A model of management teams

Management;Decision Making

BAFF activation of the ERK5 MAP kinase pathway regulates B cell survival

B cell activating factor (BAFF) stimulation of the BAFF receptor (BAFF-R) is essential for the homeostatic survival of mature B cells. Earlier in vitro experiments with inhibitors that block MEK 1 and 2 suggested that activation of ERK 1 and 2 MAP kinases is required for BAFF-R to promote B cell survival. However, these inhibitors are now known to also inhibit MEK5, which activates the related MAP kinase ERK5. In the present study, we demonstrated that BAFF-induced B cell survival was actually independent of ERK1/2 activation but required ERK5 activation. Consistent with this, we showed that conditional deletion of ERK5 in B cells led to a pronounced global reduction in mature B2 B cell numbers, which correlated with impaired survival of ERK5-deficient B cells after BAFF stimulation. ERK5 was required for optimal BAFF up-regulation of Mcl1 and Bcl2a1, which are prosurvival members of the Bcl-2 family. However, ERK5 deficiency did not alter BAFF activation of the PI3-kinase-Akt or NF-κB signaling pathways, which are also important for BAFF to promote mature B cell survival. Our study reveals a critical role for the MEK5-ERK5 MAP kinase signaling pathway in BAFF-induced mature B cell survival and homeostatic maintenance of B2 cell numbers

Statistical Modelling of Fishing Activities in the North Atlantic

This paper deals with the issue of modeling daily catches of fishing boats in the Grand Bank fishing grounds. We have data on catches per species for a number of vessels collected by the European Union in the context of the North Atlantic Fisheries Organization. Many variables can be thought to influence the amount caught: a number of ship characteristics (such as the size of the ship, the fishing technique used, the mesh size of the nets, etc.), are obvious candidates, but one can also consider the season or the actual location of the catch. In all, our database leads to 23 possible regressors, resulting in a set of 8:4£106 possible linear regression models. Prediction of future catches and posterior inference will be based on Bayesian model averaging, using a Markov Chain Monte Carlo Model Composition (MC3) approach. Particular attention is paid to the elicitation of the prior and the prediction of catch for single and aggregated observations.

Benchmark priors for Bayesian models averaging

In contrast to a posterior analysis given a particular sampling model, posterior model probabilities in the context of model uncertainty are typically rather sensitive to the specification of the prior. In particular, 'diffuse' priors on model-specific parameters can lead to quite unexpected consequences. Here we focus on the practically relevant situation where we need to entertain a (large) number of sampling models and we have (or wish to use) little or no subjective prior information. We aim at providing an 'automatic' or 'benchmark' prior structure that can be used in such cases. We focus on the Normal linear regression model with uncertainty in the choice of regressors. We propose a partly noninformative prior structure related to a Natural Conjugate $g$-prior specification, where the amount of subjective information requested from the user is limited to the choice of a single scalar hyperparameter $g_{0j}$. The consequences of different choices for $g_{0j}$ are examined. We investigate theoretical properties, such as consistency of the implied Bayesian procedure. Links with classical information criteria are provided. In addition, we examine the finite sample implications of several choices of $g_{0j}$ in a simulation study. The use of the MC$^3$ algorithm of Madigan and York (1995), combined with efficient coding in Fortran, makes it feasible to conduct large simulations. In addition to posterior criteria, we shall also compare the predictive performance of different priors. A classic example concerning the economics of crime will also be provided and contrasted with results in the literature. The main findings of the paper will lead us to propose a 'benchmark' prior specification in a linear regression context with model uncertainty.Bayes factors, Markov chain, Monte Carlo, Posterior odds, Prior elicitation

A Tax-Based Approach to Slowing Global Climate Change

In this paper, we discuss the design of carbon dioxide (CO2) taxes at the domestic and international level and the choice of taxes versus a cap-and-trade system. A strong case can be made for taxes on uncertainty, fiscal, and distributional grounds, though this critically hinges on policy specifics and how revenues are used. The efficient near-term tax is at least $5–$20 per ton of CO2 and the tax should be imposed upstream with incentives for downstream sequestration and abatement of other greenhouse gases. At the international level, a key challenge is the possibility that emissions taxes might be undermined through offsetting changes in other energy policies.Global climate change, CO2 tax, cap-and-trade, policy design

How learning to abstract shapes neural sound representations

The transformation of acoustic signals into abstract perceptual representations is the essence of the efficient and goal-directed neural processing of sounds in complex natural environments. While the human and animal auditory system is perfectly equipped to process the spectrotemporal sound features, adequate sound identification and categorization require neural sound representations that are invariant to irrelevant stimulus parameters. Crucially, what is relevant and irrelevant is not necessarily intrinsic to the physical stimulus structure but needs to be learned over time, often through integration of information from other senses. This review discusses the main principles underlying categorical sound perception with a special focus on the role of learning and neural plasticity. We examine the role of different neural structures along the auditory processing pathway in the formation of abstract sound representations with respect to hierarchical as well as dynamic and distributed processing models. Whereas most fMRI studies on categorical sound processing employed speech sounds, the emphasis of the current review lies on the contribution of empirical studies using natural or artificial sounds that enable separating acoustic and perceptual processing levels and avoid interference with existing category representations. Finally, we discuss the opportunities of modern analyses techniques such as multivariate pattern analysis (MVPA) in studying categorical sound representations. With their increased sensitivity to distributed activation changes—even in absence of changes in overall signal level—these analyses techniques provide a promising tool to reveal the neural underpinnings of perceptually invariant sound representations

Statistical Modelling of Fishing Activities in the North Atlantic

This paper deals with the issue of modeling daily catches of fishing boats in the Grand Bank fishing grounds. We have data on catches per species for a number of vessels collected by the European Union in the context of the North Atlantic Fisheries Organization. Many variables can be thought to influence the amount caught: a number of ship characteristics (such as the size of the ship, the fishing technique used, the mesh size of the nets, etc.), are obvious candidates, but one can also consider the season or the actual location of the catch. In all, our database leads to 23 possible regressors, resulting in a set of 8:4£106 possible linear regression models. Prediction of future catches and posterior inference will be based on Bayesian model averaging, using a Markov Chain Monte Carlo Model Composition (MC3) approach. Particular attention is paid to the elicitation of the prior and the prediction of catch for single and aggregated observations.

Property Tax Equity: A Study of Bemidji, Minnesota

The paper seeks to evaluate the equity of property tax assessments in a rural northern Minnesota area. Criteria of both vertical and horizontal equity were examined in terms of the ability to pay and benefits measures of the intra-decile relationships. In addition, other variables affecting intra-decile horizontal equity such as age and lakeshore location were considered. The data upon which the results were based were drawn from random sampling of 1000 households in the R-31 school district at Bemidji, Beltrami County, Minnesota. The sample represented 20 percent of all such households. A total of 216 households responded to a questionnaire which asked for adjusted gross income. tax assessments, number of children enrolled in R-31 schools, property tax credits, age of taxpayers, and whether the property was lakeshore or not. The study concludes that the property tax assessments in Bemidji violate both vertical and horizontal standards for equity whether measured in terms of the ability to pay or of benefits. It also appears that intra-decile horizontal equity is violated in terms of lakeshore versus non-lakeshore assessments. Finally, older people in the lower income deciles are taxed more heavily than average