A random generator of resource-constrained multi-project network problems

Many scheduling problems in project management, manufacturing, and elsewhere require the generation of activity networks to test proposed solution methods. Single-network generators have been used for the resource-constrained project scheduling problem (RCPSP). Since the first single-network generator was proposed in 1993, several advances have been reported in the literature. However, these generators create only one network or project at a time; they cannot generate multi-project problems to desired specifications. This paper presents the first multi-network problem generator. It is especially useful for investigating the resource-constrained multi-project scheduling problem (RCMPSP), where a controlled set of multi-project test problems is crucial for analyzing the performance of solution methods. In addition to the single-project characteristics handled by existing network generators—such as activity duration, resource types and usage, and network size, shape, and complexity—the proposed generator produces multi-project portfolios with controlled resource distributions and amounts of resource contention. To enable the generation of projects with desired levels of network complexity, we also develop several theoretical insights on the effects of network topology on the probability of successful network generation. Finally, we generate 12,320 test problems for a full-factorial experiment and use analysis of means to conclude that the generator produces “near-strongly random” problems. Fully “strongly random” problems require much greater computational expense.     

Lipolytic sensitivity and response to fasting in normotensive and hypertensive obese humans

Obese persons with hypertension are at greater risk for diabetes and hyperlipidemia than normotensive obese persons. It has been postulated that increased lipolytic rates contribute to these metabolic diseases. Therefore, we evaluated the glycerol rate of appearance (Ra) in plasma, an index of whole-body lipolytic activity, during basal conditions and during 60 minutes of epinephrine infusion after 12 and 84 hours of fasting in six normotensive (body mass index [BMI], 39.9 +/- 1.8 kg/m2) and six hypertensive (BMI, 38.7 +/- 1.6 kg/m2) obese persons. Basal glycerol Ra was lower in hypertensive than in normotensive subjects at both 12 hours (1.58 +/- 0.21 v 2.27 +/- 0.28 mumol/kg/min, respectively; P < .01) and 84 hours (2.04 +/- 0.06 v 2.50 +/- 0.13 mumol/kg/min, respectively; P < .01) of fasting. Peak glycerol Ra during epinephrine infusion after 84 hours of fasting (5.69 +/- 0.72 and 11.40 +/- 0.78 mumol/kg/min for hypertensive and normotensive subjects, respectively) was significantly greater than at 12 hours (3.09 +/- 0.29 and 5.06 +/- 0.69 mumol/kg/min) in both hypertensive and normotensive subjects. However, peak glycerol Ra was lower in hypertensive than in normotensive subjects after 12 and 84 hours of fasting (P < .01 for 84 hours). We conclude that hypertension in obese persons is associated with a decrease in both basal lipolytic rates and lipolytic sensitivity to epinephrine infusion.     

Pregnancy loss and autoantibodies against phospholipid-binding proteins

We investigated the utility of two approaches for exploiting pleiotropy to search for genes influencing related traits. To do this we first assessed the genetic correlations among a set of five closely related quantitative traits (Q1, Q2, Q3, Q4, Q5). We then used the genetic correlations among these five traits both to remove the common genetic effects of the four remaining traits, thereby identifying the unique genetic contribution to each trait, and to extract a synthetic phenotype which exploits the shared genetic information (pleiotropy) among these five traits. After obtaining these conditional traits, we then searched for evidence of quantitative trait loci (QTLs) (using variance component linkage) influencing the unique residual genetic component for each trait as well as those influencing the expression of the synthetic traits. From this work, we conclude that the removal of the common genetic effects of other traits in a group may be of greater utility when the majority of the pleiotropy initially detected between traits is attributable to the shared additive effects of polygenes, rather than to those of major loci. By contrast, decomposition of the genetic covariance matrix to its principal components is a greater utility when the majority of pleiotropy is attributable to major loci.