Parameter estimation for the distribution of single cell lag times.

In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level. We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.

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Solving two production scheduling problems with sequence-dependent set-up times

In today’s competitive markets, the importance of goodscheduling strategies in manufacturing companies lead to theneed of developing efficient methods to solve complexscheduling problems.In this paper, we studied two production scheduling problemswith sequence-dependent setups times. The setup times areone of the most common complications in scheduling problems,and are usually associated with cleaning operations andchanging tools and shapes in machines.The first problem considered is a single-machine schedulingwith release dates, sequence-dependent setup times anddelivery times. The performance measure is the maximumlateness.The second problem is a job-shop scheduling problem withsequence-dependent setup times where the objective is tominimize the makespan.We present several priority dispatching rules for bothproblems, followed by a study of their performance. Finally,conclusions and directions of future research are presented.

Proton T1 relaxation times of metabolites in human occipital white and gray matter at 7 T.

Proton T1 relaxation times of metabolites in the human brain have not previously been published at 7 T. In this study, T1 values of CH3 and CH2 group of N-acetylaspartate and total creatine as well as nine other brain metabolites were measured in occipital white matter and gray matter at 7 T using an inversion-recovery technique combined with a newly implemented semi-adiabatic spin-echo full-intensity acquired localized spectroscopy sequence (echo time = 12 ms). The mean T1 values of metabolites in occipital white matter and gray matter ranged from 0.9 to 2.2 s. Among them, the T1 of glutathione, scyllo-inositol, taurine, phosphorylethanolamine, and N-acetylaspartylglutamate were determined for the first time in the human brain. Significant differences in T1 between white matter and gray matter were found for water (-28%), total choline (-14%), N-acetylaspartylglutamate (-29%), N-acetylaspartate (+4%), and glutamate (+8%). An increasing trend in T1 was observed when compared with previously reported values of N-acetylaspartate (CH3 ), total creatine (CH3 ), and total choline at 3 T. However, for N-acetylaspartate (CH3 ), total creatine, and total choline, no substantial differences compared to previously reported values at 9.4 T were discernible. The T1 values reported here will be useful for the quantification of metabolites and signal-to-noise optimization in human brain at 7 T. Magn Reson Med 69:931-936, 2013. © 2012 Wiley Periodicals, Inc.

Optimization of multiclass queueing networks with changeover times via the achievable region approach: Part I, the single-station case

We address the performance optimization problem in a single-stationmulticlass queueing network with changeover times by means of theachievable region approach. This approach seeks to obtainperformance bounds and scheduling policies from the solution of amathematical program over a relaxation of the system's performanceregion. Relaxed formulations (including linear, convex, nonconvexand positive semidefinite constraints) of this region are developedby formulating equilibrium relations satisfied by the system, withthe help of Palm calculus. Our contributions include: (1) newconstraints formulating equilibrium relations on server dynamics;(2) a flow conservation interpretation of the constraintspreviously derived by the potential function method; (3) newpositive semidefinite constraints; (4) new work decomposition lawsfor single-station multiclass queueing networks, which yield newconvex constraints; (5) a unified buffer occupancy method ofperformance analysis obtained from the constraints; (6) heuristicscheduling policies from the solution of the relaxations.