application rate, cropping history, and irrigation were manipulated. irrigation was used to simulate different rainfall regimes. From the combined analysis of variance, the G x M interaction variance components were found to be the largest source of G x E interaction variation for both grain yield (0.117 +/- 0.005 t(2) ha(-2); 49% of total G x E 0.238 +/- 0.028 t(2) ha(-2)) and grain protein concentration (0.445 +/- 0.020%(2); 82% of total G x E 0.546 +/- 0.057%(2)), and in both cases this source of variation was larger than the genotypic variance component (grain yield 0.068 +/- 0.014 t(2) ha(-2) and grain protein 0.203 +/- 0.026%(2)). The genotypic correlation between the traits varied considerably with management-regime, ranging from -0.98 to -0.31, with an estimate of 0.0 for one trial. Pattern analysis identified advanced breeding lines with improved grain yield and grain protein concentration relative to the cultivars Hartog, Sunco and Meteor. It is likely that a large component of the previously documented G x E interactions for grain yield of wheat in the northern grains region are in part a result of G x M interactions. The implications of the strong influence of G x M interactions for the conduct of wheat breeding METs in the northern region are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

A field trial of the effect of improved piglet management on smallholder sow productivity in the Philippines

We conducted a randomised, controlled field trial during 1998/1999 to evaluate the hypothesis that improved piglet management would improve the reproductive performance of smallholder sows. Simple changes were introduced into the treatment herds including the construction of a heated piglet-separation pen, vitamin injections, creep feeding and early weaning. The control herds were unchanged. Data were collected from all sows in each enrolled herd over two farrowings. We enrolled 176 sows, including 170 (96 treatment and 74 control) sows that remained throughout the study period. Significant differences in the reproductive performance of treatment and control sows were recorded for interfarrowing interval (median 176 versus 220 days), average number liveborn over 2 litters (11 versus 12), and average preweaning mortality over 2 litters (0 versus 37%). Based on a discount rate of 17%, the benefit-cost ratio of the treatment was 11.1 and 12.1 over 3 and 5 years, respectively. (C) 2001 Elsevier Science B.V. All rights reserved.

An algorithm to predict 3 ' intron splice sites in Plasmodium falciparum genomic sequences

A new algorithm, PfAGSS, for predicting 3' splice sites in Plasmodium falciparum genomic sequences is described. Application of this program to the published P. falciparum chromosome 2 and 3 data suggests that existing programs result in a high error rate in assigning 3' intron boundaries. (C) 2001 Elsevier Science B.V. All rights reserved.

An improved survival model of hypoxia/ischaemia in the piglet suitable for neuroprotection studies

The purpose of this study, was to develop a newborn piglet model of hypoxia/ischaemia which would better emulate the clinical situation in the asphyxiated human neonate and produce a consistent degree of histopathological injury following the insult. One-day-old piglets (n = 18) were anaesthetised with a mixture of propofol (10 mg/kg/h) and alfentinal (5,5.5 mug/kg/h) i.v. The piglets were intubated and ventilated. Physiological variables were monitored continuously. Hypoxia was induced by decreasing the inspired oxygen (FiO(2)) to 3-4% and adjusting FiO(2) to maintain the cerebral function monitor peak amplitude at less than or equal to5 muV. The duration of the mild insult was 20, min while the severe insult was 30 min which included 10 min where the blood pressure was allowed to fall below 70% of baseline. Control piglets (n=4 of 18) were subjected to the same protocol except for the hypoxic/ischaemic insult. The piglets were allowed to recover from anaesthesia then euthanased 72 It after the insult. The brains were perfusion-fixed, removed and embedded in paraffin. Coronal sections were stained by haematoxylin/eosin. A blinded observer examined the frontal and parietal cortex, hippocampus, basal ganglia, thalamus and cerebellum for the degree of damage. The total mean histology score for the five areas of the brain for the severe insult was 15.6 +/-4.4 (mean +/-S.D., n=7), whereas no damage was seen in either the mild insult (n=4) or control groups. This 'severe damage' model produces a consistent level of damage and will prove useful for examining potential neuroprotective therapies in the neonatal brain. (C) 2001 Elsevier Science BY. All rights reserved.

A simulated annealing algorithm for finding consensus sequences

Motivation: A consensus sequence for a family of related sequences is, as the name suggests, a sequence that captures the features common to most members of the family. Consensus sequences are important in various DNA sequencing applications and are a convenient way to characterize a family of molecules. Results: This paper describes a new algorithm for finding a consensus sequence, using the popular optimization method known as simulated annealing. Unlike the conventional approach of finding a consensus sequence by first forming a multiple sequence alignment, this algorithm searches for a sequence that minimises the sum of pairwise distances to each of the input sequences. The resulting consensus sequence can then be used to induce a multiple sequence alignment. The time required by the algorithm scales linearly with the number of input sequences and quadratically with the length of the consensus sequence. We present results demonstrating the high quality of the consensus sequences and alignments produced by the new algorithm. For comparison, we also present similar results obtained using ClustalW. The new algorithm outperforms ClustalW in many cases.