Bayesian mixture models for complex high dimensional count data in phage display experiments

Summary.  Phage display is a biological process that is used to screen random peptide libraries for ligands that bind to a target of interest with high affinity. On the basis of a count data set from an innovative multistage phage display experiment, we propose a class of Bayesian mixture models to cluster peptide counts into three groups that exhibit different display patterns across stages. Among the three groups, the investigators are particularly interested in that with an ascending display pattern in the counts, which implies that the peptides are likely to bind to the target with strong affinity. We apply a Bayesian false discovery rate approach to identify the peptides with the strongest affinity within the group. A list of peptides is obtained, among which important ones with meaningful functions are further validated by biologists. To examine the performance of the Bayesian model, we conduct a simulation study and obtain desirable results.     

Uses of imagination: The Russian Jewish past and its afterlives in the new and old worlds

David G. Roskies, The Jewish Search for a Usable Past (Bloomington: Indiana University Press, 1999, 217pp.);

Steven J. Zipperstein, Imagining Russian Jewry: Memory, History, Identity (Seattle: University of Washington Press, 1999, 139pp.);

Veniamin Lukin, Boris Khaimovich, 700 evreiskikh mestechek Urkrainy: istoricheskii putevoditel’. Vypusk 1 : Podoliya (A Historical Guide to 100 Ukrainian Jewish Shtetls, No. 1 : Podolia) (Jerusalem‐St Petersburg; Ezro, 1997, 256pp.)     

Inertia in Russian Politics

Despite changes in values and in formal and symbolic structures, real reform of the Russian political system is hampered by institutional inertia.     

Combinatorial design of a minimum cost transfer line

The problem of equipment selection for a production line is considered. Each piece of equipment, also called unit or block, performs a set of operations. All necessary operations of the line and all available blocks with their costs are known. The difficulty is to choose the most appropriate blocks and group them into (work)stations. There are some constraints that restrict the assignment of different blocks to the same station. Two combinatorial approaches for solving this problem are suggested. Both are based on a novel concept of locally feasible stations. The first approach combinatorially enumerates all feasible solutions, and the second reduces the problem to search for a maximum weight clique. A boolean linear program based on a set packing formulation is presented. Computer experiments with benchmark data are described. Their results show that the set packing model is competitive and can be used to solve real-life problems.     

Scalable Dynamic Bid Prices for Network Revenue Management in Continuous Time

This study develops an approximate optimal control problem to produce time‐dependent bid prices for the airline network revenue management problem. The main contributions of our study are the analysis of time‐dependent bid prices in continuous time and the use of splines to modify the problem into an approximate second‐order cone program (ASOCP). The spline representation of bid prices permits the number of variables to depend solely on the number of resources and not on the size of the booking horizon. The advantage of this framework is the ASOCP's scalability, which we demonstrate by solving for bid prices on an industrial‐sized network. The numerical experiments highlight the ASOCP's ability to solve industrial sized problems in seconds.     

Outsourcing Manufacturing: Secure Price‐Masking Mechanisms for Purchasing Component Parts

This paper develops and tests a privacy‐preserving business process that supports the selection of a contract manufacturer by an original equipment manufacturer (OEM), and the determination of whether the OEM or the chosen contract manufacturer will procure each of the components to be used in the manufacture of the OEM's branded product. Our “secure price‐masking (SPM)” technology contributes to procurement theory and practice in four significant ways: First, it preserves the privacy of every party's individual component prices. Second, SPM assures that the contract manufacturers will bid their own private purchase cost (i.e., not add a margin to their cost). Third, SPM is not invertible; i.e., none of the participants can “solve” for the private inputs of any other participant based on its own inputs and the outputs provided to it by SPM. Fourth, the posterior distribution of any other participant's private inputs is practically indistinguishable from its prior distribution. We also describe the results of a proof‐of‐concept implementation.     

Improvements to MCS algorithm for the maximum clique problem

In this paper we present improvements to one of the most recent and fastest branch-and-bound algorithm for the maximum clique problem—MCS algorithm by Tomita et al. (Proceedings of the 4th international conference on Algorithms and Computation, WALCOM’10, pp. 191–203, 2010). The suggested improvements include: incorporating of an efficient heuristic returning a high-quality initial solution, fast detection of clique vertices in a set of candidates, better initial colouring, and avoiding dynamic memory allocation. Our computational study shows some impressive results, mainly we have solved p_hat1000-3 benchmark instance which is intractable for MCS algorithm and got speedups of 7, 3000, and 13000 times for gen400_p0.9_55, gen400_p0.9_65, and gen400_p0.9_75 instances correspondingly.     

Statistical inference through AFT model for biotechnical systems

The objective of this paper is to model the phenomenon of degradation-to-failure for assemblies used for lumbar arthrodesis, starting from the analysis of their structure/geometry, the load applied and the kind of failure when several occur. An AFT model is proposed to model the joint effects of the applied load and the structural dimensions of the brand (namely length and diameter of the screw, presence of a connector or not) on the failure time due to a screw failure. The estimations of S–N curves and maximum permissible load (named critical load) values are provided as functions of the structural dimensions of the product. This allows comparisons of devices in terms of key factors determining product behavior and ageing under loading stress.     

Semiparametric Regression Estimation in Copula Models

We consider some methods of semiparametric regression estimation in multivariate models when the common distribution function is represented using a copula and the marginals satisfy a generalized regression model using a transfer functional. Sufficient conditions for consistency and joint asymptotic normality of the finite-dimensional parameters are obtained.