Microstructure Effects on Daily Return Volatility in Financial Markets

We simulate a series of daily returns from intraday price movements initiated by microstructure elements. Significant evidence is found that daily returns and daily return volatility exhibit first order autocorrelation, but trading volume and daily return volatility are not correlated, while intraday volatility is. We also consider GARCH effects in daily return series and show that estimates using daily returns are biased from the influence of the level of prices. Using daily price changes instead, we find evidence of a significant GARCH component. These results suggest that microstructure elements have a considerable influence on the return generating process.Comment: 15 pages, as presented at the Complexity Workshop in Aix-en-Provenc

Learning to Generate Images with Perceptual Similarity Metrics

Deep networks are increasingly being applied to problems involving image synthesis, e.g., generating images from textual descriptions and reconstructing an input image from a compact representation. Supervised training of image-synthesis networks typically uses a pixel-wise loss (PL) to indicate the mismatch between a generated image and its corresponding target image. We propose instead to use a loss function that is better calibrated to human perceptual judgments of image quality: the multiscale structural-similarity score (MS-SSIM). Because MS-SSIM is differentiable, it is easily incorporated into gradient-descent learning. We compare the consequences of using MS-SSIM versus PL loss on training deterministic and stochastic autoencoders. For three different architectures, we collected human judgments of the quality of image reconstructions. Observers reliably prefer images synthesized by MS-SSIM-optimized models over those synthesized by PL-optimized models, for two distinct PL measures ($\ell_1$ and $\ell_2$ distances). We also explore the effect of training objective on image encoding and analyze conditions under which perceptually-optimized representations yield better performance on image classification. Finally, we demonstrate the superiority of perceptually-optimized networks for super-resolution imaging. Just as computer vision has advanced through the use of convolutional architectures that mimic the structure of the mammalian visual system, we argue that significant additional advances can be made in modeling images through the use of training objectives that are well aligned to characteristics of human perception

Sixty original plays for primary grades

Thesis (Ed.M.)--Boston Universit

Validation of magnetophonon spectroscopy as a tool for analyzing hot-electron effects in devices

It is shown that very high precision hot-electron magnetophonon experiments made on n+n−n+-GaAs sandwich device structures which are customized for magnetoresistance measurements can be very accurately modeled by a new Monte Carlo technique. The latter takes account of the Landau quantization and device architecture as well as material parameters. It is proposed that this combination of experiment and modeling yields a quantitative tool for the direct analysis of spatially localized very nonequilibrium electron distributions in small devices and low dimensional structures

First Passage Properties of the Erdos-Renyi Random Graph

We study the mean time for a random walk to traverse between two arbitrary sites of the Erdos-Renyi random graph. We develop an effective medium approximation that predicts that the mean first-passage time between pairs of nodes, as well as all moments of this first-passage time, are insensitive to the fraction p of occupied links. This prediction qualitatively agrees with numerical simulations away from the percolation threshold. Near the percolation threshold, the statistically meaningful quantity is the mean transit rate, namely, the inverse of the first-passage time. This rate varies non-monotonically with p near the percolation transition. Much of this behavior can be understood by simple heuristic arguments.Comment: 10 pages, 9 figures, 2-column revtex4 forma

One-carbon metabolism in cancer

Cells require one-carbon units for nucleotide synthesis, methylation and reductive metabolism, and these pathways support the high proliferative rate of cancer cells. As such, anti-folates, drugs that target one-carbon metabolism, have long been used in the treatment of cancer. Amino acids, such as serine are a major one-carbon source, and cancer cells are particularly susceptible to deprivation of one-carbon units by serine restriction or inhibition of de novo serine synthesis. Recent work has also begun to decipher the specific pathways and sub-cellular compartments that are important for one-carbon metabolism in cancer cells. In this review we summarise the historical understanding of one-carbon metabolism in cancer, describe the recent findings regarding the generation and usage of one-carbon units and explore possible future therapeutics that could exploit the dependency of cancer cells on one-carbon metabolism

Embedded Stellar Clusters in the W3/W4/W5 Molecular Cloud Complex

We analyze the embedded stellar content in the vicinity of the W3/W4/W5 HII regions using the FCRAO Outer Galaxy 12CO(J=1-0) Survey, the IRAS Point Source Catalog, published radio continuum surveys, and new near-infrared and molecular line observations. Thirty-four IRAS Point Sources are identified that have far-infrared colors characteristic of embedded star forming regions, and we have obtained K' mosaics and 13CO(J=1-0) maps for 32 of them. Ten of the IRAS sources are associated with an OB star and 19 with a stellar cluster, although three OB stars are not identified with a cluster. Half of the embedded stellar population identified in the K' images is found in just the 5 richest clusters, and 61% is contained in IRAS sources associated with an embedded OB star. Thus rich clusters around OB stars contribute substantially to the stellar population currently forming in the W3/W4/W5 region. Approximately 39% of the cluster population is embedded in small clouds with an average mass of ~130 Mo that are located as far as 100 pc from the W3/W4/W5 cloud complex. We speculate that these small clouds are fragments of a cloud complex dispersed by previous episodes of massive star formation. Finally, we find that 4 of the 5 known embedded massive star forming sites in the W3 molecular cloud are found along the interface with the W4 HII region despite the fact that most of the molecular mass is contained in the interior regions of the cloud. These observations are consistent with the classical notion that the W4 HII region has triggered massive star formation along the eastern edge of the W3 molecular cloud.Comment: to appear in ApJS, see http://astro.caltech.edu/~jmc/papers/w

Water Abundance in Molecular Cloud Cores

We present Submillimeter Wave Astronomy Satellite (SWAS) observations of the 1_{10}-1_{01} transition of ortho-water at 557 GHz toward 12 molecular cloud cores. The water emission was detected in NGC 7538, Rho Oph A, NGC 2024, CRL 2591, W3, W3(OH), Mon R2, and W33, and was not detected in TMC-1, L134N, and B335. We also present a small map of the water emission in S140. Observations of the H_2^{18}O line were obtained toward S140 and NGC 7538, but no emission was detected. The abundance of ortho-water relative to H_2 in the giant molecular cloud cores was found to vary between 6x10^{-10} and 1x10^{-8}. Five of the cloud cores in our sample have previous water detections; however, in all cases the emission is thought to arise from hot cores with small angular extents. The water abundance estimated for the hot core gas is at least 100 times larger than in the gas probed by SWAS. The most stringent upper limit on the ortho-water abundance in dark clouds is provided in TMC-1, where the 3-sigma upper limit on the ortho-water fractional abundance is 7x10^{-8}.Comment: 5 pages, 3 Postscript figures, uses aastex.cls, emulateapj5.sty (included), and apjfonts.sty (included

A Training Framework and Follow-Up Observations for Multiculturally Inclusive Teaching: Is Believing That We are Emphasizing Diversity Enough?

The authors present a theoretically and empirically grounded training for multiculturally inclusive teaching for new instructors. After implementing this training, qualitative data were gathered from instructors to identify their experience of the training and concerns related to incorporating issues of diversity into their classrooms (Study 1). At the end of the semester immediately following the training, quantitative data were gathered from instructors and their students to examine the interaction between students’ and instructors’ perceived diversity emphasis (Study 2). When allowed to choose the extent to which they incorporated issues of diversity in their classes, the instructors differentially reported emphasizing diversity in class. In addition, results from multi-level linear modeling analyses demonstrated that instructors’ reported emphasis on diversity in the classroom did not predict students’ perceptions of the inclusion of issues of diversity. The authors discuss implications for the development of multiculturally supportive programs of learning at universities