Price Discovery and the Accuracy of Consolidated Data Feeds in the U.S. Equity Markets

Both the scientific community and the popular press have paid much attention to the speed of the Securities Information Processor, the data feed consolidating all trades and quotes across the US stock market. Rather than the speed of the Securities Information Processor, or SIP, we focus here on its accuracy. Relying on Trade and Quote data, we provide various measures of SIP latency relative to high-speed data feeds between exchanges, known as direct feeds. We use first differences to highlight not only the divergence between the direct feeds and the SIP, but also the fundamental inaccuracy of the SIP. We find that as many as 60 percent or more of trades are reported out of sequence for stocks with high trade volume, therefore skewing simple measures such as returns. While not yet definitive, this analysis supports our preliminary conclusion that the underlying infrastructure of the SIP is currently unable to keep pace with the trading activity in today's stock market.Comment: 18 pages, 20 figures, 2 table

Revisiting Stylized Facts for Modern Stock Markets

In 2001, Rama Cont introduced a now-widely used set of 'stylized facts' to synthesize empirical studies of financial time series, resulting in 11 qualitative properties presumed to be universal to all financial markets. Here, we replicate Cont's analyses for a convenience sample of stocks drawn from the U.S. stock market following a fundamental shift in market regulation. Our study relies on the same authoritative data as that used by the U.S. regulator. We find conclusive evidence in the modern market for eight of Cont's original facts, while we find weak support for one additional fact and no support for the remaining two. Our study represents the first test of the original set of 11 stylized facts against the same stocks, therefore providing insight into how Cont's stylized facts should be viewed in the context of modern stock markets.Comment: 19 pages, 11 figure

Backflashes from fast-gated avalanche photodiodes in quantum key distribution

InGaAs single-photon avalanche photodiodes (APDs) are key enablers for high-bit rate quantum key distribution. However, the deviation of such detectors from ideal models can open side-channels for an eavesdropper, Eve, to exploit. The phenomenon of backflashes, whereby APDs reemit photons after detecting a photon, gives Eve the opportunity to passively learn the information carried by the detected photon without the need to actively interact with the legitimate receiver, Bob. While this has been observed in slow-gated detectors, it has not been investigated in fast-gated APDs where it has been posited that this effect would be lessened. Here, we perform the first experiment to characterize the security threat that backflashes provide in a GHz-gated self-differencing APD using the metric of information leakage. We find that, indeed, the information leakage is lower than that reported for slower-gated detectors, and we show that its effect on the secure key rate is negligible. We also relate the rate of backflash events to the APD dark current, thereby suggesting that their origin is the InP multiplication region in the APD

Biallelic mutations in valyl-tRNA synthetase gene VARS are associated with a progressive neurodevelopmental epileptic encephalopathy.

Aminoacyl-tRNA synthetases (ARSs) function to transfer amino acids to cognate tRNA molecules, which are required for protein translation. To date, biallelic mutations in 31 ARS genes are known to cause recessive, early-onset severe multi-organ diseases. VARS encodes the only known valine cytoplasmic-localized aminoacyl-tRNA synthetase. Here, we report seven patients from five unrelated families with five different biallelic missense variants in VARS. Subjects present with a range of global developmental delay, epileptic encephalopathy and primary or progressive microcephaly. Longitudinal assessment demonstrates progressive cortical atrophy and white matter volume loss. Variants map to the VARS tRNA binding domain and adjacent to the anticodon domain, and disrupt highly conserved residues. Patient primary cells show intact VARS protein but reduced enzymatic activity, suggesting partial loss of function. The implication of VARS in pediatric neurodegeneration broadens the spectrum of human diseases due to mutations in tRNA synthetase genes

Explorations, Vol. 5, No. 1

Articles include: Cover: What Have We Done with Tomorrow? by Leslie C. Hyde, UMCES Extension Agent for Knox-Lincoln Counties. Editorial Reflections, Carole J. Bombard UMCES: an overview Conversation with the Director: Assistant Vice-President Judith Bailey Reaching Out for Teen Awareness, by Theresa M. Ferrari Profile of a Harbormaster, by Carole J. Bombard Minding Maine’s Business, by Mary S. Bowie Family Resource Management: Learning to ease the burden, by Olive Dubord and Doris Cushman Breaking Free and Taking Control: Helen Sawyer’s Story, by Doris Manley Partnership in Conservation: The Josephine Newman Sanctuary, by Nancy Coverstone The Mount Desert Island Health Promotion Project, by Ron Beard Dynamics of Weed Control in Agriculture, by Leigh Morrow From Generation to Generation: An Extension Homemaker Family, by Nadine B. Reimer ICLAD: The Institute for Community Leadership and Development, by Jim Killacky and Deb Burwell Exploding the Cinderella Syndrome: Strengthening Stepfamilies, by Wendy Pollock Integrated Pest Management: Bringing it all together, by Glen Koehler and Jim Dill Addressing the Issues, by Patricia M. Pierson Anti-Bruise: What’s It All About? Maine Potato Harvest Anti-Bruise Program, by Neal D. Hallee H.O.P.E. Addresses Teenage Pregnancy, by Jane M. Kelly Saving Money and the Environment, by Vaughn H. Holyoke Reservoir Tillage in Nonirrigated Potato Production, by Leigh Morrow Managing Pesticide Drift, by James D. Dwyer, Leigh S. Morrow and James F. Dill The St. George River Project — what have we done with tomorrow? Putting Research to Work, by Stephen Belyea The Best Maine Blue: Fresh Pack Blueberries, by Tom DeGomez Maine’s Green Sea Urchin, by Benjamin A. Baxter Interfaces and Cooperation: Wildlife and Fisheries Sampler, by Catherine A. Elliott Extension Responds to the Salmonella Scare, by Nellie Hedstrom and Mahmoud El-Begearm

VennPlex--a novel Venn diagram program for comparing and visualizing datasets with differentially regulated datapoints.

With the development of increasingly large and complex genomic and proteomic data sets, an enhancement in the complexity of available Venn diagram analytical programs is becoming increasingly important. Current freely available Venn diagram programs often fail to represent extra complexity among datasets, such as regulation pattern differences between different groups. Here we describe the development of VennPlex, a program that illustrates the often diverse numerical interactions among multiple, high-complexity datasets, using up to four data sets. VennPlex includes versatile output features, where grouped data points in specific regions can be easily exported into a spreadsheet. This program is able to facilitate the analysis of two to four gene sets and their corresponding expression values in a user-friendly manner. To demonstrate its unique experimental utility we applied VennPlex to a complex paradigm, i.e. a comparison of the effect of multiple oxygen tension environments (1–20% ambient oxygen) upon gene transcription of primary rat astrocytes. VennPlex accurately dissects complex data sets reliably into easily identifiable groups for straightforward analysis and data output. This program, which is an improvement over currently available Venn diagram programs, is able to rapidly extract important datasets that represent the variety of expression patterns available within the data sets, showing potential applications in fields like genomics, proteomics, and bioinformatics

RNA-Seq Differentiates Tumour and Host mRNA Expression Changes Induced by Treatment of Human Tumour Xenografts with the VEGFR Tyrosine Kinase Inhibitor Cediranib.

Pre-clinical models of tumour biology often rely on propagating human tumour cells in a mouse. In order to gain insight into the alignment of these models to human disease segments or investigate the effects of different therapeutics, approaches such as PCR or array based expression profiling are often employed despite suffering from biased transcript coverage, and a requirement for specialist experimental protocols to separate tumour and host signals. Here, we describe a computational strategy to profile transcript expression in both the tumour and host compartments of pre-clinical xenograft models from the same RNA sample using RNA-Seq. Key to this strategy is a species-specific mapping approach that removes the need for manipulation of the RNA population, customised sequencing protocols, or prior knowledge of the species component ratio. The method demonstrates comparable performance to species-specific RT-qPCR and a standard microarray platform, and allowed us to quantify gene expression changes in both the tumour and host tissue following treatment with cediranib, a potent vascular endothelial growth factor receptor tyrosine kinase inhibitor, including the reduction of multiple murine transcripts associated with endothelium or vessels, and an increase in genes associated with the inflammatory response in response to cediranib. In the human compartment, we observed a robust induction of hypoxia genes and a reduction in cell cycle associated transcripts. In conclusion, the study establishes that RNA-Seq can be applied to pre-clinical models to gain deeper understanding of model characteristics and compound mechanism of action, and to identify both tumour and host biomarkers

Diversity Arrays Technology (DArT) for Pan-Genomic Evolutionary Studies of Non-Model Organisms

Background: High-throughput tools for pan-genomic study, especially the DNA microarray platform, have sparked a remarkable increase in data production and enabled a shift in the scale at which biological investigation is possible. The use of microarrays to examine evolutionary relationships and processes, however, is predominantly restricted to model or near-model organisms. Methodology/Principal Findings: This study explores the utility of Diversity Arrays Technology (DArT) in evolutionary studies of non-model organisms. DArT is a hybridization-based genotyping method that uses microarray technology to identify and type DNA polymorphism. Theoretically applicable to any organism (even one for which no prior genetic data are available), DArT has not yet been explored in exclusively wild sample sets, nor extensively examined in a phylogenetic framework. DArT recovered 1349 markers of largely low copy-number loci in two lineages of seed-free land plants: the diploid fern Asplenium viride and the haploid moss Garovaglia elegans. Direct sequencing of 148 of these DArT markers identified 30 putative loci including four routinely sequenced for evolutionary studies in plants. Phylogenetic analyses of DArT genotypes reveal phylogeographic and substrate specificity patterns in A. viride, a lack of phylogeographic pattern in Australian G. elegans, and additive variation in hybrid or mixed samples. Conclusions/Significance: These results enable methodological recommendations including procedures for detecting and analysing DArT markers tailored specifically to evolutionary investigations and practical factors informing the decision to use DArT, and raise evolutionary hypotheses concerning substrate specificity and biogeographic patterns. Thus DArT is a demonstrably valuable addition to the set of existing molecular approaches used to infer biological phenomena such as adaptive radiations, population dynamics, hybridization, introgression, ecological differentiation and phylogeography