9,725 research outputs found

    Biochemical Properties of a Decoy Oligodeoxynucleotide Inhibitor of STAT3 Transcription Factor.

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    Cyclic STAT3 decoy (CS3D) is a second-generation, double-stranded oligodeoxynucleotide (ODN) that mimics a genomic response element for signal transducer and activator of transcription 3 (STAT3), an oncogenic transcription factor. CS3D competitively inhibits STAT3 binding to target gene promoters, resulting in decreased expression of proteins that promote cellular proliferation and survival. Previous studies have demonstrated antitumor activity of CS3D in preclinical models of solid tumors. However, prior to entering human clinical trials, the efficiency of generating the CS3D molecule and its stability in biological fluids should be determined. CS3D is synthesized as a single-stranded ODN and must have its free ends ligated to generate the final cyclic form. In this study, we report a ligation efficiency of nearly 95 percent. The ligated CS3D demonstrated a half-life of 7.9 h in human serum, indicating adequate stability for intravenous delivery. These results provide requisite biochemical characterization of CS3D that will inform upcoming clinical trials

    Estimating the Value of Medal Success at the 2010 Winter Olympic Games

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    We estimate Canadians’ willingness to pay (WTP) for success by Team Canada in the 2010 Winter Olympics. The Canadian government subsidized elite athletes in the run up to the 2010 Games through the Own the Podium program, which was designed to increase Canada’s medal count. WTP estimates from a contingent valuation method (CVM) study using data from nationally representative surveys before and after the Games suggest that Own the Podium generated intangible benefits of between 3 and 5 times its cost. The aggregate value of the intangible benefits generated by the program was between 719millionand719 million and 3.4 billion. Key Words: Olympic Games, contingent valuation method, willingness to pay

    Efficient Multi-stage Inference on Tabular Data

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    Many ML applications and products train on medium amounts of input data but get bottlenecked in real-time inference. When implementing ML systems, conventional wisdom favors segregating ML code into services queried by product code via Remote Procedure Call (RPC) APIs. This approach clarifies the overall software architecture and simplifies product code by abstracting away ML internals. However, the separation adds network latency and entails additional CPU overhead. Hence, we simplify inference algorithms and embed them into the product code to reduce network communication. For public datasets and a high-performance real-time platform that deals with tabular data, we show that over half of the inputs are often amenable to such optimization, while the remainder can be handled by the original model. By applying our optimization with AutoML to both training and inference, we reduce inference latency by 1.3x, CPU resources by 30%, and network communication between application front-end and ML back-end by about 50% for a commercial end-to-end ML platform that serves millions of real-time decisions per second

    Temporal Evolution of Financial Market Correlations

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    We investigate financial market correlations using random matrix theory and principal component analysis. We use random matrix theory to demonstrate that correlation matrices of asset price changes contain structure that is incompatible with uncorrelated random price changes. We then identify the principal components of these correlation matrices and demonstrate that a small number of components accounts for a large proportion of the variability of the markets that we consider. We then characterize the time-evolving relationships between the different assets by investigating the correlations between the asset price time series and principal components. Using this approach, we uncover notable changes that occurred in financial markets and identify the assets that were significantly affected by these changes. We show in particular that there was an increase in the strength of the relationships between several different markets following the 2007--2008 credit and liquidity crisis.Comment: 15 pages, 10 figures, 1 table. Accepted for publication in Phys. Rev. E. v2 includes additional section

    Antiferromagnetism and charged vortices in high-Tc superconductors

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    The effect of the long-range Coulomb interaction on charge accumulation in antiferromagnetic vortices in high-Tc superconductors is studied within a Bogoliubov-de Gennes mean-field model of competing antiferromagnetic and d-wave superconducting orders. Antiferromagnetism is found to be associated with an accumulation of charge in the vortex core, even in the presence of the long-range Coulomb interaction. The manifestation of Pi-triplet pairing in the presence of coexisting dSC and AFM order, and the intriguing appearance of one-dimensional stripe-like ordering are discussed. The local density of states (LDOS) in the vortex core is calculated and is found to be in excellent qualitative agreement with experimental data.Comment: 14 pages, 8 figures, 2 column RevTex4 PRB forma

    Relative Astrometry of Compact Flaring Structures in Sgr A* with Polarimetric VLBI

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    We demonstrate that polarimetric interferometry can be used to extract precise spatial information about compact polarized flares of Sgr A*. We show that, for a faint dynamical component, a single interferometric baseline suffices to determine both its polarization and projected displacement from the quiescent intensity centroid. A second baseline enables two-dimensional reconstruction of the displacement, and additional baselines can self-calibrate using the flare, enhancing synthesis imaging of the quiescent emission. We apply this technique to simulated 1.3-mm wavelength observations of a "hot spot" embedded in a radiatively inefficient accretion disk around Sgr A*. Our results indicate that, even with current sensitivities, polarimetric interferometry with the Event Horizon Telescope can achieve ~5 microarcsecond relative astrometry of compact flaring structures near Sgr A* on timescales of minutes.Comment: 9 Pages, 4 Figures, accepted for publication in Ap

    Quantification of the Individual Characteristics of the Human Dentition

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    The considerations for admissibility suggested by the Daubert trilogy challenge forensic experts to provide scientific support for opinion testimony. The defense bar has questioned the reliability of bitemark analysis. Under an award from the U. S. Department of Justice, via the Midwest Forensic Resource Center, a two-year feasibility study was undertaken to quantify six dental characteristics. Using two computer programs, the exemplars of 419 volunteers were digitally scanned, characteristics were measured, and frequency was calculated. The study demonstrates that there were outliers or rare dental characteristics in measurements. An analysis of the intra-observer and inter-observer consistency demonstrated a high degree of agreement. Expansion of the sample size through collaboration with other academic researchers will be necessary to be able to quantify the occurrence of these characteristics in the general population. The automated software application, Tom\u27s Toolbox, developed specifically for this research project, could also provide a template for precisely quantifying other pattern evidence

    Quantum phases in entropic dynamics

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    In the Entropic Dynamics framework the dynamics is driven by maximizing entropy subject to appropriate constraints. In this work we bring Entropic Dynamics one step closer to full equivalence with quantum theory by identifying constraints that lead to wave functions that remain single-valued even for multi-valued phases by recognizing the intimate relation between quantum phases, gauge symmetry, and charge quantization.Comment: Presented at MaxEnt 2017, the 37th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (July 9-14, 2017, Jarinu, Brazil

    Physicochemical Characteristics and Macroinvertebrate Assemblages of Riffles Upstream and Downstream of a Streambank Impacted by Unrestricted Cattle Access

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    Riparian zones are important contributors to stream ecosystem health. Alteration of such areas can change stream structure and function, resulting in modified productivity and hydrologic patterns. We studied two riffle sites on the South Fork of the Spring River in Fulton County, AR upstream and downstream of a streambank ostensibly degraded by unrestricted cattle access. The two sites were measured for differences in physical habitat (including bank width, stream velocity, depth, substrate composition, and embeddedness), chemical characteristics (including dissolved oxygen, pH, conductivity, turbidity and total suspended solids) and biological characteristics (including benthic macroinvertebrate community composition, similarity, and standing crop). Measurements were conducted quarterly for one year. We found embeddedness, total suspended solids and turbidity to be significantly higher downstream of the cattle access area. Community metrics were similar for both sites; however, macroinvertebrate standing crop was lower downstream. These results suggest moderate differences in stream productivity downstream of the cattle access site. Future work will evaluate whether reduced cattle access and streambank stabilization efforts result in improvements in water quality and density of macroinvertebrates
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