The Multiple-partners assignment game with heterogeneous sales and multi-unit demands: competitive equilibria

A multiple-partners assignment game with heterogeneous sales and multiunit demands consists of a set of sellers that own a given number of indivisible units of (potentially many different) goods and a set of buyers who value those units and want to buy at most an exogenously fixed number of units. We define a competitive equilibrium for this generalized assignment game and prove its existence by using only linear programming. In particular, we show how to compute equilibrium price vectors from the solutions of the dual linear program associated to the primal linear program defined to find optimal assignments. Using only linear programming tools, we also show (i) that the set of competitive equilibria (pairs of price vectors and assignments) has a Cartesian product structure: each equilibrium price vector is part of a competitive equilibrium with all optimal assignments, and vice versa; (ii) that the set of (restricted) equilibrium price vectors has a natural lattice structure; and (iii) how this structure is translated into the set of agents' utilities that are attainable at equilibrium.

Differential time to positivity of blood cultures: a valid method for diagnosing catheter-related bloodstream infections in the intensive care unit

iii. Catheter-related bloodstream infection (CR-BSI) diagnosis usually involves catheter withdrawal. An alternative method for CR-BSI diagnosis is the differential time to positivity (DTP) between peripheral and catheter hub blood cultures. This study aims to validate the DTP method in short-term catheters. The results show a low prevalence of CR-BSI in the sample (8.4%). The DTP method is a valid alternative for CR-BSI diagnosis in those cases with monomicrobial cultures (80% sensitivity, 99% specificity, 92% positive predictive value, and 98% negative predictive value) and a cut-off point of 17.7 hours for positivity of hub blood culture may assess in CR-BSI diagnosis.

Statistical tests for scaling in the inter-event times of earthquakes in California

We explore in depth the validity of a recently proposed scaling law for earthquake inter-event time distributions in the case of the Southern California, using the waveform cross-correlation catalog of Shearer et al. Two statistical tests are used: on the one hand, the standard two-sample Kolmogorov-Smirnov test is in agreement with the scaling of the distributions. On the other hand, the one-sample Kolmogorov-Smirnov statistic complemented with Monte Carlo simulation of the inter-event times, as done by Clauset et al., supports the validity of the gamma distribution as a simple model of the scaling function appearing on the scaling law, for rescaled inter-event times above 0.01, except for the largest data set (magnitude greater than 2). A discussion of these results is provided.