The Highest Price Ever: The Great NYSE Seat Sale of 1928–1929 and Capacity Constraints

During the 1920s the New York Stock Exchange's position as the dominant American exchange was eroding. Costs to customers, measured as bid-ask spreads, spiked when surging inflows of orders collided with the constraint created by a fixed number of brokers. The NYSE's management proposed and the membership approved a 25 percent increase in the number of seats by issuing a quarter-seat dividend to all members. An event study reveals that the aggregate value of the NYSE rose in anticipation of improved competitiveness. These expectations were justified as bid-ask spreads became less sensitive to peak volume days

The Highest Price Ever: The Great NYSE Seat Sale of 1928-1929 and Capacity Constraints

A surge in orders during the stock market boom of the late 1920s collided against the constraint created by the fixed number of brokers on the New York Stock Exchange. Estimates of the determinants of individual stock bid-ask spreads from panel data reveal that spreads jumped when volume spiked, confirming contemporary observers complaints that there were insufficient counterparties. When the position of the NYSE as the dominant exchange became threatened, the management of the exchange proposed a 25 percent increase in the number of seats in February 1929 by issuing a quarter-seat dividend to all members. While such a "stock split" would be expected to leave the aggregate value of the NYSE unchanged, an event study reveals that its value rose in anticipation of increased efficiency. These expectations were justified as bid-ask spreads became less sensitive to peak volume days after the increase in seats.

Evaluation of Different Media in Static Bed Biofilters for Removal of Endocrine Disrupting Compounds in Domestic Wastewater

2010 S.C. Water Resources Conference - Science and Policy Challenges for a Sustainable Futur

Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases

BACKGROUND: Appropriate definition of neural network architecture prior to data analysis is crucial for successful data mining. This can be challenging when the underlying model of the data is unknown. The goal of this study was to determine whether optimizing neural network architecture using genetic programming as a machine learning strategy would improve the ability of neural networks to model and detect nonlinear interactions among genes in studies of common human diseases. RESULTS: Using simulated data, we show that a genetic programming optimized neural network approach is able to model gene-gene interactions as well as a traditional back propagation neural network. Furthermore, the genetic programming optimized neural network is better than the traditional back propagation neural network approach in terms of predictive ability and power to detect gene-gene interactions when non-functional polymorphisms are present. CONCLUSION: This study suggests that a machine learning strategy for optimizing neural network architecture may be preferable to traditional trial-and-error approaches for the identification and characterization of gene-gene interactions in common, complex human diseases

Conservation and divergence of ADAM family proteins in the Xenopus genome

Background Members of the disintegrin metalloproteinase (ADAM) family play important roles in cellular and developmental processes through their functions as proteases and/or binding partners for other proteins. The amphibian Xenopus has long been used as a model for early vertebrate development, but genome-wide analyses for large gene families were not possible until the recent completion of the X. tropicalis genome sequence and the availability of large scale expression sequence tag (EST) databases. In this study we carried out a systematic analysis of the X. tropicalis genome and uncovered several interesting features of ADAM genes in this species. Results Based on the X. tropicalis genome sequence and EST databases, we identified Xenopus orthologues of mammalian ADAMs and obtained full-length cDNA clones for these genes. The deduced protein sequences, synteny and exon-intron boundaries are conserved between most human and X. tropicalis orthologues. The alternative splicing patterns of certain Xenopus ADAM genes, such as adams 22 and 28, are similar to those of their mammalian orthologues. However, we were unable to identify an orthologue for ADAM7 or 8. The Xenopus orthologue of ADAM15, an active metalloproteinase in mammals, does not contain the conserved zinc-binding motif and is hence considered proteolytically inactive. We also found evidence for gain of ADAM genes in Xenopus as compared to other species. There is a homologue of ADAM10 in Xenopus that is missing in most mammals. Furthermore, a single scaffold of X. tropicalis genome contains four genes encoding ADAM28 homologues, suggesting genome duplication in this region. Conclusions Our genome-wide analysis of ADAM genes in X. tropicalis revealed both conservation and evolutionary divergence of these genes in this amphibian species. On the one hand, all ADAMs implicated in normal development and health in other species are conserved in X. tropicalis. On the other hand, some ADAM genes and ADAM protease activities are absent, while other novel ADAM proteins in this species are predicted by this study. The conservation and unique divergence of ADAM genes in Xenopus probably reflect the particular selective pressures these amphibian species faced during evolution.National Institutes of Health. Department of Health and Human Services (Ruth L. Kirschstein postdoctoral fellowship)National Institutes of Health. Department of Health and Human Services (5T32GA09109)American Heart Association (postdoctoral fellowship)March of Dimes Birth Defects Foundation (grant 1-FY10-399)March of Dimes Birth Defects Foundation (grant F405-140)National Institutes of Health (U.S.) (HD26402)National Institutes of Health (U.S.) (DE14365

Development and Implementation of Dynamic Scripts to Support Local Model Verification at National Weather Service Weather Forecast Offices

Local modeling with a customized configuration is conducted at National Weather Service (NWS) Weather Forecast Offices (WFOs) to produce high-resolution numerical forecasts that can better simulate local weather phenomena and complement larger scale global and regional models. The advent of the Environmental Modeling System (EMS), which provides a pre-compiled version of the Weather Research and Forecasting (WRF) model and wrapper Perl scripts, has enabled forecasters to easily configure and execute the WRF model on local workstations. NWS WFOs often use EMS output to help in forecasting highly localized, mesoscale features such as convective initiation, the timing and inland extent of lake effect snow bands, lake and sea breezes, and topographically-modified winds. However, quantitatively evaluating model performance to determine errors and biases still proves to be one of the challenges in running a local model. Developed at the National Center for Atmospheric Research (NCAR), the Model Evaluation Tools (MET) verification software makes performing these types of quantitative analyses easier, but operational forecasters do not generally have time to familiarize themselves with navigating the sometimes complex configurations associated with the MET tools. To assist forecasters in running a subset of MET programs and capabilities, the Short-term Prediction Research and Transition (SPoRT) Center has developed and transitioned a set of dynamic, easily configurable Perl scripts to collaborating NWS WFOs. The objective of these scripts is to provide SPoRT collaborating partners in the NWS with the ability to evaluate the skill of their local EMS model runs in near real time with little prior knowledge of the MET package. The ultimate goal is to make these verification scripts available to the broader NWS community in a future version of the EMS software. This paper provides an overview of the SPoRT MET scripts, instructions for how the scripts are run, and example use cases

SkyMapper Southern Survey: First Data Release (DR1)

We present the first data release (DR1) of the SkyMapper Southern Survey, a hemispheric survey carried out with the SkyMapper Telescope at Siding Spring Observatory in Australia. Here, we present the survey strategy, data processing, catalogue construction and database schema. The DR1 dataset includes over 66,000 images from the Shallow Survey component, covering an area of 17,200 deg$^2$ in all six SkyMapper passbands $uvgriz$, while the full area covered by any passband exceeds 20,000 deg$^2$. The catalogues contain over 285 million unique astrophysical objects, complete to roughly 18 mag in all bands. We compare our $griz$ point-source photometry with PanSTARRS1 DR1 and note an RMS scatter of 2%. The internal reproducibility of SkyMapper photometry is on the order of 1%. Astrometric precision is better than 0.2 arcsec based on comparison with Gaia DR1. We describe the end-user database, through which data are presented to the world community, and provide some illustrative science queries.Comment: 31 pages, 19 figures, 10 tables, PASA, accepte

Curriculum Guidelines for Undergraduate Programs in Data Science

The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science. The group consisted of 25 undergraduate faculty from a variety of institutions in the U.S., primarily from the disciplines of mathematics, statistics and computer science. These guidelines are meant to provide some structure for institutions planning for or revising a major in Data Science

Assessing the Potential Effects of Fungicides on Nontarget Gut Fungi (Trichomycetes) and Their Associated Larval Black Fly Hosts

Fungicides are moderately hydrophobic and have been detected in water and sediment, particularly in agricultural watersheds, but typically are not included in routine water quality monitoring efforts. This is despite their widespread use and frequent application to combat fungal pathogens. Although the efficacy of these compounds on fungal pathogens is well documented, little is known about their effects on nontarget fungi. This pilot study, a field survey in southwestern Idaho from April to December 2010 on four streams with varying pesticide inputs (two agricultural and two reference sites), was conducted to assess nontarget impact of fungicides on gut fungi, or trichomycetes. Tissues of larval black flies (Diptera: Simuliidae), hosts of gut fungi, were analyzed for pesticide accumulation. Fungicides were detected in hosts from streams within agricultural watersheds but were not detected in hosts from reference streams. Gut fungi from agricultural sites exhibited decreased percent infestation, density and sporulation within the gut, and black fly tissues had elevated pesticide concentrations. Differences observed between the sites demonstrate a potential effect on this symbiotic system. Future research is needed to parse out the details of the complex biotic and abiotic relationships; however, these preliminary results indicate that impacts to nontarget organisms could have far-reaching consequences within aquatic ecosystems