Minimum-Cost Checking Using Imperfect Information

The article of record as published may be found at https://doi.org/10.1287/mnsc.13.7.454An event takes place at time t, a discrete random variable with known probability function. At unit intervals of time, a measurement x is observed which yields information about the event; x is a random variable, with a known probability density function being dependent upon whether or not the event has yet occurred. After each observation, a decision is made that the event has or has not yet occurred. The latter decision implies waiting for the next measurement. The former decision, if correct, ends the procedure. If incorrect, this fact is incorporated, and the procedure continues. A decision cost structure is assumed that assigns: (1) a fixed (false alarm) cost to deciding the event has occurred when, in fact, it has not; (2) a (time late) cost proportional to the time between the occurrence of the event and the decision that it has occurred. The minimum-expected-cost decision strategy and the minimum cost thus obtained are derived by means of dynamic programming

Multiple attribute scenarios, bounded probabilities, and threats of nuclear theft

A method is presented for developing descriptions of future scenarios and using expert judgment to assess bounds on the probabilities of these scenarios. Multiple attributes are used to describe the important features of the scenarios, and the scenarios are defined as collections of different possible levels of the attributes. Experts assess either numerical values or bounds on various unconditional and conditional probabilities for different attribute levels. These are used to establish constraints for a series of linear programs which are solved to determine the highest and lowest possible probabilities for each scenario. An application is presented to the assessment of potential threats against nuclear material safeguards systems.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/23794/1/0000032.pd

A Decision Analytic Approach to Reliability-Based Design Optimization

Abstract Reliability-based design optimization is concerned with designing a product to optimize an objective function given uncertainties about whether various design constraints will be satisfied. However, the widespread practice of formulating such problems as chance-constrained programs can lead to misleading solutions. While a decision analytic approach would avoid this undesirable result, many engineers find it difficult to determine the utility functions required for a traditional decision analysis. This paper presents an alternative decision analytic formulation which, though implicitly using utility functions, is more closely related to probability maximization formulations with which engineers are comfortable and skilled. This result combines the rigor of decision analysis with the convenience of existing optimization approaches

Ideal spatial radiotherapy dose distributions subject to positional uncertainties

In radiotherapy a common method used to compensate for patient setup error and organ motion is to enlarge the clinical target volume (CTV) by a ‘margin’ to produce a ‘planning target volume’ (PTV). Using weighted power loss functions as a measure of performance for a treatment plan, a simple method can be developed to calculate the ideal spatial dose distribution (one that minimizes expected loss) when there is uncertainty. The spatial dose distribution is assumed to be invariant to the displacement of the internal structures and the whole patient. The results provide qualitative insights into the suitability of using a margin at all, and (if one is to be used) how to select a ‘good’ margin size. The common practice of raising the power parameters in the treatment loss function, in order to enforce target dose requirements, is shown to be potentially counter-productive. These results offer insights into desirable dose distributions and could be used, in conjunction with well-established inverse radiotherapy planning techniques, to produce dose distributions that are robust against uncertainties.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58093/2/pmb6_24_004.pd

Observations on the statistical nature of terrestrial irradiation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24505/1/0000782.pd

The probability distribution of terrestrial irradiation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24562/1/0000843.pd

A multi-organ transcriptome resource for the Burmese Python (Python molurus bivittatus)

<p>Abstract</p> <p>Background</p> <p>Snakes provide a unique vertebrate system for studying a diversity of extreme adaptations, including those related to development, metabolism, physiology, and venom. Despite their importance as research models, genomic resources for snakes are few. Among snakes, the Burmese python is the premier model for studying extremes of metabolic fluctuation and physiological remodelling. In this species, the consumption of large infrequent meals can induce a 40-fold increase in metabolic rate and more than a doubling in size of some organs. To provide a foundation for research utilizing the python, our aim was to assemble and annotate a transcriptome reference from the heart and liver. To accomplish this aim, we used the 454-FLX sequencing platform to collect sequence data from multiple cDNA libraries.</p> <p>Results</p> <p>We collected nearly 1 million 454 sequence reads, and assembled these into 37,245 contigs with a combined length of 13,409,006 bp. To identify known genes, these contigs were compared to chicken and lizard gene sets, and to all Genbank sequences. A total of 13,286 of these contigs were annotated based on similarity to known genes or Genbank sequences. We used gene ontology (GO) assignments to characterize the types of genes in this transcriptome resource. The raw data, transcript contig assembly, and transcript annotations are made available online for use by the broader research community.</p> <p>Conclusion</p> <p>These data should facilitate future studies using pythons and snakes in general, helping to further contribute to the utilization of snakes as a model evolutionary and physiological system. This sequence collection represents a major genomic resource for the Burmese python, and the large number of transcript sequences characterized should contribute to future research in this and other snake species.</p