SPATIAL AND SUPPLY/DEMAND AGGLOMERATION ECONOMIES: AN EVALUATION OF STATE-AND-INDUSTRY-LINKAGES IN THE U.S. FOOD SYSTEM

In this paper we postulate, measure, and evaluate the importance of cost-impacts from spatial and industrial spillovers for analysis of economic performance. To accomplish this, we incorporate measures of "activity levels" of related states and industries in a cost function model, and estimate their associated thick market and agglomeration effects in terms of shadow values and elasticities. We focus on the food processing sector, the proximity of own-industry activity in neighboring states, and the supply- and demand- side "drivers", associated with urbanization and localization economies (represented by the GSP and agricultural intensity in the own and neighboring states). We find significant cost-savings benefits to a states food processing sector of being close to other food manufacturing centers (high levels of food processing activity in neighboring states). We also find it beneficial to be in a state with high purchasing power (demand), and to have neighboring states that are agriculture-based (supply). However, it also seems costly to actually be located in a heavily agricultural or rural state, possibly due to diseconomies from "thin markets" associated with infrastructure support and labor markets.Productivity Analysis,

Chaperoning steroid hormone signaling via reversible acetylation

Glucocorticoid receptor (GR) and related steroid hormone receptors are ligand-dependent transcription factors whose regulation is critical for both homeostasis and diseases. The structural maturation of the GR has been shown to require the Hsp90 molecular chaperone complex. Evidence indicates that Hsp90-dependent maturation is critical for GR ligand binding capacity and activity. While the role for Hsp90 in GR function is well established, the regulation of this process is not well understood. Here we discuss a recent finding that identifies reversible protein acetylation controlled by the deacetylase HDAC6 as a novel mechanism that regulates Hsp90-dependent GR maturation. We will also speculate on the implications of this finding in steroid hormone signaling, oncogenic transformation and its potential therapeutic utility

A test of the pioneer factor hypothesis using ectopic liver gene activation

The pioneer factor hypothesis (PFH) states that pioneer factors (PFs) are a subclass of transcription factors (TFs) that bind to and open inaccessible sites and then recruit non-pioneer factors (non-PFs) that activate batteries of silent genes. The PFH predicts that ectopic gene activation requires the sequential activity of qualitatively different TFs. We tested the PFH by expressing the endodermal PF FOXA1 and non-PF HNF4A in K562 lymphoblast cells. While co-expression of FOXA1 and HNF4A activated a burst of endoderm-specific gene expression, we found no evidence for a functional distinction between these two TFs. When expressed independently, both TFs bound and opened inaccessible sites, activated endodermal genes, and \u27pioneered\u27 for each other, although FOXA1 required fewer copies of its motif for binding. A subset of targets required both TFs, but the predominant mode of action at these targets did not conform to the sequential activity predicted by the PFH. From these results, we hypothesize an alternative to the PFH where \u27pioneer activity\u27 depends not on categorically different TFs but rather on the affinity of interaction between TF and DNA

Estimating the proportion of guilty suspects and posterior probability of guilt in lineups using signal-detection models

Background The majority of eyewitness lineup studies are laboratory-based. How well the conclusions of these studies, including the relationship between confidence and accuracy, generalize to real-world police lineups is an open question. Signal detection theory (SDT) has emerged as a powerful framework for analyzing lineups that allows comparison of witnesses’ memory accuracy under different types of identification procedures. Because the guilt or innocence of a real-world suspect is generally not known, however, it is further unknown precisely how the identification of a suspect should change our belief in their guilt. The probability of guilt after the suspect has been identified, the posterior probability of guilt (PPG), can only be meaningfully estimated if we know the proportion of lineups that include a guilty suspect, P(guilty). Recent work used SDT to estimate P(guilty) on a single empirical data set that shared an important property with real-world data; that is, no information about the guilt or innocence of the suspects was provided. Here we test the ability of the SDT model to recover P(guilty) on a wide range of pre-existing empirical data from more than 10,000 identification decisions. We then use simulations of the SDT model to determine the conditions under which the model succeeds and, where applicable, why it fails. Results For both empirical and simulated studies, the model was able to accurately estimate P(guilty) when the lineups were fair (the guilty and innocent suspects did not stand out) and identifications of both suspects and fillers occurred with a range of confidence levels. Simulations showed that the model can accurately recover P(guilty) given data that matches the model assumptions. The model failed to accurately estimate P(guilty) under conditions that violated its assumptions; for example, when the effective size of the lineup was reduced, either because the fillers were selected to be poor matches to the suspect or because the innocent suspect was more familiar than the guilty suspect. The model also underestimated P(guilty) when a weapon was shown. Conclusions Depending on lineup quality, estimation of P(guilty) and, relatedly, PPG, from the SDT model can range from poor to excellent. These results highlight the need to carefully consider how the similarity relations between fillers and suspects influence identifications

Local Production and Developing Core Regions: Ceramic Characterization in the Lake Pátzcuaro Basin, Western Mexico

A core region is the first place for expected shifts in archaeological materials before, during, and after political changes like state emergence and imperial consolidation. Yet, studies of ceramic production have shown that there are sometimes limited or more subtle changes in the ceramic economy throughout such political fluctuations. This article synthesizes recent efforts to address political economic changes via geochemical characterization (neutron activation analysis; NAA) in the Lake Pátzcuaro Basin in western Mexico. This region was home to the Purépecha state and then empire (Tarascan; ca. AD 1350-1530), one of the most powerful kingdoms in the Americas before European arrival. The combined ceramic dataset from four sites in the region result in eight geochemical groups. Our analysis indicates that the region experienced long-term and relatively stable ceramic production that was not substantially altered by the emergence of the state and empire. In addition, we find evidence for (1) dispersed, localized production; (2) long-lived compositional ceramic recipes; and (3) a complex ceramic economy with differential community participation. We discuss why documenting local ceramic production and craft production more generally is important for the study of past political economies

Strategies for Using a Spatial Method to Promote Active Learning of Probability Concepts

We developed and tested strategies for using spatial representations to help students understand core probability concepts, including the multiplication rule for computing a joint probability from a marginal and conditional probability, interpreting an odds value as the ratio of two probabilities, and Bayesian inference. The general goal of these strategies is to promote active learning by introducing concepts in an intuitive spatial format and then encouraging students to try to discover the explicit equations associated with the spatial representations. We assessed the viability of the proposed active-learning approach with two exercises that tested undergraduates’ ability to specify mathematical equations after learning to use the spatial solution method. A majority of students succeeded in independently discovering fundamental mathematical concepts underlying probabilistic reasoning. For example, in the second exercise, 76% of students correctly multiplied marginal and conditional probabilities to find joint probabilities, 86% correctly divided joint probabilities to get an odds value, and 69% did both to achieve full Bayesian inference. Thus, we conclude that the spatial method is an effective way to promote active learning of probability equations

Genetic recombination is targeted towards gene promoter regions in dogs

The identification of the H3K4 trimethylase, PRDM9, as the gene responsible for recombination hotspot localization has provided considerable insight into the mechanisms by which recombination is initiated in mammals. However, uniquely amongst mammals, canids appear to lack a functional version of PRDM9 and may therefore provide a model for understanding recombination that occurs in the absence of PRDM9, and thus how PRDM9 functions to shape the recombination landscape. We have constructed a fine-scale genetic map from patterns of linkage disequilibrium assessed using high-throughput sequence data from 51 free-ranging dogs, Canis lupus familiaris. While broad-scale properties of recombination appear similar to other mammalian species, our fine-scale estimates indicate that canine highly elevated recombination rates are observed in the vicinity of CpG rich regions including gene promoter regions, but show little association with H3K4 trimethylation marks identified in spermatocytes. By comparison to genomic data from the Andean fox, Lycalopex culpaeus, we show that biased gene conversion is a plausible mechanism by which the high CpG content of the dog genome could have occurred.Comment: Updated version, with significant revision

The economic implications of HLA matching in cadaveric renal transplantation.

Abstract Background: The potential economic effects of the allocation of cadaveric kidneys on the basis of tissue-matching criteria are controversial. We analyzed the economic costs associated with the transplantation of cadaveric kidneys with various numbers of HLA mismatches and examined the potential economic benefits of a local, as compared with a national, system designed to minimize HLA mismatches between donor and recipient in first cadaveric renal transplantations. Methods: All data were supplied by the U.S. Renal Data System. Data on all payments made by Medicare from 1991 through 1997 for the care of recipients of a first cadaveric renal transplant were analyzed according to the number of HLA-A, B, and DR mismatches between donor and recipient and the duration of cold ischemia before transplantation. Results: Average Medicare payments for renal-transplant recipients in the three years after transplantation increased from $60,436 per patient for fully HLA-matched kidneys (those with no HLA-A, B, or DR mismatches) to$80,807 for kidneys with six HLA mismatches between donor and recipient, a difference of 34 percent (P\u3c0.001). By three years after transplantation, the average Medicare payments were $64,119 for transplantations of kidneys with less than 12 hours of cold-ischemia time and$74,997 for those with more than 36 hours (P\u3c0.001). In simulations, the assignment of cadaveric kidneys to recipients by a method that minimized HLA mismatching within a local geographic area (i.e., within one of the approximately 50 organ-procurement organizations, which cover widely varying geographic areas) produced the largest cost savings ($4,290 per patient over a period of three years) and the largest improvements in the graft-survival rate (2.3 percent) when the potential costs of longer cold-ischemia time were considered. Conclusions: Transplantation of better-matched cadaveric kidneys could have substantial economic advantages. In our simulations, HLA-based allocation of kidneys at the local level produced the largest estimated cost savings, when the duration of cold ischemia was taken into account. No additional savings were estimated to result from a national allocation program, because the additional costs of longer cold-ischemia time were greater than the advantages of optimizing HLA matching